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PubMed2026

Molecular mechanisms of plant thermal response: from signal transduction and epigenetic regulation to signaling integration.

Global warming intensification elevates heat stress to one of the major threats to crop productivity. This review synthesizes recent advances in understanding the mechanisms governing plant responses to both moderate and acute heat stress, with a focus on the integration of epigenetic regulation and signaling networks that underpin thermal adaptation. This review highlights how transcription factors PHYTOCHROME-INTERACTING FACTOR 4 (PIF4, during thermomorphogenesis) and HEAT SHOCK FACTOR A1s (HSFA1s, in heat shock responses) orchestrate plant adaptive growth through crosstalk among light, circadian, and hormone signaling pathways. Importantly, epigenetic mechanisms, including histone variant H2A.Z dynamics and histone modification reprogramming, function as central regulators of thermal plasticity. Key among these processes are HSFA2-mediated chromatin remodeling and small interfering RNA (siRNA)-dependent control of transgenerational thermomemory. Despite this progress, fundamental questions persist regarding temperature sensing, HSFA1s activation dynamics, and stress signal integration. Multi-omics and synthetic biology approaches are proposed to be pivotal in deciphering conserved principles of plant thermal resilience, ultimately providing a theoretical foundation and molecular breeding strategies for climate-smart crops.

Epigenesis, Genetic↗

PubMed2026

Prdm15 deficiency perturbs hematopoietic stem and progenitor cell homeostasis.

The maintenance of homeostasis in hematopoietic stem and progenitor cells (HSPCs) is essential for the proper development of the entire hematopoietic system. However, the mechanisms underlying this regulatory equilibrium remain elusive. Here, we report that Prdm15 deficiency in HSPCs induces the accumulation of immature hematopoietic stem cells in mice. A series of transplantation assays shows that these cells display impaired reconstitution capacity and competitive fitness, which are associated with abnormal differentiation trajectories and transcriptional alterations identified by single-cell RNA sequencing. Mechanistically, integrated multi-omics analyses including ATAC-seq and CUT&Tag sequencing of HSPCs indicate that Prdm15 deficiency induces significant transcriptional and epigenetic alterations, particularly affecting the methyltransferase KMT2C and altering H3K4me1 and H3K27ac modifications at the promoters of hematopoietic developmental genes. Collectively, our findings establish PRDM15 as a critical epigenetic regulator of HSPCs, offering valuable insights into the molecular mechanisms underlying hematopoietic homeostasis.

Cell differentiation↗

PubMed2026

Genome-wide interactions with cadmium exposure in dysglycemia: Populational effects and molecular insights.

Dysglycemia is a complex metabolic disorder governed by the interplay between environmental exposures and genetic factors, yet the precise molecular mechanisms driving these gene-environment (G×E) interactions remains poorly understood. Here, we characterized the population-level landscape and molecular causality underlying the interactions between cadmium (Cd), a widespread environmental toxicant, and genetic susceptibility loci in dysglycemia. By conducting a Genome-wide Environmental Interaction (GWEI) study within a sub-cohort of the China National Human Biomonitoring (CNHBM) cohort (N = 1298), we identified 29 genetic risk loci that significantly interact with Cd burden to exacerbate elevated fasting plasma glucose levels. Functional enrichment integrated with metabolomic profiling unmasked a profound multi-omics convergence, positioning epigenetic modifications (e.g. H3K27me3) and zinc-finger transcription factors (e.g. OVOL2, KLFs) as central regulatory hubs that disrupt metabolic homeostasis. To establish causality, we demonstrated that the rs11743277 A>T variant at the lead G×E locus functions as a Cd-responsive enhancer element, facilitating recruitment of TEAD3 and upregulating TICAM2 expression in CRISPR/Cas9-edited HepG2 cells, especially upon Cd exposure. This initiates a TICAM2-mediated inflammatory response, with elevated pro-inflammatory cytokines (IFN-β, TNF-α, IL-6) impairing downstream insulin signaling and glucose utilization. Collectively, these findings establish a robust paradigm for G×E interactions in complex metabolic disorders, revealing how environmental stressors reprogram genetic susceptibilities through molecular checkpoints and paving the way for tailored, precision-prevention strategies in environmental health.

CRISPR/Cas9 editing↗

PubMed2004

A family-based approach reveals the function of residues in the nuclear receptor ligand-binding domain.

Literature studies, 3D structure data, and a series of sequence analysis techniques were combined to reveal important residues in the structure and function of the ligand-binding domain of nuclear hormone receptors. A structure-based multiple sequence alignment allowed for the seamless combination of data from many different studies on different receptors into one single functional model. It was recently shown that a combined analysis of sequence entropy and variability can divide residues in five classes; (1) the main function or active site, (2) support for the main function, (3) signal transduction, (4) modulator or ligand binding and (5) the rest. Mutation data extracted from the literature and intermolecular contacts observed in nuclear receptor structures were analyzed in view of this classification and showed that the main function or active site residues of the nuclear receptor ligand-binding domain are involved in cofactor recruitment. Furthermore, the sequence entropy-variability analysis identified the presence of signal transduction residues that are located between the ligand, cofactor and dimer sites, suggesting communication between these regulatory binding sites. Experimental and computational results agreed well for most residues for which mutation data and intermolecular contact data were available. This allows us to predict the role of the residues for which no functional data is available yet. This study illustrates the power of family-based approaches towards the analysis of protein function, and it points out the problems and possibilities presented by the massive amounts of data that are becoming available in the "omics era". The results shed light on the nuclear receptor family that is involved in processes ranging from cancer to infertility, and that is one of the more important targets in the pharmaceutical industry.

Amino Acids↗

PubMed2006

The dynamics of the LPS triggered inflammatory response of murine microglia under different culture and in vivo conditions.

Overall, the inflammatory potential of lipopolysaccharide (LPS) in vitro and in vivo was investigated using different omics technologies. We investigated the hippocampal response to intracerebroventricular (i.c.v) LPS in vivo, at both the transcriptional and protein level. Here, a time course analysis of interleukin-6 (IL-6) and monocyte chemotactic protein-1 (MCP-1) showed a sharp peak at 4 h and a return to baseline at 16 h. The expression of inflammatory mediators was not temporally correlated with expression of the microglia marker F4/80, which did not peak until 2 days after LPS injection. Of 480 inflammation-related genes present on a microarray, 29 transcripts were robustly up-regulated and 90% of them were also detected in LPS stimulated primary microglia (PM) cultures. Further in vitro to in vivo comparison showed that the counter regulation response observed in vivo was less evident in vitro, as transcript levels in PM decreased relatively little over 16 h. This apparent deficiency of homeostatic control of the innate immune response in cultures may also explain why a group of genes comprising tnf receptor associated factor-1, endothelin-1 and schlafen-1 were regulated strongly in vitro, but not in vivo. When the overall LPS-induced transcriptional response of PM was examined on a large Affymetrix chip, chemokines and cytokines constituted the most strongly regulated and largest groups. Interesting new microglia markers included interferon-induced protein with tetratricopeptide repeat (ifit), immune responsive gene-1 (irg-1) and thymidylate kinase family LPS-inducible member (tyki). The regulation of the former two was confirmed on the protein level in a proteomics study. Furthermore, conspicuous regulation of several gene clusters was identified, for instance that of genes pertaining to the extra-cellular matrix and enzymatic regulation thereof. Although most inflammatory genes induced in vitro were transferable to our in vivo model, the observed discrepancy for some genes potentially represents regulatory factors present in the central nervous system (CNS) but not in vitro.

Animals↗

PubMed2026

Osteoarthritis Year in Review 2026: Genetics, genomics and epigenetics.

OBJECTIVE: The purpose of this narrative review is to highlight advances made over the past 12 months in the field of osteoarthritis (OA) genetics, genomics and epigenomics, with a particular focus on the interpretation of OA risk loci through functional genomic and regulatory approaches. DESIGN: PubMed and Europe PMC were searched to identify studies relevant to OA genetics, genomics and epigenomics published between 1st March 2025 and 30th April 2026. Searches used combinations of terms relating to genetics, genomics, epigenomics, functional genomics, molecular quantitative trait loci, chromatin accessibility and enhancer biology. Studies were limited to human subjects and English-language publications, with additional articles identified through citation screening and expert knowledge of the field. RESULTS: Over the past year, the field has continued to transition from large-scale locus discovery towards biological interpretation of OA genetic risk. Major advances included the largest OA genome-wide association study to date, further development of polygenic risk score approaches, and increasing integration of molecular quantitative trait loci, chromatin accessibility, and enhancer biology datasets to prioritise effector genes and elucidate regulatory mechanisms. Several studies highlighted the highly context-dependent nature of OA genetic risk mechanisms, demonstrating that distinct tissues, cell types, and regulatory layers can identify different candidate effector genes at the same locus. Additional developments included increasing application of singlecell and multi-omic technologies to study OA-relevant tissues. CONCLUSION: Recent advances in OA genetics have shifted the field from locus discovery towards mechanistic interpretation. Emerging evidence demonstrates that the biological consequences of genetic variation are highly dependent upon tissue, cell state and disease context, with different functional genomic approaches often prioritising distinct candidate genes and regulatory mechanisms at the same susceptibility locus. Together, these findings suggest that OA risk loci should increasingly be viewed as dynamic regulatory systems rather than simple variant-to-gene relationships, providing a framework for future studies aimed at resolving causal mechanisms, defining disease endotypes, and identifying therapeutic targets.

Genetics↗

PubMed2026

Clinical applications of digital twin technology in In Vitro Fertilisation.

BACKGROUND: Digital twin technology, originating from aerospace and manufacturing industries, has emerged as a transformative tool in healthcare. In vitro fertilisation (IVF) faces persistent challenges including suboptimal embryo selection, unpredictable treatment outcomes, and limited personalisation of protocols. Despite advances in assisted reproductive technology, existing literature exhibits fragmentation: artificial intelligence applications in embryo selection, ovarian stimulation, and endometrial assessment have been developed independently without systematic integration into comprehensive treatment frameworks. Digital twin technology offers unprecedented opportunities to create virtual replicas of biological systems, enabling real-time monitoring, predictive modelling, and personalised treatment strategies. AIM: This narrative review aims to critically examine the current applications of digital twin technology in IVF, evaluate its potential benefits and limitations, synthesize existing evidence into an integrative conceptual model, and identify future directions for implementation in reproductive medicine. METHOD: A comprehensive narrative review was conducted using PubMed, Scopus, Web of Science, and IEEE Xplore databases. A narrative review approach was selected over systematic review to accommodate the heterogeneity of evidence types in this emerging field, including theoretical frameworks, simulation studies, and proof-of-concept implementations that would be excluded from systematic reviews. Search terms included "digital twin," "IVF," "in vitro fertilisation," "assisted reproductive technology," "embryo selection," and "predictive modelling." Studies published between 2015 and 2025 were included, focusing on original research articles, systematic reviews, and proof-of-concept studies describing digital twin applications in reproductive medicine. RESULTS: Digital twin technology in IVF demonstrates significant potential across multiple domains including embryo development simulation, ovarian response prediction, endometrial receptivity modelling, and personalised stimulation protocols. Current applications integrate artificial intelligence, machine learning algorithms, time-lapse imaging, and omics data to create comprehensive virtual models. Early evidence suggests improvements in embryo selection accuracy, ovarian response prediction, and treatment protocol optimization, though large-scale randomized controlled trials remain limited. Implementation challenges include data integration complexity, computational requirements, regulatory considerations, and validation requirements. CONCLUSION: Digital twin technology represents a paradigm shift in IVF practice, offering personalised, predictive, and precision medicine approaches. This review synthesizes existing evidence to propose an integrative conceptual model for digital twin implementation across the IVF treatment spectrum, identifies critical knowledge gaps, and establishes research priorities to advance clinical translation. Despite current limitations, continued advancement promises improved success rates and patient outcomes.

Humans↗

PubMed2026

Proteomics at scale: Bottlenecks and opportunities for early-career researchers in a fast developing field.

The field of proteomics has rapidly evolved over the last five years enabled by rapid advances in instrumentation and computation. At the same time, the proteomics community is also growing. This is reflected by the increasing participation in international conferences such as those organized by the European Proteomics Association and the Human Proteome Organization. These events provide early-career researchers with unique opportunities to exchange ideas, develop collaborations, and build networks that support professional development. One such network is the Young Proteomics Investigators Club, a European initiative supported by European Proteomics Association and led by early-career researchers. In this Community-Driven project, we investigate recent trends in proteomics by screening conference abstracts and evaluating the session attendance at Human Proteome Organization Congresses and European Proteomics Association conferences. Based on these analyses, we identified five areas that, from our perspective, are shaping the current trends in proteomics: clinical proteomics, proteomics of post-translational modifications, single-cell proteomics, systems biology and multi-omics, and computational proteomics. For each area, we highlight both unique challenges and identify a common theme: a shift from exploratory studies with manageable sample numbers towards large screenings and cohorts and the generation of big data, which often comes with the lack of computational support, organizational networks, and infrastructure. In this light, we describe the unique challenges and opportunities faced by early-career researchers. We point to actionable directions for enabling reproducible and transparent proteomics as well as community-driven projects and initiatives, which are often providing training and support. SIGNIFICANCE: In this perspective, the Young Proteomics Investigators Club (YPIC) discusses advances in analytical developments and computational approaches in proteomics research. Based on empirical analysis of recent European Proteomics Association conference and Human Proteome Organization congresses contributions, we identify clinical, single-cell, post-translational and systems-level proteomics as the research areas that have gained most momentum in the last three to five years. What makes this work distinctive is that it is written by and for early-career researchers, thereby uniquely identifying where momentum, challenges, and unmet needs converge for the newest generation of proteomics researchers. Rather than cataloguing advances, we examine the widening gap between what modern proteomics can generate and what individual researchers can realistically process, validate, and interpret. We describe specific structural barriers including access to high performance computing, limited formal training in scalable data analysis, the need for unified benchmarking standards and navigating clinical collaboration frameworks. We then highlight opportunities for the field, such as community-curated benchmarks, interdisciplinary mentorship models, and shared computational infrastructure. By making these challenges explicit from an early-career researchers standpoint, we aim to inform how training, funding, and community initiatives can be shaped to support the next generation of proteomics researchers.

Proteomics↗

PubMed2026

Integrated salivary proteomic and metabolomic analyses reveal molecular characterization and novel biomarker panels of chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is a respiratory disorder characterized by chronic inflammation, oxidative stress, and metabolic dysregulation. The lack of convenient and easily-accessible non-invasive diagnostic approaches remains a major clinical challenge. This study applied an integrated saliva-based proteomic and untargeted metabolomic strategy to identify potential biomarkers for COPD classification. Comprehensive multi-omics analyses identified 225 differentially abundant proteins and 60 differentially abundant metabolites between patients with COPD and healthy controls, including 24 biologically relevant endogenous metabolites. Functional enrichment analyses revealed pronounced dysregulation of mitochondrial energy metabolism, redox homeostasis, lipid remodeling, and inflammatory-related pathways in COPD. By integrating salivary proteomic and metabolomic biomarkers, a stepwise feature selection combined with LASSO logistic regression was used to construct diagnostic models, yielding an optimized biomarker panel consisting of 11 proteins and 2 endogenous metabolites. This integrated model achieved excellent diagnostic performance, with an area under the ROC curve of 0.96. Collectively, these findings demonstrate that integrated salivary proteomic and metabolomic profiling provides a robust, non-invasive approach for COPD classification and offers a promising foundation for the development of biosensor-based diagnostic platforms and early disease detection. SIGNIFICANCE: Chronic obstructive pulmonary disease (COPD) remains a major global health burden. Current diagnostic approaches rely largely on spirometry and clinical assessment, which are limited in sensitivity for early-stage disease and unsuitable for large-scale screening. This study employs an integrated saliva-based proteomic and metabolomic strategy to identify non-invasive biomarkers for COPD classification. Our findings reveal coordinated dysregulation of mitochondrial energy metabolism, redox homeostasis, and lipid remodeling in COPD, highlighting the interconnected roles of metabolic reprogramming, oxidative stress, and inflammation in disease pathophysiology. Notably, a robust diagnostic panel comprising 11 proteins and 2 endogenous metabolites was established, achieving excellent classification performance (AUC of 0.96). To our knowledge, the integrated application of salivary proteomics and metabolomics for COPD diagnosis remains largely unexplored, underscoring the significance and translational potential of our findings.

Humans↗

PubMed2026

Single-organ proteomics in Drosophila melanogaster larva.

The combination of genetic accessibility, organ complexity, evolutionary conservation, and cost-efficiency makes Drosophila melanogaster (Dm) a well-known model system for biomedical and fundamental biological research. Proteomic analysis of single organs enables the identification and quantification of proteins expressed in specific organs. This will help to uncover specific biological functions and unique protein profiles that are not detectable in whole-organism analyses. In this study we have isolated single organs form Dm larvae, and we have performed a deep proteomics mapping by following a minimal manipulation preparation procedure. The combined dataset across all organs comprised 9132 identified proteins. As anticipated, principal component analysis (PCA) revealed clear separation between the proteomes of most organs, confirming distinct protein profiles. These findings demonstrate the applicability of the sample preparation strategy for high-resolution proteomic characterization of individual organs in Drosophila. Given the extensive genetic tools available for this model organism, our approach has the potential to open new avenues for proteomic studies in Drosophila melanogaster and any other biological systems where the sample amount is limiting. SIGNIFICANCE STATEMENT: Drosophila melanogaster is a well-known model system for biomedical and fundamental biological research that serves as a valuable in vivo model organism due to its high degree of evolutionary conservation with higher vertebrates, tractable genetics, and logistical efficiency. However, the proteome of Drosophila at single organ level has been elusive to date, due to several factors like low sensitivity of previous generation mass spectrometers and sample preparation procedures, difficult isolation of some organs. In this study we have applied a compilation of advanced methods including minimal sample manipulation together with simple, straightforward and efficient protein extraction and digestion methods. Obtained peptides were minimally handled to be analyzed by applying specific and sensitive nLC methods coupled on-line to state-of-the-art MS/MS system. Altogether, the applied strategy allowed us to get the first single organ study to date for this animal. These datasets represent a significative resource for future genomic, transcriptomic and proteomic studies in Drosophila, as multi-omic integration requires deep proteomics to translate data into functional biochemistry, and serves as a critical bridge and an indispensable standalone resource across the genomic, transcriptomic, and proteomic landscapes.

Animals↗

PubMed2026

Lower androgen sulfate metabolites in women with hypermobile Ehlers-Danlos syndrome may be associated with changed metabolism and disposition.

Hypermobile Ehlers-Danlos Syndrome (hEDS), characterized by joint hypermobility and multisystem involvement, is the most common type of EDS. Its comorbidities are wide-ranging, reflecting the involvement of connective tissue and its role in a multitude of processes. hEDS has been hypothesized to have hormonal aspects since the disorder is diagnosed more often in women and symptom changes closely correlate with hormonal shifts. To better understand the etiology and biochemical changes in hEDS and its comorbidities, a multiple-omics study was performed in women, controls (n = 45) and those with hEDS (n = 45), alongside the collection of questionnaires related to symptom severity. Metabolomic evaluation was performed on serum samples and RNA isolated from fibroblasts cultured from skin punches was analyzed for transcriptomics. Samples from hEDS patients had statistically significantly lower levels of multiple androgen sulfate metabolites, compared with controls, driven largely by participants aged 30-49. Changes to other classes of steroid hormones (corticosteroids, progestogens, and estrogens) were largely not significant between hEDS and control groups. Transcriptomics of skin fibroblasts from hEDS patients revealed downregulation of multiple enzymes involved in biosynthesis, metabolism, and disposition of androgens, compared with controls. Multiple steroid hormones correlated with symptoms surveyed in 18-29 year old participants with hEDS. Shifts in steroid hormone metabolites in hEDS compared with controls may be due to changes to metabolism and disposition, but more validation is necessary to be conclusive. This data provides insights into the unclear links between steroid hormones and hEDS and its comorbidities.

Humans↗

PubMed2025

Implications of EGFR expression on EGFR signaling dependency and adaptive immunity against EGFR-mutated lung adenocarcinoma.

BACKGROUND: In EGFR-mutated lung adenocarcinoma (EGFRm LUAD), EGFR mutations do not necessarily result in increased EGFR expression (EGFR-exp), which differs among patients. However, the factors influencing EGFR-exp and the impact of EGFR-exp on tumor characteristics in patients with EGFRm LUAD remain unclear. PATIENTS AND METHODS: Whole-exome and RNA sequencing were performed for patients with early- and advanced-stage EGFRm LUAD. The patients were classified into low or high EGFR-exp groups based on the median transcripts per million. We retrospectively examined the association between EGFR-exp, genomic characteristics, downstream EGFR signaling activity, tumor microenvironment (TME) status, and clinical outcomes. RESULTS: This study included 450 and 45 patients in the early- and advanced-stage cohorts, respectively. In both cohorts, the EGFR-exp low group exhibited a lower incidence of TP53 co-mutations and EGFR amplification and a higher incidence of EGFR subclonal mutations than the EGFR-exp high group. Furthermore, downstream EGFR signaling pathways, such as the MAPK signaling, were less activated in the EGFR-exp low group. However, this group showed significantly enriched adaptive immune response pathways (Q < 0.0001) and an immune-inflamed TME. Additionally, a low EGFR-exp was a significantly favorable factor for postoperative relapse (odds ratio [OR], 0.6; P = 0.04). However, in the advanced-stage cohort, a low EGFR-exp was a significant risk factor for non-responders to osimertinib (OR, 17.5; P = 0.03). CONCLUSIONS: In EGFRm LUAD, significant associations were observed between EGFR-exp levels and both EGFR signaling pathways and adaptive immune status, which in turn influence clinical outcomes. This large-scale multi-omics analysis highlights the heterogeneity among patients with EGFRm LUAD and emphasizes the need to assess EGFR-exp levels alongside mutation status for optimal treatment strategies in EGFRm LUAD.

Humans↗

PubMed2024

Proteome-Scale Tissue Mapping Using Mass Spectrometry Based on Label-Free and Multiplexed Workflows.

Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in healthy and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in a whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of ∼3500 proteins at a spatial resolution of 50 μm and the highest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provides robust protein quantifications in identifying differentially abundant proteins and spatially covariable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables the identification of protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial coexpression analysis.

Proteome↗

PubMed2024

Bridging the Gap From Proteomics Technology to Clinical Application: Highlights From the 68th Benzon Foundation Symposium.

The 68th Benzon Foundation Symposium brought together leading experts to explore the integration of mass spectrometry-based proteomics and artificial intelligence to revolutionize personalized medicine. This report highlights key discussions on recent technological advances in mass spectrometry-based proteomics, including improvements in sensitivity, throughput, and data analysis. Particular emphasis was placed on plasma proteomics and its potential for biomarker discovery across various diseases. The symposium addressed critical challenges in translating proteomic discoveries to clinical practice, including standardization, regulatory considerations, and the need for robust "business cases" to motivate adoption. Promising applications were presented in areas such as cancer diagnostics, neurodegenerative diseases, and cardiovascular health. The integration of proteomics with other omics technologies and imaging methods was explored, showcasing the power of multimodal approaches in understanding complex biological systems. Artificial intelligence emerged as a crucial tool for the acquisition of large-scale proteomic datasets, extracting meaningful insights, and enhancing clinical decision-making. By fostering dialog between academic researchers, industry leaders in proteomics technology, and clinicians, the symposium illuminated potential pathways for proteomics to transform personalized medicine, advancing the cause of more precise diagnostics and targeted therapies.

Proteomics↗

PubMed2026

3D Proteomics: Structural, Functional, Chemical and Biomarker Discovery Proteomics With LiP-MS.

Protein structural dynamics drive changes in protein function, making the capture of such dynamics essential for interrogating biological systems. Here we review limited proteolysis coupled to mass spectrometry (LiP-MS), a structural and chemical proteomics method that uses changes in susceptibility to protease cleavage to profile proteome-wide protein structural changes within complex biological samples. In the decade since its development, LiP-MS has become a broadly used structural proteomics method, with peptide-level resolution. It has identified drug targets, delineated altered cellular pathways in response to complex perturbations, revealed structural information on otherwise challenging protein targets, and demonstrated the new concept of structural biomarkers of disease. Because LiP-MS simultaneously probes numerous types of molecular events, such as molecular binding, changes in enzyme activity, chemical modifications, allosteric conformational changes, aggregation, and unfolding, it supports a new proteomics workflow which we term 3D proteomics. This workflow enables the detection of specific functional sites within proteins that are altered upon perturbation, thereby guiding the generation of molecular hypotheses. Further, by globally profiling structural in addition to protein abundance changes, LiP-MS has proven able to greatly increase the information content of functional proteomics screens. In sum, LiP-MS has supported the development of a novel conceptual framework for generating, visualizing, and interpreting structural proteomics data with peptide level resolution, thereby comprehensively probing biological systems. Here we survey the applications of LiP-MS, discuss methodological variants developed by us and others, and describe the use of this new type of omics readout for structural, functional, chemical, and biomarker discovery proteomics.

Proteomics↗

PubMed2026

Sec and Tat Mediated Secretion Safeguards Mycobacterium tuberculosis Membrane Homeostasis.

Protein secretion is essential for the growth and virulence of Mycobacterium tuberculosis, yet the organization and function of its secretion pathways remain poorly understood. We reviewed the existing literature, combined it with systematic queries, and finalized annotations based on experimental data and computational predictions to compile a curated list of 92 secretory components and 198 reactions involved in Sec, twin-arginine translocation (Tat), and ESX pathways. Using CRISPRi, targeted depletion of SecA1 or TatAC impaired both in vitro growth and ex vivo survival. Label-free quantitative secretome analysis revealed decreased export of substrates dependent on SecA1 and TatAC, with enrichment of cytosolic proteins in culture filtrates, indicating increased membrane dysbiosis. Membrane proteomics showed elevated levels of proteins engaged in intermediary and lipid metabolism, while proteins associated with the cell wall and cell processes decreased, suggesting weakened membrane integrity. Loss of SecA1 or TatAC increased membrane permeability, with the effect being more pronounced in the case of TatAC, and caused structural abnormalities seen under electron microscopy. Overall, our integrated multi-omics and functional genetics studies demonstrate that the SecA1 and Tat pathways are essential for maintaining membrane homeostasis in Mycobacterium tuberculosis. These results suggest that essential secretory proteins may be promising targets for therapeutic intervention.

Mycobacterium tuberculosis↗

PubMed2026

H-NOX and NosP Regulate Flagellar Protein and Virulence Factor Production in Vibrio cholerae.

The ability of Vibrio cholerae to transition between motile and sessile forms in the environment and in the host is critical to its survival and virulence. The molecular cues, sensor proteins, and signaling pathways mediating these transitions are highly complex and often overlapping. Nevertheless, a detailed understanding of them is critical for understanding the persistence and pathogenesis of this deadly pathogen. Nitric oxide (NO) functions as an important signaling molecule in many bacteria, affecting biofilm formation, motility, and virulence, often through interaction with heme protein sensors. The genome of V. cholerae encodes two such sensors called H-NOX and NosP. Here we constructed a Δhnox/nosP mutant and employed a multi-omics methodology that combines tandem-mass-tag (TMT)-based quantitative proteomics, phosphoproteomics, and targeted metabolomics to investigate the function of these sensors. A set of 258 proteins was differentially expressed in the mutant that included many proteins involved in flagellar biosynthesis and motility as well as critical virulence factors, iron acquisition systems, and metabolic enzymes. Many of the identified genes are also part of the ferric uptake regulator (Fur) regulon and iron-dependent transcriptional repression of several Fur targets was disrupted. Phosphoproteomics analysis also revealed proteins involved in motility and virulence as differentially phosphorylated in the mutant strain. In most cases, these phosphoproteins have not been previously observed and provide a wealth of new targets for investigating mechanisms of V. cholerae signaling. Taken together, this work illustrates a role for H-NOX and NosP in promoting factors important for infection while suppressing those important for environmental survival, suggesting a function in priming the organism for infection and/or maintaining the infectious phenotype.

Journal Article↗

PubMed2026

Multiomics profiling of plasma reveals lipid-immune dysregulation and exosome remodeling in mpox and mpox-HIV co-infection.

BACKGROUND: Monkeypox virus (MPXV) infects diverse human cell types, and human immunodeficiency virus (HIV) co-infection is common. The immunometabolic consequences of MPXV infection, and how it may be altered by HIV, remain poorly defined. METHODS: We performed quantitative plasma lipidomics and precise metabolomics in a discovery cohort (n = 81) comprising MPXV-monoinfected (MPLWOH), MPXV-HIV-coinfected (MPLWH), and HIV-monoinfected (PLWH) patients and healthy controls, integrating exosome proteomics, cytokine profiling, and transcriptomics of exosome-treated HepG2 and A549 cells for functional interpretation. An independent validation cohort (n = 65) was used to assess cross-cohort reproducibility. FINDINGS: MPXV infection induced broad lipid remodeling, with elevations in phosphatidylserine (PS) and phosphatidylethanolamine (PE) and reductions in phosphatidylcholine (PC), lysophospholipids, cholesteryl ester (CE), and exosomal lecithin-cholesterol acyltransferase (LCAT) and lipoprotein lipase (LPL). These lipid alterations were correlated with tissue injury markers and inflammatory cytokines. The MPLWH group exhibited more severe metabolic disruption, including marked sulfatide (SL) depletion, lower cholesterol and high-density lipoprotein cholesterol (HDL-c), and extensive rewiring of lipid-cytokine associations. SL depletion in MPLWH correlated with abundances of COPI-mediated retrograde trafficking proteins in exosomes. Transcriptomic profiling of exosome-treated cells provided functional validation: MPLWOH exosomes induced lipid metabolism and repair-associated epithelial programs, while MPLWH exosomes drove phospholipid remodeling and acute inflammatory and mucosal barrier-stress responses. CONCLUSIONS: MPXV infection reprograms host lipid metabolism and exosome composition, with HIV co-infection amplifying inflammatory, metabolic, and trafficking disruptions. These convergent multi-omics signatures link systemic lipid dysregulation to exosome-mediated immunomodulation and identify potential targets for host-directed interventions. FUNDING: This study was funded by the Major Project of Guangzhou National Laboratory.

Adult↗