Minimising laboratory-induced decay in bone proteomics

Noemi Procopio1, Michael Buckley1*.

1Manchester Institute of Biotechnology, The University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK

*Correspondence to m.buckley@manchester.ac.uk; +44(0)161 306 5175

Abstract

Proteomics methods are being increasingly used to study archaeological and

palaeontological bone, assisting in species identification and phylogenetic studies as well

as improving our understanding of bone diagenesis. More recently, there are developing

interests in the study of post-translation modifications (PTMs), some of which are

potentially diagnostic of decay, but none of the previous extraction methods have been

developed in light of this. To be able to record close to natural deamidation levels of

samples an extraction procedure should minimise laboratory-induced decay, such as

asparagine and glutamine deamidations, which are considered most strongly related with

decay and known to occur frequently with standard laboratory procedures. Here we tested

numerous methods to identify an optimal approach of extracting proteins from bone whilst

minimising artificial decay. Using a weak acid to partially demineralize the bone sample,

then subsequent incubation of the acid insoluble fraction with guanidine hydrochloride and

enzymatic digestion in ammonium acetate, we observed a ~50% reduction in deamidation

whilst also substantially decreasing the protocol length. We propose this optimised method

as appropriate for studies of archaeological, palaeontological as well as potentially forensic

investigations using proteomics where decay measurements could act as ‘molecular

timers’.

Keywords

Bone proteome – deamidation – forensics – post-mortem interval – shotgun proteomics

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Introduction

In recent years proteomics methods have been increasingly applied to the study

and characterization of bone, both modern1–3 and ancient4–6. Although the majority of

publications have investigated the dominant protein collagen for phylogenetic inferences7–9

and species identification10–13 to address archaeological and paleontological questions, the

suite of non-collagenous proteins (NCPs) like serum proteins and collagen-interacting

proteins present in sub-fossil bones are proving an exciting potential source for further

taxonomic information14. Unsurprisingly, most bone proteomic techniques have been

optimised for extracting the greatest number of different proteins (i.e., proteome

complexity) from the sample. However, the study of post-translational modifications

(PTMs) of proteins, such as oxidation15,16, deamidation17–19 and racemization20,21 have

become of greater interest because they can be used as degradative markers potentially

useful for post-mortem decay related studies17,22. The recording of some of these particular

PTMs is not only of interest to studies investigating the decay state, and therefore relative

age of ancient remains under similar burial histories, but of potential use in investigating

the timing of more recent decay in the field of forensics.

Apart from the differences in their chemistry, each of these PTMs is also

characterised by different kinetic rates, which can be influenced by several different factors

like the protein structure, the temperature, the pH and the ionic strength23. For example,

racemization of some amino acid residues requires more time to naturally occur than other

modifications such as deamidation and oxidation24. Where protein oxidation is thought to

be more strongly related with ageing phenomena in vivo15 with post-mortem oxidation

observed in muscle tissue25, protein deamidation can be more readily influenced by

several different factors, such as protein structure, temperature, pH and ionic strength26,

and has been shown to act physiologically as a molecular clock for protein turnover,

development and ageing27–31. Furthermore, deamidation can also increase post-mortem18,22

and so has been suggested potentially useful in palaeontological studies as a means for

authenticating the protein as being endogenous rather than contaminant32.

However, inappropriate handling and manipulation of bone samples to extract

proteomic information, including PTM data, could lead to incorrect interpretations of the

biological phenomena. In particular, protein deamidation levels have already been shown

to be strongly affected by the laboratory procedure used to extract proteins from the

specimen33–35, which will be evaluated in this study.

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Bone structure and its proteomeBone is the most likely tissue to survive long periods of burial, characterised by

different components described generally as an inorganic phase (50-70%), organic phase

(20-40%) and a water component (5-10%). The mineral phase is composed of calcium

phosphates (hydroxyapatite) and provides mechanical rigidity and strength, whereas the

organic phase is composed fundamentally of proteins and a small fraction of lipids (<3%),

and provides elasticity and flexibility36,37. About 90% of this organic component is

represented by long fibrils of Type I collagen, a structural molecule in the extracellular

matrix (ECM) characterised by a triple-helix domain composed of three α chains known as

tropocollagen36,37; in mammals, each tropocollagen molecule is made up of two identical

α1(I) chain and one α2(I) chain36. The remaining 10% organic matter is primarily

composed of NCPs but includes minor amounts of other biomolecules such as lipids and

DNA. Of the NCPs there are four main groups: glycosaminoglycan (GAG)-bearing proteins

(e.g., aggrecan, versican, decorin, biglycan and fibromodulin), glycoproteins (e.g., alkaline

phosphatase, osteonectin, tetranectin, thrombospondin, fibronectin, vitronectin,

osteopontin and bone sialoprotein), -carboxy-glutamic acid (Gla)-containing proteins

(osteocalcin and matrix-Gla-protein) and numerous other proteins such as proteolipids,

collagen-degrading metalloproteinases, bone morphogenetic proteins, growth factors,

serum-derived proteins and cell-binding proteins38,39. Many of these have functions relating

to the promotion of mineralization and other aspects of bone formation and remodelling.

Existing approaches to post-mortem interval estimationOne of the most common questions that forensic experts face is the estimation of

post-mortem interval (PMI), which can be informative on the historical truth behind a

forensic case. There are currently several standard strategies that are used to investigate

PMI, such as thanatochemistry40,41 and forensic entomology42,43, which typically investigate

the soft tissue phase of decomposition44. In doing so they suffer from poor precision and

reliability where different experts often arrive at different conclusions from analyses of the

same samples40,45,46. To improve reliability, biomolecular methods have been previously

investigated, ranging from post-mortem DNA degradation47,48 and RNA degradation

studies49 to the measurement of the levels of some proteins accumulated in the tissues

after death50–52. They have proven promising but have so far only been investigated for

short PMIs and are not ideal for longer post-mortem periods. Other strategies have been

developed to get information from bodies heavily decomposed and skeletonized which

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vary substantially from approaches based on morphological studies44,53 and histological

changes44 to analytical methods. Specific to bone analysis, these include the evaluation of

their loss of nitrogen44, loss of fluorescence pattern44,53 and loss of immunologic activity44.

More obscure methods involve the evaluation of radioisotopes present in the tissue54, the

citrate content of bones55, and the use of luminol on old skeletal remains for the detection

of blood56. Some protein-based methods have been reported, such as the measurement of

the reduction of particular amino acid levels in skeletal remains57, but with notable limits

regarding the accuracy of results44. Hence, given the recent advancements of proteomics

techniques, the development of alternative protein-based approaches to decay

measurements could be useful to determine the correct PMI from bone samples; this study

aims to set the scene for the use of proteomics as one such approach to decay estimation

– in this case the measurement of protein deamidation.

Post-translational modificationsIn addition to those already introduced (e.g., deamidation and oxidation), proteins

undergo a wide range of other modifications during the ageing process, such as

carbonylation58,59, glycation60,61, cross-linking62,63, racemization64,65, nitration65,66. However,

the deamidations of asparagine (Asn) and glutamine (Gln) are particularly ideal for use as

a ‘molecular clock’ because they occur physiologically in vivo in a time-dependent way67.

Protein deamidation is a non-enzymatic process that is characterised by the hydrolysis of

the amide linkage in Asn and Gln residues leading to the formation of a succinimide

intermediate and followed by the generation of the carboxylic acids aspartic acid and

glutamic acid respectively68. Moreover, deamidation can also occur by direct hydrolysis in

an acidic environment, without the formation of the succinimide intermediate which instead

is more commonly created under neutral or alkaline conditions68. With some previous

analyses linking deamidation levels of in situ archaeological collagen with ageing18,22, and

others demonstrating a correlation between in vivo protein deterioration and deamidation

rates67,69, we speculate that the study of shorter-term decay markers could have

applications in forensic investigations with further research. Specific studies have shown

that deamidation in vivo is influenced by protein primary28, secondary70 and tertiary

structure71, but also by several other factors such as temperature72,73, pH conditions34,73 and

ionic strength73. As such, deamidations are also known to occur in vitro67 during sample

processing steps and can arise during several phases of the protein extraction and

digestion methods most commonly used, particularly under strong pH and long exposures

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to high temperatures34,35 resulting in an overestimation of deamidation levels. The aims of

this research are to address this issue.

Previous approaches to reducing deamidationIn order to investigate the study of deamidation levels in bone proteins it is

fundamental to minimise those introduced during laboratory protocols. Two main

improvements to the in-solution digestion process with trypsin have been proposed; one

approach is the reduction of digestion times down to less than one hour rather than

overnight or day-long processes35 whereas another approach is the use of different

digestion buffers33. In the case of the former it can be inferred that the reduced digestion

length will not always be applicable to complex mixtures of proteins (such as a complete

proteomes from a biological sample) because such a short incubation with the enzyme

reduces digestion efficiency34. In the case of the latter it has been shown that laboratory

processing-induced Asn deamidation is less pronounced in ammonium acetate than in

other buffers more commonly used in proteomics methods, such as ammonium

bicarbonate. There are likely several other parameters that are also influential in reducing

processing-induced deamidations, such as incubation length within the protein extraction

buffers and the pooling of different extractions. Therefore, the purpose of our study was to

optimise the existing protocols for protein bone extraction14,74,75 taking into consideration

the suggested digestion improvements previously reported33,35 as well as other factors

likely to influence levels of protein decay (decalcification agent and extraction length), in

order to identify the optimum compromise between obtaining a diverse proteome whilst

reducing processing-induced deamidations.

Experimental SectionMaterials

A single modern cow tibia was acquired from a local butcher. Dentist’s Protaper

Universal shaping files used for the drilling procedures were purchased from Henry Schein

Minerva Dental (UK). Hydrochloric acid (HCl), acetonitrile (ACN) and

ethylenediaminetetraacetic acid (EDTA) were purchased from Fisher Scientific (UK); nitric

acid (HNO3) was purchased from VWR International; formic acid (FA) and ammonium

bicarbonate (ABC) were purchased from Fluka (UK); Tris, dithiothreitol (DTT),

iodoacetamide (IAM), trifluoroacetic acid (TFA), guanidine hydrochloride (GuHCl),

ammonium acetate (AMAC) and acetic acid (AcOH) were purchased from Sigma-Aldrich

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(UK), 10K Molecular Weight Cut Off (MWCO) ultrafiltration units were purchased from

Vivaspin (UK); sequencing grade trypsin was purchased from Promega (UK), and C18

reversed-phase Zip-Tips were purchased from Agilent Technologies (UK).

MethodsAs part of method development, several different variable parameters were tested in

order of assumed importance (Fig. 1). The starting protocol in which different modifications

have been introduced was taken from Wadsworth and Buckley14 and the variants have

been chosen from previously published methods33,74,76,77. For all experiments, cow bone

powder was manually drilled with sterile dentist’s Protaper Universal shaping files in order

to minimise the decay induced by electric drilling procedures. Approximately 25 mg of

powder was used for each analysis, carried out in triplicate starting from three different

biological samples taken from the same anatomical position of the bone to minimise the

variability within different samples.

Figure 1 - Flow charts of the overall experimental design followed in this study: A) initial tests of different acids, demineralization lengths (0.5 M EDTA only) and digestion buffer and lengths (0.5 M EDTA only) and B) further evaluation of fraction pooling.

Demineralization processFive different acids (0.6 M HCl, 0.5 M EDTA, 6% AcOH, 5% HNO3 and 10% FA) for

the demineralization of the bone sample were tested with 1 mL of acid added to each

sample in triplicate, mixed thoroughly and placed at 4°C for 66 h. After demineralization,

samples were centrifuged at 14,000 × g for 1 min and the acid soluble supernatant

removed from the acid insoluble pellet and frozen. The insoluble pellet was then incubated

with a buffer containing 6 M GuHCl and 100 mM Tris at pH 7.4 at 4°C for 66 h. Then both

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soluble and insoluble fractions were centrifuged as above and the supernatants

exchanged into 50 mM ABC using 10 kDa MWCO ultrafiltration units, collecting the

retentate with 200 µL ABC. The proteins in this solution were then reduced using 8.4 µL

5 mM DTT for 40 min at room temperature and alkylated using 33.6 µL 15 mM IAM in the

dark for 45 min at room temperature. The alkylation step was then quenched by adding a

further volume of 5 mM DTT and samples were digested using 1 μg trypsin at 37°C for

18 h.

Demineralization lengthDifferent time intervals were tested for the demineralization of the bone sample in

order to obtain the best compromise between proteome complexity (i.e., the diversity of

the proteins observed measured as a protein count) and minimum observed levels of

protein decay (measure of peptide deamidations). To do so, EDTA was added to

demineralize the samples over 6, 24 or 48 h and the subsequent steps for the proteome

extraction were carried out as described above.

Digestion buffer and digestion lengthTo compare the use of 50 mM ABC (at pH 8.7) with 50 mM AMAC33 (at pH 6.7) as

an alternative buffer for tryptic digestion, following demineralization with EDTA (~66 h at

4°C) and incubation of the acid insoluble pellets (at 4°C for ~66 h) the pooled acid soluble

and acid insoluble fractions were ultrafiltered into either buffer and then reduced and

alkylated as described above but subsequently digested for either 1, 5 or 18 h.

GuHCl incubation length and protocol refinementTo investigate extraction incubation length, following demineralization with EDTA

(4°C for 6 h) the samples were centrifuged at 14,000 × g for 1 min and the acid insoluble

fraction incubated in a 6 M GuHCl buffer containing 100 mM Tris at pH 7.4 at 4°C for either

18, 42 or 66 h. Then both the acid soluble fraction and acid insoluble fractions were pooled

and ultrafiltrated together into 50 mM AMAC and the retentate collected with 200 μL of

AMAC. For practical reasons, the samples were then frozen overnight and subsequently

reduced, alkylated, quenched and digested for 5 h as described above.

The same experiment was then repeated to refine the methodology with two

modifications; firstly, the overnight freezing of the samples before the digestion was

avoided to exclude bias in the results, secondly, the soluble fraction of the samples was

separated and excluded from the analyses, and only the acid insoluble fraction was

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ultrafiltrated in order to reduce the relative concentrations of collagen within the samples.

All successive steps were carried out as described above.

LC-Orbitrap Mass SpectrometryFor all methods tested, 1% TFA was added to the samples to stop the digest

(making 0.1% TFA), which were then desalted, purified and concentrated using OMIX C18

reversed-phase Zip-Tips following manufacturer’s protocols. Tips were prepared with two

volumes of 100 μL 0.1% TFA/50% ACN and then washed twice with 100 μL of 0.1% TFA.

The sample was then introduced to the C18 tips 5-10 times to allow peptides to bind,

followed by two wash steps with 100 μL of 0.1% TFA and a final elution in 100 μL of 50%

ACN and 0.1% TFA. Samples were dried under a fume cupboard for one day (at room

temperature) and then re-suspended in 20 μL of 0.1% TFA/5% ACN for subsequent

LC/MS/MS analysis. Re-suspended samples were analysed by LC/MS/MS using an

UltiMate® 3000 Rapid Separation LC (RSLC, Dionex Corporation, Sunnyvale, CA, USA)

coupled to an Orbitrap Elite (Thermo Fisher Scientific, Waltham, MA, USA) mass

spectrometer (120 k resolution, full scan, positive mode, normal mass range 350–1500).

Peptides were separated on an Ethylene Bridged Hybrid (BEH) C18 analytical column (75 

mm × 250 µm i.d., 1.7 μM; Waters) using a gradient from 92% A (0.1% FA in water) and

8% B (0.1% FA in ACN) to 33% B in 44 min at a flow rate of 300 nL min–1. Peptides were

then automatically selected for fragmentation by data-dependent analysis; six MS/MS

scans (Velos ion trap, product ion scans, rapid scan rate, Centroid data; scan event: 500

count minimum signal threshold, top 6) were acquired per cycle, dynamic exclusion was

employed, and one repeat scan (i.e. two MS/MS scans total) was acquired in a 30 second

repeat duration with that precursor being excluded for the subsequent 30 seconds

(activation: collision-induced dissociation (CID), 2+ default charge state, 2 m/z isolation

width, 35 eV normalized collision energy, 0.25 Activation Q, 10.0 ms activation time).

Data analysisSpectra obtained via LC/MS/MS were searched as .mgf files (created assuming 0

#C13s with peak list generation using ExtractMSN) against the Swiss-Prot database

(540,052 entries) using the Mascot search engine (version 2.4.1; Matrix Science, London,

UK). Each search included the fixed carbamidomethyl modification of cysteine (+57.02 Da)

and the variable modifications for deamidation (+0.98 Da) of asparagine/glutamine and

oxidation (+15.99 Da) of lysine, proline and methionine residues, to account for PTMs and

diagenetic alterations; the oxidation of lysine and proline is equivalent to hydroxylation.

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Enzyme specificity was set up to trypsin with up to 2 missed cleavages allowed, mass

tolerances were set at 5 parts per million for the precursor ions and 0.5 Daltons for the

fragment ions, with all spectra considered as having either 2+ or 3+ precursors. A search

with semiTrypsin specificity was also performed maintaining all other parameters; results

can be found in the Supporting Information.

It should be noted that the data were searched without any allowance for incorrect

monoisotopic peak detection to avoid the inclusion of false positive results at the cost of an

increased number of false negatives; as the occurrence of incorrect peak detection is

random this does not bias the results in these analyses. The identification rates could

potentially be improved by using a process that recalculates the monoisotopic peak from

the raw data such as Matrix Science’s Mascot Distiller, but this would not significantly

affect the experimental outcome.

To compare samples counting the number of proteins as well as the number of

deamidated peptides, Scaffold software version 4.4.1 (Proteome Software Inc., Portland,

OR) was used. Peptide identifications were accepted if they could be established at

greater than 95% probability by the Peptide Prophet algorithm78 with Scaffold delta-mass

correction. Protein identifications were accepted if they could be established at greater

than 99.0% probability and contained at least two identified peptides; protein probabilities

were assigned by the Protein Prophet algorithm79. Proteins that contained similar peptides

and could not be differentiated based on MS/MS analysis alone were grouped to satisfy

the principles of parsimony. The display option chosen for this work was “total spectrum

count” which shows the total number of spectra acquired for each protein during the

analysis and allows semi-quantitative measurement of the proteins present in the sample.

In Scaffold, the three replicates were grouped together and each experimental condition

considered as a distinct group. Subsequently, only proteins containing the keyword

“bovine” were filtered and selected in order to avoid the presence of proteins unrelated

with the bone sample. In addition, the filter related to the presence of deamidation was

also used to extrapolate data for the deamidation analysis. Then data were exported into

an Excel spreadsheet followed by the calculations of averages and standard deviations

(SD) for each group of replicates for all proteins matched.

STRING software (version 10.0) was used to create networks of the proteins

obtained with the optimised protocol. These protein interactions include direct (physical)

and indirect (functional) associations derived from “genomic context”, “high-throughput

experiments”, “co-expression” and “previous knowledge”. The clustering option chosen for

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the graphs was KMEANS = 4, and the view utilised was the “confidence view” (in which

the line thickness between proteins was proportionally related to the strength of the

associations).

Results and Discussion

Ideally an optimised protocol for protein extraction should recover a complex

proteome (i.e., relatively high number of different proteins detected) without generating

processing-induced deamidations during the procedure. To improve upon some of the

current methods used for protein extraction from bone samples, we tested different

parameters considered to be crucial for the production of processing-induced

deamidations and explored alternatives for each. We initially evaluated the effects that two

parameters could have on the demineralization process: 1) the acid used for

demineralization (0.6 M HCl, 0.5 M EDTA, 6% AcOH, 5% HNO3 and 10% FA), and 2) the

length of this demineralization step (6, 24 and 48 h). We then investigated the digestion

step, testing different buffers (50 mM ABC and 50 mM AMAC) and different time lengths

(1, 5 and 18 h). Finally, we not only evaluated the effects of different incubation times (18,

42 and 66 h) in GuHCl for the acid insoluble fraction of the protein extract, but also

compared results between analyses performed pooling both fractions of the extract (acid

soluble and extracted insoluble fractions), and analyses using only the acid insoluble

fraction. We found this latter experiment appropriate given the likelihood that the much

more dominant collagen peptides present in the acid soluble fraction would interfere with,

and ultimately reduce, the remaining NCPs to the extent that previous studies have

attempted to specifically remove as much collagen as possible14.

Optimum demineralizing agentWhen extracting proteins from bone, demineralization/decalcification is a

fundamental step to remove calcium salts from the protein-rich organic matrix, which

substantially improves the efficiency of the protein extraction compared with the protein

extraction method with undemineralized bone74. Although several studies have evaluated

various reagents to improve the extraction efficiency whilst also limiting the laboratory-

induced decay on samples76,77,80,81, none have been done that consider the impact of the

use of different acids on the processing-induced deamidation of proteins. Our hypothesis

is that strong acids, like NA and HCl in this study, could yield a better quality proteome but

at the same time they could increase processing-induced deamidation levels compared

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with weak acids, such as AA, FA and EDTA. To test this, we evaluated both the proteome

recovery and the ratio of deamidated peptides in relation to the total amount of peptides in

the sample (Fig. 2). As shown in Fig. 2A and 2B, the strongest acid (HCl) resulted in the

largest number of unique peptides matched, as well as the greatest proteome variability

compared with the other acids used in this test (572 unique peptides and 71 different

proteins). Acetic acid on the contrary gave the lowest numbers (477 unique peptides and

49 different proteins). Nitric acid yielded a poor proteome variety (58 different proteins)

although the semi-quantitative levels of proteins in this case were better than the levels

obtained using EDTA and AA (531 unique peptides versus 515 matched with EDTA and

477 matched with AA). Formic acid, with 549 unique peptides and 62 different proteins,

was respectively the second best in terms of semi-quantitative levels just after HCl and the

third best in terms of proteome variety, after HCl and EDTA (Fig. 2).

Deamidation rates, calculated by dividing the number of deamidated unique

peptides by the total number of unique peptides obtained from each sample, indicated that

the most deamidated peptides were obtained with NA (21%), followed by HCl (18%), AA

(16%), FA (15%) and EDTA (14%). Overall, as could be expected, weak acids were the

most suitable to minimise the processing-induced deamidation of peptides and, although

HCl yielded a greater proteome variety, it also introduced relatively high levels of

deamidation. Overall, NA performed most poorly, giving similar results to weak acids in

terms of protein recovery but high deamidation rates, whereas EDTA and FA gave similar

extraction efficiencies (FA was better considering the semi-quantitative data whereas

EDTA was better considering the proteome complexity) and significantly reduced levels of

processing-induced deamidations. The SD from samples treated with EDTA in Fig. 2C was

larger than those treated with FA, so we could not establish which induced fewer

deamidations; for these reasons, we assumed that they were both equally suitable for our

aims. As the more common method, we chose to use EDTA for the successive steps of

our work, but we also acknowledge the potential use of FA to gain equally good results.

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Figure 2 – Bar charts showing the average and standard deviation of A) total number of unique peptides, B) total number of proteins, and C) deamidation ratio obtained from three replicates, using different acids to demineralize the sample.

In order to also investigate whether or not the exposure to different acids was

inducing chemical cleavage activity82 we also performed a Mascot search with semiTrypsin

specificity maintaining unchanged all other parameters. From these results (Supporting

Table S-1) it was clear that the levels of semi-tryptic peptides were higher when strong

acids like HCl and NA were used and smaller when weak acids like EDTA, FA and AA

were used, the latter of which gave similar results to one another. This complements the

finding of lower proteome variety in samples treated with NA than with the other weaker

acids when results were searched with only the normal trypsin specificity.

Demineralization lengthConsidering the pH conditions in which samples are typically incubated during the

demineralization process, it was important to evaluate the impact that different

demineralization lengths could have on the final proteome and deamidation rates

observed. Given that shorter periods of incubation in acid should decrease the processing-

induced decay of proteins we performed three different tests incubating the bone powder

with 0.5 M EDTA for 6, 24 and 48 h, spanning most commonly used approaches.

Interestingly the shortest incubation proved to be sufficient at extracting a good quantity

and variety of proteins (Fig. 3A and 3B) and even yielded slightly better results than longer

demineralization periods. It is likely that longer incubation periods were damaging (i.e.,

chemically cleaving) proteins, preventing their identification during the successive steps of

the analysis. This hypothesis was confirmed through Mascot searches with semiTrypsin

specificity (Supporting Table S-1), where prolonged demineralization time periods in

EDTA, despite being a weak acid, caused an increase in proteolysis reducing the

capability to detect full tryptic peptides under normal search conditions. Generally, shorter

demineralization periods are more appropriate than longer ones to avoid protein disruption

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and consequent loss. It was clear that the demineralization length was affecting the

processing-induced deamidation of samples as deamidation rates were lower using

shorter incubation times (Fig. 3C); interestingly, 6 h of incubation reduced the overall

deamidation rates by 26.7% compared with the 48 h incubation (11% deamidations with 6

h versus 12% and 15% with 24 h and 48 h respectively).

Figure 3 - Bar chart representing the average and standard deviation of A) total number of unique peptides obtained, B) total number of proteins, and C) deamidation ratio obtained from three replicates (from two replicates in 48 h test) using different incubation times in 0.5 M EDTA. Due to a poor extraction of one of the three replicates that we performed with 48 h incubation length, one of the replicates was omitted from the calculations to have more acceptable standard deviations and more reliable results; however, the sample was not detected as an “outlier” using the Grubbs’ test with an alpha level of 0.05 (P>0.05; the unfiltered data is presented in Supporting Figure S-1).

Digestion time length and buffer choiceThe enzymatic digestion process is a crucial step of the entire procedure33,35, in

which processing-induced deamidations could be strongly reduced using appropriate

conditions and precautions. Ren et al.35 showed how a reduced digestion length could

significantly decrease the processing-induced deamidation levels, showing that 30 minutes

were sufficient to obtain a complete trypsin digestion on a reduced and alkylated

immunoglobulin, and that only minor protocol-induced deamidations were observed.

However, as they did not perform a comparison between different time lengths and

did not test their proposed method with a complex mixture of proteins, we tested three

different digestion lengths (our standard 18 h, and 1 and 5 h as reduced incubation

lengths) with our complex mixture of bone proteins (Fig. 4).

Additionally, Hao et al.33 instead focused on the buffer used for the digestion of rat

kidneys, using AMAC instead of the standard ABC to reduce levels of artificial Asn

deamidations for complex proteomic samples by reducing the pH of the digest34,83; we also

explored this observation but for the bone tissue.

The results indicate that the digestion length appears to be directly proportional to

the number of unique peptides obtained from each sample (Fig. 4A) as well as to the

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variety of the recovered proteome (Fig. 4B). We found that 1 h digestion was not sufficient

to get an adequate proteome coverage starting from a complex mixture of proteins,

whereby we observed 35% fewer unique peptides than the 18 h digestion, with 29.8% less

proteome variety. With 5 h digestion, we observed intermediate results both considering

the semi-quantitative levels of matched proteins and the proteome variety, losing only

16.6% of the unique number of peptides and the 15.9% of the proteome variety compared

with the longest incubation. These results were also supported through searches with

semiTrypsin specificity (Supporting Table S-1) where prolonged digestion length increased

the number of fully tryptic peptides matched, consequently reducing the levels of

semitryptic peptides observed in the sample. On the other hand, deamidation rates were

generally reduced using shorter incubation lengths, and this was observed for both buffers

tested.

The buffer choice also yielded interesting results where, in accordance with Hao et

al.33, the lowest levels of deamidations were observed in the five hour digests in AMAC

(Fig. 4C; 6% with 5 h digestion in AMAC versus 11% with same digestion length in ABC

and 14% with 18 h digestion in ABC). The more commonly used ABC on the other hand

usually resulted in a more diverse proteome than AMAC (around six more proteins were

frequently obtained with ABC than with AMAC) and greater semi-quantitative results (72

more unique peptides using ABC for 1h compared with AMAC, 70 more peptides with the

5 h and 32 more peptides with the 18 h digestion). Overall, AMAC appeared to greatly

reduce the decay compared with ABC as we observed as much as 43.3% more

deamidated peptides in the 5 h samples digested in ABC, 25.5% in the 1 h samples, and

37.3% more in the 18 h samples. We therefore encourage the use of AMAC as digestion

buffer in future studies relating to this aspect of studying endogenous protein decay.

Additionally, the digestion length of 5 h seemed most appropriate as a compromise

between reducing processing-induced deamidation levels and the complexity of proteome

observed. Further improvements not within the scope of this study, such as more rapid

digestion methods with greater enzyme concentrations, could also be investigated in the

future to reduce deamidation levels further while increasing the digestion efficiency.

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Figure 4 - Bar chart representing the average and the standard deviation of A) total number of unique peptides obtained, B) total number of proteins, and C) deamidation ratio obtained from three replicates using different digestion buffers (ABC, orange and AMAC, green) and using different digestion length.

GuHCl incubation lengthThe final parameter evaluated was the variation in incubation length of the acid

insoluble pellet in extraction buffer. Even though the pH of the GuHCl protein denaturing

solution is near neutral (7.4), we evaluated whether shorter incubation periods were able

to reduce the processing-induced deamidation of proteins compared with more commonly

used longer (66 h) periods of incubation. The results clearly indicated that higher amounts

of proteins could be obtained with prolonged incubation lengths (340 unique peptides

retrieved with 66 h versus 321 and 315 with 18 h and 42 h respectively; Fig. 5A), but

comprehensively the number of proteins gained was similar between short and long

incubation times (40 vs 43; Fig. 5B). However, it was noted that high standard deviations

could have an impact on data interpretation, and possibly differences between different

incubation lengths could be smaller than what we observed (Fig. 5A). With regards

deamidation rates (Fig. 5C), it was clear that shorter incubation periods reduced

deamidation levels, with a 25% reduction of observed deamidation in the 18 h sample

compared with the 66 h sample.

15

Figure 5 - Bar chart representing the average and the standard deviation of A) total number of unique peptides obtained, B) total number of proteins, and C) deamidation ratio obtained from three replicates using different incubation length in GuHCl.

Additional method refinement – pooling extractionsGiven that the aim of this study was the investigation of existing protocols for protein

extraction from bones, taking into consideration levels of processing-induced deamidations

and limiting them as much as possible, we evaluated various steps of standard procedures

that can induce some deamidations due to their temperature, pH and ionic strength.

Comparing the results obtained using the newly defined protocol versus the initial results

obtained during the first acid test, we noticed a substantial reduction of both the proteome

variety and the quantity (40 different proteins and 321 unique peptides versus the starting

71 different proteins and 572 unique peptides).

Previous analyses14,74 have shown that the reduction of collagen levels in the

samples allowed for the observations of greater varieties of NCPs; the relative abundance

of the collagenous proteins are thought to impair the detection of less abundant proteins

during LC/MS/MS analyses, ending with a limited number of other proteins observed. Two

strategies have previously been explored to decrease levels of collagen and/or to increase

levels of NCPs; one used bacterial collagenase to digest the dominant collagen in the

extracted sample14, whereas another74 proposed the use of multiple extraction steps,

keeping separate extractions such as GuHCl incubation to extract relatively more NCPs

than collagen in other fractions.

In order to improve results in terms of proteome variety, we tested a method

involving the incubation of the acid insoluble pellet with GuHCl followed by the extraction

of only this fraction for the successive steps of the procedure, without pooling fractions as

done previously. As expected, a substantial improvement was observed in keeping the two

fractions separate and analysing only the acid insoluble fraction, as the proteome variety

was greater as well as the number of unique peptides matched (Fig. 6A and 6B). In

particular, we observed an increase of 10% for semi-quantitative levels of proteins in the

acid insoluble samples compared with samples with both fractions, and we observed a

20% increase in the number of proteins recovered. The use of only the extracted acid

insoluble fraction is not only improves extraction efficiency but also makes the procedure

faster. However, it is possible that some decay signatures of interest could be specific to

the extracted acid soluble fraction of some sample types – even if their proteomes are

much less complex (Buckley unpublished data).

16

Figure 6 - Bar chart representing the average and the standard deviation of A) total number of unique peptides matched from three replicates using both SOLS and INSOLS (blue) and from two replicates using only INSOLS (orange) and B) total number or proteins using different incubation length in GuHCl obtained from three replicates using both SOLS and INSOLS (blue) and from two replicates using only INSOLS (orange). One of the replicates from the 18 h incubation length experiment was excluded from the final graphs because of its poor extraction, to reduce the standard deviations and produce realistic results; however, the sample was not detected as an “outlier” using the Grubbs’ test with an alpha level of 0.05 (P>0.05) and the complete data are also plotted in Supporting Figure S-2.

The bone proteome obtained from our optimised methodOverall the method proposed involves the demineralization of bone samples with

0.5 M EDTA for 6 h at 4°C, followed by the incubation of the acid insoluble pellet with

GuHCl for 18 h at 4°C, ultrafiltration into 50 mM AMAC and, following reduction and

alkylation at room temperature, digestion with trypsin for 5 h at 37°C. Despite this method

being satisfactory for the intended purposes of minimising deamidations whilst obtaining a

complex proteome, we consider it important to point out that the use of FA instead of

EDTA may be more appropriate for several practical and technical reasons. The EDTA

extractions proved to be substantially more time-consuming than all other acids during the

ultrafiltration step. The presence of sodium ions present in EDTA may also cause some

problems with mass spectrometry analysis if not sufficiently removed, creating adducts

with the protein in the gas phase84. Moreover, FA is becoming increasingly common in

many other proteomics applications in various fields85,86, and normally used to resuspend

proteins before LC/MS/MS analysis; therefore the eventual presence of small amounts of

this acid in the sample after the ultrafiltration will not as greatly affect subsequent

analyses. For these reasons, and because EDTA and FA appear to yield comparable

17

results, future investigations could consider FA for analysis for optimal deamidation

minimisation.

Figure 7 - Scheme of the optimised protocol for the reduction of the artificial decay.

Table 1 - Comparisons between the average number of unique peptides, unique proteins, NCPs, the number of NCPs obtained in the best of the three replicates and the average of the deamidation ratios obtained using the standard protocol (first column) and the proposed optimised one (second column).

18

Overall we have shown that our optimised protocol (Fig. 7) reduces processing-

induced deamidation levels in the samples up to ~50% of other protocols (Table 1), but

can also be carried out much more quickly: in fact, most published methods for bone

proteome extraction require the best part of one week (i.e., at least 3-4 days), whereas our

optimised one only requires two working days to the point of mass spectrometric analysis.

The extracted bone proteomeTo identify associations between the extracted proteins and to visualise the

proteome variety we used STRING software to build a map of protein associations within

the matched pooled proteome obtained using the optimised method (Fig. 8). Our method

allowed the recovery of bone-specific proteins (Fig. 8 yellow nodes), plasma proteins with

functions in bone development and/or turnover (Fig. 8 green nodes), plasma proteins with

coagulation functions (Fig. 8 blue nodes) and other proteins with less well-known

associations (Fig. 8 red nodes). The bone-specific proteins are characterised in particular

by different types of collagen, to which some other bone matrix NCPs are strongly linked,

like osteonectin (SPARC), lumican (LUM) and bone sialoprotein (IBSP). The plasma

proteins formed two main clusters, one of which centred around albumin (ALB), a protein

also present in bone that can be only partially exchanged with the plasma albumin, since

the majority of this protein is permanently fixed in the mineralized matrix of the bone 87. In

addition to apolipoproteins (APOA1, APOA2) involved in the plasma transport of

lipoproteins, transferrin (TF) and fetuin (AHSG) were also part of this cluster. TF is a

plasma protein able to deliver iron to the bone marrow to load newly formed erythrocytes 88,

whereas AHSG is a plasma protein bound to the bone matrix with important functions in

regulating the bone turnover39. The cluster of plasma proteins with coagulation-related

functions includes prothrombin (F2), coagulation factors (F9, F10), fibrinogen alpha and

beta chains (FGA and FGB), vitamin K-dependent protein C (PROC), vitamin K-dependent

protein S (PROS1), and antithrombin-III (SERPIN C1). Finally, the various proteins that do

not cluster strongly with others observed have a multitude of different functions, including

many proteins that are specific to bone such as thrombospondin (THBS1), which bind to

osteonectin, calcium and osteoblasts39, and decorin (DCN), a NCP that is expressed both

in cartilage and in bone39.

19

Figure 8 – Association map of the pooled proteome extracted using our optimised extraction method. Yellow nodes indicate bone specific proteins, green nodes indicate plasma proteins linked with the mineralized phase in bones, blue nodes indicate plasma specific proteins with coagulation functions, and red nodes indicate various remaining proteins with different functions. The black stars indicate proteins observed in each of the three replicates.

20

It is noteworthy that although a substantial number of bone-related proteins were

observed (both collagenous and non-collagenous) even with our minimally damaging

methods, there was a relatively large number of serum proteins matched, along with

numerous more ubiquitously expressed proteins. The successful extraction of a good

variety of NCPs such as albumin, fetuin and decorin, makes this extraction method

potentially suitable for phylogenetic studies and a means of species identification, as it has

been shown that these and others NCPs obtained in this study are characterised by a

higher amino acid variability between different species compared with collagen4.

Furthermore, some of these NCPs can also survive longer in archaeological bones5,89 than

DNA, making them useful for species identification purposes even when ancient DNA is

too degraded4. However, of more specific interest to potential forensic applications is that

the different types of proteins observed may offer an appropriate range of different

sequence environments within which the Asn and Gln residues deamidate at distinctly

different rates.

Conclusions

In this study we have developed an improved method for protein extraction from

bone samples with minimum laboratory-induced decay which provides a good range of

proteins. We observed a ~50% reduction in deamidation levels using this new protocol

compared with results obtained using the protocol used by Wadsworth and Buckley14. In

addition to the strong decrease of deamidation levels, our improved protocol also

dramatically decreased the length of the procedure that originally was almost one week

long down to within two days. We suggest that this method could be considered

appropriate for future studies of archaeological, palaeontological as well as forensic

investigations using proteomics where decay measurements are of interest.

AcknowledgmentsThe authors are grateful to the Royal Society for funding both a PhD studentship

(NP) and university research fellowship (MB) under grants RG130453 and UF120473

respectively. We also acknowledge the technical support of The University of

Manchester’s Faculty of Life Sciences Biomolecular Analysis core facility.

Supporting InformationFigure S-1 – Semi-quantitative levels of proteins obtained, proteome variety and

deamidation ratios from demineralization length test including the first replicate from the 48

h test.

Figure S-2 – Semi-quantitative levels of proteins obtained, proteome variety and

deamidation ratios from demineralization length test including the first replicate from the 18

h test.

Table S-1 – Results of Mascot searches with semiTrypsin specificity performed for acid

test, demineralization length test and digestion test.

Table S-2 – Scaffold peptide results for the analyses of different acids. Table S-3 – Scaffold peptide results for the analyses of different buffer protocols.

Table S-4 – Scaffold peptide results for the analyses of different demineralization lengths.

Table S-5 – Scaffold peptide results for the analyses of different GuHCl incubation

lengths.

Table S-6 – Scaffold peptide results for the analyses of different GuHCl incubation lengths

using only the acid-insoluble fraction.

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