Quantitative Proteomics Reveal Region-Specific Alterations in Neuroserpin-Deficient Mouse Brain and Retina: Insights into Serpini1 Function.

Neural regeneration and neuroprotection represent strategies for future management of neurodegenerative disorders such as Alzheimer's disease (AD) or glaucoma. However, the complex molecular mechanisms that are involved in neuroprotection are not clearly understood. A promising candidate that maintains neuroprotective signaling networks is neuroserpin (Serpini1), a serine protease inhibitor expressed in neurons which selectively inhibits extracellular tissue-type plasminogen activator (tPA)/plasmin and plays a neuroprotective role during ischemic brain injury. Abnormal function of this protein has been implicated in several conditions including stroke, glaucoma, AD, and familial encephalopathy with neuroserpin inclusion bodies (FENIB). Here, we explore the potential biochemical roles of Serpini1 by comparing proteome changes between neuroserpin-deficient (NS-/-) and control mice, in the retina (RE), optic nerve (ON), frontal cortex (FC), visual cortex (VC), and cerebellum (CB). To achieve this, a multiple-plex quantitative proteomics approach using isobaric tandem mass tag (TMT) technology was employed followed by functional enrichment and protein-protein interaction analysis. We detected around 5000 proteins in each tissue and a pool of 6432 quantified proteins across all regions, resulting in a pool of 1235 differentially expressed proteins (DEPs). Principal component analysis and hierarchical clustering highlighted similarities and differences in the retina compared to various brain regions, as well as differentiating NS-/- proteome signatures from control samples. The visual cortex revealed the highest number of DEPs, followed by cerebellar regions. Pathway analysis unveiled region-specific changes, including visual perception, focal adhesion, apoptosis, glutamate receptor activation, and supramolecular fiber organization in RE, ON, FC, VC, and CB, respectively. These novel findings provide comprehensive insights into the region-specific networking of Serpini1 in the central nervous system, further characterizing its potential role as a neuroprotective agent. Data are available via ProteomeXchange with identifier PXD046873.

A transient protein folding response targets aggregation in the early phase of TDP-43-mediated neurodegeneration.

Understanding the mechanisms that drive TDP-43 pathology is integral to combating amyotrophic lateral sclerosis (ALS), frontotemporal lobar degeneration (FTLD) and other neurodegenerative diseases. Here we generated a longitudinal quantitative proteomic map of the cortex from the cytoplasmic TDP-43 rNLS8 mouse model of ALS and FTLD, and developed a complementary open-access webtool, TDP-map ( https://shiny.rcc.uq.edu.au/TDP-map/ ). We identified distinct protein subsets enriched for diverse biological pathways with temporal alterations in protein abundance, including increases in protein folding factors prior to disease onset. This included increased levels of DnaJ homolog subfamily B member 5, DNAJB5, which also co-localized with TDP-43 pathology in diseased human motor cortex. DNAJB5 over-expression decreased TDP-43 aggregation in cell and cortical neuron cultures, and knockout of Dnajb5 exacerbated motor impairments caused by AAV-mediated cytoplasmic TDP-43 expression in mice. Together, these findings reveal molecular mechanisms at distinct stages of ALS and FTLD progression and suggest that protein folding factors could be protective in neurodegenerative diseases.

Application of WGCNA and PloGO2 in the Analysis of Complex Proteomic Data.

In this protocol we describe our workflow for analyzing complex, multi-condition quantitative proteomic experiments, with the aim to extract biological insights. The tool we use is an R package, PloGO2, contributed to Bioconductor, which we can optionally precede by running correlation network analysis with WGCNA. We describe the data required and the steps we take, including detailed code examples and outputs explanation. The package was designed to generate gene ontology or pathway summaries for many data subsets at the same time, visualize protein abundance summaries for each biological category examined, help determine enriched protein subsets by comparing them all to a reference set, and suggest key highly correlated hub proteins, if the optional network analysis is employed.

Proteomic Analysis of Whole Blood Using Volumetric Absorptive Microsampling for Precision Medicine Biomarker Studies.

Microsampling of patient blood promises several benefits over conventional phlebotomy practices to facilitate precision medicine studies. These include at-home patient blood collection, supporting telehealth monitoring, minimal postcollection processing, and compatibility with nonrefrigerated transport and storage. However, for proteomic biomarker studies, mass spectrometry of whole blood has generally been avoided in favor of using plasma or serum obtained from venepuncture. We evaluated the use of a volumetric absorptive microsampling (VAMS) device as a sample preparation matrix to enable LC-MS proteomic analyses of dried whole blood. We demonstrated the detection and robust quantitation of up to 1600 proteins from single-shot shotgun-LC-MS analysis of dried whole blood, greatly enhancing proteome depth compared with conventional single-shot LC-MS analyses of undepleted plasma. Some proteins not previously reported in blood were detected using this approach. Various washing reagents were used to demonstrate that proteins can be preferentially removed from VAMS devices prior to downstream analyses. We provide a demonstration that archival frozen blood cell pellets housed under long-term storage (exceeding 5 years) are compatible with VAMS to enable quantitation of potential biomarker proteins from biobank repositories. These demonstrations are important steps in establishing viable analysis workflows to underpin large-scale precision medicine studies. Data are available via ProteomeXchange with the identifier PXD028605.

Proteomic and Transcriptomic Analysis of Microviridae φX174 Infection Reveals Broad Upregulation of Host Escherichia coli Membrane Damage and Heat Shock Responses.

Measuring host-bacteriophage dynamics is an important approach to understanding bacterial survival functions and responses to infection. The model Microviridae bacteriophage φX174 is endemic to the human gut and has been studied for over 70 years, but the host response to infection has never been investigated in detail. To address this gap in our understanding of this important interaction within our microbiome, we have measured host Escherichia coli C proteomic and transcriptomic response to φX174 infection. We used mass spectrometry and RNA sequencing (RNA-seq) to identify and quantify all 11 φX174 proteins and over 1,700 E. coli proteins, enabling us to comprehensively map host pathways involved in φX174 infection. Most notably, we see significant host responses centered on membrane damage and remodeling, cellular chaperone and translocon activity, and lipoprotein processing, which we speculate is due to the peptidoglycan-disruptive effects of the φX174 lysis protein E on MraY activity. We also observe the massive upregulation of small heat shock proteins IbpA/B, along with other heat shock pathway chaperones, and speculate on how the specific characteristics of holdase protein activity may be beneficial for viral infections. Together, this study enables us to begin to understand the proteomic and transcriptomic host responses of E. coli to Microviridae infections and contributes insights to the activities of this important model host-phage interaction.IMPORTANCE A major part of the healthy human gut microbiome is the Microviridae bacteriophage, exemplified by the model φX174 phage, and their E. coli hosts. Although much has been learned from studying φX174 over the last half-century, until this work, the E. coli host response to infection has never been investigated in detail. We reveal the proteomic and transcriptomic pathways differentially regulated during the φX174 infection cycle and uncover the details of a coordinated cellular response to membrane damage that results in increased lipoprotein processing and membrane trafficking, likely due to the phage antibiotic-like lysis protein. We also reveal that small heat shock proteins IbpA/B are massively upregulated during infection and that these holdase chaperones are highly conserved across the domains of life, indicating that reliance on them is likely widespread across viruses.

Use of a Recombinant Biomarker Protein DDA Library Increases DIA Coverage of Low Abundance Plasma Proteins.

Credible detection and quantification of low abundance proteins from human blood plasma is a major challenge in precision medicine biomarker discovery when using mass spectrometry (MS). In this proof-of-concept study, we employed a mixture of selected recombinant proteins in DDA libraries to subsequently identify (not quantify) cancer-associated low abundance plasma proteins using SWATH/DIA. The exemplar DDA recombinant protein spectral library (rPSL) was derived from tryptic digestion of 36 recombinant human proteins that had been previously implicated as possible cancer biomarkers from both our own and other studies. The rPSL was then used to identify proteins from nondepleted colorectal cancer (CRC) EDTA plasmas by SWATH-MS. Most (32/36) of the proteins used in the rPSL were reliably identified from CRC plasma samples, including 8 proteins (i.e., BTC, CXCL10, IL1B, IL6, ITGB6, TGFα, TNF, TP53) not previously detected using high-stringency protein inference MS according to PeptideAtlas. The rPSL SWATH-MS protocol was compared to DDA-MS using MARS-depleted and postdigestion peptide fractionated plasmas (here referred to as a human plasma DDA library). Of the 32 proteins identified using rPSL SWATH, only 12 could be identified using DDA-MS. The 20 additional proteins exclusively identified using the rPSL SWATH approach were almost exclusively lower abundance (i.e., <10 ng/mL) proteins. To mitigate justified FDR concerns, and to replicate a more typical library creation approach, the DDA rPSL library was merged with a human plasma DDA library and SWATH identification repeated using such a merged library. The majority (33/36) of the low abundance plasma proteins added from the rPSL were still able to be identified using such a merged library when high-stringency HPP Guidelines v3.0 protein inference criteria were applied to our data set. The MS data set has been deposited to ProteomeXchange Consortium via the PRIDE partner repository (PXD022361).

Pollen development in cotton (Gossypium hirsutum) is highly sensitive to heat exposure during the tetrad stage.

The development of gametes in plants is acutely susceptible to heatwaves as brief as a few days, adversely affecting pollen maturation and reproductive success. Pollen in cotton (Gossypium hirsutum) was differentially affected when tetrad and binucleate stages were exposed to heat, revealing new insights into the interaction between heat and pollen development. Squares were tagged and exposed to 36/25°C (day/night, moderate heat) or 40/30°C (day/night, extreme heat) for 5 days. Mature pollen grains and leaves were collected for physiological and proteomic responses. While photosynthetic competence was not compromised even at 40°C, leaf tissues became leakier. In contrast, pollen grains were markedly smaller after the tetrad stage was exposed to 40°C and boll production was reduced by 65%. Sugar levels in pollen grains were elevated after exposure to heat, eliminating carbohydrate deficits as a likely cause of poor reproductive capacity. Proteomic analysis of pure pollen samples revealed a particularly high abundance of 70-kDa heat shock (Hsp70s) and cytoskeletal proteins. While short-term bursts of heat had a minor impact on leaves, male gametophyte development was profoundly damaged. Cotton acclimates to maxima of 36°C at both the vegetative and reproductive stages but 5-days exposure to 40°C significantly impairs reproductive development.

Workflow for Rapidly Extracting Biological Insights from Complex, Multicondition Proteomics Experiments with WGCNA and PloGO2.

We describe a useful workflow for characterizing proteomics experiments incorporating many conditions and abundance data using the popular weighted gene correlation network analysis (WGCNA) approach and functional annotation with the PloGO2 R package, the latter of which we have extended and made available to Bioconductor. The approach can use quantitative data from labeled or label-free experiments and was developed to handle multiple files stemming from data partition or multiple pairwise comparisons. The WGCNA approach can similarly produce a potentially large number of clusters of interest, which can also be functionally characterized using PloGO2. Enrichment analysis will identify clusters or subsets of proteins of interest, and the WGCNA network topology scores will produce a ranking of proteins within these clusters or subsets. This can naturally lead to prioritized proteins to be considered for further analysis or as candidates of interest for validation in the context of complex experiments. We demonstrate the use of the package on two published data sets using two different biological systems (plant and human plasma) and proteomics platforms (sequential window acquisition of all theoretical fragment-ion spectra (SWATH) and tandem mass tag (TMT)): an analysis of the effect of drought on rice over time generated using TMT and a pediatric plasma sample data set generated using SWATH. In both, the automated workflow recapitulates key insights or observations of the published papers and provides additional suggestions for further investigation. These findings indicate that the data set analysis using WGCNA combined with the updated PloGO2 package is a powerful method to gain biological insights from complex multifaceted proteomics experiments.

PGRMC1 phosphorylation affects cell shape, motility, glycolysis, mitochondrial form and function, and tumor growth.

BACKGROUND: Progesterone Receptor Membrane Component 1 (PGRMC1) is expressed in many cancer cells, where it is associated with detrimental patient outcomes. It contains phosphorylated tyrosines which evolutionarily preceded deuterostome gastrulation and tissue differentiation mechanisms. RESULTS: We demonstrate that manipulating PGRMC1 phosphorylation status in MIA PaCa-2 (MP) cells imposes broad pleiotropic effects. Relative to parental cells over-expressing hemagglutinin-tagged wild-type (WT) PGRMC1-HA, cells expressing a PGRMC1-HA-S57A/S181A double mutant (DM) exhibited reduced levels of proteins involved in energy metabolism and mitochondrial function, and altered glucose metabolism suggesting modulation of the Warburg effect. This was associated with increased PI3K/AKT activity, altered cell shape, actin cytoskeleton, motility, and mitochondrial properties. An S57A/Y180F/S181A triple mutant (TM) indicated the involvement of Y180 in PI3K/AKT activation. Mutation of Y180F strongly attenuated subcutaneous xenograft tumor growth in NOD-SCID gamma mice. Elsewhere we demonstrate altered metabolism, mutation incidence, and epigenetic status in these cells. CONCLUSIONS: Altogether, these results indicate that mutational manipulation of PGRMC1 phosphorylation status exerts broad pleiotropic effects relevant to cancer and other cell biology.

Proteomic Responses to Drought Vary Widely Among Eight Diverse Genotypes of Rice (Oryza sativa).

Rice is a critically important food source but yields worldwide are vulnerable to periods of drought. We exposed eight genotypes of upland and lowland rice (Oryza sativa L. ssp. japonica and indica) to drought stress at the late vegetative stage, and harvested leaves for label-free shotgun proteomics. Gene ontology analysis was used to identify common drought-responsive proteins in vegetative tissues, and leaf proteins that are unique to individual genotypes, suggesting diversity in the metabolic responses to drought. Eight proteins were found to be induced in response to drought stress in all eight genotypes. A total of 213 proteins were identified in a single genotype, 83 of which were increased in abundance in response to drought stress. In total, 10 of these 83 proteins were of a largely uncharacterized function, making them candidates for functional analysis and potential biomarkers for drought tolerance.

Salt-Treated Roots of Oryza australiensis Seedlings are Enriched with Proteins Involved in Energetics and Transport.

Salinity is a major constraint on rice productivity worldwide. However, mechanisms of salt tolerance in wild rice relatives are unknown. Root microsomal proteins are extracted from two Oryza australiensis accessions contrasting in salt tolerance. Whole roots of 2-week-old seedlings are treated with 80 mM NaCl for 30 days to induce salt stress. Proteins are quantified by tandem mass tags (TMT) and triple-stage Mass Spectrometry. More than 200 differentially expressed proteins between the salt-treated and control samples in the two accessions (p-value <0.05) are found. Gene Ontology (GO) analysis shows that proteins categorized as "metabolic process," "transport," and "transmembrane transporter" are highly responsive to salt treatment. In particular, mitochondrial ATPases and SNARE proteins are more abundant in roots of the salt-tolerant accession and responded strongly when roots are exposed to salinity. mRNA quantification validated the elevated protein abundances of a monosaccharide transporter and an antiporter observed in the salt-tolerant genotype. The importance of the upregulated monosaccharide transporter and a VAMP-like protein by measuring salinity responses of two yeast knockout mutants for genes homologous to those encoding these proteins in rice are confirmed. Potential new mechanisms of salt tolerance in rice, with implications for breeding of elite cultivars are also discussed.

Potential early clinical stage colorectal cancer diagnosis using a proteomics blood test panel.

BACKGROUND: One of the most significant challenges in colorectal cancer (CRC) management is the use of compliant early stage population-based diagnostic tests as adjuncts to confirmatory colonoscopy. Despite the near curative nature of early clinical stage surgical resection, mortality remains unacceptably high-as the majority of patients diagnosed by faecal haemoglobin followed by colonoscopy occur at latter stages. Additionally, current population-based screens reliant on fecal occult blood test (FOBT) have low compliance (~ 40%) and tests suffer low sensitivities. Therefore, blood-based diagnostic tests offer survival benefits from their higher compliance (≥ 97%), if they can at least match the sensitivity and specificity of FOBTs. However, discovery of low abundance plasma biomarkers is difficult due to occupancy of a high percentage of proteomic discovery space by many high abundance plasma proteins (e.g., human serum albumin). METHODS: A combination of high abundance protein ultradepletion (e.g., MARS-14 and an in-house IgY depletion columns) strategies, extensive peptide fractionation methods (SCX, SAX, High pH and SEC) and SWATH-MS were utilized to uncover protein biomarkers from a cohort of 100 plasma samples (i.e., pools of 20 healthy and 20 stages I-IV CRC plasmas). The differentially expressed proteins were analyzed using ANOVA and pairwise t-tests (p < 0.05; fold-change > 1.5), and further examined with a neural network classification method using in silico augmented 5000 patient datasets. RESULTS: Ultradepletion combined with peptide fractionation allowed for the identification of a total of 513 plasma proteins, 8 of which had not been previously reported in human plasma (based on PeptideAtlas database). SWATH-MS analysis revealed 37 protein biomarker candidates that exhibited differential expression across CRC stages compared to healthy controls. Of those, 7 candidates (CST3, GPX3, CFD, MRC1, COMP, PON1 and ADAMDEC1) were validated using Western blotting and/or ELISA. The neural network classification narrowed down candidate biomarkers to 5 proteins (SAA2, APCS, APOA4, F2 and AMBP) that had maintained accuracy which could discern early (I/II) from late (III/IV) stage CRC. CONCLUSION: MS-based proteomics in combination with ultradepletion strategies have an immense potential of identifying diagnostic protein biosignature.

Proteomics Reveals Cell-Surface Urokinase Plasminogen Activator Receptor Expression Impacts Most Hallmarks of Cancer.

While metastasis is the primary cause of colorectal cancer (CRC) mortality, the molecular mechanisms underpinning it remains elusive. Metastasis is propagated through driver oncogene/suppressor gene mutations, accompanied by passenger mutations and underlying genomic instability. To understand cancer biology, a unifying framework called the "hallmarks of cancer" (HoCs) has been developed, which organizes cell biological alterations under ten key hallmarks. Underlying these HoCs, genome instability generates mutational diversity that is amplified by inflammation. Recognizing how critical cancer cell-surface proteins influence, these HoCs have been proposed to accelerate precision medicine therapeutic development. A moderate decrease (43%↓) in HCT116 cell surface urokinase plasminogen activator receptor (uPAR) expression mitigates against many HoCs driven by these cell's KRAS and PIK3CA mutational signature. Comprehensive proteomics (whole cell lysis with two membrane protein enrichments) coupled with ingenuity pathway analysis (IPA) demonstrates that uPAR negates essential pathways across the HoC spectrum, particularly those associated with metastasis, resisting cell death, and sustaining proliferation, and parallels Cancer Hallmarks Analytics Tool analysis. Decreasing uPAR predominantly alters metastasis-related and uPAR-interactome protein expression (e.g., EGFR, caveolin, vitronectin, integrin ß4). Collectively, it is demonstrated that uPAR is a lynchpin protein capable of regulating several HoC pathways in a classical CRC mutational background.

Practical Integration of Multi-Run iTRAQ Data.

In this chapter, we describe some of the approaches we employ in the analysis of iTRAQ data in our group, with an emphasis on practical issues that can occur in larger multi-run projects. Our pipeline starts with a well-established iTRAQ workflow, makes use of protein level quantitation using ProteinPilot, and continues either via a global analysis in the presence of a common reference, or by identifying pairwise comparisons of interest and applying a method taking the protein ratios and protein ratio confidence measures into consideration. Additionally we describe what issues can occur in the more subtle scenarios involving composite databases in multi-run situations, and an approach applicable in that setting.

Amyloid ß Induces Early Changes in the Ribosomal Machinery, Cytoskeletal Organization and Oxidative Phosphorylation in Retinal Photoreceptor Cells.

Amyloid ß (Aß) accumulation and its aggregation is characteristic molecular feature of the development of Alzheimer's disease (AD). More recently, Aß has been suggested to be associated with retinal pathology associated with AD, glaucoma and drusen deposits in age related macular degeneration (AMD). In this study, we investigated the proteins and biochemical networks that are affected by Aß in the 661 W photoreceptor cells in culture. Time and dose dependent effects of Aß on the photoreceptor cells were determined utilizing tandem mass tag (TMT) labeling-based quantitative mass-spectrometric approach. Bioinformatic analysis of the data revealed concentration and time dependent effects of the Aß peptide stimulation on various key biochemical pathways that might be involved in mediating the toxicity effects of the peptide. We identified increased Tau phosphorylation, GSK3ß dysregulation and reduced cell viability in cells treated with Aß in a dose and time dependent manner. This study has delineated for the first-time molecular networks in photoreceptor cells that are impacted early upon Aß treatment and contrasted the findings with a longer-term treatment effect. Proteins associated with ribosomal machinery homeostasis, mitochondrial function and cytoskeletal organization were affected in the initial stages of Aß exposure, which may provide key insights into AD effects on the photoreceptors and specific molecular changes induced by Aß peptide.

Proteomes of Leaf-Growing Zones in Rice Genotypes with Contrasting Drought Tolerance.

Plants require a distinctive cohort of enzymes to coordinate cell division and expansion. Proteomic analysis now enables interrogation of immature leaf bases where these processes occur. Hence, proteins in tissues sampled from leaves of a drought-tolerant rice (IAC1131) are investigated to provide insights into the effect of soil drying on gene expression relative to the drought-sensitive genotype Nipponbare. Shoot growth zones are dissected to estimate the proportion of dividing cells and extract protein for subsequent tandem mass tags quantitative proteomic analysis. Gene ontology annotations of differentially expressed proteins provide insights into responses of Nipponbare and IAC1131 to drought. Soil drying does not affect the percentage of mitotic cells in IAC1131. More than 800 proteins across most functional categories increase in drought (and decrease on rewatering) in IAC1131, including proteins involved in "organizing the meristem" and "new cell formation". On the other hand, the percentage of dividing cells in Nipponbare is severely impaired during drought and fewer than 200 proteins respond in abundance when growing zones undergo a drying cycle. Remarkably, the proteomes of the growing zones of each genotype respond in a highly distinctive manner, reflecting their contrasting drought tolerance even at the earliest stages of leaf development.

Upregulation of Proteolytic Pathways and Altered Protein Biosynthesis Underlie Retinal Pathology in a Mouse Model of Alzheimer's Disease.

Increased amyloid ß (Aß) aggregation is a hallmark feature of Alzheimer's disease (AD) pathology. The APP/PS1 mouse model of AD exhibits accumulation of Aß in the retina and demonstrates reduced retinal function and other degenerative changes. The overall molecular effects of AD pathology on the retina remain undetermined. Using a proteomics approach, this study assessed the molecular effects of Aß accumulation and progression of AD pathology on the retina. Retinal tissues from younger (2.5 months) and older 8-month APP/PS1 mice were analysed for protein expression changes. A multiplexed proteomics approach using chemical isobaric tandem mass tags was applied followed by functional and protein-protein interaction analyses using Ingenuity pathway (IPA) and STRING computational tools. We identified approximately 2000 proteins each in the younger (upregulated 50; downregulated 36) and older set of APP/PS1 (upregulated 85; downregulated 79) mice retinas. Amyloid precursor protein (APP) was consistently upregulated two to threefold in both younger and older retinas (p < 0.0001). Mass spectrometry data further revealed that older APP/PS1 mice retinas had elevated levels of proteolytic enzymes cathepsin D, presenilin 2 and nicastrin that are associated with APP processing. Increased levels of proteasomal proteins Psma5, Psmd3 and Psmb2 were also observed in the older AD retinas. In contrast to the younger animals, significant downregulation of protein synthesis and elongation associated proteins such as Eef1a1, Rpl35a, Mrpl2 and Eef1e1 (p < 0.04) was identified in the older mice retinas. This study reports for the first time that not only old but also young APP/PS1 animals demonstrate increased amyloid protein levels in their retinas. Quantitative proteomics reveals new molecular insights which may represent a cellular response to clear amyloid build-up. Further, downregulation of ribosomal proteins involved in protein biosynthesis was observed which might be considered a toxicity effect.

iSwathX: an interactive web-based application for extension of DIA peptide reference libraries.

Summary: Large-scale peptide mass spectrometry (MS)/MS reference libraries are essential for the comprehensive analysis of data-independent acquisition (DIA) MS datasets, providing a comprehensive set of spectra for identification and quantification of proteins. We have developed a novel web-based R-package (iSwathX) for combining reference libraries that is compatible with different DIA analysis software. This open-source web GUI automates the process of normalization and combination of spectral libraries and provides a user-friendly method for performing library format conversions, analysis and visualizations, with no need for programing familiarity. Availability and implementation: iSwathX is freely accessible at https://biolinfo.shinyapps.io/iSwathX with the R-package and Shiny source code available from GitHub (https://github.com/znoor/iSwathX). Supplementary information: Supplementary data are available at Bioinformatics online.

Clinically Relevant Post-Translational Modification Analyses-Maturing Workflows and Bioinformatics Tools.

Post-translational modifications (PTMs) can occur soon after translation or at any stage in the lifecycle of a given protein, and they may help regulate protein folding, stability, cellular localisation, activity, or the interactions proteins have with other proteins or biomolecular species. PTMs are crucial to our functional understanding of biology, and new quantitative mass spectrometry (MS) and bioinformatics workflows are maturing both in labelled multiplexed and label-free techniques, offering increasing coverage and new opportunities to study human health and disease. Techniques such as Data Independent Acquisition (DIA) are emerging as promising approaches due to their re-mining capability. Many bioinformatics tools have been developed to support the analysis of PTMs by mass spectrometry, from prediction and identifying PTM site assignment, open searches enabling better mining of unassigned mass spectra-many of which likely harbour PTMs-through to understanding PTM associations and interactions. The remaining challenge lies in extracting functional information from clinically relevant PTM studies. This review focuses on canvassing the options and progress of PTM analysis for large quantitative studies, from choosing the platform, through to data analysis, with an emphasis on clinically relevant samples such as plasma and other body fluids, and well-established tools and options for data interpretation.

The Art of Validating Quantitative Proteomics Data.

Western blotting as an orthogonal validation tool for quantitative proteomics data has rapidly become a de facto requirement for publication. In this viewpoint article, the pros and cons of western blotting as a validation approach are discussed, using examples from our own published work, and how to best apply it to improve the quality of data published is outlined. Further, suggestions and guidelines for some other experimental approaches are provided, which can be used for validation of quantitative proteomics data in addition to, or in place of, western blotting.