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Bioanalysis of Protein Biopharmaceuticals
by Lucia Baljeu-Neuman
MSc Chemistry
Analytical Sciences
Master Thesis
Bioanalysis of Protein Biopharmaceuticals
Based on Signature Peptides
by Liquid Chromatography-Tandem Mass Spectrometry
Somatropin Quantification Using Bovine Fetuin as Internal Standard
by
Lucia Baljeu-Neuman
January 2016
Research performed between 15th of January and 15th of August 2015
Daily Supervisor:
dr Erik Baltussen
Examiner:
dr Wim Th. Kok
Bioanalysis Department / WIL Research Europe
ACKNOWLEDGEMENTS
I would like to thank Henk Lingeman, PhD, for recommending WIL Research Europe
to conduct my research.
My sincere thanks goes to Theo Noij, PhD, who provided me the opportunity to join
WIL Research Europe in Den Bosch as intern and to Erik Baltussen, PhD, who kindly
guided and advised me during the whole project.
I would also like to thank Daphne de Ruijter and the Bioanalysis team for their precious
assistance and constant support in the laboratory. In addition, I would like to thank the
personnel of WIL Research Europe for being so collegial and friendly.
My sincere thanks also goes to Chris de Koster, PhD, for guiding my first steps in protein
research and to Wim Kok, PhD, for taking over the guidance of my research and helping to
finalise this thesis.
1
SUMMARY
Protein biopharmaceuticals are large, heterogeneous molecules produced via recombinant
DNA technology. Protein biopharmaceuticals can be divided into therapeutic proteins and
monoclonal antibodies. Some of these are used to treat diseases which affect a large
number of people like cancer, diabetes and anaemia, while others are used in the treatment
of rare diseases like Pompe disease or Hunter’s syndrome.
Nowadays, the number of approved protein biopharmaceuticals is increasing rapidly.
Moreover, the patents for some of the protein biopharmaceuticals have expired and others
will expire in the next years, therefore a large increase in the number of biosimilars is
expected in the coming years.
WIL Research Europe in Den Bosch, The Netherlands, is an independent laboratory which
conducts a variety of toxicological, (bio)analytical chemistry, metabolism and
pharmaceutical studies. Although protein analysis is not part of the current portfolio, there is
considerable interest to implement this technology. Therefore, the aim of this research
project was to investigate the possibility of setting up a generic method for protein analysis
based on surrogate peptides using Liquid Chromatography coupled to tandem
Mass Spectrometry (LC-MS/MS). Surrogate peptides, also called signature peptides, are
the result of the enzymatic digestion of targeted proteins. These proteins are first
denaturated, reduced and alkylated to enhance the effectiveness of the proteolysis.
Subsequently, these peptides are separated using liquid chromatography and identified by
tandem mass spectrometry.
In this thesis a sample preparation protocol is presented, without a purification step of the
protein or surrogate peptides, that can be used as a generic sample pre-treatment for
LC-MS/MS protein biopharmaceuticals analysis based on surrogate peptide(s). This study
has focused on the analysis of transferrin, somatropin and bovine fetuin in human plasma
to demonstrate the applicability of the generic protocol for a select number of proteins.
Furthermore, the generic sample preparation has been optimised and made
cost-effective. Finally, the LC-MS/MS method for somatropin quantification using bovine
fetuin as internal standard has been validated according to the principles of bioanalytical
method validation of the Food and Drug Administration (FDA) and European Medicine
Agency (EMA).
2
CONTENTS
ACKNOWLEDGEMENTS ........................................................................................................................ 1
SUMMARY ............................................................................................................................................... 2
CONTENTS ............................................................................................................................................. 3
1. INTRODUCTION .............................................................................................................................. 4
1.1. Proteins ................................................................................................................................. 4
1.1.1. Structure and Functions of Proteins ......................................................................... 4
1.1.2. Post-translational Modifications ................................................................................ 5
1.1.3. Proteins in Clinical Diagnostics ................................................................................ 6
1.2. Biopharmaceuticals ............................................................................................................... 6
1.2.1. Description of Protein Biopharmaceuticals ............................................................... 7
1.2.2. Characteristics of Protein Biopharmaceuticals ......................................................... 7
1.2.3. Protein Biopharmaceuticals in Pharmaceutical Industry .......................................... 8
1.3. Protein Analysis .................................................................................................................... 9
1.3.1. Intact Protein Analysis .............................................................................................. 9
1.3.2. Peptide Analysis ....................................................................................................... 9
1.3.3. Method Validation ................................................................................................... 12
2. EXPERIMENTAL DATA ................................................................................................................. 13
2.1. Chemicals and Materials ..................................................................................................... 13
2.2. Preparation of the Stock Solutions, Calibration Standards and Quality Controls ............... 13
2.3. Equipment and Software ..................................................................................................... 14
2.4. Sample preparation ............................................................................................................. 14
2.4.1. Protein Denaturation ............................................................................................... 14
2.4.2. Protein Reduction and Alkylation............................................................................ 15
2.4.3. Protein Proteolysis .................................................................................................. 15
2.5. Surrogate Peptides Identification and Selection ................................................................. 15
2.5.1. Surrogate Peptides Identification by Direct MS Infusion ........................................ 15
2.5.2. Surrogate Peptides Identification by Importing MS-settings from Skyline ............. 18
2.5.3. Signature Peptide Selection ................................................................................... 18
2.6. LC-MS/MS Method ............................................................................................................. 18
3. RESULTS ....................................................................................................................................... 21
3.1. Protein Denaturation Using Five Different Denaturation Agents ........................................ 21
3.2. Protein Digestion Using Different Qualities and Quantities of Trypsin ............................... 21
3.3. Protein Digestion at Different Temperature and Incubation Time ...................................... 22
3.4. Surrogate peptides identification and selection .................................................................. 24
3.5. Method Validation ............................................................................................................... 25
4. DISCUSSION ................................................................................................................................. 26
5. CONCLUSIONS ............................................................................................................................. 28
LIST OF ABBREVIATIONS ................................................................................................................... 29
APPENDIX 1. HUMAN SERUM TRANSFERRIN - GENERAL FACTS, FASTA SEQUENCE
AND STRUCTURE......................................................................................................................... 30
APPENDIX 2. (RECOMBINANT) HUMAN GROWTH HORMONE - GENERAL FACTS, FASTA
SEQUENCE AND STRUCTURE ................................................................................................... 31
APPENDIX 3. BOVINE FETUIN - GENERAL FACTS, FASTA SEQUENCE AND STRUCTURE ........ 32
APPENDIX 4. METHOD VALIDATION: SOMATROPIN QUANTIFICATION USING BOVINE
FETUIN AS INTERNAL STANDARD AND LC-MS/MS ANALYSIS ............................................... 33
REFERENCES ...................................................................................................................................... 40
3
1.
INTRODUCTION
1.1. Proteins
All living cells and viruses contain proteins.1 Proteins are macromolecules produced inside
the ribosomes of living cells. Proteins are made of amino acids linked through amide bonds
as coded in the DNA. There are thousands of different proteins in the human body.2
For example, structural proteins, enzymes, hormones, antibodies, receptors or channels in
the cell membrane, transporters of vitamins, metal ions or drugs. Proteins have a vital role
in nearly all biological processes.2,3 The structure, functions and post-translational
modifications of proteins are described below, followed by a brief presentation of the role of
proteins in clinical diagnostics.
1.1.1.
Structure and Functions of Proteins
The structural entities of proteins are α-amino acids. These are amino acids which have the
amino-group and the carboxyl-group linked at the same carbon atom, known as the
α-carbon atom. Amino acids form peptide bonds by covalently linking the α-amino group of
one amino acid with the α-carboxyl-group of the next amino acid. The formed chain is
known as a peptide. Proteins are made of one or several peptides. The difference between
proteins and peptides is that proteins wield certain functions, as a result of their
three-dimensional structure.1 Many proteins contain besides amino acids other compounds
(prosthetic groups), such as carbohydrates, lipids or metal complexes. These proteins are
known as conjugated proteins.1,2
The amino acid sequence is called the primary structure of protein. This arrangement gives
the protein its uniqueness. Therefore, even a single amino acid modification can change the
characteristics of a protein. For example, by replacing glutamic acid with valine in the
hemoglobin molecule, sickle-cell anemia, an inherited disorder of the blood cell occurs.1
Glutamic acid is a polar amino acid while valine is a nonpolar, hydrophobic amino acid.
Therefore, hemoglobin’s properties, shape and function are altered. This abnormal
hemoglobin, known as hemoglobin S, congregates and forms long, rigid and sickle shaped
cells. These can block the capillaries, producing severe pain, physical weakness and
damage to the vital organs.1
Once the primary chain is formed, it spontaneously folds and twists due to the
hydrogen-bond interactions. This two-dimensional arrangement of the backbone atoms is
known as the secondary structure of a protein. The most common secondary structure
arrangements are the α-helix and β-pleated sheet. The interactions of the side chains,
namely hydrogen-bonds, ionic-bonds, disulphide-bonds and hydrophobic interactions, give
a protein its characteristic three-dimensional shape, the tertiary structure. Additionally,
proteins may have a quaternary structure. This fourth level of structure involves the
association of two or more subunits into a larger assembly. The folded structure, also
known as the native state, is commonly the most stable arrangement of proteins.1
Proteins can be classified, based on their shape, as globular protein or fibrous proteins.
Globular proteins have a compact spherical shape. The amino acids with nonpolar side
groups are situated inside the folded structure, while the amino acids with polar side groups
are placed on the outer surface. These proteins, such as, enzymes, hormones or plasma
proteins, are water-soluble and usually mobile within the cell. Their function is mainly
regulatory. Examples include transport mechanisms, storing oxygen, catalysing biochemical
reactions, regulating the metabolism and protecting against infections. Globular proteins are
stable over a narrow pH and temperature range. In case of higher temperature or extreme
pH, proteins can be denaturated. Protein denaturation can be reversible or irreversible.
A denaturated protein loses its three- and two-dimensional structure and thus its
function(s).
4
Fibrous proteins, which include collagen, keratin, fibrinogen, troponin and myosin, have a
long, fibrillar shape, are water-insoluble and have mostly structural functions. These
proteins are more stable when changes in pH or temperature occur. Fibrous proteins
provide the structural integrity and strength to cells and tissues.1,2
The specific function of a protein is correlated with its structure. As mentioned above,
changes in the primary structure of a protein alter its biological activity. Moreover,
modifications in protein structure may also occur during the folding process. It is assumed
that the mad cow disease (Bovine Spongiform Encephalopathy) and Creutzfeldt–Jakob
disease, the human equivalent, are caused by a protein misfolding. The prion-related
protein (PrP), which occurs in the cell membranes of nerve tissues, has a large percentage
of α-helix in its structure, while the misfolded form has a large percentage of β-pleated
sheets. These β-pleated sheets aggregate forming insoluble clusters (plaques).
The plaques are usually formed in brain tissue and have severe consequences, such as
nerve degeneration, mental deterioration, dementia, and even death.4
1.1.2.
Post-translational Modifications
Post-translational modification (PTM) is a generic name for protein modification that takes
place after its translation by ribosomes.5 As mentioned before, in paragraph 1.1.1, proteins
are synthesized from amino acids. There are twenty primary amino acids used in protein
synthesis. However, due to the PTMs, circa 140 amino acids and amino acids derivatives
have been found in the structure of different proteins.5,6 PTMs can occur by peptide bond
cleavage or by addition of one or more functional groups. These modifications can take
place at the amino terminus, carboxyl terminus or at the amino acid level. Some
modifications can be spontaneous (e.g. deamidation, cysteinylation), while other are
catalyzed by enzymes (e.g. glycosylation, phosphorylation).6,7 Moreover, PTMs can be
reversible or irreversible, rapid (e.g. phosphorylation – dephosphorylation, the on-off switch
of many enzymes) or slow (e.g. glycosylation), independent or inter-dependent
(e.g. ubiquitylation, protein degradation, follows phosphorylation).5,6,7 Other examples of
post-translational modifications are methylation, acetylation, acylation, sumoylation,
glycation, and oxidation. It is estimated that more than 300 various PTMs are involved in
the cellular activity.7
PTMs regulate protein structure as well as its functions. One protein can undergo various
modifications in order to fulfill its functional role.7 These modifications take place at specific
sites. For example, phosphorylation, the addition of a phosphate group, takes place on
serine, tyrosine or threonine residues while glycosylation, the addition of a glycan moiety,
can occur on asparagine (N-glycosylation), serine or threonine (O-glycosylation).
Moreover, N-glycosylation requires asparagine (N) residue to be in the vicinity of threonine
(T) or serine (S) residue, as in the sequence –N–X–T/S– and O-glycosylation requires the
following sequence –R–X–Y–Z–S(Z)–S/T, where R is arginine and X, Y, Z may be any
amino acid residue.5 It is estimated that 50-90% of human proteins are modified after
translation.6
PTMs regulate protein activity. It can be proven that in case of PTM deviations, these
activities are also disturbed. For example, Congenital Disorders of Glycosylation (CDG) are
inherited metabolic disorders that are caused by glycosylation defects. By means of
underglycosylation or by the presence of abnormal glycans the whole organ system and
cellular functions are affected.8
5
1.1.3.
Proteins in Clinical Diagnostics
In clinical diagnostics, the study of proteins is used for early detection, diagnostic and
therapeutic purposes. By studying the expression of proteins in living cells, reliable data on
the health of patients may be revealed. For example, newborn screening allows the
detection of phenylketonuria (PKU) disease before its clinical symptoms. PKU, a metabolic
disease, is caused by the deficiency of a specific enzyme, namely phenylalanine
hydroxylase. This leads to the accumulation of phenylalanine in blood and tissues and
untreated leads to mental retardation.9 Other proteins are produced only in case of
diseases and are used as biomarkers for diagnosis. Furthermore, there is a variation of
protein concentration between health and disease.2
Plasma is one of the most used biological fluids in clinical diagnostics. The concentration of
proteins in plasma is high, approximately 75 mg/mL.3 Albumin covers approximately 50% of
the plasma proteins, and together with the other abundant proteins, which include
immunoglobulins, fibrinogen, transferrin and apolipoproteins, represents circa 95% of the
total protein content.3 Consequently, the variation in protein abundance might be up to
10 orders of magnitude.3,10 The most abundant proteins may mask the least abundant
proteins making their detection problematic.3 In addition to plasma, proteins of clinical
significance are measured in serum, urine, saliva, cerebrospinal fluid, amniotic fluid or
feces.2
For clinical diagnostics various analytical methods are used. These can be screening tests,
used to identify a disease before its symptoms occur, quantitative tests, used for diagnosis
confirmation and for monitoring treatment, or specific tests, used in the diagnosis of specific
disorders.2 The utilized techniques can be categorised in immunochemical, electrophoretic,
spectrophotometric and mass spectrometric.2 The analytical methods used for routine testing
have to be relatively simple and low-cost, fast and robust. More information about protein
analysis is given in section 1.3.
1.2. Biopharmaceuticals
Biopharmaceuticals, also known as biologicals or biological medicines, are medicines
containing biological material, such as proteins, DNA or RNA.11 Different types of cells or
organisms may be used, namely bacteria, yeasts, plants or genetically modified
animals.12,13 Their selection is based generally on production costs and on the possibility to
induce specific protein modifications. For example, the glycosylation pattern is not the same
in different biological systems and bacteria do not produce glycosylation.12
The first biologic approved by US Food and Drug Administration (FDA) was human insulin
(Humulin) in 1982. This has been produced in the Escherichia coli bacteria, via recombinant
DNA technology.11 Meanwhile, hundreds of different biopharmaceuticals have been
authorised for use.14
Some biopharmaceuticals are used to treat high incidence diseases like cancer, diabetes
and anaemia. Other biopharmaceuticals, so-called orphan drugs, are used in the treatment
of rare diseases which affect only a small number of the population, such as Pompe
disease or Hunter’s syndrome.11,14 The biological materials included in biopharmaceuticals
can be proteins, carbohydrates or nucleic acids.13 The research described in this thesis
focuses on protein based biopharmaceuticals.
6
1.2.1.
Description of Protein Biopharmaceuticals
Protein biopharmaceuticals are not necessarily novel medicines. For example, insulin was
extracted from animal sources in the early 1920s and used to treat diabetes.13 Nowadays,
the term ‘protein biopharmaceuticals’ refers generally to recombinant proteins.
Protein biopharmaceuticals may be classified into therapeutic proteins or monoclonal
antibodies (mAbs).13,14 Their activity can be exerted by different mechanisms. For example,
by binding non-covalently to a target, like mAbs, by affecting covalent binding, like
enzymes, or by non-specific interactions, like serum albumin.15 Furthermore, protein
therapeutics can replace deficient or abnormal proteins, enhance an existing process,
provide novel function or activity, target a specific molecule or organism or deliver other
compounds (e.g. cytotoxic drug, radioactive nuclide) to the target.3,15
During the last few years, the performance of protein biopharmaceuticals has been
improved. For example, the 1989 original version of Epoietin (EPO), used in the treatment
of anaemia in kidney dialysis patients, has been modified creating the second (2001) and
the third generation EPO (2007). The second generation has two extra N-glycosylation sites
and the third generation is conjugated to polyethylene glycol (PEG). These modifications
have enhanced the half-life and biological activity of EPO.14 Furthermore, to reduce
immunogenicity and to increase efficacy of the biopharmaceuticals, chimeric, humanised or
fully human gene sequences have replaced the purely murine sequences.3,13,14
1.2.2.
Characteristics of Protein Biopharmaceuticals
Protein biopharmaceuticals are complex macromolecules. As a result, their production,
purification and long-term storage is challenging. One reason is that by cloning one protein
a substantial number of species may be formed. Due to the co- and post-translational
modifications which are taking place in the host cell, beside the expected cloned protein,
other products are also produced. Therefore, exact copies cannot be created and
batch-to-batch differences are generally present.14
Compared with small molecule drugs, biopharmaceutical production is more complex.
In the case of small molecules, it is possible to produce exact copies of the original,
so-called generic drugs or generics. In the case of biopharmaceuticals, it is not possible to
produce identical products, but similar ones, i.e. biosimilars. In order to be accepted as a
biosimilar medicine, it needs to have the same safety and efficacy profile as the reference
product.11 One example which illustrates how difficult the production of biosimilars is,
is presented further on. Genzyme, one of the leading biotech companies, produces
acid-α-glucosidase, an enzyme used in the treatment of Pompe disease, and
commercializes it under the name Myozyme. To scale-up the production of Myozyme, the
capacity of the bioreactor had been increased from 160 L to 2000 L. The glycosylation of
the end product has been so different that US FDA did not approve it as being biosimilar.
For this product the company had to apply for a new Biologics License Application (BLA).
The new biological has been commercialized under the name Lumizyme.14
Another reason which makes working with biopharmaceuticals challenging is that these can
undergo undesirable modifications during production, purification and depositing. These
modifications can be enzymatic and/or chemical. Regarding product safety and efficacy, the
alterations might be critical and non-critical.14
Protein biopharmaceuticals have several advantages over small-molecule drugs.
For example, protein biopharmaceuticals act highly specific, interfere less with other
biological processes, therefore less side effects are caused. Moreover, therapeutic proteins
can provide replacement for absent or dysfunctional proteins and are better tolerated
because of the similarity with own proteins.12 In addition, protein biopharmaceuticals have a
relatively long serum half-life, therefore they do not have to be administrated daily.13
7
Protein biopharmaceuticals are strictly examined with regard to purity, molecular identity
(primary sequence, PTMs, chemical modifications), structure (cysteine bridges, protein
folding), quantity, physicochemical properties (thermal stability, solubility, aggregation,
degradation), activity (receptor binding, cell-based activity, enzyme activity),
pharmacokinetics (ADME, serum half-life concentration) and pharmacodynamics (toxicity,
effectiveness). Currently, chromatography and mass spectrometry are the leading methods
for protein biopharmaceutical analysis. However, these methods are complemented with
other techniques such as capillary electrophoresis, isoelectric focusing, nuclear magnetic
resonance, analytical ultracentrifugation, asymmetric flow field fractionation, differential
scanning calorimetry, X-ray crystallography, circular dichroism, fluorescence and
FTIR spectroscopy. The analysis of biopharmaceuticals can be performed at the protein
level (intact protein or large fragments), peptide level, glycan level or at the amino acids
level.14
1.2.3.
Protein Biopharmaceuticals in Pharmaceutical Industry
The number of approved protein biopharmaceuticals is increasing rapidly. Nowadays, the
protein biopharmaceuticals market is evaluated at about 20% of the worldwide
pharmaceutical market. Moreover, it is expected that biologicals will cover more than
50% of the new approved drugs in the next ten years.14 Most of the biopharmaceuticals on
the market are recombinant proteins. In addition, newly engineered proteins are in
development. Among these, multi-specific fusion proteins, proteins with improved
pharmacokinetics, brain penetrant antibodies, antibody mixtures and antibody-drug
conjugates (ADC).14
In 2013, the three best-selling drugs were adalimumab (Humira), infliximab (Remicade) and
rituximab (Rituxan/MabThera), monoclonal antibodies (mAbs) used to treat arthritis.16
Also, from the top 8 best-selling drugs, in the same year, 7 were biopharmaceuticals and
8 of the top 15 were biologicals as well. Among them, the monoclonal antibodies
Trastuzumab (Herceptin), for treatment of breast cancer, and bevacizumab (Avastin) for
colorectal, lung and kidney cancer.16 The best-selling therapeutic proteins had been insulin
glargine (Lantus) for diabetes and pegfilgrastim (Neulasta) for neutropenia (granulocyte
disorder).16 The complete list of these best-selling protein biopharmaceuticals is given in
Table 1. The patents for some of the biologics have expired and others will expire in a few
years, therefore a large increase in the number of biosimilars is expected in the coming
years.14
Table 1
16
Top 8 blockbuster biologicals in 2013 (reproduced from )
Brand
name
Humira
Remicade
Rituxan/
MabThera
Active ingredient
Type
Treatment
Company
adalimumab
infliximab
rituximab
mAb
mAb
mAb
Abbott/Eisai
Merck/Mitsubishi
Roche/Biogen-Idec
Enbrel
Lantus
Avastin
Herceptin
etanercept
insulin glargine
bevacizumab
trastuzumab
mAb
protein
mAb
mAb
Amgen/Pfizer/Takeda
Sanofi
Roche
Roche
Feb 2015/Nov 2028
2014/2014
Jan 2022/Jul 2019
Jul 2014/Jun 2019
Neulasta
pegfilgrastim
protein
arthritis
arthritis
arthritis,
nonHodgkin’s
lymphoma
arthritis
diabetes
cancer
breast
cancer
neutropenia
Patent expiry
EU/US
Apr 2018/Dec 2016
Aug 2014/Sep 2018
Nov 2013/Dec 2018
Amgen
Aug 2017/Oct 2015
8
1.3. Protein Analysis
Protein analysis includes various separation methods, purification techniques and analyses
that reveal their identity, characteristics, modifications, purity or quantity. These methods
are either gel methods (e.g. SDS-PAGE, capillary gel electrophoresis) or non-gel methods
(e.g. off-gel electrophoresis, microarrays, chromatography, mass spectrometry).
In turn, these methods may be fluorescent, metabolic, chemical or enzymatic labeled or
non-labelled.
Protein properties (physical, chemical, biochemical) play an important role in their analysis.
For example, their high molecular weight is used to separate them from smaller molecules
by dialysis, ultrafiltration, gel filtration chromatography and density-gradient
ultracentrifugation. The ability to bind to specific antibodies, coenzymes, or hormone
receptors has been used for immunochemical assays and affinity chromatography.
Other important properties used in protein analysis are differential solubility, adsorption to
surfaces, electrical charge, enzymatic activity and predisposition to chemical or
enzymatic digestion.2
Nowadays, due to the technical developments, liquid chromatography combined with
tandem mass spectrometry (LC-MS/MS) is largely used in protein and biopharmaceuticals
analysis.3,14 LC-MS/MS allows protein quantitation for which an immunoassay is not
available. Moreover, the methods are highly selective, accurate and precise within a
widespread dynamic range.3 Mass spectrometry has been used to analyse intact proteins
(top-down analysis) or peptides (bottom-up analysis). These two main approaches are
presented in the following sections.
1.3.1.
Intact Protein Analysis
Intact protein analysis, also known as top-down analysis, refers to examination at the
protein level. Top-down MS analysis is used for molecular weight, protein sequence and
PTMs (number, position and nature) determination. However, the size of analytes usually
causes complications. For example, the fragmentation is less predictable and high mass
resolution instruments are required (e.g. FT-ICR, TOF or orbitrap-MS).7,14 Furthermore, the
software for data analysis is less advanced as the one for peptide analysis. Despite its
limitations, top-down analysis offers important information about the protein’s purity,
aggregation, fragmentation, and high order structures.7 Furthermore, tissues can be
visualized using mass spectrometry. For example, MALDI-TOF MS was used to identify
microbes17 and mass spectrometry imaging (MSI) has been used in clinical research for
biomarkers discovery, imaging endogenous metabolites and neurotransmitters, and for
molecular detail inside the tumor.10,18
1.3.2.
Peptide Analysis
Protein analysis at the peptide level is also known as bottom-up analysis or peptide
mapping. In this approach, the proteins are first enzymatic digested. Then the specific
peptides, also called signature peptides or surrogate peptides, are quantified. Finally, the
concentration is extrapolated to the protein level. 3,19 Therefore, the peptide formation is a
crucial step for the bottom-up protein analysis. Before LC-MS/MS analysis the surrogate
peptides may be purified and enriched to enhance the sensitivity and selectivity of the
method.
A variety of pre-treatment methods for the peptide analysis are described in the literature.
These consist usually of the following four steps: protein denaturation, reduction, alkylation
and enzymatic digestion, as shown in Figure 1 and discussed further on.
9
Protein denaturation can be defined as the unfolding of the protein. As a result, the access
of enzymes to the protein cleavage sites is facilitated.3,20,21 As mentioned before, in
paragraph 1.1.1, the folded structure of proteins depends on various interactions, therefore
protein denaturation can be performed in numerous ways. For example, Proc et al. (2010)
used 14 combinations of heat, organic solvents (acetonitrile, methanol, trifluoroethanol),
surfactants (SDS, sodium deoxycholate) and chaotropic agents (guanidine, urea) to
determine the optimum for 45 plasma proteins digested with trypsin. Nowadays, RapiGest,
a surfactant patented and introduced in 2002 by Waters, is one of the widely used
denaturation products for in-solution enzymatic protein digestions. This surfactant improves
enzymatic digestion and can be easily removed by centrifugation.21 The effect of different
denaturation agents on the peptides forming was investigated in this study as well.
DENATURATION (protein unfolding)
heat
organic sovents (ACN, MeOH, CF3CH2OH)
surfactants (RapiGest, SDS, Na deoxycholate)
chaotropic agents (urea, guanidine HCl)
REDUCTION (breaking the disulfide bonds)
DTT
30-60 min at 50-60⁰C
ALKYLATION (preventing the disulfide bonds (re)formation)
IAA
30-120 min at RT, in the dark
TRYPSIN DIGESTION (peptide forming)
enzyme:protein ratio 1:20 - 1:100
overnight, at 37⁰C
Figure 1. General protein sample pre-treatment steps for in-solution trypsin digestion.
Protein reduction facilitates the access of the enzyme to the cleavage sites by breaking the
existing disulfide bonds. It is generally accomplished by using an 1,4-dithiothreitol (DTT)
solution. Other reduction agents, like β-mercaptoethanol and tris(2-carboxyethyl)phosphine
are also mentioned in literature.22 After reduction, the thiol groups (SH) have to be derivatised
in order to avoid oxidation, renaturation and formation of new disulfide bonds. The
derivatisation is usually done by alkylation with iodoacetic acid or iodoacetamide (IAA).3,20,22
Proteins can be digested by different types of enzymes which cleave at specific amino
acids. For example, trypsin generates peptides after cleavage at the carboxyl side of
arginine (R) or lysine (Lys, K), if not followed by proline (P), endoproteinase Lys-C cleaves
on the C-terminal side of lysine, endoproteinase Glu-C cleaves on C-terminal of glutamic
acid (Glu, E) and aspartic acid (D), chymotrypsin cleaves on C-terminal of tyrosine (Y),
tryptophan (W) and phenylalanine (F), if not followed by proline, and endoproteinase Asp-N
cleaves at the N-terminal of aspartic acid (Asp, D).3,14
10
In addition, the quality and quantity of the enzymes determine the efficiency of the protein
digestion. Trypsin is commercialised in different formulations, such as proteomics grade
and trypsin suitable for cell culture. Proteomics grade trypsin is highly purified and its lysine
residues are methylated to prevent autolysis. Moreover the specific activity is about five
times higher than the activity of the trypsin suitable for cell culture.23,24
Therefore, proteomics grade trypsin is mostly used for in-solution protein digestion. Further,
an enzyme:protein ratio of 1:20 to 1:100 is generally used.3
As mentioned before, protein digestion is a critical step, therefore digestion optimisation is
essential for method development. The efficiency of digestion determines the accuracy and
precision of the protein quantification. Although the importance of this step is widely
acknowledged, there is limited literature on digestion optimisation.3,22 Trypsin digestion is
generally done overnight at 37°C, which makes it the most time consuming step. However,
this is usually convenient rather than optimal.20 Unconventional methods suggest the use of
higher incubation temperature (50-60⁰C), ultrasonic, infrared or microwave energy,
alternating electric fields or trypsin immobilised on a solid support to accelerate the protein
digestion.22,25 However, monitoring the process can help to determine the optimal
incubation time and temperature.
Another critical step is the signature peptide selection. The signature peptide can be
predicted using different software or databanks such as Skyline, MASCOT, PeptideAtlas or
BLAST. This peptide has to be unique and representative for the target protein, thus free
from PTMs and not disposed to modifications. Moreover, the signature peptide has to be
stable, has to be rapidly and reproducible formed by enzymatic digestion, and has to ionise
and dissociate rapidly by MS/MS analysis. Theoretically, a signature peptide contains
8 to 15 residues in order to restrict the distribution of charge, to achieve sufficient retention
by chromatographic separation and to obtain MS/MS fragmentation. However, monitoring a
set of signature peptides is preferred for the reliability of the data.3,19,22
An internal standard (IS) is generally used to correct for the variations which may occur
during sample preparation, chromatographic separation and detection. For protein
quantitation, peptides or intact proteins are used as internal standards. The IS can be
stable isotope labelled (SIL) or structural analogue. The SIL-peptides are produced by
incorporating an isotope, such as 13C, 15N or 18O, on the selected amino acid residue of the
chosen signature peptide. The analogues peptides are created by single conservative
amino acid replacements (SCAR), for example adding/subtracting a methylene group in
one of the side chains amino acids.3,26 The main drawback of using a peptide as an internal
standard is that it does not undergo the digestion process, which is likely one of the steps
where the most variability may occur.
Internal standards which follow the complete process are the winged or concatenated
peptides, SIL-peptides with extra cleavable groups to the N- and C- terminus, and the intact
proteins.3,27,28 Proteins can be SIL-proteins or analogue proteins.3,29 Yang et al. (2007) have
developed an assay for the quantification of somatropin and a mAb using bovine fetuin as
internal standard.29 In addition, they set analogue IS against stable isotope labelled peptide
and concluded that the results were similar. Therefore, bovine fetuin was used in this
present research as IS for the quantification of somatropin.
The peptides are normally separated using reverse phase liquid chromatography. The
separation is based on the distribution of the analytes between a liquid mobile phase
containing water, acetonitrile and 0.1% TFA/FA and a solid stationary phase, often a C18
column and normally run with a gradient program.14 Liquid chromatography is generally
used for peptide analysis because the diversity in physicochemical properties of the
peptides favors separation.14
11
Further, the peptides are analysed and quantified by MS/MS. Triple quadrupole instruments
operating in selected reaction monitoring (SRM) mode are commonly used for peptide
quantitation.3,19 The sample is first ionised, usually by electro spray ionisation (ESI), then
the first quadrupole (Q1) selects the precursor ion based on m/z ratio. Next, the precursor
ion is fragmented in the second quadrupole, the collision induced dissociation (CID), into
product ions. Finally, the target product ions are analysed by the third quadrupole (Q3).
1.3.3.
Method Validation
Analytical methods have to be validated to ensure robustness and accuracy of the
generated data. The guidance for bioanalytical method validation is based on the principles
of the FDA30 and EMA31. These guidelines provide general recommendations for
bioanalytical method validation. Furthermore, these guidelines define different categories of
validation, e.g. full validation, partial validation and cross-validation, and describe when a
certain validation type should be performed. The analytical laboratories adapt this principles
in their standard operating procedures (SOPs).
Bioanalytical method validation should include fundamental parameters like accuracy,
precision, selectivity, sensitivity, reproducibility and stability. Furthermore, depending on the
goal and application of the assay other parameters, like matrix effect, carry-over, lower limit
of quantification (LLOQ), upper limit of quantification(ULOQ), calibration curve and sample
dilution, might be validated as well.30,31
Whether an analytical method is validated or not depends on meeting the validation criteria.
The validation criteria of the parameters included in the method validation of this study are
presented further on.
A method is considered selective if the peak area of the matrix is ≤ 20% of the peak area of
the analyte at the LLOQ level and ≤ 5% of the response of the IS.
Carry-over should be ≤ 20% of the analyte at the LLOQ level and ≤ 5% of the IS response.
Calibration curve should be based on minimum six calibration standards. The back
calculated concentrations of the calibration standards should be ≤ 20% of the analyte
response at the LLOQ level and ≤ 5% of the IS response. At least 75% of the calibration
standards must fulfil this criterion. In case replicates are used, the criteria should also be
fulfilled for at least 50% of the calibration standards tested per concentration level.
The accuracy and precision should be tested using quality controls (QCs) in minimum 5-fold
per concentration level and minimum 4 concentration levels. The concentration levels
should be: LLOQ level, 3 times LLOQ level (low QC), about 30-50% of the calibration range
level (medium QC) and circa 75% of the highest calibration standard level (high QC).
The method is accurate if the mean concentration of the LLQC is within 20% of the nominal
values and within 15% for the other QC samples. The accuracy is determined within-run
accuracy and between-run.
Precision, as a function of the coefficient of variation (CV), is determined as well within-run
and between-run. The CV value should not be higher than 20% for the LLOQ and 15% for
the other QC samples.
The influence of the matrix should be investigated by analysing the analyte prepared in
minimum six different sources of human plasma and in a solvent without matrix (reference
samples). The coefficient of variation of the normalized matrix factor (ratio of the response
of the matrix sample to the mean response of the reference samples) should to be ≤ 15% at
each concentration level.
The stability of the analyte in matrix should be evaluated using low QC samples and high
QC samples. The mean concentration at each level should be within ± 15% of the nominal
concentration.
12
2.
EXPERIMENTAL DATA
This research was conducted using an LC-MS/MS method. The samples were aqueous
protein solutions and spiked plasma; patient samples were not used. The proteins
(human serum transferrin, somatropin and bovine fetuin) were diluted, denaturated,
reduced, alkylated and enzymatically digested. The signature peptides were
chromatographically separated and further fragmented and detected using a triple
quadrupole detector. The chemicals, materials, reagents and the used equipment are
presented further on, followed by the sample preparation, signature peptide selection and
analysis methods.
2.1. Chemicals and Materials
Transferrin human (T3309, purity ≥ 98%), somatropin Chemical Reference Substance
(batch 3, 3.86 mg of somatropin monomer per 55 mg vial), fetuin from fetal bovine serum
(F2379, suitable for cell culture), trypsin (T6567, proteomics grade and T4799, suitable for
cell culture), DL-Dithiothreitol (43819, purity ≥ 99%), iodoacetamide (I1149, purity ≥99%),
ammonium bicarbonate (40867, LC-MS grade), sodium dodecyl sulphate
(71725, purity ≥ 99%) and sodium deoxycholate (D6750, purity ≥ 97%) were purchased
from Sigma-Aldrich (Steinheim, Germany). RapiGest™ SF Surfactant was purchased from
Waters (Milford, MA, USA). Formic acid (99%) and acetonitrile (99.97%) were purchased
from Biosolve (Valkenswaard, The Netherlands). Water was purified using a
Milli-Q Advantage A10 system (Merck Millipore, Darmstadt, Germany).
Human plasma (50/50 mix male/female) and Guinea pig plasma (50/50 mix male/female)
were supplied by WIL Research Europe (Den Bosch, The Netherlands), while mouse
plasma
(50/50
mix
male/female)
was
purchased
from
Bio
Services
(Uden, The Netherlands). The human plasmas for validation (3 different batches male and
3 different batches female) were from Sera Lab (UK).
The 1 mL polypropylene 96-(deep)wells plates with V-bottom and silicon microplate covers
were from Screening Devices (Amersfoort, The Netherlands) and amber pushcap tubes
with thermoplastic elastomer (TPE) caps from Micronic (Lelystad, The Netherlands).
2.2. Preparation of the Stock Solutions, Calibration Standards and Quality Controls
Transferrin stock solutions (2.6 mg/mL) were prepared in brown glass tubes with
Milli-Q water and were stored in the refrigerator for maximum 1 week. The concentrations of
the human serum transferrin calibration standards were as follows: 2.6, 7.0, 20, 50, 150,
375, 1000 and 2600 µg/mL.
Somatropin stock solutions of 1.0 mg/mL, in 50 mM of NH4HCO3 or in human plasma, were
freshly made as well. The concentrations of somatropin calibration standards were 3.0, 6.0,
15, 30, 75, 150, 375 and 900 µg/mL. Somatropin quality controls were prepared at 3.0, 9.0,
45 and 675 µg/mL and were made in 50 mM of NH4HCO3 and in human plasma.
The bovine fetuin solution (1.0 mg/mL) in Milli-Q water, as well as, the trypsin (1.0 mg/mL),
DTT (33mM) and IAA (50mM) solutions in 50 mM NH4HCO3 were freshly prepared.
13
2.3. Equipment and Software
The ACQUITY UPLC was equipped with: sample manager, sampler organiser, column
manager, binary solvent manager (all Waters Corporation, Milford, MA, USA). A valco valve
(VICI AG International, Switzerland) was used for the connection with the mass
spectrometer of an AB Sciex API 4000 (AB Sciex, Ontario, Canada) equipped with Turbo
ion spray interface.
The analytical columns, Acquity UPLC BEH C18, 50  2.1 mm ID, 1.7 µm and
Acquity UPLC BEH Shield RP18, 50  2.1 mm ID, 1.7 µm, and the inline filters,
ASSY frit, 2.1 mm ID, 0.2 µm, were purchased from Waters.
Other
laboratory
equipment
used
for
the
experiments
included:
stove
(WTC Binder, Germany), benchtop centrifuge (Multifuge 3 S-R Heraeus, Thermo Scientific,
Germany), Variomag Monoshake (Thermo Electron LED, Germany), infuse pomp
(Harvard Apparatus 11, UK), injection syringe (Hamilton 1 mL, Reno, Nevada) and
pipettes (Gilson, UK).
The LC-MS/MS system was controlled by Analyst software version 1.6.2 (AB Sciex).
Furthermore, Skyline software (free version 64-bit 2.6.0.7176, MacCoss Lab, University of
Washington, USA), PeptideAtlas database (developed by Institute of Systems Biology,
Seattle, USA) and MASCOT (free version software, Matrix Science website) were used.
2.4. Sample preparation
Two protocols were used for the sample preparation. The first one was based on the
Yu and Gilar21 procedure and the second one has been the result of the optimisation
process. Both protocols are described below.
Protocol 1
The samples (10 µL) were pipetted into 96-well (1 mL) plate, diluted and denaturated by
adding 50 µL of 0.1% RapiGest surfactant in 50 mM ammonium bicarbonate (NH4HCO3).
Then, the plate was placed on a plate shaker and mixed for 1 minute at approximately
300 rpm. Subsequently, 6 µL of 33 mM dithiothreitol (DTT) in 50 mM NH4HCO3 was added,
mixed, as described before, and placed in a stove for 30 minutes at 50°C. Afterwards, the
plate was centrifuged 5 minutes at 3761 g, to cool down at room temperature and to collect
condensation. 8 µL of 50 mM Iodoacetamide (IAA) in 50 mM NH4HCO3 was added and the
plate was placed in the dark, at room temperature. After 40 minutes, 8 µL of
1 mg/mL Trypsin in 50 mM NH4HCO3 was added, mixed and placed in a stove at 37°C
overnight. After circa 20 hours the enzymatic reaction was stopped using 82 µL 1% FA in
10/90 ACN/Milli-Q water solution (ratio pretreated sample: stop solution was 1:1, v:v).
Protocol 2
The denaturation was done with 50 µL of 10% sodium deoxycholate in 50 mM NH4HCO3 and
the protein incubation with trypsin was 1 hour at 37°C. The other steps were the same as the
previous protocol.
2.4.1.
Protein Denaturation
Protein denaturation was performed using the following five denaturation agents:
heat (95⁰C, 8 minutes)32, RapiGest (0.1%)21, SDS (30%, w/v), sodium deoxycholate
(10%, w/v) and guanidine HCl (6M). The volume of all denaturation agents was 50 µL,
except for the samples denaturated by heat. These were first diluted with 50 µL of
50 mM NH4HCO3. Sample treatment was according to protocol 1 (see paragraph 2.4).
14
The samples used for this experiment were: human plasma, 100 µg/mL transferrin solution
in human plasma and 50 µg/mL somatropin with IS (10 µL of 0.100 mg/mL bovine fetuin).
Human plasma, without spiking, was used to measure transferrin because this is an
endogenous protein. The concentration range for a healthy adult is between 2.0 to 3.6
mg/mL.33 As a result the measured peak areas of the spiked and not spiked plasma were
similar.
2.4.2.
Protein Reduction and Alkylation
Protein reduction was performed be adding 6 µL of 33 mM DTT followed by incubation at
50°C for 30 minutes. Subsequently, the alkylation was performed by adding 8 µL of
50 mM IAA followed by incubation in the dark at room temperature for 40 minutes.
2.4.3.
Protein Proteolysis
In this research the proteins were digested by trypsin. The efficiency of different qualities
and quantities were tested. Further, the incubation time and temperature were monitored to
determine the optimal digestion conditions.
First experiments were conducted with both types of trypsin according to protocol 1
(paragraph 2.4). For these experiments 2.6 mg/mL transferrin aqueous solutions were
used. Subsequently, all the other tests were conducted with trypsin suitable for cell culture.
The influence of the trypsin concentration on the digestion efficiency was tested by
conducting the following experiment: aqueous transferrin samples (2 mg/mL) were treated
with 8 µL of 0.5, 1.0 and 2.0 mg/mL trypsin suitable for cell culture solution.
Further, the influence of different temperatures and different incubation times was tested.
One experiment was conducted with transferrin samples (2 mg/mL, aqueous), treated
according to the protocol 1, and incubated at 37, 50 and 60°C for 1, 2, 4, 6, 22, 26
and 72 hours. Another experiment was performed with somatropin samples (0.5 mg/mL,
50% human plasma), treated according to the protocol 2 and incubated at 37 and 50°C for
1, 2, 4 and 22 hours.
2.5. Surrogate Peptides Identification and Selection
First, the protein sequences for human serum transferrin, bovine fetuin and, human growth
hormone were acquired from the database of Universal Protein Resource (UniProt).34,35
The sequence of somatropin was acquired from the DrugBank database.36 All these
sequences are presented in Appendices 1-3. Subsequently, the lists of peptides formed by
trypsin digestion were acquired from the Skyline software. Next, the surrogate peptides
were identified by direct MS infusion and LC-MS/MS analysis using the MS/MS settings
imported from Skyline. Finally, the peptides were checked for their specificity using
PeptideAtlas and MASCOT software.
2.5.1.
Surrogate Peptides Identification by Direct MS Infusion
Blank and protein digested samples were directly infused, with 1 mL/min flow, in the first
quadrupole (Q1) of the mass spectrometer. The following solutions of protein were infused:
- transferrin (concentrations of 0.26, 2.6, 26.0, 130 and 2600 µg/mL, in Milli-Q water),
- bovine fetuin (1 mg/mL, in Milli-Q water),
- somatropin (1 mg/mL, in 50 mM ammonium bicarbonate).
The spectra of the digested proteins were compared with the blank spectrum and the peaks
which were present only in samples were considered as being potential surrogate peptides.
Their m/z values were compared with the data from Skyline. If matched, the programmed
infusion optimisation process was started.
15
Throughout this automatic procedure, the optimum values for precursor and product ions
were determined by increasing and decreasing the declustering potential (DP), collision
energy (CE) and collision exit potential (CXP) voltages. At the end of this process a report
which includes the optimal voltages was created.
An example of the identification of the somatropin surrogate peptide LEDGSPR by
MS infusion is illustrated below. Blank and protein digested samples, both aqueous
solutions, were directly infused in the mass spectrometer. Figure 2 shows the full-scan
spectrum (Q1 scans) of the (aqueous) blank digested sample, while Figure 3 shows the one
of somatropin (1.86 mg/mL, in 50 mM ammonium bicarbonate) digested sample.
Comparing the two spectra, it was observed that two peaks, by m/z values 387.4 and
382.3, were present only in the somatropin spectrum. These m/z values correspond to the
surrogate peptide LEDGSPR, respectively FETFLR. Therefore, automatic compound
optimisation was performed for each peptide, as described in paragraph 2.6.1.
In the first case, at the end of the optimisation process, it was established that the highest
intensity of the product ion was 531.3. This fragmentation, 387.4++531.3+, corresponds to
the LEDGSPRDGSPR fragmentation and confirms the Skyline data, as shown in Figure
4. In the second case, the fragmentations of the parent ion did not match the somatropin
surrogate peptide FETFLR.
Figure 2. Mass spectrum of the aqueous blank sample
(full scan in the m/z interval 300-1500 Da).
16
Figure 3. Mass spectrum of the aqueous somatropin sample (full scan in the m/z interval
300-900 Da).The peaks by m/z 387.4 and 382.3 might indicate the presence of the somatropin
surrogate peptide LEDGSPR, respectively FETFLR.
Figure 4. Somatropin data by Skyline software.
Tryptic peptides are displayed on the left side. The precursor charge (2+), m/z value (387.4115) and
[M+H] value (773.8157) of the peptide LEDGSPR are displayed on the right side, in the small yellow
window, together with the product ions. The product ions with the highest intensities, 660.66, 531.54
and 416.45, are given in blue.
17
2.5.2.
Surrogate Peptides Identification by Importing MS-settings from Skyline
Protein digests and blank samples were analysed by LC-MS/MS. The MS/MS quantitation
methods were built with data imported from Skyline (m/z of the precursor ion and product
ion, Q3, DP, CE). The extracted ion chromatograms (XIC) were examined for the presence
of signals at the selected m/z values.
2.5.3. Signature Peptide Selection
After identification, the surrogate peptides were verified for specificity using MASCOT and
PeptideAtlas software and a set of peptides was chosen for protein identification and
quantification by LC-MS/MS analysis.
2.6. LC-MS/MS Method
An LC-MS/MS method was first optimised for the transferrin analysis. The separation of
surrogate peptides was done by gradient reversed phase chromatography. During the
optimisation process, the optimal gradient, chromatographic column, injection needle, as
well as the composition of the mobile phases and the washes for the needle were
established. The surrogate peptides detection was done by using electrospray ionisation
(ESI) in positive mode and a triple quadrupole detector. Further, an LC-MS/MS method was
optimised and validated for the analysis of somatropin in human plasma using bovine fetuin
as internal standard.
The carry-over for transferrin was tested by both steel and polyetheretherketone (PEEK)
injection needle. The carry-over for the PEEK-needle was lower than 20% of the analyte
response, while the one for the steel needle was higher. In order to reduce it even further,
higher volumes of strong and weak wash were used, namely 400 µL and 1200 µL. The
linear gradient was adjusted in order to obtain the analyte optimal peak shape in minimum
time and it is described in Table 2. The column used was Acquity UPLC BEH C18.
The mobile phase A was 10/90/0.1 ACN/Milli-Q water/FA and mobile phase B was
90/10/0.1 ACN/Milli-Q water/FA. The entire LC-MS/MS conditions are given in Table 3.
The ESI source of the mass spectrometer was operated in the positive mode.
The acquisition parameters for the MS/MS/detection are listed in Table 4.
Table 2
Linear gradient for transferrin and somatropin LC method
Time
(min)
0.00
0.30
1.50
1.70
1.80
2.00
Transferrin
Mobile phase
A (%)
85.0
85.0
0.1
0.1
85.0
85.0
Somatropin
Mobile phase
B (%)
15.0
15.0
99.9
99.9
15.0
15.0
A (%)
99.9
99.9
50.0
50.0
99.9
99.9
B (%)
0.1
0.1
50.0
50.0
0.1
0.1
18
Table 3
LC-MS/MS conditions for transferrin and somatropin analysis
Column
Filter
Column temperature
Autosampler temperature
Injection volume
Injection loop
Needle
Sample syringe
Mobile phase A
Mobile phase B
Strong needle wash
Weak needle wash
Flow
Ionisation source
Ion spray voltage
Source temperature
Transferrin: Acquity UPLC BEH C18, 50  2.1 mm ID, 1.7 µm
Somatropin: Acquity UPLC BEH Shield RP18, 50  2.1 mm ID, 1.7 µm
inline filter ASSY frit, 2.1 mm id., 0.2 µm
30⁰C
4⁰C
5 µL
10 µL
30 µL Peek needle
100 µL
Transferrin: 10/90/0.1 (v/v/v) ACN/Milli-Q water/FA
Somatropin: 100/0.1 (v/v) Milli-Q water/FA
90/10/0.1 (v/v/v) ACN /Milli-Q water/FA
150/150/150/9 (v/v/v/v) 2-propanol (IPA)/ ACN/MeOH /NH4OH
Transferrin:10 / 90 ACN/Milli-Q water
Somatropin: Milli-Q water
0.6 mL/min
+
ESI
4000 V
450⁰C
Table 4
MS/MS acquisition parameters
Compound
Transferrin
Somatropin
IS (bovine fetuin)
Parent ion
(m/z, z=2)
625.4
709.0
338.4
387.4
408.9
738.4
Product ion
(m/z, z=1)
776.4
1177.5
463.5
531.5
632.6
880.0
CE
(V)
29.0
31.0
15.0
18.0
19.0
38.0
DP
(V)
66.0
126.0
55.8
59.4
61.0
85.0
Dwell time
(ms)
100
100
20
20
20
20
The LC method was optimised for the somatropin analysis. The bovine fetuin (IS) peak
presented a ‘shoulder’ using the column Acquity UPLC BEH C18, as the first chromatogram
of Figure 5 shows. Therefore, an Acquity UPLC BEH Shield RP18 column, which has an
embedded carbamate group, was tested. As a result, the two peaks were separated, as the
second chromatogram of Figure 5 shows. Therefore, this column was used for the
somatropin assay. The linear gradient was adjusted in order to obtain the analyte optimal
peak
shape
in
minimum
time
and
it
is
described
in
Table
2.
The mobile phase A was 100/0.1 Milli-Q water/FA and mobile phase B was 90/10/0.1
ACN/Milli-Q water/FA with a 0.6 mL/min flow. Further, the weak wash was replaced with
100%Milli-Q water. The entire LC-MS/MS conditions are given in Table 3.
The ESI source of the mass spectrometer was operated in the positive mode as well and
the acquisition parameters are listed in Table 4.
19
Figure 5. Chromatographic separation of bovine fetuin peptide TPIVGQPSIPGGPVR using an
Acquity UPLC BEH C18 column (above) and an Acquity UPLC BEH Shield RP18 column
(under).
Additionally, the LC-MS/MS method for the analysis of somatropin in human plasma using
bovine fetuin as internal standard was validated. The validation process was based on the
principles of FDA and EMA on bioanalytical method validation included in the
WIL Research method validation SOP. The following parameters were validated: selectivity,
accuracy and precision, calibration line, carry-over, freeze/thaw stability, short term stability
at room temperature and the stability of processed samples. Three analytical runs were
performed and the results are presented further in paragraph 3.5 and in Appendix 4.
The samples used for validation were: blank plasma with and without IS, 6 different blank
human plasma (3 male and 3 female) with and without IS, system suitability test standards
(3.0 µg/mL), calibration standards (3.0, 6.0, 15, 30, 75, 150, 375 and 900 µg/mL), quality
controls in 5-fold (QC-LLOQ (3 µg/mL), QC-L (9 µg/mL), QC-M (45 µg/mL) and
QC-H (675 µg/mL)), quality controls (QC-L and QC-H) in 2-fold prepared with the 6 different
human plasma, quality controls (QC-L and QC-H) in 3-fold prepared in 50 mM NH4HCO3.
20
3.
RESULTS
In this chapter, the results of the protein denaturation using five different denaturation
agents, the digestion optimisation and the identified surrogate peptides of transferrin,
somatropin and bovine fetuin are listed. Further, the validation of the LC-MS/MS somatropin
quantification method is presented.
3.1. Protein Denaturation Using Five Different Denaturation Agents
In this current study, the proteins were enzymatic digested after being denaturated with
RapiGest, SDS, sodium deoxycholate, guanidine HCl and by heat. The samples, in 4-fold,
were pipetted in 1.4 mL amber Micronic tubes. Denaturation was achieved by adding 50 µL
of one of the reagents mentioned before. The samples which were denaturated by heat
were first diluted with 50 µL of 50 mM NH4HCO3. The average peak areas of the surrogate
peptides are presented in Table 5. The most efficient transferrin denaturation was obtained
by heating the samples at 95⁰C, closely followed by RapiGest and Na deoxycholate.
Guanidine HCl had a low efficiency and no peptide response was found by SDS
denaturation. The efficiency of the somatropin and bovine fetuin (IS) denaturation was
similar by RapiGest and Na deoxycholate, while all the other denaturation agents were
found to be inefficient.
Table 5
Transferrin, somatropin and bovine fetuin peak areas variation with five different denaturation agents
Denaturation
agent
95⁰C
RapiGest
Guanidine HCl
SDS
Na deoxycholate
Transferrin peptide
SVIPSDGPSVACVK
5
2.0*10
5
1.6*10
3
6.0*10
no response
5
1.3*10
Peak areas (cps)
Somatropin peptide
LEDGSPR
no response
4
1.8*10
no response
no response
4
1.7*10
IS peptide
ALGGEDVR
no response
5
4.4*10
no response
no response
4
5.0*10
3.2. Protein Digestion Using Different Qualities and Quantities of Trypsin
Transferrin calibration standards (aqueous) were treated with trypsin proteomics grade and
with trypsin suitable for cell culture according to protocol 1, as described in paragraph 2.4.
The peak areas for the surrogate peptide SASDLTWDNLK, transition 625.3++776.4+, are
given in Table 6 and the calibration lines in Figure 6. The peptide formation using trypsin
suitable for cell culture was around 80% lower for the lowest and highest calibration
standard and around 50% lower for the other calibration standards, except for two outliers
(50 and 150 µg/mL).
The influence of different trypsin concentration was tested only with trypsin for cell culture.
Transferrin (2 mg/mL, in Milli-Q water) samples were analysed in 3-fold, following the
sample preparation from protocol 1. Trypsin concentrations were 0.5, 1.0 and 2.0 mg/mL
and the incubation time with trypsin was 26 hours. Two surrogate peptides were monitored,
namely SASDLTWDNLK (transition 625.4++776.4+) and SVIPSDGPSVACVK
(transition 709.0++1117.5+). Trypsin with the concentration of 1.0 mg/mL was considered
the reference. The response of the first peptide was 3% higher when using 0.5 mg/mL
trypsin and 7% lower by 2 mg/mL trypsin. The response of the second peptide was 14%
higher by using 0.5 mg/mL trypsin and 3% lower by trypsin 2 mg/mL trypsin. In Table 7 are
these results listed.
21
Table 6
++
+
Transferrin peak areas of the surrogate peptide SASDLTWDNLK (transition 625.3 776.4 )
by digestion with trypsin proteomics grade (I) and trypsin suitable for cell culture (II).
Concentration transferrin (µg/mL)
2.6
7.0
20
50
150
375
1000
2600
Peak area surrogate peptide SASDLTWDNLK (cps)
I
II
3
2
1.0*10
8.2*10
3
3
4.9*10
2.8*10
4
4
2.2*10
1.0*10
4
4
1.7*10
2.4*10
5
4
2.5*10
8.6*10
5
5
7.7*10
3.8*10
6
5
1.3*10
8.7*10
6
6
2.7*10
2.1*10
Calibration lines transferrin
Peak area (cps)
*105
30
trypsin proteomics grade
25
20
trypsin for cell culture
15
10
5
0
0
5
10
15
20
Concentration (µg/mL)
25
30 *102
Figure 6. Calibration lines for transferrin peptide SASDLTWDNLK by digestion with trypsin
proteomics grade and trypsin suitable for cell culture.
Table 7
Transferrin peak areas by digestion with trypsin suitable for cell culture at different concentrations
Conc. trypsin (mg/mL)
Peak area 1 (cps)
Peak area 2 (cps)
Peak area 3 (cps)
Peak area average (cps)
Peak areas transferrin (cps)
peptide SASDLTWDNLK
peptide SVIPSDGPSVACVK
++
+
++
+
(transition 625.4 776.4 )
(transition 709.0 1117.5 )
0.5
1.0
2.0
0.5
1.0
2.0
327508
304759
295595
513378
445558
443609
325815
339787
293293
524392
474422
438631
326555
309686
301465
523627
449353
440523
326626
318077
296784
520466
456445
440921
3.3. Protein Digestion at Different Temperature and Incubation Time
The influence of incubation time and temperature variation was tested first on 2 mg/mL
transferrin samples. The peak areas of two surrogate peptides, peptide I, SASDLTWDNLK,
transition
625.4++776.4+,
and
peptide
II,
SVIPSDGPSVACVK,
transition
++
709.0 1117.5+, were monitored at three different temperatures: 37, 50 and 60°C after 1,
2, 4, 6, 22, 26 and 72 hours of incubation time.
22
The t=0h was actually 5 minutes (0.083 hours) at room temperature. The samples were
prepared in 3-fold according to protocol 1 presented in paragraph 2.4. The average values
of the peak areas are given in Table 8. Peptide I reached the maximum after an incubation
of 22 hours at 37⁰C. At 50⁰C, the highest amount was found after 1 hour and it was about
8% lower than the maximum. At 60⁰C, the highest amount was also after 1 hour, but it was
30% lower than the maximum. Peptide II reached the maximum after 6 hours at 37⁰C.
At 50⁰C, the highest amount was found after 2 hours and it was about 10% lower than the
maximum. After 1 hour at 60⁰C, the amount was 15% lower than the t=0.083h.
Table 8
Transferrin peak areas variation with time and temperature
Time (h)
)
0.083*
1
2
4
6
22
26
Peak areas at 37⁰C (cps)
Peptide I
Peptide II
)
)
210230*
495364*
299044
532113
301684
544808
316502
540168
321150
556097
336501
475036
318077
456445
Peak areas at 50⁰C (cps)
Peptide I
Peptide II
)
)
210230*
495364*
308017
496098
302156
502194
304362
474543
289553
480272
273672
435252
263876
383655
Peak areas at 60⁰C (cps)
Peptide I
Peptide II
)
)
210230*
495364*
232481
421627
177468
404988
200481
356642
190359
351921
171557
299306
197415
239575
)
* at room temperature
The samples which were incubated for 72 hours were analysed in a different run, therefore
the t=0.083 hours was analysed a second time. The peak areas after 72 hours incubation
were lower than the peak areas at t=0.083 hours.
The responses of the transferrin signature peptides were unexpectedly high after 5 minutes
at room temperature, therefore another experiment was conducted to verify these results.
Human plasma and 2 mg/mL transferrin solution in 50 mM ammonium bicarbonate were
prepared in 3-fold, according to protocol 1, kept 5 min at room temperature before the
enzymatic reaction was stopped by adding 1% FA in 10/90 ACN/Milli-Q water and analysed
by LC-MS/MS. The average responses were: in plasma 102468 counts (peptide I),
respectively 442697 counts (peptide II) and in Milli-Q water 1953599 counts (peptide I) and
1948060 counts (peptide II).
Another set of experiments was conducted with 500 µg/mL somatropin, 1 mg/mL bovine
fetuin (IS) and somatropin with IS. The samples, in 2-fold, were treated according to
protocol 2 (paragraph 2.4) and incubated at two different temperatures, namely 37⁰C and
50⁰C, and monitored after 1, 2, 3, 4 and 22 hours. The average peak areas for somatropin
(surrogate peptide LEDGSPR transition: 387.4++531.3+) and bovine fetuin (surrogate
peptide ALGGEDVR, transition 408.9++632.6+) are presented in Table 9. Somatropin
peptide reached the maximum after 4 hours incubation at 37⁰C and the highest amount at
50⁰C was found after 22 hours (about 4% lower than the maximum). Bovine fetuin peptide
reached the maximum after 4 hours incubation at 37⁰C. The highest amount at 50⁰C was
found after 1 hour and after 4 hours and it was about 10% lower than the maximum.
23
Table 9
Somatropin and bovine fetuin (IS) peak areas variation with time and temperature
Time
(hours)
)
0.083*
1
2
3
4
22
Peak areas somatropin
peptide LEDGSPR
at 37°C
at 50°C
)
)
3129*
3129*
159295
153369
162692
144574
160577
142208
176302
165279
151130
169297
Peak areas bovine fetuin (IS)
peptide ALGGEDVR
at 37°C
at 50°C
)
)
2975*
2975*
15796
14686
16375
13607
15977
13973
16680
14686
14849
14511
)
* at room temperature
3.4. Surrogate peptides identification and selection
The surrogate peptides of transferrin, somatropin and bovine fetuin were identified first by
direct MS infusion, then by LC-MS/MS analysis as described in paragraph 2.5.1. and
respectively 2.5.2. The list of surrogate peptides identified during this research,
the m/z values of the parent ions and the m/z values of the most intensive product ions are
given below, in Table 10.
Table 10
Experimentally identified surrogate peptides for transferrin, bovine fetuin and somatropin
Protein
Transferrin
Bovine fetuin
Somatropin
Peptide sequence
[position in protein sequence]
HQTVPQNTGGK [553, 563]
APNHAVVTR [600, 608]
SVIPSDGPSVACVK [46, 59]
DSGFQMNQLR [122, 131]
FDEFFSEGCAPGSK [494, 507]
SASDLTWDNLK [453, 463]
TPIVGQPSIPGGPVR [333, 347]
HTLNQIDSVK [57, 66]
EVVDPTK [211, 217]
GSVIQK [231, 236]
ALGGEDVR [237, 244]
QDGQFSVLFTK [120, 130]
LEDGSPR [127, 133]
IVQCR [178, 182]
SNLELLR [70, 76]
LFDNAMLR [8, 15]
DLEEGIQTLMGR [115, 126]
TGQIFK [134, 139]
Parent ion
(m/z ,z = 2+)
584.1
483.0
709.1
598.6
789.3
625.3
738.4
578.1
394.4
316.4
408.9
635.7
387.3
338.4
423.0
490.4
681.8
347.4
Product ion
(m/z, z= 1+)
701.1
682.3
117.5
789.5
892.4
776.4
879.5
917.0
460.5
388.5
632.6
694.8
531.3
463.5
530.6
719.8
1005.2
407.5
After identification, the peptides were verified for specificity using MASCOT and
PeptideAtlas software. MASCOT data base matched the peptides with the protein only if a
combination of three or more peptides was introduced in the query. On the other hand,
PeptideAtlas software found all individual surrogate peptides of transferrin, five of bovine
fetuin (TPIVGQPSIPGGPVR, HTLNQIDSVK, EVVDPTK, ALGGEDVR, QDGQFSVLFTK)
and three of somatropin (SNLELLR, LFDNAMLR, DLEEGIQTLMGR) as being specific.
However, for the reliability of the data, a set of peptides was chosen for protein identification
and quantification.
24
3.5.
Method Validation
An LC-MS/MS method was validated for the analysis of somatropin in human plasma using
bovine fetuin as internal standard. The samples were treated according to the protocol 2,
described in paragraph 2.4. The validation process was based on to the principles of FDA
and EMA on bioanalytical method validation included in the WIL Research Europe SOP.
The complete validation results are presented in Appendix 4.
Three analytical runs were performed. The following parameters were tested: the influence
of the matrix on the analyte, selectivity, carry-over, accuracy and precision, calibration line,
freeze/thaw stability, short term stability at room temperature and the stability of processed
samples. Two of the most sensitive peptides for each protein were monitored, namely
IVQCR and LEDGSPR for somatropin, and ALGGEDVR and TPIVGPSIPGGPVR for
bovine fetuin (IS). The results were similar, therefore the results presented further are
restricted to the somatropin peptide LEDGSPR (transition LEDGSPRDGSPR,
387.4++531.3+) and IS peptide ALGGEDVR (transition ALGGEDVRGGEDVR,
408.9++632.6+).
The retention time of the peptides was reproducible. Somatropin peptide LEDGSPR had a
retention time of 0.90 minutes and the IS peptide ALGGEDVR 0.98 minutes.
The interference of the matrix with the analyte was lower than 20%. The matrix had no
interference with the IS, thus the method was found to be selective.
Carry-over was not detected for the internal standard, but was detected for somatropin.
The assay was found accurate and precise for the tested levels (3.0, 9.0, 45 and
675 µg/mL). The calibration line was found linear in the range of 3 to 900 µg/mL. Linear
regression and an (1/concentration2) weighing factor were used.
The samples were found to be stabile after three freeze/thaw cycles and after being stored
for 28 hours at room temperature. Further, the processed samples were found to be stabile
after being stored for 47 hours at 4°C.
25
4.
DISCUSSION
The aim of this research was to develop and optimise a generic sample preparation and
LC-MS/MS method for protein biopharmaceutical quantitation in plasma based on signature
peptide(s). Therefore a sample preparation without protein or peptide purification step was
implemented. The analytes under investigation were two proteins, human serum transferrin
and bovine fetuin, and a protein biopharmaceutical, somatropin. The sample preparation
was based on the one used for the analysis of an humanised monoclonal antibody.21 The
same procedure had been successfully used previously by WIL Research for the analysis
of human and bovine serum albumin.
In this research, it had been demonstrated that freshly prepared solutions of trypsin suitable
for cell culture, a low-cost trypsin variant, can be successfully used for protein digestion.
Additionally, it had been shown that sodium deoxycholate, a low-cost denaturation agent, is
as effective as RapiGest. Consequently, the sample preparation has been made
cost-effective. Furthermore, it was shown that heat, as denaturation agent, has been
efficient for the transferrin denaturation, but not for bovine fetuin and somatropin
denaturation. Additionally, SDS and guanidine did not result in the formation of target
peptides of any of the tested proteins. One possible explanation might be that the used
protocol had been inappropriate for these agents.
The effect of different enzyme quantities was tested only on transferrin aqueous samples.
The responses decreased with the increasing of trypsin quantity. An explanation might be
that by excess of enzyme autolysis may occur. Consequently, trypsin loses its activity and
the autolysis peptides may interfere in the analyte detection. However, no further
experiments were conducted to confirm these results.
Enzymatic digestion is usually the most time consuming step. Even though an overnight
trypsin digestion at 37⁰C is commonly used, it is more efficient to determine the optimum
conditions by monitoring the process. In this way, it has been found that the formation of the
transferrin peptide SASDLTWDNLK was maximal after 22 hours at 37°C. However, after
1 hour at 50°C, the peptide formation was only about 8% lower. In the case of somatropin
the maximum was reached after 4 hours of incubation at 37°C. However, after 1 hour
incubation at 37°C, the peptide formation was just 9% lower.
During one experiment, the enzymatic reaction was accidentally stopped after 5 minutes
instead of immediately after adding trypsin. The response of transferrin signature peptide
was unexpectedly high, almost 63% of the maximum reached after 22 hours of incubation
at 37⁰C. Therefore, an additional experiment was conducted to verify the results. That
experiment confirmed the previous data. Thus, transferrin formed surrogate peptides
rapidly. Further, the formation of peptides after 5 minutes at room temperature was
measured for somatropin and bovine fetuin samples. The peptide formation was about
2% for somatropin surrogate peptide LEDGSPR and almost 18% for bovine fetuin peptide
ALGGEDVR, thus, these proteins did not form peptides at room temperature as fast as
transferrin.
In this research, signature peptides have been identified using direct MS infusion and
LC-MS/MS analysis using the MS/MS settings imported from Skyline. Direct MS infusion
has the advantage that it can be used immediately. However, the identification of the
peptides was time-consuming, the m/z values from spectra were one-by-one compared with
the m/z values of the peptides and compound optimisation procedure was needed to
confirm the presence of the peptide. Moreover, by using low sample concentrations, as
used first for transferrin, namely 0.26-130 µg/mL, no distinction was found between the
peptides and matrix peaks. This problem was solved by increasing the sample
concentration (to 1.0-2.6 mg/mL).
26
The alternative approach, peptide selection using LC-MS/MS analysis with the MS/MS
settings imported from Skyline software was faster and reliable. In addition, samples with
low concentrations could also effectively be used.
The intensity of the formed peptides depends on the chromatographic method and mass
spectrometer. Consequently, trying to find signature peptides mentioned in literature may
not always be successful. For example, the quantification of human serum transferrin using
LC-MS/MS (HPLC Agilent Series 1200 and Agilent 6410 Triple Quad) was based on the
surrogate peptide EDPQTFYYAVAVVK.32 However, this peptide has not been identified by
our analysis method and equipment.
The identified peptides were verified for specificity using MASCOT and PeptideAtlas
software. MASCOT data base matched the peptides with the protein only if a combination
of three or more peptides was introduced in the query, while PeptideAtlas software found all
individual surrogate peptides of transferrin, five of bovine fetuin and three of somatropin as
being specific. One possible reason might be the lack of experience of using the software.
This research was based on monitoring a set of peptides for each protein to reduce the risk
of erroneous results. Two of the most intensive peptides were selected for the validation of
the LC-MS/MS method. The lower limit of quantification of somatropin in human plasma
was 3 µg/mL. Additional experiments, with spiked Guinea pig plasma and mouse plasma,
were conducted with the aim of decreasing the LLOQ. However, these experiments did not
result in a lower LLOQ, therefore the assay was validated in human plasma.
The quantitative LC-MS/MS method was validated for the analysis of somatropin in human
plasma with bovine fetuin as internal standard. The validation was based on two of the most
sensitive peptides of each protein. The following parameters were validated: selectivity,
accuracy, precision, linearity, stability of the quality controls (freeze/thaw and short term
stability at room temperature) and stability of processed samples. The method has been
found to be selective, accurate and precise for the tested levels. The calibration line was
found to be linear in the 3 to 900 µg/mL range. Carry-over was not detected for the IS, but
was detected for somatropin. This should lead to extra actions for future analyses.
The stability tests showed that somatropin samples were stable after 28 hours at room
temperature and after three freeze/thaw cycles. Additionally, the processed somatropin
samples have been found stable after being stored for 47 hours at 4⁰C.
27
5.
CONCLUSIONS
This research project focused on establishing a generic protein bioanalytical method based
on surrogate peptides. The experiments have been limited to the analysis of transferrin,
somatropin and bovine fetuin. However, it can be concluded that the sample preparation
and the LC-MS/MS method can be used as a generic procedure.
During this study, the sample preparation has been optimised and made cost and time
effective. Furthermore, six surrogate peptides for each protein were identified. Finally, the
LC-MS/MS quantification method of somatropin in human plasma using bovine fetuin as
internal standard has been validated. The method has been found to be linear in the
3 to 900 µg/mL range. The lower limit of quantification (3 µg/mL) might be further lowered
by introducing protein purification steps, such as immunocapture or immunodepletion,
and/or surrogate peptides clean up and enrichment, like 2D-SPE, 2D-LC or SFC, prior to
the LC-MS/MS analysis. Further, the use of more advanced triple quadrupole or high
resolution analysers, such as the time of flight hybrid instruments (QTOF,TOF/TOF) and
Fourier-Transform mass spectrometers (Orbitrap, FT-ICR) would lead to an enhanced
selectivity and sensitivity.
28
LIST OF ABBREVIATIONS
ADC
ADME
BEH
BLA
BLAST
CE
CID
CDG
CXP
DNA
DP
EMA
EPO
ESI
FDA
FT-ICR
FTIR
2D-LC
LC-MS/MS
mAb
MALDI
MCA
MSI
PEG
PKU
PTM
QTOF
RT
SIL
SCAR
SFC
SDS-PAGE
SOP
SRM
SST
TOF
XIC
Antibody-drug Conjugates
Absorption, Distribution, Metabolism and Excretion
Ethylene Bridged Hybrid
Biologics License Application
Basic Local Alignment Search Tool
Collision Energy
Collision Inducted Dissociation
Congenital Disorders of Glycosylation
Collision Exit Potential
Deoxyribonucleic Acid
Declustering Potential
European Medicine Agency
Epoietin
Electrospray Ionisation
Food and Drug Administration
Fourier Transform-Ion Cyclotron Resonance
Fourier Transform Infrared Spectroscopy
Two Dimensional Liquid Chromatography
Liquid Chromatography Tandem Mass Spectrometry
monoclonal Antibody
Matrix-Assisted Laser Desorption/Ionisation
Multiple Channel Acquisition
Mass Spectrometry Imaging
Polyethylene glycol
Phenylketonuria disease
Post-Translational Modification
Tandem quadrupole-Time of Flight mass spectrometer
Room Temperature
Stable Isotope Labelled
Single Conservative Amino acid Replacements
Supercritical Fluid Chromatography
Sodium Dodecyl Sulfate-Polyacrylamide Gel Electrophoresis
Standard Operation Procedure
Selected Reaction Monitoring
System of Suitability
Time Of Flight
Extracted Ion Chromatograms
29
APPENDIX 1. HUMAN SERUM TRANSFERRIN - general facts, FASTA sequence and
structure
Human serum transferrin, serotransferrin or siderophilin, is the main plasma transport
protein for iron. It consists of 698 amino acids residues and has a molecular mass of
approximatively 80 kDa.34 It is an endogenous protein and the clinical diagnostic range is
between 2.0 to 3.6 mg/mL.33 Trypsin digestion conducts to circa 72 peptides with a length
varying from 2 to 45 residues and molecular mass between 271 and 4648 Da.37
Recombinant human transferrin (OptiferrinTM) can be used to treat genetic disorders like
thalassemia (defective production of hemoglobin) and atransferrinemia (absence of
transferrin in the body). In addition, it can be used as a target drug delivery system.38
Human serum transferrin FASTA sequence34
(the surrogate peptides identified by this research are given in red)
>sp|P02787|TRFE_HUMAN Serotransferrin OS=Homo sapiens GN=TF PE=1 SV=3
MRLAVGALLVCAVLGLCLAVPDKTVRWCAVSEHEATKCQSFRDHMK SVIPSDGPSVACVK
KASYLDCIRAIAANEADAVTLDAGLVYDAYLAPNNLKPVVAEFYGSKEDPQTFYYAVAVV
KK DSGFQMNQLR GKKSCHTGLGRSAGWNIPIGLLYCDLPEPRKPLEKAVANFFSGSCAPC
ADGTDFPQLCQLCPGCGCSTLNQYFGYSGAFKCLKDGAGDVAFVKHSTIFENLANKADRD
QYELLCLDNTRKPVDEYKDCHLAQVPSHTVVARSMGGKEDLIWELLNQAQEHFGKDKSKE
FQLFSSPHGKDLLFKDSAHGFLKVPPRMDAKMYLGYEYVTAIRNLREGTCPEAPTDECKP
VKWCALSHHERLKCDEWSVNSVGKIECVSAETTEDCIAKIMNGEADAMSLDGGFVYIAGK
CGLVPVLAENYNKSDNCEDTPEAGYFAIAVVKK SASDLTWDNLK GKKSCHTAVGRTAGWN
IPMGLLYNKINHCR FDEFFSEGCAPGSK KDSSLCKLCMGSGLNLCEPNNKEGYYGYTGAF
RCLVEKGDVAFVK HQTVPQNTGGK NPDPWAKNLNEKDYELLCLDGTRKPVEEYANCHLAR
APNHAVVTR KDKEACVHKILRQQQHLFGSNVTDCSGNFCLFRSETKDLLFRDDTVCLAKL
HDRNTYEKYLGEEYVKAVGNLRKCSTSSLLEACTFRRP
Human serum transferrin structure39
30
APPENDIX 2. (RECOMBINANT) HUMAN GROWTH HORMONE - general facts, FASTA
sequence and structure
Recombinant human growth hormone (somatropin), brand names Genotropin,
Humatrope, Omnitrope, is synthesized in E. coli. It is used for treatment of dwarfism,
acromegaly and prevention of HIV-induced weight loss. Somatropin consist of 191 amino
acids residues and has a molecular mass of approximatively 22.1 kDa. 36
Trypsin digestion conducts to circa 20 peptides with a length varying from 3 to 23 residues
and molecular mass between 382 and 2616 Da.37
Somatropin FASTA sequence36
(the surrogate peptides identified by this research are given in red)
>DB00052 sequence
FPTIPLSR LFDNAMLR AHRLHQLAFDTYQEFEEAYIPKEQKYSFLQNPQTSLCFSES
IPTPSNREETQQK SNLELLR ISLLLIQSWLEPVQFLRSVFANSLVYGASDSNVYDLLK
DLEEGIQTLMGR LEDGSPR TGQIFK QTYSKFDTNSHNDDALLKNYGLLYCFRKDM
DKVETFLR IVQCR SVEGSCGF
Somatropin structure36
Growth hormone (Somatotropin, P01241) consists of 217 amino acids residues and has
molecular mass of approximatively 24.8 kDa.40 The clinical range for a healthy person
depends on age and gender and are as follows: adult men < 5 ng/mL, women < 10 ng/mL,
children 0–20 ng/mL and new-borns 5–40 ng/mL.41
Somatotropin FASTA sequence40
>sp|P01241|SOMA_HUMAN Somatotropin OS=Homo sapiens GN=GH1 PE=1 SV=2
MATGSRTSLLLAFGLLCLPWLQEGSA
FPTIPLSRLFDNAMLRAHRLHQLAFDTYQEFEEAYIPKEQKYSFLQNPQTSLCFSESIPTPS
NREETQQKSNLELLRISLLLIQSWLEPVQFLRSVFANSLVYGASDSNVYDLLKDLEEGIQTL
MGRLEDGSPRTGQIFKQTYSKFDTNSHNDDALLKNYGLLYCFRKDMDKVETFLRIVQCRS
VEGSCGF
31
APPENDIX 3. BOVINE FETUIN - general facts, FASTA sequence and structure
Bovine fetuin is a protein present in serum and cerebrospinal fluid of fetal calves.42
It consists of 359 amino acids residues and has a molecular mass of approximatively
38.4 kDa.35 Trypsin digestion conducts to circa 26 peptides with a length varying from
2 to 61 residues and molecular mass between 277 and 5960 Da.37
Bovine fetuin FASTA sequence35
(the surrogate peptides identified by this research are given in red)
>sp|P12763|FETUA_BOVIN Alpha-2-HS-glycoprotein OS=Bos taurus GN=AHSG PE=1 SV=2
MKSFVLLFCLAQLWGCHSIPLDPVAGYKEPACDDPDTEQAALAAVDYINKHLPRGYK
HTLNQIDSVK VWPRRPTGEVYDIEIDTLETTCHVLDPTPLANCSVRQQTQHAVEGDCDIHVLK
QDGQFSVLFTK CDSSPDSAEDVRKLCPDCPLLAPLNDSRVVHAVEVALATFNAESNGSYL
QLVEISRAQFVPLPVSVSVEFAVAATDCIAK EVVDPTK CNLLAEKQYGFCK GSVIQK
ALGGEDVR VTCTLFQTQPVIPQPQPDGAEAEAPSAVPDAAGPTPSAAGPPVASVVVGPSVVAV
PLPLHRAHYDLRHTFSGVASVESSSGEAFHVGK TPIVGQPSIPGGPVR LCPGRIRYFKI
Bovine fetuin structure43
32
APPENDIX 4. METHOD VALIDATION: SOMATROPIN QUANTIFICATION USING
BOVINE FETUIN AS INTERNAL STANDARD AND LC-MS/MS ANALYSIS
The LC-MS/MS method was validated for the analysis of somatropin in human plasma
using bovine fetuin as internal standard. The validation process was based on the
WIL Research Europe SOP, which is conform FDA and EMA principles on bioanalytical
method validation. The samples were as follows: blank human plasma with and without IS,
system suitability test standards, calibration standards, 6 different blank human plasma
(3 male and 3 female) with and without IS, quality controls (QC-L, QC-M, QC-H) in 5-fold,
matrix effect controls in 2-fold prepared with 6 different human plasma and reference
controls (at QC-L and QC-H level) in 3-fold prepared with 50 mM ammonium bicarbonate.
These were treated according to protocol 2 (described in paragraph 2.4).
Three analytical runs were performed. For this validation two of the most sensitive peptides
for each protein were monitored, namely IVQCR and LEDGSPR for somatropin, and
ALGGEDVR and TPIVGPSIPGGPVR for bovine fetuin (IS). The results were similar,
therefore just the results for somatropin peptide LEDGSPR (transition LEDGSPRDGSPR,
387.4++531.3+) and IS peptide ALGGEDVR (transition ALGGEDVRGGEDVR,
408.9++632.6+) are given in this appendix.
Before each analytical run, a system suitability (SST) standard was injected in triplicate.
The SST standard had the concentration level of the QC-LLOQ, namely 3 µg/mL and is
used to determine the assessment criteria for future analyses, namely retention time
window and minimum height/area ratio of the analyte peak.
The retention time window had been found between 0.67 and 1.14 minutes for somatropin
and between 0.74 and 1.24 minutes for bovine fetuin, following the 75% of the minimum
retention time and 125% of the maximum retention time guideline. The guideline for the
minimum height/area ratio stipulates that this ratio has to be higher than or equal to 75% of
the calculated minimum height/area ratio of the peak. The minimum height/area ratio had
been found 0.503 for somatropin and 0.584 for the IS. The results of the system suitability
tests are given in Table 11 and 12.
Table 11
System suitability parameters - somatropin
Analytical run
1
2
3
Criteria for
further analysis
SST-1
0.91
0.89
0.90
Retention time (min)
SST-2
SST-3
0.90
0.91
0.89
0.90
0.90
0.89
SST-1
0.743
0.671
0.869
between 0.67 – 1.14
Ratio height/area
SST-2
0.683
0.783
0.724
SST-3
2.71
0.757
0.795
>0.503
Table 12
System suitability parameters - bovine fetuin (IS)
Analytical run
1
2
3
Criteria for
further analysis
SST-1
0.98
0.98
0.98
Retention time (min)
SST-2
SST-3
0.99
0.99
0.98
0.98
0.98
0.98
between 0.74 – 1.24
SST-1
0.812
0.840
0.817
Ratio height/area
SST-2
0.899
0.872
0.826
SST-3
0.984
0.778
0.845
≥ 0.584
33
Further, the following parameters were tested: selectivity, carry-over, calibration line,
accuracy and precision, matrix effect, the stability of the samples (freeze/thaw stability,
short term stability at room temperature) and the stability of processed samples
(at 4⁰C after 47 hours).
Selectivity
The selectivity of the analytical method was determined by analysing, in the first analytical
run, human plasma from six different sources. The applied criteria for selectivity were as
follows: the peak area of the matrix which eluates with somatropin, has to be ≤ 20% of the
peak area of the analyte at the LLOQ level (3 µg/mL) and ≤ 5% of the response of the IS.
The interference of the third batch human plasma was higher than this norm, therefore a
selectivity reanalysis was carried out. For reanalysis, samples in triplicate at the QC-LLOQ
level were prepared with the batch 3 plasma. The mean accuracy was found 85% and the
coefficient of variation 15%, which fell within the criterion range of 80-120% and ≤ 20%.
The chromatograms of the blank samples showed no interfering components at the
retention time of the internal standard in the first four plasma batches. In the last two
samples IS was accidentally added. After reanalysis, no matrix interference with IS was
found. In conclusion, the analytical method was found to be selective for the IS and
somatropin at concentration levels ≥ 3 µg/mL. Table 13 shows the results of the selectivity
test for somatropin and bovine fetuin (IS).
Table 13
Selectivity test for somatropin and bovine fetuin (IS)
Matrix batch
1
2
3
4
5
6
Interference for analyte (%)
20
10
26*
0
0
16
Interference for IS (%)
0
0
0
0
133**
97**
* after reanalysis, the matrix interference with the analyte met the requirements
** accidentally IS was added to these samples; after reanalysis, no interference with IS was found.
Carry-over
Carry-over was determined over three runs by analysing a blank sample after the highest
calibration standard. Carry-over has to be ≤ 20% of the analyte response in the QC-LLOQ
and ≤ 5% of the IS response. The carry-over percentages are given in Table 14.
The chromatograms of the blank samples showed no response at the retention time of the
internal standard, thus carry-over had no effect on the accuracy of bovine fetuin in human
plasma. The response at the retention time of somatropin was higher than 20% of the
response in the QC-LLOQ, thus carry-over of somatropin was observed. Further, was
observed that carry-over decreased after analysis of blank solutions. With future sample
analysis blank solutions should be analysed throughout analytical runs and the effect of
carry-over on the results of the study samples should be evaluated.
Table 14
Carry-over percentages of somatropin and bovine fetuin (IS)
Analytical run
1
2
3
Carry-over somatropin
(in 2-fold) (%)
I
II
31
57
54
57
28
55
Carry-over bovine fetuin (IS)
(in 2-fold) (%)
I
II
0
0
0
0
0
0
34
Calibration line
Calibration standards (3.0, 6.0, 15, 30, 75, 150, 375 and 900 µg/mL) were analysed in
duplicate, at the beginning and at the end of each analytical run. A blank sample and a
blank sample with IS were analysed before the first set of calibration standards. Calibration
line was obtained by linear regression analysis with an (1/concentration2) weighing factor.
The individual data of the calibration line are given in Table 15 and the calibration line
parameters in Table 16.
The SOP stipulates that a calibration line is accepted if the back calculated accuracies are
between 80-120% for the lowest calibration standards and between 85-115% for the other
calibration standards. When a back calculated accuracy did not comply with this norm, then
the calibration line has to be re-evaluated. If ≥ 75% of the calibration standards and for core
runs at least one calibration standard of a concentration level fulfilled the acceptance
criteria, than is the calibration line accepted.
The calibration line had been re-evaluated because seven accuracies were outside the
acceptance criteria. The percentage of the calibration standards which fulfilled the
acceptance criteria was 85%. However, both calibration standards C2 and both C7 in the
third analytical run did not fulfil the second requirement of the re-evaluation. Normally, the
third analytical run should have been reanalysed. Unfortunately, there was not enough
somatropin substance left for reanalysis. However, in the guidelines for bioanalytical
method validation of FDA30 and EMA31, a minimum of six calibration standards is required.
Therefore, this assay was considered linear in the 3.0 - 900 µg/mL range.
Table 15
Individual data of the calibration line
Analytical
run
1
2
3
*)
Back calculated concentration (ng/mL) and accuracy (%)
C1
C2
C3
C4
C5
C6
C7
C8
2.87
96%
3.39
113%
3.04
101%
*)
1.95
65%
3.01
100%
2.95
98%
5.19
86%
6.23
104%
5.69
95%
6.04
101%
*)
4.13
69%
*)
4.86
81%
13.0
87%
*)
12.0
80%
14.6
97%
16.1
108%
16.9
113%
*)
18.7
124%
26.8
89%
28.9
96%
29.2
97%
28.9
96%
27.4
91%
27.7
92%
77.1
103%
76.7
102%
78.4
105%
83.4
111%
83.7
112%
*)
93.3
124%
153
102%
148
99%
146
97%
142
95%
137
91%
149
99%
383
102%
396
106%
364
97%
373
100%
*)
542
145%
*)
640
171%
1067
119%
1037
115%
871
97%
929
103%
903
100%
922
102%
*)
values outside acceptance criteria (not used for the calculation of the calibration line)
Table 16
Calibration line parameters
Analytical
run
1
2
3
Intercept
Slope
Correlation coefficient
0.01286
0.01709
0.02302
0.01999
0.02181
0.01795
0.99470
0.99843
0.99629
35
Accuracy and precision of the quality controls
The accuracy and precision of the method were established by analysing quality control
samples at four concentration levels in 5-fold. The concentrations were: QC-LLOQ 3 µg/mL,
QC-L 9 µg/mL, QC-M 45 µg/mL and QC-H 675 µg/mL. The QC’s were positioned between
the calibration standards with at least one QC set at the beginning and one at the end of the
analytical run. The within-run and between-run accuracy and precision should be between
80-120% range respectively ≤ 20% for the controls at the QC-LLOQ level and between
85-115% and ≤ 15% for the other QC’s. The results are given in Tables 17-20.
In the third analytical run, the individual accuracy of QC-LLOQ had two outliers
(66 and 67%). Therefore, the within-run precision was 23% and did not meet the
requirements. As a result, extra tests should be performed to confirm the LLOQ level.
Table 17
Accuracy and precision of QC-LLOQ
Analytical run
1
2
3
Concentration (µg/mL)
Accuracy (%)
Target Nominal Analysed Individual Within- Betweenrun
run
3
3.00
2.28
76
106
98
3.00
2.92
97
3.00
3.99
133
3.00
3.29
110
3.00
3.49
116
3
3.00
2.88
96
99
3.00
2.39
80
3.00
3.97
132
3.00
2.87
96
3.00
2.71
90
3
3.00
3.23
108
89
3.00
2.49
83
3.00
1.98
66
3.00
3.71
124
3.00
2.00
67
Precision (%)
Within- Betweenrun
run
23
0
Table 18
Accuracy and precision of QC-L
Analytical run
1
2
3
Concentration (µg/mL)
Accuracy (%)
Target Nominal Analysed Individual Within- Betweenrun
run
9
9.00
9.44
105
95
97
9.00
7.22
80
9.00
9.62
107
9.00
7.95
88
9.00
8.71
97
9
9.00
8.77
97
94
9.00
8.34
93
9.00
8.29
92
9.00
8.86
98
9.00
7.89
88
9
9.00
8.38
93
102
9.00
9.23
103
9.00
9.29
103
9.00
9.30
103
9.00
9.57
106
Precision (%)
Within- Betweenrun
run
8
3
36
Table 19
Accuracy and precision of QC-M
Analytical run
1
2
3
Concentration (µg/mL)
Accuracy (%)
Target Nominal Analysed Individual Within- Betweenrun
run
45
45.0
43.4
96
105
106
45.0
50.6
113
45.0
48.0
107
45.0
48.3
107
45.0
45.8
102
45
45.0
45.0
100
101
45.0
46.7
104
45.0
48.2
107
45.0
44.3
98
45.0
42.4
94
45
45.0
48.0
107
111
45.0
50.0
111
45.0
52.8
117
45.0
49.4
110
45.0
49.8
111
Precision (%)
Within- Betweenrun
run
5
4
Table 20
Accuracy and precision of QC-H
Analytical run
1
2
3
Concentration (µg/mL)
Accuracy (%)
Target Nominal Analysed Individual Within- Betweenrun
run
675
675
631
93
100
104
675
669
99
675
694
103
675
684
101
675
682
101
675
675
713
106
102
675
663
98
675
703
104
675
669
99
675
691
102
675
675
736
109
110
675
727
108
675
735
109
675
791
117
675
710
105
Precision (%)
Within- Betweenrun
run
4
5
Matrix effect
The influence of the matrix on somatropin was investigated by analysing samples in 2-fold
at the QC-L and QC-H level, namely 9 µg/mL and 675 µg/mL, prepared in six different
sources of human plasma and in 50 mM ammonium bicarbonate (reference samples).
The normalized matrix factor was determined as ratio of the response of the matrix sample
to the mean response of the reference samples. The coefficient of variation of the mean
normalized matrix factor has to be ≤ 15% at each concentration level. The results of the
matrix effect samples are given in Table 21. The coefficient of variation was 12% for the low
concentration and 6% for the high concentration, thus the matrix effect had no significant
effect on the analysis of somatropin in human plasma.
37
Table 21
Matrix effect
Analytical run
Target
concentration
(µg/mL)
9
Lot of human
plasma (matrix)
Normalized matrix
*)
factor
01
Coefficient of
variation
(%)
11
1.050
1.050
02
0.839
0.964
03
1.080
1.110
04
0.830
1.080
05
0.943
0.802
06
0.974
1.100
675
01
5
0.826
0.886
02
0.852
0.943
03
0.866
0.883
04
0.873
0.912
05
0.824
0.913
06
0.947
0.932
*)
the normalized matrix factor is the ratio between the response of the QC prepared in matrix and the
mean response of the QC’s prepared in 50 mM ammonium bicarbonate (reference samples)
1
Freeze/thaw stability
Somatropin samples at the QC-L and QC-H level, in 3-fold, were analysed after three
freeze/thaw cycles. Each cycle involved a storage period of a minimum of 12 hours in the
ultra-low-freezer (≤ 75⁰C) and thawing at room temperature for at least 2 hours. The results
of the freeze/thaw stability test are given in Table 22. The mean accuracies of the samples
fell within the criterion range of 85-115%, therefore the freeze/thaw stability was considered
acceptable.
Table 22
Freeze/thaw stability (3 cycles)
Analytical
run
Freeze thaw
cycles
3
3
Target
9
3
675
Concentration
(µg/mL)
Nominal
9.00
9.00
9.00
675
675
675
Analysed
8.79
6.75
9.03
741
704
743
Accuracy
(%)
Individual
Mean
98
91
75
100
110
108
104
110
38
Short term matrix stability at room temperature
Somatropin samples at the QC-L and QC-H level in 3-fold, were analysed after being stored
for 28 hours at room temperature. The results of the short term matrix stability are given in
Table 23. The mean accuracies of the samples were within the criterion range of 85-115%,
therefore can be concluded that somatropin samples were stable when stored at room
temperature up to 28 hours.
Table 23
Short term matrix stability at room temperature
Analytical
run
Time
(hours)
3
28
Target
9
28
675
Concentration
(µg/mL)
Nominal
9.00
9.00
9.00
675
675
675
Analysed
10.2
8.59
8.87
763
772
752
Accuracy
(%)
Individual
Mean
113
102
95
99
113
113
114
111
Processed sample stability stored at 4°C (in the refrigerator/autosampler)
Somatropin samples at the QC-L and QC-H level in 3-fold, were analysed after being
processed and stored for 47 hours at 4⁰C (in the autosampler). The results of the stability
test are given in Table 24. The mean accuracies of the samples were within the criterion
range of 85-115%, therefore it can be concluded that somatropin processed samples were
stable when stored at 4⁰C for up to 47 hours.
Table 24
Stability of processed somatropin samples stored 47 hours at 4⁰C
Analytical
run
Time
(hours)
3
47
Target
9
47
675
Concentration
(µg/mL)
Nominal
9.00
9.00
9.00
675
675
675
Analysed
8.36
7.82
7.53
685
690
703
Accuracy
(%)
Individual
Mean
93
88
87
84
101
103
102
104
In conclusion the LC-MS/MS bioanalytical method was validated for the analysis of
somatropin in human plasma based on signature peptide.
39
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