Clinically relevant plasma proteome for adiposity depots: evidence from systematic mendelian randomization and colocalization analyses.

BACKGROUND: The accumulation of visceral and ectopic fat comprise a major cause of cardiometabolic diseases. However, novel drug targets for reducing unnecessary visceral and ectopic fat are still limited. Our study aims to provide a comprehensive investigation of the causal effects of the plasma proteome on visceral and ectopic fat using Mendelian randomization (MR) approach. METHODS: We performed two-sample MR analyses based on five large genome-wide association study (GWAS) summary statistics of 2656 plasma proteins, to screen for causal associations of these proteins with traits of visceral and ectopic fat in over 30,000 participants of European ancestry, as well as to assess mediation effects by risk factors of outcomes. The colocalization analysis was conducted to examine whether the identified proteins and outcomes shared casual variants. RESULTS: Genetically predicted levels of 14 circulating proteins were associated with visceral and ectopic fat (P < 4.99 × 10- 5, at a Bonferroni-corrected threshold). Colocalization analysis prioritized ten protein targets that showed effect on outcomes, including FST, SIRT2, DNAJB9, IL6R, CTSA, RGMB, PNLIPRP1, FLT4, PPY and IL6ST. MR analyses revealed seven risk factors for visceral and ectopic fat (P < 0.0024). Furthermore, the associations of CTSA, DNAJB9 and IGFBP1 with primary outcomes were mediated by HDL-C and SHBG. Sensitivity analyses showed little evidence of pleiotropy. CONCLUSIONS: Our study identified candidate proteins showing putative causal effects as potential therapeutic targets for visceral and ectopic fat accumulation and outlined causal pathways for further prevention of downstream cardiometabolic diseases.

Stability-based approaches in chemoproteomics.

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

Changes Induced by P2X7 Receptor Stimulation of Human Glioblastoma Stem Cells in the Proteome of Extracellular Vesicles Isolated from Their Secretome.

Extracellular vesicles (EVs) are secreted from many tumors, including glioblastoma multiforme (GBM), the most common and lethal brain tumor in adults, which shows high resistance to current therapies and poor patient prognosis. Given the high relevance of the information provided by cancer cell secretome, we performed a proteomic analysis of microvesicles (MVs) and exosomes (EXOs) released from GBM-derived stem cells (GSCs). The latter, obtained from the brain of GBM patients, expressed P2X7 receptors (P2X7Rs), which positively correlate with GBM growth and invasiveness. P2X7R stimulation of GSCs caused significant changes in the EV content, mostly ex novo inducing or upregulating the expression of proteins related to cytoskeleton reorganization, cell motility/spreading, energy supply, protection against oxidative stress, chromatin remodeling, and transcriptional regulation. Most of the induced/upregulated proteins have already been identified as GBM diagnostic/prognostic factors, while others have only been reported in peripheral tumors. Our findings indicate that P2X7R stimulation enhances the transport and, therefore, possible intercellular exchange of GBM aggressiveness-increasing proteins by GSC-derived EVs. Thus, P2X7Rs could be considered a new druggable target of human GBM, although these data need to be confirmed in larger experimental sets.

Proteome-wide association study and functional validation identify novel protein markers for pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) remains a lethal malignancy, largely due to the paucity of reliable biomarkers for early detection and therapeutic targeting. Existing blood protein biomarkers for PDAC often suffer from replicability issues, arising from inherent limitations such as unmeasured confounding factors in conventional epidemiologic study designs. To circumvent these limitations, we use genetic instruments to identify proteins with genetically predicted levels to be associated with PDAC risk. Leveraging genome and plasma proteome data from the INTERVAL study, we established and validated models to predict protein levels using genetic variants. By examining 8,275 PDAC cases and 6,723 controls, we identified 40 associated proteins, of which 16 are novel. Functionally validating these candidates by focusing on 2 selected novel protein-encoding genes, GOLM1 and B4GALT1, we demonstrated their pivotal roles in driving PDAC cell proliferation, migration, and invasion. Furthermore, we also identified potential drug repurposing opportunities for treating PDAC. SIGNIFICANCE: PDAC is a notoriously difficult-to-treat malignancy, and our limited understanding of causal protein markers hampers progress in developing effective early detection strategies and treatments. Our study identifies novel causal proteins using genetic instruments and subsequently functionally validates selected novel proteins. This dual approach enhances our understanding of PDAC etiology and potentially opens new avenues for therapeutic interventions.

Untargeted metabolomics and molecular docking studies on green silver nanoparticles synthesized by Sarocladium subulatum: Exploring antibacterial and antioxidant properties.

The biological synthesis of silver nanoparticles (Ag-NPs) with fungi has shown promising results in antibacterial and antioxidant properties. Fungi generate metabolites (both primary and secondary) and proteins, which aid in the formation of metal nanoparticles as reducing or capping agents. While several studies have been conducted on the biological production of Ag-NPs, the exact mechanisms still need to be clarified. In this study, Ag-NPs are synthesized greenly using an unstudied fungal strain, Sarocladium subulatum AS4D. Three silver salts were used to synthesize the Ag-NPs for the first time, optimized using a cell-free extract (CFE) strategy. Additionally, these NPs were assessed for their antimicrobial and antioxidant properties. Various spectroscopic and microscopy techniques were utilized to confirm Ag-NP formation and analyze their morphology, crystalline properties, functional groups, size, stability, and concentrations. Untargeted metabolomics and proteome disruption were employed to explore the synthesis mechanism. Computational tools were applied to predict metabolite toxicity and antibacterial activity. The study identified 40 fungal metabolites capable of reducing silver ions, with COOH and OH functional groups playing a pivotal role. The silver salt type impacted the NPs' size and stability, with sizes ranging from 40 to 52 nm and zeta potentials from -0.9 to -30.4 mV. Proteome disruption affected size and stability but not shape. Biosynthesized Ag-NPs using protein-free extracts ranged from 55 to 62 nm, and zeta potentials varied from -18 to -27 mV. Molecular docking studies and PASS results found no role for the metabolome in antibacterial activity. This suggests the antibacterial activity comes from Ag-NPs, not capping or reducing agents. Overall, the research affirmed the vital role of specific reducing metabolites in the biosynthesis of Ag-NPs, while proteins derived from biological extracts were found to solely affect their size and stability.

Genetic determinants of plasma protein levels in the Estonian population.

The proteome holds great potential as an intermediate layer between the genome and phenome. Previous protein quantitative trait locus studies have focused mainly on describing the effects of common genetic variations on the proteome. Here, we assessed the impact of the common and rare genetic variations as well as the copy number variants (CNVs) on 326 plasma proteins measured in up to 500 individuals. We identified 184 cis and 94 trans signals for 157 protein traits, which were further fine-mapped to credible sets for 101 cis and 87 trans signals for 151 proteins. Rare genetic variation contributed to the levels of 7 proteins, with 5 cis and 14 trans associations. CNVs were associated with the levels of 11 proteins (7 cis and 5 trans), examples including a 3q12.1 deletion acting as a hub for multiple trans associations; and a CNV overlapping NAIP, a sensor component of the NAIP-NLRC4 inflammasome which is affecting pro-inflammatory cytokine interleukin 18 levels. In summary, this work presents a comprehensive resource of genetic variation affecting the plasma protein levels and provides the interpretation of identified effects.

ProNet DB: a proteome-wise database for protein surface property representations and RNA-binding profiles.

The rapid growth in the number of experimental and predicted protein structures and more complicated protein structures poses a significant challenge for computational biology in leveraging structural information and accurate representation of protein surface properties. Recently, AlphaFold2 released the comprehensive proteomes of various species, and protein surface property representation plays a crucial role in protein-molecule interaction predictions, including those involving proteins, nucleic acids and compounds. Here, we proposed the first extensive database, namely ProNet DB, that integrates multiple protein surface representations and RNA-binding landscape for 326 175 protein structures. This collection encompasses the 16 model organism proteomes from the AlphaFold Protein Structure Database and experimentally validated structures from the Protein Data Bank. For each protein, ProNet DB provides access to the original protein structures along with the detailed surface property representations encompassing hydrophobicity, charge distribution and hydrogen bonding potential as well as interactive features such as the interacting face and RNA-binding sites and preferences. To facilitate an intuitive interpretation of these properties and the RNA-binding landscape, ProNet DB incorporates visualization tools like Mol* and an Online 3D Viewer, allowing for the direct observation and analysis of these representations on protein surfaces. The availability of pre-computed features enables instantaneous access for users, significantly advancing computational biology research in areas such as molecular mechanism elucidation, geometry-based drug discovery and the development of novel therapeutic approaches. Database URL:  https://proj.cse.cuhk.edu.hk/aihlab/pronet/.

IMPRINTS.CETSA and IMPRINTS.CETSA.app: an R package and a Shiny application for the analysis and interpretation of IMPRINTS-CETSA data.

IMPRINTS-CETSA (Integrated Modulation of Protein Interaction States-Cellular Thermal Shift Assay) provides a highly resolved means to systematically study the interactions of proteins with other cellular components, including metabolites, nucleic acids and other proteins, at the proteome level, but no freely available and user-friendly data analysis software has been reported. Here, we report IMPRINTS.CETSA, an R package that provides the basic data processing framework for robust analysis of the IMPRINTS-CETSA data format, from preprocessing and normalization to visualization. We also report an accompanying R package, IMPRINTS.CETSA.app, which offers a user-friendly Shiny interface for analysis and interpretation of IMPRINTS-CETSA results, with seamless features such as functional enrichment and mapping to other databases at a single site. For the hit generation part, the diverse behaviors of protein modulations have been typically segregated with a two-measure scoring method, i.e. the abundance and thermal stability changes. We present a new algorithm to classify modulated proteins in IMPRINTS-CETSA experiments by a robust single-measure scoring. In this way, both the numerical changes and the statistical significances of the IMPRINTS information can be visualized on a single plot. The IMPRINTS.CETSA and IMPRINTS.CETSA.app R packages are freely available on GitHub at https://github.com/nkdailingyun/IMPRINTS.CETSA and https://github.com/mgerault/IMPRINTS.CETSA.app, respectively. IMPRINTS.CETSA.app is also available as an executable program at https://zenodo.org/records/10636134.

The long-chain flavodoxin FldX1 improves the biodegradation of 4-hydroxyphenylacetate and 3-hydroxyphenylacetate and counteracts the oxidative stress associated to aromatic catabolism in Paraburkholderia xenovorans.

BACKGROUND: Bacterial aromatic degradation may cause oxidative stress. The long-chain flavodoxin FldX1 of Paraburkholderia xenovorans LB400 counteracts reactive oxygen species (ROS). The aim of this study was to evaluate the protective role of FldX1 in P. xenovorans LB400 during the degradation of 4-hydroxyphenylacetate (4-HPA) and 3-hydroxyphenylacetate (3-HPA). METHODS: The functionality of FldX1 was evaluated in P. xenovorans p2-fldX1 that overexpresses FldX1. The effects of FldX1 on P. xenovorans were studied measuring growth on hydroxyphenylacetates, degradation of 4-HPA and 3-HPA, and ROS formation. The effects of hydroxyphenylacetates (HPAs) on the proteome (LC-MS/MS) and gene expression (qRT-PCR) were quantified. Bioaugmentation with strain p2-fldX1 of 4-HPA-polluted soil was assessed, measuring aromatic degradation (HPLC), 4-HPA-degrading bacteria, and plasmid stability. RESULTS: The exposure of P. xenovorans to 4-HPA increased the formation of ROS compared to 3-HPA or glucose. P. xenovorans p2-fldX1 showed an increased growth on 4-HPA and 3-HPA compared to the control strain WT-p2. Strain p2-fldX1 degraded faster 4-HPA and 3-HPA than strain WT-p2. Both WT-p2 and p2-fldX1 cells grown on 4-HPA displayed more changes in the proteome than cells grown on 3-HPA in comparison to glucose-grown cells. Several enzymes involved in ROS detoxification, including AhpC2, AhpF, AhpD3, KatA, Bcp, CpoF1, Prx1 and Prx2, were upregulated by hydroxyphenylacetates. Downregulation of organic hydroperoxide resistance (Ohr) and DpsA proteins was observed. A downregulation of the genes encoding scavenging enzymes (katE and sodB), and gstA and trxB was observed in p2-fldX1 cells, suggesting that FldX1 prevents the antioxidant response. More than 20 membrane proteins, including porins and transporters, showed changes in expression during the growth of both strains on hydroxyphenylacetates. An increased 4-HPA degradation by recombinant strain p2-fldX1 in soil microcosms was observed. In soil, the strain overexpressing the flavodoxin FldX1 showed a lower plasmid loss, compared to WT-p2 strain, suggesting that FldX1 contributes to bacterial fitness. Overall, these results suggest that recombinant strain p2-fldX1 is an attractive bacterium for its application in bioremediation processes of aromatic compounds. CONCLUSIONS: The long-chain flavodoxin FldX1 improved the capability of P. xenovorans to degrade 4-HPA in liquid culture and soil microcosms by protecting cells against the degradation-associated oxidative stress.

Influenza A virus replicates productively in primary human kidney cells and induces factors and mechanisms related to regulated cell death and renal pathology observed in virus-infected patients.

Introduction: Influenza A virus (IAV) infection can cause the often-lethal acute respiratory distress syndrome (ARDS) of the lung. Concomitantly, acute kidney injury (AKI) is frequently noticed during IAV infection, correlating with an increased mortality. The aim of this study was to elucidate the interaction of IAV with human kidney cells and, thereby, to assess the mechanisms underlying IAV-mediated AKI. Methods: To investigate IAV effects on nephron cells we performed infectivity assays with human IAV, as well as with human isolates of either low or highly pathogenic avian IAV. Also, transcriptome and proteome analysis of IAV-infected primary human distal tubular kidney cells (DTC) was performed. Furthermore, the DTC transcriptome was compared to existing transcriptomic data from IAV-infected lung and trachea cells. Results: We demonstrate productive replication of all tested IAV strains on primary and immortalized nephron cells. Comparison of our transcriptome and proteome analysis of H1N1-type IAV-infected human primary distal tubular cells (DTC) with existing data from H1N1-type IAV-infected lung and primary trachea cells revealed enrichment of specific factors responsible for regulated cell death in primary DTC, which could be targeted by specific inhibitors. Discussion: IAV not only infects, but also productively replicates on different human nephron cells. Importantly, multi-omics analysis revealed regulated cell death as potential contributing factor for the clinically observed kidney pathology in influenza.

Central subfield thickness of diabetic macular edema: Correlation with the aqueous humor proteome.

Purpose: Diabetic macular edema (DME) is a sight-threatening complication of diabetes. Consequently, studying the proteome of DME may provide novel insights into underlying molecular mechanisms. Methods: In this study, aqueous humor samples from eyes with treatment-naïve clinically significant DME (n = 13) and age-matched controls (n = 11) were compared with label-free liquid chromatography-tandem mass spectrometry. Additional aqueous humor samples from eyes with treatment-naïve DME (n = 15) and controls (n = 8) were obtained for validation by enzyme-linked immunosorbent assay (ELISA). Best-corrected visual acuity (BCVA) was evaluated, and the severity of DME was measured as central subfield thickness (CST) employing optical coherence tomography. Control samples were obtained before cataract surgery. Significantly changed proteins were identified using a permutation-based calculation, with a false discovery rate of 0.05. A human donor eye with DME and a control eye were used for immunofluorescence. Results: A total of 101 proteins were differentially expressed in the DME. Regulated proteins were involved in complement activation, glycolysis, extracellular matrix interaction, and cholesterol metabolism. The highest-fold change was observed for the fibrinogen alpha chain (fold change = 17.8). Complement components C2, C5, and C8, fibronectin, and hepatocyte growth factor-like protein were increased in DME and correlated with best-corrected visual acuity (BCVA). Ceruloplasmin and complement component C8 correlated with central subfield thickness (CST). Hemopexin, plasma kallikrein, monocyte differentiation antigen CD14 (CD14), and lipopolysaccharide-binding protein (LBP) were upregulated in the DME. LBP was correlated with vascular endothelial growth factor. The increased level of LBP in DME was confirmed using ELISA. The proteins involved in desmosomal integrity, including desmocollin-1 and desmoglein-1, were downregulated in DME and correlated negatively with CST. Immunofluorescence confirmed the extravasation of fibrinogen at the retinal level in the DME. Conclusion: Elevated levels of pro-inflammatory proteins, including the complement components LBP and CD14, were observed in DME. DME was associated with the loss of basal membrane proteins, compromised desmosomal integrity, and perturbation of glycolysis.

Adaptive laboratory evolution of Clostridium autoethanogenum to metabolize CO2 and H2 enhances growth rates in chemostat and unravels proteome and metabolome alterations.

Gas fermentation of CO2 and H2 is an attractive means to sustainably produce fuels and chemicals. Clostridium autoethanogenum is a model organism for industrial CO to ethanol and presents an opportunity for CO2-to-ethanol processes. As we have previously characterized its CO2/H2 chemostat growth, here we use adaptive laboratory evolution (ALE) with the aim of improving growth with CO2/H2. Seven ALE lineages were generated, all with improved specific growth rates. ALE conducted in the presence of 2% CO along with CO2/H2 generated Evolved lineage D, which showed the highest ethanol titres amongst all the ALE lineages during the fermentation of CO2/H2. Chemostat comparison against the parental strain shows no change in acetate or ethanol production, while Evolved D could achieve a higher maximum dilution rate. Multi-omics analyses at steady state revealed that Evolved D has widespread proteome and intracellular metabolome changes. However, the uptake and production rates and titres remain unaltered until investigating their maximum dilution rate. Yet, we provide numerous insights into CO2/H2 metabolism via these multi-omics data and link these results to mutations, suggesting novel targets for metabolic engineering in this bacterium.

Melanin depletion affects Aspergillus flavus conidial surface proteins, architecture, and virulence.

Melanin is an Aspergillus flavus cell wall component that provides chemical and physical protection to the organism. However, the molecular and biological mechanisms modulating melanin-mediated host-pathogen interaction in A. flavus keratitis are not well understood. This work aimed to compare the morphology, surface proteome profile, and virulence of melanized conidia (MC) and non-melanized conidia (NMC) of A. flavus. Kojic acid treatment inhibited melanin synthesis in A. flavus, and the conidial surface protein profile was significantly different in kojic acid-treated non-melanized conidia. Several cell wall-associated proteins and proteins responsible for oxidative stress, carbohydrate, and chitin metabolic pathways were found only in the formic acid extracts of NMC. Scanning electron microscopy (SEM) analysis showed the conidial surface morphology difference between the NMC and MC, indicating the role of melanin in the structural integrity of the conidial cell wall. The levels of calcofluor white staining efficiency were different, but there was no microscopic morphology difference in lactophenol cotton blue staining between MC and NMC. Evaluation of the virulence of MC and NMC in the Galleria mellonella model showed NMC was less virulent compared to MC. Our findings showed that the integrity of the conidial surface is controlled by the melanin layer. The alteration in the surface protein profile indicated that many surface proteins are masked by the melanin layer, and hence, melanin can modulate the host response by preventing the exposure of fungal proteins to the host immune defense system. The G. mellonella virulence assay also confirmed that the NMC were susceptible to host defense as in other Aspergillus pathogens. KEY POINTS: • l-DOPA melanin production was inhibited in A. flavus isolates by kojic acid, and for the first time, scanning electron microscopy (SEM) analysis revealed morphological differences between MC and NMC of A. flavus strains • Proteome profile of non-melanized conidia showed more conidial surface proteins and these proteins were mainly involved in the virulence, oxidative stress, and metabolism pathways • Non-melanized conidia of A. flavus strains were shown to be less virulent than melanised conidia in an in vivo virulence experiment with the G. melonella model.

Glycolysis is reduced in dengue virus 2 infected liver cells.

Infections with dengue virus (DENV) remain a worldwide public health problem. A number of bona fide cellular targets of DENV have been identified including liver cells. Despite the many lines of evidence confirming the involvement of hepatocytes during DENV infection, only a few studies have used proteomic analysis to understand the modulation of the cellular proteome occurring upon DENV infection. We utilized a 2D-gel electrophoresis analysis to identify proteins that were differentially regulated by DENV 2 infection of liver (Hep3B) cells at 12 h post infection (hpi) and at 48 hpi. The analysis identifies 4 proteins differentially expressed at 12 hpi, and 14 differentially regulated at 48 hpi. One candidate protein identified as downregulated at 48 hpi in the proteomic analysis (GAPDH) was validated in western blotting in Hep3B cells, and subsequently in induced pluripotent stem cell (iPSC) derived human hepatocytes. The reduced expression of GAPDH was coupled with an increase in NADH, and a significantly reduced NAD + /NADH ratio, strongly suggesting that glycolysis is down regulated in response to DENV 2 infection. Metformin, a well characterized drug used in the treatment of diabetes mellitus, is an inhibitor of hepatic gluconeogenesis was shown to reduce the level of DENV 2 infection and new virus production. Collectively these results show that although glycolysis is reduced, glucose is still required, possibly for use by the pentose phosphate pathway to generate nucleosides required for viral replication.

Native-state proteomics of Parvalbumin interneurons identifies unique molecular signatures and vulnerabilities to early Alzheimer's pathology.

Dysfunction in fast-spiking parvalbumin interneurons (PV-INs) may represent an early pathophysiological perturbation in Alzheimer's Disease (AD). Defining early proteomic alterations in PV-INs can provide key biological and translationally-relevant insights. We used cell-type-specific in-vivo biotinylation of proteins (CIBOP) coupled with mass spectrometry to obtain native-state PV-IN proteomes. PV-IN proteomic signatures include high metabolic and translational activity, with over-representation of AD-risk and cognitive resilience-related proteins. In bulk proteomes, PV-IN proteins were associated with cognitive decline in humans, and with progressive neuropathology in humans and the 5xFAD mouse model of Aß pathology. PV-IN CIBOP in early stages of Aß pathology revealed signatures of increased mitochondria and metabolism, synaptic and cytoskeletal disruption and decreased mTOR signaling, not apparent in whole-brain proteomes. Furthermore, we demonstrated pre-synaptic defects in PV-to-excitatory neurotransmission, validating our proteomic findings. Overall, in this study we present native-state proteomes of PV-INs, revealing molecular insights into their unique roles in cognitive resiliency and AD pathogenesis.

Optimizing environmental enrichment for Sprague Dawley rats: Exemplary insights into the liver proteome.

BACKGROUND: Considering the expected increase in the elderly population and the growing emphasis on aging-related biomedical research, the demand for aged laboratory animals has surged, challenging established husbandry practices. Our objective was to establish a cost-effective method for environmental enrichment, utilizing the liver as a representative organ to assess potential metabolic changes in response to differing enrichment levels. METHODS: We conducted a six-month study involving 24 male Sprague Dawley rats, randomly assigned to four environmental enrichment groups. Two groups were housed in standard cages, while the others were placed in modified rabbit cages. Half of the groups received weekly playtime in an activity focused rat housing unit. We evaluated hormone levels, playtime behavior, and subjective handling experience. Additionally, liver tissue proteomic analysis was performed. RESULTS: Initial corticosterone levels and those after 3 and 6 months showed no significant differences. Yet, testosterone levels were lower in the control group by the end of the study (p = 0.007). We observed 1871 distinct proteins in liver tissue, with 77% being common across groups. In gene ontology analysis, no specific pathways were overexpressed. In semiquantitative analysis, we observed differences in proteins associated in lipid metabolism such as Apolipoprotein A-I and Acyl-CoA 6-desaturase, which were lower in the control group (p = 0.024 and p = 0.009). Rats in the intervention groups with weekly playtime displayed the least amount of reported distress during inspection or upon room entry and were less prone to accepting treats. Removing animals from their enclosure was most effortless for those in the large cage group. Over time, there was a decrease in conflicts among rats that interacted only twice weekly during playpen time. DISCUSSION: In summary, refining husbandry practices for aging rats is both simple and budget-friendly, with no apparent adverse effects on stress levels, animal development, or relevant metabolic changes in the liver.

Heat stress alters the ovarian proteome in prepubertal gilts.

Heat stress (HS) occurs when exogenous and metabolic heat accumulation exceeds heat dissipation; a thermal imbalance that compromises female reproduction. This study investigated the hypothesis that HS alters the ovarian proteome and negatively impacts proteins engaged with insulin signaling, inflammation, and ovarian function. Prepubertal gilts (n = 19) were assigned to one of three environmental groups: thermal neutral with ad libitum feed intake (TN; n = 6), thermal neutral pair-fed (PF; n = 6), or HS (n = 7). For 7 d, HS gilts were exposed to 12-h cyclic temperatures of 35.0 ±â€…0.2 °C and 32.2 ±â€…0.1 °C, while TN and PF gilts were housed at 21.0 ±â€…0.1 °C. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was performed on ovarian protein homogenates. Relative to TN gilts, 178 proteins were altered (P ≤ 0.05, log2foldchange ≥ 1) by HS, with 76 increased and 102 decreased. STRING gene ontology classified and identified 45 biological processes including those associated with chaperone protein refolding, cytoplasmic translational initiation, and immune activation; with a protein-protein interaction web network of 158 nodes and 563 edges connected based on protein function (FDR ≤ 0.05). Relative to PF, HS altered 330 proteins (P ≤ 0.05, log2foldchange ≥ 1), with 151 increased and 179 decreased. Fifty-seven biological pathways associated with protein function and assembly, RNA processing, and metabolic processes were identified, with a protein-protein interaction network of 303 nodes and 1,606 edges. Comparing HS with both the TN and PF treatments, 72 ovarian proteins were consistently altered by HS with 68 nodes and 104 edges, with biological pathways associated with translation and gene expression. This indicates that HS alters the ovarian proteome and multiple biological pathways and systems in prepubertal gilts; changes that potentially contribute to female infertility.

Heat stress impairs female fertility, yet the mechanisms underlying reduced fecundity remain unclear. This study investigated the ovarian proteomic changes resultant from heat stress in prepubertal gilts and discovered changes related to several important biological processes that could be responsible for reduced female fertility.

TOPMed imputed genomics enhances genomic atlas of the human proteome in brain, cerebrospinal fluid, and plasma.

Comprehensive expression quantitative trait loci studies have been instrumental for understanding tissue-specific gene regulation and pinpointing functional genes for disease-associated loci in a tissue-specific manner. Compared to gene expressions, proteins more directly affect various biological processes, often dysregulated in disease, and are important drug targets. We previously performed and identified tissue-specific protein quantitative trait loci in brain, cerebrospinal fluid, and plasma. We now enhance this work by analyzing more proteins (1,300 versus 1,079) and an almost twofold increase in high quality imputed genetic variants (8.4 million versus 4.4 million) by using TOPMed reference panel. We identified 38 genomic regions associated with 43 proteins in brain, 150 regions associated with 247 proteins in cerebrospinal fluid, and 95 regions associated with 145 proteins in plasma. Compared to our previous study, this study newly identified 12 loci in brain, 30 loci in cerebrospinal fluid, and 22 loci in plasma. Our improved genomic atlas uncovers the genetic control of protein regulation across multiple tissues. These resources are accessible through the Online Neurodegenerative Trait Integrative Multi-Omics Explorer for use by the scientific community.

Cross-link assisted spatial proteomics to map sub-organelle proteomes and membrane protein topologies.

The functions of cellular organelles and sub-compartments depend on their protein content, which can be characterized by spatial proteomics approaches. However, many spatial proteomics methods are limited in their ability to resolve organellar sub-compartments, profile multiple sub-compartments in parallel, and/or characterize membrane-associated proteomes. Here, we develop a cross-link assisted spatial proteomics (CLASP) strategy that addresses these shortcomings. Using human mitochondria as a model system, we show that CLASP can elucidate spatial proteomes of all mitochondrial sub-compartments and provide topological insight into the mitochondrial membrane proteome. Biochemical and imaging-based follow-up studies confirm that CLASP allows discovering mitochondria-associated proteins and revising previous protein sub-compartment localization and membrane topology data. We also validate the CLASP concept in synaptic vesicles, demonstrating its applicability to different sub-cellular compartments. This study extends the scope of cross-linking mass spectrometry beyond protein structure and interaction analysis towards spatial proteomics, and establishes a method for concomitant profiling of sub-organelle and membrane proteomes.

The plasma proteome differentiates the multisystem inflammatory syndrome in children (MIS-C) from children with SARS-CoV-2 negative sepsis.

BACKGROUND: The Multi-System Inflammatory Syndrome in Children (MIS-C) can develop several weeks after SARS-CoV-2 infection and requires a distinct treatment protocol. Distinguishing MIS-C from SARS-CoV-2 negative sepsis (SCNS) patients is important to quickly institute the correct therapies. We performed targeted proteomics and machine learning analysis to identify novel plasma proteins of MIS-C for early disease recognition. METHODS: A case-control study comparing the expression of 2,870 unique blood proteins in MIS-C versus SCNS patients, measured using proximity extension assays. The 2,870 proteins were reduced in number with either feature selection alone or with a prior COMBAT-Seq batch effect adjustment. The leading proteins were correlated with demographic and clinical variables. Organ system and cell type expression patterns were analyzed with Natural Language Processing (NLP). RESULTS: The cohorts were well-balanced for age and sex. Of the 2,870 unique blood proteins, 58 proteins were identified with feature selection (FDR-adjusted P < 0.005, P < 0.0001; accuracy = 0.96, AUC = 1.00, F1 = 0.95), and 15 proteins were identified with a COMBAT-Seq batch effect adjusted feature selection (FDR-adjusted P < 0.05, P < 0.0001; accuracy = 0.92, AUC = 1.00, F1 = 0.89). All of the latter 15 proteins were present in the former 58-protein model. Several proteins were correlated with illness severity scores, length of stay, and interventions (LTA4H, PTN, PPBP, and EGF; P < 0.001). NLP analysis highlighted the multi-system nature of MIS-C, with the 58-protein set expressed in all organ systems; the highest levels of expression were found in the digestive system. The cell types most involved included leukocytes not yet determined, lymphocytes, macrophages, and platelets. CONCLUSIONS: The plasma proteome of MIS-C patients was distinct from that of SCNS. The key proteins demonstrated expression in all organ systems and most cell types. The unique proteomic signature identified in MIS-C patients could aid future diagnostic and therapeutic advancements, as well as predict hospital length of stays, interventions, and mortality risks.