Relative quantification of proteins in human cerebrospinal fluids by MS/MS using 6-plex isobaric tags

Deciphering Cancer Complexity: Integrative Proteogenomics and Proteomics Approaches for Biomarker Discovery

Proteomics has revolutionized the field of cancer biology because the use of a large number of in vivo (SILAC), in vitro (iTRAQ, ICAT, TMT, stable-isotope Dimethyl, and 18O) labeling techniques or label-free methods (spectral counting or peak intensities) coupled with mass spectrometry enables us to profile and identify dysregulated proteins in diseases such as cancer. These proteome and genome studies have led to many challenges, such as the lack of consistency or correlation between copy numbers, RNA, and protein-level data. This review covers solely mass spectrometry-based approaches used for cancer biomarker discovery. It also touches on the emerging role of oncoproteogenomics or proteogenomics in cancer biomarker discovery and how this new area is attracting the integration of genomics and proteomics areas to address some of the important questions to help impinge on the biology and pathophysiology of different malignancies to make these mass spectrometry-based studies more realistic and relevant to clinical settings.

Achieving a 35-Plex Tandem Mass Tag Reagent Set through Deuterium Incorporation

Mass spectrometry-based sample multiplexing with isobaric tags permits the development of high-throughput and precise quantitative biological assays with proteome-wide coverage and minimal missing values. Here, we nearly doubled the multiplexing capability of the TMTpro reagent set to a 35-plex through the incorporation of one deuterium isotope into the reporter group. Substituting deuterium frequently results in suboptimal peak coelution, which can compromise the accuracy of reporter ion-based quantification. To counteract the deuterium effect on quantitation, we implemented a strategy that necessitated the segregation of nondeuterium and deuterium-containing channels into distinct subplexes during normalization procedures, with reassembly through a common bridge channel. This multiplexing strategy of "design independent sub-plexes but acquire together" (DISAT) was used to compare protein expression differences between human cell lines and in a cysteine-profiling (i.e., chemoproteomics) experiment to identify compounds binding to cysteine-113 of Pin1.

Characterizing protein-protein interactions with thermal proteome profiling

Thermal proteome profiling (TPP) is an innovative technique that uses the principle of protein thermal stability to identify potential protein interaction partners. Employing quantitative mass spectrometry, TPP measures protein stability across the proteome, offering a comprehensive snapshot of protein interactions in a single experiment. When studying protein-protein interactions (PPI), TPP leverages changes in apparent protein melting temperatures to identify transient and weak interactions that most traditional PPI detection methodologies struggle to measure. This review discusses current TPP methodologies, the challenges of interpreting the resulting complex datasets, and opportunities to deepen and improve PPI networks. By advancing our grasp of intricate protein interactions, TPP promises to illuminate the molecular basis of diseases and drive the discovery of novel therapeutic targets.

Mass Spectrometry-Based Proteomics for Assessing Epitranscriptomic Regulations

Epitranscriptomics is a rapidly evolving field that explores chemical modifications in RNA and how they contribute to dynamic and reversible regulations of gene expression. These modifications, for example, N6-methyladenosine (m6A), are crucial in various RNA metabolic processes, including splicing, stability, subcellular localization, and translation efficiency of mRNAs. Mass spectrometry-based proteomics has become an indispensable tool in unraveling the complexities of epitranscriptomics, offering high-throughput, precise protein identification, and accurate quantification of differential protein expression. Over the past two decades, advances in mass spectrometry, including the improvement of high-resolution mass spectrometers and innovative sample preparation methods, have allowed researchers to perform in-depth analyses of epitranscriptomic regulations. This review focuses on the applications of bottom-up proteomics in the field of epitranscriptomics, particularly in identifying and quantifying epitranscriptomic reader, writer, and eraser (RWE) proteins and in characterizing their functions, posttranslational modifications, and interactions with other proteins. Together, by leveraging modern proteomics, researchers can gain deep insights into the intricate regulatory networks of RNA modifications, advancing fundamental biology, and fostering potential therapeutic applications.

4-plex quantitative glycoproteomics using glycan/protein-stable isotope labeling in cell culture

Alterations in glycoprotein abundance and glycan structures are closely linked to numerous diseases. The quantitative exploration of glycoproteomics is pivotal for biomarker discovery, but comprehensive analysis within biological samples remains challenging due to low abundance, complexity, and lack of universal technology. We developed a multiplex glycoproteomic approach using an LC-ESI-MS platform for direct comparison of glycoproteomic quantitation. Glycopeptides were isotopically labeled during cell culture, achieving high labeling efficiency (≥ 95 %) for both glycans and peptides. Quantitation was validated by mixing the same cell line in a 1:1:1:1 ratio, with mathematical correction applied to deconvolute the ratios. This method proved reliable and was applied to a comparative glycoproteomic study of three breast cancer cell lines (HTB22, MDA-MB-231, MDA-MB-231BR) and one brain cancer cell line (CRL-1620), quantifying glycopeptides from three replicates. The expression of glycopeptides was relatively quantified, and up/down-regulation between cell lines was investigated. This approach provided insights into glycosylation microheterogeneity, crucial for breast cancer brain metastasis research. Benefits include eliminating fluctuations from nano electrospray ionization and reducing analysis time, enabling up to 4-plex profiling in a single injection. Metabolic labeling introduced mass differences at the MS1 level, ensuring increased sensitivity and higher resolution for accurate quantitation. SIGNIFICANCE: Alternations in glycoprotein abundance, changes in glycosylation levels, and variations in glycan structures are closely linked to numerous diseases. The quantitative exploration of glycoproteomics has emerged as a popular area of research for biomarker discovery. However, conducting a comprehensive quantitative analysis of the glycoproteome within biological samples remains challenging due to low abundance, inherent complexities, and the absence of universal quantitative technology. Here, we developed a multiplex glycoproteomic approach using an LC-ESI-MS platform to facilitate direct comparison of glycoproteomic quantitation and enhance throughput. This approach offers benefits such as eliminating quantitative fluctuations arising from nano electrospray ionization (ESI) and reducing analysis time, enabling up to 4-plex glycoproteomic profiling in a single injection. Glycopeptides were stable isotopic labeled during cell culture procedure, attaching to monosaccharides, amino acids, or both. We achieved a high labeling efficiency (≥ 95 %) for both glycans and peptides. Quantitation validation was tested on glycopeptides by mixing the same cell line with 1:1:1:1 ratio. Due to the overlapped isotopes, a mathematical correction was applied to deconvolute the ratio of 4-plex glycopeptides. This method demonstrated quantitative reliability and was successfully applied to a comparative glycoproteomic study of three breast cancer cells (HTB22, MDA-MB-231, and MDA-MB-231BR) and one brain cancer cell (CRL-1620), identifying a total of 264 glycopeptides from three replicates. The expression of glycopeptides among these four cells was relatively quantified and up/down-regulation between two cell lines was investigated. The exploration of glycosylation microheterogeneity through glycopeptide quantification may offer valuable insights for further investigation into breast cancer brain metastasis. Conclusion: The primary advantage of our presented work lies in the multiplexing offered by combining two established labeling techniques, SILAC and IDAWG, both of which have been effectively used and widely cited in the scientific community. This combination enhances the applicability and accuracy of our method, as demonstrated by the extensive citations and successful use of these techniques independently. We believe that this multiplexing approach significantly advances the field, despite the method's current limitation to cell systems.

Proteomic analysis reveals the antiviral effects of baicalin on pseudorabies virus

Pseudorabies virus (PRV) poses a significant threat to livestock and even humans. Baicalin, a bioactive flavonoid glycoside with medicinal potential, has been reported to have various biological activities. However, its inhibitory effect on PRV remains poorly understood. In this study, we proved that baicalin effectively inhibits PRV infection. Proteomic analysis revealed that baicalin reduces the expression of 14 viral proteins, which are associated with virus replication, release and immune evasion. Furthermore, the abundance of 116 host proteins was altered by PRV infection, but restored to normal levels after treatment with baicalin. Pathway analysis indicated that baicalin mitigates reactive oxygen species (ROS) and suppresses abnormal mitochondrion by reducing the expression of NFU1 iron‑sulfur cluster scaffold homolog (NFU1) protein induced by PRV. Notably, baicalin also activates the complete coagulation cascade by increasing the expression of coagulation factor III (F3) protein and enhances nucleoplasm by upregulating the expression of solute carrier family 3 member 2 (SLC3A2) and CCAAT enhancer binding protein beta (CEBPB) proteins, contributing to its inhibitory effects on PRV. Our findings implied that baicalin has the potential to be developed as an anti-PRV drug and provide insights into the underlying molecular basis.

Conjugation of primary amine groups in targeted proteomics

Primary amines, in the form of unmodified N-terminus of peptide/protein and unmodified lysine residue, are perhaps the most important functional groups that can serve as the starting points in proteomic analysis, especially via mass spectrometry-based approaches. A variety of multifunctional probes that conjugate primary amine groups through covalent bonds have been developed and employed to facilitate protein/protein complex characterization, including identification, quantification, structure and localization elucidation, protein-protein interaction investigation, and so forth. As an integral part of more accurate peptide quantification in targeted proteomics, isobaric stable isotope-coded primary amine labeling approaches eventually facilitated protein/peptide characterization at the single-cell level, paving the way for single-cell proteomics. The development and advances in the field can be reviewed in terms of key components of a multifunctional probe: functional groups and chemistry for primary amine conjugation; hetero-bifunctional moiety for separation/enrichment of conjugated protein/protein complex; and functionalized linker/spacer. Perspectives are primarily focused on optimizing primary amine conjugation under physiological conditions to improve characterization of native proteins, especially those associated with the surface of living cells/microorganisms.

Mass spectrometry-based proteomics to study mutants and interactomes of mitochondrial translocation proteins

The multiple functions of mitochondria are governed by their proteome comprising 1000-1500 proteins depending on the organism. However, only few proteins are synthesized inside mitochondria, whereas most are "born" outside mitochondria. To reach their destined location, these mitochondrial proteins follow specific import routes established by a mitochondrial translocase network. A detailed understanding of the role and interplay of the different translocases is imperative to understand mitochondrial biology and how mitochondria are integrated into the cellular network. Mass spectrometry (MS) proved to be effective to study the translocase network regarding composition, functions, interplay, and cellular responses evoked by dysfunction. In this chapter, we provide protocols tailored to MS-enabled functional analysis of mutants and interactomes of mitochondrial translocation proteins. In the first part, we exemplify the MS-based proteomics analysis of translocation mutants for delineating the human mitochondrial importome following depletion of the central translocation protein TOMM40. The protocol comprises metabolic stable isotope labeling, TOMM40 knockdown, preparation of mitochondrial fractions, and sample preparation for liquid chromatography (LC)-MS. For deep MS analysis, prefractionation of peptide mixtures by high pH reversed-phase LC is described. In the second part, we outline an affinity purification MS approach to reveal the association of an orphaned protein with the translocase TIM23. The protocol covers FLAG-tag affinity purification of protein complexes from mitochondrial fractions and downstream sample preparation for interactome analysis. In the last unifying part, we describe methods for LC-MS, data processing, statistical analysis and visualization of quantitative MS data, and provide a Python code for effective, customizable analysis.

A Tutorial Review of Labeling Methods in Mass Spectrometry-Based Quantitative Proteomics

Recent advancements in mass spectrometry (MS) have revolutionized quantitative proteomics, with multiplex isotope labeling emerging as a key strategy for enhancing accuracy, precision, and throughput. This tutorial review offers a comprehensive overview of multiplex isotope labeling techniques, including precursor-based, mass defect-based, reporter ion-based, and hybrid labeling methods. It details their fundamental principles, advantages, and inherent limitations along with strategies to mitigate the limitation of ratio-distortion. This review will also cover the applications and latest progress in these labeling techniques across various domains, including cancer biomarker discovery, neuroproteomics, post-translational modification analysis, cross-linking MS, and single-cell proteomics. This Review aims to provide guidance for researchers on selecting appropriate methods for their specific goals while also highlighting the potential future directions in this rapidly evolving field.

6-Plex Tandem Phosphorus Tags (TPT) for Accurate Quantitative Proteomics

Isobaric chemical labeling is a widely used strategy for high-throughput quantitative proteomics based on mass spectrometry. However, commercially available reagents have high costs in applications as well as the sensitivity limitations for detection of the trace protein samples. Previously, we developed a 2-plex isobaric labeling strategy based on phosphorus chemistry for ultrasensitive proteome quantification with high accuracy. In this work, 6-plex tandem phosphorus tags (TPT) were developed with 3-fold increase in the multiplexing quantitative capacity compared to the 2-plex isobaric phosphorus reagents introduced previously. High isotope enrichment of 18O labeling was incorporated into the phosphoryl group with three exchangeable oxygen atoms by using commercially available H218O. The combinational incorporations of 18O atom in reporter ions and balance group set up the low-cost foundation for development of multiplex TPT reagents. The novel 6-plex TPT reagents could produce phosphoramidate as unique reporter ions with approximately 1 Da mass difference and thus enable 6-plex quantitative analysis in high-resolution ESI-MS/MS analysis. Using HeLa cell tryptic peptides, we concluded that 6-plex TPT reagents could facilitate large-scale accurate quantitative proteomics with very high labeling efficiency.

PCAS: An Integrated Tool for Multi-Dimensional Cancer Research Utilizing Clinical Proteomic Tumor Analysis Consortium Data

Proteomics offers a robust method for quantifying proteins and elucidating their roles in cellular functions, surpassing the insights provided by transcriptomics. The Clinical Proteomic Tumor Analysis Consortium database, enriched with comprehensive cancer proteomics data including phosphorylation and ubiquitination profiles, alongside transcriptomics data from the Genomic Data Commons, allow for integrative molecular studies of cancer. The ProteoCancer Analysis Suite (PCAS), our newly developed R package and Shinyapp, leverages these resources to facilitate in-depth analyses of proteomics, phosphoproteomics, and transcriptomics, enhancing our understanding of the tumor microenvironment through features like immune infiltration and drug sensitivity analysis. This tool aids in identifying critical signaling pathways and therapeutic targets, particularly through its detailed phosphoproteomic analysis. To demonstrate the functionality of the PCAS, we conducted an analysis of GAPDH across multiple cancer types, revealing a significant upregulation of protein levels, which is consistent with its important biological and clinical significance in tumors, as indicated in our prior research. Further experiments were used to validate the findings performed using the tool. In conclusion, the PCAS is a powerful and valuable tool for conducting comprehensive proteomic analyses, significantly enhancing our ability to uncover oncogenic mechanisms and identify potential therapeutic targets in cancer research.

Revealing the Arabidopsis AtGRP7 mRNA binding proteome by specific enhanced RNA interactome capture

BACKGROUND

The interaction of proteins with RNA in the cell is crucial to orchestrate all steps of RNA processing. RNA interactome capture (RIC) techniques have been implemented to catalogue RNA- binding proteins in the cell. In RIC, RNA-protein complexes are stabilized by UV crosslinking in vivo. Polyadenylated RNAs and associated proteins are pulled down from cell lysates using oligo(dT) beads and the RNA-binding proteome is identified by quantitative mass spectrometry. However, insights into the RNA-binding proteome of a single RNA that would yield mechanistic information on how RNA expression patterns are orchestrated, are scarce.

RESULTS

Here, we explored RIC in Arabidopsis to identify proteins interacting with a single mRNA, using the circadian clock-regulated Arabidopsis thaliana GLYCINE-RICH RNA-BINDING PROTEIN 7 (AtGRP7) transcript, one of the most abundant transcripts in Arabidopsis, as a showcase. Seedlings were treated with UV light to covalently crosslink RNA and proteins. The AtGRP7 transcript was captured from cell lysates with antisense oligonucleotides directed against the 5'untranslated region (UTR). The efficiency of RNA capture was greatly improved by using locked nucleic acid (LNA)/DNA oligonucleotides, as done in the enhanced RIC protocol. Furthermore, performing a tandem capture with two rounds of pulldown with the 5'UTR oligonucleotide increased the yield. In total, we identified 356 proteins enriched relative to a pulldown from atgrp7 mutant plants. These were benchmarked against proteins pulled down from nuclear lysates by AtGRP7 in vitro transcripts immobilized on beads. Among the proteins validated by in vitro interaction we found the family of Acetylation Lowers Binding Affinity (ALBA) proteins. Interaction of ALBA4 with the AtGRP7 RNA was independently validated via individual-nucleotide resolution crosslinking and immunoprecipitation (iCLIP). The expression of the AtGRP7 transcript in an alba loss-of-function mutant was slightly changed compared to wild-type, demonstrating the functional relevance of the interaction.

CONCLUSION

We adapted specific RNA interactome capture with LNA/DNA oligonucleotides for use in plants using AtGRP7 as a showcase. We anticipate that with further optimization and up scaling the protocol should be applicable for less abundant transcripts.

Proteomic Profiling of Messenger Ribonucleoproteins in Mouse Tissues Based on Formaldehyde Cross-Linking

Messenger ribonucleoprotein particles (mRNPs) are vital for tissue-specific gene expression via mediating posttranscriptional regulations. However, proteomic profiling of proteins in mRNPs, i.e., mRNA-associated proteins (mRAPs), has been challenging at the tissue level. Herein, we report the development of formaldehyde cross-linking-based mRNA-associated protein profiling (FAXRAP), a chemical strategy that enables the identification of mRAPs in both cultured cells and intact mouse organs. Applying FAXRAP, tissue-specific mRAPs were systematically profiled in the mouse liver, kidney, heart, and brain. Furthermore, brain mRAPs in Parkinson's disease (PD) mouse model were investigated, which revealed a global decrease of mRNP assembly in the brain of mice with PD. We envision that FAXRAP will facilitate uncovering the posttranscriptional regulation networks in various biological systems.

Macromolecular crowding in human tenocyte and skin fibroblast cultures: A comparative analysis

Although human tenocytes and dermal fibroblasts have shown promise in tendon engineering, no tissue engineered medicine has been developed due to the prolonged ex vivo time required to develop an implantable device. Considering that macromolecular crowding has the potential to substantially accelerate the development of functional tissue facsimiles, herein we compared human tenocyte and dermal fibroblast behaviour under standard and macromolecular crowding conditions to inform future studies in tendon engineering. Basic cell function analysis made apparent the innocuousness of macromolecular crowding for both cell types. Gene expression analysis of the without macromolecular crowding groups revealed expression of tendon related molecules in human dermal fibroblasts and tenocytes. Protein electrophoresis and immunocytochemistry analyses showed significantly increased and similar deposition of collagen fibres by macromolecular crowding in the two cell types. Proteomics analysis demonstrated great similarities between human tenocyte and dermal fibroblast cultures, as well as the induction of haemostatic, anti-microbial and tissue-protective proteins by macromolecular crowding in both cell populations. Collectively, these data rationalise the use of either human dermal fibroblasts or tenocytes in combination with macromolecular crowding in tendon engineering.

SHIFTR enables the unbiased identification of proteins bound to specific RNA regions in live cells

RNA-protein interactions determine the cellular fate of RNA and are central to regulating gene expression outcomes in health and disease. To date, no method exists that is able to identify proteins that interact with specific regions within endogenous RNAs in live cells. Here, we develop SHIFTR (Selective RNase H-mediated interactome framing for target RNA regions), an efficient and scalable approach to identify proteins bound to selected regions within endogenous RNAs using mass spectrometry. Compared to state-of-the-art techniques, SHIFTR is superior in accuracy, captures minimal background interactions and requires orders of magnitude lower input material. We establish SHIFTR workflows for targeting RNA classes of different length and abundance, including short and long non-coding RNAs, as well as mRNAs and demonstrate that SHIFTR is compatible with sequentially mapping interactomes for multiple target RNAs in a single experiment. Using SHIFTR, we comprehensively identify interactions of cis-regulatory elements located at the 5' and 3'-terminal regions of authentic SARS-CoV-2 RNAs in infected cells and accurately recover known and novel interactions linked to the function of these viral RNA elements. SHIFTR enables the systematic mapping of region-resolved RNA interactomes for any RNA in any cell type and has the potential to revolutionize our understanding of transcriptomes and their regulation.

Specialized replication mechanisms maintain genome stability at human centromeres

The high incidence of whole-arm chromosome aneuploidy and translocations in tumors suggests instability of centromeres, unique loci built on repetitive sequences and essential for chromosome separation. The causes behind this fragility and the mechanisms preserving centromere integrity remain elusive. We show that replication stress, hallmark of pre-cancerous lesions, promotes centromeric breakage in mitosis, due to spindle forces and endonuclease activities. Mechanistically, we unveil unique dynamics of the centromeric replisome distinct from the rest of the genome. Locus-specific proteomics identifies specialized DNA replication and repair proteins at centromeres, highlighting them as difficult-to-replicate regions. The translesion synthesis pathway, along with other factors, acts to sustain centromere replication and integrity. Prolonged stress causes centromeric alterations like ruptures and translocations, as observed in ovarian cancer models experiencing replication stress. This study provides unprecedented insights into centromere replication and integrity, proposing mechanistic insights into the origins of centromere alterations leading to abnormal cancerous karyotypes.

Potential Protein Signatures for Recurrence Prediction of Ischemic Stroke

BACKGROUND

Acute ischemic stroke is a major cause of mortality and disability worldwide, with approximately 7.4% to 7.7% recurrence within the first 3 months. This study aimed to identify potential biomarkers for predicting stroke recurrence.

METHODS AND RESULTS

We conducted a nested case-control study using a hospital-based cohort from the Third China National Stroke Registry selecting 214 age- and sex-matched patients with ischemic stroke with hypertension and no history of diabetes or heart disease. Using data-independent acquisition for discovery and multiple reaction monitoring for quantitative validation, we identified 26 differentially expressed proteins in large-artery atherosclerosis (Causative Classification of Ischemic Stroke [CCS]1), 16 in small-artery occlusion (CCS3), and 25 in undetermined causes (CCS5) among patients with recurrent stroke. In the CCS1 and CCS3 subgroups, differentially expressed proteins were associated with platelet aggregation, neuronal death/cerebroprotection, and immune response, whereas differentially expressed proteins in the CCS5 subgroup were linked to altered metabolic functions. Validated recurrence predictors included proteins associated with neutrophil activity and vascular inflammation (TAGLN2 [transgelin 2], ITGAM [integrin subunit α M]/TAGLN2 ratio, ITGAM/MYL9 [myosin light chain 9] ratio, TAGLN2/RSU1 [Ras suppressor protein 1] ratio) in the CCS3 subgroup and proteins associated with endothelial plasticity and blood-brain barrier integrity (ITGAM/MYL9 ratio and COL1A2 [collagen type I α 2 chain]/MYL9 ratio) in the CCS3 and CCS5 subgroups, respectively.

CONCLUSIONS

These findings provide a foundation for developing a blood-based biomarker panel, using causative classifications, which may be used in routine clinical practice to predict stroke recurrence.

102-Plex Approach for Accurate and Multiplexed Proteome Quantification

Hyperplexing approaches have been aimed to meet the demand for large-scale proteomic analyses. Currently, the analysis capacity has expanded to up to 54 samples within a single experiment by utilizing different isotopic and isobaric reagent combinations. In this report, we propose a super multiplexed approach to enable the analysis of up to 102 samples in a single experiment, by the combination of our recently developed TAG-TMTpro and TAG-IBT16 labeling. We systematically investigated the identification and quantification performance of the 102-plex approach using the mixtures of E. coli and HeLa peptides. Our results revealed that all labeling series demonstrated accurate and reliable quantification performance. The combination of TAG-IBT16 and TAG-TMTpro approaches expands the multiplexing capacity to 102 plexes, providing a more multiplexed quantification method for even larger-scale proteomic analysis. Data are available via ProteomeXchange with the identifier PXD042398.

Efflux pump Rv1258c activates novel functions of the oxidative stress and via the VII secretion system ESX-3-mediated iron metabolic pathway in Mycobacterium tuberculosis

Oxidative stress and iron metabolism are essential for Mycobacterium tuberculosis (M.tb) survival in host cells. The efflux pump Rv1258c belongs to the major facilitator superfamily (MFS) and can actively pump drugs to promote certain drug resistance in M.tb. In this study, we compared H37RvΔRv1258c with wild-type (WT) M.tb H37Rv. The qRT-PCR results suggested that Rv1258c is potentially involved in the iron metabolic pathway by regulating the expression of ESX-3, which is required for iron uptake. Protein-Protein Affinity Predictor (PPA-Pred2) and the artificial intelligence program AlphaFold 2 were used for prediction and showed that Rv1258c has direct interactions with PPE4 and EccD3 but weak interactions with EccB3. This was further determined via protein-protein interaction analysis of the yeast two-hybrid expression system. By comparing mutant H37RvΔRv1258c strains with WT strains, we discovered that the absence of Rv1258c led to elevated intracellular H+ potential and NAD+/NADH ratios in M.tb, thereby resulting in oxidative stress. We hypothesize that the efflux pump Rv1258c not only has the function of regulating drug resistance in M.tb but also has a novel function in activating oxidative stress and regulating ESX-3-associated iron metabolism in M.tb.

Quantitative Peptidomics: General Considerations

Peptidomics is the detection and identification of the peptides present in a sample, and quantitative peptidomics provides additional information about the amounts of these peptides. It is possible to perform absolute quantitation of peptide levels in which the biological sample is compared to synthetic standards of each peptide. More commonly, relative quantitation is performed to compare peptide levels between two or more samples. Relative quantitation can measure differences between all peptides that are detectable, which can exceed 1000 peptides in a complex sample. In this chapter, various techniques used for quantitative peptidomics are described along with discussion of the advantages and disadvantages of each approach. A guide to selecting the optimal quantitative approach is provided, based on the goals of the experiment and the resources that are available.

USP7/Maged1-mediated H2A monoubiquitination in the paraventricular thalamus: an epigenetic mechanism involved in cocaine use disorder

The risk of developing drug addiction is strongly influenced by the epigenetic landscape and chromatin remodeling. While histone modifications such as methylation and acetylation have been studied in the ventral tegmental area and nucleus accumbens (NAc), the role of H2A monoubiquitination remains unknown. Our investigations, initially focused on the scaffold protein melanoma-associated antigen D1 (Maged1), reveal that H2A monoubiquitination in the paraventricular thalamus (PVT) significantly contributes to cocaine-adaptive behaviors and transcriptional repression induced by cocaine. Chronic cocaine use increases H2A monoubiquitination, regulated by Maged1 and its partner USP7. Accordingly, Maged1 specific inactivation in thalamic Vglut2 neurons, or USP7 inhibition, blocks cocaine-evoked H2A monoubiquitination and cocaine locomotor sensitization. Additionally, genetic variations in MAGED1 and USP7 are linked to altered susceptibility to cocaine addiction and cocaine-associated symptoms in humans. These findings unveil an epigenetic modification in a non-canonical reward pathway of the brain and a potent marker of epigenetic risk factors for drug addiction in humans.

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.

SND1 binds SARS-CoV-2 negative-sense RNA and promotes viral RNA synthesis through NSP9

Regulation of viral RNA biogenesis is fundamental to productive SARS-CoV-2 infection. To characterize host RNA-binding proteins (RBPs) involved in this process, we biochemically identified proteins bound to genomic and subgenomic SARS-CoV-2 RNAs. We find that the host protein SND1 binds the 5' end of negative-sense viral RNA and is required for SARS-CoV-2 RNA synthesis. SND1-depleted cells form smaller replication organelles and display diminished virus growth kinetics. We discover that NSP9, a viral RBP and direct SND1 interaction partner, is covalently linked to the 5' ends of positive- and negative-sense RNAs produced during infection. These linkages occur at replication-transcription initiation sites, consistent with NSP9 priming viral RNA synthesis. Mechanistically, SND1 remodels NSP9 occupancy and alters the covalent linkage of NSP9 to initiating nucleotides in viral RNA. Our findings implicate NSP9 in the initiation of SARS-CoV-2 RNA synthesis and unravel an unsuspected role of a cellular protein in orchestrating viral RNA production.

Recent applications of quantitative mass spectrometry in biopharmaceutical process development and manufacturing

Biopharmaceutical products have seen rapid growth over the past few decades and continue to dominate the global pharmaceutical market. Aligning with the quality by design (QbD) framework and realization, recent advances in liquid chromatography-mass spectrometry (LC-MS) instrumentation and related techniques have enhanced biopharmaceutical characterization capabilities and have supported an increased development of biopharmaceutical products. Beyond its routine qualitative characterization, the quantitative feature of LC-MS has unique applications in biopharmaceutical process development and manufacturing. This review describes the recent applications and implications of the advancement of quantitative MS methods in biopharmaceutical process development, and characterization of biopharmaceutical product, product-related variants, and process-related impurities. We also provide insights on the emerging applications of quantitative MS in the lifecycle of biopharmaceutical product development including quality control in the Good Manufacturing Practice (GMP) environment and process analytical technology (PAT) practices during process development and manufacturing. Through collaboration with instrument and software vendors and regulatory agencies, we envision broader adoption of phase-appropriate quantitative MS-based methods for the analysis of biopharmaceutical products, which in turn has the potential to enable manufacture of higher quality products for patients.

Integrated omic profiling of the medicinal mushroom Inonotus obliquus under submerged conditions

BACKGROUND

The Inonotus obliquus mushroom, a wondrous fungus boasting edible and medicinal qualities, has been widely used as a folk medicine and shown to have many potential pharmacological secondary metabolites. The purpose of this study was to supply a global landscape of genome-based integrated omic analysis of the fungus under lab-growth conditions.

RESULTS

This study presented a genome with high accuracy and completeness using the Pacbio Sequel II third-generation sequencing method. The de novo assembled fungal genome was 36.13 Mb, and contained 8352 predicted protein-coding genes, of which 365 carbohydrate-active enzyme (CAZyme)-coding genes and 19 biosynthetic gene clusters (BCGs) for secondary metabolites were identified. Comparative transcriptomic and proteomic analysis revealed a global view of differential metabolic change between seed and fermentation culture, and demonstrated positive correlations between transcription and expression levels of 157 differentially expressed genes involved in the metabolism of amino acids, fatty acids, secondary metabolites, antioxidant and immune responses. Facilitated by the widely targeted metabolomic approach, a total of 307 secondary substances were identified and quantified, with a significant increase in the production of antioxidant polyphenols.

CONCLUSION

This study provided the comprehensive analysis of the fungus Inonotus obliquus, and supplied fundamental information for further screening of promising target metabolites and exploring the link between the genome and metabolites.

Mapping protein-exopolysaccharide binding interaction in Staphylococcus epidermidis biofilms by live cell proximity labeling

Bacterial biofilms consist of cells encased in an extracellular polymeric substance (EPS) composed of exopolysaccharides, extracellular DNA, and proteins that are critical for cell-cell adhesion and protect the cells from environmental stress, antibiotic treatments, and the host immune response. Degrading EPS components or blocking their production have emerged as promising strategies for prevention or dispersal of bacterial biofilms, but we still have little information about the specific biomolecular interactions that occur between cells and EPS components and how those interactions contribute to biofilm production. Staphylococcus epidermidis is a leading cause of nosocomial infections as a result of producing biofilms that use the exopolysaccharide poly-(1→6)-β-N-acetylglucosamine (PNAG) as a major structural component. In this study, we have developed a live cell proximity labeling approach combined with quantitative mass spectrometry-based proteomics to map the PNAG interactome of live S. epidermidis biofilms. Through these measurements we discovered elastin-binding protein (EbpS) as a major PNAG-interacting protein. Using live cell binding measurements, we found that the lysin motif (LysM) domain of EbpS specifically binds to PNAG present in S. epidermidis biofilms. Our work provides a novel method for the rapid identification of exopolysaccharide-binding proteins in live biofilms that will help to extend our understanding of the biomolecular interactions that are required for bacterial biofilm formation.

Ultrasensitive proteomics depicted an in-depth landscape for the very early stage of mouse maternal-to-zygotic transition

Single-cell or low-input multi-omics techniques have revolutionized the study of pre-implantation embryo development. However, the single-cell or low-input proteomic research in this field is relatively underdeveloped because of the higher threshold of the starting material for mammalian embryo samples and the lack of hypersensitive proteome technology. In this study, a comprehensive solution of ultrasensitive proteome technology (CS-UPT) was developed for single-cell or low-input mouse oocyte/embryo samples. The deep coverage and high-throughput routes significantly reduced the starting material and were selected by investigators based on their demands. Using the deep coverage route, we provided the first large-scale snapshot of the very early stage of mouse maternal-to-zygotic transition, including almost 5,500 protein groups from 20 mouse oocytes or zygotes for each sample. Moreover, significant protein regulatory networks centered on transcription factors and kinases between the MII oocyte and 1-cell embryo provided rich insights into minor zygotic genome activation.

Investigation of targets and anticancer mechanisms of covalently acting natural products by functional proteomics

Eriocalyxin B (EB), 17-hydroxy-jolkinolide B (HJB), parthenolide (PN), xanthatin (XT) and andrographolide (AG) are terpenoid natural products with a variety of promising antitumor activities, which commonly bear electrophilic groups (α,β-unsaturated carbonyl groups and/or epoxides) capable of covalently modifying protein cysteine residues. However, their direct targets and underlying molecular mechanisms are still largely unclear, which limits the development of these compounds. In this study, we integrated activity-based protein profiling (ABPP) and quantitative proteomics approach to systematically characterize the covalent targets of these natural products and their involved cellular pathways. We first demonstrated the anti-proliferation activities of these five compounds in triple-negative breast cancer cell MDA-MB-231. Tandem mass tag (TMT)-based quantitative proteomics showed all five compounds commonly affected the ubiquitin mediated proteolysis pathways. ABPP platform identified the preferentially modified targets of EB and PN, two natural products with high anti-proliferation activity. Biochemical experiments showed that PN inhibited the cell proliferation through targeting ubiquitin carboxyl-terminal hydrolase 10 (USP10). Together, this study uncovered the covalently modified targets of these natural products and potential molecular mechanisms of their antitumor activities.

Parallel Proteomic Comparison of Mutants With Altered Carbon Metabolism Reveals Hik8 Regulation of PII Phosphorylation and Glycogen Accumulation in a Cyanobacterium

Carbon metabolism is central to photosynthetic organisms and involves the coordinated operation and regulation of numerous proteins. In cyanobacteria, proteins involved in carbon metabolism are regulated by multiple regulators including the RNA polymerase sigma factor SigE, the histidine kinases Hik8, Hik31 and its plasmid-borne paralog Slr6041, and the response regulator Rre37. To understand the specificity and the cross-talk of such regulations, we simultaneously and quantitatively compared the proteomes of the gene knockout mutants for the regulators. A number of proteins showing differential expression in one or more mutants were identified, including four proteins that are unanimously upregulated or downregulated in all five mutants. These represent the important nodes of the intricate and elegant regulatory network for carbon metabolism. Moreover, serine phosphorylation of PII, a key signaling protein sensing and regulating in vivo carbon/nitrogen (C/N) homeostasis through reversible phosphorylation, is massively increased with a concomitant significant decrease in glycogen content only in the hik8-knockout mutant, which also displays impaired dark viability. An unphosphorylatable PII S49A substitution restored the glycogen content and rescued the dark viability of the mutant. Together, our study not only establishes the quantitative relationship between the targets and the corresponding regulators and elucidated their specificity and cross-talk but also unveils that Hik8 regulates glycogen accumulation through negative regulation of PII phosphorylation, providing the first line of evidence that links the two-component system with PII-mediated signal transduction and implicates them in the regulation of carbon metabolism.

Enhanced Multiplexing Technology for Proteomics

The identification of thousands of proteins and their relative levels of expression has furthered understanding of biological processes and disease and stimulated new systems biology hypotheses. Quantitative proteomics workflows that rely on analytical assays such as mass spectrometry have facilitated high-throughput measurements of proteins partially due to multiplexing. Multiplexing allows proteome differences across multiple samples to be measured simultaneously, resulting in more accurate quantitation, increased statistical robustness, reduced analysis times, and lower experimental costs. The number of samples that can be multiplexed has evolved from as few as two to more than 50, with studies involving more than 10 samples being denoted as enhanced multiplexing or hyperplexing. In this review, we give an update on emerging multiplexing proteomics techniques and highlight advantages and limitations for enhanced multiplexing strategies.

Mass spectrometry-based retina proteomics

A subfield of neuroproteomics, retina proteomics has experienced a transformative growth since its inception due to methodological advances in enabling chemical, biochemical, and molecular biology techniques. This review focuses on mass spectrometry's contributions to facilitate mammalian and avian retina proteomics to catalog and quantify retinal protein expressions, determine their posttranslational modifications, as well as its applications to study the proteome of the retina in the context of biology, health and diseases, and therapy developments.

MitoStores: chaperone-controlled protein granules store mitochondrial precursors in the cytosol

Hundreds of nucleus-encoded mitochondrial precursor proteins are synthesized in the cytosol and imported into mitochondria in a post-translational manner. However, the early processes associated with mitochondrial protein targeting remain poorly understood. Here, we show that in Saccharomyces cerevisiae, the cytosol has the capacity to transiently store mitochondrial matrix-destined precursors in dedicated deposits that we termed MitoStores. Competitive inhibition of mitochondrial protein import via clogging of import sites greatly enhances the formation of MitoStores, but they also form during physiological cell growth on nonfermentable carbon sources. MitoStores are enriched for a specific subset of nucleus-encoded mitochondrial proteins, in particular those containing N-terminal mitochondrial targeting sequences. Our results suggest that MitoStore formation suppresses the toxic potential of aberrantly accumulating mitochondrial precursor proteins and is controlled by the heat shock proteins Hsp42 and Hsp104. Thus, the cytosolic protein quality control system plays an active role during the early stages of mitochondrial protein targeting through the coordinated and localized sequestration of mitochondrial precursor proteins.

An optimized workflow for MS-based quantitative proteomics of challenging clinical bronchoalveolar lavage fluid (BALF) samples

BACKGROUND

Clinical bronchoalveolar lavage fluid (BALF) samples are rich in biomolecules, including proteins, and useful for molecular studies of lung health and disease. However, mass spectrometry (MS)-based proteomic analysis of BALF is challenged by the dynamic range of protein abundance, and potential for interfering contaminants. A robust, MS-based proteomics compatible sample preparation workflow for BALF samples, including those of small and large volume, would be useful for many researchers.

RESULTS

We have developed a workflow that combines high abundance protein depletion, protein trapping, clean-up, and in-situ tryptic digestion, that is compatible with either qualitative or quantitative MS-based proteomic analysis. The workflow includes a value-added collection of endogenous peptides for peptidomic analysis of BALF samples, if desired, as well as amenability to offline semi-preparative or microscale fractionation of complex peptide mixtures prior to LC-MS/MS analysis, for increased depth of analysis. We demonstrate the effectiveness of this workflow on BALF samples collected from COPD patients, including for smaller sample volumes of 1-5 mL that are commonly available from the clinic. We also demonstrate the repeatability of the workflow as an indicator of its utility for quantitative proteomic studies.

CONCLUSIONS

Overall, our described workflow consistently provided high quality proteins and tryptic peptides for MS analysis. It should enable researchers to apply MS-based proteomics to a wide-variety of studies focused on BALF clinical specimens.

Mass spectrometry-based high-throughput proteomics and its role in biomedical studies and systems biology

There are multiple reasons why the next generation of biological and medical studies require increasing numbers of samples. Biological systems are dynamic, and the effect of a perturbation depends on the genetic background and environment. As a consequence, many conditions need to be considered to reach generalizable conclusions. Moreover, human population and clinical studies only reach sufficient statistical power if conducted at scale and with precise measurement methods. Finally, many proteins remain without sufficient functional annotations, because they have not been systematically studied under a broad range of conditions. In this review, we discuss the latest technical developments in mass spectrometry (MS)-based proteomics that facilitate large-scale studies by fast and efficient chromatography, fast scanning mass spectrometers, data-independent acquisition (DIA), and new software. We further highlight recent studies which demonstrate how high-throughput (HT) proteomics can be applied to capture biological diversity, to annotate gene functions or to generate predictive and prognostic models for human diseases.

New Set of Isobaric Labeling Reagents for Quantitative 16Plex Proteomics

Peptide labeling by isobaric tags is a powerful approach for the relative quantitative analysis of proteomes in multiple groups. There has been a revolution in the innovation of new isobaric reagents; however, great effort is being made to expand simultaneous labeling groups to identify more labeled peptides and reduce reporter ion signal suppression. We redesigned the original chemical structure of the deuterium isobaric amine-reactive tag developed in our laboratory. We optimized the synthetic pathway to create a new set of 16-plex isobaric tags (IBT-16plex). The novel reagent enabled almost complete labeling of peptides within 90 min, with all labeling reporter ions exhibiting comparable MS/MS signals. Compared to a typical 16plex reagent, TMTpro-16plex, the peptides and proteins identified by IBT-16plex in trypsinized HeLa cells were significantly increased by 14.8 and 8.6%, respectively. Moreover, differences in peptide abundance within 10-fold among multiple groups were barely suppressed in IBT-16plex, whereas the dynamic range in TMTpro-16plex-labeled groups was smaller. After quantitative examination of MCF7 cell proteins, IBT-16plex was confirmed as feasible and useful for evaluating protein responses of glucose-starved MCF7 cells to a glucose-rich medium.

A guide to mass spectrometric analysis of extracellular vesicle proteins for biomarker discovery

Exosomes (small extracellular vesicles) in living organisms play an important role in processes such as cell proliferation or intercellular communication. Recently, exosomes have been extensively investigated for biomarker discoveries for various diseases. An important aspect of exosome analysis involves the development of enrichment methods that have been introduced for successful isolation of exosomes. These methods include ultracentrifugation, size exclusion chromatography, polyethylene glycol-based precipitation, immunoaffinity-based enrichment, ultrafiltration, and asymmetric flow field-flow fractionation among others. To confirm the presence of exosomes, various characterization methods have been utilized such as Western blot analysis, atomic force microscopy, electron microscopy, optical methods, zeta potential, visual inspection, and mass spectrometry. Recent advances in high-resolution separations, high-performance mass spectrometry and comprehensive proteome databases have all contributed to the successful analysis of exosomes from patient samples. Herein we review various exosome enrichment methods, characterization methods, and recent trends of exosome investigations using mass spectrometry-based approaches for biomarker discovery.

Chemical isotope labeling for quantitative proteomics

Advancements in liquid chromatography and mass spectrometry over the last decades have led to a significant development in mass spectrometry-based proteome quantification approaches. An increasingly attractive strategy is multiplex isotope labeling, which significantly improves the accuracy, precision and throughput of quantitative proteomics in the data-dependent acquisition mode. Isotope labeling-based approaches can be classified into MS1-based and MS2-based quantification. In this review, we give an overview of approaches based on chemical isotope labeling and discuss their principles, benefits, and limitations with the goal to give insights into fundamental questions and provide a useful reference for choosing a method for quantitative proteomics. As a perspective, we discuss the current possibilities and limitations of multiplex, isotope labeling approaches for the data-independent acquisition mode, which is increasing in popularity.

Small noncoding RNA interactome capture reveals pervasive, carbon source-dependent tRNA engagement of yeast glycolytic enzymes

Small noncoding RNAs fulfill key functions in cellular and organismal biology, typically working in concert with RNA-binding proteins (RBPs). While proteome-wide methodologies have enormously expanded the repertoire of known RBPs, these methods do not distinguish RBPs binding to small noncoding RNAs from the rest. To specifically identify this relevant subclass of RBPs, we developed small noncoding RNA interactome capture (snRIC_2C) based on the differential RNA-binding capacity of silica matrices (2C). We define the S. cerevisiae proteome of nearly 300 proteins that specifically binds to RNAs smaller than 200 nt in length (snRBPs), identifying informative distinctions from the total RNA-binding proteome determined in parallel. Strikingly, the snRBPs include most glycolytic enzymes from yeast. With further methodological developments using silica matrices, 12 tRNAs were identified as specific binders of the glycolytic enzyme GAPDH. We show that tRNA engagement of GAPDH is carbon source-dependent and regulated by the RNA polymerase III repressor Maf1, suggesting a regulatory interaction between glycolysis and RNA polymerase III activity. We conclude that snRIC_2C and other 2C-derived methods greatly facilitate the study of RBPs, revealing previously unrecognized interactions.

Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice

Proteomics continues to forge significant strides in the discovery of essential biological processes, uncovering valuable information on the identity, global protein abundance, protein modifications, proteoform levels, and signal transduction pathways. Cancer is a complicated and heterogeneous disease, and the onset and progression involve multiple dysregulated proteoforms and their downstream signaling pathways. These are modulated by various factors such as molecular, genetic, tissue, cellular, ethnic/racial, socioeconomic status, environmental, and demographic differences that vary with time. The knowledge of cancer has improved the treatment and clinical management; however, the survival rates have not increased significantly, and cancer remains a major cause of mortality. Oncoproteomics studies help to develop and validate proteomics technologies for routine application in clinical laboratories for (1) diagnostic and prognostic categorization of cancer, (2) real-time monitoring of treatment, (3) assessing drug efficacy and toxicity, (4) therapeutic modulations based on the changes with prognosis and drug resistance, and (5) personalized medication. Investigation of tumor-specific proteomic profiles in conjunction with healthy controls provides crucial information in mechanistic studies on tumorigenesis, metastasis, and drug resistance. This review provides an overview of proteomics technologies that assist the discovery of novel drug targets, biomarkers for early detection, surveillance, prognosis, drug monitoring, and tailoring therapy to the cancer patient. The information gained from such technologies has drastically improved cancer research. We further provide exemplars from recent oncoproteomics applications in the discovery of biomarkers in various cancers, drug discovery, and clinical treatment. Overall, the future of oncoproteomics holds enormous potential for translating technologies from the bench to the bedside.

Developing quantitative assays for six urinary glycoproteins using parallel reaction monitoring, data-independent acquisition, and TMT-based data-dependent acquisition

Quantitative approaches encompassing parallel reaction monitoring (PRM), data-independent acquisition (DIA), and data-dependent acquisition (DDA) are commonly used to investigate protein expression profiles. However, analytical performances of assays developed using PRM, DIA, and Tandem Mass Tag (TMT)-based DDA for quantitative proteomics have yet not been investigated. Here, we developed assays for glycopeptides identified from six glycoproteins, including Leucine-rich alpha-2-glycoprotein (LRG1), Prostaglandin-H2 D-isomerase (PTGDS), Aminopeptidase N (ANPEP), CD63 antigen (CD63), Clusterin (CLU), and Prostatic acid phosphatase (ACPP), using PRM, DDA, and DIA and evaluated the analytical performances of each assay using the different acquisition modes. We also compared assays in each acquisition mode on three different orbitrap instruments: Thermo Fisher Q Exactive, Exploris 480, and Lumos. We found that DIA showed the largest linear range, highest sensitivity, and most reproducibility. We then applied our developed DIA assays to urine samples from non-aggressive (n = 48) and aggressive (n = 35) prostate cancer patients. In conclusion, we developed assays for the six glycoproteins, evaluated the analytical performances of each assay in DIA, PRM, and PRM acquisition modes on three types of mass spectrometry instruments, and chose the DIA assays for the quantitative analysis of urine samples from patients with aggressive and non-aggressive prostate cancer.

Statistical and Computational Methods for Proteogenomic Data Analysis

Proteins are the functional molecules for almost all cellular and biological processes. They are also the targets of most drugs. Proteins employ complex, multilevel regulations, so their abundance levels do not well correlated with their mRNA expression levels. The structure, activity, and functional roles of proteins are affected by posttranslational modifications (PTM), which are even less correlated with mRNA expression levels than protein abundances. Comprehensive characterization of the proteomics data is critical for understanding the molecular and cellular mechanisms of biological systems and developing news therapeutics. Current large-scale proteomic profiling technologies, such as mass spectrometry, provide relative identification of peptides and proteins, with data vulnerable to outliers, batch effects, and nonrandom missingness. In order to perform high-quality proteomic data analysis, we will first introduce a data preprocessing and quality control pipeline that includes normalization, outlier detection and removal, batch effect identification and handling, and missing data imputation. Then, we will describe several statistical methods that leverage well-processed proteomic data to generate scientific discoveries, especially with an integration with genomics and transcriptomics. These methods cover topics like association analysis, network construction, clustering, and cell-type deconvolution. To demonstrate these methods, we will use the proteogenomic data from the lung squamous cell carcinoma study of the Clinical Proteomic Tumor Analysis Consortium and provide sample codes for data access and analyses.

Site-specific proteomic strategies to identify ubiquitin and SUMO modifications: Challenges and opportunities

Ubiquitin and SUMO modify thousands of substrates to regulate most cellular processes. System-wide identification of ubiquitin and SUMO substrates provides global understanding of their cellular functions. In this review, we discuss the biological importance of site-specific modifications by ubiquitin and SUMO regulating the DNA damage response, protein quality control and cell cycle progression. Furthermore we discuss the machinery responsible for these modifications and methods to purify and identify ubiquitin and SUMO modified sites by mass spectrometry. We provide a framework to aid in the selection of appropriate purification, digestion and acquisition strategies suited to answer different biological questions. We highlight opportunities in the field for employing innovative technologies, as well as discuss challenges and long-standing questions in the field that are difficult to address with the currently available tools, emphasizing the need for further innovation.

Serotype-dependent adhesion of Shiga toxin-producing Escherichia coli to bovine milk fat globule membrane proteins

Shiga toxin-producing Escherichia coli (STEC) are food-borne pathogens that can cause severe symptoms for humans. Raw milk products are often incriminated as vehicule for human STEC infection. However, raw milk naturally contains molecules, such as the milk fat globule membrane and associated proteins, that could inhibit pathogen adhesion by acting as mimetic ligands. This study aimed to: (i) evaluate the capability of STEC cells to adhere to bovine milk fat globule membrane proteins (MFGMPs), (ii) highlight STEC surface proteins associated with adhesion and (iii) evaluate the variation between different STEC serotypes. We evaluated the physicochemical interactions between STEC and milk fat globules (MFGs) by analyzing hydrophobic properties and measuring the ζ-potential. We used a plate adhesion assay to assess adhesion between MFGMPs and 15 Escherichia coli strains belonging to three key serotypes (O157:H7, O26:H11, and O103:H2). A relative quantitative proteomic approach was conducted by mass spectrometry to identify STEC surface proteins that may be involved in STEC-MFG adhesion. The majority of E. coli strains showed a hydrophilic profile. The ζ-potential values were between -3.7 and - 2.9 mV for the strains and between -12.2 ± 0.14 mV for MFGs. Our results suggest that non-specific interactions are not strongly involved in STEC-MFG association and that molecular bonds could form between STEC and MFGs. Plate adhesion assays showed a weak adhesion of O157:H7 E. coli strains to MFGMPs. In contrast, O26:H11 and O103:H2 serotypes attached more to MFGMPs. Relative quantitative proteomic analysis showed that the O26:H11 str. 21,765 differentially expressed five outer membrane-associated proteins or lipoproteins compared with the O157:H7 str. EDL933. This analysis also found strain-specific differentially expressed proteins, including four O26:H11 str. 21,765-specific proteins/lipoproteins and eight O103:H2 str. PMK5-specific proteins. For the first time, we demonstrated STEC adhesion to MFGMPs and discovered a serotype effect. Several outer membrane proteins-OmpC and homologous proteins, intimin, Type 1 Fimbriae, and AIDA-I-that may be involved in STEC-MFG adhesion were highlighted. More research on STEC's ability to adhere to MFGMs in diverse biological environments, such as raw milk cheeses and the human gastrointestinal tract, is needed to confirm the anti-adhesion properties of the STEC-MFG complex.

Radiation-Induced Intestinal Normal Tissue Toxicity: Implications for Altered Proteome Profile

Radiation-induced toxicity to healthy/normal intestinal tissues, especially during radiotherapy, limits the radiation dose necessary to effectively eradicate tumors of the abdomen and pelvis. Although the pathogenesis of intestinal radiation toxicity is highly complex, understanding post-irradiation alterations in protein profiles can provide crucial insights that make radiotherapy safer and more efficient and allow for increasing the radiation dose during cancer treatment. Recent preclinical and clinical studies have advanced our current understanding of the molecular changes associated with radiation-induced intestinal damage by assessing changes in protein expression with mass spectrometry-based approaches and 2-dimensional difference gel electrophoresis. Studies by various groups have demonstrated that proteins that are involved in the inflammatory response, the apoptotic pathway, reactive oxygen species scavenging, and cell proliferation can be targeted to develop effective radiation countermeasures. Moreover, altered protein profiles serve as a crucial biomarkers for intestinal radiation damage. In this review, we present alterations in protein signatures following intestinal radiation damage as detected by proteomics approaches in preclinical and clinical models with the aim of providing a better understanding of how to accomplish intestinal protection against radiation damage.

Advances in proteomic profiling of pediatric kidney diseases

Chronic kidney disease (CKD) can progress to kidney failure and require dialysis or transplantation, while early diagnosis can alter the course of disease and lead to better outcomes in both pediatric and adult patients. Significant CKD comorbidities include the manifestation of cardiovascular disease, heart failure, coronary disease, and hypertension. The pathogenesis of chronic kidney diseases can present as subtle and especially difficult to distinguish between different glomerular pathologies. Early detection of adult and pediatric CKD and detailed mechanistic understanding of the kidney damage can be helpful in delaying or curtailing disease progression via precise intervention toward diagnosis and prognosis. Clinically, serum creatinine and albumin levels can be indicative of CKD, but often are a lagging indicator only significantly affected once kidney function has severely diminished. The evolution of proteomics and mass spectrometry technologies has begun to provide a powerful research tool in defining these mechanisms and identifying novel biomarkers of CKD. Many of the same challenges and advances in proteomics apply to adult and pediatric patient populations. Additionally, proteomic analysis of adult CKD patients can be transferred directly toward advancing our knowledge of pediatric CKD as well. In this review, we highlight applications of proteomics that have yielded such biomarkers as PLA2R, SEMA3B, and other markers of membranous nephropathy as well as KIM-1, MCP-1, and NGAL in lupus nephritis among other potential diagnostic and prognostic markers. The potential for improving the clinical toolkit toward better treatment of pediatric kidney diseases is significantly aided by current and future development of proteomic applications.

Recent advances in isobaric labeling and applications in quantitative proteomics

Mass spectrometry (MS) has emerged at the forefront of quantitative proteomic techniques. Liquid chromatography-mass spectrometry (LC-MS) can be used to determine abundances of proteins and peptides in complex biological samples. Several methods have been developed and adapted for accurate quantification based on chemical isotopic labeling. Among various chemical isotopic labeling techniques, isobaric tagging approaches rely on the analysis of peptides from MS2-based quantification rather than MS1-based quantification. In this review, we will provide an overview of several isobaric tags along with some recent developments including complementary ion tags, improvements in sensitive quantitation of analytes with lower abundance, strategies to increase multiplexing capabilities, and targeted analysis strategies. We will also discuss limitations of isobaric tags and approaches to alleviate these restrictions through bioinformatic tools and data acquisition methods. This review will highlight several applications of isobaric tags, including biomarker discovery and validation, thermal proteome profiling, cross-linking for structural investigations, single-cell analysis, top-down proteomics, along with applications to different molecules including neuropeptides, glycans, metabolites, and lipids, while providing considerations and evaluations to each application.

Isobaric labeling: Expanding the breadth, accuracy, depth, and diversity of sample multiplexing

Isobaric labeling has rapidly become a predominant strategy for proteome-wide abundance measurements. Coupled to mass spectrometry, sample multiplexing techniques using isobaric labeling are unparalleled for profiling proteins and posttranslational modifications across multiple samples in a single experiment. Here, I highlight aspects of isobaric labeling in the context of expanding the breadth of multiplexing, improving quantitative accuracy and proteome depth, and developing a wide range of diverse applications. I underscore two facets that enhance quantitative accuracy and reproducibility, specifically the availability of quality control standards for isobaric labeling experiments and the evolution of data acquisition methods. I also emphasize the necessity for standardized methodologies, particularly for emerging high-throughput workflows. Future developments in sample multiplexing will further strengthen the importance of isobaric labeling for comprehensive proteome profiling.

Evaluation of biological mechanisms of artemisinin on bovine mammary epithelial cells by integration of network pharmacology and TMT-based quantitative proteomics

The sesquiterpene lactone, artemisinin, is a primary component of the medicinal plant Artemisia annua L., which has anti-inflammatory, antibacterial and antioxidant activities. However, the potential effects of artemisinin on the mammary gland of dairy cows and the underlying molecular mechanisms remain unclear. Here, we utilized systematic network pharmacology and proteomics to elucidate the mechanism by which artemisinin affects milk production and the proliferation of bovine mammary epithelial cells (BMECs). Nineteen bioactive compounds and 56 key targets were identified through database mining. To delineate the mechanism of artemisia’s activity, a protein-protein interaction network and integrated visual display were generated from bioinformatics assays to explore the relationships and interactions among the bioactive molecules and their targets. The gene ontology (GO) terms and kyoto encyclopedia of genes and genomes annotation suggested that the apoptotic process, cell division, p53 pathway, prolactin and PI3K-Akt pathways played vital roles in mammary gland development. Using proteomics analysis, we identified 122 up-regulated and 96 down-regulated differentially significant expressed proteins (DSEPs). The differentially significant expressed proteins had multiple biological functions associated with cell division, apoptosis, differentiation, and migration. Gene ontology enrichment analysis suggested that differentially significant expressed proteins may promote cell proliferation and regulate apoptosis in bovine mammary epithelial cells. Kyoto encyclopedia of genes and genomes pathway analysis indicated that several biological pathways, such as those involved in antigen processing and presentation, cell adhesion molecules and ribosomes, played significant roles in the effects of artemisinin on bovine mammary epithelial cells. These findings contribute to a comprehensive understanding of the mechanism by which artemisinin affects bovine mammary epithelial cells to improve mammary gland turnover by inducing cell proliferation and mammary gland development.

Proteomic Discovery and Validation of Novel Fluid Biomarkers for Improved Patient Selection and Prediction of Clinical Outcomes in Alzheimer’s Disease Patient Cohorts

Alzheimer’s disease (AD) is an irreversible neurodegenerative disease characterized by progressive cognitive decline. The two cardinal neuropathological hallmarks of AD include the buildup of cerebral β amyloid (Aβ) plaques and neurofibrillary tangles of hyperphosphorylated tau. The current disease-modifying treatments are still not effective enough to lower the rate of cognitive decline. There is an urgent need to identify early detection and disease progression biomarkers that can facilitate AD drug development. The current established readouts based on the expression levels of amyloid beta, tau, and phospho-tau have shown many discrepancies in patient samples when linked to disease progression. There is an urgent need to identify diagnostic and disease progression biomarkers from blood, cerebrospinal fluid (CSF), or other biofluids that can facilitate the early detection of the disease and provide pharmacodynamic readouts for new drugs being tested in clinical trials. Advances in proteomic approaches using state-of-the-art mass spectrometry are now being increasingly applied to study AD disease mechanisms and identify drug targets and novel disease biomarkers. In this report, we describe the application of quantitative proteomic approaches for understanding AD pathophysiology, summarize the current knowledge gained from proteomic investigations of AD, and discuss the development and validation of new predictive and diagnostic disease biomarkers.