Proteomic Data Research Articles

Assessment of Data-Independent Acquisition Mass Spectrometry (DIA-MS) for the Identification of Single Amino Acid Variants

Proteogenomics integrates genomic and proteomic data to elucidate cellular processes by identifying variant peptides, including single amino acid variants (SAAVs). In this study, we assessed the capability of data-independent acquisition mass spectrometry (DIA-MS) to identify SAAV peptides in HeLa cells using various search engine pipelines. We developed a customised sequence database (DB) incorporating SAAV sequences from the HeLa genome and conducted searches using DIA-NN, Spectronaut, and Fragpipe-MSFragger. Our evaluation focused on identifying true positive SAAV peptides and false positives through entrapment DBs. This study revealed that DIA-MS provides reproducible and comprehensive coverage of the proteome, identifying a substantial proportion of SAAV peptides. Notably, the DIA-MS searches maintained consistent identification of SAAV peptides despite varying sizes of the entrapment DB. A comparative analysis showed that Fragpipe-MSFragger (FP-DIA) demonstrated the most conservative and effective performance, exhibiting the lowest false discovery match ratio (FDMR). Additionally, integrating DIA and data-dependent acquisition (DDA) MS data search outputs enhanced SAAV peptide identification, with a lower false discovery rate (FDR) observed in DDA searches. The validation using stable isotope dilution and parallel reaction monitoring (SID-PRM) confirmed the SAAV peptides identified by DIA-MS and DDA-MS searches, highlighting the reliability of our approach. Our findings underscore the effectiveness of DIA-MS in proteogenomic workflows for identifying SAAV peptides, offering insights into optimising search engine pipelines and DB construction for accurate proteomics analysis. These methodologies advance the understanding of proteome variability, contributing to cancer research and the identification of novel proteoform therapeutic targets.

Comparative Proteomics Highlights that GenX Exposure Leads to Metabolic Defects and Inflammation in Astrocytes.

Exposure to PFAS such as GenX (HFPO dimer acid) has become increasingly common due to the replacement of older generation PFAS in manufacturing processes. While neurodegenerative and developmental effects of legacy PFAS exposure have been studied in depth, there is a limited understanding specific to the effects of GenX exposure. To investigate the effects of GenX exposure, we exposed Drosophila melanogaster to GenX and assessed the motor behavior and performed quantitative proteomics of fly brains to identify molecular changes in the brain. Additionally, metabolic network-based analysis using the iDrosophila1 model unveiled a potential link between GenX exposure and neurodegeneration. Since legacy PFAS exposure has been linked to Parkinson's disease (PD), we compared the proteome data sets between GenX-exposed flies and a fly model of PD expressing human α-synuclein. Considering the proteomic data- and network-based analyses that revealed GenX may be regulating GABA-associated pathways and the immune system, we next explored the effects of GenX on astrocytes, as astrocytes in the brain can regulate GABA. An array of assays demonstrated GenX exposure may lead to mitochondrial dysfunction and neuroinflammatory response in astrocytes, possibly linking non-cell autonomous neurodegeneration to the motor deficits associated with GenX exposure.

Exploring the Molecular Mechanisms underlying SADI-S Improves Glucose Metabolism in Type 2 Diabetic Rats through Liver Transcriptomics and Proteomics Analysis.

Metabolic surgery could improve or even reverse type 2 diabetes mellitus (T2DM). Single-anastomosis duodenal-ileal bypass with sleeve gastrectomy (SADI-S) is one of the most effective metabolic surgeries for T2DM. However, the molecular mechanisms behind the SADI-S-induced T2DM improvement are not fully understood.Here,T2DM rats received SADI-S and were sacrificed after 8 weeks; the controls received sham surgery; Liver tissues were collected for transcriptomics and proteomics analysis to identify differentially expressed genes (DEGs) and proteins (DEPs). Parallel reaction monitoring (PRM) was performed to validate the accuracy of the proteomics results.SADI-S significantly improved glucose metabolism in T2DM rats.A total of 120 genes/proteins(e.g., phosphoenolpyruvate carboxykinase (Pck1) and pyruvate kinase (Pklr)) exhibited consistent expression trends at both mRNA and protein levels. Among the upregulated genes/proteins involved in glucose metabolic pathways, enrichment was observed in pathways such as the pyruvate metabolic pathway, insulin signaling pathway, glycolysis/gluconeogenesis biological processes, glucagon signaling pathway, and AMPK signaling pathway. Downregulated genes/proteins were enriched in the pyruvate metabolic pathway. The above-mentioned signaling pathways are implicated in glucose metabolism, suggesting a potential mechanism for SADI-S-mediated alleviation of T2DM. The PRM validation results indicated that all selected proteins showed consistent trends between PRM and proteomics data. This consistency suggests the reliability of the proteomics results.

Global Co-regulatory Cross Talk Between m6A and m5C RNA Methylation Systems Coordinate Cellular Responses and Brain Disease Pathways.

N6 adenosine and C5 cytosine modification of mRNAs, tRNAs and rRNAs are regulated by the behaviour of distinct sets of writer, reader and eraser effector proteins which are conventionally considered to function independently. Here, we provide evidence of global cross-regulatory and functional interaction between the m6A and m5C RNA methylation systems. We first show that m6A and m5C effector protein transcripts are subject to reciprocal base modification supporting the existence of co-regulatory post-transcriptional feedback loops. Using global mass spectrometry proteomic data generated after biological perturbation to identify proteins which change in abundance with effector proteins, we found novel co-regulatory cellular response relationships between m6A and m5C proteins such as between the m6A eraser, ALKBH5, and the m5C writer, NSUN4. Gene ontology analysis of co-regulated proteins indicated that m6A and m5C RNA cross-system control varies across cellular processes, e.g. proteasome and mitochondrial mechanisms, and post-translational modification processes such as SUMOylation and phosphorylation. We also uncovered novel relationships between effector protein networks including contributing to intellectual disability pathways. Finally, we provided in vitro confirmation of colocalisation between m6A-RNAs and the m5C reader protein, ALYREF, after synaptic NMDA activation. These findings have important implications for understanding control of RNA metabolism, cellular proteomic responses, and brain disease mechanisms.

MitoMAMMAL: a genome scale model of mammalian mitochondria predicts cardiac and BAT metabolism

Abstract Motivation Mitochondria perform several essential functions in order to maintain cellular homeostasis and mitochondrial metabolism is inherently flexible to allow correct function in a wide range of tissues. Dysregulated mitochondrial metabolism can therefore affect different tissues in different ways which presents experimental challenges in understanding the pathology of mitochondrial diseases. System-level metabolic modelling is therefore useful in gaining in-depth insights into tissue-specific mitochondrial metabolism, yet despite the mouse being a common model organism used in research, there is currently no mouse specific mitochondrial metabolic model available. Results In this work, building upon the similarity between human and mouse mitochondrial metabolism, we have created mitoMammal, a genome-scale metabolic model that contains human and mouse specific gene-product reaction rules. MitoMammal is therefore able to model mouse and human mitochondrial metabolism. To demonstrate this feature, using an adapted E-Flux algorithm, we first integrated proteomic data extracted from mitochondria of isolated mouse cardiomyocytes and mouse brown adipocyte tissue. We then integrated transcriptomic data from in vitro differentiated human brown adipose cells and modelled the context specific metabolism using flux balance analysis. In all three simulations, mitoMammal made mostly accurate, and some novel predictions relating to energy metabolism in the context of cardiomyocytes and brown adipocytes. This demonstrates its usefulness in research relating to cardiac disease and diabetes in both mouse and human contexts. Availability and implementation MitoMammal is formatted in SBML3. The code required for constraint-based modelling used in this work is implemented in Python 3 and is available as a Jupyter Notebook. The mitoMammal metabolic model, along with Jupyter notebooks and data used in this work are available at: https://gitlab.com/habermann_lab/mitomammal. Supplementary Information Supplementary data are available at Bioinformatics Advances online.

Metabolite and protein associations with general health in the population-based CHRIS study

Identifying biomarkers able to discriminate individuals on different health trajectories is crucial to understand the molecular basis of age-related morbidity. We investigated multi-omics signatures of general health and organ-specific morbidity, as well as their interconnectivity. We examined cross-sectional metabolome and proteome data from 3,142 adults of the Cooperative Health Research in South Tyrol (CHRIS) study, an Alpine population study designed to investigate how human biology, environment, and lifestyle factors contribute to people’s health over time. We had 174 metabolites and 148 proteins quantified from fasting serum and plasma samples. We used the Cumulative Illness Rating Scale (CIRS) Comorbidity Index (CMI), which considers morbidity in 14 organ systems, to assess health status (any morbidity vs. healthy). Omics-signatures for health status were identified using random forest (RF) classifiers. Linear regression models were fitted to assess directionality of omics markers and health status associations, as well as to identify omics markers related to organ-specific morbidity. Next to age, we identified 21 metabolites and 10 proteins as relevant predictors of health status and results confirmed associations for serotonin and glutamate to be age-independent. Considering organ-specific morbidity, several metabolites and proteins were jointly related to endocrine, cardiovascular, and renal morbidity. To conclude, circulating serotonin was identified as a potential novel predictor for overall morbidity.

The PRIDE database at 20 years: 2025 update.

The PRoteomics IDEntifications (PRIDE) database (https://www.ebi.ac.uk/pride/) is the world's leading mass spectrometry (MS)-based proteomics data repository and one of the founding members of the ProteomeXchange consortium. This manuscript summarizes the developments in PRIDE resources and related tools for the last three years. The number of submitted datasets to PRIDE Archive (the archival component of PRIDE) has reached on average around 534 datasets per month. This has been possible thanks to continuous improvements in infrastructure such as a new file transfer protocol for very large datasets (Globus), a new data resubmission pipeline and an automatic dataset validation process. Additionally, we will highlight novel activities such as the availability of the PRIDE chatbot (based on the use of open-source Large Language Models), and our work to improve support for MS crosslinking datasets. Furthermore, we will describe how we have increased our efforts to reuse, reanalyze and disseminate high-quality proteomics data into added-value resources such as UniProt, Ensembl and Expression Atlas.

ERO1A levels are a prognostic indicator in EGFR mutated non small cell lung cancer

We have identified endoplasmic reticulum oxidoreductase 1 alpha (ERO1A) as a poor prognostic indicator in epidermal growth factor receptor (EGFR)-mutated non-small cell lung cancer (EGFRMUT-NSCLC). In addition, comparison of high versus low ERO1A expression among cohorts of EGFRMUT-NSCLC primary samples revealed that ERO1A expression correlated with increased expression of proteins that regulate secretion. Using the CPTAC proteomic data set in lung adenocarcinoma we found that high ERO1A protein expression correlated with both extracellular matrix and matrix modifying enzymes. In this report, we found that ablating ERO1A expression was a determinant of clonogenicity, tumor sphere formation, spheroid growth and growth in vivo, as well as response to Osimertinib. We validated that ERO1A-knockout EGFRMUT-LUAD cell lines demonstrated a reduction in secretion of both laminin gamma 2 (LAMC2) and the collagen modifying enzyme lysyl oxidase-like 2 (LOXL2). Our work supports the role of ERO1A in modulating the tumor microenvironment that is likely to contribute to tumor progression.

Proliferation associated 2G4 is required for the ciliation of vertebrate motile cilia

Motile cilia are critical structures that regulate early embryonic development and tissue homeostasis through synchronized ciliary motility. The formation of motile cilia is dependent on precisely controlled sequential processes including the generation, migration, and docking of centrioles/basal bodies as well as ciliary growth. Using the published proteomics data from various organisms, we identified proliferation-associated 2G4 as a novel regulator of ciliogenesis. Loss-of-function studies using Xenopus laevis as a model system reveal that Pa2G4 is essential for proper ciliogenesis and synchronized movement of cilia in multiciliated cells (MCCs) and the gastrocoel roof plate (GRP). Pa2G4 morphant MCCs exhibit defective basal body docking to the surface as a result of compromised Rac1 activity, apical actin network formation, and immature distal appendage generation. Interestingly, the regions that include the RNA-binding domain and the C-terminus of Pa2G4 are necessary for ciliogenesis in both MCCs and GRP cells. Our findings may provide insights into motile cilia-related genetic diseases such as Primary Ciliary Dyskinesia.

Integrative Proteomic and Phosphoproteomic Profiling Reveals the Salt-Responsive Mechanisms in Two Rice Varieties (Oryza Sativa subsp. Japonica and Indica).

Salinity stress induces ionic and osmotic imbalances in rice plants that in turn negatively affect the photosynthesis rate, resulting in growth retardation and yield penalty. Efforts have, therefore, been carried out to understand the mechanism of salt tolerance, however, the complexity of biological processes at proteome levels remains a major challenge. Here, we performed a comparative proteome and phosphoproteome profiling of microsome enriched fractions of salt-tolerant (cv. IR73; indica) and salt-susceptible (cv. Dongjin/DJ; japonica) rice varieties. This approach led to the identification of 5856 proteins, of which 473 and 484 proteins showed differential modulation between DJ and IR73 sample sets, respectively. The phosphoproteome analysis led to the identification of a total of 10,873 phosphopeptides of which 2929 and 3049 phosphopeptides showed significant differences in DJ and IR73 sample sets, respectively. The integration of proteome and phosphoproteome data showed activation of ABA and Ca2+ signaling components exclusively in the salt-tolerant variety IR73 in response to salinity stress. Taken together, our results highlight the changes at proteome and phosphoproteome levels and provide a mechanistic understanding of salinity stress tolerance in rice.

Integrated global proteomic and phosphoproteomic analysis of cisplatin-induced apoptosis in A549 cells

Protein phosphorylation, a widely occurring and significant post-translational modification, is integral to various biological processes. We previously utilized a protein affinity probe to identify genes damaged by cisplatin, revealing that it inflicts substantial damage on protein kinase and protein phosphatase genes. In this study, we investigated cisplatin-induced alterations in the global proteome and phosphoproteome of A549 cells. Employing Fe-IMAC beads and tyrosine phosphorylation enrichment antibodies, we identified 6944 protein groups and 18,274 phosphorylation sites on 4,915 proteins across three biological replicates of both cisplatin-treated A549 cells and control cells. Among these, 730 tyrosine phosphorylation sites were identified—marking the most substantial discovery of such sites in A549 cells following cisplatin treatment. Bioinformatics analysis indicated that the proteins exhibiting significant phosphorylation level changes predominantly involved in RNA processing, modification, transcription, translation, and the spliceosome. This suggests that cisplatin-induced damage to protein kinases and phosphatases may disrupt the normal function of these proteins, consequently impairing DNA replication, RNA translation, and shearing, ultimately culminating in tumor cell death. Moreover, we cross-referenced our proteomic data with our previously obtained cisplatin-damaged genes, observing that the majority of down-regulated proteins derived from cisplatin-induced gene damage. The data are available on ProteomeXchange under the identifier PXD053902.

CGAS regulates metabolic reprogramming independently of STING pathway in colorectal cancer

BackgroundCyclic GMP-AMP synthase (cGAS) is widely acknowledged for detecting cytosolic chromatin fragments and triggering innate immune responses through the production of the second messenger cGAMP, which subsequently activates the adaptor protein STING. However, the role of cGAS in regulating metabolic reprogramming independently of STING activation has not yet been explored. MethodsGene set enrichment pathway analysis (GSEA) based on TCGA transcriptomics, combined with Seahorse metabolic analysis of CRC cell lines and human normal colonic mucosa cell line FHC, was performed to profile the metabolic features in CRC. cGAS doxycycline- (dox) inducible knockout (iKO) CRC sublines were generated to investigate the role of cGAS in CRC. Transcriptome and proteome data from COAD cohorts were utilized to evaluate the RNA and protein expression levels of cGAS in COAD tissues and normal colon tissues. Overall survival information of patients with COAD was used to evaluate the prognostic value of cGAS expression. Colony formation assays were conducted to evaluate the clonogenicity of CRC cells under different situations. Flow cytometry detecting the signal of fluorogenic reactive oxygen species (ROS) probes was performed to evaluate the total cellular and mitochondrial oxidative stress level in CRC cells. A propidium iodide (PI) staining assay was used to evaluate the cell death level in CRC cells. Quantitative PCR (qPCR) was conducted to detect the RNA level of STING pathway downstream target genes. Mass spectrometry was used for the identification of novel binding partners of cGAS in CRC cells. Co-immunoprecipitation (co-IP) was conducted to confirm the interaction between cGAS and NDUFA4L2. ResultsBy integrating metabolic pathway analysis based on TCGA transcriptomics with Seahorse metabolic analysis of a panel CRC cell lines and the human normal colonic mucosa cell line FHC, we demonstrated that CRC cells exhibit typical characteristics of metabolic reprogramming, characterized by a shift from oxidative phosphorylation (OXPHOS) to glycolysis. We found that cGAS is critical for CRC cells to maintain this metabolic switch. Specifically, the suppression of cGAS through siRNA-mediated knockdown or doxycycline-inducible knockout reversed this metabolic switch, resulting in increased OXPHOS activity, elevated production of OXPHOS byproduct reactive oxygen species (ROS), and consequently caused oxidative stress. This disruption induced oxidative stress, ultimately resulting in cell death and reduced cell viability. Moreover, significant upregulation of cGAS in CRC tissues and cell lines and its association with poor prognosis in CRC patients was observed. Subsequently, we demonstrated that the role of cGAS in regulating metabolic reprogramming does not rely on the canonical cGAS-STING pathway. Co-immunoprecipitation combined with mass spectrometry identified NDUFA4L2 as a novel interactor of cGAS. Subsequent functional experiments, including mitochondrial respiration and oxidative stress assays, demonstrated that cGAS plays a crucial role in sustaining elevated levels of NDUFA4L2 protein expression. The increased expression of NDUFA4L2 is essential for cGAS-mediated regulation of metabolic reprogramming and cell survival in CRC cells. ConclusioncGAS regulates metabolic reprogramming and promotes cell survival in CRC cells through its interaction with NDUFA4L2, independently of the canonical cGAS-STING pathway.

Proteogenomic analysis dissects early-onset breast cancer patients with prognostic relevance.

Early-onset breast cancer is known for its aggressive clinical characteristics and high prevalence in East Asian countries, but a comprehensive understanding of its molecular features is still lacking. In this study, we conducted a proteogenomic analysis of 126 treatment-naïve primary tumor tissues obtained from Korean patients with young breast cancer (YBC) aged ≤40 years. By integrating genomic, transcriptomic, and proteomic data, we identified five distinct functional subgroups that accurately represented the clinical characteristics and biological behaviors of patients with YBC. Our integrated approach could be used to determine the proteogenomic status of HER2, enhancing its clinical significance and prognostic value. Furthermore, we present a proteome-based homologous recombination deficiency (HRD) analysis that has the potential to overcome the limitations of conventional genomic HRD tests, facilitating the identification of new patient groups requiring targeted HR deficiency treatments. Additionally, we demonstrated that protein-RNA correlations can be used to predict the late recurrence of hormone receptor-positive breast cancer. Within each molecular subtype of breast cancer, we identified functionally significant protein groups whose differential abundance was closely correlated with the clinical progression of breast cancer. Furthermore, we derived a recurrence predictive index capable of predicting late recurrence, specifically in luminal subtypes, which plays a crucial role in guiding decisions on treatment durations for YBC patients. These findings improve the stratification and clinical implications for patients with YBC by contributing to the optimal adjuvant treatment and duration for favorable clinical outcomes.

Loss of interferon regulatory factor-1 prevents lung fibrosis by upregulation of pon1 expression

BackgroundInterferon regulatory factor-1 (IRF1) is a transcription factor that plays a significant role in various biological processes, including inflammatory injury, viral infection, cell death, and immune responses, and it has been extensively studied in the context of different lung diseases. However, the mechanism underlying its involvement in lung fibrosis remains largely unknown.MethodsWild type (WT) mice, IRF1 global-null mice (Irf1−/−) were subjected to a bleomycin-induced lung fibrosis model to enable examination of the role of IRF1 in lung fibrosis. Proteomic analysis of lung tissue from WT and Irf1−/− mice treated with saline or bleomycin was performed to explore the mechanism of IRF1 in regulating lung fibrosis.ResultsIn the bleomycin-induced fibrosis mouse model, increased expression of IRF1 was observed. Irf1 knockout mice displayed decreased lung fibrosis relative to WT mice following treatment with bleomycin. The protein expression of fibronectin, as assessed by the Western blot analysis of lung tissues, was downregulated in Irf1−/− mice. We observed a similar reduction in collagen content using hydroxyproline detection. Histologically, there was less collagen deposition in the lungs of Irf1−/− mice compared with WT mice. Proteomics data revealed that IRF1 may be involved in lung fibrosis via the regulation of ferroptosis. We determined that paraoxonase 1(PON1), a poorly characterized protein in lung fibrosis, was upregulated in Irf1−/− mice following exposure to bleomycin. In vitro experiments revealed that IRF1 could regulate the level of GSH and MDA through PON1. We also determined that PON1 levels were lower in the plasma of IPF patients compared with healthy controls.ConclusionOur data highlight the importance of IRF1 in the fibrotic process, and PON1 may be a potential mediator of IRF1 in the progression of lung fibrosis.

Are we better together? Addressing a combined treatment of pitavastatin and temozolomide for brain cancer

Pitavastatin is commonly prescribed to treat hypercholesterolemia through the regulation of cholesterol biosynthesis. Interestingly, it has also demonstrated a great potential for treating brain tumors, although the detailed cytotoxic mechanism, particularly in glioblastoma, remains incompletely understood. This work explores the activity of pitavastatin in 2D and 3D glioblastoma models, in an attempt to provide a more representative and robust overview of its anticancer potential in glioblastoma. The results show that not only is pitavastatin 10-1000 times-fold more effective in reducing tumoral metabolic activity than temozolomide, but also demonstrate a synergistic activity with this alkylating drug. In addition, low micromolar concentrations of this statin strongly impair the growth and the invasion ability of multicellular tumor spheroids. The obtained qRT-PCR and proteomics data highlight the modulation of cell death via apoptosis (BAX/BCL2, CASP9) and autophagy (BECN1, BNIP3, BNIP3L and LC3B), as well as an epithelial to mesenchymal transition blockage (HTRA1, SERPINE1, WNT5A, ALDH3B1 and EPHA2) and remodeling of the extracellular matrix (VCAN, SERPINE1 and TGFBI). Overall, these results lay the foundation for further investigations on the potential combinatory clinical treatment with temozolomide.

AI-empowered perturbation proteomics for complex biological systems.

The insufficient availability of comprehensive protein-level perturbation data is impeding the widespread adoption of systems biology. In this perspective, we introduce the rationale, essentiality, and practicality of perturbation proteomics. Biological systems are perturbed with diverse biological, chemical, and/or physical factors, followed by proteomic measurements at various levels, including changes in protein expression and turnover, post-translational modifications, protein interactions, transport, and localization, along with phenotypic data. Computational models, employing traditional machine learning or deep learning, identify or predict perturbation responses, mechanisms of action, and protein functions, aiding in therapy selection, compound design, and efficient experiment design. We propose to outline a generic PMMP (perturbation, measurement, modeling to prediction) pipeline and build foundation models or other suitable mathematical models based on large-scale perturbation proteomic data. Finally, we contrast modeling between artificially and naturally perturbed systems and highlight the importance ofperturbation proteomics for advancing our understanding and predictive modeling of biological systems.

Melittin treatment suppressed malignant NSCLC progression through enhancing CTSB-mediated hyperautophagy

Melittin is preclinically investigated as anticancer agent in multiple tumor types. But its regulation role and regulatory mechanism regarding NSCLC is unknown. In our investigation, Proteomic test was employed to identify proteins that expressed abnormally in cancer cells and that with Melittin treatmented. The results showed CTSB was one of the Top proteins with different expression levels in the lysosomes of Melittin-treatmented cancer cells and showed an up-regulation trend. CTSB expression was increased in NSCLC cancer tissues compared to adjacent normal tissues, as demonstrated in lung cancer tissue chips experiment. However, Melittin treatment increased the CTSB level in lysosomes, which inhibited the malignant progression of NSCLC. We hypothesized that the relative homeostasis of CTSB in cancer cells was destroyed, and CTSB exerts its hydrolytic effect excessively, resulting in excessive autophagy of cancer cells, thus inhibiting the malignant progression of cancer cells. The direct combination of Melittin and CTSB was proposed by molecular docking technique, LiP-SMap was used to analyze the target genes and active components extracted from high-throughput sequencing proteomic data, and successfully verified that melittin was successfully demonstrated to directly target CTSB-binding. In vivo and in vitro studies have shown that Melittin treatment inhibits the malignant progression of A549 and HCC1833 cells and animal tumors, namely non-small cell lung cancer, by promoting CTSB-mediated hyperautophagy. CTSB-specific inhibitor CA-074 Me and autophagy inhibitor 3-MA treatment reversed the inhibit effect of Melittin to the malignant progression of NSCLC. Taken together, Melittin treatment inhibited malignant progression regarding NSCLC through enhancing CTSB-mediated hyperautophagy.

The abundance change of age-regulated secreted proteins affects lifespan of C. elegans

Proteome integrity is vital for survival and failure to maintain it results in uncontrolled protein abundances, misfolding and aggregation which cause proteotoxicity. In multicellular organisms, proteotoxic stress is communicated among tissues to maintain proteome integrity for organismal stress resistance and survival. However, the nature of these signalling molecules and their regulation in extracellular space is largely unknown. Secreted proteins are induced in response to various stresses and aging, indicating their roles in inter-tissue communication. To study the fates of age-regulated proteins with potential localization to extracellular, we analysed publicly available age-related proteome data of C. elegans. We found that abundance of majority of the proteins with signal peptides (SP) increases with age, which might result in their supersaturation and subsequent aggregation. Intriguingly, these changes are differentially regulated in the lifespan mutants. A subset of these SP proteins is also found in the cargo of extracellular vesicles. Many of these proteins are novel and functionally uncharacterized. Reducing levels of a few extracellular proteins results in increasing lifespan. This suggests that uncontrolled levels of extracellular proteins might disturb proteostasis and limit the lifespan. Overall, our findings suggest that the age-induced secreted proteins might be the potential candidates to be considered as biomarkers or for mitigating age-related pathological conditions.

Integration across biophysical scales identifies molecular and cellular correlates of person-to-person variability in human brain connectivity

Brain connectivity arises from interactions across biophysical scales, ranging from molecular to cellular to anatomical to network level. To date, there has been little progress toward integrated analysis across these scales. To bridge this gap, from a unique cohort of 98 individuals, we collected antemortem neuroimaging and genetic data, as well as postmortem dendritic spine morphometric, proteomic and gene expression data from the superior frontal and inferior temporal gyri. Through the integration of the molecular and dendritic spine morphology data, we identified hundreds of proteins that explain interindividual differences in functional connectivity and structural covariation. These proteins are enriched for synaptic structures and functions, energy metabolism and RNA processing. By integrating data at the genetic, molecular, subcellular and tissue levels, we link specific biochemical changes at synapses to connectivity between brain regions. These results demonstrate the feasibility of integrating data from vastly different biophysical scales to provide a more comprehensive understanding of brain connectivity.

The Effect of Long-Term Physical Disability and Aging on Extracellular Matrix Biogenesis in Human Skeletal Muscle

Physical inactivity and aging cause significant impairments in the functionality and mechanical properties of skeletal muscles, as well as remodeling of the extracellular matrix (ECM). We aimed to study the effect of long-term inactivity and age on the biogenesis of ECM in skeletal muscle. For quantitative mass spectrometry-based proteomic analysis and RNA sequencing, biopsy samples were taken from m. vastus lateralis in 15 young healthy volunteers, 8 young and 37 elderly patients with long-term primary osteoarthritis of the knee/hip joint – which is a model for studying the effects of inactivity on muscles. We detected 1022 mRNAs and 101 ECM and associated proteins (matrisome). An increase in the expression of two dozen highly abundant matrisome proteins, specific to elderly and young patients (in relation to young healthy people), was detected; however, changes in the expression of mRNA encoding matrisome regulators (enzymatic regulators and secreted proteins) were similar. Comparison with previous proteomic and transcriptomic data showed that the changes in the matrisome that we described differed markedly from the changes caused by aerobic physical training in young healthy people, in particular, in the expression of the dominant ECM proteins and, especially, in the expression of mRNA of ECM enzymatic regulators and secreted proteins. Comparison of the changes in the expression profiles of these regulatory genes may be useful for identifying pharmacological targets for the prevention of adverse changes/activation of ECM biogenesis under various pathological conditions/physical training.