Advances in neuroproteomics for neurotrauma: unraveling insights for personalized medicine and future prospects

Neuroproteomics, an emerging field at the intersection of neuroscience and proteomics, has garnered significant attention in the context of neurotrauma research. Neuroproteomics involves the quantitative and qualitative analysis of nervous system components, essential for understanding the dynamic events involved in the vast areas of neuroscience, including, but not limited to, neuropsychiatric disorders, neurodegenerative disorders, mental illness, traumatic brain injury, chronic traumatic encephalopathy, and other neurodegenerative diseases. With advancements in mass spectrometry coupled with bioinformatics and systems biology, neuroproteomics has led to the development of innovative techniques such as microproteomics, single-cell proteomics, and imaging mass spectrometry, which have significantly impacted neuronal biomarker research. By analyzing the complex protein interactions and alterations that occur in the injured brain, neuroproteomics provides valuable insights into the pathophysiological mechanisms underlying neurotrauma. This review explores how such insights can be harnessed to advance personalized medicine (PM) approaches, tailoring treatments based on individual patient profiles. Additionally, we highlight the potential future prospects of neuroproteomics, such as identifying novel biomarkers and developing targeted therapies by employing artificial intelligence (AI) and machine learning (ML). By shedding light on neurotrauma's current state and future directions, this review aims to stimulate further research and collaboration in this promising and transformative field.

Chemo-proteomics in antimalarial target identification and engagement

Humans have lived in tenuous battle with malaria over millennia. Today, while much of the world is free of the disease, areas of South America, Asia, and Africa still wage this war with substantial impacts on their social and economic development. The threat of widespread resistance to all currently available antimalarial therapies continues to raise concern. Therefore, it is imperative that novel antimalarial chemotypes be developed to populate the pipeline going forward. Phenotypic screening has been responsible for the majority of the new chemotypes emerging in the past few decades. However, this can result in limited information on the molecular target of these compounds which may serve as an unknown variable complicating their progression into clinical development. Target identification and validation is a process that incorporates techniques from a range of different disciplines. Chemical biology and more specifically chemo-proteomics have been heavily utilized for this purpose. This review provides an in-depth summary of the application of chemo-proteomics in antimalarial development. Here we focus particularly on the methodology, practicalities, merits, and limitations of designing these experiments. Together this provides learnings on the future use of chemo-proteomics in antimalarial development.

PEPA test: fast and powerful differential analysis from relative quantitative proteomics data using shared peptides

We propose a new hypothesis test for the differential abundance of proteins in mass-spectrometry based relative quantification. An important feature of this type of high-throughput analyses is that it involves an enzymatic digestion of the sample proteins into peptides prior to identification and quantification. Due to numerous homology sequences, different proteins can lead to peptides with identical amino acid chains, so that their parent protein is ambiguous. These so-called shared peptides make the protein-level statistical analysis a challenge and are often not accounted for. In this article, we use a linear model describing peptide-protein relationships to build a likelihood ratio test of differential abundance for proteins. We show that the likelihood ratio statistic can be computed in linear time with the number of peptides. We also provide the asymptotic null distribution of a regularized version of our statistic. Experiments on both real and simulated datasets show that our procedures outperforms state-of-the-art methods. The procedures are available via the pepa.test function of the DAPAR Bioconductor R package.

Recent Technological Advances in the Mass Spectrometry-based Nanomedicine Studies: An Insight from Nanoproteomics

Nanoscience becomes one of the most cutting-edge research directions in recent years since it is gradually matured from basic to applied science. Nanoparticles (NPs) and nanomaterials (NMs) play important roles in various aspects of biomedicine science, and their influences on the environment have caused a whole range of uncertainties which require extensive attention. Due to the quantitative and dynamic information provided for human proteome, mass spectrometry (MS)-based quantitative proteomic technique has been a powerful tool for nanomedicine study. In this article, recent trends of progress and development in the nanomedicine of proteomics were discussed from quantification techniques and publicly available resources or tools. First, a variety of popular protein quantification techniques including labeling and label-free strategies applied to nanomedicine studies are overviewed and systematically discussed. Then, numerous protein profiling tools for data processing and postbiological statistical analysis and publicly available data repositories for providing enrichment MS raw data information sources are also discussed.

Recent Trends in Plant Protein Complex Analysis in a Developmental Context

Because virtually all proteins interact with other proteins, studying protein-protein interactions (PPIs) is fundamental in understanding protein function. This is especially true when studying specific developmental processes, in which proteins often make developmental stage- or tissue specific interactions. However, studying these specific PPIs in planta can be challenging. One of the most widely adopted methods to study PPIs in planta is affinity purification coupled to mass spectrometry (AP/MS). Recent developments in the field of mass spectrometry have boosted applications of AP/MS in a developmental context. This review covers two main advancements in the field of affinity purification to study plant developmental processes: increasing the developmental resolution of the harvested tissues and moving from affinity purification to affinity enrichment. Furthermore, we discuss some new affinity purification approaches that have recently emerged and could have a profound impact on the future of protein interactome analysis in plants.

Differential Gel Electrophoresis (DIGE) Evaluation of Naphthoimidazoles Mode of Action: A Study in Trypanosoma cruzi Bloodstream Trypomastigotes

Background

The obligate intracellular protozoan Trypanosoma cruzi is the causative agent of Chagas disease, a neglected illness affecting millions of people in Latin America that recently entered non-endemic countries through immigration, as a consequence of globalization. The chemotherapy for this disease is based mainly on benznidazole and nifurtimox, which are very efficient nitroderivatives against the acute stage but present limited efficacy during the chronic phase. Our group has been studying the trypanocidal effects of naturally occurring quinones and their derivatives, and naphthoimidazoles derived from β-lapachone N1, N2 and N3 were the most active. To assess the molecular mechanisms of action of these compounds, we applied proteomic techniques to analyze treated bloodstream trypomastigotes, which are the clinically relevant stage of the parasite.

Methodology/Principal Findings

The approach consisted of quantification by 2D-DIGE followed by MALDI-TOF/TOF protein identification. A total of 61 differentially abundant protein spots were detected when comparing the control with each N1, N2 or N3 treatment, for 34 identified spots. Among the differentially abundant proteins were activated protein kinase C receptor, tubulin isoforms, asparagine synthetase, arginine kinase, elongation factor 2, enolase, guanine deaminase, heat shock proteins, hypothetical proteins, paraflagellar rod components, RAB GDP dissociation inhibitor, succinyl-CoA ligase, ATP synthase subunit B and methionine sulfoxide reductase.

Conclusion/Significance

Our results point to different modes of action for N1, N2 and N3, which indicate a great variety of metabolic pathways involved and allow for novel perspectives on the development of trypanocidal agents.

Trypanosoma cruzi is the etiological agent of Chagas disease, an important illness for Latin American countries that is now afflicting other continents due to the immigration of infected people. The available chemotherapy is limited to the chronic phase of the disease, being the development of novel active compounds essential, and the search for specific molecular targets for drugs in T. cruzi is necessary. In this context, our group has synthesized and screened many compounds ranging from natural to semi-synthetic naphthoquinones and derivatives on T. cruzi, displaying naphthoimidazoles N1, N2 and N3 the highest activity. Previous studies correlated phenotypic alterations by cell biology techniques as well as investigated mode of action by proteomic approaches in insect stage epimastigotes as a model. However, T. cruzi presents three morphologically distinct life stages with their own specific biological peculiarities and requirements that could be potential targets to drug intervention. Here, we evaluated the mechanism of action of N1, N2 and N3 in clinical relevant form of the parasite, bloodstream trypomastigotes, by proteomics. Our data pointed to 61 differentially abundant protein spots, being these proteins involved with cellular trafficking, protein synthesis, transduction signaling and energetic metabolism, among others, open interesting perspectives for trypanocidal strategies.

Thousand and one ways to quantify and compare protein abundances in label-free bottom-up proteomics

How to process and analyze MS data to quantify and statistically compare protein abundances in bottom-up proteomics has been an open debate for nearly fifteen years. Two main approaches are generally used: the first is based on spectral data generated during the process of identification (e.g. peptide counting, spectral counting), while the second makes use of extracted ion currents to quantify chromatographic peaks and infer protein abundances based on peptide quantification. These two approaches actually refer to multiple methods which have been developed during the last decade, but were submitted to deep evaluations only recently. In this paper, we compiled these different methods as exhaustively as possible. We also summarized the way they address the different problems raised by bottom-up protein quantification such as normalization, the presence of shared peptides, unequal peptide measurability and missing data. This article is part of a Special Issue entitled: Plant Proteomics--a bridge between fundamental processes and crop production, edited by Dr. Hans-Peter Mock.

Label-Free Quantitative Proteomics in Yeast

Label-free bottom-up shotgun MS-based proteomics is an extremely powerful and simple tool to provide high quality quantitative analyses of the yeast proteome with only microgram amounts of total protein. Although the experimental design of this approach is rather straightforward and does not require the modification of growth conditions, proteins or peptides, several factors must be taken into account to benefit fully from the power of this method. Key factors include the choice of an appropriate method for the preparation of protein extracts, careful evaluation of the instrument design and available analytical capabilities, the choice of the quantification method (intensity-based vs. spectral count), and the proper manipulation of the selected quantification algorithm. The elaboration of this robust workflow for data acquisition, processing, and analysis provides unprecedented insight into the dynamics of the yeast proteome.

Improved isobaric tandem mass tag quantification by ion mobility mass spectrometry

RATIONALE

Isobaric tandem mass tags are an attractive alternative to mass difference tags and label-free approaches for quantitative proteomics due to the high degree of multiplexing that can be performed with their implementation. A drawback of tandem mass tags are that the co-isolation and co-fragmentation of labeled peptide precursors can result in chimeric tandem mass (MS/MS) spectra that can underestimate the fold-change expression of each peptide. Ion mobility (IM) separations coupled to quadrupole time-of-flight (Q-TOF) instruments have the potential to mitigate MS/MS spectra chimeracy since IM-MS has the ability to separate ions based on charge, m/z, and collision cross section (CCS).

METHODS

Two complex protein mixtures, labeled with DiLeu isobaric tandem mass tags in opposite ratios, were mixed together and analyzed by data-dependent LC/IM-MS/MS. The accuracy of reporters from interfering pairs was compared with and without IM separation.

RESULTS

IM separation was able to mitigate isobaric interference from differentially charged interfering ion pairs, as well as pairs of the same charge. Of the eight example precursors shown, only one had reporters that remained compressed below the significance threshold after IM separation.

CONCLUSIONS

The results of this investigation demonstrate proof-of-principle that IM separation of tagged precursors prior to MS/MS fragmentation can help mitigate quantitative inaccuracies caused by isobaric interference. Future improvements of the method would include software for automated correction and use of higher resolution IM instrumentations.

Global quantitative proteomics using spectral counting: an inexpensive experimental and bioinformatics workflow for deep proteome coverage

As the field of proteomics shifts from qualitative identification of protein "subfractions" to quantitative comparison of proteins from complex biological samples, it is apparent that the number of approaches for quantitation can be daunting for the result-oriented biologist. There have been many recent reviews on quantitative proteomic approaches, discussing the strengths and limitations of each. Unfortunately, there are few detailed methodological descriptions of any one of these quantitative approaches. Here we present a detailed bioinformatics workflow for one of the simplest, most pervasive quantitative approach-spectral counting. The informatics and statistical workflow detailed here includes newly available freeware, such as SePro and PatternLab which post-process data according to false discovery rate parameters, and statistically model the data to detect differences and trends.

Bioinformatic progress and applications in metaproteogenomics for bridging the gap between genomic sequences and metabolic functions in microbial communities

Metaproteomics of microbial communities promises to add functional information to the blueprint of genes derived from metagenomics. Right from its beginning, the achievements and developments in metaproteomics were closely interlinked with metagenomics. In addition, the evaluation, visualization, and interpretation of metaproteome data demanded for the developments in bioinformatics. This review will give an overview about recent strategies to use genomic data either from public databases or organismal specific genomes/metagenomes to increase the number of identified proteins obtained by mass spectrometric measurements. We will review different published metaproteogenomic approaches in respect to the used MS pipeline and to the used protein identification workflow. Furthermore, different approaches of data visualization and strategies for phylogenetic interpretation of metaproteome data are discussed as well as approaches for functional mapping of the results to the investigated biological systems. This information will in the end allow a comprehensive analysis of interactions and interdependencies within microbial communities.

Critical assessment of proteome-wide label-free absolute abundance estimation strategies

There is a great interest in reliable ways to obtain absolute protein abundances at a proteome-wide scale. To this end, label-free LC-MS/MS quantification methods have been proposed where all identified proteins are assigned an estimated abundance. Several variants of this quantification approach have been presented, based on either the number of spectral counts per protein or MS1 peak intensities. Equipped with several datasets representing real biological environments, containing a high number of accurately quantified reference proteins, we evaluate five popular low-cost and easily implemented quantification methods (Absolute Protein Expression, Exponentially Modified Protein Abundance Index, Intensity-Based Absolute Quantification Index, Top3, and MeanInt). Our results demonstrate considerably improved abundance estimates upon implementing accurately quantified reference proteins; that is, using spiked in stable isotope labeled standard peptides or a standard protein mix, to generate a properly calibrated quantification model. We show that only the Top3 method is directly proportional to protein abundance over the full quantification range and is the preferred method in the absence of reference protein measurements. Additionally, we demonstrate that spectral count based quantification methods are associated with higher errors than MS1 peak intensity based methods. Furthermore, we investigate the impact of miscleaved, modified, and shared peptides as well as protein size and the number of employed reference proteins on quantification accuracy.

Insights from quantitative metaproteomics and protein-stable isotope probing into microbial ecology

The recent development of metaproteomics has enabled the direct identification and quantification of expressed proteins from microbial communities in situ, without the need for microbial enrichment. This became possible by (1) significant increases in quality and quantity of metagenome data and by improvements of (2) accuracy and (3) sensitivity of modern mass spectrometers (MS). The identification of physiologically relevant enzymes can help to understand the role of specific species within a community or an ecological niche. Beside identification, relative and absolute quantitation is also crucial. We will review label-free and label-based methods of quantitation in MS-based proteome analysis and the contribution of quantitative proteome data to microbial ecology. Additionally, approaches of protein-based stable isotope probing (protein-SIP) for deciphering community structures are reviewed. Information on the species-specific metabolic activity can be obtained when substrates or nutrients are labeled with stable isotopes in a protein-SIP approach. The stable isotopes ((13)C, (15)N, (36)S) are incorporated into proteins and the rate of incorporation can be used for assessing the metabolic activity of the corresponding species. We will focus on the relevance of the metabolic and phylogenetic information retrieved with protein-SIP studies and for detecting and quantifying the carbon flux within microbial consortia. Furthermore, the combination of protein-SIP with established tools in microbial ecology such as other stable isotope probing techniques are discussed.

Proteomics identifies molecular networks affected by tetradecylthioacetic acid and fish oil supplemented diets

Fish oil (FO) and tetradecylthioacetic acid (TTA) - a synthetic modified fatty acid have beneficial effects in regulating lipid metabolism. In order to dissect the mechanisms underlying the molecular action of those two fatty acids we have investigated the changes in mitochondrial protein expression in a long-term study (50weeks) in male Wistar rats fed 5 different diets. The diets were as follows: low fat diet; high fat diet; and three diets that combined high fat diet with fish oil, TTA or combination of those two as food supplements. We used two different proteomics techniques: a protein centric based on 2D gel electrophoresis and mass spectrometry, and LC-MS(E) based peptide centric approach. As a result we provide evidence that fish oil and TTA modulate mitochondrial metabolism in a synergistic manner yet the effects of TTA are much more dramatic. We demonstrate that fatty acid metabolism; lipid oxidation, amino acid metabolism and oxidative phosphorylation pathways are involved in fish oil and TTA action. Evidence for the involvement of PPAR mediated signalling is provided. Additionally we postulate that down regulation of components of complexes I and II contributes to the strong antioxidant properties of TTA.

BIOLOGICAL SIGNIFICANCE

This study for the first time explores the effect of fish oil and TTA - tetradecyl-thioacetic acid and the combination of those two as diet supplements on mitochondria metabolism in a comprehensive and systematic manner. We show that fish oil and TTA modulate mitochondrial metabolism in a synergistic manner yet the effects of TTA are much more dramatic. We demonstrate in a large scale that fatty acid metabolism and lipid oxidation are affected by fish oil and TTA, a phenomenon already known from more directed molecular biology studies. Our approach, however, shows additionally that amino acid metabolism and oxidative phosphorylation pathways are also strongly affected by TTA and also to some extent by fish oil administration. Strong evidence for the involvement of PPAR mediated signalling is provided linking the different metabolic effects. The global and systematic viewpoint of this study compiles many of the known phenomena related to the effects of fish oil and fatty acids giving a solid foundation for further exploratory and more directed studies of the mechanisms behind the beneficial and detrimental effects of fish oil and TTA diet supplementation. This work is already a second article in a series of studies conducted using this model of dietary intervention. In the previous study (Vigerust et al., [21]) the effects of fish oil and TTA on the plasma lipids and cholesterol levels as well as key metabolic enzymes in the liver have been studied. In an ongoing study more work is being done to explore in detail for example the link between the down regulation of the components of the respiratory chain (observed in this study) and the strong antioxidant effects of TTA. The reference diet in this study has been designed to mimic an unhealthy - high fat diet that is thought to contribute to the development of metabolic syndrome - a condition that is strongly associated with diabetes, obesity and heart failure. Fish oil and TTA are known to have beneficial effects for the fatty acid metabolism and have been shown to alleviate some of the symptoms of the metabolic syndrome. To date very little is known about the molecular mechanisms behind these beneficial effects and the potential pitfalls of the consumption of those two compounds. Only studies of each compound separately and using only small scale molecular biology approaches have been carried out. The results of this work provide an excellent starting point for further studies that will help to understand the metabolic effects of fish oil and TTA and will hopefully help to design dietary programs directed towards reduction of the prevalence of metabolic syndrome and associated diseases.

Current challenges in software solutions for mass spectrometry-based quantitative proteomics

Mass spectrometry-based proteomics has evolved as a high-throughput research field over the past decade. Significant advances in instrumentation, and the ability to produce huge volumes of data, have emphasized the need for adequate data analysis tools, which are nowadays often considered the main bottleneck for proteomics development. This review highlights important issues that directly impact the effectiveness of proteomic quantitation and educates software developers and end-users on available computational solutions to correct for the occurrence of these factors. Potential sources of errors specific for stable isotope-based methods or label-free approaches are explicitly outlined. The overall aim focuses on a generic proteomic workflow.

Current challenges in software solutions for mass spectrometry-based quantitative proteomics

Mass spectrometry-based proteomics has evolved as a high-throughput research field over the past decade. Significant advances in instrumentation, and the ability to produce huge volumes of data, have emphasized the need for adequate data analysis tools, which are nowadays often considered the main bottleneck for proteomics development. This review highlights important issues that directly impact the effectiveness of proteomic quantitation and educates software developers and end-users on available computational solutions to correct for the occurrence of these factors. Potential sources of errors specific for stable isotope-based methods or label-free approaches are explicitly outlined. The overall aim focuses on a generic proteomic workflow.

Partitioning the proteome: phase separation for targeted analysis of membrane proteins in human post-mortem brain

Neuroproteomics is a powerful platform for targeted and hypothesis driven research, providing comprehensive insights into cellular and sub-cellular disease states, Gene × Environmental effects, and cellular response to medication effects in human, animal, and cell culture models. Analysis of sub-proteomes is becoming increasingly important in clinical proteomics, enriching for otherwise undetectable proteins that are possible markers for disease. Membrane proteins are one such sub-proteome class that merit in-depth targeted analysis, particularly in psychiatric disorders. As membrane proteins are notoriously difficult to analyse using traditional proteomics methods, we evaluate a paradigm to enrich for and study membrane proteins from human post-mortem brain tissue. This is the first study to extensively characterise the integral trans-membrane spanning proteins present in human brain. Using Triton X-114 phase separation and LC-MS/MS analysis, we enriched for and identified 494 membrane proteins, with 194 trans-membrane helices present, ranging from 1 to 21 helices per protein. Isolated proteins included glutamate receptors, G proteins, voltage gated and calcium channels, synaptic proteins, and myelin proteins, all of which warrant quantitative proteomic investigation in psychiatric and neurological disorders. Overall, our sub-proteome analysis reduced sample complexity and enriched for integral membrane proteins by 2.3 fold, thus allowing for more manageable, reproducible, and targeted proteomics in case vs. control biomarker studies. This study provides a valuable reference for future neuroproteomic investigations of membrane proteins, and validates the use Triton X-114 detergent phase extraction on human post mortem brain.

Casting a net: fibres produced by Microcystis sp. in field and laboratory populations

The reasons for the apparent dominance of the toxic cyanobacterium Microcystis sp., reflected by its massive blooms in many fresh water bodies, are poorly understood. We show that in addition to a large array of secondary metabolites, some of which are toxic to eukaryotes, Microcystis sp. secretes large amounts of fibrous exopolysaccharides that form extremely long fibres several millimetres in length. This phenomenon was detected in field and laboratory cultures of various Microcystis strains. In addition, we have identified and characterized three of the proteins associated with the fibres and the genes encoding them in Microcystis sp. PCC 7806 but were unable to completely delete them from its genome. Phylogenetic analysis of the most abundant one, designated IPF-469, showed its presence only in cyanobacteria. Its closest relatives were detected in Synechocystis sp. PCC 6803 and in Cyanothece sp. strains; in the latter the genomic organization of the IPF-469 was highly conserved. IPF-469 and the other two proteins identified here, a haloperoxidase and a haemolysin-type calcium-binding protein, may be part of the fibres secretion pathway. The biological role of the fibres in Microcystis sp. is discussed.

The human salivary proteome: a critical overview of the results obtained by different proteomic platforms

The development of new separation techniques and different mass spectrometry instrumental devices, as well as the great availability of specific reactants, offers ample choice to scientists for carrying out high-throughput proteomic studies and being competitive in the field today. However, the different options available often do not provide comparable results, which can be linked to factors such as the strategy adopted, the nature of the sample and the instrumental availability. In this critical review, the results obtained so far in the study of human saliva by different proteomic approaches will be compared and discussed.

Important issues in planning a proteomics experiment: statistical considerations of quantitative proteomic data

Mass spectrometry is frequently used in quantitative proteomics to detect differentially regulated proteins. A very important but unfortunately oftentimes neglected part in detecting differential proteins is the statistical analysis. Data from proteomics experiments are usually high-dimensional and hence require profound statistical methods. It is especially important to already correctly design a proteomic experiment before it is conducted in the laboratory. Only this can ensure that the statistical analysis is capable of detecting truly differential proteins afterwards. This chapter thus covers aspects of both statistical planning and the actual analysis of quantitative proteomic experiments.

iTRAQ-based analysis of changes in the cassava root proteome reveals pathways associated with post-harvest physiological deterioration

The short storage life of harvested cassava roots is an important constraint that limits the full potential of cassava as a commercial food crop in developing countries. We investigated the molecular changes during physiological deterioration of cassava root after harvesting using isobaric tags for relative and absolute quantification (iTRAQ) of proteins in soluble and non-soluble fractions prepared during a 96 h post-harvest time course. Combining bioinformatic approaches to reduce information redundancy for unsequenced or partially sequenced plant species, we established a comprehensive proteome map of the cassava root and identified quantitatively regulated proteins. Up-regulation of several key proteins confirmed that physiological deterioration of cassava root after harvesting is an active process, with 67 and 170 proteins, respectively, being up-regulated early and later after harvesting. This included regulated proteins that had not previously been associated with physiological deterioration after harvesting, such as linamarase, glutamic acid-rich protein, hydroxycinnamoyl transferase, glycine-rich RNA binding protein, β-1,3-glucanase, pectin methylesterase, maturase K, dehydroascorbate reductase, allene oxide cyclase, and proteins involved in signal pathways. To confirm the regulation of these proteins, activity assays were performed for selected enzymes. Together, our results show that physiological deterioration after harvesting is a highly regulated complex process involving proteins that are potential candidates for biotechnology approaches to reduce such deterioration.

Recent progress in liquid chromatography-based separation and label-free quantitative plant proteomics

Recent innovations in liquid chromatography-mass spectrometry (LC-MS)-based methods have facilitated quantitative and functional proteomic analyses of large numbers of proteins derived from complex samples without any need for protein or peptide labelling. Regardless of its great potential, the application of these proteomics techniques to plant science started only recently. Here we present an overview of label-free quantitative proteomics features and their employment for analysing plants. Recent methods used for quantitative protein analyses by MS techniques are summarized and major challenges associated with label-free LC-MS-based approaches, including sample preparation, peptide separation, quantification and kinetic studies, are discussed. Database search algorithms and specific aspects regarding protein identification of non-sequenced organisms are also addressed. So far, label-free LC-MS in plant science has been used to establish cellular or subcellular proteome maps, characterize plant-pathogen interactions or stress defence reactions, and for profiling protein patterns during developmental processes. Improvements in both, analytical platforms (separation technology and bioinformatics/statistical analysis) and high throughput nucleotide sequencing technologies will enhance the power of this method.

Skeletal muscle proteomics: current approaches, technical challenges and emerging techniques

Background

Skeletal muscle fibres represent one of the most abundant cell types in mammals. Their highly specialised contractile and metabolic functions depend on a large number of membrane-associated proteins with very high molecular masses, proteins with extensive posttranslational modifications and components that exist in highly complex supramolecular structures. This makes it extremely difficult to perform conventional biochemical studies of potential changes in protein clusters during physiological adaptations or pathological processes.

Results

Skeletal muscle proteomics attempts to establish the global identification and biochemical characterisation of all members of the muscle-associated protein complement. A considerable number of proteomic studies have employed large-scale separation techniques, such as high-resolution two-dimensional gel electrophoresis or liquid chromatography, and combined them with mass spectrometry as the method of choice for high-throughput protein identification. Muscle proteomics has been applied to the comprehensive biochemical profiling of developing, maturing and aging muscle, as well as the analysis of contractile tissues undergoing physiological adaptations seen in disuse atrophy, physical exercise and chronic muscle transformation. Biomedical investigations into proteome-wide alterations in skeletal muscle tissues were also used to establish novel biomarker signatures of neuromuscular disorders. Importantly, mass spectrometric studies have confirmed the enormous complexity of posttranslational modifications in skeletal muscle proteins.

Conclusions

This review critically examines the scientific impact of modern muscle proteomics and discusses its successful application for a better understanding of muscle biology, but also outlines its technical limitations and emerging techniques to establish new biomarker candidates.

Less label, more free: approaches in label-free quantitative mass spectrometry

In this review we examine techniques, software, and statistical analyses used in label-free quantitative proteomics studies for area under the curve and spectral counting approaches. Recent advances in the field are discussed in an order that reflects a logical workflow design. Examples of studies that follow this design are presented to highlight the requirement for statistical assessment and further experiments to validate results from label-free quantitation. Limitations of label-free approaches are considered, label-free approaches are compared with labelling techniques, and forward-looking applications for label-free quantitative data are presented. We conclude that label-free quantitative proteomics is a reliable, versatile, and cost-effective alternative to labelled quantitation.

Deuterium isobaric amine-reactive tags for quantitative proteomics

This paper demonstrates the applications of a novel isobaric reagent, named deuterium ((2)H) isobaric amine-reactive tag (DiART), for quantitative proteomics. Peptides labeled with DiART were analyzed using an electrospray ionization (ESI)-based LTQ-Orbitrap mass spectrometer. Our data showed that (2)H-associated isotope effects, such as partial loss of (2)H labels during tandem mass spectrometry (MS/MS) and (2)H-related chromatographic shift, were either not observed or negligible. With the use of a hybrid collision-induced dissociation (CID)-higher energy C-trap dissociation (HCD) acquisition method, we were able to identify DiART-labeled peptides with high confidence and quantify them with high accuracy. Furthermore, we adopted a hybrid electron-transfer dissociation (ETD)-HCD acquisition protocol and developed a novel data analysis approach to measure phosphorylation of peptides. Our results showed DiART had excellent performance on LTQ-Orbitrap instruments and provided a cost-effective technique for large-scale quantitative proteomics measurements.

Interactions of apurinic/apyrimidinic endonuclease with a redox inhibitor: evidence for an alternate conformation of the enzyme

Apurinic/apyrimidinic endonuclease (APE1) is an essential base excision repair protein that also functions as a reduction and oxidation (redox) factor in mammals. Through a thiol-based mechanism, APE1 reduces a number of important transcription factors, including AP-1, p53, NF-κB, and HIF-1α. What is known about the mechanism to date is that the buried residues Cys 65 and Cys 93 are critical for APE1's redox activity. To further detail the redox mechanism, we developed a chemical footprinting-mass spectrometric assay using N-ethylmaleimide (NEM), an irreversible Cys modifier, to characterize the interaction of the redox inhibitor, E3330, with APE1. When APE1 was incubated with E3330, two NEM-modified products were observed, one with two and a second with seven added NEMs; this latter product corresponds to a fully modified APE1. In a similar control reaction without E3330, only the +2NEM product was observed in which the two solvent-accessible Cys residues, C99 and C138, were modified by NEM. Through hydrogen-deuterium amide exchange with analysis by mass spectrometry, we found that the +7NEM-modified species incorporates approximately 40 more deuterium atoms than the native protein, which exchanges nearly identically as the +2NEM product, suggesting that APE1 can be trapped in a partially unfolded state. E3330 was also found to increase the extent of disulfide bond formation involving redox critical Cys residues in APE1 as assessed by liquid chromatography and tandem mass spectrometry, suggesting a basis for its inhibitory effects on APE1's redox activity. Collectively, our results suggest that APE1 adopts a partially unfolded state, which we propose is the redox active form of the enzyme.