the impact of biosampling procedures on molecular data

The impact of biosampling procedures on molecular data

1

The impact of biosampling procedures on molecular data interpretation

Karl Sköld1, Henrik Alm2, Birger Scholz2

1 Denator AB, Uppsala Science Park, Uppsala, Sweden.

2 Department of Pharmaceutical Biosciences, Division of Drug Safety and Toxicology, Uppsala

University, Sweden,

Running title: The impact of biosampling procedures on molecular data

Contact details:

Karl Sköld, PhD

Denator AB, Uppsala Science Park, Dag Hammarskjölds väg 10a, SE-75183, Uppsala, Sweden.

Email: [email protected], Phone: +46 (0)18 508100

Henrik Alm, PhD.

Department of Pharmaceutical Biosciences, BMC, Box 591, SE-75124 Uppsala University, Sweden,

Email: [email protected], Phone: +46 (0)18 4714265, Fax: +46 (0)18 4714253

Birger Scholz, PhD (corresponding author).

Department of Pharmaceutical Biosciences, BMC, Box 591, SE-75124 Uppsala University, Sweden,

Email: [email protected], Phone: +46 (0)18 4714128, Fax: +46 (0)18 4714253

MCP Papers in Press. Published on February 4, 2013 as Manuscript R112.024869

Copyright 2013 by The American Society for Biochemistry and Molecular Biology, Inc.

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Abbreviations

2-DE Two-dimensional electrophoresis

ATP Adenosine-Tri-Phosphate

BT Bioreaction termination

BTI Bioreaction termination interval

CFI Chemical fixation inactivation

CHS Conductive heat stabilization

FDI Lyophilization inactivation

IHC Immunohistochemistry

MCI Mechano-chemical inactivation

MWR Microwave irradiation

ncRNA Non-coding RNA

PMI Post-mortem interval

PTM Posttranslational modification

SFI Snap-freezing inactivation

SFI+MCI Snap-freezing followed by mechano-chemical inactivation

SNO S-nitrosylation

tempBT Temporary bioreaction termination

termBT Terminal bioreaction termination

HS Heat stabilization


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SUMMARY

The separation between biological and technical variation without extensive use of technical replicates is

often challenging, particularly in the context of different forms of protein and peptide modifications.

Biosampling procedures in the research laboratory are easier to conduct within a shorter time frame and

under controlled conditions as compared to clinical sampling with the later often having issues of

reproducibility. But is the research laboratory biosampling really less variable? Biosampling introduces

within minutes rapid tissue specific changes in the cellular microenvironment; inducing a range of

different pathways associated with cell survival. Biosampling involves hypoxia and hypothermia which

are circumstances for which there are evolutionary conserved defense strategies in range of species and

also are relevant for a range of biomedical conditions. It remains unclear to what extent such adaptive

processes are reflected in different biosampling procedures or how important they are for the definition of

sample quality. Lately, an increasing number of comparative studies on different biosampling approaches,

post-mortem effects and pre-sampling biological state have investigated such immediate early

biosampling effects. Commonalities between biosampling effects and a range of ischemia/reperfusion and

hypometabolism/anoxia associated biological phenomena indicate that even small variations in post-

sampling time intervals are likely to introduce a set of non-random and tissue specific effects of

experimental importance (both in vivo and in vitro). This review integrates the information provided by

these comparative studies and discusses how an adaptive biological perspective in biosampling

procedures may be relevant for sample quality issues.


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INTRODUCTION

The understanding of how specific observations at the molecular level relate to properties of the entire

living organism is one of the greatest challenges in biomedical research. Observations can be influenced

significantly by both the methodologies used and the manner in which data is interpreted and shared.

Biosampling, here defined as encompassing the collection of biosamples, is therefore central to any study

investigating either molecular mechanisms or biomarkers. Biosampling methods differ in their usefulness

and no single method has universal applicability, making the choice of biosampling approach an

important part of experimental design.

Despite extensive investment in biomarker research for clinical diseases, modern molecular biology has

largely failed to deliver any substantial improvements in the biomarker field (1), a failure often blamed on

the lack of standardization in biosampling procedures. Studies on phosphoproteins in clinical tissues 20-

30 minutes post extraction and later have demonstrated that cells in such biosamples exhibit a range of

adaptive processes (2). But in an era that that aims at an ever more high-resolution understanding of

molecular processes, is functional molecular research that operates within a much shorter post-sampling

time frame much better off? Most discussions and attempts at standardization have been focused on the

quality of analytical data, which has resulted in standard operating procedures and/or minimum standards

protocols such as MIAME and MIAPE. Yet beyond minimal analytical variance, a more exact definition

of what constitutes good sample quality or an approach to differentiate subtle biological effects from

technical noise is generally lacking.

All forms of biosampling, whether post-mortem or ante-mortem, in vivo or in vitro, deprive biological

systems of oxygen and nutrients – an extreme event which biological systems are likely to respond to in

an adaptive manner even within the very short time frames encountered in the research laboratory. When

investigating immediate post-biosampling effects on the molecular level, it is very difficult to separate

between what can be called the cellular homeostatic adaptive processes (“biological processes”) and


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reactive sample degradation as both types intersect and change during the post-sampling time period

before the samples are inactivated. It should be noted that adaptive in this context does not necessarily

equate with protective, only that cellular systems initiate responses, however futile, within their scope of

capabilities, towards extreme stress. The increase of protein degradation fragments initiated directly after

sampling is nominally a non-adaptive biological process, although it has yet to be proven that all the

resulting fragments from such degradation are devoid of any biological functionality or biomarker

usefulness (see below). Sample preparation dependent modifications (such as chemical modifications

dependent on sample buffer composition and oxidations) are on the other hand clear reactive processes.

Such adaptive processes depend both on the adaptive systems inherent in the organism in question and the

exact conditions of the pre-sampling state of the organism. In animal research, there are major differences

in euthanasia protocols both with regard to methodology (such as asphyxiation, terminal anesthesia or

decapitation in the case of smaller rodents such as mice) and the time required for their performance. Yet

there is little discussion as to what extent adaptive biological reactions occur during different forms of

biosampling and how they might influence the interpretability of results and/or extrapolation between

experiments. Biological evolution has resulted in a range of different life strategies (Table 1) determining

the organisms ability to adapt and tolerate hypoxia and anoxia, hypothermia and hypometabolism (the

latter two being connected with tolerance towards anoxia). Compared to temperature-conforming

organisms, endothermic (warm-blooded) organisms have low tolerance towards anoxia and

hypometabolism/hypothermia. This is exemplified by the insufficient adaptation that underlies ischemia-

reperfusion-induced damage (3). An animal can be resuscitated after a short period of global ischemia –

rapidly adapting to the reduced oxygen levels - yet become unable to handle the sudden reintroduction of

oxygen. Intriguingly, such damage can sometimes be ameliorated by therapeutic hypothermia, a result

that is likely to depend on more than just the consequences of a reduced metabolism. A reduction of core

temperature in rats correlates with a drop of approximately 5% per degree Celsius in the cerebral

metabolic rate of oxygen (4), meaning that the observed protection in animals, and possibly humans, at 4-


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5°C reduction, occurs at a metabolic reduction of only 20-25%. The neuroprotective effects invoked by

anesthesia against ischemia/reperfusion damage (5, 6) also indicates that cells initially try to adapt to the

hypometabolism and/or hypothermia associated with biosampling. The mechanisms underlying such

physiological changes need to have an extremely short response time and are therefore heavily dependent

on enzymatic processes, singling out the proteome as being particularly sensitive to the choice of both

sampling methodology and type of tissue (7–12). A few minutes difference in sampling time can, for

instance, have profound effects on the peptidome (here defined as all proteins < 10kDa) (13, 14), yet

easily remain within the acceptable time frame for sampling in most biomedical research. In contrast,

some peptidomics biomarker signatures are dependent on protease activity induced during post-sampling

handling rather than pre-sampling levels (15). Choosing whether to heat or freeze a sample can result in

~30% difference (8) in results at the proteome level (here defined as all proteins > 10kDa) (Figure 1A-B).

This brings into question our definition of sample quality, the nature of these biosampling differences and

their implications for research methodology and data interpretation, especially when investigating the

molecular mechanisms underlying tissue-protective processes.

DEFINING SAMPLE QUALITY

Here, sample quality is referred to as an attribute of biosampling applied to both living and dead

organisms. The highest sample quality is achieved when sampling is performed in a manner optimal for

experimental reproducibility and the representativeness of the organism’s living state. The dynamic

nature of the proteome and its role in adaptive responses makes it difficult to exactly gauge the

representativeness of a sample to its pre-sampling state – at least when investigating regulatory networks

involved at the posttranslational level in adaptive responses.

When looking at in vivo metazoan biology, achieving the highest sample quality presents numerous

challenges as multicellular organisms by definition are composed of multiple, semi-autonomous, living

parts. From the biological perspective death can be seen both as a multilayered chain-of-events spanning


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different organizational layers and as a more specific event when an organism is no longer able to adapt to

its surroundings at the individual or cellular level. In the case of individual death, most cells continue

living as far as their semi-autonomous nature allows them to cope with the drastically changing

microenvironmental conditions. Consequently, the relation between the death of an organism and sample

quality can be perceived on several levels (Figure 1C):

1. ‘Individual death’: the individual (metazoan) has lost its ability to adapt to its macroenvironment,

but most cells remain alive

2. ‘Cellular death’: cells have lost the ability to adapt to their microenvironments, but their

molecules retain some biochemical function due to remaining cellular integrity and/or proximity

3. ‘Chemical activity’: molecules, such as enzymes, are inactive, but remain susceptible to non-

enzymatic changes, such as oxidation, during sample handling and storage

4. ‘Chemical inactivity’: a biosample storage dependent level when all chemical reactions are on

hold

Tissues and organs, not being semi-autonomous adaptive systems with homeostatic properties, are not

included in this hierarchy as they cannot be considered to be alive in the individual or cellular sense but

rather bioactive thanks to their component cells. They constitute the closest environment of the remaining

living cells. It is generally agreed that for a sample to be in a state as close as possible to its pre-

collection, in vivo condition, biosampling methods must attenuate and/or stop all molecular changes

(enzymatic or chemical), either by inactivating an entire specimen, for example by snap-freezing, or by

disrupting sample integrity, for instance using homogenization and/or strongly denaturizing inactivation

buffers.

Bioreaction termination and bioreaction termination intervals


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The literature describes biosampling in a relatively flexible manner. For clarity, we will use ‘bioreaction

termination’ (BT) to describe general biosample inactivation and ‘bioreaction termination interval’ (BTI)

as the time period from individual death or sample extraction from a life-supporting environment to the

actual sample inactivation. The term ‘bioreaction’ does not require the organism to be alive (i.e. neither at

the individual nor cellular level) but rather reflects all biochemical reactions that continue to occur in the

biosample. As a concept, it therefore encompasses all reactions that continue to occur in extracted tissue,

in in vitro derived cell samples or in nominally cell-free bodily fluids such as urine. The post-mortem

interval (PMI) as well as the post-excision phase/delay time (16) are therefore BTIs applied to tissue

extraction biosampling.

Depending on the choice of sampling approach, there are temporary and terminal forms of BTs.

Temporary BT methods only transiently inactivate bioreactions and are dependent on a subsequent

terminal BT step. Terminal BT methods applied immediately after sample extraction are, while having

some drawbacks (see Table 2 and (17)), arguably superior to temporary BT methods when it comes to

minimizing the BTI of biosampling and providing a more realistic representation of the molecular state in

the living organism. The main BTs used include: 1) snap freezing inactivation (SFI, a temporary BT), 2)

lyophilization inactivation (or freeze-drying FDI, a temporal BT), 3) mechano-chemical inactivation

(MCI, a terminal BT), 4) chemical fixation inactivation (CFI, a terminal BT), and 5) heat stabilization

(HS, a terminal BT) (see Table 2). The first method, snap-freezing, is the most commonly used and

requires dry ice or liquid nitrogen as a cooling medium. Lyophilization is a related cooling approach,

providing a temporary method that enables the storing of viable cells (18). Mechano-chemical

inactivation uses some mechanical means (for instance mechanical shears, a glass-Teflon homogenizer or

bead homogenization) to disrupt sample structure (i.e. sample homogenization), often in the presence of

inactivating sample buffer. It is often performed subsequent to snap-freezing in most laboratory protocols

(“SFI+MCI”).


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The retained bioactivity in snap-frozen biosamples allows a wider range of downstream analysis than

heat-inactivated samples but may provide a false sense about the molecular activity present in the pre-

sampling state. For instance, preparing snap-frozen tissues for immunohistochemistry via microtome

followed by thaw-mounting on slides allows the reinstatement of biochemical reactions such as

mitochondrial cytochrome c oxidase activity (19).

Chemical fixation inactivation can involve both cross-linking (such as formalin) and non-cross linking

(for instance the PAXgene tissue fixation system (20)) fixation reagents. The cross-linking nature of the

former is a limiter for subsequent molecular studies in general and proteomic studies in particular. Some

forms of chemical fixation inactivation, such as formalin-fixation, extend the BTI with several hours

allowing a range of biochemical reactions to occur (21). Rapid heating by conductive heat stabilization

(CHS) has been demonstrated to be more efficient than the SFI+MCI approach in minimizing BTI-

associated biological changes (8, 19, 22) and subsequent heat stabilization of snap-frozen tissue negates

the majority of normal SFI+MCI- induced changes demonstrating that the thawing of samples invokes a

range of enzyme activity (8, 23). Focused microwave irradiation (MWR) is also used as a rapid heat

stabilization source but is currently limited to small animal brain tissue applications. All heat-conductive

inactivation methods are detrimental for any subsequent morphology studies.

Biosampling - post-mortem effects

The BTI (PMI) after individual death significantly influences results at the molecular level. Human post-

mortem studies and forensic science studies tend to have extended BTIs, from 20-30min and longer,

whereas the BTI in experimental animal research is usually less than 10 minutes for smaller animals.

With animals, the BTI is usually minimized as much as possible, although material and methods sections

tend to vary considerably in the details of this stage. Post-mortem sampling occurs after cervical

dislocation, blunt trauma to the head in mice, or by euthanasia by injection (which result in shorter BTIs)


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or inhalation (resulting in longer BTIs). The effects on molecular signaling from the combination of the

more specific influence from ante-mortem conditions and immediate post excision phase are poorly

characterized. In the case of inhalation euthanasia in animals – usually spanning several minutes - the

choice of terminal anesthesia may introduces a neuroprotective hypometabolic state (see below) whereas

asphyxiation causes a gradual anoxia (as compared to decapitation-induced anoxia). Molecular research

involving neural tissue from anaesthetized animals (BTI < 80-90s) is more likely to represent a pre-

depolarization state (5) as compared to the state in non-anaesthetized animals (BTI > 50s), but, depending

on variations in animal handling and sample extraction, may result in biosamples representing a mix of

both states. Animal models with reduced brain metabolism, for instance some Alzheimer models, are

therefore likely to exhibit different neural tissue sensitivities to BTIs compared to non-hypometabolic

controls. The phosphorylation pattern of a central neurodegeneration protein, Tau, is known to be

sensitive to both anesthesia and hypometabolism (24, 25).

Biosampling - biopsies and in vitro

With the exception of surgical biopsies, biosampling from living organisms is generally limited to

relatively easily accessible parts of the body. Human surgical biopsies are common, but have a larger

variation in the time span (often from ~30 min up to several hours) from procurement to storage - the later

usually in liquid nitrogen. Clinical histological analysis of tissue biopsies has to contend with a number of

variables (16) besides issues of extended BTIs and the slowness of the BT methodology itself. Espina et

al have subdivided the BTI for the post-excision phase/post-excision delay time of surgically extracted

tissues into wounding/excision followed by pro-survival and apoptosis/cell death, reflecting the

phosphoprotein alterations in different pathways (2).

Biopsies of excreted body fluids such as tears, saliva, breast milk, urine are often used for biomarker

studies and require the inhibition of any potential biochemical activity and chemical modifications. Blood


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is of particular interest in the context of biopsies and biomarkers. It is classified as a connective tissue

and, in this sense; biosampling involves extraction of a biosample with its own particular

microenvironmental cell-supporting conditions. As an interface and/or conduit between tissues and

organs, blood is both a transport medium and an absorbent system for unspecific tissue diffusions. It

consists of endogenous and exogenous components, the former being those cells and molecules associated

with its transport functionality. Heart- specific isoforms of troponin are biomarker-examples of

exogenous blood components as they appear three to five hours post-infarction (26).Their abundance is

dependent on the severity of the infarction. Examples of commonly used biomarkers requiring short BTIs

are glucagon-like peptide-1 (GLP-1), gastric inhibitory polypeptide (GIP), glucagon, and ghrelin (27). In

addition, the complement activation and coagulation pathways present in blood introduce a specific set of

protease-associated bioreactions, influencing protein degradation patterns during the BTI (15).

Another common type of biosampling is from in vitro systems such as cell and tissue cultures. The

experimental conditions of the cultures determine the extent of sudden changes experienced by the cells.

The BTI from the initial disruption of the life-supporting culture conditions to final sample handling

varies a lot between protocols, many being relatively short (few minutes). However, cells in culture at the

same time far more closely connected to a stress full environment than cells in tissue biopsies – which are

enclosed in the organizational structure remainder of the pre-sampling tissue - and therefore likely to be

more susceptible to even small perturbations. Extensive proteomic differences have been observed in a

comparative BT study on yeast cells (28). Differences in culturing conditions and BTIs and BT

methodology, such as the extent of time washing the cells, breaking up adherence by trypsination,

biomechanical pressure effects and limited access to oxygen during centrifugation, all combine to

influence the degree to which the final sample represents the pre-sampling in vitro state.

THE BIOLOGY OF BIOREACTION TERMINATION INTERVALS


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What are the biochemical consequences of choosing a biosampling approach and to what extent do they

matter? Figure 1D depicts a flow chart of the biosampling process in post- and ante-mortem animals. The

combinatorial use of SFI and other subsequent BT methods (for instance SFI+MCI, Figure 1E), adds the

additional BTI time period (T2) which reflects the thawing period of the temporary frozen biosample

before terminal inactivation. If samples are rapidly terminally inactivated while the tissue is still deeply

frozen, T2 becomes non-influential.

The thawing and/or sample homogenization process (8) demonstrates relatively large differences between

heat stabilization (CHS) and immediate MCI or SFI+MCI even when T2 is minimized and strong

inhibitors are included. If thawing and/or weak homogenization are conducted over a longer time period

(T2 is several minutes), cells are more likely to retain their integrity for longer thereby determining the

context for any chemical reactions, adaptive (full integrity) or reactive (reduced integrity). After the initial

stage (or if MCI is performed immediately and efficiently), any subsequent chemical activity is dependent

on four factors: the concentration of molecules, the properties of the buffer, the initial proximity of the

molecules at the point of cellular lysis and their affinity towards each other. Immediate but weak

homogenization after biosampling and without subsequent SFI is likely to induce similar effects.

From this perspective, ‘weaker’ detergent-based sample buffers are more likely to retain more active

molecular complexes (high affinity and close proximity) than strong buffers, even in the presence of

different inhibitors. Adaptive processes during the overall pre-snap-freezing or MCI-stage are likely to

determine the configuration of molecular complexes associated with acute stress adaption and are

dependent on two main factors: inherent survival strategies (Table 1) and associated tissue properties.

Anoxia tolerance depends on the basal metabolic rate and body temperature together with the specific

requirements of individual tissues. For example, mammalian cardiac tissues possess oxygen reserves in

the form of myoglobin, an attribute that helps to delay the initial post-mortem BTI response (29).


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Another pro-survival strategy for cells is to maintain energy reserves via autophagy and protein

catabolism (30). One of the main cellular effects of anoxia is a gradual drop in mitochondrial ATP

production, this being the main O2 consumer, followed by a shift towards anaerobic energy production

and hypometabolism. A drop in cellular ATP production induces a massive reduction in DNA/RNA and

protein synthesis, and redistribution of the remaining ATP to supportive functions (31–35). There is a

strong case to be made that membrane permeability in combination with metabolic rate are important

factors in explaining why certain tissues are tolerant or sensitive to hypoxia and hypothermia (36). The

hypothesis that induction of hypometabolism in combination with the reduction of the ATP required for

cellular membrane potential purposes, ‘channel arrest’, are the primary tools for cells to become hypoxia-

/anoxia- tolerant, is supported by studies on membrane channel and receptor functionality in mollusks,

turtles, and hibernating mammals (37–39). In the absence of a normal de-novo synthesis cells have only

limited means to adapt to their novel situation. One would therefore expect them to use easily produced or

already present biomolecules for this purpose. Post-transcriptional regulation with non-coding RNAs is

one such example and has been observed in the context of hibernation (40). Post-translational

modification of proteins (PTMs) is another (see below). While there are differences between species,

there very likely remains some similarity in underlying stress adaptive mechanisms. Proteins identified in

hypoxic/anoxic tissue of ectothermal organisms (41, 42) overlap with those identified in BT methodology

studies (10, 12, 14, 17) for example glyceraldehyde-3-phosphate dehydrogenase (GAPDH), lactate

dehydrogenase, triosephosphate isomerase, dihydropyrimidinase-related protein 3, voltage-dependent

anion-selective channel).

Post-translational modifications

One of the main adaptive tools available to the cell is the regulation of proteins through PTMs, which are

also known to be particular sensitive to the choice of BT and BTIs (2, 7, 14, 19, 43). As long as the


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decreasing supply of ATP and other secondary energy sources such as creatinine phosphate allows it,

enzymes will use phosphorylation and other reversible PTMs to increase flux through the glycolytic

pathway and shift mitochondrial catabolism and anabolic lipid and protein pathways from an active to

suppressed state. The dependence on ATP for PTMs creates two levels of BTI-associated alterations: an

immediate ATP-dependent stage and an ATP- independent stage. Kinases require ATP whereas

phosphatases involve hydrolysis, meaning that any immediate BTI-adaptive changes involving both

kinases and phosphatases will be further modified by the ATP-independent reactivity of phosphatases.

This is seen as an initial increase in overall protein phosphorylation followed by a reduction (2).

Snap-freezing methods are associated with increased phosphatase activity, an effect that is only mildly

attenuated by the presence of phosphatase inhibitors (19). Immediate SFI+MCI on hippocampal and

cortical tissues (with a reported BTI of approximately 30 seconds) initially causes a higher level of

phosphorylation for JNK1/2, CaMKIIα and CaMKIIβ, GSK3β, Akt and RSK1 (7), indicative of adaptive

or reactive cellular activity, whereas biosamples left for 30min before SFI+MCI show a general reduction

in phosphorylation levels. The activation of certain pathways during initial BTI is counterbalanced by the

inactivation of other pathways through directed phosphatase activity. Neural phosphorylation levels of

ERK threonine and tyrosine (Thr-202, Tyr-204) in mouse striatum and cortex become reduced within one

minute and exhibit extensive reduction within 3 minutes (7, 14). Overall, there are major differences

between SFI+MCI and heat stabilization at the neuroproteomic level (Figure 1B, 2A) (8, 10, 12). In less

anoxia-sensitive human uterine biopsies (2) a number of signaling pathways (including PI3K-Akt, Ras-

ERK), have increased phosphorylation levels during the first 30 min of BTI before eventually decreasing.

Interestingly, while many signaling proteins become dephosphorylated after this initial peak, most

proteins reach a subsequent steady state at 60-80% of the initial phosphorylation level for at least an

additional hour, indicating a balancing effect of phosphatase activity (2).

Redox modifications. Oxygen is the basis for two adaptive PTM classes: Hydroxylation and S-

nitrosylation (SNO). Oxygen pressure determines the hydroxylation level of the hypoxia-responsive


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protein, hypoxia-induced factor (HIF1α), with anoxia leading to minimal hydroxylation. HIF1α regulates

the shift from mitochondrial to glycolysis energy production (44), an activity that is further stabilized by

SNO. SNO occurs on cysteine thiol side chains and requires nitrous oxide (NO) provided by NOS

enzymes (iNOS, eNOS and nNOS) and the reconversion of the NO metabolite nitrite. Endothelial NOS

(eNOS) is increasingly phosphorylated at Akt/PKB and AMPK activating target sites during the first two

hours of BTI in human uterine leiomyoma biopsies (16). The reconversion to NO allows prolonged SNO

activity - a process catalyzed by deoxygenated hemoglobin, deoxygenated myoglobin, neuroglobin,

xanthine oxidoreductase, carbonic anhydrase (45–48) and mitochondrial electron transport enzymes such

as cytochrome C oxidase (49–51). Due to the presence of eNOS, vascular tissues are particularly prone to

SNO activity in response to acute hypoxia (52, 53). Inhalation euthanasia in animal models may therefore

give a different redox-associated proteomic profile than more rapid euthanasia methods.

SUMOylation. Protein SUMOylation is a reversible, tissue-protective process induced by hypoxia and

sensitive to different types of cellular stress (54–57) and may therefore also be a feature of BTIs. This

modification is related to the ubiquitination pathway but requires fewer enzymes for its functionality and

includes HIF1α among its substrates (58). In mouse brain cortex samples with a BTI of approximately 30

seconds contain more SUMO-3 compared to samples with BTI of 30 minutes, but not more SUMO1 & 2

monomers (7). The exact mechanism behind SUMOylation-derived tissue protection is unclear but is

likely to be part of the cellular PTM-based shift to low ATP levels using hypometabolic state as it is

causes repression of gene transcription in hibernating or hypothermic mammalian systems through the

modification of transcription factors (57, 59).

Acetylation. Acetylation, like phosphorylation, is an evolutionarily conserved reversible PTM system

which influences a large proportion of the proteome and is closely linked to metabolism and mRNA

expression regulation (60). While more extensive studies on BTI effects on acetylation modifications are

lacking, anoxia (5h-20h) in warm-blooded animals is associated with altered H3K9ac and HDAC levels

(61) and HDAC inhibitors ameliorate the effects of ischemia/reperfusion (62, 63). In general, prolonged


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BTIs (5-50h) cause altered neuroprotein acetylation levels (64) and more specifically influence H3K9ac

and H3K27ac (65). This contrasts with reports on another chromatin marker, cytosine methylation, which

remains stable during prolonged BTIs (66). BTI-acetylation effects are also implied by the enrichment of

BT-sensitive and acetylation-regulated proteins in studies of four tissues (Figure 2B). Among BT-

sensitive proteins, GAPDH is especially interesting in this context as it is transported into the nucleus

after SNO-modification where it causes the activation of lysine acetyl transferases (CBP/p300) and

inhibition of deacetylases (HDAC2, SIRT1) (67, 68), thereby linking redox signaling to acetylation

regulation (Figure 2A). This involvement of protein acetylation in initial BTI adaption may have

consequences for mechanistic epigenetics studies, particularly in neuroepigenetics. As histone lysine

acetylation is closely linked to same-residue methylation, any such changes are also likely to involve

histone methylation changes.

Akt/PKB and AMPK signaling

The serine/threonine kinase Akt (also known as PKB) is likely one of the main regulators in initial BTI

induced cellular hypoxia/anoxia adaption. It belongs to the pro-survival insulin/growth hormone and Ca++

sensitive PI3K-Akt pathway - a SFI-MCI sensitive set of proteins (7) involved in mammalian hibernation

processes (69), neuroprotection against ischemia, and hypothermia-mediated cardiac protection after

cardiac arrest (70, 71). Akt regulates the protein-synthesis/metabolism controlling mTORC complexes

(mTORC1 & mTORC2) (72, 73) together with disulfide isomerase (ERP57) (8–10), another BT-sensitive

protein. Both Akt and ERP57 are targets of SNO (74, 75) with ERP57 also being a redox-sensitive

chaperone in the endoplasmatic reticulum (75) and transporter of extracellular NO into cells. Altered

PI3K-Akt pathway activity (76) has been linked to anesthesia, a condition associated with

hypometabolism, which delays neural membrane depolarization by approximately ~30s from 50s to 80s

after death by decapitation (5, 77). Tau, a substrate to Akt associated GSK3β, is sensitive to anesthetic


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agents and anesthesia-induced hypothermia (24, 25, 78, 79). The neuronal PI3K-Akt pathway is activated

by physiological NMDA-R activity – a glutamate receptor whose increased activation is also of major

importance for ischemia-associated cell damage (Figure 2C). This points to a close linkage between

neuronal neurodegradation and neuroprotection/adaptive processes (80). Damaging levels of NMDA-R-

associated Ca++ cause increased Ca++ protease activity - likely to be one of the reasons behind the BTI-

induced degradome profile in neural biosamples (see below). Ca++ proteases such as calpain (81) are

rapidly elevated during ischemia and are also able to inhibit PI3K/Akt pathway activity. The AMP-

activated protein kinase (AMPK) is another mTORC- complex regulating protein that is sensitive to

initial choice of biosampling methodology, in particular when followed by a freeze-thaw process (23).

BTI-associated degradation

Sample quality is often defined by the extent of ‘sample degradation’ or ‘reduced sample integrity’ and

linked to the amount of degradation fragments (the degradome in the case of proteins) present in a

biosample. The degradome is composed of enzyme-dependent (proteases) and independent (hydrolysis)

process products, the former being a form of PTM. Not surprisingly, proteolytic degradation is often seen

as a reactive rather than an adaptive process. Sample handling generally involves proteases getting access

to cellular compartments normally kept protected, thus providing new proteolytic substrates. Even a very

short BTI (< 3min) or using SFI+MCI is associated with a clear increase in peptides (8, 14). This image is

not as clear with larger proteins (>10kDa). Proteomic profiles derived from SFI+MCI neural tissue and in

vitro yeast biosamples demonstrate an increase in low MW proteins and a reduction in high MW proteins

(some of the former being fragments of the latter), a trend absent in SFI-handled biosamples from heart,

liver and pancreas tissue (8, 10, 28). The neural tissue degradation profile is possibly a reflection of its

high sensitivity to ischemia and/or the dissipation of ion gradients and subsequent rise in Ca++

concentration (causing an elevation of Ca++ protease activity) (77, 82). The absence of sufficient ATP

reduces the re-uptake of glutamate in the synaptic clefts and inhibits the active export of intracellular

calcium thereby enabling activation of calcium sensitive proteases such as calpain (80). The increased


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level of degradation products present in snap-frozen yeast samples is therefore interesting as it implies

that at least some in vitro samples are as sensitive as neural tissues to BT choice and BTI extent. What is

less understood is to what level, if any, the components of the initial BTI degradome possess bioactive

properties (i.e. proteolytic fragments with independent biological properties), how cleavage relates to

other forms of PTMs (for instance creating novel modification sites) and/or what such degradomes may

mean for biomarker analysis.

Peptides from the BTI-sensitive Akt-pathway-associated CRMP2 protein have been reported to be

neuroprotective against NMDA-R-associated excitotoxicity, possibly through the reduction of NMDA-R

mediated Ca++ influx (83). Presence of proteolytic fragment bioactivity is also hinted at in BT-

comparative peptidomics of the pancreas (8). Specific peptide regions within the insulin 1 C-peptide

(“founder peptide”) are known to stimulate Na+/K+-ATPase (84) and are overrepresented in its default

(CHS-derived) pancreatic degradation profile (Figure 3A). The major cluster of C-peptide fragments

follows a C-terminal gap (VARQ), a sequence reported to have the full activity of the C-peptide (84) in

stimulating Na+/K+-ATPase activity. It represents a set of peptides that all contain a region with

moderately effective Na+/K+-ATPase activity. A smaller, lighter cluster also contains this somewhat less

efficient Na+/K+-ATPase stimulating fragment, indicating the presence of an additional pool of potentially

C-peptide- derived active peptides. In certain cases the sample handling introduces a specific sequence of

protease activity (15, 85). A first tier of protease activity in human serum involves complement activation

pathways and coagulation producing a set of founder peptides (for instance bradykinin, fibrinopeptide A

and complement C3F). A second tier of protease activity from blood exogenous proteases is believed to

subsequently target these founder peptides (15). These exogenous proteases are likely health-state specific

proteins diffused from different tissues and post-sampling protease activity can occur very rapidly. For

instance, addition of the synthetic complement C3F founder peptide to fresh plasma leads, within

seconds, to removal of the C-terminal arginine and, within 10 to 15 minutes, to truncation of the N-

terminal (Figure 3B). Tumors are believed to contribute with a range of blood exogenous proteases,


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creating subtle cancer-specific degradome/biomarker signatures (85). This also illustrates one additional

subtlety inherent in the notion of sample quality. In contrast with the aims of most functional studies,

molecular biomarkers are not required to be directly involved in the core processes underlying any

particular disease as long as they establish a robust association to that disease state. In the case of cancer

serum degradomes, biosample quality is defined by its representativeness of the protease activity state

(i.e. the degradome) in patients suffering from cancer rather than the absolute levels of those proteases

(Figure 3B).

CONCLUDING REMARKS

Great effort is put into standardizing molecular biology methodologies and their associated data handling

and into reducing technical variation as much as possible. While reducing technical variation is clearly

worthwhile, the biological adaptive processes inherent in biosampling have received much less attention.

This is for instance reflected in commonly used terminology (focusing on “sample degradation”, “reduced

sample integrity”) which implies an initial default state that subsequently loses its integrity rather than a

an set of adaptive processes. Research articles on anoxia and stress-associated phenomena are often very

specific in mentioning the exact extent of oxygen deprivation but are more vague on the exact

circumstances surrounding BTI and BT. In the same vein, while phosphatase and protease inhibitors are a

relatively common component in sample buffers to stop dephosphorylation and proteolysis, attenuation of

additional phosphorylation via kinase inhibitors receives much less attention. Overall, the molecular

biology literature places relatively little focus on the distinctions between different sampling

methodologies, time intervals before sample inactivation or even the different pre-sampling states of the

organisms involved (such as anesthetized or conscious animals).

Espina et al (2, 16) reached a similar conclusion in their tissue biopsies studies on post-excision delay

induced protein modification effects. They noted that excised biosamples can no longer be viewed as non-


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reactive or unchanging after procurement (2, 16). The present overview of immediate early changes after

sampling and comparisons between biosampling methodologies indicates that such issues are relevant

even before the time frame investigated by Espina and coworkers (>10 min post-excision phase and

upwards). All biosamples, with the possible exception of in vivo microwave inactivated brain samples,

possess a BTI which influences the representativeness of the sample. The relevance of the BTI extent and

the BT methods employed – and the notion of representativeness in sample quality - is always dependent

on the purpose for the biosampling. As the example with the cancer serum degradomes (Figure 3B)

demonstrates: representativeness in biomarker studies is not always directly correlated with the shortest

possible BTI but with the power for classification. A somewhat longer BTI actually increases the

representativeness in this context (15).

Mechanistic studies tend on the other hand be more interested in the absolute representativeness of the

pre-sampling state. This, paradoxically, is likely to increase variability in immediate early BTI time

frames. Taking the pre-sampling state, organism/tissue properties and acute adaptive reactions into

account means that as individual researchers attempt to reduce the BTI, the more likely it is that small

differences in time – especially with neural tissue - within and between experiments (and labs) will

introduce greater variability in certain classes of biomolecules and make it more difficult to distinguish

biological from technical variation. With the exception of peptides and peptide fragments, such

immediate early BTI effects are unlikely to influence the measurement of the total levels of most proteins

but rather involve their posttranslational modifications. In conclusion, there is a need for a more

differentiated approach to biosampling in experimental biology and biomarker studies. Increased attention

to such issues is of value for the interpretation of molecular biology data and biomarkers.


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FIGURE LEGENDS

Figure 1. Adaptive and reactive factors in biosampling. A) Proteomics comparison between snap-

frozen inactivation (SFI) and conductive heat stabilization (CHS). CHS treatment of SFI tissue

(SFI+CHS) reduces the extent of the SFI induced changes. B) Schematic of tissue-specific bioreaction

termination- method sensitive, two-dimensional electrophoresis expression patterns. C) Schematic of the

different levels of organization involved in biosampling in relation to the death event. D) Schematic view

of components in biosampling from individual organisms, post-mortem and living (ante-mortem) and

how the choice of BT-methodology determines the bioreaction termination interval (BTI) composition.

Post-mortem sampling involves a maximum of three time components (death pre-sampling T0, post-

sampling to first temporal or terminal inactivation T1, post-temporary to terminal inactivation T2) and

biopsies a maximum of two time components (T1, T2) depending on the choice of terminal (termBT) or

temporal (tempBT) bioreaction termination methods. E) SFI followed by mechano-chemical inactivation

(MCI) involves, depending on its efficiency, two biochemical reaction stages. In the initial stage cellular

integrity remains, constraining and defining the scope of biochemical reactions. In the second stage,

reactions are likely to depend on the total concentration of different molecules, the initial proximity states

between molecules at the point of lysis and their affinity towards each other.

Figure 2. Overview of immediate early BTI sensitive pathways. A) Pathway schemes of signaling

proteins (AMPK, Akt and MAPK pathways), some of their downstream substrates (including mTOR

complexes) and their sensitivity to BT. Dark purple nodes are proteins identified by 2-DE methods as

sensitive to BT choice (snap-frozen and heat-stabilized). Light purple nodes are proteins showing

increased phosphorylation in snap-frozen samples as compared to heat-stabilized samples. Green nodes

are proteins found to have unaltered or reduced levels of phosphorylation in snap-frozen samples relative

to heat-stabilized samples. Circular grey nodes are phosphatases (PTEN, PP1, PP2A). The sno-prefix

reflects some proteins with known S-nitrosylation modifications (HDAC2 and SIRT1, ERP57, Akt,

HIF1α). B) Enrichment analysis of UniProt annotations in proteins identified to be specifically sensitive


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to BT choice in brain, heart, liver and pancreas tissue (DAVID based calculation (86), * adjusted p<0.05).

Based on non-redundant protein identities, an enrichment of acetylation modification is in common for all

tissue. C) Balance between neuronal NMDA-R-associated neuroprotection and neurodegradation.

Physiological NMDA-R signaling involves neuroprotective pathways such as the PI3K-Akt pathway.

Increased NMDA-R-associated calcium uptake induces increased calcium protease activity, ROS and NO

generation and alters mitochondrial functionality(80, 87). D) BTI duration effects on CREB-S133

phosphorylation in formalin-fixed (CFI) mouse cortex tissue. Regular formalin fixation causes extensive

dephosphorylation of CREB due to slow tissue penetration, an effect that is prevented by initial heat

stabilization (CHS + CFI).

Figure 3. Visualization of individual peptide degradomes detected in peptidomics studies. A)

Visualization of the mouse insulin 1 C-peptide degradome and its BT-method sensitivity through a step-

wise N and C-terminal reduction approach. Blue diamond nodes demonstrate which C-peptide sequences

are present at higher levels in CHS pancreas samples whereas red diamond nodes show peptides present

at high levels in snap-frozen samples. The cluster of sequences to the right of the “peptide pyramid”

represent the nodes on the far right indicating peptides with an intact founder peptide N-terminal together

with an increasingly truncated C-terminal. Based on data from Scholz et al (8). B) Human serum

preparation induced degradation of the complement C3F peptide. Red nodes demonstrate which particular

C3F-derived peptides are overrepresented in serum taken from individuals with prostate cancer. Orange

nodes/peptides do not differ from levels found in healthy individuals. Based on data from Villanueva et al

(15).


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TABLES

Table1. Survival strategies and anoxia sensitivity

Survival strategy Organisms Anoxia sensitivity

Ectothermal strategy - temperature

conforming

Fish, amphibians, reptiles Usually extensively tolerant to anoxia,

hypometabolism and hypothermia

(88, 89)

Endothermal strategy -some

mammals use temporary

hypometabolic states: daily

metabolic rate depression (torpor)

or seasonal (aestivation,

hibernation)

Mammals and birds - tachymetabolic

organisms

Weak tolerance to anoxia


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Table2.

A) Strong denaturizing buffers or inhibitors can also be used without the help of a Mechano-chemical method. B) Depending on bioreaction termination from frozen state (can be combined with lyophilization, strong denaturizing sample buffers or heat stabilization). C) Depending on the strength of the buffer it can be more or less permanent and there is a risk of enzymatic activity when diluting the buffers. Representative references: D) (18), E) (90), F) (20), G) (19), H) (43), I) (91), J) (92).

Mechanochemical inactivationA

Snap freezingB LyophilizationD InhibitorsE

•Protease•Kinase•Phosphatase

Strong denaturizing sample buffer

Formalin fixation•Crosslinkingfixative

PAXgene TissueSystemF

•Precipitation fixative

Heat stabilization•ConductiveG

•MicrowaveH

Bioreactiontermination

Temporary Temporary Temporary Terminal / TemporaryC

Terminal Terminal Terminal

Speed of inhibition Rapid Rapid SlowB SlowB Slow Slow Rapid

Sub-dissection in RT N.A N.A N.A N.A Yes Yes Yes

Price Low High Moderate Low Low Moderate High

Toxic Low Low High Low High Low Low

Analysis compatibility (stabilizing effect and interference downstream on analysis)

IHC compatible Yes N.A N.A N.A Yes Yes No

RNA/DNA Yes Yes Yes Yes No/Yes Yes No/Yes

MetabolitesI,J NoB NoB No No No No Yes

Endogenous peptides NoB NoB No No N.A N.A Yes

Transient specific phosphorylations

NoB NoB Yes Yes No No Yes

Biological activity Yes Yes Yes N.A N.A N.A N.A

Organelle sub-fractionation

Yes N.A Yes N.A N.A N.A N.A


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Figure 1. Adaptive and reactive factors in biosampling.


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Figure 2. Overview of immediate early BTI sensitive pathways.


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Figure 3. Visualization of individual peptide degradomes detected in peptidomics studies.


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the impact of biosampling procedures on molecular data

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