protti: an R package for comprehensive data analysis of peptide- and protein-centric bottom-up proteomics data

Inhibition of hepatic p63 ameliorates steatohepatitis with fibrosis in mice

OBJECTIVE

p63 is a transcription factor involved in multiple biological functions. In the liver, the TAp63 isoform induces lipid accumulation in hepatocytes. However, the role of liver TAp63 in the progression of metabolic dysfunction-associated steatohepatitis (MASH) with fibrosis is unknown.

METHODS

We evaluated the hepatic p63 levels in different mouse models of steatohepatitis with fibrosis induced by diet. Next, we used virogenetic approaches to manipulate the expression of TAp63 in adult mice under diet-induced steatohepatitis with fibrosis and characterized the disease condition. Finally, we performed proteomics analysis in mice with overexpression and knockdown of hepatic TAp63.

RESULTS

Levels of TAp63, but not of ΔN isoform, are increased in the liver of mice with diet-induced steatohepatitis with fibrosis. Both preventive and interventional strategies for the knockdown of hepatic TAp63 significantly ameliorated diet-induced steatohepatitis with fibrosis in mice fed a methionine- and choline-deficient diet (MCDD) and choline deficient and high fat diet (CDHFD). The overexpression of hepatic TAp63 in mice aggravated the liver condition in mice fed a CDHFD. Proteomic analysis in the liver of these mice revealed alteration in multiple proteins and pathways, such as oxidative phosphorylation, antioxidant activity, peroxisome function and LDL clearance.

CONCLUSIONS

These results indicate that liver TAp63 plays a critical role in the progression of diet-induced steatohepatitis with fibrosis, and its inhibition ameliorates the disease.

Aryl amino acetamides prevent Plasmodium falciparum ring development via targeting the lipid-transfer protein PfSTART1

With resistance to most antimalarials increasing, it is imperative that new drugs are developed. We previously identified an aryl acetamide compound, MMV006833 (M-833), that inhibited the ring-stage development of newly invaded merozoites. Here, we select parasites resistant to M-833 and identify mutations in the START lipid transfer protein (PF3D7_0104200, PfSTART1). Introducing PfSTART1 mutations into wildtype parasites reproduces resistance to M-833 as well as to more potent analogues. PfSTART1 binding to the analogues is validated using organic solvent-based Proteome Integral Solubility Alteration (Solvent PISA) assays. Imaging of invading merozoites shows the inhibitors prevent the development of ring-stage parasites potentially by inhibiting the expansion of the encasing parasitophorous vacuole membrane. The PfSTART1-targeting compounds also block transmission to mosquitoes and with multiple stages of the parasite's lifecycle being affected, PfSTART1 represents a drug target with a new mechanism of action.

Systematic identification of structure-specific protein-protein interactions

The physical interactome of a protein can be altered upon perturbation, modulating cell physiology and contributing to disease. Identifying interactome differences of normal and disease states of proteins could help understand disease mechanisms, but current methods do not pinpoint structure-specific PPIs and interaction interfaces proteome-wide. We used limited proteolysis-mass spectrometry (LiP-MS) to screen for structure-specific PPIs by probing for protease susceptibility changes of proteins in cellular extracts upon treatment with specific structural states of a protein. We first demonstrated that LiP-MS detects well-characterized PPIs, including antibody-target protein interactions and interactions with membrane proteins, and that it pinpoints interfaces, including epitopes. We then applied the approach to study conformation-specific interactors of the Parkinson's disease hallmark protein alpha-synuclein (aSyn). We identified known interactors of aSyn monomer and amyloid fibrils and provide a resource of novel putative conformation-specific aSyn interactors for validation in further studies. We also used our approach on GDP- and GTP-bound forms of two Rab GTPases, showing detection of differential candidate interactors of conformationally similar proteins. This approach is applicable to screen for structure-specific interactomes of any protein, including posttranslationally modified and unmodified, or metabolite-bound and unbound protein states.

A chemical probe to modulate human GID4 Pro/N-degron interactions

The C-terminal to LisH (CTLH) complex is a ubiquitin ligase complex that recognizes substrates with Pro/N-degrons via its substrate receptor Glucose-Induced Degradation 4 (GID4), but its function and substrates in humans remain unclear. Here, we report PFI-7, a potent, selective and cell-active chemical probe that antagonizes Pro/N-degron binding to human GID4. Use of PFI-7 in proximity-dependent biotinylation and quantitative proteomics enabled the identification of GID4 interactors and GID4-regulated proteins. GID4 interactors are enriched for nucleolar proteins, including the Pro/N-degron-containing RNA helicases DDX21 and DDX50. We also identified a distinct subset of proteins whose cellular levels are regulated by GID4 including HMGCS1, a Pro/N-degron-containing metabolic enzyme. These data reveal human GID4 Pro/N-degron targets regulated through a combination of degradative and nondegradative functions. Going forward, PFI-7 will be a valuable research tool for investigating CTLH complex biology and facilitating development of targeted protein degradation strategies that highjack CTLH E3 ligase activity.

Stability-based approaches in chemoproteomics

Target deconvolution can help understand how compounds exert therapeutic effects and can accelerate drug discovery by helping optimise safety and efficacy, revealing mechanisms of action, anticipate off-target effects and identifying opportunities for therapeutic expansion. Chemoproteomics, a combination of chemical biology with mass spectrometry has transformed target deconvolution. This review discusses modification-free chemoproteomic approaches that leverage the change in protein thermodynamics induced by small molecule ligand binding. Unlike modification-based methods relying on enriching specific protein targets, these approaches offer proteome-wide evaluations, driven by advancements in mass spectrometry sensitivity, increasing proteome coverage and quantitation methods. Advances in methods based on denaturation/precipitation by thermal or chemical denaturation, or by protease degradation are evaluated, emphasising the evolving landscape of chemoproteomics and its potential impact on future drug-development strategies.

Pursuing Impactful Quantitative Proteomics Using QC-Channels in Every Spectrum and Trend-Design in Experiment

False changes discovered by quantitative proteomics reduce the trust of biologists in proteomics and limit the applications of proteomics to unlock biological mechanisms, which suppresses the application of proteomics techniques in the pharmaceutical industry more than it does in academic research. To remove false changes that arise during LC-MS/MS data acquisition, we evaluated the contributions of peptide abundance and number of unique peptides on reproducibility. Lower abundance and only one unique peptide have a higher risk of generating a higher coefficient of variation (CV), resulting in less accurate quantification. However, the abundance of peptides in samples is not adjustable and discarding proteins quantified by only one unique peptide is not a choice either. Indeed, a large percentage of proteins are accurately quantified by only one unique peptide. Therefore, to improve the calculations of the CV, we leverage a new function in PEAKS called QC-channels which enables technical replicates of each spectrum to be evaluated prior to calculation of the CV. While the QC-channels function in PEAKS significantly reduced the false quantification, random false changes still exist due to known or unknown reasons. To address this challenge, we present the idea of Trend-design to track trend changes rather than changes from two points to remove false quantifications and reveal consequential changes responding to a treatment or condition. The idea was confirmed by molecules with different affinity and dose in the current study. The combination of QC-channels and Trend-design enables a more impactful quantitative proteomics to allow unlocking biological mechanisms using proteomics.

Systematic identification of 20S proteasome substrates

For years, proteasomal degradation was predominantly attributed to the ubiquitin-26S proteasome pathway. However, it is now evident that the core 20S proteasome can independently target proteins for degradation. With approximately half of the cellular proteasomes comprising free 20S complexes, this degradation mechanism is not rare. Identifying 20S-specific substrates is challenging due to the dual-targeting of some proteins to either 20S or 26S proteasomes and the non-specificity of proteasome inhibitors. Consequently, knowledge of 20S proteasome substrates relies on limited hypothesis-driven studies. To comprehensively explore 20S proteasome substrates, we employed advanced mass spectrometry, along with biochemical and cellular analyses. This systematic approach revealed hundreds of 20S proteasome substrates, including proteins undergoing specific N- or C-terminal cleavage, possibly for regulation. Notably, these substrates were enriched in RNA- and DNA-binding proteins with intrinsically disordered regions, often found in the nucleus and stress granules. Under cellular stress, we observed reduced proteolytic activity in oxidized proteasomes, with oxidized protein substrates exhibiting higher structural disorder compared to unmodified proteins. Overall, our study illuminates the nature of 20S substrates, offering crucial insights into 20S proteasome biology.

Analysis and visualization of quantitative proteomics data using FragPipe-Analyst

The FragPipe computational proteomics platform is gaining widespread popularity among the proteomics research community because of its fast processing speed and user-friendly graphical interface. Although FragPipe produces well-formatted output tables that are ready for analysis, there is still a need for an easy-to-use and user-friendly downstream statistical analysis and visualization tool. FragPipe-Analyst addresses this need by providing an R shiny web server to assist FragPipe users in conducting downstream analyses of the resulting quantitative proteomics data. It supports major quantification workflows including label-free quantification, tandem mass tags, and data-independent acquisition. FragPipe-Analyst offers a range of useful functionalities, such as various missing value imputation options, data quality control, unsupervised clustering, differential expression (DE) analysis using Limma, and gene ontology and pathway enrichment analysis using Enrichr. To support advanced analysis and customized visualizations, we also developed FragPipeAnalystR, an R package encompassing all FragPipe-Analyst functionalities that is extended to support site-specific analysis of post-translational modifications (PTMs). FragPipe-Analyst and FragPipeAnalystR are both open-source and freely available.

Regulatory sites of CaM-sensitive adenylyl cyclase AC8 revealed by cryo-EM and structural proteomics

Membrane adenylyl cyclase AC8 is regulated by G proteins and calmodulin (CaM), mediating the crosstalk between the cAMP pathway and Ca2+ signalling. Despite the importance of AC8 in physiology, the structural basis of its regulation by G proteins and CaM is not well defined. Here, we report the 3.5 Å resolution cryo-EM structure of the bovine AC8 bound to the stimulatory Gαs protein in the presence of Ca2+/CaM. The structure reveals the architecture of the ordered AC8 domains bound to Gαs and the small molecule activator forskolin. The extracellular surface of AC8 features a negatively charged pocket, a potential site for unknown interactors. Despite the well-resolved forskolin density, the captured state of AC8 does not favour tight nucleotide binding. The structural proteomics approaches, limited proteolysis and crosslinking mass spectrometry (LiP-MS and XL-MS), allowed us to identify the contact sites between AC8 and its regulators, CaM, Gαs, and Gβγ, as well as to infer the conformational changes induced by these interactions. Our results provide a framework for understanding the role of flexible regions in the mechanism of AC regulation.

In situ analysis of osmolyte mechanisms of proteome thermal stabilization

Organisms use organic molecules called osmolytes to adapt to environmental conditions. In vitro studies indicate that osmolytes thermally stabilize proteins, but mechanisms are controversial, and systematic studies within the cellular milieu are lacking. We analyzed Escherichia coli and human protein thermal stabilization by osmolytes in situ and across the proteome. Using structural proteomics, we probed osmolyte effects on protein thermal stability, structure and aggregation, revealing common mechanisms but also osmolyte- and protein-specific effects. All tested osmolytes (trimethylamine N-oxide, betaine, glycerol, proline, trehalose and glucose) stabilized many proteins, predominantly via a preferential exclusion mechanism, and caused an upward shift in temperatures at which most proteins aggregated. Thermal profiling of the human proteome provided evidence for intrinsic disorder in situ but also identified potential structure in predicted disordered regions. Our analysis provides mechanistic insight into osmolyte function within a complex biological matrix and sheds light on the in situ prevalence of intrinsically disordered regions.

Mass Spectrometry-Based Immunopeptidomics of Peptides Presented on Human Leukocyte Antigen Proteins

Human leukocyte antigen (HLA) proteins are a group of glycoproteins that are expressed at the cell surface, where they present peptides to T cells through physical interactions with T-cell receptors (TCRs). Hence, characterizing the set of peptides presented by HLA proteins, referred to hereafter as the immunopeptidome, is fundamental for neoantigen identification, immunotherapy, and vaccine development. As a result, different methods have been used over the years to identify peptides presented by HLA proteins, including competition assays, peptide microarrays, and yeast display systems. Nonetheless, over the last decade, mass spectrometry-based immunopeptidomics (MS-immunopeptidomics) has emerged as the gold-standard method for identifying peptides presented by HLA proteins. MS-immunopeptidomics enables the direct identification of the immunopeptidome in different tissues and cell types in different physiological and pathological states, for example, solid tumors or virally infected cells. Despite its advantages, it is still an experimentally and computationally challenging technique with different aspects that need to be considered before planning an MS-immunopeptidomics experiment, while conducting the experiment and with analyzing and interpreting the results. Hence, we aim in this chapter to provide an overview of this method and discuss different practical considerations at different stages starting from sample collection until data analysis. These points should aid different groups aiming at utilizing MS-immunopeptidomics, as well as, identifying future research directions to improve the method.

Identification of proteoforms of short open reading frame-encoded peptides in Blautia producta under different cultivation conditions

IMPORTANCE

The identification of short open reading frame-encoded peptides (SEP) and different proteoforms in single cultures of gut microbes offers new insights into a largely neglected part of the microbial proteome landscape. This is of particular importance as SEP provide various predicted functions, such as acting as antimicrobial peptides, maintaining cell homeostasis under stress conditions, or even contributing to the virulence pattern. They are, thus, taking a poorly understood role in structure and function of microbial networks in the human body. A better understanding of SEP in the context of human health requires a precise understanding of the abundance of SEP both in commensal microbes as well as pathogens. For the gut beneficial B. producta, we demonstrate the importance of specific environmental conditions for biosynthesis of SEP expanding previous findings about their role in microbial interactions.

A Bioconductor workflow for processing, evaluating, and interpreting expression proteomics data

Background: Expression proteomics involves the global evaluation of protein abundances within a system. In turn, differential expression analysis can be used to investigate changes in protein abundance upon perturbation to such a system. Methods: Here, we provide a workflow for the processing, analysis and interpretation of quantitative mass spectrometry-based expression proteomics data. This workflow utilizes open-source R software packages from the Bioconductor project and guides users end-to-end and step-by-step through every stage of the analyses. As a use-case we generated expression proteomics data from HEK293 cells with and without a treatment. Of note, the experiment included cellular proteins labelled using tandem mass tag (TMT) technology and secreted proteins quantified using label-free quantitation (LFQ). Results: The workflow explains the software infrastructure before focusing on data import, pre-processing and quality control. This is done individually for TMT and LFQ datasets. The application of statistical differential expression analysis is demonstrated, followed by interpretation via gene ontology enrichment analysis. Conclusions: A comprehensive workflow for the processing, analysis and interpretation of expression proteomics is presented. The workflow is a valuable resource for the proteomics community and specifically beginners who are at least familiar with R who wish to understand and make data-driven decisions with regards to their analyses.

ATP-independent substrate recruitment to proteasomal degradation in mycobacteria

Mycobacteria and other actinobacteria possess proteasomal degradation pathways in addition to the common bacterial compartmentalizing protease systems. Proteasomal degradation plays a crucial role in the survival of these bacteria in adverse environments. The mycobacterial proteasome interacts with several ring-shaped activators, including the bacterial proteasome activator (Bpa), which enables energy-independent degradation of heat shock repressor HspR. However, the mechanism of substrate selection and processing by the Bpa-proteasome complex remains unclear. In this study, we present evidence that disorder in substrates is required but not sufficient for recruitment to Bpa-mediated proteasomal degradation. We demonstrate that Bpa binds to the folded N-terminal helix-turn-helix domain of HspR, whereas the unstructured C-terminal tail of the substrate acts as a sequence-specific threading handle to promote efficient proteasomal degradation. In addition, we establish that the heat shock chaperone DnaK, which interacts with and co-regulates HspR, stabilizes HspR against Bpa-mediated proteasomal degradation. By phenotypical characterization of Mycobacterium smegmatis parent and bpa deletion mutant strains, we show that Bpa-dependent proteasomal degradation supports the survival of the bacterium under stress conditions by degrading HspR that regulates vital chaperones.

Distinct laccase expression and activity profiles of Trametes versicolor facilitate degradation of benzo[a]pyrene

A Trametes versicolor isolate from the Changbai Mountain showed promising activity in degrading benzo[a]pyrene (BaP), which is a high molecular weight (HMW) polycyclic aromatic hydrocarbon (PAH) compound. It was hypothesized that the T. versicolor isolate encode BaP-degrading enzymes, among which laccase is mostly sought after due to significant commercial potential. Genome of the T. versicolor isolate was sequenced and assembled, and seven laccase homologues were identified (TvLac1-7) as candidate genes potentially contributing to BaP degradation. In order to further identify the BaP responsive laccases, time-course transcriptomic and proteomic analyses were conducted in parallel on the T. versicolor isolate upon BaP treatment. Homologous laccases showed distinct expression patterns. Most strikingly, TvLac5 was rapidly induced in the secreted proteomes (secretomes), while TvLac2 was repressed. Recombinant laccase expression and biochemical characterization further showed corresponding enzymatic activity profiles, where TvLac5 was 21-fold more effective in BaP degradation compared to TvLac2. Moreover, TvLac5 also showed 3.6-fold higher BaP degrading activity compared to a commercial laccase product of T. versicolor origin. Therefore, TvLac5 was concluded to be a BaP-responsive enzyme from T. versicolor showing effective BaP degradation activity.

Structures of wild-type and selected CMT1X mutant connexin 32 gap junction channels and hemichannels

In myelinating Schwann cells, connection between myelin layers is mediated by gap junction channels (GJCs) formed by docked connexin 32 (Cx32) hemichannels (HCs). Mutations in Cx32 cause the X-linked Charcot-Marie-Tooth disease (CMT1X), a degenerative neuropathy without a cure. A molecular link between Cx32 dysfunction and CMT1X pathogenesis is still missing. Here, we describe the high-resolution cryo-electron cryo-myography (cryo-EM) structures of the Cx32 GJC and HC, along with two CMT1X-linked mutants, W3S and R22G. While the structures of wild-type and mutant GJCs are virtually identical, the HCs show a major difference: In the W3S and R22G mutant HCs, the amino-terminal gating helix partially occludes the pore, consistent with a diminished HC activity. Our results suggest that HC dysfunction may be involved in the pathogenesis of CMT1X.

Tidyproteomics: an open-source R package and data object for quantitative proteomics post analysis and visualization

BACKGROUND

The analysis of mass spectrometry-based quantitative proteomics data can be challenging given the variety of established analysis platforms, the differences in reporting formats, and a general lack of approachable standardized post-processing analyses such as sample group statistics, quantitative variation and even data filtering. We developed tidyproteomics to facilitate basic analysis, improve data interoperability and potentially ease the integration of new processing algorithms, mainly through the use of a simplified data-object.

RESULTS

The R package tidyproteomics was developed as both a framework for standardizing quantitative proteomics data and a platform for analysis workflows, containing discrete functions that can be connected end-to-end, thus making it easier to define complex analyses by breaking them into small stepwise units. Additionally, as with any analysis workflow, choices made during analysis can have large impacts on the results and as such, tidyproteomics allows researchers to string each function together in any order, select from a variety of options and in some cases develop and incorporate custom algorithms.

CONCLUSIONS

Tidyproteomics aims to simplify data exploration from multiple platforms, provide control over individual functions and analysis order, and serve as a tool to assemble complex repeatable processing workflows in a logical flow. Datasets in tidyproteomics are easy to work with, have a structure that allows for biological annotations to be added, and come with a framework for developing additional analysis tools. The consistent data structure and accessible analysis and plotting tools also offers a way for researchers to save time on mundane data manipulation tasks.

prolfqua: A Comprehensive R-Package for Proteomics Differential Expression Analysis

Mass spectrometry is widely used for quantitative proteomics studies, relative protein quantification, and differential expression analysis of proteins. There is a large variety of quantification software and analysis tools. Nevertheless, there is a need for a modular, easy-to-use application programming interface in R that transparently supports a variety of well principled statistical procedures to make applying them to proteomics data, comparing and understanding their differences easy. The prolfqua package integrates essential steps of the mass spectrometry-based differential expression analysis workflow: quality control, data normalization, protein aggregation, statistical modeling, hypothesis testing, and sample size estimation. The package makes integrating new data formats easy. It can be used to model simple experimental designs with a single explanatory variable and complex experiments with multiple factors and hypothesis testing. The implemented methods allow sensitive and specific differential expression analysis. Furthermore, the package implements benchmark functionality that can help to compare data acquisition, data preprocessing, or data modeling methods using a gold standard data set. The application programmer interface of prolfqua strives to be clear, predictable, discoverable, and consistent to make proteomics data analysis application development easy and exciting. Finally, the prolfqua R-package is available on GitHub https://github.com/fgcz/prolfqua, distributed under the MIT license. It runs on all platforms supported by the R free software environment for statistical computing and graphics.

promor: a comprehensive R package for label-free proteomics data analysis and predictive modeling

Summary

We present promor, a comprehensive, user-friendly R package that streamlines label-free quantification proteomics data analysis and building machine learning-based predictive models with top protein candidates.

Availability and implementation

promor is freely available as an open source R package on the Comprehensive R Archive Network (CRAN) (https://CRAN.R-project.org/package=promor) and distributed under the Lesser General Public License (version 2.1 or later). Development version of promor is maintained on GitHub (https://github.com/caranathunge/promor) and additional documentation and tutorials are provided on the package website (https://caranathunge.github.io/promor/).

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Target Deconvolution by Limited Proteolysis Coupled to Mass Spectrometry

Limited proteolysis coupled to mass spectrometry (LiP-MS) is a recent proteomics technique that allows structure-based target engagement profiling on a proteome-wide level. To achieve this, native lysates are first incubated with a compound, followed by a short incubation with a nonspecific protease. Binding of a compound can change accessibility at the binding site or induce other structural changes in the target. This leads to treatment-specific proteolytic fingerprints upon limited proteolysis, which can be analyzed by standard bottom-up MS-based proteomics. Here, we describe a basic LiP-MS protocol using the natural product rapamycin as an example compound. Along with the provided LiP-MS reference data available via ProteomeXchange with identifier PXD035183, this enables the straightforward implementation of the method by scientists with a basic biochemistry and mass spectrometry background. We describe how the procedure can easily be adapted to other protein samples and small molecules.

MS-DAP Platform for Downstream Data Analysis of Label-Free Proteomics Uncovers Optimal Workflows in Benchmark Data Sets and Increased Sensitivity in Analysis of Alzheimer's Biomarker Data

In the rapidly moving proteomics field, a diverse patchwork of data analysis pipelines and algorithms for data normalization and differential expression analysis is used by the community. We generated a mass spectrometry downstream analysis pipeline (MS-DAP) that integrates both popular and recently developed algorithms for normalization and statistical analyses. Additional algorithms can be easily added in the future as plugins. MS-DAP is open-source and facilitates transparent and reproducible proteome science by generating extensive data visualizations and quality reporting, provided as standardized PDF reports. Second, we performed a systematic evaluation of methods for normalization and statistical analysis on a large variety of data sets, including additional data generated in this study, which revealed key differences. Commonly used approaches for differential testing based on moderated t-statistics were consistently outperformed by more recent statistical models, all integrated in MS-DAP. Third, we introduced a novel normalization algorithm that rescues deficiencies observed in commonly used normalization methods. Finally, we used the MS-DAP platform to reanalyze a recently published large-scale proteomics data set of CSF from AD patients. This revealed increased sensitivity, resulting in additional significant target proteins which improved overlap with results reported in related studies and includes a large set of new potential AD biomarkers in addition to previously reported.

Global, in situ analysis of the structural proteome in individuals with Parkinson's disease to identify a new class of biomarker

Parkinson's disease (PD) is a prevalent neurodegenerative disease for which robust biomarkers are needed. Because protein structure reflects function, we tested whether global, in situ analysis of protein structural changes provides insight into PD pathophysiology and could inform a new concept of structural disease biomarkers. Using limited proteolysis-mass spectrometry (LiP-MS), we identified 76 structurally altered proteins in cerebrospinal fluid (CSF) of individuals with PD relative to healthy donors. These proteins were enriched in processes misregulated in PD, and some proteins also showed structural changes in PD brain samples. CSF protein structural information outperformed abundance information in discriminating between healthy participants and those with PD and improved the discriminatory performance of CSF measures of the hallmark PD protein α-synuclein. We also present the first analysis of inter-individual variability of a structural proteome in healthy individuals, identifying biophysical features of variable protein regions. Although independent validation is needed, our data suggest that global analyses of the human structural proteome will guide the development of novel structural biomarkers of disease and enable hypothesis generation about underlying disease processes.