Actinobacteria

Transcription

Actinobacteria

Zur Homepage der Dissertation
Diversität und Dynamik von Bakteriengemeinschaften
in vier ausgewählten Seen der Mecklenburgischen
Seenplatte
Diversity and Dynamics of Bacterioplankton
Communities in four selected Lakes of the
Mecklenburg Lake District
Dissertation
Von der Fakultät für Mathematik und Naturwissenschaften
der Carl von Ossietzky Universität Oldenburg zur Erlangung
des Grades und Titels eines
Doktors der Naturwissenschaften (Dr. rer. nat.)
angenommene Dissertation
von
Martin Allgaier
geboren am 20.12.1976 in Böblingen
Oldenburg, August 2006
Erstreferent:
PD Dr. Hans-Peter Grossart
Erster Koreferent:
Prof. Dr. Meinhard Simon
Tag der Disputation:
06. Oktober 2006
Die Untersuchungen zu vorliegender Arbeit wurden am Leibniz-Institut für
Gewässerökologie und Binnenfischerei (IGB), Abteilung Limnologie
Geschichteter Seen in Neuglobsow durchgeführt.
Meinen Eltern
Erklärung
Teilergebnisse dieser Arbeit sind als Beiträge bei den genannten Fachzeitschriften
erschienen (Kapitel III), für die Publikation akzeptiert (Kapitel II) oder wurden als
Manuskripte zur Publikation eingereicht (Kapitel IV, V). Mein Beitrag an der Erstellung der
Manuskripte wird im Folgenden erläutert:
ALLGAIER, M., AND GROSSART, H.-P. (2006) Seasonal dynamics and phylogenetic diversity
of free-living and particle-associated bacterial communities in four lakes of Northeastern
Germany. Aquatic Microbial Ecology, accepted.
Konzeptentwicklung und Durchführung der praktischen Arbeiten durch M. A. mit Ausnahme der
Bestimmung der limnologischen Parameter (Mitarbeiter der Abteilung III des IGB). Erstellung des
Manuskriptes durch M. A., Überarbeitung durch H.-P. G. und M. A.
ALLGAIER, M., AND GROSSART, H.-P. (2006) Diversity and seasonal dynamics of
Actinobacteria in four lakes in Northeastern Germany. Applied and Environmental
Microbiology 72:3489-3497.
Konzeptentwicklung und Durchführung der praktischen Arbeiten durch M. A. Erstellung des
ALLGAIER, M., BRÜCKNER, S., JASPERS, E., AND GROSSART, H.-P. (2006) Intra- and interlake variability of free-living and particle-associated Actinobacteria populations. Submitted
to Environmental Microbiology.
Konzeptentwicklung durch M. A. Durchführung der praktischen Arbeiten zu gleichen Teilen durch
M. A. und S. B. (S. B.: DGGE, Clusteranalysen, Klonbibliotheken; M. A.: phylogenetische
Analysen, Statistik, NMS). Die limnologischen Parameter wurden von Mitarbeitern der Abteilung III
des IGB bestimmt. Erstellung des Manuskriptes durch M. A., Überarbeitung durch H.-P. G., S. B.,
E. J. und M. A.
ALLGAIER, M., AND GROSSART, H.-P. (2006) Abundance and phylogenetic diversity of freeliving and particle-associated epilimnetic Actinobacteria of Lake Kinneret (Israel) – A case
study. Submitted to Environmental Microbiology.
Konzeptentwicklung und Durchführung der praktischen Arbeiten durch M. A. Erstellung des
vii
Weitere Veröffentlichungen
ALLGAIER, M., AND GROSSART, H.-P. (2005) Bacterial diversity and seasonal dynamics in 2
lakes of the Mecklenburg Lake District, Northern Germany. IGB Annual Report 2004, 88100.
GROSSART, H.-P., LEVOLD, F., ALLGAIER, M., SIMON, M., AND BRINKHOFF, T. (2005) Marine
diatom species harbour distinct bacterial communities. Environmental Microbiology 7:860873.
GROSSART, H.-P., ALLGAIER, M., PASSOW, U., AND RIEBESELL, U. (2006) Testing the effect
of CO2 concentration on dynamics of marine heterotrophic bacterioplankton. Limnology
and Oceanography 51:1-11.
GROSSART, H.-P., KIØRBOE, T., TANG, K.W., ALLGAIER, M., YAM, E.M. AND PLOUG, H.
(2006) Interactions between marine snow and heterotrophic bacteria: Aggregate formation
and microbial dynamics. Aquatic Microbial Ecology 42:19-26.
Tagungsbeiträge
ALLGAIER, M., AND GROSSART, H.-P. (2004) Bacterial dynamics and diversity in four lakes
of the Brandenburg-Mecklenburg Lake District, Northern Germany. Jahrestagung der
Vereinigung für Allgemeine und Angewandte Mikrobiologie (VAAM), 28.03.-31.03.2004,
Braunschweig, Deutschland (Poster).
ALLGAIER, M., AND GROSSART, H.-P. (2004) Bacterial community structures in two
adjacent but very different lakes in Northern Germany. 10th International Symposium on
Microbial Ecology (ISME-10), 22.08.-27.08.2004, Cancun, Mexico (Poster).
ALLGAIER, M., AND GROSSART, H.-P. (2004) Bacterial community structures in two adjacent
but very different lakes in Northern Germany. Jahrestagung der Deutschen Gesellschaft
für Limnologie (DGL), 20.09.-24.09.2004, Potsdam, Deutschland (Poster).
Weitere Tagungsbeiträge
GROSSART, H.-P., ALLGAIER, M., PASSOW, U., ENGEL, A., SCHULZ, K., AND RIEBESELL, U.
(2004) The effect of different CO2 concentrations on bacterial abundance and activity in
the course of a diatom bloom. Jahrestagung der Vereinigung für Allgemeine und
Angewandte Mikrobiologie (VAAM), 28.03.-31.03.2004, Braunschweig, Deutschland
(Vortrag).
GROSSART, H.-P., LEVOLD, F., ALLGAIER, M., SIMON, M., AND BRINKHOFF, T. (2004)
Dynamics of phytoplankton-bacteria interactions. 10th International Symposium on
Microbial Ecology (ISME-10), 22.08.-27.08.2004, Cancun, Mexico (Poster).
RIEBESELL, U., ALLGAIER, M., AVGOUSTIDI, V., BELLERBY, R., CARBONNEL, V., CHOU, L.,
DELILLE, B., EGGE, J., ENGEL, A., GROSSART, H.-P., HUONNIC, P., JANSEN, S., JOHANESSEN,
viii
T., JOINT, I., KRINGSTAD, S., LOVDAL, L., MARTIN-JEZEQUEL, V., MOROS, C., MÜHLING, M.,
NIGHTINGALE, P.D., PASSOW, U., ROST, B., SCHULZ, K., SKJELVAN, I., TERBRÜGGEN, A., AND
TRIMBORN, S. (2004) Pelagic ecosystems in a high CO2 ocean: the mesocosm approach.
SOLAS Open Science Conference, 13.10.-16.10.2004, Halifax, Canada (Poster).
GROSSART, H.-P., ALLGAIER, M., PASSOW, U., ENGEL, A., SCHULZ, K., AND RIEBESELL, U.
(2004) The effect of different CO2 concentrations on bacterial abundance and activity in
the course of a diatom bloom. SOLAS Open Science Conference, 13.10.-16.10.2004,
Halifax, Canada (Poster).
PASSOW, U., ARNOSTI, C., ALLGAIER, M., AND GROSSART, H.-P. (2004) Hydrolysis rates of
specific polysaccharides in mesocosm with high or low atmospheric CO2 concentrations.
SOLAS Open Science Conference, 13.10.-16.10.2004, Halifax, Canada (Poster).
EGGE, J., GROSSART, H.-P., ALLGAIER, M., AND ENGEL, A. (2004) Assimilation, organic
production and release of carbon. SOLAS Open Science Conference, 13.10.-16.10.2004,
Halifax, Canada (Poster).
BRÜCKNER, S., ALLGAIER, M., GROSSART, H.-P., AND JASPERS, E. (2006) Assessment of
inter- and intra-lake variability of Actinobacteria populations by using specific primers.
Jahrestagung der Vereinigung für Allgemeine und Angewandte Mikrobiologie (VAAM),
19.03.-22.03.2006, Jena, Deutschland (Poster).
ALLGAIER, M., RIEBESELL, U., AND GROSSART, H.-P. (2006) Response of marine bacteria to
CO2 enrichment in mesocosm perturbation studies. European Geoscience Union (EGU)
General Assembly, 02.04.-07.04.2006, Wien, Österreich (Poster).
ix
Abkürzungsverzeichnis
ANOSIM
analysis of similarity
ANOVA
analysis of variance
BAC
bacterial artificial chromosome (Inserts bis 200 kb möglich)
BL
Breiter Luzin
BLAST
Basic Local Alignment Search Tool
BPP
Bakterielle Proteinproduktion
CARD-FISH
catalyzed reporter deposition FISH
COSMID
Plasmid, in das cos-Stellen des λ–Phagen eingebaut wurden
und die daher in vitro in eine Phagenhülle verpackt werden
können
DAPI
4,6-diamidino-2-phenylindole
DGGE
Denaturierende Gradienten Gelelektrophorese
DNA
deoxyribonucleic acid
DOC
dissolved organic carbon
DOM
dissolved organic matter
et al.
et alii
FISH
Fluoreszenz in situ Hybridisierung
FNE bzw. FU-NE
Große Fuchskuhle (Nordost-Becken)
FOSMID
low-copy-number COSMID, das sich von dem F-Faktor aus
E. coli ableitet (Inserts bis 40 kb möglich)
FSW bzw. FU-SW
Große Fuchskuhle (Südwest-Becken)
NMS
non-metric multidimensional scaling
PCR
polymerase chain reaction
POC
particulate organic carbon
POM
particulate organic matter
PP
Primärproduktion
RDP
Ribosomal Database Project
rRNA
ribosomal ribonucleic acid
ST
Stechlinsee
STE
Stechlinsee (Epilimnion)
STM
Stechlinsee (Metalimnion)
STH bzw. ST-HL
Stechlinsee (Hypolimnion)
TOC
total organic carbon
TW
Tiefwarensee
v.s.
versus
x
Zusammenfassung
In
der
vorliegenden
Arbeit
wurde
die
Bakterioplanktongemeinschaften in vier
Diversität
und
Dynamik
heterotropher
limnologisch unterschiedlichen
Seen
der
Mecklenburgischen Seenplatte (Stechlinsee, Große Fuchskuhle, Breiter Luzin und
Tiefwarensee) bestimmt und miteinander verglichen. Dazu wurden die Seen von April
2003 bis März 2004 ein Jahr lang monatlich beprobt und hinsichtlich mikrobieller und
limnologischer
Veränderungen
untersucht.
Anhand
Denaturierender
Gradienten
Gelelektrophorese (DGGE) und Klonbibliotheken von 16S rRNA-Genfragmenten wurde
die phylogenetische Diversität der Bakteriengemeinschaften bestimmt und deren
saisonale Veränderungen untersucht. Dabei wurde zwischen frei-lebenden und partikelassoziierten Bakterien unterschieden, um eine höhere phylogenetische Auflösung zu
erlangen. Bei der molekularbiologischen Charakterisierung der Bakteriengemeinschaften
wurden die Actinobacteria als eine der dominanten Bakteriengruppen in allen vier Seen
identifiziert. Dies führte im Weiteren zu gezielten Studien an dieser Bakteriengruppe, in
denen die Diversität, Abundanz, Saisonalität und Verbreitung limnischer Actinobacteria
detailliert
untersucht
wurde.
Als
mögliche
Einflussfaktoren
für
die
Bakterien-
gemeinschaften wurden für alle Gewässer eine Vielzahl an limnologischen Parametern
bestimmt (z.B. Temperatur, gelöster organischer Kohlenstoff (DOC), Stickstoff, Phosphor,
Primärproduktion oder Phytoplanktonbiomasse) und statistisch mit der Diversität bzw.
Abundanz der gesamten Bakteriengemeinschaften und Actinobacteria in Verbindung
gebracht.
Die wichtigsten Ergebnisse dieser Arbeit können wie folgt zusammengefasst werden:
•
Die
Bakterioplanktongemeinschaften
der
vier
Untersuchungsgewässer
unterschieden sich signifikant voneinander. Phylogenetische Analysen von 16S
rRNA-Gensequenzen deuteten auf das Vorkommen von α-, β-, γ-Proteobacteria,
Actinobacteria, Bacteroidetes, Cyanobacteria, Verrucomicrobia, Planctomycetes
und Vertretern des Candidate Division OP10 in den Seen hin.
•
Die
getrennte
Analyse
von
frei-lebenden
und
partikel-assoziierten
Bakteriengemeinschaften ergab deutliche Unterschiede in der Struktur und
phylogenetischen Diversität der beiden Bakterienfraktionen. Klonbibliotheken von
frei-lebenden
Bakteriengemeinschaften
wurden
von
Sequenzen
der
Actinobacteria, Bacteroidetes, α- und β-Proteobacteria dominiert, wohingegen sich
xi
die partikel-assoziierten Bakteriengemeinschaften hauptsächlich aus Vertretern
der Bacteroidetes, α-Proteobacteria und Planctomycetes zusammensetzten.
•
Vertreter der Actinobacteria wurden in allen Seen mit Abundanzen von 30-58 %
als eine der dominanten Bakteriengruppen nachgewiesen. Etwa 80 % aller
Actinobacteria konnten dem erst kürzlich beschriebenen acI-Cluster zugeordnet
werden. Durch umfangreiche phylogenetische Analysen konnten innerhalb der
limnischen Actinobacteria neue Cluster (acSTL) und Subcluster (scB 1-4, acIV
D-E) beschrieben werden. Ein Vergleich von Actinobacteria-Sequenzen der vier
Untersuchungsgewässer mit Sequenzen aus dem subtropischen See Genezareth
(Israel)
zeigte
keine
signifikanten
Unterschiede
in
der
phylogenetischen
Zusammensetzung limnischer Actinobacteria verschiedener Klimazonen. Dies
unterstützt die Annahme einer globalen Verbreitung limnischer Actinobacteria.
•
Mittels spezifischer Nachweisverfahren (DGGE) konnte gezeigt werden, dass sich
die Actinobacteria-Populationen der vier Untersuchungsgewässer signifikant
voneinander unterscheiden. Im Stechlinsee wurden sogar Unterschiede zwischen
den
Actinobacteria-Populationen
des
Epi-,
Meta-,
und
Hypolimnions
nachgewiesen. Die getrennte Analyse von frei-lebenden und partikel-assoziierten
Actinobacteria ergab deutliche Unterschiede in der Struktur der beiden
Actinobacteria-Fraktionen.
Die
phylogenetische
Analyse
partikel-assoziierter
Actinobacteria deutete dabei auf eine spezifische Anpassung bestimmter
phylogenetischer Linien an Partikel hin.
•
Sowohl
die
gesamten
wie
auch
Vertreter
der
Actinobacteria zeigten ausgeprägte saisonale Veränderungen hinsichtlich ihrer
Diversität
und
Abundanz.
Für
die
der
vier
Untersuchungsgewässer wurden relativ einheitliche saisonale Muster mit Maxima
im Sommer und Spätherbst nachgewiesen. Generell waren die saisonalen
Veränderungen innerhalb der frei-lebenden Bakterien meist stärker ausgeprägt als
bei den partikel-assoziierten Bakteriengemeinschaften.
•
Der statistische Vergleich zwischen der Diversität und Abundanz der gesamten
Umweltparametern
Temperatur,
bzw.
erbrachten
Alkalinität,
DOC,
Actinobacteria
starke
Korrelationen
Stickstoff,
xii
Phosphor,
und
bei
verschiedenen
Parametern
wie:
Exoenzymaktivitäten,
Primärproduktion und Phytoplanktonbiomasse. In allen Analysen konnten jedoch
keine übereinstimmenden Korrelationsmuster zwischen den Seen identifiziert
werden – weder für die gesamten Bakteriengemeinschaften noch für die
Actinobacteria.
Dies
deutet
auf
die
Anpassung
der
jeweiligen
Bakteriengemeinschaften an die entsprechenden Umweltbedingungen in ihrem
Habitat hin. Bei den Actinobacteria kann aufgrund der phylogenetischen
Ähnlichkeiten zwischen den Actinobacteria-Populationen der vier Seen von einer
Mikrodiversität gesprochen werden.
xiii
Summary
The diversity and dynamics of heterotrophic bacterioplankton communities was
investigated in four limnological different lakes of the Mecklenburg Lake District,
Northeastern Germany (Lake Stechlin, Lake Grosse Fuchskuhle, Lake Breiter Luzin, and
Lake Tiefwaren). For this purpose all lakes were sampled monthly between April 2003 and
March 2004 and characterized regarding to their microbial and limnological changes.
Denaturing gradient gel electrophoresis (DGGE) and clone libraries were used to
determine the phylogenetic diversity and seasonal dynamics of the bacterial communities.
To obtain higher phylogenetic resolutions, free-living and particle-associated bacteria
were investigated separately as two different entities. Actinobacteria were found to be one
of the most dominant bacterial groups within bacterioplankton communities of all lakes.
Therefore, particular studies of this thesis were focused on the description and
characterization (e.g. phylogenetic diversity, seasonality, abundances, and distribution) of
freshwater Actinobacteria. Several limnological variables were determined for the studied
lakes (e.g. temperature, dissolved organic carbon (DOC), nitrogen, phosphorous, primary
production, phytoplankton biomass) to test statistically their influence on changes in
diversity and abundance of total bacterial communities and Actinobacteria, respectively.
The major findings of this thesis can be summarized as follows:
•
Bacterioplankton communities of the four studied lakes were significantly different.
Phylogenetic inferences of 16S rRNA gene sequences indicated the occurrence of
α-,
β-,
γ-Proteobacteria,
Actinobacteria,
Bacteroidetes,
Cyanobacteria,
Verrucomicrobia, Planctomycetes, and members of the Candidate Division OP10
in almost all lakes.
•
Separate analyses of free-living and particle-associated bacterial communities
revealed significant differences in the community structure and phylogenetic
diversity of both bacterial fractions. Phylogenetic analyses of clone libraries
indicated
that
free-living
bacteria
were
dominated
by
Actinobacteria,
Bacteroidetes, α-, and β-Proteobacteria, whereas particle-associated bacterial
communities consists predominantly of Bacteroidetes, α-Proteobacteria, and
Planctomycetes, respectively.
•
Members of the Actinobacteria were found to be one of the most dominant
bacterial groups within the bacterioplankton of all lakes which accounted for up to
xiv
30-58 % of all DAPI stained cells. About 80 % of all Actinobacteria were
phylogenetically related to the recently described freshwater cluster acI.
Throughout extensive phylogenetic analyses of actinobacterial 16S rRNA gene
sequences several new clusters (acSTL) and subclusters (scB 1-4, acIV D-E) were
described within the phylogenetic tree of freshwater Actinobacteria. A comparison
between actinobacterial sequences of the four studied lakes with sequences
derived from subtropical Lake Kinneret (Israel) indicated no differences between
freshwater Actinobacteria of different climatic zones and, thus, supporting the idea
of a global distribution of freshwater Actinobacteria.
•
The specific investigation of freshwater Actinobacteria (DGGE) showed significant
differences between Actinobacteria populations of the four studied lakes. In Lake
Stechlin additionally intra-lake differences occurred between Actinobacteria
populations of the epi-, meta-, and hypolimnion. Separate analyses of free-living
and particle-associated Actinobacteria revealed clear differences between both
actinobacterial
fractions.
Phylogenetic
analyses
of
particle-associated
Actinobacteria suggest that distinct actinobacterial lineages exclusively occur on
particles.
•
Total bacterioplankton communities and members of the Actinobacteria showed
pronounced seasonal changes in respect to their community structure and
abundances. Actinobacteria exhibited uniform seasonal patterns in all lakes with
maximal abundances in late spring and fall/winter. In general, seasonal dynamics
were more pronounced for free-living bacteria than for particle-associated bacterial
communities.
•
Statistical analyses between diversity and abundances of total bacterial
communities
and
Actinobacteria,
respectively,
and
several
environmental
parameters indicated strong correlations to parameters such as: temperature,
alkalinity, DOC, nitrogen, phosphorous, ectoenzyme activities, primary production
and phytoplankton biomass. However, no consistent correlation patterns could be
identified between the four studied lakes - neither for total bacterial communities
nor for Actinobacteria. This suggests a potential adaptation of bacterial
communities to their respective environment. Due to high phylogenetic similarities
between Actinobacteria populations of the four studied lakes, Actinobacteria are
proposed to exhibit a distinct microdiversity.
xv
Inhaltsverzeichnis
Zusammenfassung
xi
Summary
I
II
III
IV
xiv
Einleitung
1
Die ökologische Bedeutung des heterotrophen
Bakterioplanktons in aquatischen Systemen
Untersuchung und Charakterisierung komplexer
Phylogenie und Biogeographie aquatischer Bakterien
Saisonale Dynamik von Bakteriengemeinschaften
Aggregate als Lebensraum für aquatische Bakterien
Das Untersuchungsgebiet: Die Mecklenburgische Seenplatte
Zielsetzung der Arbeit
Literatur
5
7
10
11
12
17
19
Seasonal dynamics and phylogenetic diversity of free-living
and particle-associated bacterial communities in four lakes
of Northeastern Germany
29
Abstract
Introduction
Materials and Methods
Results
Discussion
Literature cited
Figures and Tables
32
32
33
37
41
46
51
Diversity and seasonal dynamics of Actinobacteria
populations in four lakes of Northeastern Germany
59
Intra- and inter-lake variability of free-living and
particle-associated Actinobacteria populations
71
Summary
Introduction
Results
Discussion
Experimental procedures
References
Figures and Tables
74
74
75
77
81
87
90
xvi
3
V
VI
Abundance and phylogenetic diversity of free-living
and particle-associated epilimnetic Actinobacteria of
Lake Kinneret (Israel) – A case study
95
Summary
Introduction
Results and Discussion
References
Figures
98
98
99
102
104
Gesamtbetrachtung und Ausblick
107
Gesamtbetrachtung
Die Bakterienpopulationen in den Untersuchungsgewässern
Limnische Actinobacteria
Phylogenetische Diversität
Verbreitung, Dynamik und ökologische Anpassung
limnischer Actinobacteria
Verknüpfung von Struktur und Funktion aquatischer
Aktuelle Projekte und Ausblicke
Literatur
109
109
111
111
112
114
116
118
Danksagung
121
Lebenslauf
123
Erklärung
125
Anhang
127
xvii
I
Einleitung
Kapitel I
Einleitung
Die ökologische Bedeutung des heterotrophen Bakterioplanktons
in aquatischen Systemen
Mikroorganismen sind eine wichtige Komponente in aquatischen Nahrungsnetzen, die auf
eine Vielzahl physikalischer, chemischer und biologischer Änderungen reagieren.
Heterotrophe Bakterien leisten in aquatischen Ökosystemen einen signifikanten Anteil am
Abbau organischer Kohlenstoffverbindungen (Cotner & Biddanda, 2002). Sie erfüllen in
erster Linie die Funktion der Mineralisation, d.h. der Überführung organischer Substanz in
mineralische, anorganische Substanz. Diese kann von den autotrophen Organismen zur
Neusynthese von Biomasse genutzt werden. Ihre wichtige Rolle in der Natur, besonders
in den Gewässern, wurde lange übersehen. Noch bis Ende der siebziger Jahre des
letzten Jahrhunderts ging man davon aus, dass der größte Teil der Primärproduktion als
partikuläres Material über die einzelnen Trophiestufen einer linearen Nahrungskette
(„grazing food chain“; Abbildung I.1) weitergegeben wird (Steele, 1974). Durch die
Entwicklung radiochemischer Analyseverfahren wurde jedoch zunehmend die zentrale
Rolle heterotropher Bakterien in aquatischen Stoffkreisläufen erkannt und anstelle der
linearen Nahrungskette ein komplexes Nahrungsnetz postuliert (Parsons & Strickland,
1962; Wright & Hobbie, 1966).
Im freien Wasserkörper (Pelagial) der Ozeane, großer Fließgewässer und Seen finden
sich
große
Mengen
an
organischem
Kohlenstoff,
dessen
Hauptquelle
die
Primärproduktion planktischer Algen und Cyanobakterien ist (Schwoerbel, 1999). In den
Ozeanen liegen etwa 91 % des gesamten organischen Materials in gelöster Form
(dissolved organic matter; DOM) vor (Hedges, 1992). Zu den DOM-Quellen zählen neben
den Exsudaten des Phytoplanktons und dem durch „sloppy feeding“ freigesetzten DOM
des Zooplanktons (Lampert, 1978; Jumars et al., 1989) auch organische Materialen, die
durch virale Lyse von Phyto- und Bakterioplankton (Bratbak et al., 1992; Fuhrman, 1999)
sowie der Hydrolyse partikulären organischen Materials (POM) durch Bakterien
freigesetzt werden (Smith et al., 1992; Grossart & Simon, 1998). Gelöste organische
Materialien sind für Organismen höherer Trophiestufen nicht direkt zugänglich, können
aber von heterotrophen Mikroorganismen genutzt werden. Aufgrund ihrer effektiven
Aufnahmesysteme und eines hohen Oberflächen-Volumen-Verhältnisses gelten Bakterien
als wichtige Konsumenten des gelösten organischen Kohlenstoffs (DOC). Durch die
Überführung der gelösten organischen Substanz in die partikuläre Fraktion der
Bakterienzellen wird eine Weitergabe an Organismen höherer Trophiestufen möglich.
Über die Ingestion von Bakterien durch heterotrophe Nanoflagellaten und Ciliaten können
30-60 % der autochthonen Primärproduktion durch den „microbial loop“ höheren
3
Kapitel I
Einleitung
Trophiestufen zugeführt werden (Azam et al., 1983; Cole et al., 1988; Sherr et al., 1989).
In oligotrophen Systemen kann der Abbau organischen Kohlenstoffs durch heterotrophe
Bakterien die Primärproduktion sogar um ein Vielfaches übersteigen. Dabei schleusen
heterotrophe Bakterien allochthonen Kohlenstoff in den pelagischen Kohlenstoffkreislauf
ein und führen dem Nahrungsnetz so zusätzliche Nährstoffe zu (Findlay et al., 1991; del
Giorgio et al., 1997).
Bakterien spielen jedoch nicht nur im Kohlenstoffkreislauf eine zentrale Rolle. Durch ihre
große
Vielfalt
an
Stoffwechseleigenschaften
(u.a.
Nitrifizierung,
Denitrifizierung,
Sulfatreduktion) sind Bakterien an weiteren Stoffkreisläufen verschiedener Elemente
entscheidend beteiligt (Schlegel, 1992; Madigan et al., 2000).
Gasaustausch
(u.a. O2, CO2)
Sonnenlicht
(hν und UV)
„grazing food chain“
„sinking flux“
Phytoplankton
Zooplankton
Fische
POM
DOM
Protozoen
Viren
Aggregation
Bakterien
Sedimentation
„microbial loop“
SEDIMENT
Abbildung I.1: Vereinfachte schematische Darstellung des aquatischen Nahrungsnetzes
(nach Azam, 1998).
4
Kapitel I
Einleitung
Untersuchung und Charakterisierung komplexer
Wie in dem vorangegangenen Kapitel dargestellt, spielen Mikroorganismen eine
entscheidende Rolle in vielen Stoffkreisläufen. Trotzdem wissen wir heute noch sehr
wenig über die Identität der beteiligten Arten und über die Populationsdynamik einzelner
Bakteriengruppen in natürlichen Systemen. Für das bessere Verständnis eines
Ökosystems ist es aber notwendig, die Struktur der Bakteriengemeinschaften möglichst
genau zu kennen (Cottrell & Kirchman, 2002; Pernthaler & Amann, 2005). Aufgrund ihrer
geringen Größe und der wenig ausgeprägten morphologischen Merkmale (z.B. Kokken,
Stäbchen, Spirillen, Vibrionen oder Spirochäten) ist es nur in Ausnahmefällen möglich,
Bakterien anhand ihrer Morphologie zu unterscheiden (Sieburth et al., 1978, Schlegel,
1992). Noch bis in die 80er Jahre des letzten Jahrhunderts wurden deshalb
Bakteriengemeinschaften oft als funktionelle Einheit (black box) zusammengefasst
(Pinhassi et al., 1997), in der nicht zwischen einzelnen phylogenetischen Gruppen
unterschieden wurde. Es ist jedoch nicht nur die geringe morphologische Vielfalt, die eine
Charakterisierung
natürlicher
nahezu
unmöglich
macht,
sondern auch die schwierige Kultivierbarkeit vieler Mikroorganismen. Da sich bislang nur
etwa 1 % aller Bakterien erfolgreich im Labor kultivieren lässt (Amann et al., 1995), ist
eine zuverlässige Erfassung der Diversität natürlicher Bakteriengemeinschaften anhand
klassischer Anreicherungs- und Kultivierungsexperimente so gut wie ausgeschlossen.
Gegenwärtig gibt es ca. 6900 gültig beschriebene Bakterienarten, denen eine geschätzte
≥ 109 möglicherweise existierenden Bakterienspezies gegenübersteht
Zahl von
(Dykhuizen, 1998). Dieses Phänomen der geringen Kultivierbarkeit vieler Bakterien trotz
hohen Abundanzen in den natürlichen Ökosystemen wurde von Staley & Konopka (1985)
als „great plate count anomaly“ (Plattenanomalie) bezeichnet. Die Gründe für die
„Unkultivierbarkeit“ vieler Bakterien sind vermutlich in den physiologischen Zuständen und
spezifischen
Anforderungen
der
Bakterien
selbst,
so
wie
den
angewandten
Kultivierungsmethoden zu suchen (Bloomfield et al., 1998; Rappé et al., 2002; Stevenson
et al., 2004).
Durch die Einführung molekularbiologischer Techniken in die aquatische mikrobielle
Ökologie
wurde
die
Erforschung
entscheidend
der
phylogenetischen
vorangetrieben (Olsen
Diversität
et
al.,
natürlicher
1986).
Im
Mittelpunkt der molekularbiologischen Analysen stand dabei die Verwendung von 16S
rRNA-Gensequenzen als „molekulare Chronometer“ (Woese, 1987). Der Vergleich von
16S rRNA-Gensequenzen lässt eine relativ sichere und zuverlässige phylogenetische
5
Kapitel I
Einleitung
Klassifizierung einzelner Bakteriengruppen und –arten zu. Durch die Anwendung
verschiedener
molekularbiologischer
Techniken
wie
Denaturing
Gradient
Gel
Electrophoresis (DGGE) (Muyzer et al., 1993), Terminal Restriction Fragment Length
Polymorphism (TRFLP) (Clement et al., 1998), Automated Ribosomal Intergenic Spacer
Analysis
(ARISA)
(Fisher
&
ohne
Triplett,
1999)
aufwändige
oder
Klonbibliotheken
Kultivierungsansätze
direkt
können
in
ihren
natürlichen Habitaten untersucht werden. Auf diese Weise wurden in den letzten Jahren
verschiedenste aquatische Bakteriengemeinschaften untersucht und beschrieben (z.B.
Giovannoni et al., 1990; Rappé et al., 2000; Urbach et al., 2001; Van der Gucht et al.,
2005; Newton et al., 2006). Diese, rein zur Bestimmung der phylogenetischen Diversität
ausgelegten Methoden, erlauben jedoch keine Aussagen über die in situ Abundanz
einzelner Bakteriengruppen. Anhand von Klonbibliotheken kann zwar ein erster Eindruck
über das Auftreten einzelner Bakteriengruppen gewonnen werden, doch müssen diese
Ergebnisse durch quantitative Analysen bestätigt werden (vgl. Kapitel III). Diese Lücke
wurde durch die Fluoreszenz in situ Hybridisierung (FISH) geschlossen, mit deren Hilfe
Bakterien in ihrem natürlichen Habitat nachgewiesen und quantifiziert werden können
(Amann et al., 1995; Glöckner et al., 1999). Bei der FISH werden zur 16S oder 23S rRNA
komplementäre Oligonukleotid-Sonden verwendet, die mit einem Fluoreszenzfarbstoff
markiert sind. Je nach Spezifität der Sonde kann so die Abundanz ganzer
Bakteriengruppen oder spezifischer Cluster in einer Probe mikroskopisch bestimmt
werden.
Die Einführung der Molekularbiologie in die mikrobielle Ökologie brachte einen riesigen
Fortschritt bei der phylogenetischen Beschreibung natürlicher Bakteriengemeinschaften.
Da jedoch von den phylogenetischen Informationen nur eingeschränkt auf die Physiologie
der Bakterien geschlossen werden kann, blieb die Frage nach der Funktion oft ungeklärt.
Dies führte zu einem Umdenken in der mikrobiellen Ökologie. So wurden neben den rein
phylogenetischen
Analysen
wieder
vermehrt
Anstrengungen
unternommen,
die
physiologischen und ökologischen Eigenschaften der Bakterien zu untersuchen. Aus
diesem Grund wurde in den letzten Jahren wieder verstärkt kultiviert (z.B. Jaspers et al.,
2001; Rappé et al., 2002; Hahn et al., 2003; Schauer et al., 2005; Gich et al., 2005), da
die
physiologische
Charakterisierung
von
Bakterienisolaten
immer
noch
die
zuverlässigsten Ergebnisse über die Physiologie und biochemischen Eigenschaften der
Bakterien liefert. Man versuchte vor allem, die Bakterien zu isolieren, die anhand der
molekularbiologischen Analysen in den jeweiligen Habitaten als dominant identifiziert
wurden (z.B. marines SAR11 Cluster, Rappé et al., 2002 oder limnische Actinobacteria
des acI Clusters, Gich et al., 2005).
6
Kapitel I
Einleitung
Auch auf der molekularbiologischen Seite wurden neue Methoden entwickelt, um die
physiologischen Eigenschaften unkultivierter Bakterien zu untersuchen. Eine Reihe von
Methoden richtet sich dabei auf den in situ Nachweis von Stoffwechseleigenschaften
bestimmter Bakteriengruppen in ihrer natürlichen Umgebung (Lee et al., 1999; Borneman,
1999; Lebaron et al., 2002; Nercessian et al., 2005). Durch die Verknüpfung von
Mikroautoradiographie und FISH (MAR-FISH) kann beispielsweise gezielt die Aufnahme
spezifischer Substrate durch bestimmte Bakterien untersucht werden (Lee et al., 1999;
Ouverney & Fuhrman, 1999; Cottrell & Kirchman, 2000b). Von einem rein genetischen
Ansatz gehen die in neuerer Zeit populär geworden Genom- bzw. Metagenom-Analysen
(z.B. BAC oder FOSMID libraries) aus (Béjà et al., 2002; Venter et al., 2004; Béjà, 2004).
Bei diesen Verfahren werden ganze Bakteriengenome oder Teile davon sequenziert und
auf funktionelle Gene untersucht. Durch das Vorhandensein bestimmter Gene können so
Rückschlüsse auf mögliche physiologische Eigenschaften der jeweiligen Bakterien
gezogen werden. Diese genetischen Ansätze werden zunehmend mit funktionellen
Analysen gekoppelt, in dem auf mRNA bzw. Proteinebene die Expression einzelner
funktioneller Gene unter natürlichen Bedingungen untersucht wird (z.B. Nazaret et al.,
1994; Nogales et al., 2002; Rodriguez-Valera, 2004; Wilmes & Bond, 2004; Schulze et al.,
2005; Uchiyama et al., 2005).
Da sowohl die klassischen mikrobiologischen Ansätze als auch die molekularbiologischen
Methoden ihre Stärken und Schwächen haben, ist in der mikrobiellen Ökologie
zunehmend der Trend zu einem polyphasischen Ansatz zu beobachten. Bei dieser
Herangehensweise
werden
Kultivierungstechniken
und
molekularbiologische
Untersuchungen miteinander kombiniert, um so möglichst genaue Informationen über die
phylogenetische Diversität und Physiologie von Bakteriengemeinschaften zu erhalten
(Gillis et al., 2002; Hahn et al., 2003; Gich et al., 2005; Schauer et al., 2005; Wu & Hahn,
2006).
Phylogenie und Biogeographie aquatischer Bakterien
Die Einführung kultivierungsunabhängiger Methoden in die Mikrobielle Ökologie
ermöglichte ganz neue Einblicke in die phylogenetische Zusammensetzung aquatischer
Bakteriengemeinschaften (Rappé & Giovannoni, 2003). Anhand der Analyse von 16S
rRNA-Gensequenzen wurde in den letzten Jahren eine Vielzahl limnischer und mariner
Bakteriengemeinschaften eingehend untersucht (z.B. Glöckner et al., 1999; Crump et al.,
1999; Rappé et al., 2000; Urbach et al., 2001; Nasreen & Hollibaugh, 2002; Van der
Gucht et al., 2005; Stevens et al., 2005; Lindström et al., 2005; Newton et al., 2006).
7
Kapitel I
Einleitung
Dennoch ist unser gegenwärtiges Bild von der phylogenetischen Diversität aquatischer
Bakteriengemeinschaften immer noch lückenhaft. Dies wird eindrücklich durch eine erst
kürzlich veröffentlichte Studie gezeigt, bei der in einer einzelnen Wasserprobe aus der
Sargassosee mehr als hundert neue und bislang unbekannte 16S rRNA-Gensequenzen
identifiziert wurden (Venter et al., 2004).
Etwa 80 % der bislang bekannten 16S rRNA-Gensequenzen aus dem marinen
Bakterioplankton lassen sich neun distinkten Gruppen zuordnen (Giovannoni & Rappé,
2000). Vergleichende Analysen von 16S rRNA-Gensequenzen aus limnischen Habitaten
hingegen führten zu der Unterscheidung von 34 phylogenetischen Gruppen (Zwart et al.,
2002). Diese phylogenetische Aufteilung limnischer und mariner Bakterien darf aber nicht
als endgültig angesehen werden, da sie sich durch das Hinzukommen neuer Sequenzen
signifikant
ändern
kann.
So
wurden
beispielsweise
innerhalb
der
limnischen
Actinobacteria durch spezifische Analysen weitere phylogenetische Gruppen identifiziert,
die bei den vorangegangenen Analysen aufgrund fehlender Sequenzinformationen nicht
erkannt werden konnten (Warnecke et al., 2004). Mittels spezifischer in situ
Nachweisverfahren
Bacteroidetes
in
(z.B.
FISH)
limnischen
konnten
Systemen
Actinobacteria,
als
die
β-Proteobacteria
dominanten
und
Bakteriengruppen
nachgewiesen werden (Glöckner et al., 2000; Pernthaler et al., 2004; Warnecke et al.,
2005). Aber auch andere Gruppen, wie die α-Proteobacteria, Verrucomicrobia oder
Planctomycetes können bedeutende Anteile an limnischen Bakteriengemeinschaften
ausmachen (Zwart et al., 2002, 2003; Eiler & Bertilsson, 2004). In marinen Habitaten
hingegen
zählen
α-Proteobacteria,
γ-Proteobacteria
und
Bacteroidetes
zu
den
dominanten Bakteriengruppen (Cottrell & Kirchman, 2000; Morris et al., 2002; Pernthaler
et al., 2002; Kirchman et al., 2003).
Neben den Unterschieden in der Verbreitung und Abundanz einzelner Bakteriengruppen
deuten vergleichende phylogenetische Analysen von 16S rRNA-Gensequenzen auch auf
Unterschiede zwischen limnischen und marinen Bakteriengemeinschaften hin (Crump et
al., 1999; Glöckner et al., 1999; Rappé et al., 2000; Selje & Simon, 2003). Der Nachweis
identischer
Phylotypen
(z.B.
α-Proteobacteria,
β-Proteobacteria,
Actinobacteria,
Bacteroidetes) in beiden Habitaten lässt zunächst Ähnlichkeiten zwischen limnischen und
marinen Bakterien vermuten, doch die genauere Analyse der phylogenetischen
Beziehungen widerlegt diesen Eindruck deutlich (Glöckner et al., 1999; Rappé et al.,
2000). So finden sich innerhalb der α-Proteobacteria, Actinobacteria und Bacteroidetes
neben Gruppen, denen Bakterien beider Habitate angehören, auch spezifische Cluster,
die ausschließlich aus limnischen bzw. marinen Sequenzen bestehen (Giovannoni et al.,
8
Kapitel I
Einleitung
1990; Teske et al., 1994; Bahr et al., 1996; Crump et al., 1999; Zwart et al., 1998, 2002;
Rappé et al., 2000; Warnecke et al., 2004)
Mit
der
steigenden
Zahl
an
verschiedener
phylogenetischen
Habitate
rückte
Beschreibungen
die
Frage
nach
von
der
geographischen Verbreitung (Biogeographie) einzelner Bakteriengruppen bzw. –arten in
den Fokus der mikrobiellen Ökologie (Staley, 1999; Finlay, 2002; Fenchel, 2003; Hughes
Martiny et al., 2006; Ward & Bora, 2006). Der Niederländer L.M.G. Baas-Becking war
einer der ersten Mikrobiologen, der sich mit diesem Thema auseinander gesetzt hat. Mit
seiner Hypothese: „Alles is overal: maar het milieu selecteert“ (Alles ist überall, aber die
Umwelt selektiert) (Baas-Becking, 1934) postulierte er, dass Bakterien kosmopolitisch
verbreitet sind und nicht den gleichen geographischen Schranken unterworfen sind wie
höhere Organismen. Er stützte seine Hypothese dabei auf die Eigenschaft von Bakterien,
leicht durch Wasser, Luft und Tiere verbreitet werden zu können (Griffin et al., 2002).
Lediglich
die
jeweiligen
Standortbedingungen
wie
Temperatur,
Salinität
oder
Nährstoffverfügbarkeit steuern die Struktur der Bakteriengemeinschaften und selektieren
die vorherrschenden Bakterienarten. Aufgrund dieser Annahme sollten ähnliche Habitate
auch ähnliche Bakteriengemeinschaften beherbergen. Tatsächlich scheint sich der zweite
Teil der Hypothese von Baas-Becking („maar het milieu selecteert“) zu bestätigen
(Hughes Martiny et al., 2006). So wurden beispielsweise in limnischen und marinen
Habitaten unterschiedliche Bakteriengemeinschaften nachgewiesen, die an die jeweiligen
Umweltbedingungen angepasst zu sein scheinen (Mullins et al., 1995; Glöckner et al.,
1999; Rappé et al., 2000; Zwart et al., 2002; Crump et al., 2004; Hahn & Pöckl, 2005;
Wu & Hahn, 2006). Der erste Teil der Hypothese („Alles is overal“) von Baas-Becking wird
hingegen noch kontrovers diskutiert (Fenchel et al., 1997; Staley, 1997; Finlay, 2002;
Fenchel, 2003; Hughes Martiny et al., 2006). Es gibt zwar eine ganze Reihe von Arbeiten,
die auf eine globale Verbreitung von Mikroorganismen hindeuten (z.B. Glöckner et al.,
1999; Rappé et al., 2000; Zwart et al., 2002; Warnecke et al., 2004; Hahn & Pöckl, 2005;
Ward & Bora, 2006), doch reichen die gegenwärtig bekannten Informationen nicht für eine
fundierte Bestätigung der Hypothese aus. Generell fehlt es an größeren vergleichenden
Studien, die gezielt das Auftreten und die Verbreitung einzelner Bakteriengruppen in
bestimmten Habitaten unterschiedlicher geographischer Regionen untersuchen (Hughes
Martiny et al., 2006). Des Weiteren müssen auch noch diverse methodische Limitationen
überwunden werden, da mit den heutigen molekularbiologischen Methoden nicht
hundertprozentig ausgeschlossen werden kann, dass nicht nachgewiesene Bakterien
auch wirklich nicht in dem untersuchten Habitat vorkommen (Staley, 1999).
9
Kapitel I
Einleitung
Saisonale Dynamik von Bakteriengemeinschaften
Aquatische Bakteriengemeinschaften werden von einer Vielzahl an Umweltfaktoren
beeinflusst, die zu einer ausgeprägten räumlichen und zeitlichen Dynamik der jeweiligen
Bakterienpopulationen führen (Muylaert et al., 2002). Während die saisonale Dynamik des
Phyto- und Zooplanktons bereits eingehend untersucht wurde (Sommer, 1989), ist über
die Dynamik von Bakteriengemeinschaften bislang nur wenig bekannt (Kent et al., 2004).
Studien an aquatischen Bakteriengemeinschaften haben mehrfach ausgeprägte saisonale
Veränderungen in der Struktur der Bakteriengemeinschaften gezeigt (z.B. Höfle et al.,
1999; Bosshard et al., 2000; Van der Gucht et al., 2001; Crump et al., 2003; Zwisler et al.,
2003; Yannarell et al., 2003; Kent et al., 2004). Dabei wurde deutlich, dass die Dynamik
der Bakteriengemeinschaften nicht nur starren saisonalen Mustern folgt, sondern auch
Veränderungen zwischen den einzelnen Jahren vorkommen können (Yannarell et al.,
2003;
Kent
et
al.,
2004;
Newton
et
al.,
2006).
Generell
gibt
es
zwei
Regulationsmechanismen, die das Wachstum von aquatischen Bakteriengemeinschaften
beeinflussen
und
somit
grundlegend
für
Veränderungen
in
der
Struktur
der
Bakteriengemeinschaften verantwortlich sind. Zum einen wird das bakterielle Wachstum
durch die Verfügbarkeit von Nährstoffen (bottom up) limitiert (z.B. Coveney & Wetzel,
1992; Schweitzer & Simon, 1995; Fisher et al., 2000) und zum anderen durch Grazer und
Phagen (top down) reguliert (z.B. Šimek et al., 1995, 2001; Hahn & Höfle, 2001; Vrede et
al.,
2003;
Jacquet
et
al.,
2005).
Jahreszeitliche
Veränderungen
in
den
Bakteriengemeinschaften sind daher eng an die saisonale Dynamik des Phyto- und
Zooplanktons gekoppelt (Muylaert et al., 2002). Die durch das Phytoplankton produzierten
gelösten organischen Materialien (Exsudate) sind wichtige Nahrungsquellen für
heterotrophe Bakterien, die insbesondere in der Folge einer Frühjahrsblüte zu erheblichen
Wachstums- bzw. Produktionsraten der Bakterien führen können (Baines & Pace, 1991).
Auf der anderen Seite unterliegen die Bakteriengemeinschaften einem erheblichen
Fraßdruck durch Protozoen wie heterotrophe Nanoflagellaten (HNF) und Ciliaten (z.B.
Sanders et al., 1989; Šimek et al., 1995; Adrian & Schneider-Ort, 1999; Hahn & Höfle,
2001). Neben diesen biologischen Prozessen wurden auch physiko-chemische Parameter
identifiziert (z.B. Temperatur, pH, PO4-P), die einen Steuerungseinfluss auf die Struktur
der
zeigen
(Lindström,
2001;
Muylaert
et
al.,
2002;
Stepanauskas et al., 2003; Yannarell & Triplett, 2005; Lindström et al., 2005). So führen
beispielsweise niedrige Wassertemperaturen oder der Mangel an anorganischen
Nährstoffen zu einer Limitation des bakteriellen Wachstums (Chrzanowski et al., 1995;
Schweitzer & Simon, 1995; Pomeroy & Wiebe, 2001; Šimek et al., 2003). Es sind aber
10
Kapitel I
Einleitung
nicht nur die gewässerinternen Prozesse, die maßgeblich für die saisonalen
Veränderungen in den Bakteriengemeinschaften verantwortlich sind, sondern auch
allochthone Prozesse, wie z.B. der Eintrag von externen Nährstoffen (Crump et al., 2003).
Des Weiteren können durch Zuflüsse Bakterien in bereits bestehende Systeme eingespült
werden, die zu beachtlichen Änderungen in den Bakteriengemeinschaften führen können
(Lindström & Bergström, 2004). Aufgrund der Komplexität und Vielzahl an limnologischen
Prozessen ist unser gegenwärtiges Wissen über den Einfluss einzelner Umweltparameter
auf die Dynamik aquatischer Bakteriengemeinschaften sehr begrenzt. Vor allem fehlt es
an gezielten Studien zur saisonalen Dynamik einzelner Bakteriengruppen. Wie molekulare
Analysen
von
gezeigt
haben,
können
einzelne
Bakteriengruppen sehr unterschiedliche saisonale Dynamiken aufweisen (Pernthaler et
al., 1998; Glöckner et al., 2000; Crump et al., 2003). Neben diesen „dynamischen“
Bakterienpopulationen gibt es aber auch Bakteriengruppen, die nahezu keinen saisonalen
Veränderungen unterliegen und unverändert das ganze Jahr über vorkommen (Crump et
al., 2003; Selje & Simon, 2003).
Aggregate als Lebensraum für aquatische Bakterien
Im Pelagial limnischer und mariner Habitate spielen Aggregate eine besondere Rolle für
heterotrophe
(Simon
et
al.,
2002).
Die
aus
autochthonem und allochthonem partikulären Material bestehenden Aggregate gelten
aufgrund ihrer erhöhten Nährstoffkonzentrationen im Vergleich zum Umgebungswasser
als „hot spots“ für die Mikroorganismen (Pedrós-Alio & Brock, 1983; Gotschalk &
Alldredge, 1989; Herndl, 1992). Das gute Nährstoffangebot auf den Aggregaten führt bei
partikel-assoziierten Bakterien zu deutlich höheren Wachstumsraten, zellspezifischen
Aktivitäten und Aufnahmeraten von Zuckern und Aminosäuren als bei Bakterien aus der
Freiwasserfraktion (Middelboe et al., 1995; Grossart & Simon, 1998; Friedrich et al., 1999;
Grossart & Ploug, 2001; Grossart et al., 2003). In pelagischen Systemen sind partikelassoziierte Bakterien durchschnittlich an ca. 10-15 % der gesamten bakteriellen
Produktion und Abundanz beteiligt (Griffith et al., 1994; Turley & Mackie, 1994; Grossart &
Simon, 1998). Unter bestimmten Bedingungen können sie sogar über die Hälfte der
gesamten bakteriellen Biomasse oder Aktivität ausmachen (Smith et al., 1995; Middelboe
et al., 1995; Zimmermann, 1997). Durch die hydrolytische Aktivität partikel-assoziierter
Bakterien werden oft mehr Substrate freigesetzt als von den Bakterien selber verwertet
werden (Smith et al., 1992; Grossart & Simon, 1998). Diese gelösten Substanzen werden
in das Umgebungswasser abgegeben und dienen so frei-lebenden Bakterien als wichtige
11
Kapitel I
Einleitung
Nährstoffquelle. Aufgrund der hohen mikrobiellen Aktivitäten können sich auf den
Aggregaten
sehr
spezifische
physikalische,
chemische
und
hydrodynamische
Bedingungen einstellen (Alldredge et al., 1987; Fletcher, 1991; Simon et al., 2002). Stark
erhöhte
Respirationsraten
können
beispielsweise
zu sehr
niedrigen
Sauerstoff-
konzentrationen auf den Aggregaten führen, bis zur Entstehung anoxischer Bereiche
(Alldredge et al., 1987; Ploug et al., 1997; Ploug, 2001).
Partikel-assoziierte Bakteriengemeinschaften unterscheiden sich jedoch nicht nur
hinsichtlich ihrer physiologischen Aktivitäten von frei-lebenden Bakterien, sondern auch in
ihrer phylogenetischen Zusammensetzung (DeLong et al., 1993; Crump et al., 1999;
Riemann & Winding, 2001; Selje & Simon, 2003; Stevens et al., 2005). Verschiedene
Studien lassen vermuten, dass bestimmte Bakteriengruppen an das Wachstum auf
Partikeln angepasst sind (Fandino et al., 2001; Riemann & Winding, 2001; Kirchman,
2002; vgl. Kapitel II, IV und V). So wurden in limnischen Systemen beispielsweise
Cytophaga-Flavobacteria, α- und β-Proteobacteria als dominante Vertreter auf Partikeln
gefunden,
wohingegen
in
marinen
Systemen
Cytophaga-Flavobacteria,
α-
und
γ-Proteobacteria partikel-assoziierte Bakteriengemeinschaften dominieren (Weiss et al.,
1996; Böckelmann et al., 2000; Kirchman, 2002; Schweitzer et al., 2001; Simon et al.,
2002). Auch wenn viele Studien auf phylogenetische Unterschiede zwischen frei-lebenden
und partikel-assoziierten Bakterien hindeuten, dürfen die beiden Bakteriengemeinschaften
aber nicht als strikt getrennte Fraktionen angesehen werden. Wie eine neuere Studie
zeigt, kann es durch bewegliche Bakterien zu hohen Austauschraten zwischen freilebenden und partikel-assoziierten Bakterien kommen (Kiørboe et al., 2002). Die partikelassoziierten Bakteriengemeinschaften können dabei sehr stark von den frei-lebenden
Bakterien geprägt werden (Grossart et al., 2006).
Das Untersuchungsgebiet: Die Mecklenburgische Seenplatte
Die Mecklenburgische Seenplatte bildet den zentralen und südlichen Teil des
Bundeslandes Mecklenburg-Vorpommern, im Nordosten Deutschlands. Sie ist ein Teil
des Baltischen Landrückens (Marcinek, 1981) und erstreckt sich zwischen dem ElbeLübeck-Kanal im Westen und der Uckermark im Osten. Der größte Teil der Seenplatte
liegt in Mecklenburg-Vorpommern, Ausläufer reichen aber bis nach Niedersachsen und
Brandenburg hinein. So wird die Mecklenburgische Seenplatte immer wieder auch als
Mecklenburgisch-Brandenburgische
Seenplatte
bezeichnet.
Die
Entstehung
der
Mecklenburgischen Seenplatte ist auf Vorgänge in der letzten Eiszeit Nord- bzw.
Mitteleuropas (Weichseleiszeit, ca. 70.000-10.000 vor heute) und dem anschließenden
12
Kapitel I
Einleitung
Holozän zurückzuführen. Dabei führten mit Moränenmaterial überschüttete Eisblöcke und
subglaziale Rinnen mit Schmelzwasser zur Bildung der zahlreichen Seen (Marcinek &
Nietz, 1973; Krausch & Zühlke, 1974; Casper, 1985; Schmidt, 1997). Durch die
unterschiedliche Entstehungsgeschichte der einzelnen Seen (z.B. Abflussrinnen oder
Abschmelzen von Toteisblöcken) findet man in der Mecklenburgischen Seenplatte auf
engsten Raum eine Vielzahl z.T. sehr unterschiedlicher Seen.
Für diese Arbeit wurden vier Seen der Mecklenburgischen Seenplatte ausgewählt, die
sich in ihrer Morphometrie, physikochemischen und biologischen Beschaffenheit deutlich
voneinander
unterscheiden:
Stechlinsee,
Große
Fuchskuhle,
Breiter
Luzin
und
Tiefwarensee (Tabelle I.1 und Abbildung I.2). Der Stechlinsee und die Große Fuchskuhle
liegen im nördlichen Teil Brandenburgs und gehören zum Rheinsberger Seengebiet. Der
Breite Luzin und der Tiefwarensee hingegen liegen in Mecklenburg-Vorpommern im
Feldberger Seengebiet (Breiter Luzin) bzw. bei Waren an der Müritz (Tiefwarensee).
Tabelle I.1: Übersicht über die grundlegenden morphometrischen und limnologischen Parameter
der vier Untersuchungsgewässer.
Stechlinsee
Große
Fuchskuhle
Breiter Luzin
Tiefwarensee
N 53° 10’
E 13° 02’
N 53° 10’
E 13° 02’
N 53° 20’
E 13° 28’
N 53° 31’
E 12° 42’
Fläche [km2]
4,3
0,02
3,57
1,4
maximale Tiefe [m]
69,5
5,6
58,5
24
mittlere Tiefe [m]
22,8
3,5
25,2
8,2
Volumen [x 10 m ]
96,9
0,05
67,5
12,9
Uferlinie [km]
16,1
0,5
13,2
k.A.
26,0
0,005
14,0
17,5
6,5 – 10,5
0,9 – 2,2**
1,6 – 3,8
3,1 – 8,9
oligotroph
(NO)
eutroph ;
dystroph(SW)
mesotroph
eutroph
8,5
6,5(NO); 4,7(SW)
8,5
8,3
geographische
Position
6
3
2
Einzugsgebiet [km ]
Sichttiefe [m]*
Trophie
pH*
k.A. keine Angaben; *diese Angaben beziehen sich auf Werte, die im Rahmen der monatlichen Probennahmen zwischen April 2003 und
März 2004 ermittelt wurden: **Südwest-Becken: 0,9 – 1,5 m, Nordost-Becken: 1,0 – 2,2 m; (NO) Nordost-Becken; (SW) Südwest-Becken.
Im Folgenden werden die vier Untersuchungsgewässer im Einzelnen kurz dargestellt und
beschrieben. Weitere Informationen zu physikalischen, chemischen, biologischen und
mikrobiologischen Eigenschaften der vier Seen sind in den Kapiteln II, III und IV
aufgeführt.
13
Kapitel I
Einleitung
Stechlinsee
Der Stechlinsee ist einer der klarsten Seen Norddeutschlands. Die Wasseroberfläche
umfasst 4,3 km2 bei einer maximalen Tiefe von 69,5 m (Casper, 1985; Schlegel et al.,
1998). Der Stechlinsee ist ein mono- bis dimiktischer, oligotropher See, dessen
planktische Primärproduktion Phosphor-limitiert ist (Koschel, 1976). Die geringe
Stoffproduktion führt unter den gegebenen morphometrischen Bedingungen zu einer
günstigen
Sauerstoffbilanz,
die
sich
im
Hypolimnion
durch
eine
ganzjährige
Sauerstoffsättigung von über 60 % äußert.
Stechlinsee
Große Fuchskuhle
N
N
N
1 km
Breiter Luzin
Tiefwarensee
Nordsee
Ostsee
Hamburg
Berlin
Deutschland
N
Frankfurt (M)
München
N
W
1 km
1 km
Abbildung I.2: Die vier Untersuchungsgewässer der Mecklenburgischen Seenplatte.
Große Fuchskuhle
Die Große Fuchskuhle ist ein huminstoffreiches Kleingewässer, das komplett von Wald
umgeben ist und im Westen an ein Torfmoor grenzt. Die Wasseroberfläche umfasst ca.
0,02 km2 bei einer maximalen Tiefe von 5,6 m (Kasprzak, 1993). Trotz der geringen Tiefe
ist der See während der Sommermonate geschichtet, wobei das Hypolimnion meist
anoxisch wird (Casper, 1985). In den Jahren 1986 und 1990 wurde die Große Fuchskuhle
14
Kapitel I
Einleitung
für Biomanipulationsexperimente mittels Plastikplanen in zwei bzw. vier Kompartimente
(Südwest (SW), Nordwest (NW), Südost (SO), Nordost (NO)) unterteilt (Kasprzak, 1993;
Koschel, 1995). Durch die Teilung wurden die beiden Ostbecken, im Gegensatz zu den
Westbecken, vom Moorkörper abgetrennt. Dies führte in der Folge zu deutlichen
limnologischen Unterschieden zwischen Ost- und Westbecken. Während die beiden
Westbecken ihren ursprünglichen dystrophen Charakter weitestgehend beibehielten,
entwickelten die beiden Ostbecken einen mehr mesotrophen Charakter. Aufgrund der
ausgeprägten limnologischen Unterschiede (Koschel, 1995; Bittl & Babenzien, 1996;
Šimek et al., 1998; Hehmann et al., 2001; Sachse et al., 2001) wurden im Rahmen dieser
Arbeit das Nordost- und das Südwest-Becken untersucht.
Breiter Luzin
Der Breite Luzin ist mit einer Oberfläche von 3,57 km2 und einer Tiefe von 58,5 m einer
der größten und tiefsten Seen des Feldberger Seengebietes (Landkreis MecklenburgStrelitz). Ursprünglich hatte der Breite Luzin einen oligotrophen Charakter, ist jedoch
durch den erhöhten Eintrag von Nährstoffen der umliegenden landwirtschaftlichen
Nutzflächen gegenwärtig als mesotroph einzustufen. Wie der Stechlinsee zeichnet sich
der Breite Luzin ebenfalls durch hohe hypolimnische Sauerstoffkonzentrationen aus.
Als Relikt aus der Eiszeit hat sich im Breiten Luzin die Eiszeitgarnele Mysis relicta
erhalten (Waterstraat, 1988). Durch Mysis relicta wird in der Nahrungskette eine
zusätzliche
trophische
Ebene
zwischen
Zooplankton
und
planktivoren
Fischen
eingeschaltet.
Tiefwarensee
Der Tiefwarensee ist ein dimiktischer Hartwassersee mit eutrophem Charakter (Koschel et
al., 1998). Der See liegt am nordöstlichen Stadtrand von Waren (Müritz) und hat eine
Fläche von ca. 1,4 km2 bei einer maximalen Tiefe von 24 m.
In den 80er Jahren des letzten Jahrhunderts verschlechterte sich innerhalb kürzester Zeit
die Wasserqualität des Tiefwarensees sehr stark. Die Gründe hierfür lagen in
menschlichen
Aktivitäten
Nährstoffbelastung
wurde
wie
der
Industrie
und
Landwirtschaft.
See
teilweise
sogar
Durch
hypertroph.
die
starke
Eingeleitete
Sanierungsmaßnahmen konnten die externe Phosphor-Last um etwa 90 % senken
(Koschel et al., 2006). Durch eine kombinierte hypolimnische Phosphor-Fällung mit
Aluminat und Calciumhydroxid (Gonsiorczyk et al., 2002) konnte die Wasserqualität des
Tiefwarensees zwischen 2001 und 2005 erheblich verbessert werden. Der See kann
daher heute wieder als eutroph eingestuft werden.
15
Kapitel I
Einleitung
Der See Genezareth (Israel)
Zusätzlich zu den vier oben genannten Seen der Mecklenburgischen Seenplatte wurde im
Rahmen einer Fallstudie zur Abundanz und Phylogenie von Actinobacteria (vgl. Kapitel V)
der See Genezareth (Israel) im Oktober 2004 beprobt.
Der meso-eutrophe See Genezareth liegt im Norden Israels am Fuße der Golanhöhen im
Ostafrikanischen Grabensystem, dass sich von Syrien bis zum Sambesi erstreckt. Der
See liegt 209 m unter dem Meeresspiegel und hat eine Fläche von 170 km2 mit einer
maximalen Tiefe von 43 m (durchschnittliche Seetiefe: 24 m). Mit seinem Volumen von
4 x 106 m3 ist der See Genezareth der größte Trinkwasserspeicher Israels. Aufgrund
seiner geographischen Lage ist der See Genezareth als subtropischer See einzuordnen.
Das Epilimnion des von April bis November stabil geschichteten Sees kann sich daher auf
bis zu 30 °C erwärmen. Mit Beginn der Schichtung im April wird das Hypolimnion relativ
schnell anoxisch und weist Sulfidkonzentrationen von 5,0 – 9,0 mg l-1 auf und
Ammoniumkonzentrationen von 0,5 – 1,3 mg l-1 (Berman et al., 2004). Durch die leichte
Durchmischung der Wassersäule zwischen Dezember und Februar wird der See
Genezareth als monomiktisch eingestuft. Die jährliche Netto-Primärproduktion beträgt
610 g C m-2 (Bermann et al., 1995).
16
Kapitel I
Einleitung
Zielsetzung der Arbeit
Aus mikrobiologischer Sicht sind an den Seen der Mecklenburgischen Seenplatte bislang
wenige Untersuchungen durchgeführt worden. Vor allem fehlt es an vergleichenden
Studien, die Rückschlüsse auf das Vorkommen, die Verbreitung und Anpassung einzelner
Bakteriengruppen an die Gewässer dieser Region ermöglichen. Frühere Studien waren
meist auf einzelne Seen oder Bakteriengruppen fokussiert und liefern nur begrenzt
Informationen hinsichtlich der Zusammensetzung und Dynamik der entsprechenden
Bakterioplanktongemeinschaften (Babenzien, 1991; Sass et al., 1996, 1997; Glöckner et
al., 1998, 2003; Burkert et al., 2003; Warnecke et al., 2004, Babenzien & Cypionka, 2005;
Babenzien et al., 2005).
Diese Arbeit hatte daher das Ziel, systematisch die Diversität und Dynamik heterotropher
Bakterioplanktongemeinschaften im Pelagial von vier limnologisch unterschiedlichen Seen
der Mecklenburgischen Seenplatte (Stechlinsee, Große Fuchskuhle, Breiter Luzin und
Tiefwarensee) zu bestimmen und miteinander zu vergleichen. Dabei sollten die
dominanten Bakteriengruppen identifiziert und ihre Verbreitung und Abundanz mittels
spezifischer Nachweissysteme eingehend untersucht werden. In einem weiteren Schritt
sollte versucht werden, die Struktur der Bakteriengemeinschaften mit limnologischen
Parametern in Verbindung zu bringen (Verknüpfung von „Struktur und Funktion“), um so
Aussagen
über
die
Anpassung
und
Ökologie
der
entsprechenden
Bakterien-
gemeinschaften machen zu können. Die Ziele können im Einzelnen wie folgt
zusammengefasst werden:
I)
Charakterisierung
der
in
den
vier
Untersuchungsgewässern: Stechlinsee, Große Fuchskuhle, Breiter Luzin
und Tiefwarensee.
II)
Identifizierung und Charakterisierung dominanter Bakteriengruppen.
III)
Verknüpfung
von
Struktur
und
Funktion
–
Identifizierung
von
Umweltfaktoren, die einen Steuerungseinfluss auf die Diversität und
Dynamik der untersuchten Bakteriengemeinschaften zeigen.
Voraussetzung für diese Arbeit war eine „generelle Bestandsaufnahme“, bei der die
phylogenetische Zusammensetzung und saisonale Dynamik der Bakteriengemeinschaften
der vier ausgewählten Seen bestimmt wurde. Im Rahmen des Forschungsprogramms des
Leibniz-Institutes für Gewässerökologie und Binnenfischerei (IGB) in Neuglobsow wurden
dazu von den vier Untersuchungsgewässern ein Jahr lang monatlich Proben genommen
17
Kapitel I
Einleitung
und mittels verschiedener molekularbiologischer Methoden analysiert. Um eine höhere
phylogenetische Auflösung zu erlangen, wurde dabei zwischen frei-lebenden und partikelassoziierten
Bakterien
unterschieden.
Die
Ergebnisse
aus
der
molekularen
Charakterisierung der Bakteriengemeinschaften und deren Vergleich sind in Kapitel II
ausführlich dargestellt und wurden bereits als Manuskript bei Aquatic Microbial Ecology
zur Publikation eingereicht.
Die durch die molekulare Charakterisierung der Bakteriengemeinschaften identifizierten
dominanten Bakteriengruppen wurden im Weiteren qualitativ und quantitativ hinsichtlich
ihrer Diversität, Abundanz und geographischen Verbreitung untersucht. Durch die
Anwendung
und
Entwicklung
spezifischer
Nachweissysteme
wurden
einzelne
Bakteriengruppen und Cluster hochauflösend charakterisiert. Die Ergebnisse dieser
Untersuchungen sind in den Kapiteln III, IV und V aufgeführt. Das Manuskript mit den
Ergebnissen aus Kapitel III wurde bereits bei Applied and Environmental Microbiology
veröffentlicht (Allgaier & Grossart, 2006). Die Manuskripte aus den Kapiteln IV und V
wurden bei Environmental Microbiology zur Publikation eingereicht und befinden sich
gegenwärtig in der Begutachtung.
In der heutigen aquatischen mikrobiellen Ökologie spielt die Verknüpfung von Struktur
und
Funktion
natürlicher
eine
zentrale
Rolle.
Durch
experimentelle oder rein statistische Ansätze wird dabei der Einfluss einzelner
Umweltparameter auf Veränderungen in den Bakteriengemeinschaften untersucht. Im
dritten Teil dieser Arbeit sollte daher versucht werden, mittels verschiedener statistischer
Verfahren
Veränderungen
in
den
bzw.
dominanten
Bakteriengruppen mit einzelnen Umweltparametern in Verbindung zu bringen. Durch die
Ergebnisse sollten mögliche Rückschlüsse auf die Physiologie bzw. ökologische
Anpassung der Bakterien an die entsprechenden Umweltbedingungen gezogen werden
können. Die Ergebnisse aus den statistischen Analysen sind in den Kapiteln II und IV
aufgeführt und zur Publikation eingereicht (s.o.). Die nicht in den Manuskripten
enthaltenen Ergebnisse zur statistischen Verknüpfung von Struktur und Funktion der
Bakteriengemeinschaften sind im Anhang zusammengefasst.
18
Kapitel I
Einleitung
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YANNARELL, A.C., KENT, A.D., LAUSTER, G.H., KRATZ, T.K., TRIPLETT, E.W. (2003)
Temporal patterns in bacterial communities in three temperate lakes of different
trophic status. Microb. Ecol. 46:391-405.
YANNARELL, A.C., AND TRIPLETT, E.W. (2005) Geographic environmental sources of
variation in lake bacterial community composition. Appl. Environ. Microbiol. 71:227239.
ZIMMERMANN, H. (1997) The microbial community on aggregates in the Elbe Estuary.
Aquat. Microb. Ecol. 13:37-46.
ZWART, G., HIORNS, W., METHÉ, B., KAMST-VAN AGTERVELD, M.P., HUISMANS, R., NOLD, S.,
ZEHR, J., AND LAANBROEK, H. (1998) Nearly identical 16S rRNA sequences
recovered from lakes in North America and Europe indicate the existence of clades
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Typical freshwater bacteria: an analysis of available 16S rRNA gene sequences
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ZWART, G., VAN HANNEN, E.J., KAMST-VAN AGTERFELD, M.P., VAN DER GUCHT, K.,
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27
II
Seasonal dynamics and
phylogenetic diversity of free-living
and particle-associated bacterial
communities in four lakes of
Northeastern Germany
Kapitel II
Diversity and dynamics of bacterioplankton communities
Aquatic Microbial Ecology (accepted)
Seasonal dynamics and phylogenetic diversity of free-living and
particle-associated bacterial communities in four lakes of Northeastern
Germany
Martin Allgaier and Hans-Peter Grossart*
Leibniz-Institute of Freshwater Ecology and Inland Fisheries
Department Limnology of Stratified Lakes
Alte Fischerhütte 2
D-16775 Stechlin-Neuglobsow
Germany
Running title: Diversity and dynamics of freshwater bacterioplankton
Key words:
bacterioplankton communities, phylogenetic diversity, seasonal
dynamics, freshwater bacteria, DGGE, clone libraries
*Corresponding author: Leibniz-Institut für Gewässerökologie und Binnenfischerei;
Abteilung Limnologie geschichteter Seen; Alte Fischerhütte 2; D-16775 StechlinNeuglobsow; Phone: +49 33082 69991; Fax: +49 33082 69917; email: [email protected]
31
Kapitel II
ABSTRACT: The phylogenetic diversity and seasonal dynamics of free-living and particleassociated bacterial communities was investigated in the epilimnion of four limnological
different lakes of the Mecklenburg Lake District, Northeastern Germany. Bacterial
community structure and seasonal dynamics were analyzed by denaturing gradient gel
electrophoresis (DGGE) and clone libraries of 16S rRNA gene fragments. Communities of
free-living and particle-associated bacteria greatly differed among the lakes. In addition,
significant differences occurred between both bacterial fractions within each single lake.
Seasonal changes were more pronounced within free-living compared to particleassociated bacterial communities. Several strong correlations were found between freeliving and particle-associated bacteria by non-metric multidimensional scaling (NMS)
analyses (e.g. pH, dissolved organic carbon (DOC), phytoplankton biomasses, or primary
production). Phylogenetically, all cloned and sequenced 16S rRNA gene fragments
belonged to already known freshwater clusters. Clone libraries of free-living bacteria were
dominated by sequences of β-Proteobacteria, Actinobacteria, and Bacteroidetes, whereas
those of particle-associated bacteria predominantly consist of Bacteroidetes and
Cyanobacteria sequences, respectively. Other freshwater phyla, such as α-, and
γ-Proteobacteria, Verrucomicrobia, Planctomycetes, or members of the Candidate
Division OP10 were found in low proportions. These differences may indicate an
adaptation of distinct bacterioplankton communities to the respective environmental
conditions in each lake.
INTRODUCTION
Heterotrophic bacteria are known to play a key role in biogeochemical processes and are
responsible for the break-down of organic matter and the remineralisation of nutrients
(Cotner & Biddanda 2002). Until the late 1980ies, aquatic bacteria have been considered
as an entity or black box without any further differentiation in respect to their taxonomic
composition. An important first step towards understanding the role of aquatic bacterial
communities is the determination of the phylogenetic diversity of the appropriate
bacterioplankton communities (Cottrell & Kirchman 2000). The introduction of molecular
methods into aquatic microbial ecology has facilitated the study of bacterioplankton
community structure (Morris et al. 2002). Currently several studies have characterized
bacterial community composition and dynamics of different aquatic habitats by cultureindependent methods such as denaturing gradient gel electrophoresis (DGGE) or
sequence analyses of 16S rRNA gene fragments (e.g. Glöckner et al. 1999, Rappé et al.
2000, Trusova & Gladyshev 2002, Zwart et al. 2002, Van der Gucht et al. 2005). However,
32
Kapitel II
there are fewer studies on freshwater than on marine bacterial communities. In general,
bacterial communities in freshwater are dominated by β-Proteobacteria, Actinobacteria,
and members of the Bacteroidetes, whereas pronounced differences and variations were
found between free-living and particle-associated bacterial communities (Weiss et al.
1996, Rappé et al. 2000, Schweitzer et al. 2001, Zwart et al. 2002, Selje & Simon 2003).
Nevertheless, so far no comprehensive seasonal study on free-living and particleassociated bacterioplankton communities of different freshwater habitats exists.
Although many studies focus on the composition of freshwater bacterioplankton
communities, surprisingly few examine the temporal and seasonal dynamics of bacterial
communities in detail (Pinhassi & Hagström 2000, Van der Gucht et al. 2001, Zwisler et al.
2003, Kent et al. 2004). Thus, seasonal and spatial dynamics of complex freshwater
bacterioplankton communities is yet poorly understood. It has been shown, however, that
changes in environmental conditions significantly influence bacterial community structure
throughout distinct seasons and periods (e.g. Fisher et al. 2000, Langenheder & Jürgens
2001, Hahn & Höfle 2001, Crump et al. 2003, Kent et al. 2004). Various parameters, such
as dissolved organic carbon, grazing by heterotrophic nanoflagellates, or phytoplankton
biomass were found to affect freshwater bacterial communities (Methé & Zehr 1999,
Pernthaler et al. 2001, Muylaert et al. 2002).
In this study we have compared the seasonal dynamics and phylogenetic diversity of freeliving and particle-associated bacterial communities of four selected lakes of the
Mecklenburg Lake District, Northeastern Germany, to test: I) whether both bacterial
fractions consistently differ from each other, II) whether there are pronounced seasonal
and spatial patterns in community structure of both fractions, and III) whether the
observed patterns can be linked to environmental variables.
MATERIALS AND METHODS
Study sites and sampling collection. Four limnological different lakes were selected for
this study. All lakes are located in the Mecklenburg Lake District (Northeastern Germany)
which was formed after the last ice age (Weichselian stage). Oligotrophic Lake Stechlin
and mesotrophic Lake Breiter Luzin are among the deepest lakes in this area (68.5 m and
58.5 m, respectively) and are both characterized by high hypolimnetic oxygen
concentrations (up to 60 % O2 saturation). Lake Stechlin is situated in the middle of a
mixed forest mainly composed of beech and pine trees, whereas the catchment area of
Lake Breiter Luzin consists of natural forests and farm land.
33
Kapitel II
In comparison, eutrophic Lake Tiefwaren is strongly influenced by anthropogenic
activities. Extensive agriculture and industry in the late 1980s resulted in a formerly
hypertrophic state. A restoration approach by a combination of aluminate and calcium
hydroxide precipitation between 2001 and 2005 (Koschel et al. 2006) yielded in its present
eutrophic state.
The relatively small Lake Grosse Fuchskuhle is situated in a mixed forest and was
artificially divided into four compartments (southwest (SW), northwest (NW), northeast
(NE), and southeast (SE)) for biomanipulation experiments by large plastic curtains in the
1990ies (Kasprzak 1993, Koschel 1995). Due to their great differences in limnological
parameters (Bittl & Babenzien 1996, Hehmann et al. 2001) the NE and SW compartments
were selected for this study. The dystrophic SW compartment is the most acidic
compartment of the lake (pH 4.7) since it is strongly influenced by the high input of humic
matter from the adjacent bog area. The mesotrophic NE compartment receives less humic
acids and, hence, is more neutral (pH 6.5). A summary of the most important
physicochemical and biological parameters of all studied lakes are given in Table 1.
All lakes were sampled monthly between April 2003 and March 2004, except during ice
coverage in December (Lake Breiter Luzin), January (all lakes), and February (Lake
Grosse Fuchskuhle). Composite water samples representing the epilimnion were
collected with a Ruttner sampler at the deepest point of each lake. Based on the thermal
stratification sub-samples were taken from 0, 5, and 10 m depth (April-May and OctoberMarch) or 0, and 5 m depth (June-September) in Lake Stechlin, Lake Breiter Luzin, and
Lake Tiefwaren, respectively, and mixed in sterile glass flasks in equal volumes.
Epilimnetic samples of the two compartments of Lake Grosse Fuchskuhle were collected
as mixed samples from 0 and 2 m depth (April and October-March) or as surface samples
(May-September) due to the relatively shallow epilimnion. All water samples were taken
into the lab in dark cooling boxes and processed 2-4 h after sampling.
DNA extraction and PCR amplification of 16S rRNA gene fragments. Particleassociated bacteria were retained by filtering 150-300 ml of sample from each assay onto
a 5.0 µm Nuclepore membrane. Free-living bacteria were collected by filtering 100-150 ml
of the 5.0 µm filtrate onto a 0.2 µm Nuclepore membrane. Extraction of genomic DNA was
performed using a standard protocol with phenol/chloroform/isoamylalcohol, SDS,
polyvinylpyrrolidone, and zirconium beads (Allgaier & Grossart 2006).
For DGGE analysis, a 550 bp fragment of the 16S rRNA gene was amplified using the
primer pair 341f (5’ – CCT ACG GGA GGC AGC AG – 3’) and 907r (5’ – CCG TCA ATT
CMT TTG AGT TT – 3’) (Muyzer et al. 1998). At the 5’-end of the primer 341f an
34
Kapitel II
additional 40 bp GC-rich nucleotide sequence (GC-clamp) was added to stabilize
migration of the DNA fragment in the DGGE (Muyzer et al. 1993). The PCR reaction
mixture contained: 2-5 µl template DNA, each primer at a concentration of 200 nM, each
deoxyribonucleoside triphosphate at a concentration of 250 µM, 2 mM MgCl2, 5 µl of 10 x
PCR reaction buffer, and 0.5 U of BIOTAQ Red DNA Polymerase (Bioline) in a total
volume of 50 µl. PCR amplification was performed with a Gradient Cycler PT-200 (MJ
Research) using the following conditions: initial denaturation at 95 °C (3 min), followed by
30 cycles of denaturation at 95 °C (1 min), annealing at 55 °C (1 min), and extension at
72 °C (2 min). A final extension at 72 °C for 10 min completed the reaction.
For clone libraries the almost complete 16S rRNA gene was amplified using the primer
pair 8f (5’ – AGA GTT TGA TCM TGG CTC AG – 3’) and 1492r (5’ – GGY TAC CTT GTT
ACG ACT T – 3’) specific for the domain bacteria (Muyzer et al. 1995). PCR reaction and
conditions were used as described previously (Allgaier & Grossart 2006).
DGGE analysis of PCR products. PCR products were analyzed by using the INGENY
PhorU DGGE-System (Ingeny) according to the protocol of Brinkhoff & Muyzer (1997).
The DGGE was performed in a 7 % (v/v) polyacrylamide gel with a denaturing gradient
from 40 to 70 % of urea and formamide. For better comparability of different DGGE
profiles, PCR products were quantified on agarose gels using a quantitative DNA ladder
(Low DNA Mass Ladder, Invitrogen) and similar amounts of DNA were loaded onto the
DGGE gels. The DGGE was run in 1 x TAE electrophoresis buffer (40 mM Tris-HCl
(pH 8.3), 20 mM acetic acid, 1 mM EDTA) for 20 h at a constant voltage of 100 V and a
constant temperature of 60 °C. The gels were stained with 1 x SYBR Gold (Molecular
Probes) and documented using an AlphaImager 2200 Transilluminator (Biozym). A
mixture of DNA from three isolates derived from the studied lakes was used for external
standardisation of the gels.
Analyses of DGGE profiles and multivariate statistics. Analyses of the DGGE banding
patterns were done using the Software GelCompar II, Version 3.5 (Applied Maths). We
applied 5-15 % background subtraction depending on the signal-to-noise ratio of the gels.
A band based binary presence/absence table was calculated applying Dice similarity
coefficient which was imported into the ordination software PC-ORD, Version 4.0 (MJM
Software Design). We used non-metric multidimensional scaling (NMS) ordinations
instead of constrained ordination techniques (e.g. canonical correspondence analysis
(CCA)) to avoid distortions originating from the non-normal distribution of our species data
obtained from the DGGE profiles (McCune & Grace 2002). NMS uses only rank order
35
Kapitel II
information of a similarity matrix of the samples rather than the original data matrix. In a
first step NMS searches for the best model describing differences in bacterial community
structure and in a second step, limnological variables are fitted independently to this
model by means of multiple regression criteria. In contrast, constrained ordination
techniques directly search for the most suitable model describing relationships between
community data and environmental variables accounting for both data sets at the same
time.
Primary NMS analyses of all gels were done by a standard setup using relativise
Sørensen distance measures, random starting coordinates, a step-down from six to one
dimension, an instability criterion of 0.0001, 300 iterations to reach stability, 50 runs with
real data sets, and 100 runs with the Monte Carlo permutation test (Mehner et al. 2005).
The final run was performed with the optimum number of dimensions (2-5 dimensions)
and the appropriate configurations as starting coordinates. Varimax rotation was applied
to find corresponding groups and sample units. For the identification of particular
environmental parameters explaining changes in bacterial community composition within
the epilimnion of the lakes Pearson’s product moment correlations of limnological
parameters and the DGGE profiles were calculated on the significant ordination axes.
Analysis of similarity (ANOSIM, Clarke & Green 1988) was used to test statistically the
significance of differences between the DGGE banding patterns within each single lake
and between all lakes. ANOSIM generates a test statistic (R) which is an indication of the
degree of separation between groups. A score of 1 indicate complete separation whereas
a score of 0 indicates no separation. Equal to NMS analyses, ANOSIM is based on a
similarity matrix and not on the original data matrix. ANOSIM analyses were performed
with the software PRIMER 5, Version 5.2.9 (PRIMER-E Ltd).
To test the significance of differences between absolute numbers of DGGE bands of the
lakes, ANOVA with post-hoc test (Scheffé) was performed using the SPSS program,
Version 9.0 (SPSS).
Construction of clone libraries. Cloning of the almost complete 16S rRNA gene
fragments of free-living and particle-associated bacteria was done using the pGEM-TEasy Vector System II (Promega) according to the manufacturer’s protocol. Clone libraries
were constructed for samples from May 2003 (only Lake Stechlin) and November 2003
(all lakes). A total of 19-29 clones of each clone library were picked and sequenced as
described previously (Allgaier & Grossart 2006).
36
Kapitel II
Phylogenetic analyses. Partial sequences were assembled and corrected manually
using
the
software
Chromas,
Version
1.45
(Griffith
University).
Phylogenetic
reconstructions were performed using the ARB software package (http://arb-home.de).
16S rRNA gene sequences of the clone libraries were first checked and classified by
BLAST (http://www.ncbi.nlm.nih.gov/BLAST/) and the RDP-classifier of the Ribosomal
Database Project (http://rdp.cme.msu.edu/). Sequences were then imported into the ARB
database of ca. 52,000 reference sequences including the closest related sequences
determined by BLAST. The sequences were aligned automatically using the integrated
alignment module within the ARB package and subsequently corrected manually. For
stability of the phylogenetic trees first backbone trees were calculated comprising only
sequences of ≥ 1400 nucleotides. Consistence of branching patterns of the trees was
checked applying the three phylogenetic reconstruction methods – neighbor-joining,
maximum parsimony, and maximum likelihood to the appropriate sets of sequences.
Sequences ≤ 1400 nucleotides were added afterwards to the trees according to maximum
parsimony criteria. This tool does not correct for evolutionary distances and does not allow
changes in the overall tree topology.
Nucleotide sequence accession numbers. Obtained 16S rRNA gene sequences were
deposited in GenBank with the following accession numbers: DQ501285-DQ501378.
RESULTS
Numbers of DGGE bands
Highest numbers of DGGE bands of free-living and particle-associated bacteria were
found in Lake Breiter Luzin with seasonal means of 40 ± 2 and 41 ± 5.7 DGGE fragments,
respectively, and lowest numbers within Lake Tiefwaren (24 ± 4.2 and 15 ± 7,
respectively). Seasonal means of absolute numbers of DGGE bands in Lake Stechlin and
the two (NE and SW) compartments of Lake Grosse Fuchskuhle ranged from 27 ± 4.9
(SW compartment of Lake Grosse Fuchskuhle) to 35 ± 3 (Lake Stechlin) for free-living
bacteria and from 24 ± 3.8 (SW compartment of Lake Grosse Fuchskuhle) to 30 ± 7.1 (NE
compartment of Lake Grosse Fuchskuhle) for the particle-associated fractions,
respectively. ANOVA revealed that the number of DGGE bands of free-living bacteria of
Lake Breiter Luzin and Lake Stechlin were significant different from those of Lake
Tiefwaren and the two compartments (NE and SW) of Lake Grosse Fuchskuhle (Table 2).
Within particle-associated bacteria number of DGGE bands of Lake Breiter Luzin and
Lake Tiefwaren were statistically significant different from each other and from all other
37
Kapitel II
lakes, whereas no significant differences were found between Lake Stechlin and the two
compartments (NE and SW) of Lake Grosse Fuchskuhle (Table 2). No significant
differences were found between the numbers of DGGE bands of free-living and particleassociated bacteria within each single lake.
Analyses of DGGE banding patterns
The DGGE banding patterns of free-living and particle-associated bacteria showed distinct
differences in regard to bacterial community composition and seasonal dynamics (for
example see Figure 1). Free-living and particle-associated bacterial communities were
different among the four lakes as indicated by the formation of lake-specific clusters of
DGGE profiles throughout NMS analyses (Figure 2A). Except for particle-associated
bacteria from Lake Stechlin and the SW compartment of Lake Grosse Fuchskuhle all
differences were statistically significant as determined by ANOSIM (Table 3A). Within
free-living bacteria DGGE profiles of Lake Breiter Luzin, Lake Stechlin, and the two
compartments (NE and SW) of Lake Grosse Fuchskuhle exhibited clearly separated
clusters, whereas DGGE banding patterns of Lake Tiefwaren showed particular overlaps
with those of the NE compartment of Lake Grosse Fuchskuhle (Figure 2A). Although the
formation of lake-specific clusters within particle-associated bacteria was statistically
significant, it was less obvious than for free-living bacterial communities (Figure 2A).
The comparison of the DGGE profiles of each single lake revealed significant differences
between free-living and particle-associated bacterial communities (Figure 2B). Except for
the NE compartment of Lake Grosse Fuchskuhle all observed differences were
statistically significant (Table 3B). Additionally, NMS analyses indicated seasonal changes
in bacterial community composition as depicted by the formation of season-specific
clusters of samples within NMS plots (Figure 2B). Season-specific clusters varied
between lakes and bacterial fractions. In general, winter and spring samples of free-living
bacteria clustered together and were clearly separated from samples related to summer
and fall. Formation of seasonal clusters within particle-associated bacteria, however, was
less pronounced compared to free-living bacterial communities.
Sequence analyses of clone libraries
To obtain more detailed informations on the phylogenetic diversity of free-living and
particle-associated bacteria of the studied lakes, clone libraries of 16S rRNA gene
fragments were constructed and sequenced. Altogether, 12 clone libraries from May (only
Lake Stechlin) and November (all lakes) resulted in a total of 277 clones (Table 4). As
determined by BLAST and the RDP classifier, 16S rRNA gene sequences of free-living
38
Kapitel II
bacteria
belonged
to
α-Proteobacteria
(8.3
%),
β-Proteobacteria
(10.4
%),
γ-Proteobacteria (0.7 %), δ-Proteobacteria (1.4 %), Actinobacteria (44.4 %), Bacteroidetes
(14.6 %), Candidate Division OP10 (1.4 %), Cyanobacteria (10.4 %), and chloroplasts (3.5
%). Other bacterial phyla such as Chlorobi, Thermomicrobia or Acidobacteria were
present only at a low percentage (4.9 %). Excluding sequences of chloroplasts of
eucaryotic algae 16S rRNA gene sequences from clone libraries of particle-associated
bacteria were affiliated to α-Proteobacteria (8.1 %), β-Proteobacteria (3.2 %),
γ-Proteobacteria (3.2 %), Actinobacteria (1.6 %), Bacteroidetes (24.2 %), Candidate
Division OP10 (1.6 %), Planctomycetes (4.8 %), Verrucomicrobia (3.2 %), and
Cyanobacteria (43.5 %).
In general, clone libraries of free-living bacteria were dominated by Actinobacteria,
members of the Bacteroidetes, and β-Proteobacteria. Actinobacteria sequences occurred
in consistently high numbers in all four lakes. Members of the Bacteroidetes were found
mainly in Lake Stechlin (May and November), Lake Tiefwaren, and the SW compartment
of Lake Grosse Fuchskuhle. However, no Bacteroidetes were found within free-living
bacteria of Lake Breiter Luzin. Sequences of β-Proteobacteria occurred in relatively high
numbers in Lake Stechlin (only November), Lake Breiter Luzin, and the NE compartment
of Lake Grosse Fuchskuhle (Table 4). Cyanobacterial 16S rRNA gene sequences were
almost exclusively from the May 2003 clone library of free-living bacteria of Lake Stechlin.
When excluding sequences of chloroplasts of eucaryotic algae, clone libraries of particleassociated bacteria were dominated by sequences of Cyanobacteria and members of the
Bacteroidetes. Clones of the Bacteroidetes were found in Lake Tiefwaren, Lake Stechlin
(May), Lake Breiter Luzin, and the NE compartment of Lake Grosse Fuchskuhle (Table 4).
Sequences of Cyanobacteria were almost present in Lake Breiter Luzin, Lake Tiefwaren,
and Lake Stechlin (May and November). Phylogenetic lineages such as Verrucomicrobia
or Planctomycetes occurred in low proportions.
Detailed phylogenetic reconstructions of the free-living and particle-associated bacterial
16S rRNA gene sequences confirmed the phylogenetic classification retrieved by BLAST
and RDP (Figure 3A-C). Because this study was focused on heterotrophic bacteria no
phylogenetic trees were constructed for the Cyanobacteria and the chloroplast
sequences. In general, free-living and particle-associated bacteria were equally distributed
throughout the constructed phylogenetic trees and no distinct lake-specific or bacterial
fraction-specific clusters appeared. A further separation into classes within the
Bacteroidetes was clearly shown by the phylogenetic tree presented in Figure 3B. The
majority of the 16S rRNA gene sequences of the Bacteroidetes belonged to the class
39
Kapitel II
Sphingobacteria. Only 8 sequences were affiliated to the class Flavobacteria and 3
sequences to the class Bacteroidetes, respectively.
Actinobacterial 16S rRNA gene sequences were phylogenetically affiliated to the
freshwater clusters acI, acII, acIV, and acSTL, and to the clusters Soil I-III and Microthrix.
Detailed descriptions of the diversity and phylogenetic relationship of actinobacterial
sequences of this study are given in Allgaier & Grossart (2006).
Relationship between DGGE profiles and environmental variables
Identification of potential correlations between limnological parameters and seasonal
changes within free-living and particle-associated bacterial communities were performed
by non-metric multidimensional scaling (NMS) analyses because of the non-normal
distribution of the species data. Fifteen limnological parameters were used for these
analyses: secchi depth, temperature, conductivity, pH, total nitrogen, total phosphorous,
oxygen concentration, dissolved organic carbon (DOC), total bacterial numbers, bacterial
protein production (total, free-living, and particle-associated), biomasses of phytoplankton
and zooplankton, as well as total primary production.
NMS analyses were separately performed for free-living and particle-associated bacteria
of each single lake and with a combined data set composed of both bacterial fractions. In
addition, two comprehensive data sets of free-living and particle-associated bacteria were
used comprising DGGE profiles and limnological variables of all studied lakes. Pearson’s
product moment correlations of the combined data sets of free-living and particleassociated bacteria of the single lakes revealed only weak correlations (Pearson’s r ≤ 0.7,
data not shown). In contrast, separate analyses of free-living and particle-associated
bacterial communities exhibited several distinct correlations to environmental parameters,
such as temperature, pH, dissolved organic carbon (DOC), bacterial production, primary
production, or phytoplankton biomass (Table 5). However, no consistent patterns could be
observed between the lakes and both bacterial fractions. Comprehensive statistical
analyses including all epilimnetic samples revealed solely a strong correlation between
free-living bacteria and pH (r 0.785, Table 5). As indicated in Figure 2A, pH was highly
correlated with free-living bacteria of Lake Breiter Luzin.
40
Kapitel II
DISCUSSION
Differences in the community structure of free-living and
particle-associated bacteria
To our knowledge this is one of the first comprehensive studies on seasonal changes in
bacterial community structure and dynamics in freshwater systems which consistently
separates free-living from particle-associated bacteria. Our DGGE analyses revealed
significant differences between both bacterial fractions in all lakes. This is in accordance
to previous studies using a ≥ 5.0 µm filtration step to differentiate between free-living and
particle-associated bacteria (e.g. Crump et al. 1999, Riemann & Winding 2001, Selje &
Simon 2003, Stevens et al. 2005). Our own microscopical examination revealed that freeliving and particle-associated bacteria were indeed reliably separated by 5.0 µm
Nuclepore membranes.
The formation of lake-specific clusters within NMS analyses of DGGE banding patterns of
all lakes was more pronounced for free-living than for particle-associated bacteria (Figure
2A). Smaller differences between particle-associated bacterial communities may be due to
more stable environmental conditions on particles and, suggest specific adaptation of
particle-associated bacteria to these specific microenvironments (Weiss et al. 1996,
Grossart & Simon 1998, Brachvogel et al. 2001, Schweitzer et al. 2001). For example,
lake snow aggregates are nutrient rich “hot-spots” for limnetic bacteria leading to higher
bacterial abundances, biomasses, and activities than in the ambient water (Grossart &
Simon 1993, Middelboe et al. 1995, Crump & Baross 1996, Schweitzer et al. 2001, Simon
et al. 2002).
Seasonal dynamics of freshwater bacterioplankton communities
For analyses of bacterial diversity and seasonal dynamics we have used DGGE of PCR
amplified 16S rRNA gene fragments and subsequent NMS analyses. It has been shown
that DGGE analyses are biased by several methodological limitations (Rainey et al. 1994,
Murray et al. 1996, Cottrell & Kirchman 2000). For example, amplification of 16S rRNA
gene fragments can cause selective amplifications of specific bacterial lineages
depending on the primer set used and may exclude minor members of the respective
bacterial community (Suzuki & Giovannoni 1996, Wintzingerode et al. 1997). In addition,
formation of heteroduplex or chimeric molecules and the occurrence of bacteria with
multiple 16S rRNA operons can cause an overestimation of the actual bacterial diversity
(Liesack et al. 1991, Cilia et al. 1996, Ferris & Ward 1997, Klappenbach et al. 2000). On
the other hand, bacterial diversity may be underestimated since single DGGE bands can
41
Kapitel II
comprise several different 16S rRNA gene fragments with similar running behaviour
(Sekiguchi et al. 2001). However, sequencing of particular DGGE bands indicates that the
vast majority of bands consist of a single phylotype and, thus, our DGGE profiles have the
potential to reveal valuable insights into diversity and dynamics of bacterioplankton
communities.
Several studies show pronounced seasonal changes within bacterioplankton communities
in various aquatic systems (Pernthaler et al. 1998, Van der Gucht et al. 2001, Dang &
Lovell 2002, Zwisler et al. 2003, Crump et al. 2003, Kent et al. 2004, Stevens et al. 2005).
Seasonal changes may be linked to numerous environmental factors, such as
phytoplankton succession, protozoan grazing, and viral lysis (Shiah & Ducklow 1994, Van
Hannen et al. 1999, Hahn & Höfle 1999, Pinhassi & Hagström 2000, Fandino et al. 2001,
Yager et al. 2001, Brussaard et al. 2005). Because phytoplankton blooms and grazing
events are generally restricted to distinct seasonal time periods, our monthly sampling
may have considerable effects on the observed patterns. Due to the large time intervals
between the individual samplings we probably missed the full development of
phytoplankton blooms or their subsequently break down. Temporal variations within
phytoplankton blooms, periods of elevated grazing, or increased leaf litter input may
explain the formation of different season-specific clusters in each lake. Artificially derived
changes of bacterial communities throughout impacts of inlet bacteria as shown
previously (Crump et al. 2003, Lindström & Bergström 2004) can be excluded
unambiguously because all lakes are independent from external water inflow. The lakes
are generally maintained by autochthonous processes except during fall and early winter,
when leaf litter leads to a significant input of allochthonous carbon into the lakes. For Lake
Stechlin it has been shown that carbon input throughout leafs can contribute to almost a
quarter of the total annual organic carbon input which leads to significantly increased
14
C-glucose uptake by heterotrophic bacteria (Babenzien pers. com.).
Changes of bacterial community composition in relation
to environmental variables
The seasonal clusters formed by the DGGE banding patterns of free-living bacteria of
Lake Breiter Luzin, Lake Stechlin, and the NE compartment of Lake Grosse Fuchskuhle
seem to be related to stratification and mixing events of the lakes (Figure 2B, Table 1).
During mixing bacterial communities consist of bacteria of the entire water column,
whereas distinct bacterial communities developed in the epi- and hypolimnion during the
summer stratification. In addition, our results of NMS analyses and Pearson’s product
moment correlations indicated strong correlations (Pearson’s r ≥ 0.800) between free-
42
Kapitel II
living bacteria (Lake Breiter Luzin and the NE and SW compartments of Lake Grosse
Fuchskuhle) and the following parameters: secchi depth, temperature, and total bacterial
production (Table 5). Furthermore, particle-associated bacteria were strongly correlated
with conductivity, total phosphorous, and phytoplankton biomass in Lake Breiter Luzin and
Lake Stechlin (Table 5). Statistically significant relationships of these parameters have
been previously shown for total bacterial communities of different freshwater habitats
(Lindtsröm 2000, 2001, Muylaert et al. 2002, Crump et al. 2003, Stepanauskas et al.
2003, Yannarell & Triplett 2004, 2005, Schauer et al. 2005, Lindtsröm et al. 2005). Our
observed lake-specific correlation-patterns may indicate the adaptation of distinct bacterial
communities to specific environments. However, it still remains speculative which
limnological parameters control the respective bacterial community structure. Therefore,
their ecological and physiological relevance has to be investigated in more detail and
should also include a high phylogenetic resolution (Lindström et al. 2005).
The application of presence/absence data of DGGE banding patterns for our multivariate
statistical analysis may limit its interpretation since the use of presence/absence data
significantly influences statistical relationships between community structure and
environmental variables (Muylaert et al. 2002, Yannarell & Triplett 2005). The application
of semi-quantitative or quantitative data of DGGE banding patterns is more robust towards
preferential amplification of certain genotypes and, hence, overestimation of these species
over others as it can occur in presence/absence analyses. Thus, quantitative data sets
are generally more suitable for multivariate statistical analysis (Muylaert et al. 2002).
Because quantifications of PCR products for our DGGE analyses were not precise
enough to generate quantitative data sets we rather used presence/absence
transformations in our statistical analyses to circumvent potential artefacts derived from
the application of deficient community data. Nevertheless, multiple linear regression
analyses and application of other multivariate statistical methods confirm our NMS results.
Phylogenetic diversity of freshwater bacterial communities
Diversity determined by the numbers of DGGE bands was relatively high for both bacterial
fractions compared to other studies (Riemann & Winding 2001, LaMontagne & Holden
2003, Stevens et al. 2005, Van der Gucht et al. 2005). Even though absolute numbers of
DGGE bands of free-living and particle-associated bacteria were similar our DGGE
profiles and clone libraries indicate distinct phylogenetic differences between both
bacterial fractions. The retrieved 16S rRNA gene sequences belonged to already known
freshwater clusters and are predominantly related to yet uncultured bacteria (Hiorns et al.
1997, Crump et al. 1999, Glöckner et al. 2000, Zwart et al. 2002). Clone libraries of free-
43
Kapitel II
living bacteria were dominated by members of the Actinobacteria, Bacteroidetes, and
β-Proteobacteria, whereas particle-associated bacterial communities mainly comprised
sequences of Cyanobacteria and members of the Bacteroidetes, respectively. However,
the number of sequenced clones was too low to draw general conclusions on the
quantitative proportion of distinct bacterial lineages. Furthermore, our clone libraries were
restricted to two selected time points: May (Lake Stechlin) and November 2003 (all lakes)
and, hence, may be rather limited in their phylogenetic information. The close
phylogenetic relationship of the obtained 16S rRNA gene sequences to already known
freshwater clusters suggest that the retrieved sequences most likely represent the “real”
bacterial community composition. In addition, actinobacterial clusters were distributed in a
similar manner as found by quantitative CARD-FISH analyses (Allgaier & Grossart 2006).
Members of the Bacteroidetes were found as a dominant phylogenetic group within clone
libraries of all lakes and bacterial fractions. Bacteria of the Bacteroidetes are common in
freshwater habitats but also occur in other aquatic environments (Glöckner et al. 1999,
Crump et al. 1999, Cottrell & Kirchman 2000b, Kirchman 2002, Sekiguchi et al. 2002,
Zwisler et al. 2003, Eiler & Bertilsson 2004). They are known to play an important role in
the turnover of organic matter (Cottrell & Kirchman 2000b) and are capable to degrade
polymeric substrates such as cellulose and chitin (Kirchman 2002, Jam et al. 2005).
Sequences of α- and β-Proteobacteria were predominantly found within clone libraries of
free-living bacteria. In general, α-Proteobacteria belong to the dominant bacterial group
within marine environments but also occur regularly in freshwater habitats (Glöckner et al.
1999, Rappé et al. 2000, Bouvier & del Giorgio 2002, Simon et al. 2002). The low
numbers of β-Proteobacteria in our clone libraries of particle-associated bacteria are in
contradiction to previous studies (Weiss et al. 1996, Grossart & Simon 1998, Schweitzer
et al. 2001) and may be an artefact caused by the high numbers of Cyanobacteria and
chloroplasts sequences in clone libraries of particle-associated bacteria.
Sequences of the Actinobacteria were found as the most dominant phylogenetic group
within clone libraries of free-living bacteria (Allgaier & Grossart 2006). Phylogenetic
analyses of the actinobacterial 16S rRNA gene sequences revealed several new clusters
(acSTL) and subclusters (scB 1-4, acIV C-D) within the phylogenetic tree of freshwater
Actinobacteria.
Bacteria of the γ-Proteobacteria, δ-Proteobacteria, Candidate Division OP10, Chlorobi,
Fibrobacteres, Thermomicrobia, Chloroflexi, Candidate Division TM7, and Acidobacteria
occurred only in low proportions and obviously represent minor members of the bacterial
communities in the studied lakes. Sequences of Verrucomicrobia and Planctomycetes
were randomly found in our clone libraries of particle-associated bacteria. The occurrence
44
Kapitel II
of Verrucomicrobia was described for several lakes (Zwart et al. 2003, Kolmonen et al.
2004, Eiler & Bertilsson 2004). Even though all sequences of Verrucomicrobia were found
on particles, it is uncertain whether they are exclusively adapted to these
microenvironments as it has been shown for Planctomycetes (Neef et al. 1998).
In summary, our results show clear seasonal dynamics within free-living and particleassociated bacteria of all studied lakes. Significant differences were found between both
fractions in respect to community structure and phylogenetic diversity. Bacterial
communities were strongly correlated with limnological parameters such as secchi depth,
temperature, conductivity, phosphorous, bacterial production, and phytoplankton biomass.
However, no uniform correlation-patterns between bacterial communities and the
measured limnological parameters were found for all lakes. This may indicate an
adaptation of individual bacterial communities to specific lake conditions. Phylogenetically,
almost all cloned and sequenced 16S rRNA gene fragments belonged to already known
freshwater clusters. Members of the Bacteroidetes occurred in both bacterial fractions
whereas Actinobacteria, α-, and β-Proteobacteria were mainly found within the free-living
bacteria. To obtain further informations on relationships between bacterioplankton
communities and environmental variables, more specific studies on distinct phylogenetic
lineages and/or defined seasonal periods are needed.
Acknowledgements. We thank E. Mach for technical assistance during sampling and in
the lab. R. Koschel, L. Krienitz, and P. Kasprzak are thanked for providing data on
chemistry, phytoplankton and zooplankton biomasses and community composition,
respectively. We also thank K. Pohlmann for her helpful comments on statistical analyses
and writing. This study was supported by the Leibniz foundation and by a grant of the
Studienstiftung des deutschen Volkes given to M. Allgaier.
45
Kapitel II
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TABLE 1: Limnological characteristics of the sampled lakes.
Parameter
Geographical position
Max. depth [m]
Surface area [km2]
Catchment area [km2]
Characteristics of
catchment area
Stratification (2003)
Secchi depth [m]
Trophy
pH
PO4-P [µg l-1]
DOC [mg l-1]
Bacterial numbers [106 ml-1]
Primary production [µgC l-1 d-1]
Bacterial production [µgC l-1 d-1]
Lake Stechlin
(ST)
Lake Grosse Fuchskuhle
northeast basin
southwest basin
(FNE)
(FSW)
Lake Breiter Luzin
(BL)
Lake Tiefwaren
(TW)
N 53° 10’
E 13° 02’
69.5
4.3
26.0
mixed forest
N 53° 10’
E 13° 02’
5.6
0.02
0.005
mixed forest; bog area
N 53° 20’
E 13° 28’
58.5
3.57
14.0
forest and
agriculture
June-October
1.6 - 3.8
mesotrophic
8.5 ±0.2
3 ±4
5.8 ±0.6
1.93 ±0.49
103 ±44
51 ±58
N 53° 31’
E 12° 42’
24
1.4
17.5
forest; small
town
June-September
3.1 - 8.9
eutrophic
8.3 ±0.2
2 ±1
10.6 ±5.3
2.21 ±0.47
114 ±99
35 ±37
June-October
6.5 - 10.5
oligotrophic
8.5 ±0.2
2 ±0.9
4.3 ±1.1
1.35 ±0.58
31 ±11
22 ±15
May-September
1.0 - 2.2
eutrophic
6.5 ±0.6
5 ±2
10.3 ±1.3
2.74 ±1.0
182 ±156
39 ±21
May-September
0.9 - 1.5
dystrophic
4.7 ±0.2
7 ±2
24.8 ±5.1
1.93 ±0.69
512 ±863
63 ±101
data for pH, PO4-P, DOC, bacterial numbers, primary production, and bacterial production are average values of epilimnetic
samples from April-November 2003 and March 2004; trophic status was determined following the guideline EUR 14563 EN
of the Commission of the European Communities (Premazzi & Chiaudani 1992).
TABLE 2: Significance levels (p) of ANOVA statistics of the absolute numbers of DGGE
bands of free-living and particle-associated bacteria. Significance values (p ≤0.05) are
highlighted by grey boxes.
BL vs. ST
BL vs. FNE
BL vs. FSW
BL vs. TW
ST vs. FNE
ST vs. FSW
ST vs. TW
FNE vs. FSW
FNE vs. TW
FSW vs. TW
free-living
particle-associated
0.106
≤0.001
≤0.001
≤0.001
≤0.01
≤0.001
≤0.001
0.967
0.055
0.224
≤0.01
≤0.05
≤0.001
≤0.001
0.994
0.665
≤0.001
0.387
≤0.001
≤0.05
ANOVA revealed degrees of freedom of df = 4 for both, free-living and particle-associated bacteria with F values of
F = 37.604 (free-living) and F = 24.4 (particle-associated), respectively. The abbreviations for the lakes are given in Table 1.
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TABLE 3: ANOSIM statistics of comparison of DGGE profiles of free-living and particleassociated bacteria. (A) Comparison of free-living and particle-associated bacteria of all
lakes. (B) Comparison of free-living and particle-associated bacteria within each single
lake. Significance values with p ≤0.05 are shaded grey.
A
free-living bacteria
BL vs. FNE
BL vs. FSW
BL vs. ST
BL vs. TW
FNE vs. FSW
FNE vs. ST
FNE vs. TW
FSW vs. ST
FSW vs. TW
ST vs. TW
Sample statistic (R)
Significance level (p)
0.748
0.982
0.969
0.664
0.553
0.684
0.28
0.924
0.59
0.68
≤0.01
≤0.001
≤0.001
≤0.001
≤0.001
≤0.001
≤0.001
≤0.01
≤0.001
≤0.001
0.408
0.695
0.661
0.508
0.29
0.307
0.408
0.141
0.315
0.455
≤0.001
≤0.001
≤0.001
≤0.001
≤0.001
≤0.001
≤0.001
0.052
≤0.01
≤0.001
0.462
0.245
0.475
0.459
0.289
≤0.001
0.08
≤0.001
≤0.001
≤0.001
B
BL (FL vs. PA)
FNE (FL vs. PA)
FSW (FL vs. PA)
ST (FL vs. PA)
TW (FL vs. PA)
The global test revealed a sample statistic of 0.499 with a significance level of p ≤0.001. FL: free-living; PA: particleassociated. The abbreviations for the lakes are given in Table 1.
TABLE 4: Phylogenetic classification of 16S rRNA gene sequences derived from 12 clone
libraries of free-living and particle-associated freshwater bacterial communities.
α-Proteobacteria
β-Proteobacteria
γ-Proteobacteria
δ-Proteobacteria
Actinobacteria
Bacteroidetes
Cand.Div. OP10
Planctomycetes
Verrucomicrobia
other phyla*
Cyanobacteria
Chloroplasts
ST (M)
(FL / PA)
n = 29 / 20
2/1/-/2
-/7/1
3/3
1/-/-/-/12 / 2
3 / 12
ST (N)
(FL / PA)
n = 23 / 19
-/3
3/1
-/1/13 / 4/-/1
-/1
-/1
1/1/3
-/9
BL (N)
(FL / PA)
n = 27 / 28
2/1
4/-/-/16 / -/3
1/-/2
-/2/2
2 / 17
-/3
FNE (N)
(FL / PA)
n = 20 / 20
-/1
5/1
-/1/11 / 2/2
-/-/-/1/-/- / 16
FSW (N)
(FL / PA)
n = 20 / 25
2/-/-/-/7/9/1
-/-/-/-/-/2 / 24
TW (N)
(FL / PA)
n = 25 / 21
6/2/1/-/10 / 3/6
-/-/-/1
3/2
-/5
-/7
∑
(FL / PA)
n = 144 / 133
12 / 5
15 / 2
1/2
2/64 / 1
21 / 15
2/1
-/3
-/2
7/4
15 / 27
5 / 71
* Chlorobi, Fibrobacteres, Thermomicrobia, Chloroflexi, Cand.Div. TM7, Acidobacteria (see also phylogenetic trees);
(M)
(N)
FL: free-living bacteria; PA: particle-associated bacteria; : samples from May 2003; : samples from November 2003.
52
Kapitel II
TABLE 5: Results of NMS ordinations and Pearson’s product moment correlations of
DGGE profiles of free-living (A) and particle-associated (B) bacterial communities and
limnological parameters. Pearson’s r values ≥0.7 are given for the three significant
ordination axes. Limnological parameters with correlations r ≤0.7 were excluded from this
table. The first column shows the results of the comprehensive analyses of epilimnetic
samples of all lakes.
A
B
(1)
(2)
free-living
Secchi depth
Temperature
O2 [mg l-1]
pH
Conductivity
Total N
Total P
DOC
BPP (total)
PP (total)
PP (≤3.0 ≥0.2µm)
Phytoplankton
particle-associated
Secchi depth
Temperature
Conductivity
Total P
PP (≤3.0 ≥0.2µm)
Zooplankton
Phytoplankton
Epilimnion
(all lakes)
BL
FNE
FSW
ST
TW
0.785 (2)
-
-0.877 (1)
0.895 (1)
-0.705 (1)
- 0.738 (2)
-0.800 (1)
- 0.773 (2)
-0.818 (1)
-
-0.846 (1)
0.772 (1)
0.797 (1)
-
0.704 (1)
-0.787 (1)
0.790 (3)
-0.720 (3)
-
-0.747 (2)
0.713 (2)
-0.722 (2)
0.701 (3)
-
-
-0.846 (3)
-0.831 (3)
-
-
- 0.757 (3)
-0.725 (1)
0.821 (1)
-0.745 (1)
-0.750 (1)
-
-
(3)
, ,
correlations to ordination axes 1, 2, and 3, respectively; PA particle-associated; DOC dissolved organic carbon;
BPP bacterial protein production; PP primary production. The abbreviations for the lakes are given in Table 1.
particle-associated
ST
D
AP
R
M
A
JU Y
N
JU
L
AU
SE G
P
O
C
N T
O
D V
EC
M
A
ST R
D
ST
D
AP
R
M
AY
JU
N
JU
L
AU
G
SE
P
O
C
NT
O
D V
EC
M
A
ST R
D
free-living
STD: standard
FIGURE 1: Inverted DGGE profiles of amplified 16S rRNA gene fragments of free-living
and particle-associated bacteria of the NE compartment of Lake Grosse Fuchskuhle
between April 2003 and March 2004.
53
Kapitel II
A
free-living
BL
FNE
FSW
ST
TW
particle-associated
Axis 2
pH
stress = 21.33
stress = 19.34
Axis 1
B
BL
SEP
AUG
NOV
FEB
FNE
APR
AUG
AUG
NOV
JUN
FSW
APR
AUG
JUL SEP
DEC
JUL
MAR
MAR
OCT
MAY
MAY
SEP
APR
JUN
MAY
MAR
JUN
NOV
JUL
APR
JUL
NOV
JUN
MAR
OCT
NOV
APR
APR
JUL NOV
MAR
SEP
MAY
MAR
JUN
OCT
SEP
MAY
FEB
JUN
DEC
JUL
SEP
Axis 2
MAY
AUG
AUG
OCT
stress = 15.61
stress = 9.12
ST
APR
stress = 14.02
TW
JUN
MAY
APR
MAY
NOV
JUN
DEC AUG
JUN
OCT
APR
MAY
FEB
FEB
JUL
MAR
MAR
AUG
JUL NOV
OCT
DEC
MAR
OCT NOV
AUG
FEB
AUG
NOV
OCT
DEC
FEB
DEC
MAY
SEP
SEP
JUL
APR
JUN
JUL
MAR
stress = 13.35
stress = 12.43
Axis 1
FIGURE 2: Results of NMS ordinations of DGGE banding patterns of free-living and
particle-associated bacterial communities of the four studied lakes. The results of the first
two ordination axes are given. (A) Results of comprehensive NMS analyses of all lakes.
Within NMS plot of free-living bacteria pH is displayed as strongly correlated limnological
variable. (B) NMS plots of the single lakes. Open symbols: free-living bacteria; solid
symbols: particle-associated bacteria. The abbreviations for the lakes are given in
Table 1.
54
Kapitel II
Lake Tiefwaren clone TW11-8 (DQ501378)
Antarctic bacterium R-7724 (AJ440986)
Lake Breiter Luzin clone BL11-26 (DQ501292)
Rhodoferax ferrireducens T118 (AF435948)
uncultured beta proteobacterium SW72 (AJ575699)
58
Lake Grosse Fuchskuhle (NE) clone FNE11-27 (DQ501307)
particle-associated
Lake Stechlin clone ST11-2 (DQ501330)
uncultured bacterium L013.11 (AF358003)
uncultured bacterium (AY662010)
100
uncultured beta proteobacterium (AY622262)
beta proteobacterium F1021 (AF236005)
76
unidentified bacterium LWSR-25 (AY345542)
uncultured beta proteobacterium TLM05 (AF534429)
Pavin Lake clone P38.4 (AY752086)
100
uncultured bacterium 220ds20 (AY212668)
100
65
uncultured beta proteobacterium 08 (AF361193)
100
uncultured bacterium oc35 (AY491578)
beta proteobacterium MWH-MoK1 (AJ550652)
beta proteobacterium MWH-JaW7 (AJ550658)
100
beta proteobacterium MWH-CaK1 (AJ550667)
72
Polynucleobacter necessarius(T) (X93019)
uncultured freshwater bacterium LD28 (Z99999)
100
75
unidentified bacterium GLSR-10 (AY345583)
100
gamma proteobacterium HTB082 (AB010842)
uncultured bacterium p-261-05 (AF371859)
100
100 Lake Tiefwaren clone TW11-18 (DQ501358)
Methylobacter psychrophilus(T) (AF152597)
73
uncultured bacterium FukuN13 (AJ290055)
uncultured freshwater bacterium LD12 (Z99997)
uncultured bacterium S9JU-44 (AB154321)
100
100
Caedibacter caryophila str. 221 (X71837)
74
99
uncultured alpha proteobacterium GWS-K33 (AY515452)
100
Rhodobacter sphaeroides IL106 (D16424)
Lake Tiefaren clone TW11-20 (DQ501360)
84
uncultured eubacterium GKS59 (AJ224988)
100
alpha proteobacterium A0902 (AF236003)
100
alpha proteobacterium AP-9-1 (AY145547)
100
100
alpha proteobacterium AP-6 (AY145544)
uncultured alpha proteobacterium SW32 (AJ575704)
100 uncultured alpha proteobacterium SW22 (AJ575705)
Lake Grosse Fuchskuhle (SW) clone FSW11-5 (DQ501324)
100
uncultured delta proteobacterium JG37-AG-118 (AG518799)
100
uncultured bacterium Q3-6C17 (AY048892)
89
uncultured delta proteobacterium S15B-MN10 (AJ583187)
100
Syntrophus sp. (AJ133796)
A
β-Proteobacteria
γ-Proteobacteria
α-Proteobacteria
δ-Proteobacteria
0.10
FIGURE 3: Maximum likelihood trees of cloned and sequenced 16S rRNA gene
fragments of free-living and particle-associated bacteria. Solid lines indicate sequences
that were included in the primary analyses (sequences ≥1400 nucleotides), whereas
dotted lines indicate partial sequences (≤1400 nucleotides) added by maximum parsimony
criteria. Sequences of this study are shown in bold letters. Sequences of particleassociated bacteria are marked by grey boxes. GenBank accession numbers are given in
parentheses. The scale bar corresponds to 10 base substitutions per 100 nucleotide
positions. Bootstrap values at the main branching points are given. (A) Proteobacteria;
(B) Bacteroidetes; (C) overall phylogenetic tree of 16S rRNA gene sequences which occur
only in low numbers in the clone libraries.
55
Kapitel II
85
100
96
69
100
0.10
56
Bacteroidetes
Sphingobacteria
67
63
99
Bacteroidetes
84
Flavobacteria
B
uncultured bacterium BA2 (AF087043)
uncultured Cytophagales bacterium PRD01a005B (AF289153)
uncultured Bacteroidetes clone Flo-53 (AY684349)
uncultured bacterium NB-12 (AB117716)
100
uncultured Cytophagales bacterium O6 (AF361205)
99
100
64
uncultured bacterium WCHB1-32 (AF050543)
uncultured bacterium L15 (AY444993)
Uncultured bacterium clone BSV85 (AJ229229)
uncultured Lake Michigan sediment bacterium LMBA49 (AF320926)
uncultured Cytophaga Sva1038 (AJ240979)
98
99
uncultured bacterium PK91 (AY555796)
Bacteroidetes bacterium LC9 (AY337604)
Cytophagales str. MBIC 4147 (AB022889)
100
Sphingobacterium like sp. PC1.9 (X89912)
uncultured Sphingobacteriaceae bacterium LiUU-5-303 (AY509378)
uncultured bacterium oc26 (AY491570)
100
Sphingobacterium comitans (X91814)
99
uncultured Bacteroidetes bacterium LiUU-11-161 (AY509379)
75
uncultured bacterium TLM10 (AF534434)
100
91
uncultured bacterium D136 (AY274142)
Sep Reservoir clone S4.12 (AY752114)
uncultured bacterium TLM09 (AF534433)
uncultured bacterium FukuS59 (AJ290042)
uncultured Bacteroidetes bacterium SW36 (AJ575722)
100
uncultured Bacteroidetes bacterium BIti15 (AJ318185)
53
100
uncultured bacteriumGKS2-217 (AJ290034)
uncultured bacterium s22 (AY171331)
100
uncultured Bacteroidetes bacterium NE60 (AJ575728)
98
Flectobacillus speluncae GWF20C (AY065625)
100
unidentified bacterium GLBR-3 (AY345577)
Flexibacter roseolus IFO 16707 (AB078063)
Thermonema rossianum SC-1 (Y08957)
100
uncultured Fibrobacteres bacterium LiUU-9-330 (AY509521)
uncultured sludge bacterium A12b (AF234699)
uncultured bacterium KD4-114 (AY218625)
uncultured bacterium #0319-6E22 (AF234130)
uncultured soil bacterium S1220 (AF507716)
Chlorobi
Fibrobacteres
Kapitel II
C
79
100
84
91
100
100
100
63
99
74
uncultured soil bacterium 12-1 (AY326633)
uncultured bacterium sipK52 (AJ307949)
uncultured Crater Lake bacterium CL500-11 (AF316759)
100
uncultured bacterium SJA-35 (AJ009460)
uncultured bacterium C2-12 (AJ387902)
uncultured bacterium KD4-96 (AY218649)
100
uncultured Chloroflexi bacterium Gitt-GS-136 (AJ582210)
uncultured bacterium HTH4 (AF418964)
100
green non-sulfur bacterium B1-5 (AB079645)
uncultured bacterium TM7LH20 (AF269006)
100
metal-contaminated soil clone K (AF145815)
uncultured bacterium 177up (AY212628)
uncultured bacterium HTB7 (AF418946)
uncultured bacterium CH21 (AJ271047)
planctomycetes str. 467 (AJ231174)
uncultured bacterium Dpcom 231 (AY453243)
100
Planctomycetes sp. Schlesner 642 (X81950)
uncultured bacterium HTA2 (AF418943)
100
100
uncultured Verrucomicrobium DEV005 (AJ401105)
100
uncultured Verrucomicrobia bacterium SW59 (AJ575730)
uncultured Acidobacteria bacterium S15A-MN55 (AJ534690)
Geothrix fermentansT (U41563)
100
uncultured epsilon proteobacterium FTLM50 (AF529126)
0.10
57
Thermomicrobia
Chloroflexi
Cand.Div TM7
CandDiv. OP10
Planctomycetes
Verrucomicrobia
Acidobacteria
III
Diversity and seasonal dynamics of
Actinobacteria populations in four
lakes in Northeastern Germany
Kapitel III
Diversity and dynamics of freshwater Actinobacteria
61
Kapitel III
62
Kapitel III
63
Kapitel III
64
Kapitel III
65
Kapitel III
66
Kapitel III
67
Kapitel III
68
Kapitel III
69
IV
Intra- and inter-lake variability of
free-living and particle-associated
Actinobacteria populations
Kapitel IV
Variability of freshwater Actinobacteria populations
submitted to Environmental Microbiology (June, 2006)
Intra- and inter-lake variability of free-living and particle-associated
Martin Allgaier1, Sarah Brückner1, Elke Jaspers2, and Hans-Peter Grossart1*
1
Leibniz-Institute of Freshwater Ecology and Inland Fisheries; Department Limnology of
Stratified Lakes; Alte Fischerhütte 2; D-16775 Stechlin-Neuglobsow; Germany
2
mikroLogos; Augustastr. 58; D-47198 Duisburg; Germany
Running title: Variability of freshwater Actinobacteria communities
Key words:
Actinobacteria, free-living and particle-associated, phylogenetic diversity,
seasonal dynamics, DGGE
73
Kapitel IV
Summary
We analysed the inter- and intra-lake variability of free-living and particle-associated
freshwater Actinobacteria populations in four limnological different lakes of the
Mecklenburg
Lake
District,
Northeastern
Germany.
Denaturing
gradient
gel
electrophoresis (DGGE) specific for Actinobacteria was used to investigate phylogenetic
differences and seasonal dynamics of actinobacterial communities in the epilimnion of all
lakes (inter-lake variability) and to assess differences between Actinobacteria populations
of the epi-, meta-, and hypolimnion of a single lake (intra-lake variability), respectively.
DGGE banding patterns showed significant differences between free-living and particleassociated Actinobacteria populations within all analysed samples. Phylogenetic
inferences of 16S rRNA gene sequences suggest that particular members of particleassociated Actinobacteria were exclusively affiliated to certain actinobacterial lineages.
Non-metric multidimensional scaling (NMS) ordination analyses revealed distinct interand intra-lake differences between Actinobacteria populations of the studied lakes and
water layers with obvious seasonal changes. In an attempt to relate these changes to
environmental variables, several strong correlations were found between Actinobacteria
and
limnological
variables,
such
as
conductivity,
total
phosphorous,
alkalinity,
phytoplankton biomass, primary production, or ectoenzyme activities. However, no
uniform correlation-patterns were found between the lakes and water layers indicating a
potential
adaptation
of
distinct
Actinobacteria
communities
to
their
respective
environment.
Introduction
Bacterioplankton communities are known to play a key role in biogeochemical processes
of aquatic ecosystems (Cotner and Biddanda, 2002). Several studies on freshwater
bacterioplankton communities indicated a core group of bacterial phylotypes which
commonly occur in diverse limnetic habitats (Zwart et al., 2002). Recently, Actinobacteria
were found to be one of the most dominant fraction within freshwater bacterioplankton
communities (Glöckner et al., 2000; Van der Gucht et al., 2005; Warnecke et al., 2005;
Allgaier and Grossart, 2006). Actinobacteria are well known from soil environments
(Goodfellow and Williams, 1983; Rheims et al., 1999) but it has been shown that they are
also part of the autochthonous bacterioplankton of different aquatic habitats (Warnecke et
al., 2004). Phylogenetic analyses based on the comparison of 16S rRNA gene sequences
revealed distinct freshwater actinobacterial lineages which were clearly separated from
Actinobacteria of other environments (Warnecke et al., 2004; Allgaier and Grossart,
74
Kapitel IV
2006). The majority of the recently determined freshwater actinobacterial sequences
belong to yet uncultured bacteria. Due to the lack of isolates almost nothing is known
about their physiological and ecological role. Results from grazing experiments indicated
that some aquatic Actinobacteria are better protected from protistan grazing than other
members of the heterotrophic bacterioplankton (Pernthaler et al., 2001; Jezbera et al.,
2005). Furthermore, solar UV radiation (Warnecke et al., 2005), phytoplankton-derived
dissolved organic materials (DOM) (Stepanauskas et al., 2003), and pH (Lindtsröm et al.,
2005) were proposed to affect actinobacterial community structure. Distinct relationships
between Actinobacteria and particular environmental parameters are supported by
pronounced seasonal dynamics of various freshwater Actinobacteria communities
(Glöckner et al., 2000; Allgaier and Grossart, 2006).
The majority of the currently known freshwater Actinobacteria were found within the freeliving bacterioplankton and seem to be less abundant on particles (Allgaier and Grossart,
2006; Allgaier and Grossart, unpublished). Our present knowledge on the abundance and
phylogenetic diversity of particle-associated Actinobacteria is rather scarce. So far, no
study exists which systematically investigate differences between free-living and particleassociated freshwater Actinobacteria in detail. We therefore examined the phylogenetic
differences of free-living and particle-associated Actinobacteria populations by using
DGGE and clone libraries of 16S rRNA gene sequences. The observed phylogenetic
patterns were statistically related to various limnological parameters to receive closer
informations
on
microenvironment.
potential
adaptation
of
Because
quantitative
Actinobacteria
analyses
of
to
their
freshwater
respective
Actinobacteria
populations indicated differences between Actinobacteria communities of different habitats
(Warnecke et al., 2005; Allgaier and Grossart, 2006) we characterized Actinobacteria
populations of several lakes and water layers to obtain further informations on the interand intra-lake variability of freshwater Actinobacteria populations.
Results
Analyses of DGGE banding patterns of free-living and particle-associated
DGGE banding patterns of free-living and particle-associated Actinobacteria revealed
significant differences (p ≤ 0.001) between both actinobacterial fractions within each
single lake (Figure 1). The absolute numbers of DGGE bands varied between 4.3 ±2.6
and 17.4 ±3.6 for free-living Actinobacteria and between 3 ±1.6 and 13.1 ±6.3 for the
particle-associated fractions for each lake, respectively (Table 1). Both, free-living and
75
Kapitel IV
particle-associated Actinobacteria showed relatively high diversity determined by the
number of DGGE bands, however, with distinct differences in their respective banding
patterns. Due to problems with DNA extraction and PCR amplification of 16S rRNA gene
fragments no DGGE results were available for free-living Actinobacteria from September
2003 (Lake Stechlin) and for particle-associated Actinobacteria from August, October, and
November 2003 (NE compartment of Lake Grosse Fuchskuhle), and from October and
December 2003 (SW compartment of Lake Grosse Fuchskuhle), respectively.
As indicated by the phylogenetic affiliations of actinobacterial 16S rRNA gene sequences
retrieved from two clone libraries of Lake Tiefwaren, distinct phylogenetic differences
occurred between free-living and particle-associated Actinobacteria (Figure 2). The
majority of the 28 sequenced clones of free-living Actinobacteria belonged to the
freshwater cluster acI, whereas 5 of the 11 sequences of particle-associated
Actinobacteria were phylogenetically affiliated to Mycobacteriaceae, Microsphaera, or
Microthrix (Figure 2). Three sequences obtained from the clone libraries belonged to the
Verrucomicrobia and, thus, not to the class Actinobacteria (Figure 2).
Comparison of Actinobacteria populations of different lakes and water layers
The inter- and intra-lake variability of freshwater Actinobacteria populations was
investigated by comparison of DGGE profiles of Actinobacteria from all studied lakes and
water layers. Studies of inter-lake variability compared epilimnetic Actinobacteria
populations of all lakes whereas those of the intra-lake variability had calculated only for
epi-, meta-, and hypolimnion of Lake Stechlin. Non-metric multidimensional scaling (NMS)
analyses of the DGGE banding patterns of free-living and particle-associated
Actinobacteria revealed significant differences between epilimnetic Actinobacteria
populations of all lakes and actinobacterial fractions (Figure 3). The formation of lakespecific clusters within NMS analyses was statistically significant as determined by
ANOSIM (Table 2 A). In general, samples of Lake Breiter Luzin, Lake Stechlin, and Lake
Tiefwaren were more similar to each other than to samples of the two compartments (NE
and SW) of Lake Grosse Fuchskuhle (Figure 3).
The comparison of DGGE profiles of the epi-, meta-, and hypolimnion of Lake Stechlin
indicated significant differences between Actinobacteria populations in the three water
layers for both actinobacterial fractions (Figure 4, Table 2 B). As depicted in the NMS
ordination plots epi- and hypolimnetic Actinobacteria populations were more similar to
each other than to Actinobacteria of the metalimnion (Figure 4).
All free-living and particle-associated Actinobacteria communities showed obvious
seasonal changes as indicated by the formation of distinct season-specific clusters within
76
Kapitel IV
NMS plots (Figure 1 and 4). For example, in the hypolimnetic samples of Lake Stechlin
two clearly separated seasonal clusters occurred in both actinobacterial fractions which
represented fall/winter and spring/summer, respectively (Figure 4). However, seasonspecific clusters varied between lakes, water layers, and actinobacterial fractions and thus
no consistent pattern could be observed.
Statistical relationships between diversity of Actinobacteria populations and
environmental variables
Because of the non-normal distribution of the species data non-metric multidimensional
scaling (NMS) analyses and Pearson’s product moment correlations were performed to
identify potential relationships between DGGE profiles of the Actinobacteria and the
measured limnological parameters. Statistical analyses for the combined data sets of freeliving and particle-associated Actinobacteria of each individual lake revealed only weak
correlations (Pearson’s r ≤ 0.7, data not shown). However, separate analyses of free-living
and
particle-associated
Actinobacteria
exhibited
several
correlations
between
Actinobacteria populations and limnological parameters, e.g. temperature, conductivity,
PO4-P, silicate, primary production, bacterial production, and protease activity (Table 3).
High numbers of strong correlations to biological parameters (e.g. primary production,
bacterial production, and ectoenzyme activities) were found especially for free-living and
particle-associated Actinobacteria of Lake Tiefwaren and the NE compartment of Lake
Grosse Fuchskuhle, respectively (Table 3). Although comprehensive analyses of freeliving and particle-associated Actinobacteria of epilimnetic samples of all lakes revealed
strong correlations to pH, conductivity, alkalinity, total and dissolved organic carbon (TOC,
DOC), and iron, no consistent correlation-patterns were found between distinct
environmental variables and Actinobacteria populations of any single lake (Table 3). As
indicated by the arrows in the NMS ordination plots of epilimnetic samples of all lakes,
free-living Actinobacteria of Lake Breiter Luzin and Lake Tiefwaren were strongly
influenced by pH, conductivity, and alkalinity (Figure 3). Particle-associated Actinobacteria
of the SW compartment of Lake Grosse Fuchskuhle, Lake Breiter Luzin, and Lake
Stechlin were influenced by pH, alkalinity, iron, TOC, and DOC, respectively (Figure 3).
Discussion
Application and evaluation of Actinobacteria specific primers for DGGE
This study was focused on the phylogenetic diversity and seasonal dynamics of
Actinobacteria populations in four limnological different lakes of the Mecklenburg Lake
77
Kapitel IV
District, Northeastern Germany. We separated between free-living and particle-associated
Actinobacteria communities to obtain a higher phylogenetic resolution and to receive more
detailed informations on potential adaptations of distinct actinobacterial lineages to
specific microenvironments. For characterization of the Actinobacteria communities we
applied DGGE of PCR amplified 16S rRNA gene fragments and NMS analyses. We used
a primer set specific for the class Actinobacteria (HGC236F/HGC664R, Glöckner et al.,
2000) and optimized it for DGGE. As it has been shown previously DGGE comprises
several potential limitations such as selective PCR amplification of specific bacterial
lineages (Suzuki and Giovannoni, 1996; Wintzingerode et al., 1997), formation of
heteroduplex and chimeric molecules (Liesack et al., 1991), or the occurrence of bacteria
with multiple 16S rRNA operons (Cilia et al., 1996; Klappenbach et al., 2000). Because
the primers HGC236F and HGC664R had never been used for DGGE analyses before we
compared their phylogenetic resolution with a second actinobacterial primer set published
elsewhere (GC-517f/AB1165r, Gich et al., 2005). The direct comparison of both primer
sets revealed a significant higher phylogenetic resolution for primers HGC236F and
HGC664R (12 DGGE bands) compared to the primer pair GC-517f/AB1165r (3 DGGE
bands). Sequencing of several DGGE bands confirmed the specificity of both primer sets
for Actinobacteria (data not shown). However, our clone libraries obtained using the
primers
HGC236F
and
HGC664R
revealed
3
sequences
belonging
to
the
Verrucomicrobia. This artefact most likely derived from the fact that the primer HGC236F
has also the potential to bind to particular verrucomicrobial 16S rRNA gene sequences.
So far, we were not able to circumvent this bias but we estimated it of lower importance
because the vast majority of the sequenced DGGE bands exclusively belonged to the
Actinobacteria.
Differences between free-living and particle-associated Actinobacteria communities
Our DGGE analyses revealed significant differences between free-living and particleassociated Actinobacteria of all lakes and water layers indicating a potential adaptation of
distinct phylotypes to their respective microenvironment. This suggestion is supported by
our statistical analyses which showed different correlation-patterns between free-living
and particle-associated actinobacterial communities (Table 3). As it has been shown
previously distinct bacterial communities can develop on particles (DeLong et al., 1993;
Crump et al., 1999; Fandino et al., 2001; Riemann and Winding, 2001). To our knowledge
no study exists which has specifically examined the abundance and phylogeny of particleassociated Actinobacteria. Semi-quantitative microscopic examinations of particles in
78
Kapitel IV
combination with CARD-FISH, however, indicated generally low abundances of particleassociated Actinobacteria in the studied lakes (Allgaier and Grossart, unpublished).
The phylogenetic diversity observed within DGGE banding patterns of particle-associated
Actinobacteria was surprisingly high compared to a previous study on bacterial community
structure of the four studied lakes, where Actinobacteria occur almost exclusively in the
free-living stage (Allgaier and Grossart, 2006). These discrepancies are most likely linked
to methodological artefacts, such as the application of two different primer sets in both
studies (universal primers versus Actinobacteria specific primers), the low numbers of
sequenced clones, or the preferential amplification of distinct phylotypes during PCR.
Nevertheless, our results clearly show that the application of specific primers is more
suitable to investigate the phylogenetic diversity of a specific bacterial lineage than
universal primer sets. Specific primers reveal a much higher phylogenetic resolution of
distinct bacterial groups and enable the study of less abundant bacteria which would be
not
detected
by
PCR
using
universal
primers
only
(e.g.
particle-associated
Actinobacteria).
The differences found between free-living and particle-associated Actinobacteria
populations within our DGGE analyses were supported by two clone libraries of the
November 2003 sample of Lake Tiefwaren which indicated particular phylogenetic
differences between both actinobacterial fractions. For example, sequences belonging to
the Mycobacteriaceae, Microsphaera, Sporichthya, or Microthrix were predominantly
derived from particle-associated Actinobacteria, whereas members of the acI cluster were
mainly free-living (Figure 2). We are aware of the fact that the number of sequenced
clones was too low to obtain quantitative data on the phylogenetic distribution of
Actinobacteria. However, similar investigations on Lake Kinneret bacterioplankton
supported our results that free-living and particle-associated Actinobacteria may show
distinct phylogenetic affiliations to different actinobacterial lineages (Allgaier and Grossart,
in prep.).
Inter- and intra-lake differences of freshwater Actinobacteria populations
The significant formation of lake-specific clusters within NMS ordination analyses
indicated clear differences between actinobacterial communities of all lakes. A previous
study on the phylogenetic diversity of the Actinobacteria communities had shown that
Actinobacteria of the studied lakes belong to similar phylogenetic lineages, such as the
freshwater clusters acI, acII, acIV, or acSTL (Allgaier and Grossart, 2006). Because we
did not sequence DGGE bands in this study we are not able to draw any convincing
conclusions which actinobacterial lineages are represented by particular bands. We, thus,
79
Kapitel IV
speculate that the high diversity found within DGGE banding patterns provide more
detailed insights into the intra-cluster diversity of already known actinobacterial lineages.
The occurrence of intra-cluster differences between Actinobacteria of the studied lakes
has been shown previously by the presence of lake-specific clusters (e.g. scB1-4)
(Allgaier and Grossart, 2006).
Differences between bacterial communities of various freshwater habitats have been
shown previously including the here studied lakes (e.g. Lindström, 2000; Van der Gucht et
al., 2005; Allgaier and Grossart, submitted) and are most likely derived from the
adaptation of bacterioplankton communities to their respective environment (Kritzberg et
al., 2006). In addition, in Lake Stechlin pronounced intra-lake differences occur between
actinobacterial communities of the epi-, meta-, and hypolimnion. As shown by the NMS
analyses of the DGGE profiles distinct Actinobacteria populations developed in the three
water layers. Specific limnological conditions in the metalimnion (e.g. high O2
concentrations, accumulation of organic nutrients, or increased primary production) may
lead to the development of separate actinobacterial communities which were significantly
different from those of the epi- and hypolimnion. Due to the lack of detailed measurements
of limnological parameters in the metalimnion of Lake Stechlin we were not able to obtain
closer informations on potential relationships between the respective Actinobacteria
populations and changes in distinct limnological variables.
Seasonal
dynamics
and
ecological
potential
of
freshwater
Actinobacteria
populations
Actinobacteria populations of the studied lakes showed distinct seasonal changes in their
abundance with maxima in late spring and fall (Allgaier and Grossart, 2006). Similar
seasonal variations were found for Actinobacteria in Lake Gossenköllesee (Glöckner et
al., 2000). However, our recent knowledge on seasonal dynamics in respect to changes in
phylogenetic diversity of distinct Actinobacteria populations is rather scarce (Newton et al.,
2006). Our results strongly suggest that there are also seasonal variations in the
phylogenetic diversity of freshwater Actinobacteria as indicated by the formation of
season-specific clusters within NMS analyses. Seasonal changes of aquatic bacterial
communities are commonplace and may be linked to numerous environmental factors,
such as phytoplankton succession, protozoan grazing, or viral lysis (Van Hannen et al.,
1999; Hahn and Höfle, 1999; Brussaard et al., 2005; Newton et al., 2006). For
Actinobacteria it has been proposed that phytoplankton-derived dissolved organic
materials (DOM) (Stepanauskas et al., 2003), pH (Lindtsröm et al., 2005), or grazing
(Pernthaler et al., 2001; Jezbera et al., 2005; Newton et al., 2006) affect changes in their
80
Kapitel IV
community structure. Our Pearson’s product moment correlations revealed several strong
correlations between physical, chemical, and biological parameters and the respective
Actinobacteria communities (Table 3). The general inconsistency of the correlation patters
between the lakes and actinobacterial fractions may indicate the development of distinct
Actinobacteria populations depending on the respective environmental conditions. The
close phylogenetic relationship between the actinobacterial communities of the studied
lakes (Allgaier and Grossart, 2006), thus, leads to the suggestion that Actinobacteria of
similar phylogenetic affiliations may inhabit different ecological niches (Moore et al., 1998;
Jaspers and Overmann, 2004). To elucidate the significance of distinct relationships
between Actinobacteria and limnological variables further studies are necessary.
In summary, our results showed significant differences between free-living and particleassociated Actinobacteria communities. Phylogenetic analyses of 16S rRNA gene
sequences suggest that particular members of particle-associated Actinobacteria were
specifically affiliated to certain actinobacterial lineages. As indicated by our DGGE and
NMS analyses, free-living and particle-associated Actinobacteria showed distinct seasonal
changes within both actinobacterial fractions. The inter- and intra-lake comparison of
Actinobacteria populations revealed distinct differences between Actinobacteria of the
studied lakes and water layers. All actinobacterial communities were strongly correlated to
certain limnological parameters, such as conductivity, total phosphorous, alkalinity,
phytoplankton biomass, primary production, and ectoenzyme activities. However, no
consistent correlation-patterns were found between the lakes and actinobacterial
fractions. This may indicate that Actinobacteria of different lakes or water layers are
adapted to their respective environment and may inhabit different ecological niches.
Experimental Procedures
Lake description and sampling
Four lakes of the Mecklenburg Lake District (Northeastern Germany) were selected for
this comparative study on freshwater Actinobacteria populations: Lake Breiter Luzin, Lake
Stechlin, Lake Grosse Fuchskuhle, and Lake Tiefwaren. All lakes show different physical,
chemical, and biological properties with trophic states ranging from oligotrophic to
eutrophic and dystrophic, respectively. The main limnological characteristics of the lakes
are summarized in Table 4. Lake Grosse Fuchskuhle was artificially divided into four
compartments by large plastic curtains for biomanipulation experiments in 1990
(Kasprzak, 1993; Koschel, 1995). In this study, only the northeast (NE) and the southwest
81
Kapitel IV
(SW) compartments were investigated because of their great limnological differences (Bittl
and Babenzien, 1996; Hehmann et al., 2001). At the time of this study, Lake Tiefwaren
was restored by a combination of aluminate and calcium hydroxide precipitation (Koschel
et al., 2006). More detailed descriptions on morphometry, limnology, and microbiology of
the studied lakes are published in Allgaier and Grossart (2006).
All lakes were sampled monthly between April 2003 and March 2004, except during ice
coverage in December (Lake Breiter Luzin), January (all lakes), and February (Lake
Grosse Fuchskuhle). Water samples of 1 litre were taken at the deepest points of the
lakes using a Ruttner sampler. Depending on the thermal stratification, epilimnetic
samples were obtained by taking sub-samples in 0, 5, and 10 m depth (April-May and
October-March) or in 0 and 5 m depth (June-September) in Lake Stechlin, Lake Breiter
Luzin, and Lake Tiefwaren. The sub-samples were mixed in sterile glass flasks in equal
shares. The epilimnetic samples of the NE and SW compartments of Lake Grosse
Fuchskuhle were taken as mixed samples from 0 and 2 m depth (April and OctoberMarch) or as surface samples (May-September) due to their shallow epilimnion. For the
investigation of the intra-lake variability of Actinobacteria communities additionally
metalimnetic (7-15 m) and hypolimnetic (40 m) samples were taken from Lake Stechlin.
The metalimnion was only sampled during stratification of the lake between June and
October 2003. Incubations for measurements of primary production and bacterial
production were carried out under in situ conditions during sampling. Water samples for
molecular and chemical analyses were taken to the lab in dark cooling boxes and
processed for further analyses within 2-4 h after sampling.
Measurement of limnological variables
To elucidate specificity and ecological adaptations of Actinobacteria populations a set of
various physical, chemical, and biological parameters was determined. The following
physico-chemical parameters were determined by electrode measurements: temperature
(WTW Oxi 197-S), pH (WTW pH 197), conductivity (WTW LF 197-S), oxygen
concentration, and oxygen saturation (both WTW Oxi 197-S). Alkalinity down to a pH of
4.3 was determined by titration with 1N hydrochloric acid using a Metrohm 686
Titriprocessor (Metrohm). Secchi depth was measured using a secchi disk (d = 0.25 m).
The chemical parameters comprised of: total organic carbon (TOC), dissolved organic
carbon (DOC), total nitrogen, NO2-N, NO3-N, NH4-N, total phosphorous, PO4-P, calcium,
iron, silicate, and calcium carbonate. TOC and DOC were analyzed using a Shimadzu
total organic carbon analyzer TOC-5050 by standard methods as described in Wetzel and
Likens (1991). Inorganic nutrients, such as the different nitrogen and phosphorous
82
Kapitel IV
species and calcium, iron, and silicate were analyzed photometrically by a Tecator FIAstar
5010 Analyzer following standard protocols (Strickland and Parsons, 1978; Wetzel and
Likens, 1991) and the manufacturer’s instructions. Calcium carbonate was determined
indirectly by transforming calcium carbonate into CO2 by acidification with 10 %
hydrochloric acid. The resulting CO2 was measured by a Saxon Junkalor Infralyt 1211 and
subsequently recalculated into calcium carbonate concentrations.
The biological parameters comprised of: total bacterial numbers, ectoenzyme activity of
β-D-glucosidase and protease, bacterial protein production (BPP), primary production
(PP), zooplankton abundances (only crustaceans), and phytoplankton community
structure and biomasses. Bacterial numbers were determined by epifluorescence
microscopy after staining of the bacterial cells with 4,6-diamidino-2-phenylindole (DAPI;
1mg/100ml) on a 0.2 µm Nuclepore polycarbonate membrane. Hydrolytic ectoenzyme
activities were determined using the fluorescent substrate analogues L-leucinemethylcoumarinyl amide (leu-MCA) and methyl-umbelliferyl-β-D-glucoside (β-D-glc-MUF)
(Hoppe, 1983). BPP and PP were determined by
Azam, 1989) and H
CO3-
14
14
C-leucine incorporation (Simon and
uptake (Wetzel and Likens, 1991), respectively. Both, BPP and
PP were determined for different size fractions obtained by filtration. BPP was determined
for the fractions ≥ 5.0 µm (particle-associated bacteria), ≤ 5.0 ≥ 0.2 µm (free-living
bacteria), and ≥ 0.2 µm (total bacteria), and PP for the fractions ≥ 0.6 µm (total), ≤ 20.0
≥ 0.6 µm, ≥ 3.0 µm, and ≤ 3.0 ≥ 0.2 µm. Phytoplankton as well as zooplankton community
structure were determined microscopically. Biomasses were determined with a calibrated
imaging analysis system (Analysis).
DNA extraction and PCR amplification of 16S rRNA gene fragments
Particle-associated and free-living Actinobacteria were separated by sequential filtration of
the water samples throughout 5.0 and 0.2 µm Nuclepore polycarbonate filters,
respectively (see also Allgaier and Grossart, 2006). Extraction of genomic DNA was
performed, using a standard protocol with phenol/chloroform/isoamylalcohol, SDS,
polyvinylpyrrolidone, and zirconium beads as described previously (Allgaier and Grossart,
2006).
For DGGE analysis, a 428 bp fragment of the 16S rRNA gene was amplified using a
primer pair specific for the class Actinobacteria: HGC236F: 5’ – AAC AAG CTG ATA GGC
CGC – 3’ and HGC664R: 5’ – AGG AAT TCC AGT CTC CCC – 3’ (Glöckner et al., 2000).
At the 5’-end of the primer HGC236F, an additional 40 bp GC-rich nucleotide sequence
(GC-clamp) was added to stabilize migration of the DNA fragment in the DGGE (Muyzer
et al., 1993). The reaction mixtures for the PCR amplification contained: 2-5 µl template
83
Kapitel IV
DNA, 200 nM of each of the appropriate primers, 250 µM of each deoxyribonucleoside
triphosphate, 2 mM MgCl2, 5 µl 10x PCR buffer, and 0.5 U BIOTAQ Red DNA Polymerase
(Bioline) in a total volume of 50 µl. PCR reactions were performed in a Gradient Cycler
PT-200 (MJ Research) using an initial denaturation step at 95°C (10 min), followed by 30
cycles of denaturation at 95°C (1 min), annealing at 52°C (1 min), and extension at 72°C
(2 min). A final extension at 72°C (10 min) and subsequent cooling at 15°C completed the
reaction.
For clone libraries the same primer sets and PCR conditions were used, however, without
the GC-clamp at the 5’-end of the HGC236F primer.
DGGE analysis of PCR products
DGGE was performed as described previously (Allgaier and Grossart, 2006) in a 7 % (v/v)
polyacrylamide gel with a modified denaturing gradient from 55 to 70 % of urea and
formamide. Prior loading of PCR products onto DGGE gels, DNA was quantified on
agarose gels using a quantitative DNA ladder (Low DNA Mass Ladder, Invitrogen). After
electrophoresis of 18 h, DNA bands were stained with 1x SYBR Gold (Molecular Probes)
and documented using an AlphaImager 2200 Transilluminator (Biozym).
Analyses of DGGE profiles and statistics
DGGE banding patterns were analyzed by non-metric multidimensional scaling (NMS)
ordinations using the software packages GelCompar II, Version 3.5 (Applied Maths) and
PC-ORD, Version 4.0 (MJM Software Design). Within GelCompar II a band based binary
presence/absence table was calculated applying Dice similarity coefficient. This
presence/absence table was imported into PC-ORD and used for the NMS ordination
analyses. The advantage of NMS over other multivariate statistical methods (e.g.
canonical correspondence analysis, CCA) is that this method uses rank order information
of a similarity matrix of the samples rather than the original data matrix. Thus, NMS avoids
distortions originating from the non-normal distribution of the species data of the DGGE
gels (McCune and Grace, 2002).
Primary analyses of all gels were done by a standard setup using relativise Sørensen
distance measures, random starting coordinates, a step-down from six to one dimension,
an instability criterion of 0.0001, 300 iterations to reach stability, 50 runs with real data
sets, and 100 runs with the Monte Carlo permutation test. The final run was performed
with the optimum number of dimensions (2-6 dimensions) and the appropriate
configurations as starting coordinates. Varimax rotation was applied to find corresponding
groups and sample units.
84
Kapitel IV
For the identification of correlations between environmental variables and the DGGE
profiles of the Actinobacteria populations Pearson’s product moment correlations were
calculated for the significant axes of the NMS ordinations. Pearson’s product moment
correlations were performed separately for free-living and particle-associated bacteria of
each single lake and with a combined data set composed of both bacterial fractions. In
addition, two comprehensive data sets of free-living and particle-associated Actinobacteria
were used comprising DGGE profiles and limnological variables of the epilimnia of all
lakes.
To test the significance of differences between the DGGE banding patterns analysis of
similarity (ANOSIM) (Clarke and Green, 1988) was applied using the software PRIMER 5,
Version 5.2.9 (PRIMER-E Ltd.). ANOSIM generates a test statistic (R) which is an
indication of the degree of separation between groups. A score of 1 indicates complete
separation whereas a score of 0 indicates no separation.
Construction of clone libraries and sequencing
Cloning of the actinobacterial 16S rRNA gene fragments derived from PCR with the
specific primer set HGC236F/HGC664R was done using the pGEM-T-Easy Vector
System II (Promega) according to the manufacturer’s protocol. Two clone libraries were
constructed for the November 2003 sample of Lake Tiefwaren - one clone library for freeliving Actinobacteria and one for the particle-associated fraction. A total of 60 clones
(30 clones of each clone library) were picked and sequenced with the primers M13F (5’ –
GTT TTC CCA GTC ACG AC – 3’) and M13R (5’ – CAG GAA ACA GCT ATG AC – 3’) as
described previously (Allgaier and Grossart, 2006).
Phylogenetic analysis
Phylogenetic analyses of the partial 16S rRNA gene sequences were done using the ARB
software package (http://arb-home.de). The retrieved sequences were imported into an
ARB database of 52,000 reference sequences including the closest related sequences
determined by BLAST (http://www.ncbi.nlm.nih.gov/BLAST/). Sequences were first
aligned automatically by the integrated alignment module within the ARB package and
subsequently corrected manually. For stability of the phylogenetic tree a backbone tree
was calculated comprising only sequences of ≥ 1400 nucleotides. Consistence of
branching patterns was checked applying the three phylogenetic reconstruction methods:
neighbor-joining, maximum parsimony, and maximum likelihood to the appropriate set of
sequences. Sequences ≤ 1400 nucleotides were added afterwards to the tree according
to maximum parsimony criteria. To exclude highly variable positions within the 16S rRNA
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Kapitel IV
gene sequences a 50 % base frequency filter specific for Actinobacteria was calculated.
This filter uses only those sequence positions of the alignment for phylogenetic
reconstructions, where 50 % of the analyzed sequences have identical entries. Thus, the
phylogenetic calculations become more robust and potential alignment errors are
excluded. The final tree was calculated using the maximum likelihood algorithm.
Nucleotide sequence accession numbers
The partial sequences of 16S rRNA gene fragments obtained in this study were deposited
in GenBank with the following accession numbers: DQ662857-DQ662895.
Acknowledgement
We thank E. Mach for technical assistance during sampling and for the measurement of
several limnological parameters. R. Koschel, L. Krienitz, and P. Kasprzak are thanked for
providing data on chemistry, phytoplankton and zooplankton biomasses and community
composition, respectively. K. Pohlmann is warmly acknowledged for help in statistical
analyses and her many fruitful comments on this manuscript. This study was supported by
the Leibniz foundation and by a grant of the Studienstiftung des deutschen Volkes given
to M. Allgaier.
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TABLE 1: Absolute numbers of DGGE bands of free-living and particle-associated
Actinobacteria of the sampled lakes.
Lake
Lake Breiter Luzin
Lake Stechlin (epilimnion)
Lake Stechlin (metalimnion)
Lake Stechlin (hypolimnion)
Lake Grosse Fuchskuhle (NE)
Lake Grosse Fuchskuhle (SW)
Lake Tiefwaren
free-living
17.4 ±3.6
13.5 ±2.6
17 ±2.9
14.2 ±1.4
8.2 ±2.9
4.3 ±2.6
13.7 ±1.4
particle-associated
10.8 ±2.5
12.9 ±2.5
13 ±1.9
8.9 ±4.4
6 ±1.6
3 ±1.6
13.1 ±6.3
NE northeast compartment; SW southwest compartment
TABLE 2: Results of ANOSIM statistics from the comparison of DGGE banding patterns
of free-living and particle-associated Actinobacteria of the epilimnetic samples of all four
lakes (A) and of epi-, meta-, and hypolimnetic samples of Lake Stechlin (B). Significance
values with p ≤0.05 are given in grey.
free-living bacteria
A
BL vs. FNE
BL vs. FSW
BL vs. ST
BL vs. TW
FNE vs. FSW
FNE vs. ST
FNE vs. TW
FSW vs. ST
FSW vs. TW
ST vs. TW
0.469
0.674
0.666
0.622
0.271
0.500
0.480
0.583
0.651
0.688
≤0.001
≤0.001
≤0.001
≤0.001
≤0.001
≤0.001
≤0.001
≤0.001
≤0.001
≤0.001
0.403
0.397
0.375
0.309
0.444
0.454
0.290
0.574
0.298
0.350
≤0.001
≤0.001
≤0.001
≤0.001
≤0.01
≤0.001
≤0.05
≤0.001
≤0.05
≤0.001
0.953
0.684
0.965
≤0.001
≤0.001
≤0.001
0.522
0.452
0.855
≤0.05
≤0.001
≤0.001
B
STE vs. STM
STE vs. STH
STM vs. STH
The global tests revealed sample statistics of 0.509 (free-living) and 0.326 (particle-associated) within epilimnetic samples,
and 0.783 (free-living) and 0.417 (particle-associated) within samples of the three water layers of Lake Stechlin,
respectively. Significance levels of all global tests were p ≤0.001. BL Lake Breiter Luzin; STE Lake Stechlin (epilimnion);
STM Lake Stechlin (metalimnion); STH Lake Stechlin (hypolimnion); FNE Lake Grosse Fuchskuhle (NE compartment);
FSW Lake Grosse Fuchskuhle (SW compartment); TW Lake Tiefwaren.
90
Kapitel IV
TABLE 3: Results of Pearson product moment correlations of NMS analyses of free-living
(A) and particle-associated (B) Actinobacteria communities of the lakes and the measured
limnological parameters. Pearson’s r values ≥0.7 are given for the three significant
ordination axes. Limnological parameters with correlations r ≤0.7 were excluded from this
table. The first column shows the results of the comprehensive analyses of epilimnetic
samples of all lakes.
A
BL
FNE
FSW
ST
STH
TW
-0.728 (2)
-0.728 (2)
-0.714 (2)
-
0.719 (2)
-0.832 (2)
-0.731 (3)
0.741 (3)
-0.940 (2)
0.733 (1)
0.715 (1)
-0.721 (2)
0.705 (2)
0.794 (1)
0.784 (1)
0.715 (2)
0.792 (2)
N.D.
-
0.771 (2)
N.D.
-
0.744 (1)
0.761 (1)
-
-0.865 (1)
N.D.
N.D.
N.D.
N.D.
N.D.
N.D
-0.931 (3)
0.800 (3)
-0.830 (3)
-0.890 (3)
-0.740 (3)
-0.856 (3)
-0.872 (3)
-0.845 (3)
-0.896 (3)
-0.807 (3)
0.726 (2)
-0.763 (1)
-0.809 (3)
-
-0.786 (2)
0.867 (2)
-0.721 (2)
-0.749 (2)
0.717 (2)
-
-0.859 (2)
-0.818 (2)
-
0.776 (3)
-0.708 (1)
0.730 (3)
0.773 (3)
0.872 (1)
0.933 (1)
-0.867 (2)
0.811 (3)
-0.855 (2)
0.849 (3)
-0.715 (3)
-0.854 (3)
N.D.
-0.757 (1)
0.737 (3)
-0.839 (3)
-0.729 (2)
-0.702 (2)
N.D.
-
0.700 (3)
-0.741 (3)
-
-0.796 (3)
-0.817 (3)
-0.819 (3)
-0.796 (2)
-0.837 (3)
N.D.
N.D.
N.D.
N.D.
0.701 (3)
-0.768 (1)
N.D.
N.D.
-0.742 (2)
-0.753 (2)
-
free-living
DOC
Temperature
pH
Conductivity
β-D-glc. activity
Protease activity
BPP (FL)
BPP (total)
PP (total)
PP (<20 µm)
PP (>3.0 µm)
PP (<3.0 >0.2µm)
NO2-N
PO4-P
Total P
Calcium
Iron
Silicate
TOC
Alkalinity
Zooplankton
Phytoplankton
B
Epilimnion
(all lakes)
particle-associated
Bacterial numbers
DOC
Temperature
O2 [mg/l]
O2 [%]
pH
Conductivity
β-D-glc. activity
Protease activity
BPP (FL)
BPP (total)
PP (total)
PP (<20 µm)
PP (>3.0 µm)
PP (<3.0 >0.2µm)
NH4-N
PO4-P
Total P
Calcium
Iron
Silicate
TOC
Alkalinity
Zooplankton
Phytoplankton
(1) (2) (3)
, , correlations to ordination axes 1, 2, and 3, respectively; PA particle-associated; FL free-living; DOC dissolved
organic carbon; β-D-glc. β-D-glucosidase; BPP bacterial protein production; PP primary production; TOC total organic
carbon; N.D. not determined; abbreviations for the lakes are given Table 2.
91
Kapitel IV
TABLE 4: Main limnological characteristics of the studied lakes.
Parameter
Lake Stechlin
Lake Grosse Fuchskuhle
northeast basin
southwest basin
Lake Breiter Luzin
Lake Tiefwaren
N 53° 10’
E 13° 02’
69.5
4.3
26.0
6.5 - 10.5
oligotrophic
8.5 (± 0.2)
N 53° 10’
E 13° 02’
5.6
0.02
0.005
N 53° 20’
E 13° 28’
58.5
3.57
14.0
1.6 - 3.8
mesotrophic
8.5 (± 0.2)
N 53° 31’
E 12° 42’
24
1.4
17.5
3.1 - 8.9
eutrophic
8.3 (± 0.2)
Geographical position
Max. depth [m]
Surface area [km2]
Catchment area [km2]
Secchi depth [m]
Trophy
pH
1.0 - 2.2
eutrophic
6.5 (± 0.6)
0.9 - 1.5
dystrophic
4.7 (± 0.2)
data for pH are average values of epilimnetic samples from April-November 2003 and March 2004; trophic status was
determined following the guideline EUR 14563 EN of the Commission of the European Communities (Premazzi &
Chiaudani, 1992).
FEB
SEP
MAR
MAR
NOV
MAR
OCT
DEC
NOV
MAR
JUL
SEP DEC OCT
JUN
NOV AUG
JUN
JUN
JUL
APR
AUG
MAY
AUG
AUG
APR
SEP
OCT
MAY
NOV
JUL
APR
JUN
MAR
AUG
JUL
JUL
FEB
SEP
OCT
SEP
DEC
SEP
JUN
NOV
Axis 2
MAR
BL
FNE
MAY
APR
MAY
MAY
JUL
JUN
FSW
APR
stress = 13.285
stress = 14.498
stress = 4.538
APR
APR MAY
MAY
MAR
JUL
FEB
OCT
APR SEP
JUN
DEC
AUG
OCT
FEB
NOV
MAY
NOV
JUN
DEC
NOV
JUL
MAR
SEP
JUL
FEB
MAY
AUG
AUG
MAR
SEP
JUN
AUG
DEC
OCT
JUN
JUL
MAR
APR
STE
stress = 6.713
APR
MAY
OCT
NOV
TW
FEB
DEC
stress = 10.35
Axis 1
FIGURE 1: NMS ordination plots of free-living and particle-associated Actinobacteria
populations of the studied lakes. Open symbols: free-living Actinobacteria; solid symbols:
particle-associated Actinobacteria. The abbreviations for the lakes are given in Table 2.
92
Kapitel IV
Actinobacteria
particle-associated
100
100
100
100
99
100
Swedish lake clone LiUU-9-93; AY496998
Columbia River clone CR-FL3; AF141389
uncultured bacterium S9F-17; AB154306
Lake Tiefwaren clone TWAC-40; DQ662890
Lake Blankaart clone BKB7; AJ310373
Zwischenahner Meer clone Z35; AF488670
86
70
Delaware River clone Sta2-35; AY562338
Pavin Lake clone P38.5; AY752087
uncultured actinobacterium clone FNE11-3; DQ316345
uncultured actinobacterium; AJ629849
uncultured actinobacterium R3; AJ575499
Lake Tiefwraen clone TWAC-20; DQ662869
97
Changjiang River clone; AY071878
uncultured actinobacterium N3; AJ575530
uncultured actinobacterium S8; AJ575509
99
Zwischenahner Meer clone Z38; AF488673
Delaware River clone B30e; AY562270
86
uncultured bacterium S9A-11; AB154300
73
uncultured actinobacterium clone BL11-23; DQ316328
100
100
100 Lake Soyang clone SY2-69; AF107512
41
Mycobacterium sp. DhA-55; AJ011510
Mycobacterium sp. BPC5; AF494537
100
Mycobacterium sp. M0183; AF055322
55
uncultured actinobacterium S15A-MN29; AJ534679
76
68
uncultured bacterium PeM41; AJ576407
Sporichthya polymorpha; AB025317
uncultured bacterium ARFS-32; AJ277698
uncultured bacterium 7; AF513101
uncultured actinobacterium clone ST5-24; DQ316370
uncultured actinobacterium NM2; AJ575535
uncultured actinobacterium S1; AJ575504
uncultured actinobacterium clone STH5-14; DQ316384
uncultured bacterium ARFS-6; AJ277690
Microthrix parvicella; X89560
uncultured Crater Lake bacterium CL120-133; AF316730
uncultured Verrucomicrobia bacterium VC12; AY211073
uncultured bacterium PK291; AY555799
100
uncultured bacterium PK286; AY555797
acI
Mycobacteriaceae
Microsphaera
Sporichthya
acIV
Microthrix
Verrucomicrobia
0.10
FIGURE 2: Maximum Likelihood tree of cloned and sequenced 16S rRNA gene fragments
of free-living and particle-associated Actinobacteria. Solid lines indicate sequences ≥ 1400
nucleotides, whereas dotted lines mark partial sequences (≤ 1400 nucleotides) which
were added to the tree by maximum parsimony criteria. Sequences of this study are
shown in bold letters. Sequences of particle-associated Actinobacteria are marked by grey
boxes. GenBank accession numbers are given. The scale bar corresponds to 10 % base
substitutions. Bootstrap values at the main branching points are given.
93
Kapitel IV
free-living
particle-associated
BL
FNE
FSW
ST
TW
pH
pH
ALK
ALK
Axis 2
COND
IRON
TOC
DOC
stress = 16.328
stress = 17.976
Axis 1
FIGURE 3: Joint plot of the results of the comprehensive NMS analyses of the epilimnetic
samples of all lakes and limnological variables with a correlation strength of a Pearson’s
r ≥ 0.7. ALK: alkalinity; COND: conductivity; TOC: total organic carbon; DOC: dissolved
organic carbon.
free-living
MAY
DEC
APR
particle-associated
AUG
DEC
MAR
OCT
NOV
OCT
FEB
JUL
MAY
JUN
AUG
JUN
MAR NOV
APR
AUG
DEC
FEB
FEB
MAR
APR
JUL
MAR
OCT
AUG
JUN
JUL
DEC
OCT
JUN
MAY
JUL
APR
FEB
NOV
NOV
SEP
Axis 2
OCT
AUG
MAY
JUL
OCT
epilimnion
JUN
metalimnion
hypolimnion
JUL
AUG
JUN
SEP
stress = 5.399
stress = 8.434
Axis 1
FIGURE 4: NMS ordination plots of the intra-lake comparison of free-living and particleassociated actinobacterial communities of the epi-, meta-, and hypolimnion of Lake
Stechlin.
94
V
Abundance and phylogenetic
diversity of free-living and particleassociated epilimnetic
Actinobacteria of Lake Kinneret
(Israel) – A case study
Kapitel V
Actinobacteria of Lake Kinneret (Israel)
submitted to Environmental Microbiology (July, 2006)
Abundance and phylogenetic diversity of free-living and
particle-associated epilimnetic Actinobacteria
of Lake Kinneret (Israel) – A case study
Martin Allgaier and Hans-Peter Grossart*
Leibniz-Institute of Freshwater Ecology and Inland Fisheries
Department Limnology of Stratified Lakes
Alte Fischerhütte 2
D-16775 Stechlin-Neuglobsow
Germany
Running title:
Abundance and phylogeny of Actinobacteria in Lake Kinneret
Key words:
Actinobacteria, free-living and particle-associated, phylogenetic
diversity, CARD-FISH, Lake Kinneret
97
Kapitel V
Summary
We studied the abundance and phylogenetic diversity of free-living and particleassociated Actinobacteria in the epilimnion of Lake Kinneret in October 2004.
Actinobacteria communities were characterized by CARD-FISH and clone libraries of
actinobacterial 16S rRNA gene fragments. Actinobacteria accounted for 45 % of total
bacterial numbers. Phylogenetically, all retrieved 16S rRNA gene sequences belonged to
known actinobacterial lineages (e.g. Mycobacteriaceae, Corynebacteriaceae, acI cluster)
and indicated no phylogenetic differences to freshwater Actinobacteria populations of
other climatic zones. However, separate phylogenetic analyses of free-living and particleassociated Actinobacteria revealed distinct differences between both fractions suggesting
a potential adaptation of certain actinobacterial lineages to specific microenvironments.
Introduction
The class Actinobacteria comprises a variety of gram-positive bacteria with a high
genomic G+C content which are best described for soil environments (Goodfellow and
Williams, 1983; Rheims et al., 1999). Recent studies have shown that Actinobacteria also
occur in the epilimnion of freshwater habitats and frequently belong to the dominant
fraction of bacterioplankton communities (Glöckner et al., 2000; Warnecke et al., 2005;
Allgaier and Grossart, 2006). Freshwater Actinobacteria clusters in distinct phylogenetic
lineages which are clearly separated from Actinobacteria of other environments
(Warnecke et al., 2004). Their phylogenetic separation and in situ activity suggest that
Actinobacteria are an autochthonous component of limnetic habitats (Warnecke et al.,
2005). Nevertheless, almost nothing is known about their physiology and ecological role.
Lake Kinneret is a subtropical monomictic lake in northern Israel covering an area of ca.
170 km2 with a maximum depth of 43 m. The lake is considered as mesotrophic-eutrophic
with an annual net primary production of 610 g C m-2 (Berman et al., 1995). The lake is
strongly stratified from April to November with an anoxic hypolimnion. Several studies
have investigated the role of heterotrophic bacteria in Lake Kinneret (Hart et al., 2000;
Berman et al., 2001; 2004; Pinhassi and Berman, 2003). However, currently no studies
exist examining the community structure of the entire bacterioplankton or single
phylogenetic lineages of this lake. Due to their global distribution and high abundances in
freshwater habitats we assessed the abundance and phylogenetic diversity of
Actinobacteria in the epilimnion of Lake Kinneret to test, whether Actinobacteria are also a
dominant bacterial group in a subtropical lake and whether Lake Kinneret harbour distinct
98
Kapitel V
phylogenetic lineages which are different from actinobacterial communities of other known
freshwater systems. We differentiated between free-living and particle-associated
Actinobacteria to reveal higher resolutions in their community structure and to obtain
additionally insights into potential ecological adaptations of distinct phylogenetic lineages
to specific microenvironments.
Results and Discussion
This study was conducted in October 2004 when the thermal stratification of Lake
Kinneret was well developed and stable. A single water sample was taken close to the
central lake station (Station A; 32°82’N, 35°61’E) 1 m above the thermocline in 16 m depth
at the 8th of October. Abundances of total and particle-associated Actinobacteria were
determined by catalyzed reporter deposition fluorescent in situ hybridization (CARD-FISH)
(Sekar et al., 2003). As determined by the probe mix EUB I-III (Daims et al., 1999)
hybridization efficiencies were around 94 % (total Bacteria) and 75 % (particle-associated
Bacteria). The quantification of Actinobacteria by the oligonucleotide probe HGC69a
(Roller et al., 1994) revealed high abundances of total Actinobacteria in the analyzed
water sample (Figure 1). Also particle-associated bacterial communities showed relatively
high proportions of Actinobacteria (Figure 1). Around 62 (total) and 29 % (particleassociated) of all Actinobacteria belonged to the freshwater cluster acI (Warnecke et al.,
2004) indicating a dominance of this cluster within actinobacterial communities of Lake
Kinneret. Due to high standard deviations within particle-associated Actinobacteria we
were not able to calculate reliable proportions of free-living Actinobacteria by subtracting
the numbers of particle-associated Actinobacteria from those of total Actinobacteria. The
absolute cell numbers, however, revealed a numerical dominance of free-living compared
to particle-associated Actinobacteria (data not shown). In general, our results of the
CARD-FISH approach indicated that Actinobacteria belong to the dominant fraction of
bacterioplankton communities in the lower epilimnion of Lake Kinneret in October 2004.
We are aware of the fact that our results are restricted to a single water sample from a
particular sampling date and that additionally studies are needed to draw any convincing
conclusions on the occurrence and abundance of Actinobacteria in Lake Kinneret.
Nevertheless, the obtained data are well comparable to studies on epilimnetic
Actinobacteria of several temperate lakes (Glöckner et al., 2000; Warnecke et al., 2005;
Allgaier and Grossart, 2006) indicating that Actinobacteria abundances in freshwater
systems of different climatic zones are not substantially different.
99
Kapitel V
Cloning and sequencing of free-living and particle-associated actinobacterial 16S rRNA
gene fragments resulted in a total of 47 clones (29 free-living, 18 particle-associated). The
majority of the sequences were phylogenetically affiliated to the acI cluster (Figure 2) and
support our results of the CARD-FISH approach. Furthermore, several sequences of
Mycobacteriaceae and Corynebacteriacea were found. In general, no significant
phylogenetic differences were observed between actinobacterial communities of Lake
Kinneret and freshwater habitats of other climatic zones (Hiorns et al., 1997; Methé and
Zehr, 1999; Urbach et al., 2001; Warnecke et al., 2004; Allgaier and Grossart, 2006).
Despite these phylogenetic similarities it can not be excluded that Actinobacteria of Lake
Kinneret are ecophysiologically adapted to their respective subtropical environmental
conditions. For example, Hahn & Pöckl (2005) showed that phylogenetically identical
Actinobacteria isolates from different climatic regions are well adapted to their prevailing
thermal conditions and, thus, represent different ecotypes.
Even though no significant phylogenetic differences were found between Actinobacteria
populations of Lake Kinneret and other freshwater habitats, distinct differences occurred
between free-living and particle-associated Actinobacteria of Lake Kinneret. Phylogenetic
lineages such as Mycobacteriaceae, Propionibacteriaceae, or Micrococcaceae exclusively
comprise particle-associated Actinobacteria, whereas Corynebacteriaceae, the acI, and
the acIV cluster contain mainly free-living Actinobacteria (Figure 2). This notion suggests
a potential adaptation of distinct actinobacterial lineages to specific microenvironments.
To our knowledge, currently no other study exists showing these phylogenetic differences
between free-living and particle-associated Actinobacteria. However, differences between
both actinobacterial fractions seem to be not a peculiarity of Lake Kinneret since similar
differences were also observed in Lake Tiefwaren (northeastern Germany) (Allgaier et al.,
submitted).
At present, the ecological relevance of the adaptation of distinct actinobacterial phyla to
specific microenvironments is largely unknown. Several Actinobacteria of the genera
Mycobacterium and Corynebacterium are known as pathogens, e.g. Mycobacterium
tuberculosis or Corynebacterium diphtheriae but both genera also comprise nonpathogenic members derived from various natural habitats, such as soils, plants, and
aquatic environments (Padgitt and Moshier, 1987). A distinct adaptation to particles is
most likely for members of the Micrococcaceae because bacteria of this group occur in
high abundances on mammalian skins (Kocur et al., 1992). However, it remains
speculative why distinct phylogenetic lineages of Actinobacteria predominantly occur on
particles and others mainly in the free-living form. To further elucidate this topic more
detailed analyses are necessary.
100
Kapitel V
In summary, our case study indicates that Actinobacteria are the dominant epilimnetic
bacterial fraction of Lake Kinneret in October 2004 with proportions similar to other
freshwater habitats. Our phylogenetic analyses suggest no substantial differences
between Actinobacteria communities of subtropical Lake Kinneret and other freshwater
systems of the temperate zone. The differentiation between free-living and particleassociated Actinobacteria revealed distinct differences between both bacterial fractions
and
suggest
an
adaptation
of
certain
actinobacterial
lineages
to
specific
microenvironments. Nevertheless, our results give only first insights into abundance and
phylogeny of Actinobacteria in Lake Kinneret. Therefore, further studies are necessary to
obtain more detailed informations on the phylogenetic diversity and ecology of
Actinobacteria populations in this lake.
Acknowledgement
We thank all participants of the German Israeli Minerva School at the Yigal Allon Kinneret
Limnological Laboratory (KLL), Israel, in October 2004, especially the members of the
organization committee O. Hadas, A. Sukenik, H. Baumert, and K.-P. Witzel. We also
would like to thank the staff of the KLL for their great help during sampling and in the lab.
P. Corredor and K.-P. Witzel is thanked for their support performing DNA extraction.
Further we would like to thank F. Warnecke and J. Pernthaler for the introduction into
CARD-FISH and for providing the oligonucleotide probes. This study was supported by
the Minerva foundation.
101
Kapitel V
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103
% of total DAPI counts
Kapitel V
Actinobacteria
(probe HGC69a)
acI cluster
(probe AcI-852)
70
60
50
40
30
20
10
0
TOTAL
PA
FIGURE 1: Relative abundance of members of the class Actinobacteria (probe HGC69a,
Roller et al., 1994) and the acI cluster (probe AcI-852, Warnecke et al., 2005) in the lower
epilimnion (16 m) of Lake Kinneret derived from CARD-FISH. Error bars represent
standard deviations determined from 10 (total) and 25 (particle-associated) independently
counted microscopic fields, respectively. (TOTAL) total Actinobacteria, (PA) particleassociated Actinobacteria. For CARD-FISH water samples of 5 ml were filtered through
0.2 µm Nuclepore polycarbonate filters (total Actinobacteria) and 10 ml through 5.0 µm
filters (particle-associated Actinobacteria). CARD-FISH was performed as described
previously (Sekar et al., 2003; Allgaier and Grossart, 2006).
104
Kapitel V
Mycobacterium sp. Myc399 (AF491284)
Lake Kinneret clone LKAC-10; DQ675143
Mycobacterium peregrinum ; AF058712
Mycobacterium sp. DSM3803; AY147261
Mycobacterium sp. HE5; AJ012738
Mycobacterium chitae; X55603
Mycobacterium sp. MCRO16; X93027
100
Mycobacterium sp. KMS; AY083217
91
Mycobacterium sp.; U46146
uncultured corynebacterium MTcory21R; AF115944
Corynebacterium imitans; AF537597
Corynebacterium sp. 2002-2300500; AY244775
Corynebacterium sp. 1 ex sheep; Y13427
Corynebacterium jeikeium ; X82062
uncultured corynebacterium MTcory14R; AF115940
Lake
Kinneret clone LKAC-24; DQ675147
100
97
uncultured actinobacterium APe2_64; AB074644
Pseudonocardia zijingensis; AF325725
uncultured bacterium #0649-1I18; AF234120
Pseudonocardia thermophila; AJ252830
100
90
uncultured bacterium a2b011; AF419680
100
98
Propionibacterium propionicum ; AJ003058
uncultured bacterium PeM19; AJ576388
100
Nocardioides sp. NSP41; AF005024
Micrococcus luteus HN2-11; AF057289
Micrococcus sp. 98TH11322; AY159889
Micrococcus sp. MN81d1c; AJ313024
bacterium str. 71381; AF227843
100
uncultured actinobacterium R6; AJ575502
uncultured bacterium S9F-07; AB154305
98
95
Lake Kinneret clone clone LKAC-36; DQ675160
uncultured actinobacterium clone FSW11-20; DQ316352
97
78
92
98 Lake Kinneret clone LKAC-31; DQ675155
99
uncultured bacterium S9A-07; AB154299
uncultured actinobacterium NM1; AJ575534
100
uncultured actinobacterium clone TWAC-34; DQ662883
Swedish lake clone LiUU-5-233: AY496989
95
Lake Soyang clone SY2-69; AF107512
uncultured actinobacterium FBP218; AY250865
Sporichthya polymorpha; X72377
Crater Lake clone CL120-38; AF316671
Crater Lake clone CL120-45; AF316672
Actinobacteria
particle-associated
98
59
99
41
80
88
97
83
100
100
Mycobacteriaceae
Corynebacteriaceae
Pseudonocardiaceae
Propionibacteriaceae
Nocardioidaceae
Micrococcaceae
acI
Sporichthya
acIV
0.10
FIGURE 2: Maximum likelihood tree of 16S rRNA gene sequences derived from clone
libraries of free-living and particle-associated Actinobacteria. At first a backbone tree was
calculated including sequences ≥ 1400 nucleotides (solid lines). In a second step, partial
sequences (≤ 1400 nucleotides) were added to this tree according to maximum parsimony
criteria (dotted lines). Sequences of this study are shown in bold letters. GenBank
accession numbers are given. The scale bar corresponds to 10 % base substitutions.
Bootstrap values at the main branching points are given. For more details on sequence
alignments and phylogenetic reconstructions see Allgaier and Grossart (2006). Cloning
and sequencing of actinobacterial 16S rRNA gene fragments were performed as
described previously (Allgaier and Grossart, 2006). For DNA extraction water samples of
100-150 ml were filtered sequentially through 5.0 and 0.2 µm Nuclepore polycarbonate
membranes to separate free-living and particle-associated bacteria. Actinobacterial 16S
rRNA gene fragments were PCR amplified with primers specific for Actinobacteria
(Warnecke et al., 2004). For each actinobacterial fraction one clone library was
constructed.
105
VI
Kapitel VI
Gesamtbetrachtung
Aquatische Lebensräume sind hochkomplexe Ökosysteme, in denen eine Vielzahl
biologischer Prozesse miteinander vernetzt ist. Viele der Prozesse werden von
Mikroorganismen bzw. Bakterien gesteuert, die signifikant am Stoffumsatz in diesen
Systemen beteiligt sind (Cotner & Biddanda, 2002). Trotz ihrer biogeochemischen
Bedeutung ist bislang relativ wenig über die phylogenetische Diversität und Dynamik
vieler aquatischer Bakteriengemeinschaften bekannt. Die Mehrzahl der Untersuchungen
an aquatischen Bakterien wurde in marinen Habitaten durchgeführt (Giovannoni, 2004).
Da zum Teil deutliche Unterschiede zwischen limnischen und marinen Bakterien
existieren (Methé et al., 1998; Glöckner et al., 1999; Rappé et al., 2000; Zwart et al.,
2002), erscheint das Studium limnischer Bakteriengemeinschaften aus heutiger Sicht
umso notwendiger. In limnischen Systemen mangelt es vor allem an vergleichenden
Studien, die detaillierte Rückschlüsse auf generelle Muster und Anpassungen von
Bakteriengemeinschaften oder einzelnen Bakteriengruppen an ihre Umwelt ermöglichen.
In
der
hier
vorliegenden
Arbeit
wurde
daher
gezielt
der
Ansatz
verfolgt,
Bakteriengemeinschaften aus limnologisch unterschiedlichen Seen hinsichtlich ihrer
phylogenetischen Diversität, saisonalen Dynamik und ökologischen Anpassungen zu
charakterisieren und miteinander zu vergleichen. In einem ersten Schritt wurden dazu
mittels verschiedener molekularbiologischer Verfahren die Bakteriengemeinschaften in
vier ausgewählten Seen der Mecklenburgischen Seenplatte im jahreszeitlichen Verlauf
untersucht (vgl. Kapitel II). Die offensichtliche Dominanz von Vertretern der
Actinobacteria in den Untersuchungsgewässern führte im Folgenden zu gezielten Studien
an dieser Bakteriengruppe. Die dabei erzielten Ergebnisse lieferten neue und detaillierte
Einblicke in die phylogenetische Diversität, saisonale Dynamik und Anpassung
spezifischer Actinobacteria-Populationen an ihre Habitate (vgl. Kapitel III-V).
Die Bakterienpopulationen in den Untersuchungsgewässern
Wie die DGGE-Profile zeigten, gab es signifikante Unterschiede zwischen den
der
vier
untersuchten
Seen
(vgl.
Kapitel
II).
Diese
Unterschiede wurden sowohl zwischen frei-lebenden wie auch partikel-assoziierten
Bakteriengemeinschaften gefunden. Dass sich die beiden Fraktionen nicht immer
voneinander unterscheiden, wurde mehrfach gezeigt (Hollibaugh et al., 2000; Riemann &
Winding, 2001; Stevens et al., 2005). Bewegliche Bakterien können durch aktives
Anheften und Verlassen von Partikeln zu erheblichen Austauschraten zwischen den
beiden Bakterienfraktionen führen (Kiørboe et al., 2002). Auf Ebene der 16S rRNA waren
109
Kapitel VI
die
Unterschiede
zwischen
den
der
vier
Untersuchungsgewässer weniger stark ausgeprägt als bei den DGGE Analysen. Die
phylogenetischen
Vergleiche
von
16S
rRNA-Gensequenzen
deuteten
auf
das
Vorkommen meist identischer Phylotypen in den Seen hin. Da in dieser Arbeit keine
DGGE-Banden sequenziert wurden, kann die phylogenetische Diversität der DGGEProfile nicht mit den Ergebnissen aus den Klonbibliotheken verglichen werden. Es ist
durchaus
möglich,
dass
die
DGGE-Banden
auf
Sequenzebene
eine
ähnliche
phylogenetische Diversität darstellen wie sie durch die Klonbibliotheken gezeigt wurde.
Die durch die Klonbibliotheken identifizierten Bakterien konnten alle phylogenetisch
bereits bekannten Süßwasser-Clustern zugeordnet werden (Zwart et al., 2002). Die
Klonbibliotheken wurden vor allem von Sequenzen der Actinobacteria dominiert, gefolgt
von Vertretern der Bacteroidetes, α- und β-Proteobacteria (vgl. Kapitel II und III).
Während nahezu keine phylogenetischen Unterschiede zwischen den Seen erkennbar
waren, gab es deutliche Unterschiede in der phylogenetischen Zusammensetzung von
frei-lebenden und partikel-assoziierten Bakteriengemeinschaften. Frei-lebende Bakteriengemeinschaften wurden von Actinobacteria, Bacteroidetes, α- und β-Proteobacteria
dominiert,
wohingegen
sich
die
partikel-assoziierten
überwiegend aus Vertretern der Bacteroidetes, α-Proteobacteria und Planctomycetes
zusammensetzten. Besonders auffällig war die Tatsache, dass bis auf eine Sequenz alle
Actinobacteria-Sequenzen aus der frei-lebenden Bakterienfraktion stammten (vgl.
Kapitel II). Durch die gezielte Analyse der partikel-assoziierten Bakterien konnte jedoch
gezeigt werden, dass Actinobacteria trotz ihrer geringen Abundanz auf Partikeln eine
ähnliche phylogenetische Diversität aufweisen können wie frei-lebende Actinobacteria
(vgl. Kapitel IV und V). Phylogenetische Unterschiede zwischen frei-lebenden und
partikel-assoziierten Bakterien sind aus früheren Studien bekannt (Weiss et al., 1996;
Grossart & Simon, 1998; Brachvogel et al., 2001; Schweitzer et al., 2001). Sie lassen auf
die Anpassung bestimmter Bakteriengruppen an die spezifischen Lebensbedingungen auf
den Partikeln schließen. Aufgrund der begrenzten Anzahl an sequenzierten Klonen
können mit den vorliegenden Daten jedoch keine quantitativen Aussagen über das
Vorkommen einzelner Bakteriengruppen gemacht werden. Wie bereits in Kapitel II und III
diskutiert wurde, geben die erhaltenen Sequenzen dennoch einen grundlegenden Einblick
in die phylogenetische Diversität der untersuchten Bakteriengemeinschaften.
110
Kapitel VI
Limnische Actinobacteria
Phylogenetische Diversität
Vertreter der Actinobacteria wurden in allen Untersuchungsgewässern als eine der
dominanten Bakteriengruppen identifiziert (vgl. Kapitel III). In den letzten Jahren hat sich
mehrfach gezeigt, dass Actinobacteria neben den β-Proteobacteria einen wesentlichen
Bestandteil limnischer Bakteriengemeinschaften ausmachen können (Hiorns et al., 1997;
Burkert et al., 2003; Van der Gucht et al., 2005). Dennoch ist über diese Bakteriengruppe
bislang nur wenig bekannt. Die hier vorliegende Arbeit konnte grundlegend dazu
beitragen, neue Erkenntnisse über die phylogenetische Diversität und Dynamik limnischer
Actinobacteria, so wie deren Verbreitung und Anpassung an bestimmte Habitate zu
gewinnen (vgl. Kapitel III-V).
Die Actinobacteria der vier Untersuchungsgewässer konnten phylogenetisch überwiegend
bereits bekannten Clustern zugeordnet werden (z.B. acI, acII, oder acIV) (Warnecke et al.,
2004). Durch die umfangreichen Sequenzinformationen wurden aber auch neue Cluster
(acSTL) und Subcluster (scB 1-4, acIV D-E) entdeckt (vgl. Kapitel III). Wie in Kapitel IV
ausführlich dargestellt, gab es signifikante Unterschiede zwischen den ActinobacteriaPopulationen der vier untersuchten Seen. Im Stechlinsee konnten sogar Unterschiede in
den Actinobacteria-Populationen von Epi-, Meta- und Hypolimnion nachgewiesen werden.
Weitaus überraschender war jedoch die Entdeckung, dass sich frei-lebende und partikelassoziierte Actinobacteria-Populationen deutlich voneinander unterscheiden und dass
innerhalb der partikel-assoziierten Actinobacteria eine große phylogenetische Diversität
existiert (vgl. Kapitel IV und V). Nachdem in den universellen Klonbibliotheken (vgl.
Kapitel II und III) Actinobacteria fast ausschließlich frei-lebend gefunden wurden,
deuteten die spezifischen Analysen der Actinobacteria-Populationen eine bislang nicht
gezeigte phylogenetische Diversität innerhalb der partikel-assoziierten Actinobacteria an.
Anhand von vier 16S rRNA-Gen-Klonbibliotheken frei-lebender und partikel-assoziierter
Actinobacteria aus dem Tiefwarensee und dem See Genezareth konnte gezeigt werden,
dass partikel-assoziierte Actinobacteria teilweise anderen phylogenetischen Linien
angehören
als
frei-lebende
Actinobacteria.
Frei-lebende
Actinobacteria
wurden
beispielsweise mehrheitlich den beiden Clustern acI und acIV zugeordnet, wohingegen
partikel-assoziierte
Actinobacteria innerhalb der
Mycobacteriaceae,
Microsphaera,
Microthrix, und Micrococcaceae vorkamen (vgl. Kapitel IV und V).
Die Unterschiede zwischen den Actinobacteria-Populationen der untersuchten Seen und
Bakterienfraktionen deuten auf eine spezifische Anpassung der entsprechenden
an
ihre
Umweltbedingungen
111
hin.
Durch
die
enge
Kapitel VI
phylogenetische Verwandtschaft der identifizierten Actinobacteria kann hier sogar von
einer Mikrodiversität gesprochen werden (Moore et al., 1998; Jaspers & Overmann,
2004). Für eine genaue Klärung sind jedoch weiterführende Untersuchungen notwendig.
Die vorgeschlagene Mikrodiversität wird von den Ergebnissen aus verschiedenen
statistischen Analysen unterstützt, in denen seenspezifische Korrelationsmuster zwischen
Actinobacteria und bestimmten Umweltparametern gefunden wurden (vgl. Kapitel IV und
Anhang). Bei Actinobacteria-Isolaten aus Gewässern verschiedener klimatischer Zonen
wurde bereits eine ausgeprägte Mikrodiversität nachgewiesen (Hahn & Pöckl, 2005). Wie
die Ergebnisse der Studie zeigten, gab es eine deutliche Anpassung der jeweiligen
Actinobacteria an die klimatischen Bedingungen ihrer Ursprungshabitate.
Verbreitung, Dynamik und ökologische Anpassung limnischer Actinobacteria
Limnische Actinobacteria wurden weltweit bereits in verschiedenen Gewässern
nachgewiesen (z.B. Semenova & Kuznedelov, 1998; Urbach et al., 2001; Hahn & Pöckl,
2005; Haukka, et al., 2005; Van der Gucht et al., 2005). Den heute bekannten
Sequenzinformationen
zur
Folge
gibt
es
offensichtlich
keine
phylogenetischen
Unterschiede zwischen den bislang untersuchten Actinobacteria-Populationen. Nach der
Hypothese von Staley & Gosink (1999) können limnische Actinobacteria demnach als
kosmopolitisch angesehen werden, da sie keine geographischen Subcluster aufweisen.
Durch die in dieser Arbeit vorgestellte Fallstudie zur Abundanz und Diversität von
Actinobacteria im subtropischen See Genezareth (vgl. Kapitel V) konnte der
kosmopolitische Charakter der Actinobacteria weiter unterstützt werden. Die dort
identifizierten
Actinobacteria
wiesen
keine
phylogenetischen
Unterschiede
zu
Actinobacteria-Populationen aus limnischen Systemen temperenter Klimazonen auf. Die
globale Verbreitung und phylogenetische Ähnlichkeit von Actinobacteria-Populationen
verschiedener Gewässer und geographischer Regionen steht nicht im Widerspruch zu der
angenommenen Mikrodiversität innerhalb limnischer Actinobacteria (s.o.). Vielmehr wird
durch diese Annahme die Hypothese von Staley & Gosink (1999) unterstützt, da sich
deutlich zeigt, dass phylogenetisch identische Actinobacteria in der Lage sind,
verschiedene Habitate zu besiedeln.
Gegenwärtig existieren nur wenige Studien, in denen die relative Abundanz von
Actinobacteria in limnischen Systemen bestimmt wurden (Glöckner et al., 2000; Warnecke
et al., 2005). Bislang ist nur eine Studie bekannt, in der die saisonale Dynamik limnischer
Actinobacteria untersucht wurde (Glöckner et al. 2000). In der hier vorliegenden Arbeit
wurden erstmals vergleichende Untersuchungen zur jahreszeitlichen Dynamik limnischer
Actinobacteria verschiedener Seen durchgeführt. Durch die Entwicklung hochspezifischer
112
Kapitel VI
Oligonukleotidsonden (Warnecke et al., 2005) konnten nicht nur die Actinobacteria als
Großgruppe, sondern auch Vertreter verschiedener limnischer Cluster und Subcluster
quantifiziert werden (vgl. Kapitel III). Unabhängig vom Untersuchungsgewässer zeigten
die Actinobacteria-Populationen relativ einheitliche saisonale Muster mit Maxima im
Sommer und Spätherbst (vgl. Kapitel III). Diese ausgeprägte Saisonalität lässt eine
Kopplung zwischen Actinobacteria und bestimmten limnologischen Prozessen annehmen.
Die Maxima im Sommer und Herbst deuten stark auf einen selektiven Vorteil der
Actinobacteria in Phasen erhöhten grazings in den Gewässern hin (Pernthaler et al.,
2001; Jezbera et al., 2005, 2006). Der direkte Einfluss von grazing auf die Saisonalität
und Abundanz limnischer Actinobacteria konnte hier jedoch nicht untersucht werden, da
entsprechende Daten zu möglichen „Grazern“ (z.B. heterotrophe Nanoflagellaten) fehlten.
Ausführliche statistische Analysen sollten dennoch Einblicke in mögliche Abhängigkeiten
zwischen Actinobacteria und verschiedenen Umweltparametern liefern. Die Anwendung
linearer Regressionsanalysen und multivariater statistischer Verfahren (non-metric
multidimensional scaling, NMS) erbrachte eine Vielzahl unterschiedlicher Korrelationen
zwischen der Abundanz und Diversität von Actinobacteria und verschiedenen
limnologischen Parametern (vgl. Kapitel IV und Anhang). Es konnten jedoch keine
Schlüsselparameter identifiziert werden, die einen generellen Steuerungseinfluss auf die
Struktur und Dynamik limnischer Actinobacteria-Populationen vermuten lassen. Die
Ergebnisse
der
statistischen
Analysen
zeigten
vielmehr
seenspezifische
Korrelationsmuster zwischen Actinobacteria und bestimmten Umweltparametern, welche
die
Hypothese
der
physiologischen
und
ökologischen
Anpassung
limnischer
Actinobacteria an ihre Umwelt unterstützen (Hahn & Pöckl, 2005; vgl. Kapitel IV und
Anhang). Dass es Unterschiede in den Ergebnissen der beiden statistischen Verfahren
(linear vs. multivariat) und Spezies-Datensätzen (Abundanz vs. Diversität) geben wird,
war vorhersehbar. Sie sind auf die jeweilige statistische Methode bzw. verwendeten
Spezies-Datensätze
Abhängigkeiten
zurückzuführen.
zwischen
zwei
Während
Variablen
lineare
aufzeigen,
Regressionen
berücksichtigen
nur
direkte
multivariate
statistische Analysen auch Interaktionen zwischen einzelnen Parametern (McGarigal et
al., 2000).
Zusammenfassend bleibt festzuhalten, dass es innerhalb der limnischen Actinobacteria
eine große phylogenetische Diversität mit einer ausgeprägten saisonalen Dynamik gibt.
Die vergleichenden Untersuchungen der Actinobacteria-Populationen zwischen den
Untersuchungsgewässern und die statistischen Analysen deuten auf eine offensichtliche
ökologische Anpassung der jeweiligen Actinobacteria an ihre Umgebung hin. Mittels der
statistischen Analysen war es jedoch nicht möglich, grundlegende Informationen zu
113
Kapitel VI
physiologischen Eigenschaften der Actinobacteria zu erhalten. Für eine detaillierte
physiologische und ökologische Beschreibung limnischer Actinobacteria ist daher die
erfolgreiche Isolierung von Vertretern dieser Bakteriengruppe unumgänglich.
Verknüpfung von Struktur und Funktion aquatischer
Durch die Entwicklung kultivierungsunabhängiger Nachweisverfahren für Bakterien in der
mikrobiellen Ökologie kann heute die Struktur von Bakteriengemeinschaften relativ
einfach und zuverlässig bestimmt werden. Probleme treten erst bei dem Versuch auf, von
den molekularbiologischen Daten auf die Physiologie der Bakterien zu schließen.
Molekularbiologische Studien sind rein beschreibende Analysen der genetischen
Diversität von Bakteriengemeinschaften und lassen in der Regel nur begrenzt
Rückschlüsse auf ökophysiologische Eigenschaften der Bakterien zu. Da bislang nur ein
Bruchteil aller bekannten Bakterien kultiviert werden konnte, gibt es nur wenige
Informationen
zu
physiologischen
Eigenschaften
verschiedener
Bakteriengruppen
(Amann et al., 1995; Suzuki et al., 1997). Mittels hochspezifischer in situ Methoden (z.B.
Mikroautoradiographie gekoppelt mit Fluoreszenz in situ Hybridisierung; MAR-FISH) wird
daher seit einiger Zeit versucht, Informationen zur Ökologie bislang unkultivierter
Mikroorganismen zu erhalten (Alonso et al., 2005, 2006; Horňák et al., 2006). Neben
diesen experimentellen Studien gibt es aber auch eine ganze Reihe von Untersuchungen,
die
mittels
statistischer
Verfahren
auf
die
ökologische
Funktion
von
ganzen
Bakteriengemeinschaften oder einzelnen Bakteriengruppen zu schließen versuchen
(Lindström, 2001; Muylaert et al., 2002; Van der Gucht et al., 2005; Lindström et al., 2005;
Yannarell & Triplett, 2005; Newton et al., 2006). So wurden in der hier vorliegenden Arbeit
verschiedene statistische Methoden angewendet, um die Struktur und Dynamik der
und
Actinobacteria
der
vier
untersuchten
Seen
mit
limnologischen Parametern in Verbindung zu bringen (vgl. Kapitel II und IV). Die
erzielten Ergebnisse erlaubten jedoch keine konkreten Aussagen über Zusammenhänge
zwischen der Diversität und Abundanz der Bakterien und bestimmter limnologischer
Variablen. Die Gründe hierfür können vielerlei Ursprung sein und sind im Detail zu klären.
Vor allem hat sich aber gezeigt, dass eine höhere phylogenetische und zeitliche
Auflösung notwendig ist, um detaillierte Ergebnisse bezüglich der Zusammenhänge
zwischen Bakterien und Umweltparametern zu erhalten. Durch die gezielte Anwendung
der statistischen Verfahren auf die Actinobacteria konnten beispielsweise zahlenmäßig
mehr und stärkere Korrelationen zu bestimmten limnologischen Parametern gefunden
114
Kapitel VI
werden als bei den Analysen mit den gesamten Bakteriengemeinschaften (vgl. Kapitel II,
IV und Anhang). Ähnliches konnte auch bei den statistischen Analysen innerhalb der
Actinobacteria beobachtet werden. Durch die getrennte Analyse von frei-lebenden und
partikel-assoziierten Actinobacteria-Populationen konnten deutlich mehr Korrelationen
festgestellt werden als bei Analysen mit Datensätzen, die beide Bakterienfraktionen
enthielten (vgl. Kapitel IV und Anhang).
Die Problematik statistischer Ansätze zur Klärung physiologischer und ökologischer
Eigenschaften aquatischer Bakterien wurde mehrfach beschrieben und diskutiert
(Muylaert et al., 2002; Yannarell & Triplett, 2005; Newton et al., 2006). Auch wenn die hier
vorliegenden Ergebnisse durch ihre Heterogenität keine konkreten Rückschlüsse auf die
Ökologie der untersuchten Bakteriengemeinschaften zulassen, können statistische
Analysen generell gute Einblicke in die Physiologie und ökologische Rolle aquatischer
Bakteriengemeinschaften liefern (Stepanauskas et al., 2003; Yannarell & Triplett, 2005;
Lindström et al., 2005; Newton et al., 2006). Diese Erkenntnisse müssen jedoch durch
experimentelle Nachweise bestätigt werden. Detaillierte Kenntnisse über die ökologischen
Nischen einzelner Bakteriengruppen können letztendlich dazu genutzt werden, gezielt
Strategien zur Isolierung bislang unkultivierter Mikroorganismen zu entwickeln.
115
Kapitel VI
Aktuelle Projekte und Ausblicke
Im Rahmen dieser Arbeit konnten neue Erkenntnisse über die Struktur und Dynamik
limnischer Bakteriengemeinschaften und einzelner Bakteriengruppen gewonnen werden.
Dennoch sind einige Fragen offen geblieben, die es in Zukunft zu beantworten gilt. Eine
der größten Herausforderungen wird vor allem die Verknüpfung von Struktur und Funktion
aquatischer Bakteriengemeinschaften sein.
Aufbauend auf dieser Arbeit soll durch zwei weiterführende Projekte die Rolle der
Actinobacteria in den untersuchten Seen und anderen aquatischen Ökosystemen näher
beleuchtet werden. Die beiden Projekte verfolgen dabei zwei unterschiedliche
Herangehensweisen, um weitere Informationen über die physiologische und ökologische
Rolle limnischer Actinobacteria zu erhalten. In Kooperation mit dem Max-Planck-Institut
für Marine Mikrobiologie in Bremen und dem DOE Joint Genome Institute (USA) sollen im
ersten Projekt FOSMID libraries von Actinobacteria aus dem Stechlinsee und der Grossen
Fuchskuhle hergestellt und analysiert werden. Diese FOSMID libraries sollen gezielt auf
funktionelle
Gene
untersucht
werden,
um
so
Informationen
über
mögliche
Stoffwechseleigenschaften limnischer Actinobacteria zu erhalten. Neben diesem rein
molekularbiologischen Ansatz soll im zweiten Projekt versucht werden, Vertreter der
Actinobacteria zu isolieren und physiologisch zu charakterisieren. In Zusammenarbeit mit
Dr. Lasse Riemen von der Universität Kalmar (Schweden) sollen dazu neue
Isolierungsstrategien entwickelt werden, die auf eine erfolgreiche Isolierung der bislang
unkultivierten limnischen Actinobacteria hoffen lassen.
Auch wenn über die Phylogenie und Verbreitung limnischer Actinobacteria mittlerweile viel
bekannt ist, gibt es in diesem Bereich noch weiteren Informationsbedarf. Hierbei sollte vor
allem die detaillierte Untersuchung partikel-assoziierter Actinobacteria im Vordergrund
stehen. Ein wichtiger Punkt im Zusammenhang mit der Untersuchung der Phylogenie und
Biogeographie
limnischer
Actinobacteria
ist
die
Weiterentwicklung
spezifischerer
Nachweisverfahren, wie z.B. FISH-Sonden oder real time quantitative PCR (RTQ-PCR).
Wie bereits bei den Ergebnissen zur Abundanz und saisonalen Dynamik der
Actinobacteria zu sehen war, können mit den bislang etablierten FISH-Sonden etwa
60-91 % der Actinobacteria des acI Clusters detektiert werden (vgl. Kapitel III). Es bleibt
also immer noch ein Prozentsatz von 9-40 %, der nicht nachgewiesen werden kann.
Ähnliches gilt auch für andere Cluster innerhalb der Actinobacteria, für die gegenwärtig
nur wenige oder keine FISH-Sonden existieren.
Trotz der hohen Abundanz von Actinobacteria darf die Charakterisierung anderer
Bakteriengruppen nicht vernachlässigt werden. Wie die Klonbibliotheken von frei-
116
Kapitel VI
lebenden und partikel-assoziierten Bakterien der Untersuchungsgewässer zeigten, bilden
Vertreter der Bacteroidetes und diverser Gruppen der Proteobacteria weitere dominante
Fraktionen innerhalb des heterotrophen Bakterioplanktons. Diese Bakteriengruppen
wurden in der hier vorliegenden Arbeit nicht weiter untersucht, so dass über ihre
Abundanz, phylogenetische Diversität und saisonale Dynamik in den vier Untersuchungsgewässern nur wenig bekannt ist.
Durch die kontinuierliche Weiterführung der Probennahmen in den vier untersuchten Seen
von 2004 bis heute liegen Proben vor, mit denen die hier erzielten Ergebnisse bestätigt
und ergänzt werden können. Mit diesem Datensatz soll ein noch umfangreicherer Einblick
in die Diversität, Dynamik und Ökologie limnischer Bakteriengemeinschaften möglich
werden. Ausgehend von diesen Ergebnissen können neue Strategien entwickelt werden,
wie aquatische Bakteriengemeinschaften oder bestimmte Bakteriengruppen besser
nachgewiesen und charakterisiert werden können. Aufgrund der großen Diversität an
Mikroorganismen erscheint es jedoch als sinnvoll, zukünftige Studien auf einzelne und
dominante
Bakteriengruppen
zu
fokussieren.
Weiterhin
sollten
jahreszeitliche
Untersuchungen durch mehrere kleinere Studien ergänzt werden, die detaillierte Einblicke
in die Veränderungen und Anpassungen limnischer Bakteriengemeinschaften zu
bestimmten Zeitpunkten (z.B. Algenblüten) liefern.
117
Kapitel VI
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120
Danksagung
An erster Stelle möchte ich mich bei Hans-Peter Grossart bedanken, der mir diese Arbeit
überhaupt erst ermöglicht hat. Sein Vertrauen in meine Fähigkeiten und die Freiräume,
die er mir bei der Ausgestaltung des Themas gelassen hat, weiß ich sehr zu schätzen.
Dankbar bin ich auch für den immer freundschaftlichen Umgang, die vielen interessanten
Diskussionen und den inhaltlichen Ratschlägen, wann immer sie nötig waren. Mein Dank
gilt auch der von ihm geförderten Internationalität unserer Arbeitsgruppe. Der Austausch
mit
unseren
ausländischen
Gästen
und
die
Teilnahme
an
internationalen
Forschungsprojekten haben mir immer große Freude bereitet und sehr zur Bereicherung
meines Arbeitsalltages beigetragen.
Meinhard Simon danke ich für das stets große Interesse am Fortgang meiner Arbeit und
seiner
Hilfsbereitschaft
und
Unterstützung
bei
allen
wissenschaftlichen
und
organisatorischen Fragen, die sich im Zusammenhang mit dieser Arbeit ergeben haben.
Vielen Dank auch für die freundliche und unkomplizierte Übernahme des zweiten
Gutachtens dieser Arbeit!
Bedanken möchte ich mich auch ganz herzlich bei den vielen Kolleginnen und Kollegen,
die mich in den letzten Jahren begleitet und unterstützt haben. Mein besonderer Dank gilt
dabei unserer technischen Assistentin Elke Mach, die mit ihrer stets guten Laune immer
für eine angenehme und entspannte Arbeitsatmosphäre in unserem Labor gesorgt hat.
Danke auch für die vielen schönen und unterhaltsamen Stunden bei den Probennahmen
und für die Messung der unterschiedlichsten limnologischen Parameter! Ein großer Dank
geht auch an meine ehemalige Diplomandin Sarah Brückner, die bei der Entwicklung der
Actinobacteria-spezifischen DGGE und verschiedenen molekularbiologischen Analysen
eine große Hilfe war. Prof. Dr. Rainer Koschel, Dr. Lothar Krienitz und Dr. Peter Kasprzak
möchte ich ganz herzlich für die Bereitstellung der chemischen Daten so wie der Daten
zum Phytoplankton und Zooplankton danken, die für meine statistischen Analysen
unerlässlich
waren.
unerschöpflichen
Prof.
Dr.
Bemühungen
Rainer
Koschel
danken,
möchte
trotz
ich
zudem
manchmal
für
seine
komplizierter
Finanzierungssituationen immer einen Weg für die Fortsetzung dieser Arbeit geschaffen
zu haben.
Ein großes Dankeschön gilt auch allen Kolleginnen und Kollegen in Neuglobsow. Vielen
Dank für eure Hilfe und Unterstützung in (fast) allen Lebenslagen. Es war eine sehr
schöne Zeit mit euch zusammen am Stechlinsee, an die ich sicherlich noch lange
zurückdenken werde!
121
Ein herzliches Dankeschön möchte ich Kirsten Pohlmann aussprechen, die mir bei allen
statistischen Fragen und Problemen immer mit Rat und Tat helfend zur Seite stand.
Vielen Dank auch für das Korrekturlesen meiner Manuskripte!
Falk Warnecke und Jakob Pernthaler möchte ich ganz herzlich für die Einführung in die
CARD-FISH und die Bereitstellung der verschiedenen Oligonukleotidsonden danken.
Eure Unterstützung war eine große Hilfe für mich und hat sicherlich mit zum Gelingen
dieser Arbeit beigetragen.
Der Studienstiftung des deutschen Volkes und der Leibniz-Stiftung danke ich für die
Finanzierung dieser Arbeit.
Ein ganz besonderer Dank gilt meinen Eltern. Ihr habt immer zu mir gehalten und mich
unterstützt, wo es notwendig war. Ihr seid sehr wichtig für mich!
Nicht auszusprechen vermag ich den Dank an meine Verlobte Silke. Ihre Liebe und
Zuversicht haben mir immer wieder neue Kraft und Mut gegeben, so manches Tief zu
überstehen und diese Arbeit erfolgreich zu bewältigen. Danke Silke!
Zu guter Letzt danke ich meinen beiden Schwestern und allen meinen Freunden und
Bekannten, die mir während der gesamten Zeit immer zur Seite standen!
122
Lebenslauf
Persönliche Angaben:
Name:
Vorname:
Geburtstag:
Geburtsort:
Familienstand:
Staatsangehörigkeit:
Allgaier
Martin
20.12.1976
Böblingen
ledig
deutsch
Schulausbildung:
1983-1984
1984-1996
Michael Bauer Schule in Stuttgart (Freie Waldorfschule)
Freie Waldorfschule am Bodensee in Überlingen-Rengoldshausen,
Erhalt der Allgemeinen Hochschulreife
Zivildienst:
1996-1997
Zivildienst in der Altenpflege im Hesse-Diederichsen-Heim in
Hamburg
Universitätsausbildung:
10/1997-09/1999
09/1999
10/1999-12/2001
01/2002-10/2002
10/2002
Grundstudium der Biologie an der Technischen Universität
Braunschweig
Vordiplom in Biologie an der Technischen Universität Braunschweig
Hauptstudium der Biologie an der Technischen Universität
Braunschweig. Hauptfach: Mikrobiologie; Nebenfächer: Genetik,
Zoologie
Diplomarbeit im Fach Mikrobiologie an der Gesellschaft für
Biotechnologische Forschung (GBF) in Braunschweig. Titel der
Arbeit: „Anreicherung, Kultivierung und molekularbiologische
Charakterisierung phototropher mariner Proteobakterien“
Abschluss als Diplom-Biologe an der Technischen Universität
Braunschweig
Berufstätigkeit:
Seit 02/2003
03/2004-03/2006
26.04.-27.05.2003
03.-15.10.2004
09.05.-15.06.2005
Wissenschaftlicher
Angestellter
am
Leibniz-Institut
für
Gewässerökologie und Binnenfischerei (IGB) an der Außenstelle in
Neuglobsow
Promotionsstipendiat der Studienstiftung des deutschen Volkes
Teilnahme am „2nd Pelagic Ecosystem CO2 Enrichment Experiment“
(PeECE II) in Bergen/Norwegen.
Teilnahme an der German-Israeli Minerva School: „Identification
and quantification of metalimnetic processes in a subtropical lake –
Lake Kinneret as a case study“, am Yigal Allon Kinneret
Limnological Laboratory KLL (See Genezareth, Israel)
Teilnahme am „3rd Pelagic Ecosystem CO2 Enrichment Experiment“
(PeECE III) in Bergen/Norwegen.
123
Erklärung
Hiermit bestätige ich, dass ich die vorliegende Dissertation selbstständig verfasst und nur
die angegebenen Quellen und Hilfsmittel verwendet habe.
Neuglobsow, den 03. August 2006
125
Anhang
Anhang
Anhang
Im Folgenden sind die Ergebnisse aus den statistischen Analysen zusammengefasst, die
in den Manuskripten (vgl. Kapitel II-V) nicht weiter aufgeführt wurden. Tabelle A1 gibt
einen Überblick über alle in dieser Arbeit durchgeführten statistischen Berechnungen.
Neben Unterschieden in der statistischen Methode (lineare Regressionen vs. non-metric
multidimensional scaling, NMS) unterschieden sich die einzelnen Analysen hauptsächlich
in den jeweiligen Spezies-Datensätzen. So wurden zum einen absolute Abundanzen
(DAPI, CARD-FISH) von Bakterien bzw. einzelner Bakteriengruppen verwendet und zum
anderen Ergebnisse aus Diversitätsanalysen (DGGE-Profile). Die statistischen Analysen
wurden für alle Seen bzw. Wasserschichten separat durchgeführt. Zusätzlich wurden
vergleichende Datensätze verwendet, die Spezies-Daten und die entsprechenden
limnologischen Parameter der Epilimnia aller Seen enthielten. Mit diesen Analysen sollte
geklärt werden, ob es allgemeingültige Abhängigkeiten zwischen verschiedenen
Bakteriengemeinschaften und einzelnen limnologischen Parametern gibt. Die Ergebnisse
aus diesen vergleichenden Analysen sind in den Tabellen in der ersten Spalte unter
„EPIL“ dargestellt. Für alle Ergebnistabellen gilt, dass nur die Parameter aufgeführt sind,
die signifikante Abhängigkeiten zu den entsprechenden Spezies-Datensätzen zeigten.
Alle weiteren Parameter wurden der Übersicht halber nicht dargestellt.
Tabelle A1: Übersicht über alle in dieser Arbeit durchgeführten statistischen Analysen.
Statistik
Datensätze
Ergebnis
Spezies-Daten
Limnologische
Parameter
Lineare
Regressionen
Bacteria - Abundanzen
(DAPI)
alle Parameter*
Anhang;
Tabelle A4
NMS
Bacteria - Diversität
(DGGE)
15 Parameter**
vgl. Kapitel II;
Tabelle 5
Lineare
Regressionen
Actinobacteria - Abundanzen
(CARD-FISH)
alle Parameter*
Anhang;
Tabelle A2
NMS
Actinobacteria - Abundanzen
(CARD-FISH)
alle Parameter*
Anhang;
Tabelle A3
NMS
Actinobacteria - Diversität
(DGGE)
alle Parameter*
vgl. Kapitel IV;
Tabelle 3
* vgl. Kapitel IV; ** vgl. Kapitel II; NMS non-metric multidimensional scaling Analysen
129
Anhang
Tabelle A2: Lineare Regressionsanalysen zwischen Actinobacteria-Abundanzen und den
gemessenen limnologischen Parametern. In der Tabelle sind die R2-Werte mit den entsprechenden
Signifikanzniveaus (* P ≤ 0.05; ** P ≤ 0.01; *** P ≤ 0.001) aufgeführt. Es wurden separate
statistische Analysen für die: (A) gesamten Actinobacteria (HGC69a), (B) Actinobacteria des acIClusters (AcI-852), (C) Actinobacteria des acI-A-Subclusters (AcI-840-1) und (D) acI-B-Subclusters
(AcI-840-2) durchgeführt.
A
AcI-852 (acI)
AcI-840-1 (acI-A)
AcI-840-2 (acI-B)
Gesamtzellzahl
Temperatur
Leitfähigkeit
β-D-Glc.-Aktivität
NO2-N
NH4-N
Gesamt-N
Eisen
Silikat
Alkalinitätª
B
FNE
FSW
ST
ST-HL
TW
0.966***
0.244**
0.767***
0.162*
0.479***
0.978***
0.795**
0.696*
-
0.995***
0.903***
0.911***
0.896***
0.726*
0.788**
0.769*
0.645*
0.637*
N.D.
0.901***
0.746**
0.780*
N.D.
0.927***
0.714*
0.739*
0.993***
0.970***
0.972***
-
0.935***
0.720*
0.699*
0.571*
0.966***
0.303***
0.761***
0.185*
0.452***
0.978***
0.754*
0.716*
-
0.995***
0.916***
0.934***
0.653*
0.875**
0.636*
0.722*
0.784**
0.772*
N.D.
0.913***
0.852**
0.718*
N.D.
0.932***
0.823**
0.717*
0.830**
0.994***
0.956***
0.971***
N.D.
-
0.944***
0.689*
0.715*
0.674*
0.742*
0.691*
0.641*
0.529*
0.235**
0.292***
0.135*
-
0.664*
0.667*
0.681*
0.850**
0.737*
0.989***
0.646*
0.887***
0.895***
0.836**
0.555*
0.864**
0.657*
0.863**
N.D.
0.766*
N.D.
0.733*
-
0.961***
0.937***
0.920***
N.D.
N.D.
-
-
0.772***
0.765***
0.162*
0.163*
0.146*
0.471***
0.790**
0.742*
0.797**
-
0.903***
0.924***
0.847**
0.787**
0.867**
0.635*
N.D.
0.704*
0.806**
N.D.
0.776*
0.850**
0.775*
0.704*
0.980***
0.977***
0.957***
-
-
(AcI-840-1)
HGC69a
AcI-852 (acI)
AcI-840-2 (acI-B)
Temperatur
O2 [%]
Leitfähigkeit
BPP (PA)
BPP (gesamt)
PP (≥3.0 µm)
PP (≤3.0 ≥0.2 µm)
NO2-N
NH4-N
Gesamt-N
Alkalinitätª
D
BL
(AcI-852)
HGC69a
AcI-840-1 (acI-A)
AcI-840-2 (acI-B)
Gesamtzellzahl
Temperatur
Leitfähigkeit
Protease-Aktivität
PP (gesamt)
NO2-N
NH4-N
Gesamt-N
TOC
Alkalinitätª
C
EPIL
(HGC69a)
(AcI-840-2)
HGC69a
AcI-852 (acI)
AcI-840-1 (acI-A)
Gesamtzellzahl
Temperatur
Leitfähigkeit
NH4-N
Gesamt-N
Alkalinitätª
N.D. nicht bestimmt; ªAlkalinität wurde nur für den Stechlinsee, Breiten Luzin und Tiefwarensee bestimmt; β-D-Glc. β-DGlukosidase; BPP bakterielle Proteinproduktion; PA partikel-assoziierte Bakterien; PP Primärproduktion; TOC gesamter
organischer Kohlenstoff; EPIL Epilimnion; BL Breiter Luzin; FNE Große Fuchskuhle (Nordost-Becken); FSW Große
Fuchskuhle (Südwest-Becken); ST Stechlinsee (Epilimnion); ST-HL Stechlinsee (Hypolimnion); TW Tiefwarensee.
130
Anhang
Tabelle A3: Ergebnisse der non-metric multidimensional scaling (NMS) Analysen zwischen
Actinobacteria-Abundanzen und den gemessenen limnologischen Parametern. In der Tabelle sind
nur Parameter mit einem Pearson Produkt-Moment-Korrelationskoeffizienten von r ≥ 0.7 für die
ersten drei signifikanten Ordinationsachsen aufgeführt. Es wurden separate statistische Analysen
für die: (A) gesamten Actinobacteria (HGC69a), (B) Actinobacteria des acI-Clusters (AcI-852),
(C) Actinobacteria des acI-A-Subclusters (AcI-840-1) und (D) acI-B-Subclusters (AcI-840-2)
durchgeführt.
A
HGC69a
AcI-852 (acI)
Sichttiefe
Gesamtzellzahl
DOC
O2 [mg/l]
pH
PP (gesamt)
PP (≤20 µm)
PP (≥3 µm)
NO3-N
Gesamt-N
PO4-P
Gesamt-P
Eisen
Silikat
TOC
Alkalinität
Zooplankton
B
BL
FNE
FSW
ST
ST-HL
TW
-
-0.733
(1)
-0.707
(1)
-0.726
(1)
-0.717
-
(3)
(1)
-0.848
N.D.
-
(1)
0.756
(3)
-0.759
N.D.
-
(3)
-0.765
(2)
-0.715
(2)
-0.712
(2)
0.780
(1)
0.800
(3)
0.716
(2)
0.717
N.D.
N.D.
N.D.
N.D.
(2)
-0.807
(2)
-0.814
(1)
-0.862
N.D.
(2)
-0.706
(2)
-0.785
(2)
-0.725
(2)
0.854
-
-
0,740
(3)
0,701
(1)
-0,719
(1)
0,765
(1)
0,765
(3)
(2)
0,770
(2)
0,776
(2)
0,828
(2)
0,716
(3)
0,727
(2)
-0,784
-
(1)
-0,747
-
(3)
0,748
-
(1)
0,745
(1)
-0,863
(2)
0,722
N.D.
(3)
-0,838
N.D.
(1)
0,830
(2)
0,724
(2)
0,723
(1)
-0,838
-
-
(2)
0,753
(2)
-0,739
(3)
0,703
-
(1)
0,725
(1)
-0,772
(3)
0,720
(3)
0,718
(1)
-0,755
(1)
-0,779
(1)
-0,785
(3)
-0,755
(1)
0,705
-
(2)
0,939
(1)
0,761
(1)
0,738
(2)
0,782
-
-0,738
(2)
-0,729
(2)
-0,732
(2)
-0,703
N.D.
(2)
0,715
(3)
-0,745
(2)
-0,729
(3)
-0,740
(3)
0,736
N.D.
(2)
(3)
-0,740
-
(AcI-852)
HGC69a
AcI-852 (acI)
AcI-840-1 (acI-A)
Temperatur
O2 [mg/l]
O2 [%]
Protease-Aktivität
BPP (PA)
PP (≤20 µm)
NO2-N
NO3-N
NH4-N
PO4-P
Calzium
Eisen
Zooplankton
C
EPIL
(HGC69a)
(AcI-840-1)
HGC69a
AcI-852 (acI)
AcI-840-1 (acI-A)
AcI-840-2 (acI-B)
Sichttiefe
DOC
Temperatur
O2 [%]
pH
BPP (FL)
BPP (PA)
BPP (gesamt)
NH4-N
Gesamt-N
PO4-P
Gesamt-P
Calzium
Zooplankton
131
Anhang
D
EPIL
BL
FNE
-
(1)
0,783
(1)
0,711
(1)
-0,712
(1)
-0,766
(1)
-0,718
(2)
0,722
(1)
-0,788
0,708
(1)
0,718
(3)
-0,726
N.D.
-
FSW
ST
ST-HL
TW
(3)
-0,702
(1)
-0,722
(3)
0,748
(3)
0,722
N.D.
-
(1)
0,789
(1)
0,766
(1)
0,916
(1)
-0,702
(2)
-0,787
-
(2)
0,738
(2)
0,745
(2)
0,754
(1)
-0,729
(2)
0,742
(2)
0,790
(2)
0,802
N.D.
N.D.
(2)
-0,725
N.D.
N.D.
(3)
0,714
(1)
-0,714
-
(AcI-840-2)
AcI-852 (acI)
AcI-840-2 (acI-B)
Gesamtzellzahl
DOC
Temperatur
O2 [mg/l]
O2 [%]
pH
ß-D-Glc.-Aktivität
BPP (FL)
BPP (PA)
BPP (gesamt)
PP (gesamt)
PP (≤3.0 ≥0.2 µm)
NO3-N
PO4-P
Gesamt-P
Calzium
Alkalinität
Zooplankton
Phytoplankton
(1)
(2)
(1)
(3)
Ordinationsachse 1;
Ordinationsachse 2;
Ordinationsachse 3; N.D. nicht bestimmt; DOC gelöster organischer
Kohlenstoff; BPP bakterielle Proteinproduktion; PP Primärproduktion; FL frei-lebende Bakterien; PA partikel-assoziierte
Bakterien; β-D-Glc. β-D-Glukosidase; Abkürzungen für die Seen siehe Tabelle A2.
Tabelle A4: Ergebnisse aus den linearen Regressionsanalysen zwischen den absoluten
Bakterienzahlen und den gemessenen limnologischen Parametern. Die Tabelle zeigt die jeweiligen
R2-Werte mit den dazugehörigen Signifikanzniveaus (* P ≤ 0.05; ** P ≤ 0.01; *** P ≤ 0.001).
Sichttiefe
DOC
pH
O2 [mg/l]
O2 [%]
Protease-Aktivität
BPP (FL)
PP (≥3.0 µm)
NO2-N
NH4-N
Gesamt-N
Eisen
Silikat
Alkalinitätª
EPIL
BL
FNE
FSW
ST
ST-HL
TW
0.188*
0.415**
-
0.928***
N.D.
N.D.
0.791*
-
0.647*
0.769*
0.741*
0.699*
0.758*
0.709*
0.632*
N.D.
0.671*
0.797**
0.710*
0.714*
0.661*
0.682*
-
N.D. nicht bestimmt; ªAlkalinität wurde nur für den Stechlinsee, Breiten Luzin und Tiefwarensee bestimmt; DOC gelöster
organischer Kohlenstoff; β-D-Glc. β-D-Glukosidase; BPP (FL) bakterielle Proteinproduktion der frei-lebenden
Bakterienfraktion; PP Primärproduktion. Abkürzungen für die Seen siehe Tabelle A2.
132

Actinobacteria

Transcription

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