SARS-CoV-2 infection remodels the host protein thermal stability landscape

Tapioca: a platform for predicting de novo protein-protein interactions in dynamic contexts

Protein-protein interactions (PPIs) drive cellular processes and responses to environmental cues, reflecting the cellular state. Here we develop Tapioca, an ensemble machine learning framework for studying global PPIs in dynamic contexts. Tapioca predicts de novo interactions by integrating mass spectrometry interactome data from thermal/ion denaturation or cofractionation workflows with protein properties and tissue-specific functional networks. Focusing on the thermal proximity coaggregation method, we improved the experimental workflow. Finely tuned thermal denaturation afforded increased throughput, while cell lysis optimization enhanced protein detection from different subcellular compartments. The Tapioca workflow was next leveraged to investigate viral infection dynamics. Temporal PPIs were characterized during the reactivation from latency of the oncogenic Kaposi's sarcoma-associated herpesvirus. Together with functional assays, NUCKS was identified as a proviral hub protein, and a broader role was uncovered by integrating PPI networks from alpha- and betaherpesvirus infections. Altogether, Tapioca provides a web-accessible platform for predicting PPIs in dynamic contexts.

Transcriptomics-inferred dynamics of SARS-CoV-2 interactions with host epithelial cells

Virus-host interactions can reveal potentially effective and selective therapeutic targets for treating infection. Here, we performed an integrated analysis of the dynamics of virus replication and the host cell transcriptional response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection using human Caco-2 colon cancer cells as a model. Time-resolved RNA sequencing revealed that, upon infection, cells immediately transcriptionally activated genes associated with inflammatory pathways that mediate the antiviral response, which was followed by an increase in the expression of genes involved in ribosome and mitochondria function, thus suggesting rapid alterations in protein production and cellular energy supply. At later stages, between 24 and 48 hours after infection, the expression of genes involved in metabolic processes-in particular, those related to xenobiotic metabolism-was decreased. Mathematical modeling incorporating SARS-CoV-2 replication suggested that SARS-CoV-2 proteins inhibited the host antiviral response and that virus transcripts exceeded the translation capacity of the host cells. Targeting kinase-dependent pathways that exhibited increases in transcription in host cells was as effective as a virus-targeted inhibitor at repressing viral replication. Our findings in this model system delineate a sequence of SARS-CoV-2 virus-host interactions that may facilitate the identification of druggable host pathways to suppress infection.

Multidimensional Landscape of SA-AKI Revealed by Integrated Proteomics and Metabolomics Analysis

Sepsis-associated acute kidney injury (SA-AKI) is a severe and life-threatening condition with high morbidity and mortality among emergency patients, and it poses a significant risk of chronic renal failure. Clinical treatments for SA-AKI remain reactive and non-specific, lacking effective diagnostic biomarkers or treatment targets. In this study, we established an SA-AKI mouse model using lipopolysaccharide (LPS) and performed proteomics and metabolomics analyses. A variety of bioinformatic analyses, including gene set enrichment analysis (GSEA), weighted gene co-expression network analysis (WGCNA), protein and protein interactions (PPI), and MetaboAnalyst analysis, were conducted to investigate the key molecules of SA-AKI. Integrated proteomics and metabolomics analysis revealed that sepsis led to impaired renal mitochondrial function and metabolic disorders. Immune-related pathways were found to be activated in kidneys upon septic infection. The catabolic products of polyamines accumulated in septic kidneys. Overall, our integrated analysis provides a multidimensional understanding of SA-AKI and identifies potential pathways for this condition.

Statistical Detection of Differentially Abundant Proteins in Experiments with Repeated Measures Designs and Isobaric Labeling

Repeated measures experimental designs, which quantify proteins in biological subjects repeatedly over multiple experimental conditions or times, are commonly used in mass spectrometry-based proteomics. Such designs distinguish the biological variation within and between the subjects and increase the statistical power of detecting within-subject changes in protein abundance. Meanwhile, proteomics experiments increasingly incorporate tandem mass tag (TMT) labeling, a multiplexing strategy that gains both relative protein quantification accuracy and sample throughput. However, combining repeated measures and TMT multiplexing in a large-scale investigation presents statistical challenges due to unique interplays of between-mixture, within-mixture, between-subject, and within-subject variation. This manuscript proposes a family of linear mixed-effects models for differential analysis of proteomics experiments with repeated measures and TMT multiplexing. These models decompose the variation in the data into the contributions from its sources as appropriate for the specifics of each experiment, enable statistical inference of differential protein abundance, and recognize a difference in the uncertainty of between-subject versus within-subject comparisons. The proposed family of models is implemented in the R/Bioconductor package MSstatsTMT v2.2.0. Evaluations of four simulated datasets and four investigations answering diverse biological questions demonstrated the value of this approach as compared to the existing general-purpose approaches and implementations.

CETSA and thermal proteome profiling strategies for target identification and drug discovery of natural products

BACKGROUND

Monitoring target engagement at various stages of drug development is essential for natural product (NP)-based drug discovery and development. The cellular thermal shift assay (CETSA) developed in 2013 is a novel, broadly applicable, label-free biophysical assay based on the principle of ligand-induced thermal stabilization of target proteins, which enables direct assessment of drug-target engagement in physiologically relevant contexts, including intact cells, cell lysates and tissues. This review aims to provide an overview of the work principles of CETSA and its derivative strategies and their recent progress in protein target validation, target identification and drug lead discovery of NPs.

METHODS

A literature-based survey was conducted using the Web of Science and PubMed databases. The required information was reviewed and discussed to highlight the important role of CETSA-derived strategies in NP studies.

RESULTS

After nearly ten years of upgrading and evolution, CETSA has been mainly developed into three formats: classic Western blotting (WB)-CETSA for target validation, thermal proteome profiling (TPP, also known as MS-CETSA) for unbiased proteome-wide target identification, and high-throughput (HT)-CETSA for drug hit discovery and lead optimization. Importantly, the application possibilities of a variety of TPP approaches for the target discovery of bioactive NPs are highlighted and discussed, including TPP-temperature range (TPP-TR), TPP-compound concentration range (TPP-CCR), two-dimensional TPP (2D-TPP), cell surface-TPP (CS-TPP), simplified TPP (STPP), thermal stability shift-based fluorescence difference in 2D gel electrophoresis (TS-FITGE) and precipitate supported TPP (PSTPP). In addition, the key advantages, limitations and future outlook of CETSA strategies for NP studies are discussed.

CONCLUSION

The accumulation of CETSA-based data can significantly accelerate the elucidation of the mechanism of action and drug lead discovery of NPs, and provide strong evidence for NP treatment against certain diseases. The CETSA strategy will certainly bring a great return far beyond the initial investment and open up more possibilities for future NP-based drug research and development.

Hsp90 could promote BmNPV proliferation by interacting with Actin-4 and enhance its expression

As a highly infectious pathogen, Bombyx mori nuclear polyhedrosis virus (BmNPV) has a high lethality rate in silkworm. Our previous study have confirmed that Hsp90 plays a positive role in BmNPV proliferation and Hsp90 inhibitor, geldanamycin (GA) can decrease the replication of BmNPV in vitro. However, its molecular mechanism is not fully understood. In the present study, first, we found that GA could inhibit the proliferation of BmNPV in a dose-dependent manner and delay the pathogenesis of BmNPV in vivo possibly by altering the transcript level of genes associated with cell apoptosis and immune pathways. Furthermore, by immunoprecipitation (IP) and mass spectrometry analysis, we identified a series of proteins potentially interacting with Hsp90 including two BmNPV encoded proteins. Subsequently, by Co-IP we confirmed the interaction between BmActin-4 and BmHsp90. Knocking down Bmhsp90 by small interfering RNA inhibited the protein expression level of BmActin-4. Over-expression of Bmactin-4 promoted the replication of BmNPV whereas knockdown of Bmactin-4 suppressed BmNPV replication. In addition, decrease of the transcript level of Bmhsp90 in Bmactin-4 knocking down BmN cells was also detected. Taken together, BmHsp90 can interact with BmActin-4 and promote its expression, thereby promoting BmNPV proliferation. Our findings may enrich the molecular mechanism of Hsp90 for promoting virus proliferation and provide new clues to elucidate the interact mechanism between silkworm and virus.

Targeting heat shock proteins 90 and 70: A promising remedy for both autoimmune bullous diseases and COVID-19

Heat shock proteins (Hsps), including Hsp90 and Hsp70, are intra- and extracellular molecules implicated in cellular homeostasis and immune processes and are induced by cell stress such as inflammation and infection. Autoimmune bullous disorders (AIBDs) and COVID-19 represent potentially life-threatening inflammatory and infectious diseases, respectively. A significant portion of AIBDs remain refractory to currently available immunosuppressive therapies, which may represent a risk factor for COVID-19, and suffer from treatment side-effects. Despite advances in vaccination, there is still a need to develop new therapeutic approaches targeting SARS-CoV-2, especially considering vaccine hesitancy, logistical distribution challenges, and breakthrough infections. In this mini review, we briefly summarize the role of targeting Hsp90/70 as a promising double-edged sword in the therapy of AIBDs and COVID-19.

Decoding the Role of Temperature in RNA Virus Infections

RNA viruses include respiratory viruses, such as coronaviruses and influenza viruses, as well as vector-borne viruses, like dengue and West Nile virus. RNA viruses like these encounter various environments when they copy themselves and spread from cell to cell or host to host. Ex vivo differences, such as geographical location and humidity, affect their stability and transmission, while in vivo differences, such as pH and host gene expression, impact viral receptor binding, viral replication, and the host immune response against the viral infection. A critical factor affecting RNA viruses both ex vivo and in vivo, and defining the outcome of viral infections and the direction of viral evolution, is temperature. In this minireview, we discuss the impact of temperature on viral replication, stability, transmission, and adaptation, as well as the host innate immune response. Improving our understanding of how RNA viruses function, survive, and spread at different temperatures will improve our models of viral replication and transmission risk analyses.

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.

Target Discovery for Host-Directed Antiviral Therapies: Application of Proteomics Approaches

Current epidemics, such as AIDS or flu, and the emergence of new threatening pathogens, such as the one causing the current coronavirus disease 2019 (COVID-19) pandemic, represent major global health challenges. While vaccination is an important part of the arsenal to counter the spread of viral diseases, it presents limitations and needs to be complemented by efficient therapeutic solutions. Intricate knowledge of host-pathogen interactions is a powerful tool to identify host-dependent vulnerabilities that can be exploited to dampen viral replication. Such host-directed antiviral therapies are promising and are less prone to the development of drug-resistant viral strains. Here, we first describe proteomics-based strategies that allow the rapid characterization of host-pathogen interactions. We then discuss how such data can be exploited to help prioritize compounds with potential host-directed antiviral activity that can be tested in preclinical models.

Progress Identifying and Analyzing the Human Proteome: 2021 Metrics from the HUPO Human Proteome Project

The 2021 Metrics of the HUPO Human Proteome Project (HPP) show that protein expression has now been credibly detected (neXtProt PE1 level) for 18 357 (92.8%) of the 19 778 predicted proteins coded in the human genome, a gain of 483 since 2020 from reports throughout the world reanalyzed by the HPP. Conversely, the number of neXtProt PE2, PE3, and PE4 missing proteins has been reduced by 478 to 1421. This represents remarkable progress on the proteome parts list. The utilization of proteomics in a broad array of biological and clinical studies likewise continues to expand with many important findings and effective integration with other omics platforms. We present highlights from the Immunopeptidomics, Glycoproteomics, Infectious Disease, Cardiovascular, Musculo-Skeletal, Liver, and Cancers B/D-HPP teams and from the Knowledgebase, Mass Spectrometry, Antibody Profiling, and Pathology resource pillars, as well as ethical considerations important to the clinical utilization of proteomics and protein biomarkers.

Drug Target Identification in Tissues by Thermal Proteome Profiling

Drug target deconvolution can accelerate the drug discovery process by identifying a drug's targets (facilitating medicinal chemistry efforts) and off-targets (anticipating toxicity effects or adverse drug reactions). Multiple mass spectrometry-based approaches have been developed for this purpose, but thermal proteome profiling (TPP) remains to date the only one that does not require compound modification and can be used to identify intracellular targets in living cells. TPP is based on the principle that the thermal stability of a protein can be affected by its interactions. Recent developments of this approach have expanded its applications beyond drugs and cell cultures to studying protein-drug interactions and biological phenomena in tissues. These developments open up the possibility of studying drug treatment or mechanisms of disease in a holistic fashion, which can result in the design of better drugs and lead to a better understanding of fundamental biology. Expected final online publication date for the Annual Review of Pharmacology and Toxicology, Volume 62 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Role of Heat Shock Proteins (HSP70 and HSP90) in Viral Infection

Heat shock proteins (HSPs) are a large group of chaperones found in most eukaryotes and bacteria. They are responsible for the correct protein folding, protection of the cell against stressors, presenting immune and inflammatory cytokines; furthermore, they are important factors in regulating cell differentiation, survival and death. Although the biological function of HSPs is to maintain cell homeostasis, some of them can be used by viruses both to fold their proteins and increase the chances of survival in unfavorable host conditions. Folding viral proteins as well as replicating many different viruses are carried out by, among others, proteins from the HSP70 and HSP90 families. In some cases, the HSP70 family proteins directly interact with viral polymerase to enhance viral replication or they can facilitate the formation of a viral replication complex and/or maintain the stability of complex proteins. It is known that HSP90 is important for the expression of viral genes at both the transcriptional and the translational levels. Both of these HSPs can form a complex with HSP90 and, consequently, facilitate the entry of the virus into the cell. Current studies have shown the biological significance of HSPs in the course of infection SARS-CoV-2. A comprehensive understanding of chaperone use during viral infection will provide new insight into viral replication mechanisms and therapeutic potential. The aim of this study is to describe the molecular basis of HSP70 and HSP90 participation in some viral infections and the potential use of these proteins in antiviral therapy.

Individual COVID-19 disease trajectories revealed by plasma proteomics

Since the start of 2020, the world has been upended by the pandemic caused by the severe acute respiratory coronavirus type 2 (SARS‐CoV‐2), the causative agent of coronavirus disease 2019 (COVID‐19). It has not only led to a tragic loss of life and terrible economic costs but has also been met with an unprecedented response of the scientific and medical communities. In an effort to better understand this viral infection, scientists around the world generated the largest surge in research in documented history for any topic (Lever & Altman, 2021). A part of this work has included the need to better understand the impact of the virus on human proteins—the key machinery of the cell—and human physiology. In their recent study, Geyer and colleagues (Geyer et al, 2021) analyzed a total of 720 proteomes from longitudinal serum samples of 31 hospitalized COVID‐19 patients and control individuals with COVID‐19‐like symptoms but not infected with SARS‐CoV‐2, providing a comprehensive characterization of the plasma proteome changes along the time course of infection.