Bottom-Up Proteomics (2013-2015): Keeping up in the Era of Systems Biology

The path forward for protein footprinting, covalent labeling, and mass spectrometry-based protein conformational analyses

Mass spectrometry-based approaches to assess protein conformation have become widely utilized due to their sensitivity, low sample requirements, and broad applicability to proteins regardless of size and environment. Their wide applicability and sensitivity also make these techniques suitable for the analysis of complex mixtures of proteins, and thus, they have been applied at the cell and even the simple organism levels. These works are impressive, but they predominately employ "bottom-up" workflows and require proteolytic digestion prior to analysis. Once digested, it is not possible to distinguish the proteoform from which any single peptide is derived and therefore, one cannot associate distal-in primary structure-concurrent post-translational modifications (PTMs) or covalent labels, as they would be found on separate peptides. Thus, analyses via bottom-up proteomics report the average PTM status and higher-order structure (HOS) of all existing proteoforms. Second, these works predominately employ promiscuous reagents to probe protein HOS. While this does lead to improved conformational resolution, the formation of many products can divide the signal associated with low-copy number proteins below signal-to-noise thresholds and complicate the bioinformatic analysis of these already challenging systems. In this perspective, I further detail these limitations and discuss the positives and negatives of top-down proteomics as an alternative.

Integrating the analysis of human biopsies using post-translational modifications proteomics

Proteome diversities and their biological functions are significantly amplified by post-translational modifications (PTMs) of proteins. Shotgun proteomics, which does not typically survey PTMs, provides an incomplete picture of the complexity of human biopsies in health and disease. Recent advances in mass spectrometry-based proteomic techniques that enrich and study PTMs are helping to uncover molecular detail from the cellular level to system-wide functions, including how the microbiome impacts human diseases. Protein heterogeneity and disease complexity are challenging factors that make it difficult to characterize and treat disease. The search for clinical biomarkers to characterize disease mechanisms and complexity related to patient diagnoses and treatment has proven challenging. Knowledge of PTMs is fundamentally lacking. Characterization of complex human samples that clarify the role of PTMs and the microbiome in human diseases will result in new discoveries. This review highlights the key role of proteomic techniques used to characterize unknown biological functions of PTMs derived from complex human biopsies. Through the integration of diverse methods used to profile PTMs, this review explores the genetic regulation of proteoforms, cells of origin expressing specific proteins, and several bioactive PTMs and their subsequent analyses by liquid chromatography and tandem mass spectrometry.

Structure-aware deep model for MHC-II peptide binding affinity prediction

The prediction of major histocompatibility complex (MHC)-peptide binding affinity is an important branch in immune bioinformatics, especially helpful in accelerating the design of disease vaccines and immunity therapy. Although deep learning-based solutions have yielded promising results on MHC-II molecules in recent years, these methods ignored structure knowledge from each peptide when employing the deep neural network models. Each peptide sequence has its specific combination order, so it is worth considering adding the structural information of the peptide sequence to the deep model training. In this work, we use positional encoding to represent the structural information of peptide sequences and validly combine the positional encoding with existing models by different strategies. Experiments on three datasets show that the introduction of position-coding information can further improve the performance built upon the existing model. The idea of introducing positional encoding to this field can provide important reference significance for the optimization of the deep network structure in the future.

The Influence of Protein Secretomes of Enterococcus durans on ex vivo Human Gut Microbiome

The gut microbiome plays a critical role to all animals and humans health. Methods based on ex vivo cultures are time and cost-effective solutions for rapid evaluation of probiotic effects on microbiomes. In this study, we assessed whether the protein secretome from the potential probiotic Enterococcus durans LAB18S grown on fructoligosaccharides (FOS) and galactoligosaccharides (GOS) had specific effects on ex vivo cultured intestinal microbiome obtained from a healthy individual. Metaproteomics was used to evaluate changes in microbial communities of the human intestinal microbiome. Hierarchical clustering analysis revealed 654 differentially abundant proteins from the metaproteome samples, showing that gut microbial protein expression varied on the presence of different E. durans secretomes. Increased amount of Bacteroidetes phylum was observed in treatments with secretomes from E. durans cultures on FOS, GOS and albumin, resulting in a decrease of the Firmicutes to Bacteroidetes (F/B) ratio. The most functionally abundant bacterial taxa were Roseburia, Bacteroides, Alistipes and Faecalibacterium. The results suggest that the secretome of E. durans may have favorable effects on the intestinal microbial composition, stimulating growth and different protein expression of beneficial bacteria. These findings suggest that proteins secreted by E. durans growing on FOS and GOS have different effects on the modulation of gut microbiota functional activities during cultivation.

Collision energies: Optimization strategies for bottom-up proteomics

Mass-spectrometry coupled to liquid chromatography is an indispensable tool in the field of proteomics. In the last decades, more and more complex and diverse biochemical and biomedical questions have arisen. Problems to be solved involve protein identification, quantitative analysis, screening of low abundance modifications, handling matrix effect, and concentrations differing by orders of magnitude. This led the development of more tailored protocols and problem centered proteomics workflows, including advanced choice of experimental parameters. In the most widespread bottom-up approach, the choice of collision energy in tandem mass spectrometric experiments has outstanding role. This review presents the collision energy optimization strategies in the field of proteomics which can help fully exploit the potential of MS based proteomics techniques. A systematic collection of use case studies is then presented to serve as a starting point for related further scientific work. Finally, this article discusses the issue of comparing results from different studies or obtained on different instruments, and it gives some hints on methodology transfer between laboratories based on measurement of reference species.

Characterizing the top-down sequencing of protein ions prior to mobility separation in a timsTOF

Mass spectrometry (MS)-based proteomics workflows of intact protein ions have increasingly been utilized to study biological systems. These workflows, however, frequently result in convoluted and difficult to analyze mass spectra. Ion mobility spectrometry (IMS) is a promising tool to overcome these limitations by separating ions by their mass- and size-to-charge ratios. In this work, we further characterize a newly developed method to collisionally dissociate intact protein ions in a trapped ion mobility spectrometry (TIMS) device. Dissociation occurs prior to ion mobility separation and thus, all product ions are distributed throughout the mobility dimension, enabling facile assignment of near isobaric product ions. We demonstrate that collisional activation within a TIMS device is capable of dissociating protein ions up to 66 kDa. We also demonstrate that the ion population size within the TIMS device significantly influences the efficiency of fragmentation. Lastly, we compare CIDtims to the other modes of collisional activation available on the Bruker timsTOF and demonstrate that the mobility resolution in CIDtims enables the annotation of overlapping fragment ions and improves sequence coverage.

Insights into Common Octopus (Octopus vulgaris) Ink Proteome and Bioactive Peptides Using Proteomic Approaches

The common octopus (Octopus vulgaris) is nowadays the most demanded cephalopod species for human consumption. This species was also postulated for aquaculture diversification to supply its increasing demand in the market worldwide, which only relies on continuously declining field captures. In addition, they serve as model species for biomedical and behavioral studies. Body parts of marine species are usually removed before reaching the final consumer as by-products in order to improve preservation, reduce shipping weight, and increase product quality. These by-products have recently attracted increasing attention due to the discovery of several relevant bioactive compounds. Particularly, the common octopus ink has been described as having antimicrobial and antioxidant properties, among others. In this study, the advanced proteomics discipline was applied to generate a common octopus reference proteome to screen potential bioactive peptides from fishing discards and by-products such as ink. A shotgun proteomics approach by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) using an Orbitrap Elite instrument was used to create a reference dataset from octopus ink. A total of 1432 different peptides belonging to 361 non-redundant annotated proteins were identified. The final proteome compilation was investigated by integrated in silico studies, including gene ontology (GO) term enrichment, pathways, and network studies. Different immune functioning proteins involved in the innate immune system, such as ferritin, catalase, proteasome, Cu/Zn superoxide dismutase, calreticulin, disulfide isomerase, heat shock protein, etc., were found in ink protein networks. Additionally, the potential of bioactive peptides from octopus ink was addressed. These bioactive peptides can exert beneficial health properties such as antimicrobial, antioxidant, antihypertensive, and antitumoral properties and are therefore considered lead compounds for developing pharmacological, functional foods or nutraceuticals.

A peptide-centric approach to analyse quantitative proteomics data- an application to prostate cancer biomarker discovery

Bottom-up proteomics is a popular approach in molecular biomarker research. However, protein analysts have realized the limitations of protein-based approaches for identifying and quantifying proteins in complex samples, such as the identification of peptides sequences shared by multiple proteins and the difficulty in identifying modified peptides. Thus, there are many exciting opportunities to improve analysis methods. Here, an alternative method focused on peptide analysis is proposed as a complement to the conventional proteomics data analysis. To investigate this hypothesis, a peptide-centric approach was applied to reanalyse a urine proteome dataset of samples from prostate cancer patients and controls. The results were compared with the conventional protein-centric approach. The relevant proteins/peptides to discriminate the groups were detected based on two approaches, p-value and VIP values obtained by a PLS-DA model. A comparison of the two strategies revealed high inconsistency between protein and peptide information and greater involvement of peptides in key PCa processes. This peptide analysis unveiled discriminative features that are lost when proteins are analyzed as homogeneous entities. This type of analysis is innovative in PCa and integrated with the widely used protein-centric approach might provide a more comprehensive view of this disease and revolutionize biomarker discovery. SIGNIFICANCE: In this study, the application of a protein and peptide-centric approaches to reanalyse a urine proteome dataset from prostate cancer (PCa) patients and controls showed that many relevant proteins/peptides are missed by the conservative nature of p-value in statistical tests, therefore, the inclusion of variable selection methods in the analysis of the dataset reported in this work is fruitful. Comparison of protein- and peptide-based approaches revealed a high inconsistency between protein and peptide information and a greater involvement of peptides in key PCa processes. These results provide a new perspective to analyse proteomics data and detect relevant targets based on the integration of peptide and protein information. This data integration allows to unravel discriminative features that normally go unnoticed, to have a more comprehensive view of the disease pathophysiology and to open new avenues for the discovery of biomarkers.

Gut Microbiome Proteomics in Food Allergies

Food allergies (FA) have dramatically increased in recent years, particularly in developed countries. It is currently well-established that food tolerance requires the strict maintenance of a specific microbial consortium in the gastrointestinal (GI) tract microbiome as alterations in the gut microbiota can lead to dysbiosis, causing inflammation and pathogenic intestinal conditions that result in the development of FA. Although there is currently not enough knowledge to fully understand how the interactions between gut microbiota, host responses and the environment cause food allergies, recent advances in '-omics' technologies (i.e., proteomics, genomics, metabolomics) and in approaches involving systems biology suggest future headways that would finally allow the scientific understanding of the relationship between gut microbiome and FA. This review summarizes the current knowledge in the field of FA and insights into the future advances that will be achieved by applying proteomic techniques to study the GI tract microbiome in the field of FA and their medical treatment. Metaproteomics, a proteomics experimental approach of great interest in the study of GI tract microbiota, aims to analyze and identify all the proteins in complex environmental microbial communities; with shotgun proteomics, which uses liquid chromatography (LC) for separation and tandem mass spectrometry (MS/MS) for analysis, as it is the most promising technique in this field.

Rewiring of Gene Expression in Pseudomonas aeruginosa During Diauxic Growth Reveals an Indirect Regulation of the MexGHI-OpmD Efflux Pump by Hfq

In Pseudomonas aeruginosa, the RNA chaperone Hfq and the catabolite repression protein Crc act in concert to regulate numerous genes during carbon catabolite repression (CCR). After alleviation of CCR, the RNA CrcZ sequesters Hfq/Crc, which leads to a rewiring of gene expression to ensure the consumption of less preferred carbon and nitrogen sources. Here, we performed a multiomics approach by assessing the transcriptome, translatome, and proteome in parallel in P. aeruginosa strain O1 during and after relief of CCR. As Hfq function is impeded by the RNA CrcZ upon relief of CCR, and Hfq is known to impact antibiotic susceptibility in P. aeruginosa, emphasis was laid on links between CCR and antibiotic susceptibility. To this end, we show that the mexGHI-opmD operon encoding an efflux pump for the antibiotic norfloxacin and the virulence factor 5-Methyl-phenazine is upregulated after alleviation of CCR, resulting in a decreased susceptibility to the antibiotic norfloxacin. A model for indirect regulation of the mexGHI-opmD operon by Hfq is presented.

Predicting fragment intensities and retention time of iTRAQ- and TMTPro-labeled peptides with Prosit-TMT

Isobaric labeling increases the throughput of proteomics by enabling the parallel identification and quantification of peptides and proteins. Over the past decades, a variety of isobaric tags have been developed allowing the multiplexed analysis of up to 18 samples. However, experiments utilizing such tags often exhibit reduced identification rates and thus show decreased analytical depth. Re-scoring has been shown to rescue otherwise missed identifications but was not yet systematically applied on isobarically labeled data. Because iTRAQ 4/8-plex and the recently released TMTpro 16/18-plex share similar characteristics with TMT 6/10/11-plex, we hypothesized that Prosit-TMT, trained exclusively on 6/10/11-plex labeled peptides, may be applicable to these isobaric labeling strategies as well. To investigate this, we re-analyzed nine publicly available datasets covering iTRAQ and TMTpro labeling for samples with human and mouse origin. We highlight that Prosit-TMT shows remarkably good performance when comparing experimentally acquired and predicted fragmentation spectra (R of 0.84 - 0.9) and retention times (ΔRT95% of 3 - 10% gradient time) of peptides. Furthermore, re-scoring substantially increases the number of confidently identified spectra, peptides, and proteins. This article is protected by copyright. All rights reserved.

Prosit-TMT: Deep Learning Boosts Identification of TMT-Labeled Peptides

The prediction of fragment ion intensities and retention time of peptides has gained significant attention over the past few years. However, the progress shown in the accurate prediction of such properties focused primarily on unlabeled peptides. Tandem mass tags (TMT) are chemical peptide labels that are coupled to free amine groups usually after protein digestion to enable the multiplexed analysis of multiple samples in bottom-up mass spectrometry. It is a standard workflow in proteomics ranging from single-cell to high-throughput proteomics. Particularly for TMT, increasing the number of confidently identified spectra is highly desirable as it provides identification and quantification information with every spectrum. Here, we report on the generation of an extensive resource of synthetic TMT-labeled peptides as part of the ProteomeTools project and present the extension of the deep learning model Prosit to accurately predict the retention time and fragment ion intensities of TMT-labeled peptides with high accuracy. Prosit-TMT supports CID and HCD fragmentation and ion trap and Orbitrap mass analyzers in a single model. Reanalysis of published TMT data sets show that this single model extracts substantial additional information. Applying Prosit-TMT, we discovered that the expression of many proteins in human breast milk follows a distinct daily cycle which may prime the newborn for nutritional or environmental cues.

Nano liquid chromatography, an updated review

Low flow chromatography has a rich history of innovation but has yet to reach widespread implementation in bioanalytical applications. Improvements in pump technology, microfluidic connections, and nano-electrospray sources for mass spectrometry have laid the groundwork for broader application, and innovation in this space has accelerated in recent years. This article reviews the instrumentation used for nano-flow liquid chromatography , the types of columns employed, and strategies for multi-dimensionality of separations, which is key to the future state of the technique to the high-throughput needs of modern bioanalysis. An update of the current applications where nano-LC is widely used, such as proteomics and metabolomics, is discussed. But the trend towards biopharmaceutical development of increasingly complex, targeted, and potent therapeutics for the safe treatment of disease drives the need for ultimate selectivity and sensitivity of our analytical platforms for targeted quantitation in a regulated space. The selectivity needs are best addressed by mass spectrometric detection, especially at high resolutions, and exquisite sensitivity is provided by nano-electrospray ionization as the technology continues to evolve into an accessible, robust, and easy to use platform.

Fragmentation and Mobility Separation of Peptide and Protein Ions in a Trapped-Ion Mobility Device

Ion mobility separations (IMS) have increasingly been coupled with mass spectrometry to increase peak capacity and deconvolute complex mass spectra in proteomics workflows. IMS separations can be integrated prior to or following the collisional activation step. Post-activation IMS separations have demonstrated many advantages, yet few instrument platforms are capable of this feat. Here, we present the fragmentation of peptide ions within a commercially available trapped-ion mobility spectrometry device. Fragmentation is initiated prior to mobility analysis enabling the separation of generated product ions. The added separation step deconvolutes product ion spectra and permits improved annotation of product ions. Furthermore, we demonstrate the isolation and fragmentation of mobility separated product ions with the downstream quadrupole and collisional cell. When applied to melittin and ubiquitin, this ion mobility assisted pseudo-MS³ fragmentation approach generates sequence coverage ∼50% greater than that of typical MS² analyses. We envision this ion-mobility-assisted fragmentation technique as the foundation of a powerful new pseudo-MS³ workflow for application toward middle- or top-down proteomics.

Mass spectrometry-based top-down and bottom-up approaches for proteomic analysis of the Moroccan Buthus occitanus scorpion venom

Buthus occitanus (B. occitanus) is one of the most dangerous scorpions in the world. Despite the involvement of B. occitanus scorpion in severe cases of envenomation in Morocco, no study has focused yet on the proteomic composition of the Moroccan B. occitanus scorpion venom. Mass spectrometry‐based proteomic techniques are commonly used in the study of scorpion venoms. The implementation of top‐down and bottom‐up approaches for proteomic analyses facilitates screening by allowing a global view of the structural aspects of such complex matrices. Here, we provide a partial overview of the venom of B. occitanus scorpion, in order to explore the diversity of its toxins and hereafter understand their effects. To this end, a combination of top‐down and bottom‐up approaches was applied using nano‐high liquid chromatography coupled to nano‐electrospray tandem mass spectrometry (nano‐LC‐ESI MS/MS). The LC‐MS results showed that B. occitanus venom contains around 200 molecular masses ranging from 1868 to 16 720 Da, the most representative of which are those between 5000 and 8000 Da. Interestingly, combined top‐down and bottom‐up LC‐MS/MS results allowed the identification of several toxins, which were mainly those acting on ion channels, including those targeting sodium (NaScTxs), potassium (KScTxs), chloride (ClScTxs), and calcium channels (CaScTx), as well as antimicrobial peptides (AMPs), amphipathic peptides, myotropic neuropeptides, and hypothetical secreted proteins. This study reveals the molecular diversity of B. occitanus scorpion venom and identifies components that may have useful pharmacological activities.

Using high-abundance proteins as guides for fast and effective peptide/protein identification from human gut metaproteomic data

BACKGROUND

A few recent large efforts significantly expanded the collection of human-associated bacterial genomes, which now contains thousands of entities including reference complete/draft genomes and metagenome assembled genomes (MAGs). These genomes provide useful resource for studying the functionality of the human-associated microbiome and their relationship with human health and diseases. One application of these genomes is to provide a universal reference for database search in metaproteomic studies, when matched metagenomic/metatranscriptomic data are unavailable. However, a greater collection of reference genomes may not necessarily result in better peptide/protein identification because the increase of search space often leads to fewer spectrum-peptide matches, not to mention the drastic increase of computation time. Video Abstract METHODS: Here, we present a new approach that uses two steps to optimize the use of the reference genomes and MAGs as the universal reference for human gut metaproteomic MS/MS data analysis. The first step is to use only the high-abundance proteins (HAPs) (i.e., ribosomal proteins and elongation factors) for metaproteomic MS/MS database search and, based on the identification results, to derive the taxonomic composition of the underlying microbial community. The second step is to expand the search database by including all proteins from identified abundant species. We call our approach HAPiID (HAPs guided metaproteomics IDentification).

RESULTS

We tested our approach using human gut metaproteomic datasets from a previous study and compared it to the state-of-the-art reference database search method MetaPro-IQ for metaproteomic identification in studying human gut microbiota. Our results show that our two-steps method not only performed significantly faster but also was able to identify more peptides. We further demonstrated the application of HAPiID to revealing protein profiles of individual human-associated bacterial species, one or a few species at a time, using metaproteomic data.

CONCLUSIONS

The HAP guided profiling approach presents a novel effective way for constructing target database for metaproteomic data analysis. The HAPiID pipeline built upon this approach provides a universal tool for analyzing human gut-associated metaproteomic data.

Functional Network Profiles in ARSACS Disclosed by Aptamer-Based Proteomic Technology

Although the genetic basis of autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS) has been uncovered, our poor understanding of disease mechanisms requires new light on functional pathways and modifying factors to improve early diagnostic strategies and offer alternative treatment options in a rare condition with no cure. Investigation of the pathologic state combining disease models and quantitative omic approach might improve biomarkers discovery with possible implications in patients' diagnoses. In this study, we analyzed proteomics data obtained using the SomaLogic technology, comparing cell lysates from ARSACS patients and from a SACS KO SH-SY5Y neuroblastoma cell model. Single-stranded deoxyoligonucleotides, selected in vitro from large random libraries, bound and quantified molecular targets related to the neuroinflammation signaling pathway and to neuronal development. Changes in protein levels were further analyzed by bioinformatics and network approaches to identify biomarkers of ARSACS and functional pathways impaired in the disease. We identified novel significantly dysregulated biological processes related to neuroinflammation, synaptogenesis, and engulfment of cells in patients and in KO cells compared with controls. Among the differential expressed proteins found in this work, we identified several proteins encoded by genes already known to be mutated in other forms of neurodegeneration. This finding suggests that common dysfunctional networks could be therapeutic targets for future investigations.

MicroPOTS Analysis of Barrett's Esophageal Cell Line Models Identifies Proteomic Changes after Physiologic and Radiation Stress

Moving from macroscale preparative systems in proteomics to micro- and nanotechnologies offers researchers the ability to deeply profile smaller numbers of cells that are more likely to be encountered in clinical settings. Herein a recently developed microscale proteomic method, microdroplet processing in one pot for trace samples (microPOTS), was employed to identify proteomic changes in ∼200 Barrett’s esophageal cells following physiologic and radiation stress exposure. From this small population of cells, microPOTS confidently identified >1500 protein groups, and achieved a high reproducibility with a Pearson’s correlation coefficient value of R > 0.9 and over 50% protein overlap from replicates. A Barrett’s cell line model treated with either lithocholic acid (LCA) or X-ray had 21 (e.g., ASNS, RALY, FAM120A, UBE2M, IDH1, ESD) and 32 (e.g., GLUL, CALU, SH3BGRL3, S100A9, FKBP3, AGR2) overexpressed proteins, respectively, compared to the untreated set. These results demonstrate the ability of microPOTS to routinely identify and quantify differentially expressed proteins from limited numbers of cells.

Sequential amidation of peptide C-termini for improving fragmentation efficiency

Owing to the poor fragmentation efficiency caused by the lack of a positively charged basic group at the C-termini of peptides, the identification of nontryptic peptides in classical proteomics is known to be less efficient. Particularly, attaching positively charged basic groups to C-termini via chemical derivatizations is known to be able to enhance their fragmentation efficiency. In this study, we introduced a novel strategy, C-termini sequential amidation reaction (CSAR), to improve peptide fragmentation efficiency. By this strategy, C-terminal and side-chain carboxyl groups were firstly amidated by neutral methylamine (MA), and then C-terminal amide bonds were selectively deamidated through peptide amidase while side-chain amide bonds remained unchanged, followed by the secondary amidation of C-termini via basic agmatine (AG). We optimized the amidation reaction conditions to achieve the MA derivatization efficiency of >99% for side-chain carboxyl groups and AG derivatization efficiency of 80% for the hydrolytic C-termini. We applied CSAR strategy to identify bovine serum albumin (BSA) chymotryptic digests, resulting in the increased fragmentation efficiencies (improvement by 9-32%) and charge states (improvement by 39-52%) under single or multiple dissociation modes. The strategy described here might be a promising approach for the identification of peptides that suffered from poor fragmentation efficiency.

Review of Three-Dimensional Liquid Chromatography Platforms for Bottom-Up Proteomics

Proteomics is a large-scale study of proteins, aiming at the description and characterization of all expressed proteins in biological systems. The expressed proteins are typically highly complex and large in abundance range. To fulfill high accuracy and sensitivity of proteome analysis, the hybrid platforms of multidimensional (MD) separations and mass spectrometry have provided the most powerful solution. Multidimensional separations provide enhanced peak capacity and reduce sample complexity, which enables mass spectrometry to analyze more proteins with high sensitivity. Although two-dimensional (2D) separations have been widely used since the early period of proteomics, three-dimensional (3D) separation was barely used by low reproducibility of separation, increased analysis time in mass spectrometry. With developments of novel microscale techniques such as nano-UPLC and improvements of mass spectrometry, the 3D separation becomes a reliable and practical selection. This review summarizes existing offline and online 3D-LC platforms developed for proteomics and their applications. In detail, setups and implementation of those systems as well as their advances are outlined. The performance of those platforms is also discussed and compared with the state-of-the-art 2D-LC. In addition, we provide some perspectives on the future developments and applications of 3D-LC in proteomics.

Reverse diauxie phenotype in Pseudomonas aeruginosa biofilm revealed by exometabolomics and label-free proteomics

Microorganisms enhance fitness by prioritizing catabolism of available carbon sources using a process known as carbon catabolite repression (CCR). Planktonically grown Pseudomonas aeruginosa is known to prioritize the consumption of organic acids including lactic acid over catabolism of glucose using a CCR strategy termed "reverse diauxie." P. aeruginosa is an opportunistic pathogen with well-documented biofilm phenotypes that are distinct from its planktonic phenotypes. Reverse diauxie has been described in planktonic cultures, but it has not been documented explicitly in P. aeruginosa biofilms. Here a combination of exometabolomics and label-free proteomics was used to analyze planktonic and biofilm phenotypes for reverse diauxie. P. aeruginosa biofilm cultures preferentially consumed lactic acid over glucose, and in addition, the cultures catabolized the substrates completely and did not exhibit the acetate secreting "overflow" metabolism that is typical of many model microorganisms. The biofilm phenotype was enabled by changes in protein abundances, including lactate dehydrogenase, fumarate hydratase, GTP cyclohydrolase, L-ornithine N(5)-monooxygenase, and superoxide dismutase. These results are noteworthy because reverse diauxie-mediated catabolism of organic acids necessitates a terminal electron acceptor like O2, which is typically in low supply in biofilms due to diffusion limitation. Label-free proteomics identified dozens of proteins associated with biofilm formation including 16 that have not been previously reported, highlighting both the advantages of the methodology utilized here and the complexity of the proteomic adaptation for P. aeruginosa biofilms. Documenting the reverse diauxic phenotype in P. aeruginosa biofilms is foundational for understanding cellular nutrient and energy fluxes, which ultimately control growth and virulence.

Miniaturized sample preparation on a digital microfluidics device for sensitive bottom-up microproteomics of mammalian cells using magnetic beads and mass spectrometry-compatible surfactants

While LC-MS-based proteomics with high nanograms to micrograms of total protein has become routine, the analysis of samples derived from low cell numbers is challenged by factors such as sample losses, or difficulties encountered with the manual manipulation of small liquid volumes. Digital microfluidics (DMF) is an emerging technique for miniaturized and automated droplet manipulation, which has been proposed as a promising tool for proteomic sample preparation. However, proteome analysis of samples prepared on-chip by DMF has previously been unfeasible, due to incompatibility with down-stream LC-MS instrumentation. To overcome these limitations, we here developed protocols for bottom-up LC-MS based proteomics sample preparation of as little as 100 mammalian cells on a commercially available digital microfluidics device. To this end, we developed effective cell lysis conditions optimized for DMF, as well as detergent-buffer systems compatible with downstream proteolytic digestion on DMF chips and subsequent LC-MS analysis. A major step was the introduction of the single-pot, solid-phase-enhanced sample preparation (SP3) approach on-chip, which allowed the removal of salts and anti-fouling polymeric detergents, thus rendering sample preparation by DMF compatible with LC-MS-based proteome analysis. Application of DMF-SP3 to the proteome analysis of Jurkat T cells led to the identification of up to 2500 proteins from approximately 500 cells, and up to 1200 proteins from approximately 100 cells on an Orbitrap mass spectrometer, emphasizing the high compatibility of DMF-SP3 with low protein input and minute volumes handled by DMF. Taken together, we demonstrate the first sample preparation workflow for proteomics on a DMF chip device reported so far, allowing the sensitive analysis of limited biological material.

Multiple solvent elution, a method to counter the effects of coelution and ion suppression in LC-MS analysis in bottom up proteomics

On average a human cell type expresses around 10,000 different protein coding genes synthesizing all the different molecular forms of the protein product (proteoforms) found in a cell. In a typical shotgun bottom up proteomic approach, the proteins are enzymatically cleaved, producing several 100,000 s of different peptides that are analyzed with liquid chromatography-tandem mass spectrometry (LC-MSMS). One of the major consequences of this high sample complexity is that coelution of peptides cannot be avoided. Moreover, low abundant peptides are difficult to identify as they have a lower chance of being selected for fragmentation due to ion-suppression effects and the semi-stochastic nature of the precursor selection in data-dependent shotgun proteomic analysis where peptides are selected for fragmentation analysis one-by-one as they elute from the column. In the current study we explore a simple novel approach that has the potential to counter some of the effect of coelution of peptides and improves the number of peptide identifications in a bottom-up proteomic analysis. In this method, peptides from a HeLa cell digest were eluted from the reverse phase column using three different elution solvents (acetonitrile, methanol and acetone) in three replicate reversed phase LC-MS/MS shotgun proteomic analysis. Results were compared with three technical replicates using the same solvent, which is common practice in proteomic analysis. In total, we see an increase of up to 10% in unique protein and up to 30% in unique peptide identifications from the combined analysis using different elution solvents when compared to the combined identifications from the three replicates of the same solvent. In addition, the overlap of unique peptide identifications common in all three LC-MS analyses in our approach is only 23% compared to 50% in the replicates using the same solvent. The method presented here thus provides an easy to implement method to significantly reduce the effects of coelution and ion suppression of peptides and improve protein coverage in shotgun proteomics. Data are available via ProteomeXchange with identifier PXD011908.

Perspective and Guidelines for Metaproteomics in Microbiome Studies

The microbiome is emerging as a prominent factor affecting human health, and its dysbiosis is associated with various diseases. Compositional profiling of microbiome is increasingly being supplemented with functional characterization. Metaproteomics is intrinsically focused on functional changes and therefore will be an important tool in those studies of the human microbiome. In the past decade, development of new experimental and bioinformatic approaches for metaproteomics has enabled large-scale human metaproteomic studies. However, challenges still exist, and there remains a lack of standardizations and guidelines for properly performing metaproteomic studies on human microbiome. Herein, we provide a perspective of recent developments, the challenges faced, and the future directions of metaproteomics and its applications. In addition, we propose a set of guidelines/recommendations for performing and reporting the results from metaproteomic experiments for the study of human microbiomes. We anticipate that these guidelines will be optimized further as more metaproteomic questions are raised and addressed, and metaproteomic applications are published, so that they are eventually recognized and applied in the field.

A Multiplex Fragment-Ion-Based Method for Accurate Proteome Quantification

Multiplex proteome quantification with high accuracy is urgently required to achieve a comprehensive understanding of dynamic cellular and physiological processes. Among the existing quantification strategies, fragment-ion-based methods can provide highly accurate results, but the multiplex capacity is limited to 3-plex. Herein, we developed a multiplex pseudo-isobaric dimethyl labeling (m-pIDL) method to extend the capacity of the fragment-ion-based method to 6-plex by one-step dimethyl labeling with several millidalton and dalton mass differences between precursor ions and enlarging the isolation window of precursor ions to 10 m/ z during data acquisition. m-pIDL showed high quantification accuracy within the 20-fold dynamic range. Notably, the ratio compression was 1.13-fold in a benchmark two-proteome model (5:1 mixed E. coli proteins with HeLa proteins as interference), indicating that by m-pIDL, the ratio distortion of isobaric labeling approaches and the approximate 40% ratio shift of the label-free quantification strategy could be effectively eliminated. Additionally, m-pIDL did not show ratio variation among post-translational modifications (CV = 6.66%), which could benefit the measurement of universal protein properties for proteomic atlases. We further employed m-pIDL to monitor the time-resolved responses of the TGF-β-induced epithelial-mesenchymal transition (EMT) in lung adenocarcinoma A549 cell lines, which facilitated the finding of new potential regulatory proteins. Therefore, the 6-plex quantification of m-pIDL with the remarkably high accuracy might create new prospects for comprehensive proteome analysis.

"One-Pot" Sample Processing Method for Proteome-Wide Analysis of Microbial Cells and Spores

PURPOSE

Bacterial endospores, the transmissible forms of pathogenic bacilli and clostridia, are heterogeneous multilayered structures composed of proteins. These proteins protect the spores against a variety of stresses, thus helping spore survival, and assist in germination, by interacting with the environment to form vegetative cells. Owing to the complexity, insolubility, and dynamic nature of spore proteins, it has been difficult to obtain their comprehensive protein profiles.

EXPERIMENTAL DESIGN

The intact spores of Bacillus subtilis, Bacillus cereus, and Peptoclostridium difficile and their vegetative counterparts were disrupted by bead beating in 6 m urea under reductive conditions. The heterogeneous mixture was then double digested with LysC and trypsin. Next, the peptide mixture was pre-fractionated with zwitterionic hydrophilic interaction liquid chromatography (ZIC-HILIC) followed by reverse-phase LC-FT-MS analysis of the fractions.

RESULTS

"One-pot" method is a simple, robust method that yields identification of >1000 proteins with high confidence, across all spore layers from B. subtilis, B. cereus, and P. difficile.

CONCLUSIONS AND MEDICAL RELEVANCE

This method can be employed for proteome-wide analysis of non-spore-forming as well as spore-forming pathogens. Analysis of spore protein profile will help to understand the sporulation and germination processes and to distinguish immunogenic protein markers.

Ultra-high mass multimer analysis of protein-1a capping domains by a silicon nanomembrane detector

Conventional time of flight ion detectors are based on secondary electron multipliers encountering a significant loss in detection efficiency, sensitivity and resolution with protein mass above 50kDa. In this work we employ a silicon nanomembrane detector in a Matrix-Assisted Laser Desorption/Ionization coupled to time of flight (MALDI-TOF) mass spectrometer. The operating principle relies on phonon-assisted field emission with excellent performance in the high mass range from 0.001-2MDa. In addition to the analysis of standard proteins the nanomembrane detector (NMD) has the potential for the detection and structural investigation of complex macromolecular assemblies through non-covalent interactions. In order to investigate this hypothesis, the N-terminal capping/methyltransferase domain (CAP) of the Brome Mosaic Virus (BMV) 1a replication protein by MALDI-TOF-NMD is analyzed. The signals detected at the high m/z-ratios of 912.6/982.7 (×10³) and 1333.3 (×10³) could be modified species of CAP-tricta/tetractamer and the octadecamer. For the first time, the NMD is applied to detect biologically complex macromolecular protein assemblies. Hence, this technology overcomes the limitations of conventional TOF-detectors and increases the analytical range of MALDI-TOF. This technology will be a future alternative for the structural analysis of intact virus capsids that will complement other MS-based techniques such as native mass spectrometry.

Combined use of protein biomarkers and network analysis unveils deregulated regulatory circuits in Duchenne muscular dystrophy

Although the genetic basis of Duchenne muscular dystrophy has been known for almost thirty years, the cellular and molecular mechanisms characterizing the disease are not completely understood and an efficacious treatment remains to be developed. In this study we analyzed proteomics data obtained with the SomaLogic technology from blood serum of a cohort of patients and matched healthy subjects. We developed a workflow based on biomarker identification and network-based pathway analysis that allowed us to describe different deregulated pathways. In addition to muscle-related functions, we identified other biological processes such as apoptosis, signaling in the immune system and neurotrophin signaling as significantly modulated in patients compared with controls. Moreover, our network-based analysis identified the involvement of FoxO transcription factors as putative regulators of different pathways. On the whole, this study provided a global view of the molecular processes involved in Duchenne muscular dystrophy that are decipherable from serum proteome.

Fixed-Charge Trimethyl Pyrilium Modification for Enabling Enhanced Top-Down Mass Spectrometry Sequencing of Intact Protein Complexes

Mass spectrometry of intact proteins and protein complexes has the potential to provide a transformative level of information on biological systems, ranging from sequence and post-translational modification analysis to the structures of whole protein assemblies. This ambitious goal requires the efficient fragmentation of both intact proteins and the macromolecular, multicomponent machines they collaborate to create through noncovalent interactions. Improving technologies in an effort to achieve such fragmentation remains perhaps the greatest challenge facing current efforts to comprehensively analyze cellular protein composition and is essential to realizing the full potential of proteomics. In this work, we describe the use of a trimethyl pyrylium (TMP) fixed-charge covalent labeling strategy aimed at enhancing fragmentation for challenging intact proteins and intact protein complexes. Combining analysis of TMP-modified and unmodified protein complexes results in a greater diversity of regions within the protein that give rise to fragments, and results in an up to 2.5-fold increase in sequence coverage when compared to unmodified protein alone, for protein complexes up to 148 kDa. TMP modification offers a simple and powerful platform to expand the capabilities of existing mass spectrometric instrumentation for the complete characterization of intact protein assemblies.

IMTBX and Grppr: Software for Top-Down Proteomics Utilizing Ion Mobility-Mass Spectrometry

Top-down proteomics has emerged as a transformative method for the analysis of protein sequence and post-translational modifications (PTMs). Top-down experiments have historically been performed primarily on ultrahigh resolution mass spectrometers due to the complexity of spectra resulting from fragmentation of intact proteins, but recent advances in coupling ion mobility separations to faster, lower resolution mass analyzers now offer a viable alternative. However, software capable of interpreting the highly complex two-dimensional spectra that result from coupling ion mobility separation to top-down experiments is currently lacking. In this manuscript we present a software suite consisting of two programs, IMTBX ("IM Toolbox") and Grppr ("Grouper"), that enable fully automated processing of such data. We demonstrate the capabilities of this software suite by examining a series of intact proteins on a Waters Synapt G2 ion-mobility equipped mass spectrometer and compare the results to the manual and semiautomated data analysis procedures we have used previously.

Toward Large-Scale Computational Prediction of Protein Complexes

Cellular functions are often performed by multiprotein structures called protein complexes. These complexes are dynamic structures that evolve during the cell cycle or in response to external and internal stimuli, and are tightly regulated by protein expression in different tissues resulting in quantitative and qualitative variation of protein complexes. Advances in high-throughput techniques, such as mass-spectrometry and yeast two-hybrid provided a large amount of data on protein-protein interactions. This sparked the development of computational methods able to predict protein complex formation under a variety of biological and clinical conditions. However, the challenges that need to be addressed for successful computational protein complex prediction are highly complex.The post-genomic era saw an emerging number of algorithms and software, which are able to predict protein complexes from protein-protein interaction networks and a variety of other sources. Despite the high capacity of these methods to qualitatively predict protein complexes, they could provide only limited or no quantitative information of the predicted complexes. Recently, a new large-scale simulation of protein complexes was able to achieve this task by simulating protein complex formation on the proteome scale.In this chapter, we review representative methods that can predict multiple protein complexes at different scales and discuss how these can be combined with emerging sources of data in order to improve protein complex characterization.

Increased serotransferrin and ceruloplasmin turnover in diet-controlled patients with type 2 diabetes

Type 2 diabetes mellitus (T2DM) is associated with oxidative stress and perturbed iron metabolism. Serotransferrin (Trf) and ceruloplasmin (Cp) are two key proteins involved in iron metabolism and anti-oxidant defense. Non-enzymatic glycation and oxidative modification of plasma proteins are known to occur under hyperglycemia and oxidative stress. In this study, shotgun proteomics and 2H2O-based metabolic labeling were used to characterize post-translational modifications and assess the kinetics of Trf and Cp in T2DM patients and matched controls in vivo. Six early lysine (Amadori) and one advanced arginine glycation were detected in Trf. No glycation, but five asparagine deamidations, were found in Cp. T2DM patients had increased fractional catabolic rates of both Trf and Cp that correlated with HbA1c (p < 0.05). The glycated Trf population was subject to an even faster degradation compared to the total Trf pool, suggesting that hyperglycemia contributed to an increased Trf degradation in T2DM patients. Enhanced production of Trf and Cp kept their levels stable. The changes in Trf and Cp turnover were associated with increased systemic oxidative stress without any alteration in iron status in T2DM. These findings can help better understand the potential role of altered Trf and Cp metabolism in the pathogenesis of T2DM and other diseases.

Targeted Annotation of S-Sulfonylated Peptides by Selective Infrared Multiphoton Dissociation Mass Spectrometry

Protein S-sulfinylation (R-SO₂^-) and S-sulfonylation (R-SO₃^-) are irreversible oxidative post-translational modifications of cysteine residues. Greater than 5% of cysteines are reported to occupy these higher oxidation states, which effectively inactivate the corresponding thiols and alter the electronic and physical properties of modified proteins. Such higher oxidation states are reached after excessive exposure to cellular oxidants, and accumulate across different disease states. Despite widespread and functionally relevant cysteine oxidation across the proteome, there are currently no robust methods to profile higher order cysteine oxidation. Traditional data-dependent liquid chromatography/tandem mass spectrometry (LC/MS/MS) methods generally miss low-occupancy modifications in complex analyses. Here, we present a data-independent acquisition (DIA) LC/MS-based approach, leveraging the high IR absorbance of sulfoxides at 10.6 μm, for selective dissociation and discovery of S-sulfonated peptides. Across peptide standards and protein digests, we demonstrate selective infrared multiphoton dissociation (IRMPD) of S-sulfonated peptides in the background of unmodified peptides. This selective DIA IRMPD LC/MS-based approach allows identification and annotation of S-sulfonated peptides across complex mixtures while providing sufficient sequence information to localize the modification site.

SITS Derivatization of Peptides to Enhance 266 nm Ultraviolet Photodissociation (UVPD)

N-terminal derivatization of peptides with the chromogenic reagent 4-acetamido-4-isothiocyanatostilbene-2,2-disulfonic acid (SITS) is demonstrated to enhance the efficiency of 266 nm ultraviolet photodissociation (UVPD). Attachment of the chromophore results in a mass shift of 454 Da and provides significant gains in the number and abundances of diagnostic fragment ions upon UVPD. Activation of SITS-tagged peptides with 266 nm UVPD leads to many fragment ions akin to the a/b/y ions commonly produced by CID, along with other sequence ions (c, x, and z) typically accessed through higher energy pathways. Extreme bias towards C-terminal fragment ions is observed upon activation of SITS-tagged peptides using multiple 266 nm laser pulses. Due to the high reaction efficiency of the isothiocyanate coupling to the N-terminus of peptides, we demonstrate the ability to adapt this strategy to a high-throughput LC-MS/MS workflow with 266 nm UVPD. Graphical Abstract ᅟ.

Mining the fecal proteome: from biomarkers to personalised medicine

INTRODUCTION

Fecal proteomics has gained increased prominence in recent years. It can provide insights into the diagnosis and surveillance of many bowel diseases by both identifying potential biomarkers in stool samples and helping identify disease-related pathways. Fecal proteomics has already shown its potential for the discovery and validation of biomarkers for colorectal cancer screening, and the analysis of fecal microbiota by MALDI-MS for the diagnosis of a range of bowel diseases is gaining clinical acceptance. Areas covered: Based on a comprehensive analysis of the current literature, we introduce the range of sensitive and specific proteomics methods which comprise the current 'Proteomics Toolbox', explain how the integration of fecal proteomics with data processing/bioinformatics has been used for the identification of potential biomarkers for both CRC and other gut-related pathologies and analysis of the fecal microbiome, outline some of the current fecal assays in current clinical practice and introduce the concept of personalised medicine which these technologies will help inform. Expert commentary: Integration of fecal proteomics with other proteomics and genomics strategies as well as bioinformatics is paving the way towards personalised medicine, which will bring with it improved global healthcare.

Comprehensive de Novo Peptide Sequencing from MS/MS Pairs Generated through Complementary Collision Induced Dissociation and 351 nm Ultraviolet Photodissociation

We describe a strategy for de novo peptide sequencing based on matched pairs of tandem mass spectra (MS/MS) obtained by collision induced dissociation (CID) and 351 nm ultraviolet photodissociation (UVPD). Each precursor ion is isolated twice with the mass spectrometer switching between CID and UVPD activation modes to obtain a complementary MS/MS pair. To interpret these paired spectra, we modified the UVnovo de novo sequencing software to automatically learn from and interpret fragmentation spectra, provided a representative set of training data. This machine learning procedure, using random forests, synthesizes information from one or multiple complementary spectra, such as the CID/UVPD pairs, into peptide fragmentation site predictions. In doing so, the burden of fragmentation model definition shifts from programmer to machine and opens up the model parameter space for inclusion of nonobvious features and interactions. This spectral synthesis also serves to transform distinct types of spectra into a common representation for subsequent activation-independent processing steps. Then, independent from precursor activation constraints, UVnovo's de novo sequencing procedure generates and scores sequence candidates for each precursor. We demonstrate the combined experimental and computational approach for de novo sequencing using whole cell E. coli lysate. In benchmarks on the CID/UVPD data, UVnovo assigned correct full-length sequences to 83% of the spectral pairs of doubly charged ions with high-confidence database identifications. Considering only top-ranked de novo predictions, 70% of the pairs were deciphered correctly. This de novo sequencing performance exceeds that of PEAKS and PepNovo on the CID spectra and that of UVnovo on CID or UVPD spectra alone. As presented here, the methods for paired CID/UVPD spectral acquisition and interpretation constitute a powerful workflow for high-throughput and accurate de novo peptide sequencing.

Metaproteomic strategies and applications for gut microbial research

The human intestine hosts various complex microbial communities that are closely associated with multiple health and disease processes. Determining the composition and function of these microbial communities is critical to unveil disease mechanisms and promote human health. Recently, meta-omic strategies have been developed that use high-throughput techniques to provide a wealth of information, thus accelerating the study of gut microbes. Metaproteomics is a newly emerged analytical approach that aims to identify proteins on a large scale in complex environmental microbial communities (e.g., the gut microbiota). This review introduces the recent analytical strategies and applications of metaproteomics, with a focus on advances in gut microbiota research, including a discussion of the limitations and challenges of these approaches.

Development and application of immobilized surfactant in mass spectrometry-based proteomics

The synthesis process of Fe₃O₄@TMOS, a surfactant for the pretreatment of complex biological samples.

Evolution of a mass spectrometry-grade protease with PTM-directed specificity

Mapping posttranslational modifications (PTMs), which diversely modulate biological functions, represents a significant analytical challenge. The centerpiece technology for PTM site identification, mass spectrometry (MS), requires proteolytic cleavage in the vicinity of a PTM to yield peptides for sequencing. This requirement catalyzed our efforts to evolve MS-grade mutant PTM-directed proteases. Citrulline, a PTM implicated in epigenetic and immunological function, made an ideal first target, because citrullination eliminates arginyl tryptic sites. Bead-displayed trypsin mutant genes were translated in droplets, the mutant proteases were challenged to cleave bead-bound fluorogenic probes of citrulline-dependent proteolysis, and the resultant beads (1.3 million) were screened. The most promising mutant efficiently catalyzed citrulline-dependent peptide bond cleavage (k_cat/K_M = 6.9 × 10⁵ M^-1⋅s^-1). The resulting C-terminally citrullinated peptides generated characteristic isotopic patterns in MALDI-TOF MS, and both a fragmentation product y₁ ion corresponding to citrulline (176.1030 m/z) and diagnostic peak pairs in the extracted ion chromatograms of LC-MS/MS analysis. Using these signatures, we identified citrullination sites in protein arginine deiminase 4 (12 sites) and in fibrinogen (25 sites, two previously unknown). The unique mass spectral features of PTM-dependent proteolytic digest products promise a generalized PTM site-mapping strategy based on a toolbox of such mutant proteases, which are now accessible by laboratory evolution.

Mechanistic study of CBT-Cys click reaction and its application for identifying bioactive N-terminal cysteine peptides in amniotic fluid

CBT-Cys click condensation reaction has a high second-order reaction rate constant and has found wide applicability in recent years. However, its reaction mechanism has not been experimentally validated and its application for identifying bioactive N-terminal Cys peptides in real clinical samples has not been reported. Herein, firstly, by employing induced nanoelectrospray ionization-mass spectrometry (InESI-MS) and a home-built micro-reactor, we successfully intercepted and structurally characterized the crucial intermediate in this click reaction for the first time. With the intermediate, the proposed mechanism of this reaction was corroborated. Moreover, we also applied this MS setup to monitor the reaction in real time and obtained the second-order reaction rate constants of this reaction at different pH values. After mechanistic study, we applied this click reaction for identifying bioactive N-terminal cysteine peptides in amniotic fluid (AF). Eight unique N-terminal Cys peptides in AF, three of which are located in the functional domain regions of their corresponding proteins, were identified with a false positive rate less than 1%. One of the three peptides was found able to inhibit the growth of uterine endometrial cancer HEC-1-B cells but not the endometrial normal cells via a typical apoptotic pathway. With its mechanism satisfactorily elucidated, the kinetic parameters obtained, as well as its application for fishing bioactive N-terminal Cys peptides from vast complex clinical samples, we anticipate that this CBT-Cys click reaction could be applied more widely for the facile isolation, site-specific identification, and quantification of N-terminal Cys-containing peptides in complex biological samples.

Cysteine-Selective Peptide Identification: Selenium-Based Chromophore for Selective S-Se Bond Cleavage with 266 nm Ultraviolet Photodissociation

The tremendous number of peptides identified in current bottom-up mass spectrometric workflows, although impressive for high-throughput proteomics, results in little selectivity for more targeted applications. We describe a strategy for cysteine-selective proteomics based on a tagging method that installs a S-Se bond in peptides that is cleavable upon 266 nm ultraviolet photodissociation (UVPD). The alkylating reagent, N-(phenylseleno)phthalimide (NPSP), reacts with free thiols in cysteine residues and attaches a chromogenic benzeneselenol (SePh) group. Upon irradiation of tagged peptides with 266 nm photons, the S-Se bond is selectively cleaved, releasing a benzeneselenol moiety corresponding to a neutral loss of 156 Da per cysteine. Herein we demonstrate a new MS/MS scan mode, UVPDnLossCID, which facilitates selective screening of cysteine-containing peptides. A "prescreening" event occurs by activation of the top N peptide ions by 266 nm UVPD. Peptides exhibiting a neutral loss corresponding to one or more SePh groups are reactivated and sequenced by CID. Because of the low frequency of cysteine in the proteome, unique cysteine-containing peptides may serve as surrogates for entire proteins. UVPDnLossCID does not generate as many peptide spectrum matches (PSMs) as conventional bottom-up methods; however, UVPDnLossCID provides far greater selectivity.

MetaPro-IQ: a universal metaproteomic approach to studying human and mouse gut microbiota

BACKGROUND

The gut microbiota has been shown to be closely associated with human health and disease. While next-generation sequencing can be readily used to profile the microbiota taxonomy and metabolic potential, metaproteomics is better suited for deciphering microbial biological activities. However, the application of gut metaproteomics has largely been limited due to the low efficiency of protein identification. Thus, a high-performance and easy-to-implement gut metaproteomic approach is required.

RESULTS

In this study, we developed a high-performance and universal workflow for gut metaproteome identification and quantification (named MetaPro-IQ) by using the close-to-complete human or mouse gut microbial gene catalog as database and an iterative database search strategy. An average of 38 and 33 % of the acquired tandem mass spectrometry (MS) spectra was confidently identified for the studied mouse stool and human mucosal-luminal interface samples, respectively. In total, we accurately quantified 30,749 protein groups for the mouse metaproteome and 19,011 protein groups for the human metaproteome. Moreover, the MetaPro-IQ approach enabled comparable identifications with the matched metagenome database search strategy that is widely used but needs prior metagenomic sequencing. The response of gut microbiota to high-fat diet in mice was then assessed, which showed distinct metaproteome patterns for high-fat-fed mice and identified 849 proteins as significant responders to high-fat feeding in comparison to low-fat feeding.

CONCLUSIONS

We present MetaPro-IQ, a metaproteomic approach for highly efficient intestinal microbial protein identification and quantification, which functions as a universal workflow for metaproteomic studies, and will thus facilitate the application of metaproteomics for better understanding the functions of gut microbiota in health and disease.

In Vitro Metabolic Labeling of Intestinal Microbiota for Quantitative Metaproteomics

Intestinal microbiota is emerging as one of the key environmental factors influencing or causing the development of numerous human diseases. Metaproteomics can provide invaluable information on the functional activities of intestinal microbiota and on host-microbe interactions as well. However, the application of metaproteomics in human microbiota studies is still largely limited, in part due to the lack of accurate quantitative intestinal metaproteomic methods. Most current metaproteomic microbiota studies are based on label-free quantification, which may suffer from variability during the separate sample processing and mass spectrometry runs. In this study, we describe a quantitative metaproteomic strategy, using in vitro stable isotopically ((15)N) labeled microbiota as a spike-in reference, to study the intestinal metaproteomes. We showed that the human microbiota were efficiently labeled (>95% (15)N enrichment) within 3 days under in vitro conditions, and accurate light-to-heavy protein/peptide ratio measurements were obtained using a high-resolution mass spectrometer and the quantitative proteomic software tool Census. We subsequently employed our approach to study the in vitro modulating effects of fructo-oligosaccharide and five different monosaccharides on the microbiota. Our methodology improves the accuracy of quantitative intestinal metaproteomics, which would promote the application of proteomics for functional studies of intestinal microbiota.