DNA techniques
Transcription
DNA techniques
Differentiating between live and dead bacteria in water samples using PMA-16S rDNA and 16S rRNA based sequence Li, 1 R. , Tun, 1Department 2 H.M. , Khafipour, 2,3 E. , 3,4 Kumar, A. , Fernando, 5 W.G.D. , 1 Farenhorst, A. of Soil Science; 2Department of Animal Science; 3Department of Medical Microbiology and Infectious Diseases; 4Department of Microbiology; 5Department of Plant Science; University of Manitoba, Winnipeg, Manitoba, Canada Introduction !!The limitation of DNA based techniques is the inability to differentiate live (vital) and dead (inactive) cells, which can lead to false positive results in the absence of live microbes in water [1,2]. !!Propidium monoazide (PMA) has been used for the selective removal of dead cells from downstream DNA applications [3,4]. !!Ribosomal ribonucleic acid (rRNA) can demonstrate active microbial cells in water as it is produced by metabolically active cells. •! Output paired-end reads were merged using PANDASeq !" assembler and analyzed using QIIME. #" Bioinformatics Mycobacterium smegmatis, Bacillus amyloquefaciens Dead Mycobacterium smegmatis, Bacillus amyloquefaciens and live E.coli, Yersinia enterocolitica Dead •! Multivariate data analysis [Prinicpal Co-ordinate Analysis (PCoA), PERMANOVA] was done for detecting differences for beta-diversity. P < 0 .05 was considered significant. $" Statistics Results !!The efficiencies of RNA and PMA-DNA based methodologies to discriminate live and dead cells of bacterial community are shown in Figure 1 and Table 1. E.coli, Yersinia enterocolitica, and Mycobacterium smegmatis, Bacillus amyloquefaciens 1 !" #" Different water sources !!For both the lake and river water, the bacterial profile was significantly different between the DNA and RNA based $" methods (P = 0.10), but not the DNA and PMA-DNA methodologies. For treated water (plant, piped, cistern), the bacterial profile was similar for the RNA, DNA and PMADNA methods (Table 2). live 1 Comparison Group DNA vs. RNA DNA vs. PMA P (MC) 0.34 0.06 DNA vs. RNA 0.05 DNA vs. PMA 0.29 DNA vs. RNA DNA vs. PMA 0.09 0.37 DNA vs. RNA DNA vs. PMA 0.13 0.13 P-values based on Montel Carlo test Table 2. Permutation Montel Carlo test unweighted unifrac distance of different water source using DNA based, RNA based and PMA-DNA based methodologies Water source Comparison Groups P (MC) DNA vs. PMA 0.37 First Nations Cistern DNA vs. RNA 0.13 DNA vs. PMA 0.26 First Nations Tap DNA vs. RNA 0.15 First Nations DNA vs. PMA 0.37 DNA vs. RNA 0.10 Source Water DNA vs. PMA 0.33 Winnipeg Tap DNA vs. RNA 0.22 DNA vs. PMA 0.61 Red River DNA vs. RNA 0.11 Discussion !!In this study, we found that RNA method were more reliable than PMA-DNA in differentiating live/dead bacterial cells in both spiked water and different water sources. The efficiency of PMA-DNA method in detecting live bacterial could be affected by several factors, such as the concentration of PMA dye, the PMA incubation time and temperature. RNA is only produced by metabolically active cells, making RNA suitable to detect live bacterial cells. Extraction of DNA, RNA and PMA-DNA from spiked water and water samples !!Spiked water (100 mL) and water samples (500 mL) were filtered through 0.20µm, 47nm polyethersulfone filter. DNA and RNA were extracted. RNA was transcripted to cDNA. !!Filtered-based PMA-DNA was extracted as described by Hellein et al. (2012) and Nocker et al. (2010) !!The library of V4 amplicons of 16S rRNA constructed and subjected to 300 cycle paired-end MiSeq Illumina sequencing [5]. Dead E.coli, Yersinia enterocolitica, •! Alpha- & beta-diversity of microbial communities were determined. !!To compare the efficiency of PMA-based 16S rDNA versus 16S rRNA sequencing in detecting live bacterial cells in different water samples. !! Water was spiked with two Gram positive strains Mycobacterium smegmatis, Bacillus amyloliquefaciens strain BS6, and two Gram negative strains E. coli, Yersinia enterocolitica in the following treatments: A) all live strains, B) all dead strains, C) live negative strains + dead positive strains, and D) live positive strains + dead negative strains. !!Water samples were collected in a fly-in First Nations community in Manitoba from a lake, the water treatment plant, piped tap water and cistern water. Piped tap water and river water (Red River) were also collected in the City of Winnipeg, Manitoba. Mycobacterium smegmatis, Bacillus amyloquefaciens •! The resulting operational taxonomic units were aligned at 97% similarity threshold to green-genes database. Spiked water Water samples Treatment Live E.coli, Yersinia enterocolitica, •! Demulitiplexing merged reads, quality check and chimera detection and filtering was done in QIIME. Objective Materials and Methods Table 1. Permutation Montel Carlo test unweighted unifrac distance of spiked water using DNA based, RNA based and PMA-DNA based methodologies Acknowledgements !!We gratefully acknowledge the Natural Sciences and Engineering Council of Canada (NSERC) for provided research funding to complete this study. References Figure 1. PCoA analysis of unweighted unifrac distances showing bacterial composition variations in the spiked water among DNA based, RNA based, and PMA-DNA based profiles. A) all live strains, B) all dead strains, C) live negative strains + dead positive strains, and D) live positive strains + dead negative strains. create-h2o.ca 1. Paul,Jh., Jeffrey, WH., David,AW., et al. 1989. Appl. Envrion. Microbiol. 55: 1823-1828 2. Dupray, E, Caprais, MP, Derrien,A, Fach, P. 1997. J. Appl. Microbiol. 82: 507-510 3. Hellein, KN, Kennedy, EM, Harwood, VJ, Gordon, KV, Wang, SY, Lepo, JE. 2012. J. Microbiol. Methods. 89: 76-78. 4. Nocker, A., Cheung, CY., Camper, AK., 2006. J. Microbiol.Methods 67, 310-320. 5. Caporaso, JG, Kuczynski, J, Stombaugh, J, Bittinger, K, Bushman, FD, Costello, EK, et al. 2010. Nature methods. 7(5): 335-336. UNIVERSITY Gut Microbiome and OF MANITOBA Large Animal Biosecurity Laboratories