Proteomic Studies Research Articles

Abstract TP140: The Blood Proteome Profiling Identifies Biomarkers Associated With Ischemic Stroke Prognosis

Blackground: Due to the narrow therapeutic time window and strict indications, there are still a large number of patients unable to receive thrombolysis and endovascular therapy, resulting in a poor long-term functional prognosis. Moreover, it is unclear what effective therapeutic targets as well as molecular systemic changes in stroke in the chronic phase. Therefore, to provide useful insights into its pathogenesis, identification of therapeutic targets and biomarker discovery, we analyze the proteomic profile of blood in ischemic stroke patients in order to gain insights into the disease. Method: We use proteomics technologies to examine serum at baseline and use the modified Rankin Scale (mRS) to evaluate neurological function at baseline and 3-month follow-up after ischemic stroke. Based on data-independent acquisition mass spectrometry and parallel reaction monitoring (PRM) technology, we implement a staged discovery-confirmatory pipeline in serum samples from better prognosis patients(n=48) and poor prognosis patients(n=50) according to mRS to comprehensively identify and validate more accurate biomarker performance characteristics of candidate proteins. Results: In this proteomic study, we characterize 4,740 circulating proteins and 324 differentially expressed proteins in 98 patients. We identify circulating proteomic signatures for ischemic stroke prognosis, and correlate these with clinical data to develop a proteomic profile of 14 markers. Based on machine learning algorithms such as LASSO regression and exhaustive feature selection (EFS), we finally identify some biomarkers (IQGAP2, LYZ, PDGFD, EHD3, CETP, FYB1) are validated as contributors to the ischemic stroke prognosis model through verification of an additional 58 serum samples. (AUC range:0.65-0.99). Conclusion: We identify potential biomarkers and therapeutic targets and offer an opportunity for more precise prognosis and treatment in ischemic stroke.

Abstract WP93: Cross-Platform Proteomics and Machine Learning Algorithms Nominate Biomarkers of Atrial Fibrillation in Stroke Patients: An Exploratory Study

Introduction: Atrial fibrillation (AFib) is a major risk factor for ischemic stroke (IS). AFib diagnosis is critical to optimize secondary prevention and reduce the recurrent stroke risk. Objectives: We undertook an exploratory cross-platform proteomics study to discover plasma biomarkers of AFib diagnosis in patients with IS or transient ischemic attack (TIA). Methods: We used clinical and proteomics data of stroke patients aged ≥18 years lodged within a prospective plasma repository from 2010 to 2014. We collected blood from each patient at hospital admission before administering any therapeutic intervention. Our outcome was differentially expressed levels of proteins in stroke patients with AFib compared to patients without AFib. We performed aptamer-based proteomics using the plasma 7K SomaScan assay. We identified the differentially expressed proteins using (i) ±1.5-fold change and unadjusted p-value <0.05 cut-offs, (ii) Boruta random forest-based machine learning algorithm, and (iii) 30% or more variation explained by AFib in variance partitioning analysis (VPA). We selected the top proteins that were identified using two of the three selection approaches and conducted multivariable adjusted analyses. We conducted internal validation on the same samples using the PeptiQuant Plus biomarker assessment kits (BAK-270) for targeted protein quantitation. Results: We included 60 patients with IS/TIA (mean age 62.9 years, 50% males) classified into 11 AFib and 49 no AFib (Figure 1). SomaScan quantified 7307 protein targets including 6373 unique proteins. We identified 171 differentially expressed proteins in stroke patients with AFib compared to no AFib. After adjusting for age, sex, diabetes, and coronary artery disease in the multivariable analysis, we identified 53 top proteins independently associated with AFib in stroke patients (adjusted p<0.05) (Figure 2). In the validation phase, we quantified 216 proteins using the BAK-270 platform, of which 185 proteins were overlapping with SomaScan. Using BAK-270, we validated increased levels of IGFBP2, B2M, and COL18A1 and decreased levels of CNDP1, AHSG, and SERPINA4 in stroke patients with AFib compared to no AFib (Figure 3). Conclusions: Our exploratory study highlights the potential of plasma proteomics as a valuable tool for discovering protein biomarkers to discriminate IS/TIA patients with AFib compared to no AFib. Further longitudinal studies with adequate sample sizes are needed to support these findings.

Phosphoproteomics delineates hepatocellular carcinoma subtypes and pinpoints therapeutic targets.

Only a minority of patients could benefit from systemic therapy owing to the high heterogeneity of HCC. Therefore, a deeper understanding of the pathogenesis of HCC is essential for precision therapy. Genomic and proteomic studies of HCC have enhanced our understanding of HCC. However, phosphoproteomic characterization of HCC remains poorly understood. We conducted an in-depth analysis of a clinical cohort of HCC using high-coverage phosphoproteomic. Effective therapeutic targets were validated using liver cancer cell lines and HCC patient-derived xenograft (PDX) mouse models that correspond to the phosphoproteomic subtypes of HCC. Phosphoproteomic analysis classified HCC into three subtypes, A, B, and C, with increasing malignancy and correlation with clinical features, including patient prognosis, tumor staging, serum alpha fetoprotein (AFP) levels, tumor thrombus, and tumor size. Phosphoproteomic subtyping deeply reflected the biological characteristics and clinical features of HCC patients. The profiles of HCC dysregulated kinase activities inferred from the different phosphoproteomic subtypes, consistently identifying increased kinase activity related to cell proliferation. Subtype-C HCC patients showed the most significant dysregulation, indicating a potential therapeutic target. The corresponding drug, bosutinib, demonstrated efficacy in inhibiting the growth of subtype C tumors in liver cancer cell lines and HCC patient-derived xenograft (PDX) mouse models representative of the phosphoproteomic HCC subtypes. Our study provides a comprehensive exploration of the phosphoproteomic landscape of HCC, establishing new subtypes that match clinical features and identifying potential therapeutic targets for the most malignant C subtype.

Relative quantification of proteins and post-translational modifications in proteomic experiments with shared peptides: a weight-based approach.

Bottom-up mass spectrometry-based proteomics studies changes in protein abundance and structure across conditions. Since the currency of these experiments are peptides, ie subsets of protein sequences that carry the quantitative information, conclusions at a different level must be computationally inferred. The inference is particularly challenging in situations where the peptides are shared by multiple proteins or post-translational modifications. While many approaches infer the underlying abundances from unique peptides, there is a need to distinguish the quantitative patterns when peptides are shared. We propose a statistical approach for estimating protein abundances, as well as site occupancies of post-translational modifications, based on quantitative information from shared peptides. The approach treats the quantitative patterns of shared peptides as convex combinations of abundances of individual proteins or modification sites, and estimates the abundance of each source in a sample together with the weights of the combination. In simulation-based evaluations, the proposed approach improved the precision of estimated fold changes between conditions. We further demonstrated the practical utility of the approach in experiments with diverse biological objectives, ranging from protein degradation and thermal proteome stability, to changes in protein post-translational modifications. The approach is implemented in an open-source R package MSstatsWeightedSummary. The package is currently available at https://github.com/Vitek-Lab/MSstatsWeightedSummary (doi:10.5281/zenodo.14662989). Code required to reproduce the results presented in this article can be found in a repository https://github.com/mstaniak/MWS_reproduction (doi:10.5281/zenodo.14656053). Supplementary data are available at Bioinformatics online.

Glymphatic system clearance and Alzheimer’s disease risk: a CSF proteome-wide study

BackgroundThe emerging evidence of the role of the glymphatic system (GS) in Alzheimer’s disease (AD) provides new opportunities for intervention from the earliest stages of the disease. The aim of the study is to evaluate the efficacy of GS in AD to identify new disease biomarkers. MethodsWe performed a two-stage proteomic study to evaluate the GS health using intravenous gadolinium-based contrast agent (GBCA) with serial T1 3T magnetic resonance imaging (MRI) in individuals with amnestic mild cognitive impairment (aMCI). In Stage 1 (evaluated in the Cohort 1 of aMCI participants (n = 11)), we correlated the levels of 7K cerebrospinal fluid (CSF) proteins (estimated by SOMAscan) with GS health in 78 Freesurfer-segmented brain regions of interest (ROIs).ResultsA total of seven different proteins were significantly associated with GS health (p-value < 6.4 × 10–4). The stronger correlations were identified for NSUN6, GRAAK, OLFML3, ACTN2, RUXF, SHPS1 and TIM-4. A pathway enrichment analysis revealed that the proteins associated with GS health were mainly implicated in neurodegenerative processes, immunity and inflammation. In Stage 2, we validated these proteomic results in a new cohort of aMCI participants (with and without evidence of AD pathology in CSF (aMCI(-) and aMCI/AD( +); n = 22 and 7, respectively) and healthy controls (n = 10). Proteomic prediction models were generated in each ROI. These were compared with demographic-only models for identifying participants with aMCI(-) and aMCI/AD( +) vs controls. This analysis was repeated to determine if the models could identify those with aMCI/AD( +) from both aMCI(-) and controls. The proteomic models were found to outperform the demographic-only models.ConclusionsOur study identifies proteins linked with GS health and involved the immune system in aMCI participants.

Revisiting the Effect of Trypsin Digestion Buffers on Artificial Deamidation.

Deamidation of asparagine and glutamine residues occurs spontaneously, is influenced by pH, temperature, and incubation time, and can be accelerated by adjacent amino acid residues. Incubation conditions used for proteolytic digestion in bottom-up proteomic studies can induce significant deamidation that affects results, either knowingly or unknowingly. This has prompted studies into modifications to common trypsin digestion protocols to minimize chemical deamidation, including shorter incubation times and specific lysis buffers. Prior work suggested ammonium acetate at pH 6 to minimize chemical deamidation, but this buffer has compatibility issues with trypsin digestion and common assays (e.g., bicinchoninic acid assays). Here, we re-evaluated former comparisons of Tris-HCl, ammonium bicarbonate, and triethylammonium bicarbonate buffers for the amount of artificial, chemically induced deamidation generated in a standard bottom-up proteomics workflow, and we added an evaluation of three commonly used and biologically compatible buffers, HEPES (4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid), EPPS (3-[4-(2-Hydroxyethyl)piperazin-1-yl]propane-1-sulfonic acid), and PBS (phosphate buffered saline). Our findings show that HEPES exhibited the least amount of artificial deamidation and is a reasonable choice for general proteomic experiments, especially for studies considering N-glycosylation.

Quantitative proteomic studies of the intestinal mucosa provide new insights into the molecular mechanism of ulcerative colitis

BackgroundDifferentiation between ulcerative colitis (UC) and other intestinal inflammatory diseases is difficult, and the precise etiology of UC is poorly understood. Thus, there is a need for novel diagnostic and prognostic biomarkers for UC.MethodsIntestinal mucosal biopsy tissue specimens of inflamed (ulcerative colitis-inflamed, UC-I) and non-inflamed (ulcerative colitis-noninflamed, UC-N) tissue were obtained simultaneously during colonoscopy from newly diagnosed UC patients prior to any treatments. Label-free liquid chromatography tandem mass spectrometry (LC-MS/MS) quantitative proteomics was used to detect proteomic differences between UC-I, UC-N, and normal control subjects (n = 5). Proteins with a fold-change > 1.5 and P < 0.05 between groups were considered to be differentially expressed (DEPs). Candidate biomarkers were further verified in 8 patients of each group by parallel reaction monitoring (PRM) (a prospective cohort, n = 8). Expression of TXNDC5 was quantified using immunohistochemistry (IHC).ResultsA total of 4,788 proteins were identified. Multiple upregulated pathways, including leukocyte trans-endothelial migration and natural killer (NK) cell-mediated cytotoxicity, were identified. Network analysis showed that proteins were involved in 4 pathways in UC-I and 3 pathways in UC-N tissues, and participated in protein-protein interactions. Increased expression of 9 DEPs, including TXNDC5, EPX, and ITGAM were detected in UC patients compared to normal control subjects. Subsequent verification of the 9 DEPs by PRM confirmed the reliability of the mass spectrometry data. TXNDC5 expression was significantly increased in UC.ConclusionsThe pathways, networks, and proteins identified in this study may provide new insights into the molecular pathogenesis of UC. Further studies are required to determine if the proteins identified may help in the diagnosis and treatment of UC.

Novel protocol for isolation and transient transformation of Rhodes grass (Chloris gayana) protoplasts

Abstract Rhodes grass (Chloris gayana) is a warm-season C4 grass currently grown as a forage in some tropical regions, with anticipated future application in areas affected by climate change. However, there are few resources available for this grass, with few genomic resources and only one established transformation system, thus limiting the application of biotechnology methods for its improvement. Protoplast transformation can be used as a time- and resource-efficient way to examine gene pathways and functions of transcriptional elements via proteomics and transcriptomics, and to validate gene constructs. The aim of this work was therefore to establish the first Rhodes grass leaf mesophyll protoplast isolation and transient transformation protocol. A range of protoplast isolation factors were examined, including enzyme quantity and vacuum infiltration time. Up to 4.13 × 106 protoplasts were isolated per gram of fresh weight with an average 94.8% viability from an overnight digestion protocol with 4% (w/v) cellulase R10, 0.8% (w/v) Macerozyme R10, and no vacuum infiltration. Transformation conditions were optimized via Taguchi’s orthogonal array, which compared combinations of three levels each of green fluorescent protein (GFP) plasmid DNA quantity, polyethylene glycol (PEG) concentration, and transformation time. A transient transformation efficiency of up to 27.88% was observed by GFP expression. DNA quantity was identified to be the only factor from those tested effecting transformation efficiency (p &lt; 0.001) in a linear way. Work here represents the first report for Rhodes grass protoplast isolation and transformation, which could facilitate genome editing and transcriptome and proteome studies.

Immune Checkpoints and the Immunology of Liver Fibrosis

Liver fibrosis is a very complicated dynamic process where several immune cells are involved. Both innate and adaptive immunity are implicated, and their interplay is always present. Multi-directional interactions between liver macrophages, hepatic stellate cells (HSCs), immune cells, and several cytokines are important for the induction and perpetuation of liver fibrosis. Detailed studies of proteomics and transcriptomics have produced new evidence for the role of individual cells in the process of liver fibrosis and cirrhosis. Most of these cells are controlled by the various immune checkpoints whose main function is to maintain the homeostasis of the implicated immune cells. Recent evidence indicates that several immune checkpoints are involved in liver fibrosis. In particular, the role of the programmed cell death protein 1 (PD-1), the programmed death-ligand 1 (PD-L1), and the role of the cytotoxic T lymphocyte-associated antigen 4 (CTLA-4) have been investigated, particularly after the availability of checkpoint inhibitors. Their activation leads to the exhaustion of CD4+ve and CD8+ve T cells and the promotion of liver fibrosis. In this review, the current pathogenesis of liver fibrosis and the immunological abnormalities are discussed. The recent data on the involvement of immune checkpoints are identified as possible targets of future interventions.

Neuro-reproductive toxicity and carcinogenicity of 1-bromopropane - studies for evidence-based preventive medicine (EBPM).

Bromopropane was introduced commercially as an alternative to ozone-depleting and global warming solvents. The identification of 1-bromopropane neurotoxicity in animal experiments was followed by reports of human cases of 1-bromopropane toxicity. In humans, the most common clinical features of 1-bromopropane neurotoxicity are decreased sensation, weakness in extremities, and walking difficulties. Moreover, decreased cognition, abnormal findings on brain magnetic resonance imaging, urinary incontinence, and numbness in the perineal area have also been described in workers exposed to 1-bromoporopane. Murine histological studies showed that exposure to 1-bromopropane reduced the density of brain noradrenergic axons. Furthermore, proteome studies demonstrated 1-bromopropane-induced changes in the expression of proteins in the hippocampus of rats, similar to the changes seen in mice exposed to acrylamide, suggesting a common mechanism of electrophile-induced neurotoxicity. In addition to its neurotoxicity, 1-bromopropane also induces male reproductive toxicity in rats, though the targeted areas in the reproductive system differ from those affected by 2-bromopropane. However, exposure to high levels of 1-bromopropane was reported to induce spermatogenic cell degeneration, similar to that caused by 2-bromopropane, suggesting common mechanism(s) underlying 1- and 2-bromopropane-induced male reproductive toxicity. Plural approaches, including human, animal and mechanistic studies, are useful for identification of 1-bromopropane neurotoxicity. The International Agency for Research on Cancer (IARC) summarized that 1-bromopropane as well as 2-bromopropane share several key characteristics of carcinogens. Plural approaches can establish evidence-based preventive medicine (EBPM) by modification of the conventional evidence-based medicine (EBM), which has been developed for therapeutic medicine and represented by the EBM pyramid.

Pharma teams up for huge proteomics study

Pharma teams up for huge proteomics study

Abstract B031: Proteomic profiling of oligometastatic castration-sensitive prostate cancer treated with stereotactic ablative radiotherapy

Abstract Background: The trajectory of metastatic castration-sensitive prostate cancer varies based on disease presentation and biology. While proteomic profiling studies of primary prostate tissue have linked protein expression with metastatic progression and prognosis, few studies have explored biological changes after treatment and their associations with response. Therefore, we conducted proteomic profiling of patients with oligometastatic castration-sensitive prostate cancer (omCSPC) treated with stereotactic ablative radiotherapy (SABR) or observation in the ORIOLE phase 2 randomized clinical trial (RCT). Methods Plasma from omCSPC patients in the ORIOLE trial was collected at baseline (day 1), day 90, and day 180. Protein abundance was quantified using the Olink Explore Assay. Differential expression from baseline to day 90 or 180 in each treatment arm was analyzed using a 2-sided t-test with Benjamini-Hochberg correction. Changes in protein expression at day 90 and 180 were compared with a Pearson correlation. Pathway enrichment was performed via gene set enrichment analysis (GSEA) using Reactome, KEGG, and Hallmark gene sets. Associations with progression-free survival (PFS) were analyzed using Kaplan-Meier and log-rank tests. Results In total, 1,472 proteins were assayed across 130 samples from 46 patients over 3 time points. Significant changes in expression post-SABR were noted at day 90 and 180 compared to baseline (using adjusted p-value cutoff of 0.05). At day 90, four proteins (FCRL1, CD22, TCL1A, FCER2) were downregulated; at day 180, only FCRL1, a Fc receptor-like gene family preferentially expressed in B cells, remained downregulated. No significant expression changes were found in the observation arm. Differential expression of proteins during follow-up were associated with PFS. In particular, LTO1, a maturation factor of ABCE1 important for ribosomal biogenesis and translation, was overexpressed at both day 90 and 180 post-SABR, and overexpression was associated with improved PFS at day 90 (median 24.5 mo vs 6 mo; p=0.017) and day 180 (median 33 mo vs 6 mo; p=0.043). These associations were absent in the observation arm. For proteins differentially expressed in the SABR arm at day 90, several signaling pathways were significantly enriched for patients with prolonged PFS, including positive enrichment of unfolded protein response (UPR) (p=0.008) and IL-4/IL-13 (p=0.009). At 180 days, several pathways were enriched for patients with prolonged PFS including negative enrichment of CTLA4 inhibitory signaling (p=0.005) and CD28 co-stimulation (p=0.008). Conclusion Proteomic analysis in omCSPC patients from the ORIOLE trial reveals significant expression changes at days 90 and 180 after SABR. B-cell signaling proteins were selectively downregulated in the SABR arm, and pathways associated with protein translation and immune response were enriched post-SABR for patients with prolonged PFS. Further research will explore connections to genomic and transcriptomic changes, with additional validation needed. Citation Format: Jarey H. Wang, Amol Shetty, Yang Song, Noura Radwan, Soha Bazyar, Xiaolei Shi, Theodore L. DeWeese, Daniel Y. Song, Ryan M. Phillips, Matthew P. Deek, Philip Sutera, Ana P. Kiess, Phuoc T. Tran. Proteomic profiling of oligometastatic castration-sensitive prostate cancer treated with stereotactic ablative radiotherapy. [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Targeted Therapies in Combination with Radiotherapy; 2025 Jan 26-29; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(2_Suppl):Abstract nr B031.

Standard operating procedure combined with comprehensive quality control system for multiple LC-MS platforms urinary proteomics

Urinary proteomics is emerging as a potent tool for detecting sensitive and non-invasive biomarkers. At present, the comparability of urinary proteomics data across diverse liquid chromatography−mass spectrometry (LC-MS) platforms remains an area that requires investigation. In this study, we conduct a comprehensive evaluation of urinary proteome across multiple LC-MS platforms. To systematically analyze and assess the quality of large-scale urinary proteomics data, we develop a comprehensive quality control (QC) system named MSCohort, which extracted 81 metrics for individual experiment and the whole cohort quality evaluation. Additionally, we present a standard operating procedure (SOP) for high-throughput urinary proteome analysis based on MSCohort QC system. Our study involves 20 LC-MS platforms and reveals that, when combined with a comprehensive QC system and a unified SOP, the data generated by data-independent acquisition (DIA) workflow in urine QC samples exhibit high robustness, sensitivity, and reproducibility across multiple LC-MS platforms. Furthermore, we apply this SOP to hybrid benchmarking samples and clinical colorectal cancer (CRC) urinary proteome including 527 experiments. Across three different LC-MS platforms, the analyses report high quantitative reproducibility and consistent disease patterns. This work lays the groundwork for large-scale clinical urinary proteomics studies spanning multiple platforms, paving the way for precision medicine research.

Challenges and opportunities for statistical power and biomarker identification arising from rhythmic variation in proteomics

Time-of-day variation in the molecular profile of biofluids and tissues is a well-described phenomenon, but—especially for proteomics—is rarely considered in terms of the challenges this presents to reproducible biomarker identification. We provide a case study analysis of human circadian and ultradian rhythmicity in proteins, including in the complement and coagulation cascades and apolipoproteins, with PLG, CFAH, ZA2G and ITIH2 demonstrated as rhythmic for the first time. We also show that rhythmicity increases the risk of Type II errors due to the reduction in statistical power from increased variance, and that controlling for rhythmic time-of-day variation improves statistical power and reduces the chances of Type II errors. We recommend that best practice in proteomics study design should account for temporal variation and that time of sampling be reported as part of study metadata. These simple steps can mitigate against both false and missed discoveries, as well as improving reproducibility.

Distinct pro-inflammatory/pro-angiogenetic signatures distinguish children with Long COVID from controls.

Recent proteomic studies have documented that Long COVID in adults is characterized by a pro-inflammatory signature with thromboinflammation. However, if similar events happen also in children with Long COVID has never been investigated. We performed an extensive protein analysis of blood plasma from pediatric patients younger than 19 years of age Long COVID and a control group of children with acute COVID-19, MIS-C, and healthy controls resulted similar for sex distribution and age. Children were classified as Long COVID if symptoms persisted for at least 8 weeks since the initial infection, negatively impacted daily life and could not be explained otherwise. 112 children were included in the study, including 34 children fulfilling clinical criteria of Long COVID, 32 acute SARS-CoV-2 infection, 27 MIS-C and 19 healthy controls. Compared with controls, pediatric Long COVID was characterized by higher expression of the proinflammatory and pro-angiogenetic set of chemokines CXCL11, CXCL1, CXCL5, CXCL6, CXCL8, TNFSF11, OSM, STAMBP1a. A Machine Learning model based on proteomic profile was able to identify LC with an accuracy of 0.93, specificity of 0.86 and sensitivity of 0.97. Pediatric Long COVID patients have a well distinct blood protein signature marked by increased ongoing general and endothelial inflammation, similarly as happens in adults. Pediatric Long COVID has a distinct blood protein signature marked by increased ongoing general and endothelial inflammation. This is the first study studying and documenting proinflammatory profile in blood samples of children with long COVID. Long COVID was characterized by higher expression of the proinflammatory and pro-angiogenetic set of chemokines CXCL11, CXCL1, CXCL5, CXCL6, CXCL8, TNFSF11, OSM, STAMBP1a. A proteomic profile was able to identify Long COVID with an accuracy of 0.93, specificity of 0.86 and sensitivity of 0.97. These findings may inform development of future diagnostic tests.

Non-histone lactylation: unveiling its functional significance

Lactylation, a newly discovered protein posttranslational modification (PTM) in 2019, primarily occurs on lysine residues. Lactylation of histones was initially identified, and subsequent studies have increasingly demonstrated its widespread presence on non-histone proteins. Recently, high-throughput proteomics studies have identified a large number of lactylated proteins and sites, revealing their global regulatory role in disease development. Notably, this modification is catalyzed by lactyltransferase and reversed by delactylase, with numerous new enzymes, such as AARS1/2, reported to be involved. Specifically, these studies have revealed how lactylation exerts its influence through alterations in protein spatial conformation, molecular interactions, enzyme activity and subcellular localization. Indeed, lactylation is implicated in various physiological and pathological processes, including tumor development, cardiovascular and cerebrovascular diseases, immune cell activation and psychiatric disorders. This review provides the latest advancements in research on the regulatory roles of non-histone protein lactylation, highlighting its crucial scientific importance for future studies.

Impact of Local Air Pressure on Ion Mobilities and Data Consistency in diaPASEF-Based High Throughput Proteomics.

Data-independent acquisition (DIA) on ion mobility mass spectrometers enables deep proteome coverage and high data completeness in large-scale proteomics studies. For advanced acquisition schemes such as parallel accumulation serial fragmentation-based DIA (diaPASEF) stability of ion mobility (1/K0) over time is crucial for consistent data quality. We found that minor changes in environmental air pressure systematically affect the vacuum pressure in the TIMS analyzer, causing ion mobility shifts. By comparing experimental ion mobilities with historical weather data, we attributed observed drifts to fluctuations in the ground air pressure. Moderate air pressure changes of e.g. fifteen mbar induce ion mobility shifts of 0.025 Vs/cm2. These drifts negatively impact peptide quantification across consecutively acquired samples due to drift-dependent abundance changes and increased missing values for ions located at the boundaries of diaPASEF isolation windows, which cannot be corrected by postprocessing. To address this, we applied an in-batch mobility autocalibration feature on a run-wise basis, leading to full elimination of ion mobility drifts.

A split-GAL4 driver line resource for Drosophila neuron types.

Techniques that enable precise manipulations of subsets of neurons in the fly central nervous system (CNS) have greatly facilitated our understanding of the neural basis of behavior. Split-GAL4 driver lines allow specific targeting of cell types in Drosophila melanogaster and other species. We describe here a collection of 3060 lines targeting a range of cell types in the adult Drosophila CNS and 1373 lines characterized in third-instar larvae. These tools enable functional, transcriptomic, and proteomic studies based on precise anatomical targeting. NeuronBridge and other search tools relate light microscopy images of these split-GAL4 lines to connectomes reconstructed from electron microscopy images. The collections are the result of screening over 77,000 split hemidriver combinations. Previously published and new lines are included, all validated for driver expression and curated for optimal cell-type specificity across diverse cell types. In addition to images and fly stocks for these well-characterized lines, we make available 300,000 new 3D images of other split-GAL4 lines.

A split-GAL4 driver line resource for Drosophila neuron types

Techniques that enable precise manipulations of subsets of neurons in the fly central nervous system (CNS) have greatly facilitated our understanding of the neural basis of behavior. Split-GAL4 driver lines allow specific targeting of cell types in Drosophila melanogaster and other species. We describe here a collection of 3060 lines targeting a range of cell types in the adult Drosophila CNS and 1373 lines characterized in third-instar larvae. These tools enable functional, transcriptomic, and proteomic studies based on precise anatomical targeting. NeuronBridge and other search tools relate light microscopy images of these split-GAL4 lines to connectomes reconstructed from electron microscopy images. The collections are the result of screening over 77,000 split hemidriver combinations. Previously published and new lines are included, all validated for driver expression and curated for optimal cell-type specificity across diverse cell types. In addition to images and fly stocks for these well-characterized lines, we make available 300,000 new 3D images of other split-GAL4 lines.

New potential susceptibility factors contributing to tomato bacterial spot disease.

The label-free shotgun proteomics analysis carried out in this study aimed to understand the molecular mechanisms that contribute towards tomato susceptibility to Xanthomonas euvesicatoria pv. perforans (Xep). To achieve this, comparative proteomics was performed on susceptible inoculated plants with the bacterium and the control group (saline solution) at 24 and 48 h after inoculation (hai). The results revealed that most of the identified proteins showed increased abundance in the infected group and were classified into different gene ontology groups. Eight of these proteins were related to susceptibility in other pathosystems, suggesting their potential involvement in the development of bacterial spot in tomato. Some of these proteins are involved in the negative regulation of salicylic acid, PR proteins and reactive oxygen species (ROS), as well as contributing to the acquisition of sugars by the pathogen. The results obtained in this study provided us with valuable information for understanding the molecular mechanisms that lead to tomato susceptibility to Xep and will help in developing tomato cultivars resistant to bacterial spot. SIGNIFICANCE: Our proteomic study of tomato plants during infection by Xep allowed for the identification of potential proteins that contribute to bacterial spot tomato disease development. These proteins can act in different ways to favor the pathogen, such as the negative modulation of phytohormones involved in plant defense, the inhibition of PR proteins and reactive oxygen species, as well as to collaborate in the acquisition of sugar for pathogen nutrition.