Mass Spectrometry-based Quantitative Proteomics Research Articles

Quantitative proteomics analysis of cerebrospinal fluid reveals putative protein biomarkers for canine non-infectious meningoencephalomyelitis.

Accurate ante-mortem diagnosis of non-infectious meningoencephalomyelitis (NIME) in dogs is challenging due to the similarity of clinical presentations, imaging findings, and cerebrospinal fluid (CSF) analysis results with other diseases. This study aimed to apply state-of-the-art quantitative proteomic technology to identify novel biomarkers for NIME. Serum and CSF samples from 11 dogs were included, with the control group consisting of patients presenting with intervertebral disc disease (IVDD, n = 6) and the study group consisting of dogs suffering from NIME (n = 5). Mass spectrometry-based quantitative proteomics revealed a set of 36 proteins with significant differential abundance in CSF samples. Up-regulated proteins in NIME CSF included immunoglobulins, inter-alpha-trypsin inhibitor heavy chain 2, acid sphingomyelinase-like phosphodiesterase, and chitinase 3-like protein 1, all associated with immune response and inflammation. Conversely, significantly down-regulated proteins included neural cell adhesion molecule, contactin-1, and procollagen C-endopeptidase enhancer, which are involved in neurodevelopment and synaptic plasticity. No differences in serum profiles were observed among the groups. This study identified a panel of CSF protein biomarker candidates for NIME and provided new insights into the pathogenesis of the disease, suggesting that neuronal dysfunction and immune dysregulation may be involved.

Integral Solvent-Induced Protein Precipitation for Target-Engagement Studies in Plasmodium falciparum.

The limited understanding of the mechanism of action (MoA) of several antimalarials and the rise of drug resistance toward existing malaria therapies emphasizes the need for new strategies to uncover the molecular target of compounds in Plasmodium falciparum. Integral solvent-induced protein precipitation (iSPP) is a quantitative mass spectrometry-based (LC-MS/MS) proteomics technique. The iSPP leverages the change in solvent-induced denaturation of the drug-bound protein relative to its unbound state, allowing identification of the direct drug-protein target without the need to modify the drug. Here, we demonstrate proof-of-concept of iSPP in P. falciparum (Pf) lysate. At first, we profiled the solvent-induced denaturation behavior of the Pf proteome, generating denaturation curves and determining the melting concentration (CM) of 2712 proteins. We then assessed the extent of stabilization of three antimalarial target proteins in multiple organic solvent gradients, allowing for a rational selection of an optimal solvent gradient. Subsequently, we validated iSPP by successfully showing target-engagement of several standard antimalarials. The iSPP assay allows the testing of multiple conditions within reasonable LC-MS/MS measurement time. Furthermore, it requires a minimal amount of protein input, reducing culturing time and simplifying protein extraction. We envision that iSPP will be useful as a complementary tool for MoA studies for next-generation antimalarials.

Abstract 4136813: Redox Serum Proteomics Of Left Ventricular Assist Device Unloaded Human Heart

Heart failure (HF) is a global epidemic claiming millions of lives worldwide. Unloading the heart of end-stage HF patients via left ventricular assist devices (LVADs) is used not only as a bridge to transplantation but also as a bridge to recovery in certain selected patients. To date, assessment of patients’ recovery from HF is based on clinical and symptomatic evaluation. The use of non-invasive biomarkers that monitor the remodeling/reverse remodeling associated with HF progression/recovery is still lacking. In this study we applied mass spectrometry-based quantitative redox proteomics to identify serum biomarkers to monitor both the progression of HF and its recovery after LVAD treatment. A fingerprint of reversed behavior at the protein and at the oxidized Cys peptide level has been discovered when comparing HF and LVAD patients. HDL proteins related to lipid metabolism were decreased in HF samples and increased in LVAD patients. In addition, a number of inflammatory proteins showed a decrease in LVAD samples and an increase in HF samples. In particular APOA4, C7, F2 or SAA2 discriminated between HF and LVAD patients. A pool of peptides containing specific oxidized Cys residues showed an inverse relationship in HF as opposed to LVAD samples. Oxidized Cys-containing peptides derived from Albumin, IGK and IGG1 discriminated HF from LVAD samples. Discriminatory sensitivity and specificity were enhanced by using a combination of the proteins APOA4, C7, F2 and the above-mentioned peptide derived from Albumin. Responders and non-responders could also be separated by proteins such as APOA4, and Cys-oxidized peptides, such as the ones derived from Albumin or IGK mentioned above. This is the first study to apply redox proteomics to explore the protein profile of the LVAD unloaded human heart. These data suggest that HDL plays an important role in LVAD recovery and that a specific group of peptides is associated with the recovery process; the mechanisms involved need further study. Our data could have important implications to the management of patients in the LVAD recovery program and could serve to identify new therapeutic targets.

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 utilises 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.

Abstract C024: Quantitative mass spectrometry-based multi-omic profiling to overcome drug resistance in pancreatic cancer post KRAS G12D inhibition

Abstract Recently developed inhibitors targeting the KRASG12D oncoprotein are undergoing clinical trial evaluation including in patients with pancreatic adenocarcinoma (PDAC). However, resistance to such targeted therapies is a frequent occurrence, potentially undermining the long-term success of KRAS inhibitors (KRASi). To uncover the adaptive pathways and cell surface biomarkers to KRASi and to identify effective drug combinations that can overcome resistance, we employ a mass spectrometry-based quantitative temporal proteomics workflow. This approach allows us to map the proteomic changes in response to KRASi in both in vitro and in vivo PDAC models. We identify and quantify 10,898 proteins, creating the most extensive proteomic dataset related to KRASi to date. We identify shared mechanisms of both acute and long-term adaptation to KRASi across PDAC models. Utilizing this proteomic information, we are pinpointing drug combinations that pair KRASi with inhibitors of CDK4/6, AURKA, and mTOR to increase cytotoxicity and thereby reduce development of long-term resistance. Surfaceome analyses identifies cell surface proteins upregulated upon acute and long-term KRASi, including TACSTD2 (Trop-2). Antibody-drug conjugates targeting upregulated surface proteins may be a useful orthogonal approach towards preventing or circumventing KRASi resistance with testing of Trop-2 and other candidates ongoing. In summary, through mass spectrometry-based quantitative temporal proteomics, we identify proteomic adaptations to KRASi in PDAC and propose combination treatments with promising therapeutic potential. Citation Format: Qijia Yu, Nicole Sindoni, Huan Zhang, Ziyue Li, Joao A. Paulo, Andrew J. Aguirre, Joseph D. Mancias. Quantitative mass spectrometry-based multi-omic profiling to overcome drug resistance in pancreatic cancer post KRAS G12D inhibition [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr C024.

Dia-PASEF Proteomics of Tumor and Stroma LMD Enriched from Archived HNSCC Samples.

We employed laser microdissection to selectively harvest tumor cells and stroma from the microenvironment of formalin-fixed, paraffin-embedded head and neck squamous cell carcinoma (HNSCC) tissues. The captured HNSCC tissue fractions were analyzed by quantitative mass spectrometry-based proteomics using a data independent analysis approach. In paired samples, we achieved excellent proteome coverage having quantified 6,668 proteins with a median quantitative coefficient of variation under 10%. We observed significant differences in relevant functional pathways between the spatially resolved tumor and stroma regions. Our results identified extracellular matrix (ECM) as a major component enriched in the stroma, including many cancer associated fibroblast signature proteins in this compartment. We demonstrate the potential for comparative deep proteome analysis from very low starting input in a scalable format that is useful to decipher the alterations in tumor and the stromal microenvironment. Correlating such results with clinical features or disease progression will likely enable identification of novel targets for disease classification and interventions.

Quantitative proteomics and immunohistochemistry uncover NT5DC2 as a diagnostic biomarker for papillary urothelial carcinoma

The accurate diagnosis of papillary urothelial carcinoma (PUC) is frequently challenging due to benign mimickers. Other than morphology-based diagnostic criteria, reliable biomarkers for differentiating benign and malignant papillary urothelial neoplasms remain elusive, so we sought to discover new markers to address this challenge. We first performed tandem mass spectrometry-based quantitative proteomics using diverse papillary urothelial lesions, including PUC, urothelial papilloma (UP), inverted urothelial papilloma, and cystitis cystica. We prioritized potential diagnostic biomarkers using machine learning, and subsequently validated through immunohistochemistry (IHC) in two independent cohorts. Metabolism, transport, cell cycle, development, and immune response functions were differentially enriched between malignant and benign papillary neoplasms. RhoB and NT5DC2 were shortlisted as optimal candidate markers for PUC diagnosis. In our pilot study using IHC, NT5DC2 was subsequently selected as its expression consistently differed in PUC (p = 0.007). Further validation of NT5DC2 using 49 low-grade (LG) urothelial lesions, including 15 LG-PUCs and 17 UPs, which are the most common mimickers, concordantly revealed lower IHC expression levels in LG-PUC (p = 0.0298). Independent external validation with eight LG-PUCs and eight UPs confirmed the significant downregulation of NT5DC2 in LG-PUC (p = 0.0104). We suggest that NT5DC2 is a potential IHC biomarker for differentiating LG-PUC from its benign mimickers, especially UP.

Imputation of label-free quantitative mass spectrometry-based proteomics data using self-supervised deep learning

Imputation techniques provide means to replace missing measurements with a value and are used in almost all downstream analysis of mass spectrometry (MS) based proteomics data using label-free quantification (LFQ). Here we demonstrate how collaborative filtering, denoising autoencoders, and variational autoencoders can impute missing values in the context of LFQ at different levels. We applied our method, proteomics imputation modeling mass spectrometry (PIMMS), to an alcohol-related liver disease (ALD) cohort with blood plasma proteomics data available for 358 individuals. Removing 20 percent of the intensities we were able to recover 15 out of 17 significant abundant protein groups using PIMMS-VAE imputations. When analyzing the full dataset we identified 30 additional proteins (+13.2%) that were significantly differentially abundant across disease stages compared to no imputation and found that some of these were predictive of ALD progression in machine learning models. We, therefore, suggest the use of deep learning approaches for imputing missing values in MS-based proteomics on larger datasets and provide workflows for these.

Electro-elution-based purification of covalent DNA-protein cross-links.

Covalent DNA-protein cross-links (DPCs) are pervasive DNA lesions that challenge genome stability and can be induced by metabolic or chemotherapeutic cross-linking agents including reactive aldehydes, topoisomerase poisons and DNMT1 inhibitors. The purification of x-linked proteins (PxP), where DNA-cross-linked proteins are separated from soluble proteins via electro-elution, can be used to identify DPCs. Here we describe a versatile and sensitive strategy for PxP. Mammalian cells are collected following exposure to a DPC-inducing agent, embedded in low-melt agarose plugs and lysed under denaturing conditions. Following lysis, the soluble proteins are extracted from the agarose plug by electro-elution, while genomic DNA and cross-linked proteins are retained in the plug. The cross-linked proteins can then be analyzed by standard analytical techniques such as sodium dodecyl-sulfate-polyacrylamide gel electrophoresis followed by western blotting or fluorescent staining. Alternatively, quantitative mass spectrometry-based proteomics can be used for the unbiased identification of DPCs. The isolation and analysis of DPCs by PxP overcomes the limitations of alternative methods to analyze DPCs that rely on precipitation as the separating principle and can be performed by users trained in molecular or cell biology within 2-3 d. The protocol has been optimized to study DPC induction and repair in mammalian cells but may also be adapted to other sample types including bacteria, yeast and tissue samples.

Quantitative proteomic analysis of plasma membranes from the fish pathogen Saprolegnia parasitica reveals promising targets for disease control.

The phylum Oomycota contains economically important pathogens of animals and plants, including Saprolegnia parasitica, the causal agent of the fish disease saprolegniasis. Due to intense fish farming and banning of the most effective control measures, saprolegniasis has re-emerged as a major challenge for the aquaculture industry. Oomycete cells are surrounded by a polysaccharide-rich cell wall matrix that, in addition to being essential for cell growth, also functions as a protective "armor." Consequently, the enzymes responsible for cell wall synthesis provide potential targets for disease control. Oomycete cell wall biosynthetic enzymes are predicted to be plasma membrane proteins. To identify these proteins, we applied a quantitative (iTRAQ) mass spectrometry-based proteomics approach to the plasma membrane of the hyphal cells of S. parasitica, providing the first complete plasma membrane proteome of an oomycete species. Of significance is the identification of 65 proteins enriched in detergent-resistant microdomains (DRMs). In silico analysis showed that DRM-enriched proteins are mainly involved in molecular transport and β-1,3-glucan synthesis, potentially contributing to pathogenesis. Moreover, biochemical characterization of the glycosyltransferase activity in these microdomains further supported their role in β-1,3-glucan synthesis. Altogether, the knowledge gained in this study provides a basis for developing disease control measures targeting specific plasma membrane proteins in S. parasitica.IMPORTANCEThe significance of this research lies in its potential to combat saprolegniasis, a detrimental fish disease, which has resurged due to intensive fish farming and regulatory restrictions. By targeting enzymes responsible for cell wall synthesis in Saprolegnia parasitica, this study uncovers potential avenues for disease control. Particularly noteworthy is the identification of several proteins enriched in membrane microdomains, offering insights into molecular mechanisms potentially involved in pathogenesis. Understanding the role of these proteins provides a foundation for developing targeted disease control measures. Overall, this research holds promise for safeguarding the aquaculture industry against the challenges posed by saprolegniasis.

Microenvironment shapes small-cell lung cancer neuroendocrine states and presents therapeutic opportunities

Small-cell lung cancer (SCLC) is the most fatal form of lung cancer. Intratumoral heterogeneity, marked by neuroendocrine (NE) and non-neuroendocrine (non-NE) cell states, defines SCLC, but the cell-extrinsic drivers of SCLC plasticity are poorly understood. To map the landscape of SCLC tumor microenvironment (TME), we apply spatially resolved transcriptomics and quantitative mass spectrometry-based proteomics to metastatic SCLC tumors obtained via rapid autopsy. The phenotype and overall composition of non-malignant cells in the TME exhibit substantial variability, closely mirroring the tumor phenotype, suggesting TME-driven reprogramming of NE cell states. We identify cancer-associated fibroblasts (CAFs) as a crucial element of SCLC TME heterogeneity, contributing to immune exclusion, and predicting exceptionally poor prognosis. Our work provides a comprehensive map of SCLC tumor and TME ecosystems, emphasizing their pivotal role in SCLC's adaptable nature, opening possibilities for reprogramming the TME-tumor communications that shape SCLC tumor states.

Investigation of Uterine Fluid Extracellular Vesicles' Proteomic Profiles Provides Novel Diagnostic Biomarkers of Bovine Endometritis.

Cow uterine infections pose a challenge in dairy farming, resulting in reproductive disorders. Uterine fluid extracellular vesicles (UF-EVs) play a key role in cell-to-cell communication in the uterus, potentially holding the signs of aetiology for endometritis. We used mass spectrometry-based quantitative shotgun proteomics to compare UF-EV proteomic profiles in healthy cows (H), cows with subclinical (SE) or clinical endometritis (CLE) sampled at 28-35 days postpartum. Functional analysis was performed on embryo cultures with the exposure to different EV types. A total of 248 UF-EV proteins exhibited differential enrichment between the groups. Interestingly, in SE, EV protein signature suggests a slight suppression of inflammatory response compared to CLE-UF-EVs, clustering closer with healthy cows' profile. Furthermore, CLE-UF-EVs proteomic profile highlighted pathways associated with cell apoptosis and active inflammation aimed at pathogen elimination. In SE-UF-EVs, the regulation of normal physiological status was aberrant, showing cell damage and endometrial repair at the same time. Serine peptidase HtrA1 (HTRA1) emerged as a potential biomarker for SE. Supplementation of CLE- and SE-derived UF-EVs reduced the embryo developmental rates and quality. Therefore, further research is warranted to elucidate the precise aetiology of SE in cattle, and HTRA1 should be further explored as a potential diagnostic biomarker.

Quantitative Proteomic Analysis Reveals Functional Alterations of the Peripheral Immune System in Colorectal Cancer

Colorectal cancer (CRC) is characterized by high morbidity, high mortality, and limited response to immunotherapies. The peripheral immune system is an important component of tumor immunity, and enhancements of peripheral immunity help to suppress tumor progression. However, the functional alterations of the peripheral immune system in CRC are unclear. Here, we used mass spectrometry-based quantitative proteomics to establish a protein expression atlas for the peripheral immune system in CRC, including plasma and five types of immune cells (CD4+ T cells, CD8+ T cells, monocytes, natural killer cells, and B cells). Synthesizing the results of the multidimensional analysis, we observed an enhanced inflammatory phenotype in CRC, including elevated expression of plasma inflammatory proteins, activation of the inflammatory pathway in monocytes, and increased inflammation-related ligand-receptor interactions. Notably, we observed tumor effects on peripheral T cells, including altered cell subpopulation ratios and suppression of cell function. Suppression of CD4+ T cell function is mainly mediated by high expression levels of protein tyrosine phosphatases. Among them, the expression of protein tyrosine phosphatase receptor type J (PTPRJ) gradually increased with CRC progression; knockdown of PTPRJ in vitro could promote T cell activation, thereby enhancing peripheral immunity. We also found that the combination of leucine-rich α-2 glycoprotein 1 (LRG1) and apolipoprotein A4 (APOA4) had the best predictive ability for colorectal cancer and has the potential to be a biomarker. Overall, this study provides a comprehensive understanding of the peripheral immune system in CRC. It also offers insights regarding the potential clinical utilities of these peripheral immune characteristics as diagnostic indicators and therapeutic targets.

Integrated Proteomics and Protein Co-expression Network Analysis Identifies Novel Epileptogenic Mechanism in Mesial Temporal Lobe Epilepsy.

Over 50 million people worldwide are affected by epilepsy, a common neurological disorder that has a high rate of drug resistance and diverse comorbidities such as progressive cognitive and behavioural disorders, and increased mortality from direct or indirect effects of seizures and therapies. Despite extensive research with animal models and human studies, limited insights have been gained into the mechanisms underlying seizures and epileptogenesis, which has not translated into significant reductions in drug resistance, morbidities, or mortality. To better understand the molecular signaling networks associated with seizures in MTLE patients, we analyzed the proteome of brain samples from MTLE and control cases using an integrated approach that combines mass spectrometry-based quantitative proteomics, differential expression analysis, and co-expression network analysis. Our analyses of 20 human brain tissues from MTLE patients and 20 controls showed the organization of the brain proteome into a network of 9 biologically meaningful modules of co-expressed proteins. Of these, 6 modules are positively or negatively correlated to MTLE phenotypes with hub proteins that are altered in MTLE patients. Our study is the first to employ an integrated approach of proteomics and protein co-expression network analysis to study patients with MTLE. Our findings reveal a molecular blueprint of altered protein networks in MTLE brain and highlight dysregulated pathways and processes including altered cargo transport, neurotransmitter release from synaptic vesicles, synaptic plasticity, proteostasis, RNA homeostasis, ion transport and transmembrane transport, cytoskeleton disorganization, metabolic and mitochondrial dysfunction, blood micro-particle function, extracellular matrix organization, immune response, neuroinflammation, and cell signaling. These insights into MTLE pathogenesis suggest potential new candidates for future diagnostic and therapeutic development.

Proteomic and phosphoproteomic characterization of cardiovascular tissues after long term exposure to simulated space radiation.

Introduction: It may take decades to develop cardiovascular dysfunction following exposure to high doses of ionizing radiation from medical therapy or from nuclear accidents. Since astronauts may be exposed continually to a complex space radiation environment unlike that experienced on Earth, it is unresolved whether there is a risk to cardiovascular health during long-term space exploration missions. Previously, we have described that mice exposed to a single dose of simplified Galactic Cosmic Ray (GCR5-ion) develop cardiovascular dysfunction by 12months post-radiation. Methods: To investigate the biological basis of this dysfunction, here we performed a quantitative mass spectrometry-based proteomics analysis of heart tissue (proteome and phosphoproteome) and plasma (proteome only) from these mice at 8months post-radiation. Results: Differentially expressed proteins (DEPs) for irradiated versus sham irradiated samples (fold-change ≥1.2 and an adjusted p-value of ≤0.05) were identified for each proteomics data set. For the heart proteome, there were 87 significant DEPs (11 upregulated and 76 downregulated); for the heart phosphoproteome, there were 60 significant differentially phosphorylated peptides (17 upregulated and 43 downregulated); and for the plasma proteome, there was only one upregulated protein. A Gene Set Enrichment Analysis (GSEA) technique that assesses canonical pathways from BIOCARTA, KEGG, PID, REACTOME, and WikiPathways revealed significant perturbation in pathways in each data set. For the heart proteome, 166 pathways were significantly altered (36 upregulated and 130 downregulated); for the plasma proteome, there were 73 pathways significantly altered (25 upregulated and 48 downregulated); and for the phosphoproteome, there were 223 pathways significantly affected at 0.1 adjusted p-value cutoff. Pathways related to inflammation were the most highly perturbed in the heart and plasma. In line with sustained inflammation, neutrophil extracellular traps (NETs) were demonstrated to be increased in GCR5-ion irradiated hearts at 12-month post irradiation. NETs play a fundamental role in combating bacterial pathogens, modulating inflammatory responses, inflicting damage on healthy tissues, and escalating vascular thrombosis. Discussion: These findings suggest that a single exposure to GCR5-ion results in long-lasting changes in the proteome and that these proteomic changes can potentiate acute and chronic health issues for astronauts, such as what we have previously described with late cardiac dysfunction in these mice.

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

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

Atrial proteomic profiling reveals a switch towards profibrotic gene expression program in CREM-IbΔC-X mice with persistent atrial fibrillation

BackgroundOverexpression of the CREM (cAMP response element-binding modulator) isoform CREM-IbΔC-X in transgenic mice (CREM-Tg) causes the age-dependent development of spontaneous AF. PurposeTo identify key proteome signatures and biological processes accompanying the development of persistent AF through integrated proteomics and bioinformatics analysis. MethodsAtrial tissue samples from three CREM-Tg mice and three wild-type littermates were subjected to unbiased mass spectrometry-based quantitative proteomics, differential expression and pathway enrichment analysis, and protein-protein interaction (PPI) network analysis. ResultsA total of 98 differentially expressed proteins were identified. Gene ontology analysis revealed enrichment for biological processes regulating actin cytoskeleton organization and extracellular matrix (ECM) dynamics. Changes in ITGAV, FBLN5, and LCP1 were identified as being relevant to atrial fibrosis and structural based on expression changes, co-expression patterns, and PPI network analysis. Comparative analysis with previously published datasets revealed a shift in protein expression patterns from ion-channel and metabolic regulators in young CREM-Tg mice to profibrotic remodeling factors in older CREM-Tg mice. Furthermore, older CREM-Tg mice exhibited protein expression patterns reminiscent of those seen in humans with persistent AF. ConclusionsThis study uncovered distinct temporal changes in atrial protein expression patterns with age in CREM-Tg mice consistent with the progressive evolution of AF. Future studies into the role of the key differentially abundant proteins identified in this study in AF progression may open new therapeutic avenues to control atrial fibrosis and substrate development in AF.

Exploring the mechanism of contact-dependent cell-cell communication on chemosensitivity based on single-cell high-throughput drug screening platform

High-throughput drug screening (HTDS) has significantly reduced the time and cost of new drug development. Nonetheless, contact-dependent cell-cell communication (CDCCC) may impact the chemosensitivity of tumour cells. There is a pressing need for low-cost single-cell HTDS platforms, alongside a deep comprehension of the mechanisms by which CDCCC affects drug efficacy, to fully unveil the efficacy of anticancer drugs. In this study, we develop a microfluidic chip for single-cell HTDS and evaluate the molecular mechanisms impacted by CDCCC using quantitative mass spectrometry-based proteomics. The chip achieves high-quality drug mixing and single-cell capture, with single-cell drug screening results on the chip showing consistency with those on the 96-well plates under varying concentration gradients. Through quantitative proteomic analysis, we deduce that the absence of CDCCC in single tumour cells can enhance their chemoresistance potential, but simultaneously subject them to stronger proliferation inhibition. Additionally, pathway enrichment analysis suggests that CDCCC could impact several signalling pathways in tumour single cells that regulate vital biological processes such as tumour proliferation, adhesion, and invasion. These results offer valuable insights into the potential connection between CDCCC and the chemosensitivity of tumour cells. This research paves the way for the development of single-cell HTDC platforms and holds the promise of advancing tumour personalized treatment strategies.

Strophanthidin Induces Apoptosis of Human Lung Adenocarcinoma Cells by Promoting TRAIL-DR5 Signaling.

Strophanthidin (SPTD), one of the cardiac glycosides, is refined from traditional Chinese medicines such as Semen Lepidii and Antiaris toxicaria, and was initially used for the treatment of heart failure disease in clinic. Recently, SPTD has been shown to be a potential anticancer agent, but the underlying mechanism of action is poorly understood. Herein, we explored the molecular mechanism by which SPTD exerts anticancer effects in A549 human lung adenocarcinoma cells by means of mass spectrometry-based quantitative proteomics in combination with bioinformatics analysis. We revealed that SPTD promoted the expression of tumor necrosis factor (TNF)-related apoptosis-inducing ligand receptor 2 (TRAIL-R2, or DR5) in A549 cells to activate caspase 3/6/8, in particular caspase 3. Consequently, the activated caspases elevated the expression level of apoptotic chromatin condensation inducer in the nucleus (ACIN1) and prelamin-A/C (LMNA), ultimately inducing apoptosis via cooperation with the SPTD-induced overexpressed barrier-to-autointegration factor 1 (Banf1). Moreover, the SPTD-induced DEPs interacted with each other to downregulate the p38 MAPK/ERK signaling, contributing to the SPTD inhibition of the growth of A549 cells. Additionally, the downregulation of collagen COL1A5 by SPTD was another anticancer benefit of SPTD through the modulation of the cell microenvironment.

Pseudomonas aeruginosa MipA-MipB envelope proteins act as new sensors of polymyxins.

Due to the rising incidence of antibiotic-resistant infections, the last-line antibiotics, polymyxins, have resurged in the clinics in parallel with new bacterial strategies of escape. The Gram-negative opportunistic pathogen Pseudomonas aeruginosa develops resistance to colistin/polymyxin B by distinct molecular mechanisms, mostly through modification of the lipid A component of the LPS by proteins encoded within the arnBCDATEF-ugd (arn) operon. In this work, we characterized a polymyxin-induced operon named mipBA, present in P. aeruginosa strains devoid of the arn operon. We showed that mipBA is activated by the ParR/ParS two-component regulatory system in response to polymyxins. Structural modeling revealed that MipA folds as an outer-membrane β-barrel, harboring an internal negatively charged channel, able to host a polymyxin molecule, while the lipoprotein MipB adopts a β-lactamase fold with two additional C-terminal domains. Experimental work confirmed that MipA and MipB localize to the bacterial envelope, and they co-purify in vitro. Nano differential scanning fluorimetry showed that polymyxins stabilized MipA in a specific and dose-dependent manner. Mass spectrometry-based quantitative proteomics on P. aeruginosa membranes demonstrated that ∆mipBA synthesized fourfold less MexXY-OprA proteins in response to polymyxin B compared to the wild-type strain. The decrease was a direct consequence of impaired transcriptional activation of the mex operon operated by ParR/ParS. We propose MipA/MipB to act as membrane (co)sensors working in concert to activate ParS histidine kinase and help the bacterium to cope with polymyxin-mediated envelope stress through synthesis of the efflux pump, MexXY-OprA.IMPORTANCEDue to the emergence of multidrug-resistant isolates, antibiotic options may be limited to polymyxins to eradicate Gram-negative infections. Pseudomonas aeruginosa, a leading opportunistic pathogen, has the ability to develop resistance to these cationic lipopeptides by modifying its lipopolysaccharide through proteins encoded within the arn operon. Herein, we describe a sub-group of P. aeruginosa strains lacking the arn operon yet exhibiting adaptability to polymyxins. Exposition to sub-lethal polymyxin concentrations induced the expression and production of two envelope-associated proteins. Among those, MipA, an outer-membrane barrel, is able to specifically bind polymyxins with an affinity in the 10-µM range. Using membrane proteomics and phenotypic assays, we showed that MipA and MipB participate in the adaptive response to polymyxins via ParR/ParS regulatory signaling. We propose a new model wherein the MipA-MipB module functions as a novel polymyxin sensing mechanism.