A Quantitative Proteome Map of the Human Body

A proteome-wide association study identifies putative causal proteins for breast cancer risk

BACKGROUND

Genome-wide association studies (GWAS) have identified more than 200 breast cancer risk-associated genetic loci, yet the causal genes and biological mechanisms for most loci remain elusive. Proteins, as final gene products, are pivotal in cellular function. In this study, we conducted a proteome-wide association study (PWAS) to identify proteins in breast tissue related to breast cancer risk.

METHODS

We profiled the proteome in fresh frozen breast tissue samples from 120 cancer-free European-ancestry women from the Susan G. Komen Tissue Bank (KTB). Protein expression levels were log2-transformed then normalized via quantile and inverse-rank transformations. GWAS data were also generated for these 120 samples. These data were used to build statistical models to predict protein expression levels via cis-genetic variants using the elastic net method. The prediction models were then applied to the GWAS summary statistics data of 133,384 breast cancer cases and 113,789 controls to assess the associations of genetically predicted protein expression levels with breast cancer risk overall and its subtypes using the S-PrediXcan method.

RESULTS

A total of 6388 proteins were detected in the normal breast tissue samples from 120 women with a high detection false discovery rate (FDR) p value < 0.01. Among the 5820 proteins detected in more than 80% of participants, prediction models were successfully built for 2060 proteins with R > 0.1 and P < 0.05. Among these 2060 proteins, five proteins were significantly associated with overall breast cancer risk at an FDR p value < 0.1. Among these five proteins, the corresponding genes for proteins COPG1, DCTN3, and DDX6 were located at least 1 Megabase away from the GWAS-identified breast cancer risk variants. COPG1 was associated with an increased risk of breast cancer with a p value of 8.54 × 10-4. Both DCTN3 and DDX6 were associated with a decreased risk of breast cancer with p values of 1.01 × 10-3 and 3.25 × 10-4, respectively. The corresponding genes for the remaining two proteins, LSP1 and DNAJA3, were located in previously GWAS-identified breast cancer risk loci. After adjusting for GWAS-identified risk variants, the association for DNAJA3 was still significant (p value of 9.15 × 10-5 and adjusted p value of 1.94 × 10-4). However, the significance for LSP1 became weaker with a p value of 0.62. Stratification analyses by breast cancer subtypes identified three proteins, SMARCC1, LSP1, and NCKAP1L, associated with luminal A, luminal B, and ER-positive breast cancer. NCKAP1L was located at least 1Mb away from the GWAS-identified breast cancer risk variants. After adjusting for GWAS-identified breast cancer risk variants, the association for protein LSP1 was still significant (adjusted p value of 6.43 × 10-3 for luminal B subtype).

CONCLUSION

We conducted the first breast-tissue-based PWAS and identified seven proteins associated with breast cancer, including five proteins not previously implicated. These findings help improve our understanding of the underlying genetic mechanism of breast cancer development.

A proteogenomic surfaceome study identifies DLK1 as an immunotherapeutic target in neuroblastoma

Cancer immunotherapies produce remarkable results in B cell malignancies; however, optimal cell surface targets for many solid cancers remain elusive. Here, we present an integrative proteomic, transcriptomic, and epigenomic analysis of tumor and normal tissues to identify biologically relevant cell surface immunotherapeutic targets for neuroblastoma, an often-fatal childhood cancer. Proteogenomic analyses reveal sixty high-confidence candidate immunotherapeutic targets, and we prioritize delta-like canonical notch ligand 1 (DLK1) for further study. High expression of DLK1 directly correlates with a super-enhancer. Immunofluorescence, flow cytometry, and immunohistochemistry show robust cell surface expression of DLK1. Short hairpin RNA mediated silencing of DLK1 in neuroblastoma cells results in increased cellular differentiation. ADCT-701, a DLK1-targeting antibody-drug conjugate (ADC), shows potent and specific cytotoxicity in DLK1-expressing neuroblastoma xenograft models. Since high DLK1 expression is found in several adult and pediatric cancers, our study demonstrates the utility of a proteogenomic approach and credentials DLK1 as an immunotherapeutic target.

Durable Muscle Extracellular Matrix Engineered with Adhesive Phenolic Moieties for Effective Skeletal Muscle Regeneration in Muscle Atrophy

Muscle atrophy detrimentally impacts health and exacerbates physical disability, leading to increased mortality. In particular, sarcopenia, aging-related degenerative muscle loss, necessitates urgent remedies. Current approaches for treating muscle atrophy include exercise and nutrition, while drug exploration remains in its early stages. Cell therapy, focusing on satellite cells, faces significant challenge due to poor engraftment, safety issue, and high cost. Cell-free approach using extracellular matrix (ECM) shows a regenerative potential, but a lack of mechanical and adhesive properties hinders prolonged efficacy of ECM therapy. Here, durable muscle ECM (MEM) hydrogels for muscle atrophy by fortifying MEM with adhesive phenolic moieties including catechol and pyrogallol are demonstrated. The resultant phenolic MEM hydrogels exhibit enhanced mechanical and adhesive properties and provide sustained muscle-like microenvironments to address muscle atrophy. No local and systemic toxicities are observed after phenolic MEM injection into tibialis anterior muscle. Notably, these engineered MEM hydrogels, devoid of cells or drugs, induce tissue rejuvenation by promoting muscle protein synthesis and facilitating functional muscle recovery in mouse models of disuse- and age-induced atrophy. This study introduces cell-free, ECM-based therapeutics with translational potential for muscle atrophy by reversing muscle loss and restoring function.

ExoSloNano: Multi-Modal Nanogold Tags for identification of Macromolecules in Live Cells & Cryo-Electron Tomograms

In situ cryo-Electron Microscopy (cryo-EM) enables the direct interrogation of structure-function relationships by resolving macromolecular structures in their native cellular environment. Tremendous progress in sample preparation, imaging and data processing over the past decade has contributed to the identification and determination of large biomolecular complexes. However, the majority of proteins are of a size that still eludes identification in cellular cryo-EM data, and most proteins exist in low copy numbers. Therefore, novel tools are needed for cryo-EM to identify the vast majority of macromolecules across multiple size scales (from microns to nanometers). Here, we introduce and validate novel nanogold probes that enable the detection of specific proteins using cryo-ET (cryo-Electron Tomography) and resin-embedded correlated light and electron microscopy (CLEM). We demonstrate that these nanogold probes can be introduced into live cells, in a manner that preserves intact molecular networks and cell viability. We use this system to identify both cytoplasmic and nuclear proteins by room temperature EM, and resolve associated structures by cryo-ET. We further employ gold particles of different sizes to enable future multiplexed labeling and structural analysis. By providing high efficiency protein labeling in live cells and molecular specificity within cryo-ET tomograms, we establish a broadly enabling tool that significantly expands the proteome available to electron microscopy.

Inferring post-transcriptional regulation within and across cell types in human testis

Single-cell tissue atlases commonly use RNA abundances as surrogates for protein abundances. Yet, protein abundance also depends on the regulation of protein synthesis and degradation rates. To estimate the contributions of such post transcriptional regulation, we quantified the proteomes of 5,883 single cells from human testis using 3 distinct mass spectrometry methods (SCoPE2, pSCoPE, and plexDIA). To distinguish between biological and technical factors contributing to differences between protein and RNA levels, we developed BayesPG, a Bayesian model of transcript and protein abundance that systematically accounts for technical variation and infers biological differences. We use BayesPG to jointly model RNA and protein data collected from 29,709 single cells across different methods and datasets. BayesPG estimated consensus mRNA and protein levels for 3,861 gene products and quantified the relative protein-to-mRNA ratio (rPTR) for each gene across six distinct cell types in samples from human testis. About 28% of the gene products exhibited significant differences at protein and RNA levels and contributed to about 1, 500 significant GO groups. We observe that specialized and context specific functions, such as those related to spermatogenesis are regulated after transcription. Among hundreds of detected post translationally modified peptides, many show significant abundance differences across cell types. Furthermore, some phosphorylated peptides covary with kinases in a cell-type dependent manner, suggesting cell-type specific regulation. Our results demonstrate the potential of inferring protein regulation in from single-cell proteogenomic data and provide a generalizable model, BayesPG, for performing such analyses.

OrgXenomics: an integrated proteomic knowledge base for patient-derived organoid and xenograft

Patient-derived models (PDMs, particularly organoids and xenografts) are irreplaceable tools for precision medicine, from target development to lead identification, then to preclinical evaluation, and finally to clinical decision-making. So far, PDM-based proteomics has emerged to be one of the cutting-edge directions and massive data have been accumulated. However, such PDM-based proteomic data have not been provided by any of the available databases, and proteomics profiles of all proteins in proteomic study are also completely absent from existing databases. Herein, an integrated database named 'OrgXenomics' was thus developed to provide the proteomic data for PDMs, which was unique in (a) explicitly describing the establishment detail for a wide array of models, (b) systematically providing the proteomic profiles (expression/function/interaction) for all proteins in studied proteomic analysis and (c) comprehensively giving the raw data for diverse organoid/xenograft-based proteomic studies of various diseases. Our OrgXenomics was expected to server as one good complement to existing proteomic databases, and had great implication for the practice of precision medicine, which could be accessed at: https://idrblab.org/orgxenomics/.

Spermatogenic Stem Cells: Core Biology, Defining Features, and Utilities

The actions of spermatogenic stem cells (SSCs) provide the foundation for continual spermatogenesis and regeneration of the cognate lineage following cytotoxic insult or transplantation. Several decades of research with rodent models have yielded knowledge about the core biology, morphological features, and molecular profiles of mammalian SSCs. Translation of these discoveries to utilities for human fertility preservation, improving animal agriculture, and wildlife conservation are actively being pursued. Here, we provide overviews of these aspects covering both historical and current states of understanding.

Clinicopathologic Characteristics of Trop Family Proteins (Trop-2 and EpCAM) in Gastric Carcinoma

PURPOSE

Trop family proteins, including epithelial cell adhesion molecule (EpCAM) and Trop-2, have garnered attention as potential therapeutic and diagnostic targets for various malignancies. This study aimed to elucidate the clinicopathological significance of these proteins in gastric carcinoma (GC) and to reinforce their potential as biomarkers for patient stratification in targeted therapies.

MATERIALS AND METHODS

Immunohistochemical (IHC) analyses of EpCAM and Trop-2 were performed on GC and precancerous lesions, following rigorous orthogonal validation of the antibodies to ensure specificity and sensitivity.

RESULTS

Strong membranous staining (3+) for Trop-2 was observed in 49.3% of the GC cases, whereas EpCAM was strongly expressed in almost all cases (93.2%), indicating its widespread expression in GC. A high Trop-2 expression level, characterized by an elevated H-score, was significantly associated with intestinal type by Lauren classification, gastric mucin type, presence of lymph node metastasis, human epidermal growth factor receptor 2-positivity, and Epstein-Barr virus (EBV)-positivity. Patients with a high Trop-2 expression level exhibited poorer survival outcomes on univariate and multivariate analyses. High EpCAM expression levels were prevalent in differentiated histologic type, microsatellite instability-high, and EBV-negative cancer, and were correlated with high densities of CD3 and CD8 T cells and elevated combined positive score for programmed death-ligand 1.

CONCLUSIONS

These results highlight the differential expression of Trop-2 and EpCAM and their prognostic implications in GC. The use of meticulously validated antibodies ensured the reliability of our IHC data, thereby offering a robust foundation for future therapeutic strategies targeting Trop family members in GC.

Statistically and functionally fine-mapped blood eQTLs and pQTLs from 1,405 humans reveal distinct regulation patterns and disease relevance

Studying the genetic regulation of protein expression (through protein quantitative trait loci (pQTLs)) offers a deeper understanding of regulatory variants uncharacterized by mRNA expression regulation (expression QTLs (eQTLs)) studies. Here we report cis-eQTL and cis-pQTL statistical fine-mapping from 1,405 genotyped samples with blood mRNA and 2,932 plasma samples of protein expression, as part of the Japan COVID-19 Task Force (JCTF). Fine-mapped eQTLs (n = 3,464) were enriched for 932 variants validated with a massively parallel reporter assay. Fine-mapped pQTLs (n = 582) were enriched for missense variations on structured and extracellular domains, although the possibility of epitope-binding artifacts remains. Trans-eQTL and trans-pQTL analysis highlighted associations of class I HLA allele variation with KIR genes. We contrast the multi-tissue origin of plasma protein with blood mRNA, contributing to the limited colocalization level, distinct regulatory mechanisms and trait relevance of eQTLs and pQTLs. We report a negative correlation between ABO mRNA and protein expression because of linkage disequilibrium between distinct nearby eQTLs and pQTLs.

A sexually dimorphic hepatic cycle of periportal VLDL generation and subsequent pericentral VLDLR-mediated re-uptake

Recent single-cell transcriptomes revealed spatiotemporal programmes of liver function on the sublobular scale. However, how sexual dimorphism affected this space-time logic remained poorly understood. We addressed this by performing scRNA-seq in the mouse liver, which revealed that sex, space and time together markedly influence xenobiotic detoxification and lipoprotein metabolism. The very low density lipoprotein receptor (VLDLR) exhibits a pericentral expression pattern, with significantly higher mRNA and protein levels in female mice. Conversely, VLDL assembly is periportally biased, suggesting a sexually dimorphic hepatic cycle of periportal formation and pericentral uptake of VLDL. In humans, VLDLR expression is also pericentral, with higher mRNA and protein levels in premenopausal women compared to similarly aged men. Individuals with low hepatic VLDLR expression show a high prevalence of atherosis in the coronary artery already at an early age and an increased incidence of heart attack.

Brain-body mitochondrial distribution patterns lack coherence and point to tissue-specific and individualized regulatory mechanisms

Energy transformation capacity is generally assumed to be a coherent individual trait driven by genetic and environmental factors. This predicts that some individuals should have high and others low mitochondrial oxidative phosphorylation (OxPhos) capacity across organ systems. Here, we test this assumption using multi-tissue molecular and enzymatic activities in mice and humans. Across up to 22 mouse tissues, neither mitochondrial OxPhos capacity nor mtDNA density were correlated between tissues (median r = -0.01-0.16), indicating that animals with high mitochondrial capacity in one tissue can have low capacity in other tissues. Similarly, the multi-tissue correlation structure of RNAseq-based indices of mitochondrial gene expression across 45 tissues from 948 women and men (GTEx) showed small to moderate coherence between only some tissues (regions of the same brain), but not between brain-body tissue pairs in the same person (median r = 0.01). Mitochondrial DNA copy number (mtDNAcn) also lacked coherence across organs and tissues. Mechanistically, tissue-specific differences in mitochondrial gene expression were attributable in part to i) tissue-specific activation of canonical energy sensing pathways including the transcriptional coactivator PGC-1 and the integrated stress response (ISR), and ii) proliferative activity across tissues. Finally, we identify subgroups of individuals with high mitochondrial gene expression in some tissues (e.g., heart) but low expression in others (e.g., skeletal muscle) who display different clinical phenotypic patterns. Taken together, these data raise the possibility that tissue-specific energy sensing pathways may contribute to the idiosyncratic mitochondrial distribution patterns associated with the inter-organ heterogeneity and phenotypic diversity among individuals.

Improved deconvolution of natural products' protein targets using diagnostic ions from chemical proteomics linkers

Identification of interactions between proteins and natural products or similar active small molecules is crucial for understanding of their mechanism of action on a molecular level. To search elusive, often labile, and low-abundant conjugates between proteins and active compounds, chemical proteomics introduces a feasible strategy that allows to enrich and detect these conjugates. Recent advances in mass spectrometry techniques and search algorithms provide unprecedented depth of proteome coverage and the possibility to detect desired modified peptides with high sensitivity. The chemical 'linker' connecting an active compound-protein conjugate with a detection tag is the critical component of all chemical proteomic workflows. In this review, we discuss the properties and applications of different chemical proteomics linkers with special focus on their fragmentation releasing diagnostic ions and how these may improve the confidence in identified active compound-peptide conjugates. The application of advanced search options improves the identification rates and may help to identify otherwise difficult to find interactions between active compounds and proteins, which may result from unperturbed conditions, and thus are of high physiological relevance.

Systematic mapping of mitochondrial calcium uniporter channel (MCUC)-mediated calcium signaling networks

The mitochondrial calcium uniporter channel (MCUC) mediates mitochondrial calcium entry, regulating energy metabolism and cell death. Although several MCUC components have been identified, the molecular basis of mitochondrial calcium signaling networks and their remodeling upon changes in uniporter activity have not been assessed. Here, we map the MCUC interactome under resting conditions and upon chronic loss or gain of mitochondrial calcium uptake. We identify 89 high-confidence interactors that link MCUC to several mitochondrial complexes and pathways, half of which are associated with human disease. As a proof-of-concept, we validate the mitochondrial intermembrane space protein EFHD1 as a binding partner of the MCUC subunits MCU, EMRE, and MCUB. We further show a MICU1-dependent inhibitory effect of EFHD1 on calcium uptake. Next, we systematically survey compensatory mechanisms and functional consequences of mitochondrial calcium dyshomeostasis by analyzing the MCU interactome upon EMRE, MCUB, MICU1, or MICU2 knockdown. While silencing EMRE reduces MCU interconnectivity, MCUB loss-of-function leads to a wider interaction network. Our study provides a comprehensive and high-confidence resource to gain insights into players and mechanisms regulating mitochondrial calcium signaling and their relevance in human diseases.

Induction of oxidative- and endoplasmic-reticulum-stress dependent apoptosis in pancreatic cancer cell lines by DDOST knockdown

The dolichyl-diphosphooligosaccharide-protein glycosyltransferase non-catalytic subunit (DDOST) is a key component of the oligosaccharyltransferase complex catalyzing N-linked glycosylation in the endoplasmic reticulum lumen. DDOST is associated with several cancers and congenital disorders of glycosylation. However, its role in pancreatic cancer remains elusive, despite its enriched pancreatic expression. Using quantitative mass spectrometry, we identify 30 differentially expressed proteins and phosphopeptides (DEPs) after DDOST knockdown in the pancreatic ductal adenocarcinoma (PDAC) cell line PA-TU-8988T. We evaluated DDOST / DEP protein-protein interaction networks using STRING database, correlation of mRNA levels in pancreatic cancer TCGA data, and biological processes annotated to DEPs in Gene Ontology database. The inferred DDOST regulated phenotypes were experimentally verified in two PDAC cell lines, PA-TU-8988T and BXPC-3. We found decreased proliferation and cell viability after DDOST knockdown, whereas ER-stress, ROS-formation and apoptosis were increased. In conclusion, our results support an oncogenic role of DDOST in PDAC by intercepting cell stress events and thereby reducing apoptosis. As such, DDOST might be a potential biomarker and therapeutic target for PDAC.

Host-pathogen interactions from a metabolic perspective: methods of investigation

Metabolism shapes immune homeostasis in health and disease. This review presents the range of methods that are currently available to investigate the dialog between metabolism and immunity at the systemic, tissue and cellular levels, particularly during infection.

SPIDER: constructing cell-type-specific protein-protein interaction networks

Motivation

Protein-protein interactions (PPIs) play essential roles in the buildup of cellular machinery and provide the skeleton for cellular signaling. However, these biochemical roles are context dependent and interactions may change across cell type, time, and space. In contrast, PPI detection assays are run in a single condition that may not even be an endogenous condition of the organism, resulting in static networks that do not reflect full cellular complexity. Thus, there is a need for computational methods to predict cell-type-specific interactions.

Results

Here we present SPIDER (Supervised Protein Interaction DEtectoR), a graph attention-based model for predicting cell-type-specific PPI networks. In contrast to previous attempts at this problem, which were unsupervised in nature, our model's training is guided by experimentally measured cell-type-specific networks, enhancing its performance. We evaluate our method using experimental data of cell-type-specific networks from both humans and mice, and show that it outperforms current approaches by a large margin. We further demonstrate the ability of our method to generalize the predictions to datasets of tissues lacking prior PPI experimental data. We leverage the networks predicted by the model to facilitate the identification of tissue-specific disease genes.

Availability and implementation

Our code and data are available at https://github.com/Kuper994/SPIDER.

MICU1 and MICU2 control mitochondrial calcium signaling in the mammalian heart

Activating Ca2+-sensitive enzymes of oxidative metabolism while preventing calcium overload that leads to mitochondrial and cellular injury requires dynamic control of mitochondrial Ca2+ uptake. This is ensured by the mitochondrial calcium uptake (MICU)1/2 proteins that gate the pore of the mitochondrial calcium uniporter (mtCU). MICU1 is relatively sparse in the heart, and recent studies claimed the mammalian heart lacks MICU1 gating of mtCU. However, genetic models have not been tested. We find that MICU1 is present in a complex with MCU in nonfailing human hearts. Furthermore, using murine genetic models and pharmacology, we show that MICU1 and MICU2 control cardiac mitochondrial Ca2+ influx, and that MICU1 deletion alters cardiomyocyte mitochondrial calcium signaling and energy metabolism. MICU1 loss causes substantial compensatory changes in the mtCU composition and abundance, increased turnover of essential MCU regulator (EMRE) early on and, later, of MCU, that limit mitochondrial Ca2+ uptake and allow cell survival. Thus, both the primary consequences of MICU1 loss and the ensuing robust compensation highlight MICU1's relevance in the beating heart.

Systematic identification of minor histocompatibility antigens predicts outcomes of allogeneic hematopoietic cell transplantation

T cell alloreactivity against minor histocompatibility antigens (mHAgs)-polymorphic peptides resulting from donor-recipient (D-R) disparity at sites of genetic polymorphisms-is at the core of the therapeutic effect of allogeneic hematopoietic cell transplantation (allo-HCT). Despite the crucial role of mHAgs in graft-versus-leukemia (GvL) and graft-versus-host disease (GvHD) reactions, it remains challenging to consistently link patient-specific mHAg repertoires to clinical outcomes. Here we devise an analytic framework to systematically identify mHAgs, including their detection on HLA class I ligandomes and functional verification of their immunogenicity. The method relies on the integration of polymorphism detection by whole-exome sequencing of germline DNA from D-R pairs with organ-specific transcriptional- and proteome-level expression. Application of this pipeline to 220 HLA-matched allo-HCT D-R pairs demonstrated that total and organ-specific mHAg load could independently predict the occurrence of acute GvHD and chronic pulmonary GvHD, respectively, and defined promising GvL targets, confirmed in a validation cohort of 58 D-R pairs, for the prevention or treatment of post-transplant disease recurrence.

Comprehensive Overview of Bottom-Up Proteomics Using Mass Spectrometry

Proteomics is the large scale study of protein structure and function from biological systems through protein identification and quantification. "Shotgun proteomics" or "bottom-up proteomics" is the prevailing strategy, in which proteins are hydrolyzed into peptides that are analyzed by mass spectrometry. Proteomics studies can be applied to diverse studies ranging from simple protein identification to studies of proteoforms, protein-protein interactions, protein structural alterations, absolute and relative protein quantification, post-translational modifications, and protein stability. To enable this range of different experiments, there are diverse strategies for proteome analysis. The nuances of how proteomic workflows differ may be challenging to understand for new practitioners. Here, we provide a comprehensive overview of different proteomics methods. We cover from biochemistry basics and protein extraction to biological interpretation and orthogonal validation. We expect this Review will serve as a handbook for researchers who are new to the field of bottom-up proteomics.

DNA damage-associated protein co-expression network in cardiomyocytes informs on tolerance to genetic variation and disease

Cardiovascular disease (CVD) is associated with both genetic variants and environmental factors. One unifying consequence of the molecular risk factors in CVD is DNA damage, which must be repaired by DNA damage response proteins. However, the impact of DNA damage on global cardiomyocyte protein abundance, and its relationship to CVD risk remains unclear. We therefore treated induced pluripotent stem cell-derived cardiomyocytes with the DNA-damaging agent Doxorubicin (DOX) and a vehicle control, and identified 4,178 proteins that contribute to a network comprising 12 co-expressed modules and 403 hub proteins with high intramodular connectivity. Five modules correlate with DOX and represent distinct biological processes including RNA processing, chromatin regulation and metabolism. DOX-correlated hub proteins are depleted for proteins that vary in expression across individuals due to genetic variation but are enriched for proteins encoded by loss-of-function intolerant genes. While proteins associated with genetic risk for CVD, such as arrhythmia are enriched in specific DOX-correlated modules, DOX-correlated hub proteins are not enriched for known CVD risk proteins. Instead, they are enriched among proteins that physically interact with CVD risk proteins. Our data demonstrate that DNA damage in cardiomyocytes induces diverse effects on biological processes through protein co-expression modules that are relevant for CVD, and that the level of protein connectivity in DNA damage-associated modules influences the tolerance to genetic variation.

Proton pump inhibitor effect on esophageal protein signature of eosinophilic esophagitis, prediction, and evaluation of treatment response

BACKGROUND

Recently, we have identified a dysregulated protein signature in the esophageal epithelium of eosinophilic esophagitis (EoE) patients including proteins associated with inflammation and epithelial barrier function; however, the effect of proton pump inhibitor (PPI) treatment on this signature is unknown. Herein, we used a proteomic approach to investigate: (1) whether PPI treatment alters the esophageal epithelium protein profile observed in EoE patients and (2) whether the protein signature at baseline predicts PPI response.

METHODS

We evaluated the protein signature of esophageal biopsies using a cohort of adult EoE (n = 25) patients and healthy controls (C) (n = 10). In EoE patients, esophageal biopsies were taken before (pre) and after (post) an 8-week PPI treatment, determining the histologic response. Eosinophil count PostPPI was used to classify the patients: ≥15 eosinophils/hpf as non-responders (non-responder) and < 15 eosinophils/hpf as responders (R). Protein signature was determined and differentially accumulated proteins were characterized to identify altered biological processes and signaling pathways.

RESULTS

Comparative analysis of differentially accumulated proteins between groups revealed common signatures between three groups of patients with inflammation (responder-PrePPI, non-responder-PrePPI, and non-responder-PostPPI) and without inflammation (controls and responder-PostPPI). PPI therapy almost reversed the EoE specific esophageal protein signature, which is enriched in pathways associated with inflammation and epithelial barrier function, in responder-PostPPI. Furthermore, we identified a set of candidate proteins to differentiate responder-PrePPI and non-responder-PrePPI EoE patients before treatment.

CONCLUSION

These findings provide evidence that PPI therapy reverses the alterations in esophageal inflammatory and epithelial proteins characterizing EoE, thereby providing new insights into the mechanism of PPI clinical response. Interestingly, our results also suggest that PPI response could be predicted at baseline in EoE.

Mass spectrometry-based proteomic landscape of rice reveals a post-transcriptional regulatory role of N6-methyladenosine

Rice is one of the most important staple food and model species in plant biology, yet its quantitative proteomes are largely uncharacterized. Here we quantify the relative protein levels of over 15,000 genes across major rice tissues using a tandem mass tag strategy followed by intensive fractionation and mass spectrometry. We identify tissue-specific and tissue-enriched proteins that are linked to the functional specificity of individual tissues. Proteogenomic comparison of rice and Arabidopsis reveals conserved proteome expression, which differs from mammals in that there is a strong separation of species rather than tissues. Notably, profiling of N6-methyladenosine (m6A) across the rice major tissues shows that m6A at untranslated regions is negatively correlated with protein abundance and contributes to the discordance between RNA and protein levels. We also demonstrate that our data are valuable for identifying novel genes required for regulating m6A methylation. Taken together, this study provides a paradigm for further research into rice proteogenome.

Self-consistent signal transduction analysis for modeling context-specific signaling cascades and perturbations

Biological signal transduction networks are central to information processing and regulation of gene expression across all domains of life. Dysregulation is known to cause a wide array of diseases, including cancers. Here I introduce self-consistent signal transduction analysis, which utilizes genome-scale -omics data (specifically transcriptomics and/or proteomics) in order to predict the flow of information through these networks in an individualized manner. I apply the method to the study of endocrine therapy in breast cancer patients, and show that drugs that inhibit estrogen receptor α elicit a wide array of antitumoral effects, and that their most clinically-impactful ones are through the modulation of proliferative signals that control the genes GREB1, HK1, AKT1, MAPK1, AKT2, and NQO1. This method offers researchers a valuable tool in understanding how and why dysregulation occurs, and how perturbations to the network (such as targeted therapies) effect the network itself, and ultimately patient outcomes.

IS-PRM-Based Peptide Targeting Informed by Long-Read Sequencing for Alternative Proteome Detection

Alternative splicing is a major contributor of transcriptomic complexity, but the extent to which transcript isoforms are translated into stable, functional protein isoforms is unclear. Furthermore, detection of relatively scarce isoform-specific peptides is challenging, with many protein isoforms remaining uncharted due to technical limitations. Recently, a family of advanced targeted MS strategies, termed internal standard parallel reaction monitoring (IS-PRM), have demonstrated multiplexed, sensitive detection of predefined peptides of interest. Such approaches have not yet been used to confirm existence of novel peptides. Here, we present a targeted proteogenomic approach that leverages sample-matched long-read RNA sequencing (lrRNA-seq) data to predict potential protein isoforms with prior transcript evidence. Predicted tryptic isoform-specific peptides, which are specific to individual gene product isoforms, serve as "triggers" and "targets" in the IS-PRM method, Tomahto. Using the model human stem cell line WTC11, LR RNaseq data were generated and used to inform the generation of synthetic standards for 192 isoform-specific peptides (114 isoforms from 55 genes). These synthetic "trigger" peptides were labeled with super heavy tandem mass tags (TMT) and spiked into TMT-labeled WTC11 tryptic digest, predicted to contain corresponding endogenous "target" peptides. Compared to DDA mode, Tomahto increased detectability of isoforms by 3.6-fold, resulting in the identification of five previously unannotated isoforms. Our method detected protein isoform expression for 43 out of 55 genes corresponding to 54 resolved isoforms. This lrRNA-seq-informed Tomahto targeted approach is a new modality for generating protein-level evidence of alternative isoforms─a critical first step in designing functional studies and eventually clinical assays.

Are We There Yet? Assessing the Readiness of Single-Cell Proteomics to Answer Biological Hypotheses

Single-cell analysis is an active area of research in many fields of biology. Measurements at single-cell resolution allow researchers to study diverse populations without losing biologically meaningful information to sample averages. Many technologies have been used to study single cells, including mass spectrometry-based single-cell proteomics (SCP). SCP has seen a lot of growth over the past couple of years through improvements in data acquisition and analysis, leading to greater proteomic depth. Because method development has been the main focus in SCP, biological applications have been sprinkled in only as proof-of-concept. However, SCP methods now provide significant coverage of the proteome and have been implemented in many laboratories. Thus, a primary question to address in our community is whether the current state of technology is ready for widespread adoption for biological inquiry. In this Perspective, we examine the potential for SCP in three thematic areas of biological investigation: cell annotation, developmental trajectories, and spatial mapping. We identify that the primary limitation of SCP is sample throughput. As proteome depth has been the primary target for method development to date, we advocate for a change in focus to facilitate measuring tens of thousands of single-cell proteomes to enable biological applications beyond proof-of-concept.

Hypoxia inhibits the iMo/cDC2/CD8+ TRMs immune axis in the tumor microenvironment of human esophageal cancer

BACKGROUND

Esophageal cancer (ESCA) is a form of malignant tumor associated with chronic inflammation and immune dysregulation. However, the specific immune status and key mechanisms of immune regulation in this disease require further exploration.

METHODS

To investigate the features of the human ESCA tumor immune microenvironment and its possible regulation, we performed mass cytometry by time of flight, single-cell RNA sequencing, multicolor fluorescence staining of tissue, and flow cytometry analyses on tumor and paracancerous tissue from treatment-naïve patients.

RESULTS

We depicted the immune landscape of the ESCA and revealed that CD8+ (tissue-resident memory CD8+ T cells (CD8+ TRMs) were closely related to disease progression. We also revealed the heterogeneity of CD8+ TRMs in the ESCA tumor microenvironment (TME), which was associated with their differentiation and function. Moreover, the subset of CD8+ TRMs in tumor (called tTRMs) that expressed high levels of granzyme B and immune checkpoints was markedly decreased in the TME of advanced ESCA. We showed that tTRMs are tumor effector cells preactivated in the TME. We then demonstrated that conventional dendritic cells (cDC2s) derived from intermediate monocytes (iMos) are essential for maintaining the proliferation of CD8+ TRMs in the TME. Our preliminary study showed that hypoxia can promote the apoptosis of iMos and impede the maturation of cDC2s, which in turn reduces the proliferative capacity of CD8+ TRMs, thereby contributing to the progression of cancer.

CONCLUSIONS

Our study revealed the essential antitumor roles of CD8+ TRMs and preliminarily explored the regulation of the iMo/cDC2/CD8+ TRM immune axis in the human ESCA TME.

Proteomic predictors of individualized nutrient-specific insulin secretion in health and disease

Population-level variation and mechanisms behind insulin secretion in response to carbohydrate, protein, and fat remain uncharacterized. We defined prototypical insulin secretion responses to three macronutrients in islets from 140 cadaveric donors, including those with type 2 diabetes. The majority of donors' islets exhibited the highest insulin response to glucose, moderate response to amino acid, and minimal response to fatty acid. However, 9% of donors' islets had amino acid responses, and 8% had fatty acid responses that were larger than their glucose-stimulated insulin responses. We leveraged this heterogeneity and used multi-omics to identify molecular correlates of nutrient responsiveness, as well as proteins and mRNAs altered in type 2 diabetes. We also examined nutrient-stimulated insulin release from stem cell-derived islets and observed responsiveness to fat but not carbohydrate or protein-potentially a hallmark of immaturity. Understanding the diversity of insulin responses to carbohydrate, protein, and fat lays the groundwork for personalized nutrition.

Mass spectrometry for the study of adipocyte cell secretome in cardiovascular diseases

Adipose tissue is classically considered the primary site of lipid storage, but in recent years has garnered appreciation for its broad role as an endocrine organ, capable of remotely signaling to other tissues to alter their metabolic program. The adipose tissue is now recognized as a crucial regulator of cardiovascular health, mediated by the secretion of several bioactive products, with a wide range of endocrine and paracrine effects on the cardiovascular system. Thanks to the development and improvement of high-throughput mass spectrometry, the size and components of the human secretome have been characterized. In this review, we summarized the recent advances in mass spectrometry-based studies of the cell and tissue secretome for the understanding of adipose tissue biology, which may help to decipher the complex molecular mechanisms controlling the crosstalk between the adipose tissue and the cardiovascular system, and their possible clinical translation.

Bioinformatic Analysis Reveals the Association of Human N-Terminal Acetyltransferase Complexes with Distinct Transcriptional and Post-Transcriptional Processes

N-terminal acetyltransferases (NAT) are the protein complexes that deposit the abundant N-terminal acetylation (Nt-Ac) on eukaryotic proteins, with seven human complexes currently identified. Despite the increasing recognition of their biological and clinical importance, NAT regulation remains elusive. In this study, we performed a bioinformatic investigation to identify transcriptional and post-transcriptional processes that could be involved in the regulation of human NAT complexes. First, co-expression analysis of independent transcriptomic datasets revealed divergent pathway associations for human NAT, which are potentially connected to their distinct cellular functions. One interesting connection uncovered was the coordinated regulation of the NatA and proteasomal genes in cancer and immune cells, confirmed by analysis of multiple datasets and in isolated primary T cells. Another distinctive association was of NAA40 (NatD) with DNA replication, in cancer and non-cancer settings. The link between NAA40 transcription and DNA replication is potentially mediated through E2F1, which we have experimentally shown to bind the promoter of this NAT. Second, the coupled examination of transcriptomic and proteomic datasets revealed a much greater intra-complex concordance of NAT subunits at the protein compared to the transcript level, indicating the predominance of post-transcriptional processes for achieving their coordination. In agreement with this concept, we also found that the effects of somatic copy number alterations affecting NAT genes are attenuated post-transcriptionally. In conclusion, this study provides novel insights into the regulation of human NAT complexes.

Superb Silk Hydrogels with High Adaptability, Bioactivity, and Versatility Enabled by Photo-Cross-Linking

The exceptional biocompatibility and adaptability of hydrogels have garnered significant interest in the biomedical field for the fabrication of biomedical devices. However, conventional synthetic hydrogels still exhibit relatively weak and fragile properties. Drawing inspiration from the photosynthesis process, we developed a facile approach to achieve a harmonious combination of superior mechanical properties and efficient preparation of silk fibroin hydrogel through photo-cross-linking technology, accomplished within 60 s. The utilization of riboflavin and H2O2 enabled a sustainable cyclic photo-cross-linking reaction, facilitating the transformation from tyrosine to dityrosine and ultimately contributing to the formation of highly cross-linked hydrogels. These photo-cross-linking hydrogels exhibited excellent elasticity and restorability even after undergoing 1000 cycles of compression. Importantly, our findings presented that hydrogel-encapsulated adipose stem cells possess the ability to stimulate cell proliferation along with stem cell stemness. This was evidenced by the continuous high expression levels of OCT4 and SOX2 over 21 days. Additionally, the utilization of photo-cross-linking hydrogels can be extended to various material molding platforms, including microneedles, microcarriers, and bone screws. Consequently, this study offered a significant approach to fabricating biomedical hydrogels capable of facilitating real-time cell delivery, thereby introducing an innovative avenue for designing silk devices with exceptional machinability and adaptability in biomedical applications.

Statistical Testing for Protein Equivalence Identifies Core Functional Modules Conserved across 360 Cancer Cell Lines and Presents a General Approach to Investigating Biological Systems

Quantitative proteomics has enhanced our capability to study protein dynamics and their involvement in disease using various techniques, including statistical testing, to discern the significant differences between conditions. While most focus is on what is different between conditions, exploring similarities can provide valuable insights. However, exploring similarities directly from the analyte level, such as proteins, genes, or metabolites, is not a standard practice and is not widely adopted. In this study, we propose a statistical framework called QuEStVar (Quantitative Exploration of Stability and Variability through statistical hypothesis testing), enabling the exploration of quantitative stability and variability of features with a combined statistical framework. QuEStVar utilizes differential and equivalence testing to expand statistical classifications of analytes when comparing conditions. We applied our method to an extensive data set of cancer cell lines and revealed a quantitatively stable core proteome across diverse tissues and cancer subtypes. The functional analysis of this set of proteins highlighted the molecular mechanism of cancer cells to maintain constant conditions of the tumorigenic environment via biological processes, including transcription, translation, and nucleocytoplasmic transport.

IMMUNOTAR - Integrative prioritization of cell surface targets for cancer immunotherapy

Cancer remains a leading cause of mortality globally. Recent improvements in survival have been facilitated by the development of less toxic immunotherapies; however, identifying targets for immunotherapies remains a challenge in the field. To address this challenge, we developed IMMUNOTAR, a computational tool that systematically prioritizes and identifies candidate immunotherapeutic targets. IMMUNOTAR integrates user-provided RNA-sequencing or proteomics data with quantitative features extracted from publicly available databases based on predefined optimal immunotherapeutic target criteria and quantitatively prioritizes potential surface protein targets. We demonstrate the utility and flexibility of IMMUNOTAR using three distinct datasets, validating its effectiveness in identifying both known and new potential immunotherapeutic targets within the analyzed cancer phenotypes. Overall, IMMUNOTAR enables the compilation of data from multiple sources into a unified platform, allowing users to simultaneously evaluate surface proteins across diverse criteria. By streamlining target identification, IMMUNOTAR empowers researchers to efficiently allocate resources and accelerate immunotherapy development.

Cellular control of protein levels: A systems biology perspective

How cells regulate protein levels is a central question of biology. Over the past decades, molecular biology research has provided profound insights into the mechanisms and the molecular machinery governing each step of the gene expression process, from transcription to protein degradation. Recent advances in transcriptomics and proteomics have complemented our understanding of these fundamental cellular processes with a quantitative, systems-level perspective. Multi-omic studies revealed significant quantitative, kinetic and functional differences between the genome, transcriptome and proteome. While protein levels often correlate with mRNA levels, quantitative investigations have demonstrated a substantial impact of translation and protein degradation on protein expression control. In addition, protein-level regulation appears to play a crucial role in buffering protein abundances against undesirable mRNA expression variation. These findings have practical implications for many fields, including gene function prediction and precision medicine.

Multi-Omic Analysis of Esophageal Adenocarcinoma Uncovers Candidate Therapeutic Targets and Cancer-Selective Posttranscriptional Regulation

Efforts to address the poor prognosis associated with esophageal adenocarcinoma (EAC) have been hampered by a lack of biomarkers to identify early disease and therapeutic targets. Despite extensive efforts to understand the somatic mutations associated with EAC over the past decade, a gap remains in understanding how the atlas of genomic aberrations in this cancer impacts the proteome and which somatic variants are of importance for the disease phenotype. We performed a quantitative proteomic analysis of 23 EACs and matched adjacent normal esophageal and gastric tissues. We explored the correlation of transcript and protein abundance using tissue-matched RNA-seq and proteomic data from seven patients and further integrated these data with a cohort of EAC RNA-seq data (n = 264 patients), EAC whole-genome sequencing (n = 454 patients), and external published datasets. We quantified protein expression from 5879 genes in EAC and patient-matched normal tissues. Several biomarker candidates with EAC-selective expression were identified, including the transmembrane protein GPA33. We further verified the EAC-enriched expression of GPA33 in an external cohort of 115 patients and confirm this as an attractive diagnostic and therapeutic target. To further extend the insights gained from our proteomic data, an integrated analysis of protein and RNA expression in EAC and normal tissues revealed several genes with poorly correlated protein and RNA abundance, suggesting posttranscriptional regulation of protein expression. These outlier genes, including SLC25A30, TAOK2, and AGMAT, only rarely demonstrated somatic mutation, suggesting post-transcriptional drivers for this EAC-specific phenotype. AGMAT was demonstrated to be overexpressed at the protein level in EAC compared to adjacent normal tissues with an EAC-selective, post-transcriptional mechanism of regulation of protein abundance proposed. Integrated analysis of proteome, transcriptome, and genome in EAC has revealed several genes with tumor-selective, posttranscriptional regulation of protein expression, which may be an exploitable vulnerability.

A novel PSMB8 isoform associated with multiple sclerosis lesions induces P-body formation

Introduction

Multiple sclerosis (MS) is an inflammatory and demyelinating disease of the central nervous system (CNS). Current therapies primarily target the inflammatory component of the disease and are highly effective in early stages of MS while limited therapies have an effect in the more chronic progressive stages of MS where resident glia have a larger role. MS lesions tend to be inflammatory even after the initial peripheral immune cell invasion has subsided and this inflammation is known to cause alternative splicing events.

Methods

We used qPCR of normal-appearing white matter and white matter lesions from postmortem MS tissue, in vitro studies, and immunostaining in MS tissue to investigate the alternative splicing of one gene known to be important during recovery in an animal model of MS, PSMB8.

Results

We found a novel, intron-retained isoform which has not been annotated, upregulated specifically in MS patient white matter lesions. We found that this novel isoform activates the nonsense-mediated decay pathway in primary human astrocytes, the most populous glial cell in the CNS, and is then degraded. Overexpression of this isoform in astrocytes leads to an increased number of processing bodies in vitro, the primary site of mRNA decay. Finally, we demonstrated that MS white matter lesions have a higher burden of processing bodies compared to normal-appearing white matter, predominantly in GFAP-positive astrocytes.

Discussion

The increase in alternative splicing of the PSMB8 gene, the stress that this alternative splicing causes, and the observation that processing bodies are increased in white matter lesions suggests that the lesion microenvironment may lead to increased alternative splicing of many genes. This alternative splicing may blunt the protective or reparative responses of resident glia in and around white matter lesions in MS patients.

Species-wide quantitative transcriptomes and proteomes reveal distinct genetic control of gene expression variation in yeast

Gene expression varies between individuals and corresponds to a key step linking genotypes to phenotypes. However, our knowledge regarding the species-wide genetic control of protein abundance, including its dependency on transcript levels, is very limited. Here, we have determined quantitative proteomes of a large population of 942 diverse natural Saccharomyces cerevisiae yeast isolates. We found that mRNA and protein abundances are weakly correlated at the population gene level. While the protein coexpression network recapitulates major biological functions, differential expression patterns reveal proteomic signatures related to specific populations. Comprehensive genetic association analyses highlight that genetic variants associated with variation in protein (pQTL) and transcript (eQTL) levels poorly overlap (3%). Our results demonstrate that transcriptome and proteome are governed by distinct genetic bases, likely explained by protein turnover. It also highlights the importance of integrating these different levels of gene expression to better understand the genotype-phenotype relationship.

Correlating transcription and protein expression profiles of immune biomarkers following lipopolysaccharide exposure in lung epithelial cells

Universal and early recognition of pathogens occurs through recognition of evolutionarily conserved pathogen associated molecular patterns (PAMPs) by innate immune receptors and the consequent secretion of cytokines and chemokines. The intrinsic complexity of innate immune signaling and associated signal transduction challenges our ability to obtain physiologically relevant, reproducible and accurate data from experimental systems. One of the reasons for the discrepancy in observed data is the choice of measurement strategy. Immune signaling is regulated by the interplay between pathogen-derived molecules with host cells resulting in cellular expression changes. However, these cellular processes are often studied by the independent assessment of either the transcriptome or the proteome. Correlation between transcription and protein analysis is lacking in a variety of studies. In order to methodically evaluate the correlation between transcription and protein expression profiles associated with innate immune signaling, we measured cytokine and chemokine levels following exposure of human cells to the PAMP lipopolysaccharide (LPS) from the Gram-negative pathogen Pseudomonas aeruginosa. Expression of 84 messenger RNA (mRNA) transcripts and 69 proteins, including 35 overlapping targets, were measured in human lung epithelial cells. We evaluated 50 biological replicates to determine reproducibility of outcomes. Following pairwise normalization, 16 mRNA transcripts and 6 proteins were significantly upregulated following LPS exposure, while only five (CCL2, CSF3, CXCL5, CXCL8/IL8, and IL6) were upregulated in both transcriptomic and proteomic analysis. This lack of correlation between transcription and protein expression data may contribute to the discrepancy in the immune profiles reported in various studies. The use of multiomic assessments to achieve a systems-level understanding of immune signaling processes can result in the identification of host biomarker profiles for a variety of infectious diseases and facilitate countermeasure design and development.

lncRNA-mRNA Co-Expression and Regulation Analysis in Lung Fibroblasts from Idiopathic Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease marked by abnormal accumulation of extracellular matrix (ECM) due to dysregulated expression of various RNAs in pulmonary fibroblasts. This study utilized RNA-seq data meta-analysis to explore the regulatory network of hub long non-coding RNAs (lncRNAs) and messenger RNAs (mRNAs) in IPF fibroblasts. The meta-analysis unveiled 584 differentially expressed mRNAs (DEmRNA) and 75 differentially expressed lncRNAs (DElncRNA) in lung fibroblasts from IPF. Among these, BCL6, EFNB1, EPHB2, FOXO1, FOXO3, GNAI1, IRF4, PIK3R1, and RXRA were identified as hub mRNAs, while AC008708.1, AC091806.1, AL442071.1, FAM111A-DT, and LINC01989 were designated as hub lncRNAs. Functional characterization revealed involvement in TGF-β, PI3K, FOXO, and MAPK signaling pathways. Additionally, this study identified regulatory interactions between sequences of hub mRNAs and lncRNAs. In summary, the findings suggest that AC008708.1, AC091806.1, FAM111A-DT, LINC01989, and AL442071.1 lncRNAs can regulate BCL6, EFNB1, EPHB2, FOXO1, FOXO3, GNAI1, IRF4, PIK3R1, and RXRA mRNAs in fibroblasts bearing IPF and contribute to fibrosis by modulating crucial signaling pathways such as FoxO signaling, chemical carcinogenesis, longevity regulatory pathways, non-small cell lung cancer, and AMPK signaling pathways.

Nitrosative Stress in Astronaut Skeletal Muscle in Spaceflight

Long-duration mission (LDM) astronauts from the International Space Station (ISS) (>180 ISS days) revealed a close-to-normal sarcolemmal nitric oxide synthase type-1 (NOS1) immunoexpression in myofibers together with biochemical and quantitative qPCR changes in deep calf soleus muscle. Nitro-DIGE analyses identified functional proteins (structural, metabolic, mitochondrial) that were over-nitrosylated post- vs. preflight. In a short-duration mission (SDM) astronaut (9 ISS days), s-nitrosylation of a nodal protein of the glycolytic flux, specific proteins in tricarboxylic acid (TCA) cycle, respiratory chain, and over-nitrosylation of creatine kinase M-types as signs of impaired ATP production and muscle contraction proteins were seen. S-nitrosylation of serotransferrin (TF) or carbonic anhydrase 3 (CA3b and 3c) represented signs of acute response microgravity muscle maladaptation. LDM nitrosoprofiles reflected recovery of mitochondrial activity, contraction proteins, and iron transporter TF as signs of muscle adaptation to microgravity. Nitrosated antioxidant proteins, alcohol dehydrogenase 5/S-nitrosoglutathione reductase (ADH5/GSNOR), and selenoprotein thioredoxin reductase 1 (TXNRD1) levels indicated signs of altered redox homeostasis and reduced protection from nitrosative stress in spaceflight. This work presents a novel spaceflight-generated dataset on s-nitrosylated muscle protein signatures from astronauts that helps both to better understand the structural and molecular networks associated to muscular nitrosative stress and to design countermeasures to dysfunction and impaired performance control in human spaceflight missions.

A Pilot Urinary Proteome Study Reveals Widespread Influences of Circadian Rhythm Disruption by Sleep Deprivation

It is widely accepted that circadian rhythm disruption caused short- or long-term adverse effects on health. Although many previous studies have focused on exploration of the molecular mechanisms, there is no rapid, convenient, and non-invasive method to reveal the influence on health after circadian rhythm disruption. Here, we performed a high-resolution mass spectrometry-based data-independent acquisition (DIA) quantitative urinary proteomic approach in order to explore whether urine could reveal stress changes to those brought about by circadian rhythm disruption after sleep deprivation. After sleep deprivation, the subjects showed a significant increase in both systolic and diastolic blood pressure compared with routine sleep. More than 2000 proteins were quantified and they contained specific proteins for various organs throughout the body. And a total of 177 significantly up-regulated proteins and 68 significantly down-regulated proteins were obtained after sleep deprivation. These differentially expressed proteins (DEPs) were associated with multiple organs and pathways, which reflected widespread influences of sleep deprivation. Besides, machine learning identified a panel of five DEPs (CD300A, SCAMP3, TXN2, EFEMP1, and MYH11) that can effectively discriminate circadian rhythm disruption. Taken together, our results validate the value of urinary proteome in predicting and diagnosing the changes by circadian rhythm disruption.

The wedish initiative for the stdy of ary sclerosing cholangitis (SUPRIM)

Background

Despite more than 50 years of research and parallel improvements in hepatology and oncology, there is still today neither a treatment to prevent disease progression in primary sclerosing cholangitis (PSC), nor reliable early diagnostic tools for the associated hepatobiliary cancers. Importantly, the limited understanding of the underlying biological mechanisms in PSC and its natural history not only affects the identification of new drug targets but implies a lack of surrogate markers that hampers the design of clinical trials and the evaluation of drug efficacy. The lack of easy access to large representative well-characterised prospective resources is an important contributing factor to the current situation.

Methods

We here present the SUPRIM cohort, a national multicentre prospective longitudinal study of unselected PSC patients capturing the representative diversity of PSC phenotypes. We describe the 10-year effort of inclusion and follow-up, an intermediate analysis report including original results, and the associated research resource. All included patients gave written informed consent (recruitment: November 2011-April 2016).

Findings

Out of 512 included patients, 452 patients completed the five-year follow-up without endpoint outcomes. Liver transplantation was performed in 54 patients (10%) and hepatobiliary malignancy was diagnosed in 15 patients (3%). We draw a comprehensive landscape of the multidimensional clinical and biological heterogeneity of PSC illustrating the diversity of PSC phenotypes. Performances of available predictive scores are compared and perspectives on the continuation of the SUPRIM cohort are provided.

Interpretation

We envision the SUPRIM cohort as an open-access collaborative resource to accelerate the generation of new knowledge and independent validations of promising ones with the aim to uncover reliable diagnostics, prognostic tools, surrogate markers, and new treatment targets by 2040.

Funding

This work was supported by the Swedish Cancer Society, Stockholm County Council, and the Cancer Research Funds of Radiumhemmet.

A Novel Method for the Rat Model of Abdominal Aortic Aneurysm Induced by Retroperitoneal Implantation of an Osmotic Pump System With Lipopolysaccharide

BACKGROUND

Few methods can cocurrently mimic the pathological characteristics and nature history of human abdominal aortic aneurysms (AAAs), especially for the exist of the self-healing tendency of rodents. This study tested a novel method for the AAA rat model induced by retroperitoneal implantation of an osmotic pump system with lipopolysaccharide (LPS) based on the hypothesis that chronic inflammation of perivascular adipose tissue directly influenced the development and progression of AAAs.

METHODS

20 male Sprague-Dawley rats (10-month-old) fed with the Paigen diet were randomly divided into 4 groups: the blank group ×2, the sham group ×4, the empty capsule group ×4, and the LPS capsule group ×10. The LPS capsule group received implantations of the ALZET® osmotic pump capsule with LPS (3.6 μg/day) parallel to the abdominal aorta through a retroperitoneal approach. Two weeks later, 6 rats were randomly selected from the LPS capsule group to form the anti-inflammatory group and received implantations of another osmotic pump capsule with interleukin (IL)-10 (75 ng/day) through the same approach. The changes in abdominal aortic diameter were observed by ultrasound every 2 weeks, and samples were harvested for histopathologic and immunohistochemical analysis 6 weeks later.

RESULTS

Within the 6 weeks after modeling, the LPS capsule group showed sustained and significant aortic dilatation (P < 0.01), while the anti-inflammatory group showed a rapid and obvious shrinkage 2 weeks after the IL-10 osmotic pump capsule implantation (P < 0.01). The LPS capsule group presented excellent pathological mimicking of human AAAs and showed severe medial degeneration with the least elastic content among the 5 groups at the end of the sixth week (P < 0.05). Notably, the anti-inflammatory group showed perfect medial preservation with the most elastic content (P < 0.05) and the highest elastin/collagen ratio (P < 0.01) at the end of the study. Matrix metalloproteinases (MMP) 2 and 9 and toll-like receptor 2 showed strong expression in the LPS capsule group at the end of the sixth week, which was significantly higher than that in the blank group and sham group. Interestingly, the anti-inflammatory group showed a slightly higher MMP9 expression than the LPS capsule group though there was no statistical difference between them.

CONCLUSIONS

This novel method for the rat AAA model induced by retroperitoneal implantation of an osmotic pump capsule with LPS can concurrently mimic the histological characteristics and natural history of human AAAs. Further studies were needed to improve the osmotic pump system.

Reframing sepsis immunobiology for translation: towards informative subtyping and targeted immunomodulatory therapies

Sepsis is a common and deadly condition. Within the current model of sepsis immunobiology, the framing of dysregulated host immune responses into proinflammatory and immunosuppressive responses for the testing of novel treatments has not resulted in successful immunomodulatory therapies. Thus, the recent focus has been to parse observable heterogeneity into subtypes of sepsis to enable personalised immunomodulation. In this Personal View, we highlight that many fundamental immunological concepts such as resistance, disease tolerance, resilience, resolution, and repair are not incorporated into the current sepsis immunobiology model. The focus for addressing heterogeneity in sepsis should be broadened beyond subtyping to encompass the identification of deterministic molecular networks or dominant mechanisms. We explicitly reframe the dysregulated host immune responses in sepsis as altered homoeostasis with pathological disruption of immune-driven resistance, disease tolerance, resilience, and resolution mechanisms. Our proposal highlights opportunities to identify novel treatment targets and could enable successful immunomodulation in the future.

Discovery and characterization of noncanonical E2-conjugating enzymes

E2-conjugating enzymes (E2s) play a central role in the enzymatic cascade that leads to the attachment of ubiquitin to a substrate. This process, termed ubiquitylation, is required to maintain cellular homeostasis and affects almost all cellular process. By interacting with multiple E3 ligases, E2s dictate the ubiquitylation landscape within the cell. Since its discovery, ubiquitylation has been regarded as a posttranslational modification that specifically targets lysine side chains (canonical ubiquitylation). We used Matrix-Assisted Laser Desorption/Ionization-Time Of Flight Mass Spectrometry to identify and characterize a family of E2s that are instead able to conjugate ubiquitin to serine and/or threonine. We used structural modeling and prediction tools to identify the key activity determinants that these E2s use to interact with ubiquitin as well as their substrates. Our results unveil the missing E2s necessary for noncanonical ubiquitylation, underscoring the adaptability and versatility of ubiquitin modifications.

Ribosomal frameshifting at normal codon repeats recodes functional chimeric proteins in human

Ribosomal frameshifting refers to the process that ribosomes slip into +1 or -1 reading frame, thus produce chimeric trans-frame proteins. In viruses and bacteria, programmed ribosomal frameshifting can produce essential trans-frame proteins for viral replication or regulation of other biological processes. In humans, however, functional trans-frame protein derived from ribosomal frameshifting is scarcely documented. Combining multiple assays, we show that short codon repeats could act as cis-acting elements that stimulate ribosomal frameshifting in humans, abbreviated as CRFS hereafter. Using proteomic analyses, we identified many putative CRFS events from 32 normal human tissues supported by trans-frame peptides positioned at codon repeats. Finally, we show a CRFS-derived trans-frame protein (HDAC1-FS) functions by antagonizing the activities of HDAC1, thus affecting cell migration and apoptosis. These data suggest a novel type of translational recoding associated with codon repeats, which may expand the coding capacity of mRNA and diversify the regulation in human.

Translation variation across genetic backgrounds reveals a post-transcriptional buffering signature in yeast

Gene expression is known to vary among individuals, and this variability can impact the phenotypic diversity observed in natural populations. While the transcriptome and proteome have been extensively studied, little is known about the translation process itself. Here, we therefore performed ribosome and transcriptomic profiling on a genetically and ecologically diverse set of natural isolates of the Saccharomyces cerevisiae yeast. Interestingly, we found that the Euclidean distances between each profile and the expression fold changes in each pairwise isolate comparison were higher at the transcriptomic level. This observation clearly indicates that the transcriptional variation observed in the different isolates is buffered through a phenomenon known as post-transcriptional buffering at the translation level. Furthermore, this phenomenon seemed to have a specific signature by preferentially affecting essential genes as well as genes involved in complex-forming proteins, and low transcribed genes. We also explored the translation of the S. cerevisiae pangenome and found that the accessory genes related to introgression events displayed similar transcription and translation levels as the core genome. By contrast, genes acquired through horizontal gene transfer events tended to be less efficiently translated. Together, our results highlight both the extent and signature of the post-transcriptional buffering.

Organelle resolved proteomics uncovers PLA2R1 as a novel cell surface marker required for chordoma growth

Chordomas are clinically aggressive tumors with a high rate of disease progression despite maximal therapy. Given the limited therapeutic options available, there remains an urgent need for the development of novel therapies to improve clinical outcomes. Cell surface proteins are attractive therapeutic targets yet are challenging to profile with common methods. Four chordoma cell lines were analyzed by quantitative proteomics using a differential ultracentrifugation organellar fractionation approach. A subtractive proteomics strategy was applied to select proteins that are plasma membrane enriched. Systematic data integration prioritized PLA2R1 (secretory phospholipase A2 receptor-PLA2R1) as a chordoma-enriched surface protein. The expression profile of PLA2R1 was validated across chordoma cell lines, patient surgical tissue samples, and normal tissue lysates via immunoblotting. PLA2R1 expression was further validated by immunohistochemical analysis in a richly annotated cohort of 25-patient tissues. Immunohistochemistry analysis revealed that elevated expression of PLA2R1 is correlated with poor prognosis. Using siRNA- and CRISPR/Cas9-mediated knockdown of PLA2R1, we demonstrated significant inhibition of 2D, 3D and in vivo chordoma growth. PLA2R1 depletion resulted in cell cycle defects and metabolic rewiring via the MAPK signaling pathway, suggesting that PLA2R1 plays an essential role in chordoma biology. We have characterized the proteome of four chordoma cell lines and uncovered PLA2R1 as a novel cell-surface protein required for chordoma cell survival and association with patient outcome.