Proteomic Data Research Articles

7449 A Genome-wide CRISPR Screen Identifies Drivers of Impaired Glucose Uptake in Human Insulin Resistance

Abstract Disclosure: N. Haider: None. Y. Lee: None. P. Yi: None. C.R. Kahn: None. Insulin resistance is a major risk factor in the development of type 2 diabetes (T2D), and metabolic syndrome. Although 25% of people within the general non-diabetic population are insulin resistant, the primary underlying cause of insulin resistance remains elusive. In this study, we have used induced pluripotent stem cells (iPSC) derived from non-diabetic humans at both ends of the insulin sensitivity spectrum, i.e., the top 20% of insulin resistance vs. the top 20% of insulin sensitive, as well as individuals with T2D to model human insulin resistance. We find that iPSCs differentiated into myoblasts (iMyos) from T2D and non-diabetic individuals in the highest quintile of insulin resistance (I-Res) show impaired insulin signaling and defective insulin-stimulated glucose uptake, as compared to iMyos from the insulin sensitive individuals (I-Sen), indicating that these cells in vitro mirror the alterations seen in vivo in a cell autonomous manner. To uncover the primary upstream drivers that contribute to the impaired glucose uptake associated with insulin resistance, we conducted a genome-wide loss-of-function screen using a CRISPR-based approach to identify genes that positively or negatively regulated glucose uptake in I-Res and T2D iMyos. Knockdown of ∼525 genes show effect to rescue the impaired glucose uptake in both I-Res and T2D iMyos, i.e., were negative regulators of glucose uptake. We hypothesized that important negative regulators of glucose uptake might be over-expressed at the protein level in I-Res and T2D iMyos and crossing the iMyos proteomics data with the CRISPR screen revealed 8 top candidates that are increased at the protein level and whose knockdown rescued glucose uptake in I-Res and T2D iMyos. These included candidates associated with cytoskeleton changes, protein kinases, transmembrane transport, mitochondrial and nuclear proteins. In summary, iPSC derived myoblasts from patients with insulin resistance and T2D mirror defects in glucose uptake observed in vivo. Combining CRISPR screening and global proteomics, we have identified important upstream regulators of insulin resistance in humans. Presentation: 6/2/2024

Impact of a teat disinfectant based on Lactococcus cremoris on the cow milk proteome

BackgroundDairy cow milking practices require cleaning and disinfection of the teat skin before and after milking to ensure the safety and quality of milk and prevent intramammary infections. Antimicrobial proteins of natural origin can be valuable alternatives to traditional disinfectants. In a recent field trial, we demonstrated that a teat dip based on a nisin A-producing Lactococcus cremoris (L) had comparable efficacy to conventional iodophor dip (C) in preventing dairy cow mastitis. Here, we present the differential shotgun proteomics investigation of the milk collected during the trial.MethodsFour groups of quarter milk samples with low (LSCC) and high somatic cell count (HSCC) collected at the beginning (T0) and end (TF) of the trial were analyzed for a total of 28 LSCC (14 LSCC T0 and 14 LSCC TF) and 12 HSCC (6 HSCC T0 and 6 HSCC TF) samples. Milk proteins were digested into peptides, separated by nanoHPLC, and analyzed by tandem mass spectrometry (LC-MS/MS) on an Orbitrap Fusion Tribrid mass spectrometer. The proteins were identified with MaxQuant and interaction networks of the differential proteins were investigated with STRING. The proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD045030.ResultsIn healthy milk (LSCC), we detected 90 and 80 differential proteins at T0 and TF, respectively. At TF, the Lactococcus group showed higher levels of antimicrobial proteins. In mastitis milk (HSCC), we detected 88 and 106 differential proteins at T0 and TF, respectively. In the Lactococcus group, 14 proteins with antimicrobial and immune defense functions were enriched at TF vs. 4 proteins at T0. Cathelicidins were among the most relevant enriched proteins. Western immunoblotting validation confirmed the differential abundance.ConclusionsAt T0, the proteomic differences observed in healthy milk of the two groups were most likely dependent on physiological variation. On the other hand, antimicrobial and immune defense functions were higher in the milk of cows with mammary gland inflammation of the Lactococcus-treated group. Among other factors, the immunostimulatory action of nisin A might be considered as a contributor.

A quantitative proteomic approach to evaluate the efficacy of carnosine in a murine model of chronic obstructive pulmonary disease (COPD)

The aim of the work was to study a dose-dependent effect of inhaled carnosine (10, 50 or 100 mg/kg/day) in mice exposed to cigarette smoke as a model of chronic obstructive pulmonary disease (COPD). A dose-dependent loading of the dipeptide in lung tissue and bronchoalveolar lavage (BAL) was firstly demonstrated by LC-ESI-MS analysis. Cigarette smoke exposure induced a significant lung inflammation and oxidative stress in mice which was dose-dependently reduced by carnosine. Inflammation was firstly evaluated by measuring the cytokines content in the BAL. All the measured cytokines were found significantly higher in the smoke group in respect to control, although the data are affected by a significant variability. Carnosine was found effective only at the highest dose tested and significantly only for keratinocyte-derived cytokine (KC). Due to the high variability of cytokines, a quantitative proteomic approach to better understand the functional effect of carnosine and its molecular mechanisms was used. Proteomic data clearly indicate that smoke exposure had a great impact on lung tissue with 692 proteins differentially expressed above a threshold of 1.5-fold. Protein network analysis identified the activation of some pathways characteristic of COPD, including inflammatory response, fibrosis, induction of immune system by infiltration and migration of leukocyte pathways, altered pathway of calcium metabolism and oxidative stress. Carnosine at the tested dose of 100 mg/kg was found effective in reverting all the pathways evoked by smoke. Only a partial reverse of the dysregulated proteins was evident at low- and mid-tested doses, although, for some specific proteins, indicating an overall dose-dependent effect. Regarding the molecular mechanisms involved, we found that carnosine upregulated some key enzymes related to Nrf2 activation and in particular glutathione peroxidase, reductase, transferase, SOD, thioredoxins, and carbonyl reductase. Such mechanism would explain the antioxidant and anti-inflammatory effects of the dipeptide.

Biomarkers and pathways in autism spectrum disorder: An individual meta-analysis based on proteomic and metabolomic data.

The utilization of biomarkers for the diagnosis and management of autism spectrum disorders (ASD) remains a relatively unexplored frontier in clinical practice. Proteomics and metabolomics are important tools for revealing key biomarkers and evaluating biological pathways in ASD. We conducted an individual meta-analysis to compare the consistency of biomarkers of ASD from central nervous system (brain and cerebrospinal fluid), circulatory system (blood), and non-invasive samples (urine, saliva, and faeces) and performed pathway enrichment analyses to identify pathways enriched in ASD. After screening 926 proteomics and 619 metabolomics articles, we collected data from 10 studies involving 940 differential proteins and 16 studies assessing a total of 748 differential metabolites. In brain tissue, blood, and urine of ASD cases and controls, flotillin-2 (FLOT2), apolipoprotein E (ApoE), and EH domain-containing protein 3 (EHD3) exhibit differential expression, while vinculin (VCL) displays variations in saliva, blood, and urine. Similarly, in case-control studies, gelsolin (GSN) shows differential expression in brain tissue, saliva, and urine, and malate dehydrogenase 2 (MDH2) in brain tissue, blood, and saliva. Hippuric acid and salicyluric acid were simultaneously found in the brain, blood, urine, and faeces. In terms of pathways, glycolysis/gluconeogenesis, carbon metabolism, and glutathione metabolism were enriched in the brain as well as in saliva or urine. In our study, we identified six shared protein and two metabolic markers in central nervous system, circulatory system, and non-invasive samples, underscoring their potential value for ASD diagnosis and management, warranting further research.

An atlas of the aging mouse proteome reveals the features of age-related post-transcriptional dysregulation

To what extent and how post-transcriptional dysregulation affects aging proteome remains unclear. Here, we provide proteomic data of whole-tissue lysates (WTL) and low-solubility protein-enriched fractions (LSF) of major tissues collected from mice of 6, 15, 24, and 30 months of age. Low-solubility proteins are preferentially affected by age and the analysis of LSF doubles the number of proteins identified to be differentially expressed with age. Simultaneous analysis of proteome and transcriptome using the same tissue homogenates reveals the features of age-related post-transcriptional dysregulation. Post-transcriptional dysregulation becomes evident especially after 24 months of age and age-related post-transcriptional dysregulation leads to accumulation of core matrisome proteins and reduction of mitochondrial membrane proteins in multiple tissues. Based on our in-depth proteomic data and sample-matched transcriptome data of adult, middle-aged, old, and geriatric mice, we construct the Mouse aging proteomic atlas (https://aging-proteomics.info/), which provides a thorough and integrative view of age-related gene expression changes.

Alternate RNA decoding results in stable and abundant proteins in mammals.

Amino acid substitutions may substantially alter protein stability and function, but the contribution of substitutions arising from alternate translation (deviations from the genetic code) is unknown. To explore it, we analyzed deep proteomic and transcriptomic data from over 1,000 human samples, including 6 cancer types and 26 healthy human tissues. This global analysis identified 60,024 high confidence substitutions corresponding to 8,801 unique sites in proteins derived from 1,990 genes. Some substitutions are shared across samples, while others exhibit strong tissue-type and cancer specificity. Surprisingly, products of alternate translation are more abundant than their canonical counterparts for hundreds of proteins, suggesting sense codon recoding. Recoded proteins include transcription factors, proteases, signaling proteins, and proteins associated with neurodegeneration. Mechanisms contributing to substitution abundance include protein stability, codon frequency, codon-anticodon mismatches, and RNA modifications. We characterize sequence motifs around alternatively translated amino acids and how substitution ratios vary across protein domains, tissue types and cancers. The substitution ratios are positively associated with intrinsically disordered regions and genetic polymorphisms in gnomAD, though the polymorphisms cannot account for the substitutions. Both the sequence and the tissue-specificity of alternatively translated proteins are conserved between human and mouse. These results demonstrate the contribution of alternate translation to diversifying mammalian proteomes, and its association with protein stability, tissue-specific proteomes, and diseases.

B-251 Comprehensive Proteomics Analysis Reveals an Exosomal Biomarker Signature Useful for Detection of Non-Small Cell Lung Cancer

Abstract Background Lung cancer is the second most commonly diagnosed lung cancer in the world, and Non-Small Cell Lung Cancer is the most prevalent subtype. Tissue biopsy is the gold standard for detecting lung cancer, but is highly invasive as it necessitates the extraction of a sample of tissue for histologic analysis. It also carries risks of bleeding and/or infection, and is inconvenient from a patient perspective. The development of a minimally invasive test, such as one utilizing a blood or urine sample, capable of providing accurate results for lung cancer detection and/or subtyping, would significantly enhance the clinical landscape and streamline patient care. Methods In this study we utilize A549 and H1299 human lung cancer cell lines, differing in cell type, location within the lung, and genetic composition (Kras & p53 status), along with two additional cancer cell lines (HeLa/cervical cancer and SCBO/bladder cancer), as controls. Cell lysate and exosome proteomics data were obtained using data independent acquisition- liquid chromatography mass spectrometry (DIA-LCMS) and analyzed using ProteoDisco 2.0, a custom-designed software application in R. Raw mass spectra data was subject to quantile normalization to mitigate external, non-biological differences between the samples. Differential protein expression was performed and Student's t-test was used to identify significantly different proteins across the sample types. A correlation coefficient matrix and Principal Component Analysis were used to assess global differences, and hierarchical clustering and heat maps allowed for visualizing of specific groups of proteins that separated all sample types. Results Over 1000 proteins were identified in each of the exosome samples, and >7500 proteins were detected in the lysates. Correlation coefficient matrix and PCA demonstrate that exosomal protein profiles, relative to cell lysates, are better at differentiating between the two lung cancer cell lines and controls. Surprisingly, exosomal proteomic patterns are different for the two lung cancers, implicating activation of different signaling pathways. Specifically, hierarchical clustering identified protein clusters showing enrichment for multiple biological processes: H1299 cells manifest enrichment of apical junction proteins and in epithelial-mesenchymal transition (EMT) ontology, while A549 cell lines show enrichment in proteins involved in oxidative phosphorylation. This combination of functional pathways can be used as a biomarker signature to distinguish between these two lung cancer subtypes, and from controls. Conclusions A short list of exosomal proteins, comprising apical junction, EMT, and oxidative phosphorylation constituents can detect lung cancer and further distinguish between subtypes represented by A549 and H1299 lung cancer cells. This biomarker signature has potential for detecting and subtyping lung cancer, to allow for early detection of disease, development of personalized treatment strategies, and result in improved clinical outcomes for this deadly disease.

Retinal Proteome Profiling of Inherited Retinal Degeneration Across Three Different Mouse Models Suggests Common Drug Targets in Retinitis Pigmentosa

Inherited retinal degenerations (IRDs) are a leading cause of blindness among the population of young people in the developed world. Approximately half of IRDs initially manifest as gradual loss of night vision and visual fields, characteristic of retinitis pigmentosa (RP). Due to challenges in genetic testing, and the large heterogeneity of mutations underlying RP, targeted gene therapies are an impractical largescale solution in the foreseeable future. For this reason, identifying key pathophysiological pathways in IRDs that could be targets for mutation-agnostic and disease-modifying therapies (DMTs) is warranted. In this study, we investigated the retinal proteome of three distinct IRD mouse models, in comparison to sex- and age-matched wild-type mice. Specifically, we used the Pde6βRd10 (rd10) and RhoP23H/WT (P23H) mouse models of autosomal recessive and autosomal dominant RP, respectively, as well as the Rpe65-/- mouse model of Leber´s congenital amaurosis type 2 (LCA2). The mice were housed at two distinct institutions and analyzed using LC-MS in three separate facilities/instruments following data-dependent and data-independent acquisition modes. This cross-institutional and multi-methodological approach signifies the reliability and reproducibility of the results. The largescale profiling of the retinal proteome, coupled with in vivo electroretinography recordings, provided us with a reliable basis for comparing the disease phenotypes and severity. Despite evident inflammation, cellular stress, and downscaled phototransduction observed consistently across all three models, the underlying pathologies of RP and LCA2 displayed many differences, sharing only four general KEGG pathways. The opposite is true for the two RP models in which we identify remarkable convergence in proteomic phenotype even though the mechanism of primary rod death in rd10 and P23H mice is different. Our data highlights the cAMP and cGMP second-messenger signaling pathways as potential targets for therapeutic intervention. The proteomic data is curated and made publicly available, facilitating the discovery of universal therapeutic targets for RP.

Interplay between Lipids and Complement Proteins—How Multiomics Data Integration Can Help Unravel Age-related Macular Degeneration Pathophysiology: A Proof-of-concept Study

RationaleWe hypothesized that the integration of multi-omics data sets can help unravel some complex aspects of AMD pathophysiology. Our objectives were to identify correlation patterns between genetic variants, complement proteins and lipids using a multi-omics data integration approach and to determine how these interconnections affect AMD. Materials and methodsThe analyses were performed in a subset of the Singapore Indian Eye Study (SINDI) study. We randomly selected 155 AMD cases and age- and sex-matched them with 155 controls. We measured in serum samples 35 complement proteins and 66 lipids, and used nine genetic variants. Firstly, a multi-omics data integration method was used to identify correlation patterns between the omics data. Then, we tested possible interactions between the lipids and complement proteins using logistic regression models. ResultsAmong the 155 AMD cases, 93 (60.0%) had early and 62 (40.0%) intermediate AMD. Firstly, we identified two clusters between complement proteins and lipids involving (1) MASP1 and several different HDL particles, and (2) FHR1, CPN2 and CO8G, and sphingomyelin and different cholesterol. Secondly, we identified one interaction between C1R and sphingomyelin with an odds of AMD 2 times higher for individuals with low levels of sphingomyelin and C1R (OR=2.13 [1.09, 4.17]). ConclusionWe report here, using a cutting-edge multi-omics integration approach, the complex interconnections between genetic, metabolomics and proteomic data. This method permitted us to obtain a holistic picture and identify multi-omics signature of AMD pathophysiology. These results advocate for a personalized therapeutic approach that accounts for multiple pathways. However, these results need to be validated in larger studies with different ethnic groups.

Proteome-wide association study using cis and trans variants and applied to blood cell and lipid-related traits in the Women's Health Initiative study.

In most Proteome-Wide Association Studies (PWAS), variants near the protein-coding gene (±1 Mb), also known as cis single nucleotide polymorphisms(SNPs), are used to predict protein levels, which are then tested for association with phenotypes. However, proteins can be regulated through variants outside of the cis region. An intermediate GWAS step to identify protein quantitative trait loci (pQTL) allows for the inclusion of trans SNPs outside the cis region in protein-level prediction models. Here, we assess the prediction of 540 proteins in 1002 individuals from the Women's Health Initiative (WHI), split equally into a GWAS set, an elastic net training set, and a testing set. We compared the testing r2 between measured and predicted protein levels using this proposed approach, to the testing r2 using only cis SNPs. The two methods usually resulted in similar testing r2, but some proteins showed a significant increase in testing r2 with our method. For example, for cartilage acidic protein 1, the testing r2 increased from 0.101 to 0.351. We also demonstrate reproducible findings for predicted protein association with lipid and blood cell traits in WHI participants without proteomics data and in UK Biobank utilizing our PWAS weights.

Thioredoxin-1 protein interactions in neuronal survival and neurodegeneration

Neuronal cell death remains the main aspect of neurodegenerative diseases and the main challenge for treatment strategies. Thioredoxin1 (Trx1) is a major cytoplasmic thiol oxidoreductase protein involved in redox signaling, hence a crucial player in maintaining neuronal health. Trx1 levels are notably reduced in neurodegenerative diseases including Alzheimer's and Parkinson's diseases, however, the impact of this decrease on neuronal physiology remains largely unexplored. This is mainly due to the nature of Trx1 redox regulatory role which is afforded by a rapid electron transfer to its oxidized protein substrates. During this reaction, Trx1 forms a transient bond with the oxidized disulfide bond in the substrate. This is a highly fast reaction which makes the identification of Trx1 substrates a technically challenging task. In this project, we utilized a transgenic mouse model expressing a Flag-tagged mutant form of Trx1 that can form stable disulfide bonds with its substrates, hence allowing identification of the Trx1 target proteins. Autophagy is a vital housekeeping process in neurons that is critical for degradation of damaged proteins under oxidative stress conditions and is interrupted in neurodegenerative diseases. Given Trx1's suggested involvement in autophagy, we aimed to identify potential Trx1 substrates following pharmacologic induction of autophagy in primary cortical neurons. Treatment with rapamycin, an autophagy inducer, significantly reduced neurite outgrowth and caused cytoskeletal alterations. Using immunoprecipitation and mass spectrometry, we have identified 77 Trx1 target proteins associated with a wide range of cellular functions including cytoskeletal organization and neurodegenerative diseases. Focusing on neuronal cytoskeleton organization, we identified a novel interaction between Trx1 and RhoB which was confirmed in genetic models of Trx1 downregulation in primary neuronal cultures and HT22 mouse immortalized hippocampal neurons. The applicability of these findings was also tested against the publicly available proteomic data from Alzheimer's patients. Our study uncovers a novel role for Trx1 in regulating neuronal cytoskeleton organization and provides a mechanistic explanation for its multifaceted role in the physiology and pathology of the nervous system, offering new insights into the molecular mechanisms underlying neurodegeneration.

Identification and comparison of protein composition of biofilms in response to EGCG from Enterococcus faecalis and Staphylococcus lugdunensis, which showed opposite patterns in biofilm-forming abilities.

Bacterial biofilm is resistant to conventional antibiotic treatments, leading to complications associated with many infection-related human diseases. Epigallocatechin Gallate (EGCG), a phenolic catechin enriched in green tea, is recognized for its anti-bacterial and anti-biofilm activities. In this study, we examined the protein components of the biofilms formed in the absence or presence of EGCG using Enterococcus faecalis and Staphylococcus lugdunensis, which had shown opposing patterns in biofilm formation. A clustering heatmap revealed that the two microorganisms expressed the different protein sets in response to EGCG. Proteins that were noticeably upregulated included those associated with stress responsiveness and gluconeogenesis in E. faecalis, and gene modification in S. lugdunensis. Conversely, downregulated proteins were related to tRNA-modifying enzyme activity in E. faecalis, and anabolic metabolism in S. lugdunensis. Among the proteins identified only in EGCG-responsive biofilms, enzymes involved in de novo purine biosynthesis were enriched in E. faecalis, while proteins likely to cause DNA instability and pathogenicity changes were abundantly present in S. lugdunensis. The classification based on gene ontology (GO) terms by microorganism exhibited that metabolic process or catabolic activity was at the top rank in E. faecalis with more than 33 proteins, and in S. lugdunensis, localization or transport was highly ranked with 4 proteins. These results support the hypothesis that EGCG might cause different cellular programs in each microorganism. Finally, comparison of the proteomes between two groups that form biofilms to similar extents discovered that 2 proteins were commonly found in the weak biofilm-forming groups (E. faecalis and EGCG-responding S. lugudunensis), whereas 9 proteins were common among the strong biofilm-forming groups (S. lugdunensis and EGCG-responding E. faecalis). It was suggested that these proteins could serve as potential indicators to detect the presence and predict the extent of biofilm formation by multiple microorganisms. Taken all together, proteomics data and analyses performed in this study provided useful and new information on the proteins embedded in the biofilms formed at the specific conditions, which can aid in diagnosis and the development of tailored treatment strategies.

Protein Modifications During Early Embryo Development.

Infertility is a global reproductive health burden. Assisted reproductive technologies (ARTs) have been widely used to help patients become pregnant. Few embryos develop to the blastocyst stage with ARTs, leading to relatively low live birth rates. Protein modifications play crucial roles in nearly every aspect of cell biology, including reproductive processes. The aim of this study was to explore the characteristics of protein modifications during embryonic development. Proteomic data from humans and mice were acquired from the integrated proteome resources (iProX) of ProteomeXchange (PXD024267) and a tandem mass tag (TMT)-mass spectrometry dataset. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were applied for functional annotation. Protein-protein interactions (PPIs) of the modification-related genes were revealed by the STRING database. Modified proteins during mouse embryogenesis were visualized through heatmaps of hierarchically clustering using k-means. We identified modification-related proteins in human embryo development and characterized them through heatmaps, GO analysis, KEGG analysis, and PPI network analysis. We found that the 4-cell stage to the 8-cell stage might be the demarcation period for modification-related protein expression patterns during embryo development. Using quantitative mass spectrometry, we elucidated the methylation, acetylation, and ubiquitination events that occur during mouse embryogenesis to validate our findings in human embryonic development to some extent. The results of our study suggest that the posttranslational modifications (PTMs) of human preimplantation embryos might exhibit the same trends as those in mice to exert synergistic and fine-tuned regulatory effects during embryonic development.

The modulation of proteomics and antioxidant stress is involved in the effect of nitazoxanide against Japanese encephalitis virus in vitro

Japanese encephalitis virus (JEV) is a significant circulating arbovirus flavivirus and the primary cause of viral encephalitis in Asia. Previous studies have demonstrated that nitazoxanide (NTZ), an antiparasitic gastroenteritis medication classified as a thiazolide, exhibits efficacy against JEV both in vitro and in vivo. To explore the potential antiviral mechanisms, we employed Tandem Mass Tag (TMT)-based quantitative proteomics to identify differentially expressed proteins (DEPs) among three groups: Blank cell group, JEV-infected cell group, and JEV-infected cells treated with NTZ. Our analysis revealed that NTZ treatment led to the upregulation of 30 DEPs and downregulation of 54 DEPs in JEV-infected cells. Enrichment analysis using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) indicated that these DEPs are involved in various biological processes and signaling pathways, including transport, localization, response to wounding, P53 pathway activation, and fatty acid metabolism-related pathways. Moreover, we observed that the expression trend of TMX2, a protein associated with redox homeostasis, was consistent with findings from TMT-based quantitative proteomics. Further investigations into reactive oxygen species (ROS), mitochondrial membrane potential, antioxidant enzyme activity, and the KEAP1-NRF2 pathway demonstrated that NTZ effectively regulates the KEAP1-NRF2 pathway while suppressing oxidative stress induced by JEV infection. In conclusion, the proteomic data along with antioxidant stress results presented herein provide a foundational basis for further research into the molecular mechanisms and potential targets of NTZ against JEV.

ISubGen generates integrative disease subtypes by pairwise similarity assessment.

There are myriad types of biomedical data-molecular, clinical images, and others. When a group of patients with the same underlying disease exhibits similarities across multiple types of data, this is called a subtype. Existing subtyping approaches struggle to handle diverse data types with missing information. To improve subtype discovery, we exploited changes in the correlation-structure between different data types to create iSubGen, an algorithm for integrative subtype generation. iSubGen can accommodate any feature that can be compared with a similarity metric to create subtypes versatilely. It can combine arbitrary data types for subtype discovery, such as merging genetic, transcriptomic, proteomic, and pathway data. iSubGen recapitulates known subtypes across multiple cancers even with substantial missing data and identifies subtypes with distinct clinical behaviors. It performs equally with or superior to other subtyping methods, offering greater stability and robustness to missing data and flexibility to new data types. It is available at https://cran.r-project.org/web/packages/iSubGen.

Multilevel Proteomics Reveals Epigenetic Signatures in BCG-Mediated Macrophage Activation

The bacillus Calmette-Guérin BCG vaccine (Mycobacterium bovis) is primarily used to prevent tuberculosis (TB) infections but has wide-ranging immunogenic effects. One of its most notable properties is its ability to induce trained immunity, a memory-like response in innate immune cells such as macrophages. Through targeted analyses of well-established histone marks, prior research has shown that these changes are generated through epigenetic modification. Mass spectrometry-based proteomic approaches provide a way to globally profile various aspects of the proteome, providing data to further identify unexplored mechanisms of BCG-mediated immunomodulation. Here we use multi-level proteomics (total, histone, and phospho to identify networks and potential mechanisms that mediate BCG induced immunomodulation in macrophages. Histone-focused proteomics and total proteomics were performed at the University of Cape Town (data available via ProteomeXchange with identifier PXD051187), while phosphoproteomics data was retrieved from the ProteomeXchange Repository (identifier PXD013171). We identify several epigenetic mechanisms that may drive BCG-induced training phenotypes. Evidence across the proteomics and histone-focused proteomics data sets pair 6 epigenetic effectors (NuA4, NuRD, NSL, Sin3A, SIRT2, SIRT6) and their substrates.

Highly-Multiplexed Immunofluorescence PhenoCycler Panel for Murine FFPE Yields Insight into Tumor Microenvironment Immunoengineering

Spatial proteomics profiling is an emerging set of technologies that has the potential to elucidate the cell types, interactions, and molecular signatures that make up complex tissue microenvironments, with applications in the study of cancer, immunity, and much more. An emerging technique in the field is Co-Detection-by-indEXing (CODEX), recently renamed as the PhenoCycler system. This is a highly-multiplexed immunofluorescence imaging technology that relies on oligonucleotide-barcoded antibodies and cyclic immunofluorescence to visualize many antibody markers in a single specimen while preserving tissue architecture. Existing PhenoCycler panels are primarily designed for fresh-frozen tissues. Formalin-fixed paraffin-embedded (FFPE) blocks offer several advantages in preclinical research, but few antibody clones have been identified in this setting for PhenoCycler imaging. Here, we present a novel PhenoCycler panel of 28 validated antibodies for murine FFPE tissues. We describe our workflow for selecting and validating clones, barcoding antibodies, designing our panel, and performing multiplex imaging. We further detail our analysis pipeline for comparing marker expressions, clustering and phenotyping single-cell proteomics data, and quantifying spatial relationships. We then apply our panel and analysis protocol to profile the effects of three gene-delivery nanoparticle formulations, in combination with systemic anti-PD1, on the murine melanoma tumor immune microenvironment. Intralesional delivery of genes expressing the costimulatory molecule 4-1BBL and the cytokine IL-12 led to a shift towards intratumoral M1 macrophage polarization and promoted closer associations between intratumoral CD8 T cells and macrophages. Delivery of IFNγ, in addition to 4-1BBL and IL-12, further increased markers of antigen presentation on tumor cells and intratumoral antigen-presenting cells but also promoted greater expression of checkpoint marker PD-L1 and closer associations between intratumoral CD8 T cells and PD-L1-expressing tumor cells. These findings help to explain the benefits of 4-1BBL and IL-12 delivery while offering additional mechanistic insights into the limitations of IFNγ therapeutic efficacy.

Proteo-transcriptomic profiles reveal genetic mechanisms underlying primary hair follicle development in coarse sheep fetal skin

Long hair trait represents a valuable genetic asset in Qinghai Tibetan sheep, with its quality and yield being contingent upon the characteristics of hair follicles (HFs). This study aims to elucidate the genetic mechanism underlying primary hair follicles (PFs) formation through an integrated analysis of proteomics and transcriptomics. Samples were collected at key stages of fetal HF formation (E65 and E85) for histological observation, revealing significant alterations in the microstructure of PF (E65) during the developmental process. In this study, a comprehensive analysis revealed a total of 217 overlapping genes that exhibited concordant expression patterns at both the proteomic and transcriptomic levels. Furthermore, to ensure the reliability of our findings, we employed parallel response monitoring (PRM) to validate the obtained proteomic data. The protein-protein interaction (PPI) network diagram highlights five hub core proteins (TTN, IGTA2, F2, EGFR, and MYH14). These differentially expressed proteins (DEPs) play crucial roles in metabolic processes, cell adhesion, and diverse biological processes. The potential synergy between transcriptional regulation and post-translational modifications plays a pivotal role in governing the initiation PF development. The findings presented in this study offer innovative insights into the molecular mechanisms underlying HFs generation and establish a robust foundation for targeted breeding strategies aimed at augmenting wool traits in sheep. SignificanceThe composition of coarse hair primarily consists of long, myelinated fibers originating from primary hair follicles. Sheep fetal skin initiates the formation of primary hair follicles around E65, followed by the development of secondary hair follicles around E85. Conducting differential proteomic and transcriptomic analyses during these developmental stages enhances our understanding of the molecular mechanisms underlying primary hair follicle development and offers valuable insights for sustainable utilization of high-quality germplasm resources.

In-depth proteomics and Phosphoproteomics reveal biomarkers and molecular pathways of chronic intermittent hypoxia in mice

Obstructive sleep apnea (OSA) syndrome is characterized by Chronic Intermittent Hypoxia (CIH). In this study, we employed Data-independent acquisition (DIA) Mass Spectrometry to conduct comprehensive proteomic and phosphoproteomic profiling of a murine model subjected to Chronic Intermittent Hypoxia (CIH), a model we had previously established. Utilizing three CIH and three normal control genioglossus samples, we gathered valuable insights into the molecular alterations associated with CIH. Our analyses identified a total of 4576 protein groups and 13,867 phosphosites. Differential analysis of the proteomic data highlighted a significant upregulation of Ras signaling (Egf, Ngf, and Fyb1) and calcium signaling (Tnn, Thbs4, and Ppp2r2d) in CIH samples, contrasting with a notable decrease in oxidative phosphorylation (Atp5mf, Atp5me, and Atp5mg). Additionally, we observed a substantial increase in the phosphorylation of PI3K-AKT signaling (Ptk2_Y861, Mapk3_T203, and Eif4b_S230) and HIF-1 signaling (Gapdh_S208, Eno3_T229, and Camk2b_T382) in CIH samples. These findings prompted a deeper investigation into the association of the characterized proteins and phosphoproteins with Obstructive Sleep Apnea (OSA). The comprehensive profiling revealed molecular signatures that may serve as valuable insights into the pathophysiology of chronic intermittent hypoxia and its link to obstructive sleep apnea. Our observations provide a foundation for future research endeavors, offering potential avenues for advancing our understanding and treatment strategies for these conditions. SignificanceThe significance of this study lies in its comprehensive exploration of the molecular mechanisms underpinning Chronic Intermittent Hypoxia (CIH), a key feature of Obstructive Sleep Apnea (OSA). By employing Data-independent acquisition (DIA) Mass Spectrometry, this research provides an in-depth proteomic and phosphoproteomic analysis, uncovering critical signaling pathways and molecular alterations associated with CIH. The identification of significant changes in Ras and calcium signaling pathways, along with increased phosphorylation in PI3K-AKT and HIF-1 signaling, offers novel insights into the pathophysiological processes involved in CIH and OSA. These findings not only enhance our understanding of the molecular basis of OSA but also pave the way for the development of targeted therapeutic strategies, ultimately contributing to better management and treatment of OSA and related conditions.

OMIBONE: Omics-driven computer model of bone regeneration for personalized treatment

Treatment of bone fractures are standardized according to the AO classification, which mainly refers to the mechanical stabilization required in a given situation but neglect individual differences due to patient's healing potential or accompanying diseases. Specially in elderly or immune-compromised patients, the complexity of individual constrains on a biological as well as mechanical level are hard to account for. Here, we introduce a novel framework that allows to predict bone regeneration outcome using combined proteomic and mechanical analyses in a computer model. The framework uses Ingenuity Pathway Analysis (IPA) software to link protein changes to alterations in biological processes and integrates these in an Agent-Based Model (ABM) of bone regeneration. This combined framework allows to predict bone formation and the potential of an individual to heal a given fracture setting. The performance of the framework was evaluated by replicating the experimental setup of a mouse femur fracture stabilized with an intramedullary pin. The model was informed by serum derived proteomics data. The tissue formation patterns were compared against experimental data based on x-ray and histology images. The results indicate the framework potential in predicting an individual's bone formation potential and hold promise as a concept to enable personalized bone healing predictions for a chosen fracture fixation.