A Quantitative Proteome Map of the Human Body

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.

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.

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.

Multi-omic analysis of Esophageal Adenocarcinoma uncovers candidate therapeutic targets and cancer-selective post-transcriptional regulation

BACKGROUND

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.

METHODS

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 7 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.

CENTRAL FINDINGS

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 post-transcriptional 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 over-expressed at the protein level in EAC compared to adjacent normal tissues with an EAC-selective, post-transcriptional mechanism of regulation of protein abundance proposed.

CONCLUSIONS

By quantitative proteomic analysis we have identified GPA33 as an EAC-selective biomarker. Integrated analysis of proteome, transcriptome, and genome in EAC has revealed several genes with tumor-selective, post-transcriptional regulation of protein expression which may be an exploitable vulnerability.

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.

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

Population level variation and molecular mechanisms behind insulin secretion in response to carbohydrate, protein, and fat remain uncharacterized despite ramifications for personalized nutrition. Here, we define prototypical insulin secretion dynamics in response to the three macronutrients in islets from 140 cadaveric donors, including those diagnosed with type 2 diabetes. While islets from the majority of donors exhibited the expected relative response magnitudes, with glucose being highest, amino acid moderate, and fatty acid small, 9% of islets stimulated with amino acid and 8% of islets stimulated with fatty acids had larger responses compared with high glucose. We leveraged this insulin response heterogeneity and used transcriptomics and proteomics to identify molecular correlates of specific nutrient responsiveness, as well as those proteins and mRNAs altered in type 2 diabetes. We also examine nutrient-responsiveness in stem cell-derived islet clusters and observe that they have dysregulated fuel sensitivity, which is a hallmark of functionally immature cells. Our study now represents the first comparison of dynamic responses to nutrients and multi-omics analysis in human insulin secreting cells. Responses of different people's islets to carbohydrate, protein, and fat lay the groundwork for personalized nutrition.

ONE-SENTENCE SUMMARY

Deep phenotyping and multi-omics reveal individualized nutrient-specific insulin secretion propensity.

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

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. 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. 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. 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.

A transient protein folding response targets aggregation in the early phase of TDP-43-mediated neurodegeneration

Understanding the mechanisms that drive TDP-43 pathology is integral to combating amyotrophic lateral sclerosis (ALS), frontotemporal lobar degeneration (FTLD) and other neurodegenerative diseases. Here we generated a longitudinal quantitative proteomic map of the cortex from the cytoplasmic TDP-43 rNLS8 mouse model of ALS and FTLD, and developed a complementary open-access webtool, TDP-map ( https://shiny.rcc.uq.edu.au/TDP-map/ ). We identified distinct protein subsets enriched for diverse biological pathways with temporal alterations in protein abundance, including increases in protein folding factors prior to disease onset. This included increased levels of DnaJ homolog subfamily B member 5, DNAJB5, which also co-localized with TDP-43 pathology in diseased human motor cortex. DNAJB5 over-expression decreased TDP-43 aggregation in cell and cortical neuron cultures, and knockout of Dnajb5 exacerbated motor impairments caused by AAV-mediated cytoplasmic TDP-43 expression in mice. Together, these findings reveal molecular mechanisms at distinct stages of ALS and FTLD progression and suggest that protein folding factors could be protective in neurodegenerative diseases.

DNA damage remodels the MITF interactome to increase melanoma genomic instability

Since genome instability can drive cancer initiation and progression, cells have evolved highly effective and ubiquitous DNA damage response (DDR) programs. However, some cells (for example, in skin) are normally exposed to high levels of DNA-damaging agents. Whether such high-risk cells possess lineage-specific mechanisms that tailor DNA repair to the tissue remains largely unknown. Using melanoma as a model, we show here that the microphthalmia-associated transcription factor MITF, a lineage addition oncogene that coordinates many aspects of melanocyte and melanoma biology, plays a nontranscriptional role in shaping the DDR. On exposure to DNA-damaging agents, MITF is phosphorylated at S325, and its interactome is dramatically remodeled; most transcription cofactors dissociate, and instead MITF interacts with the MRE11-RAD50-NBS1 (MRN) complex. Consequently, cells with high MITF levels accumulate stalled replication forks and display defects in homologous recombination-mediated repair associated with impaired MRN recruitment to DNA damage. In agreement with this, high MITF levels are associated with increased single-nucleotide and copy number variant burdens in melanoma. Significantly, the SUMOylation-defective MITF-E318K melanoma predisposition mutation recapitulates the effects of DNA-PKcs-phosphorylated MITF. Our data suggest that a nontranscriptional function of a lineage-restricted transcription factor contributes to a tissue-specialized modulation of the DDR that can impact cancer initiation.

Matrisome and Immune Pathways Contribute to Extreme Vascular Outcomes in Williams-Beuren Syndrome

BACKGROUND

Supravalvar aortic stenosis (SVAS) is a characteristic feature of Williams-Beuren syndrome (WBS). Its severity varies: ~20% of people with Williams-Beuren syndrome have SVAS requiring surgical intervention, whereas ~35% have no appreciable SVAS. The remaining individuals have SVAS of intermediate severity. Little is known about genetic modifiers that contribute to this variability.

METHODS AND RESULTS

We performed genome sequencing on 473 individuals with Williams-Beuren syndrome and developed strategies for modifier discovery in this rare disease population. Approaches include extreme phenotyping and nonsynonymous variant prioritization, followed by gene set enrichment and pathway-level association tests. We next used GTEx v8 and proteomic data sets to verify expression of candidate modifiers in relevant tissues. Finally, we evaluated overlap between the genes/pathways identified here and those ascertained through larger aortic disease/trait genome-wide association studies. We show that SVAS severity in Williams-Beuren syndrome is associated with increased frequency of common and rarer variants in matrisome and immune pathways. Two implicated matrisome genes (ACAN and LTBP4) were uniquely expressed in the aorta. Many genes in the identified pathways were previously reported in genome-wide association studies for aneurysm, bicuspid aortic valve, or aortic size.

CONCLUSIONS

Smaller sample sizes in rare disease studies necessitate new approaches to detect modifiers. Our strategies identified variation in matrisome and immune pathways that are associated with SVAS severity. These findings suggest that, like other aortopathies, SVAS may be influenced by the balance of synthesis and degradation of matrisome proteins. Leveraging multiomic data and results from larger aorta-focused genome-wide association studies may accelerate modifier discovery for rare aortopathies like SVAS.

Capture of the Mouse Organ Membrane Proteome Specificity in Peptidisc Libraries

Membrane proteins, particularly those on the cell surface, play pivotal roles in diverse physiological processes, and their dysfunction is linked to a broad spectrum of diseases. Despite being crucial biomarkers and therapeutic drug targets, their low abundance and hydrophobic nature pose challenges in isolation and quantification, especially when extracted from tissues and organs. To overcome these hurdles, we developed the membrane-mimicking peptidisc, enabling the isolation of the membrane proteome in a water-soluble library conducive to swift identification through liquid chromatography with tandem mass spectrometry. This study applies the method across five mice organs, capturing between 200 and 450 plasma membrane proteins in each case. More than just membrane protein identification, the peptidisc is used to estimate the relative abundance across organs, linking cell-surface protein molecular functions to organ biological roles, thereby contributing to the ongoing discourse on organ specificity. This contribution holds substantial potential for unveiling new avenues in the exploration of biomarkers and downstream applications involving knowledge of the organ cell-surface proteome.

Circadian protein expression patterns in healthy young adults

OBJECTIVES

To explore how the blood plasma proteome fluctuates across the 24-hour day and identify a subset of proteins that show endogenous circadian rhythmicity.

METHODS

Plasma samples from 17 healthy adults were collected hourly under controlled conditions designed to unmask endogenous circadian rhythmicity; in a subset of 8 participants, we also collected samples across a day on a typical sleep-wake schedule. A total of 6916 proteins were analyzed from each sample using the SomaScan aptamer-based multiplexed platform. We used differential rhythmicity analysis based on a cosinor model with mixed effects to identify a subset of proteins that showed circadian rhythmicity in their abundance.

RESULTS

One thousand and sixty-three (15%) proteins exhibited significant daily rhythmicity. Of those, 431 (6.2%) proteins displayed consistent endogenous circadian rhythms on both a sleep-wake schedule and under controlled conditions: it included both known and novel proteins. When models were fitted with two harmonics, an additional 259 (3.7%) proteins exhibited significant endogenous circadian rhythmicity, indicating that some rhythmic proteins cannot be solely captured by a simple sinusoidal model. Overall, we found that the largest number of proteins had their peak levels in the late afternoon/evening, with another smaller group peaking in the early morning.

CONCLUSIONS

This study reveals that hundreds of plasma proteins exhibit endogenous circadian rhythmicity in humans. Future analyses will likely reveal novel physiological pathways regulated by circadian clocks and pave the way for improved diagnosis and treatment for patients with circadian disorders and other pathologies. It will also advance efforts to include knowledge about time-of-day, thereby incorporating circadian medicine into personalized medicine.

Multiomics Data Reveal the Important Role of ANXA2R in T Cell-mediated Rejection After Renal Transplantation

BACKGROUND

T cell-mediated rejection (TCMR) is a severe issue after renal transplantation, but research on its T cell-receptor (TCR) repertoire is lacking. This study intended to elucidate the TCR repertoire landscape in TCMR and hence identify novel potential targets.

METHODS

A total of 12 multiomics data sets were collected. The TRUST4 algorithm was used to construct and analyze the TCR repertoire in renal allografts with TCMR and stable renal function. Then, novel TCR-related key genes were identified through various criteria and literature research. In bulk transcriptome, cell line, single-cell transcriptome data sets, multiple immune cell infiltration algorithms, and gene set enrichment analysis were used to analyze potential mechanisms of the identified key gene. Twenty-three pathological sections were collected for immunofluorescence staining in the clinical cohort. Finally, the diagnostic and prognostic values of ANXA2R were evaluated in multiple renal transplant data sets.

RESULTS

Allografts with TCMR showed significantly increased clonotype and specific clonal expansion. ANXA2R was found to be a novel key gene for TCMR and showed strong positive connections with the TCR complex and lymphocyte cells, especially CD8 + T cells. Immunofluorescence staining confirmed the existence of ANXA2R + CD8 + T cells, with their percentage significantly elevated in TCMR compared with stable renal function. Finally, both mRNA and protein levels of ANXA2R showed promising diagnostic and prognostic value for renal transplant recipients.

CONCLUSIONS

ANXA2R , identified as a novel TCR-related gene, had critical roles in clinicopathology, diagnosis, and prognosis in renal transplantation, which offered promising potential therapeutic targets.

Emerging Roles of Cullin-RING Ubiquitin Ligases in Cardiac Development

Heart development is a spatiotemporally regulated process that extends from the embryonic phase to postnatal stages. Disruption of this highly orchestrated process can lead to congenital heart disease or predispose the heart to cardiomyopathy or heart failure. Consequently, gaining an in-depth understanding of the molecular mechanisms governing cardiac development holds considerable promise for the development of innovative therapies for various cardiac ailments. While significant progress in uncovering novel transcriptional and epigenetic regulators of heart development has been made, the exploration of post-translational mechanisms that influence this process has lagged. Culling-RING E3 ubiquitin ligases (CRLs), the largest family of ubiquitin ligases, control the ubiquitination and degradation of ~20% of intracellular proteins. Emerging evidence has uncovered the critical roles of CRLs in the regulation of a wide range of cellular, physiological, and pathological processes. In this review, we summarize current findings on the versatile regulation of cardiac morphogenesis and maturation by CRLs and present future perspectives to advance our comprehensive understanding of how CRLs govern cardiac developmental processes.

Remodeling of the human skeletal muscle proteome found after long-term endurance training but not after strength training

Exercise training has tremendous systemic tissue-specific health benefits, but the molecular adaptations to long-term exercise training are not completely understood. We investigated the skeletal muscle proteome of highly endurance-trained, strength-trained, and untrained individuals and performed exercise- and sex-specific analyses. Of the 6,000+ proteins identified, >650 were differentially expressed in endurance-trained individuals compared with controls. Strikingly, 92% of the shared proteins with higher expression in both the male and female endurance groups were known mitochondrial. In contrast to the findings in endurance-trained individuals, minimal differences were found in strength-trained individuals and between females and males. Lastly, a co-expression network and comparative literature analysis revealed key proteins and pathways related to the health benefits of exercise, which were primarily related to differences in mitochondrial proteins. This network is available as an interactive database resource where investigators can correlate clinical data with global gene and protein expression data for hypothesis generation.

Transcriptional profile of ribosome-associated quality control components and their associated phenotypes in mammalian cells

During protein synthesis, organisms detect translation defects that induce ribosome stalling and result in protein aggregation. The Ribosome-associated Quality Control (RQC) complex, comprising TCF25, LTN1, and NEMF, is responsible for identifying incomplete protein products from unproductive translation events, targeting them for degradation. Although RQC disruption causes adverse effects on vertebrate neurons, data regarding mRNA/protein expression and regulation across tissues are lacking. Employing high-throughput methods, we analyzed public datasets to explore RQC gene expression and phenotypes. Our findings revealed widespread expression of RQC components in human tissues; however, silencing of RQC yielded only mild negative effects on cell growth. Notably, TCF25 exhibited elevated mRNA levels that were not reflected in the protein content. We experimentally demonstrated that this disparity arose from post-translational protein degradation by the proteasome. Additionally, we observed that cellular aging marginally influenced RQC expression, leading to reduced mRNA levels in specific tissues. Our results suggest the necessity of RQC expression in all mammalian tissues. Nevertheless, when RQC falters, alternative mechanisms seem to compensate, ensuring cell survival under nonstress conditions.

How Can Proteomics Help to Elucidate the Pathophysiological Crosstalk in Muscular Dystrophy and Associated Multi-System Dysfunction?

This perspective article is concerned with the question of how proteomics, which is a core technique of systems biology that is deeply embedded in the multi-omics field of modern bioresearch, can help us better understand the molecular pathogenesis of complex diseases. As an illustrative example of a monogenetic disorder that primarily affects the neuromuscular system but is characterized by a plethora of multi-system pathophysiological alterations, the muscle-wasting disease Duchenne muscular dystrophy was examined. Recent achievements in the field of dystrophinopathy research are described with special reference to the proteome-wide complexity of neuromuscular changes and body-wide alterations/adaptations. Based on a description of the current applications of top-down versus bottom-up proteomic approaches and their technical challenges, future systems biological approaches are outlined. The envisaged holistic and integromic bioanalysis would encompass the integration of diverse omics-type studies including inter- and intra-proteomics as the core disciplines for systematic protein evaluations, with sophisticated biomolecular analyses, including physiology, molecular biology, biochemistry and histochemistry. Integrated proteomic findings promise to be instrumental in improving our detailed knowledge of pathogenic mechanisms and multi-system dysfunction, widening the available biomarker signature of dystrophinopathy for improved diagnostic/prognostic procedures, and advancing the identification of novel therapeutic targets to treat Duchenne muscular dystrophy.

Leveraging inter-individual transcriptional correlation structure to infer discrete signaling mechanisms across metabolic tissues

Inter-organ communication is a vital process to maintain physiologic homeostasis, and its dysregulation contributes to many human diseases. Given that circulating bioactive factors are stable in serum, occur naturally, and are easily assayed from blood, they present obvious focal molecules for therapeutic intervention and biomarker development. Recently, studies have shown that secreted proteins mediating inter-tissue signaling could be identified by 'brute force' surveys of all genes within RNA-sequencing measures across tissues within a population. Expanding on this intuition, we reasoned that parallel strategies could be used to understand how individual genes mediate signaling across metabolic tissues through correlative analyses of gene variation between individuals. Thus, comparison of quantitative levels of gene expression relationships between organs in a population could aid in understanding cross-organ signaling. Here, we surveyed gene-gene correlation structure across 18 metabolic tissues in 310 human individuals and 7 tissues in 103 diverse strains of mice fed a normal chow or high-fat/high-sucrose (HFHS) diet. Variation of genes such as FGF21, ADIPOQ, GCG, and IL6 showed enrichments which recapitulate experimental observations. Further, similar analyses were applied to explore both within-tissue signaling mechanisms (liver PCSK9) and genes encoding enzymes producing metabolites (adipose PNPLA2), where inter-individual correlation structure aligned with known roles for these critical metabolic pathways. Examination of sex hormone receptor correlations in mice highlighted the difference of tissue-specific variation in relationships with metabolic traits. We refer to this resource as gene-derived correlations across tissues (GD-CAT) where all tools and data are built into a web portal enabling users to perform these analyses without a single line of code (gdcat.org). This resource enables querying of any gene in any tissue to find correlated patterns of genes, cell types, pathways, and network architectures across metabolic organs.

Protein interaction networks in the vasculature prioritize genes and pathways underlying coronary artery disease

Population-based association studies have identified many genetic risk loci for coronary artery disease (CAD), but it is often unclear how genes within these loci are linked to CAD. Here, we perform interaction proteomics for 11 CAD-risk genes to map their protein-protein interactions (PPIs) in human vascular cells and elucidate their roles in CAD. The resulting PPI networks contain interactions that are outside of known biology in the vasculature and are enriched for genes involved in immunity-related and arterial-wall-specific mechanisms. Several PPI networks derived from smooth muscle cells are significantly enriched for genetic variants associated with CAD and related vascular phenotypes. Furthermore, the networks identify 61 genes that are found in genetic loci associated with risk of CAD, prioritizing them as the causal candidates within these loci. These findings indicate that the PPI networks we have generated are a rich resource for guiding future research into the molecular pathogenesis of CAD.

Levels of complement factor H-related 4 protein do not influence susceptibility to age-related macular degeneration or its course of progression

Dysregulation of the alternative pathway (AP) of the complement system is a significant contributor to age-related macular degeneration (AMD), a primary cause of irreversible vision loss worldwide. Here, we assess the contribution of the liver-produced complement factor H-related 4 protein (FHR-4) to AMD initiation and course of progression. We show that FHR-4 variation in plasma and at the primary location of AMD-associated pathology, the retinal pigment epithelium/Bruch's membrane/choroid interface, is entirely explained by three independent quantitative trait loci (QTL). Using two distinct cohorts composed of a combined 14,965 controls and 20,741 cases, we ascertain that independent QTLs for FHR-4 are distinct from variants causally associated with AMD, and that FHR-4 variation is not independently associated with disease. Additionally, FHR-4 does not appear to influence AMD progression course among patients with disease driven predominantly by AP dysregulation. Modulation of FHR-4 is therefore unlikely to be an effective therapeutic strategy for AMD.

TTD: Therapeutic Target Database describing target druggability information

Target discovery is one of the essential steps in modern drug development, and the identification of promising targets is fundamental for developing first-in-class drug. A variety of methods have emerged for target assessment based on druggability analysis, which refers to the likelihood of a target being effectively modulated by drug-like agents. In the therapeutic target database (TTD), nine categories of established druggability characteristics were thus collected for 426 successful, 1014 clinical trial, 212 preclinical/patented, and 1479 literature-reported targets via systematic review. These characteristic categories were classified into three distinct perspectives: molecular interaction/regulation, human system profile and cell-based expression variation. With the rapid progression of technology and concerted effort in drug discovery, TTD and other databases were highly expected to facilitate the explorations of druggability characteristics for the discovery and validation of innovative drug target. TTD is now freely accessible at: https://idrblab.org/ttd/.

TheMarker: a comprehensive database of therapeutic biomarkers

Distinct from the traditional diagnostic/prognostic biomarker (adopted as the indicator of disease state/process), the therapeutic biomarker (ThMAR) has emerged to be very crucial in the clinical development and clinical practice of all therapies. There are five types of ThMAR that have been found to play indispensable roles in various stages of drug discovery, such as: Pharmacodynamic Biomarker essential for guaranteeing the pharmacological effects of a therapy, Safety Biomarker critical for assessing the extent or likelihood of therapy-induced toxicity, Monitoring Biomarker indispensable for guiding clinical management by serially measuring patients' status, Predictive Biomarker crucial for maximizing the clinical outcome of a therapy for specific individuals, and Surrogate Endpoint fundamental for accelerating the approval of a therapy. However, these data of ThMARs has not been comprehensively described by any of the existing databases. Herein, a database, named 'TheMarker', was therefore constructed to (a) systematically offer all five types of ThMAR used at different stages of drug development, (b) comprehensively describe ThMAR information for the largest number of drugs among available databases, (c) extensively cover the widest disease classes by not just focusing on anticancer therapies. These data in TheMarker are expected to have great implication and significant impact on drug discovery and clinical practice, and it is freely accessible without any login requirement at: https://idrblab.org/themarker.

Strategies for translating proteomics discoveries into drug discovery for dementia

Tauopathies, diseases characterized by neuropathological aggregates of tau including Alzheimer's disease and subtypes of frontotemporal dementia, make up the vast majority of dementia cases. Although there have been recent developments in tauopathy biomarkers and disease-modifying treatments, ongoing progress is required to ensure these are effective, economical, and accessible for the globally ageing population. As such, continued identification of new potential drug targets and biomarkers is critical. "Big data" studies, such as proteomics, can generate information on thousands of possible new targets for dementia diagnostics and therapeutics, but currently remain underutilized due to the lack of a clear process by which targets are selected for future drug development. In this review, we discuss current tauopathy biomarkers and therapeutics, and highlight areas in need of improvement, particularly when addressing the needs of frail, comorbid and cognitively impaired populations. We highlight biomarkers which have been developed from proteomic data, and outline possible future directions in this field. We propose new criteria by which potential targets in proteomics studies can be objectively ranked as favorable for drug development, and demonstrate its application to our group's recent tau interactome dataset as an example.

Mass spectrometry-based proteomics approaches to interrogate skeletal muscle adaptations to exercise

Acute exercise and chronic exercise training elicit beneficial whole-body changes in physiology that ultimately depend on profound alterations to the dynamics of tissue-specific proteins. Since the work accomplished during exercise owes predominantly to skeletal muscle, it has received the majority of interest from exercise scientists that attempt to unravel adaptive mechanisms accounting for salutary metabolic effects and performance improvements that arise from training. Contemporary scientists are also beginning to use mass spectrometry-based proteomics, which is emerging as a powerful approach to interrogate the muscle protein signature in a more comprehensive manner. Collectively, these technologies facilitate the analysis of skeletal muscle protein dynamics from several viewpoints, including changes to intracellular proteins (expression proteomics), secreted proteins (secretomics), post-translational modifications as well as fiber-, cell-, and organelle-specific changes. This review aims to highlight recent literature that has leveraged new workflows and advances in mass spectrometry-based proteomics to further our understanding of training-related changes in skeletal muscle. We call attention to untapped areas in skeletal muscle proteomics research relating to exercise training and metabolism, as well as basic points of contention when applying mass spectrometry-based analyses, particularly in the study of human biology. We further encourage researchers to couple the hypothesis-generating and descriptive nature of omics data with functional analyses that propel our understanding of the complex adaptive responses in skeletal muscle that occur with acute and chronic exercise.

iProPhos: A Web-Based Interactive Platform for Integrated Proteome and Phosphoproteome Analysis

Large-scale omics studies have generated a wealth of mass spectrometry-based proteomics data, which provide additional insights into disease biology spanning genomic boundaries. However, there is a notable lack of web-based analysis and visualization tools that facilitate the reutilization of these data. Given this challenge, we present iProPhos, a user-friendly web server to deliver interactive and customizable functionalities. iProPhos incorporates a large number of samples, including 1444 tumor samples and 746 normal samples across 12 cancer types, sourced from the Clinical Proteomic Tumor Analysis Consortium. Additionally, users can also upload their own proteomics/phosphoproteomics data for analysis and visualization. In iProPhos, users can perform profiling plotting and differential expression, patient survival, clinical feature-related, and correlation analyses, including protein-protein, mRNA-protein, and kinase-substrate correlations. Furthermore, functional enrichment, protein-protein interaction network, and kinase-substrate enrichment analyses are accessible. iProPhos displays the analytical results in interactive figures and tables with various selectable parameters. It is freely accessible at http://longlab-zju.cn/iProPhos without login requirement. We present two case studies to demonstrate that iProPhos can identify potential drug targets and upstream kinases contributing to site-specific phosphorylation. Ultimately, iProPhos allows end-users to leverage the value of big data in cancer proteomics more effectively and accelerates the discovery of novel therapeutic targets.

Systemic proteome phenotypes reveal defective metabolic flexibility in Mecp2 mutants

Genes mutated in monogenic neurodevelopmental disorders are broadly expressed. This observation supports the concept that monogenic neurodevelopmental disorders are systemic diseases that profoundly impact neurodevelopment. We tested the systemic disease model focusing on Rett syndrome, which is caused by mutations in MECP2. Transcriptomes and proteomes of organs and brain regions from Mecp2-null mice as well as diverse MECP2-null male and female human cells were assessed. Widespread changes in the steady-state transcriptome and proteome were identified in brain regions and organs of presymptomatic Mecp2-null male mice as well as mutant human cell lines. The extent of these transcriptome and proteome modifications was similar in cortex, liver, kidney, and skeletal muscle and more pronounced than in the hippocampus and striatum. In particular, Mecp2- and MECP2-sensitive proteomes were enriched in synaptic and metabolic annotated gene products, the latter encompassing lipid metabolism and mitochondrial pathways. MECP2 mutations altered pyruvate-dependent mitochondrial respiration while maintaining the capacity to use glutamine as a mitochondrial carbon source. We conclude that mutations in Mecp2/MECP2 perturb lipid and mitochondrial metabolism systemically limiting cellular flexibility to utilize mitochondrial fuels.

Signaling plasticity in the integrated stress response

The Integrated Stress Response (ISR) is an essential homeostatic signaling network that controls the cell's biosynthetic capacity. Four ISR sensor kinases detect multiple stressors and relay this information to downstream effectors by phosphorylating a common node: the alpha subunit of the eukaryotic initiation factor eIF2. As a result, general protein synthesis is repressed while select transcripts are preferentially translated, thus remodeling the proteome and transcriptome. Mounting evidence supports a view of the ISR as a dynamic signaling network with multiple modulators and feedback regulatory features that vary across cell and tissue types. Here, we discuss updated views on ISR sensor kinase mechanisms, how the subcellular localization of ISR components impacts signaling, and highlight ISR signaling differences across cells and tissues. Finally, we consider crosstalk between the ISR and other signaling pathways as a determinant of cell health.

D2H2: diabetes data and hypothesis hub

Motivation

There is a rapid growth in the production of omics datasets collected by the diabetes research community. However, such published data are underutilized for knowledge discovery. To make bioinformatics tools and published omics datasets from the diabetes field more accessible to biomedical researchers, we developed the Diabetes Data and Hypothesis Hub (D2H2).

Results

D2H2 contains hundreds of high-quality curated transcriptomics datasets relevant to diabetes, accessible via a user-friendly web-based portal. The collected and processed datasets are curated from the Gene Expression Omnibus (GEO). Each curated study has a dedicated page that provides data visualization, differential gene expression analysis, and single-gene queries. To enable the investigation of these curated datasets and to provide easy access to bioinformatics tools that serve gene and gene set-related knowledge, we developed the D2H2 chatbot. Utilizing GPT, we prompt users to enter free text about their data analysis needs. Parsing the user prompt, together with specifying information about all D2H2 available tools and workflows, we answer user queries by invoking the most relevant tools via the tools' API. D2H2 also has a hypotheses generation module where gene sets are randomly selected from the bulk RNA-seq precomputed signatures. We then find highly overlapping gene sets extracted from publications listed in PubMed Central with abstract dissimilarity. With the help of GPT, we speculate about a possible explanation of the high overlap between the gene sets. Overall, D2H2 is a platform that provides a suite of bioinformatics tools and curated transcriptomics datasets for hypothesis generation.

Availability and implementation

D2H2 is available at: https://d2h2.maayanlab.cloud/ and the source code is available from GitHub at https://github.com/MaayanLab/D2H2-site under the CC BY-NC 4.0 license.

Pan-cancer analysis of antibody-drug conjugate targets and putative predictors of treatment response

BACKGROUND

Antibody-drug conjugates (ADCs) are a rapidly expanding class of compounds in oncology. Our goal was to assess the expression of ADC targets and potential downstream determining factors of activity across pan-cancer and normal tissues.

MATERIALS AND METHODS

ADCs in clinical trials (n = 121) were identified through ClinicalTrials.gov, corresponding to 54 targets. Genes potentially implicated in treatment response were identified in the literature. Gene expression from The Cancer Genome Atlas (9000+ cancers of 31 cancer types), the Genotype-Tissue Expression database (n = 19,000 samples from 31 normal tissue types), and the TNMplot.com (n = 12,494 unmatched primary and metastatic samples) were used in this analysis. To compare relative expression across and within tumour types we used pooled normal tissues as reference.

RESULTS

For most ADC targets, mRNA levels correlated with protein expression. Pan-cancer target expression distributions identified appealing cancer types for each ADC development. Co-expression of multiple targets was common and suggested opportunities for ADC combinations. Expression levels of genes potentially implicated in ADC response downstream of the target might provide additional information (e.g. TOP1 was highly expressed in many tumour types, including breast and lung cancers). Metastatic compared to primary tissues overexpressed some ADCs targets. Single sample "targetgram" plots were generated to visualise the expression of potentially competing ADC targets and resistance/sensitivity markers highlighting high inter-patient heterogeneity. Off-cancer target expression only partially explains adverse events, while expression of determinants of payload activity explained more of the observed toxicities.

CONCLUSION

Our findings draw attention to new therapeutic opportunities for ADCs that can be tested in the clinic and our web platform (https://tnmplot.com) can assist in prioritising upcoming ADC targets for clinical development.

A proteomic meta-analysis refinement of plasma extracellular vesicles

Extracellular vesicles play major roles in cell-to-cell communication and are excellent biomarker candidates. However, studying plasma extracellular vesicles is challenging due to contaminants. Here, we performed a proteomics meta-analysis of public data to refine the plasma EV composition by separating EV proteins and contaminants into different clusters. We obtained two clusters with a total of 1717 proteins that were depleted of known contaminants and enriched in EV markers with independently validated 71% true-positive. These clusters had 133 clusters of differentiation (CD) antigens and were enriched with proteins from cell-to-cell communication and signaling. We compared our data with the proteins deposited in PeptideAtlas, making our refined EV protein list a resource for mechanistic and biomarker studies. As a use case example for this resource, we validated the type 1 diabetes biomarker proplatelet basic protein in EVs and showed that it regulates apoptosis of β cells and macrophages, two key players in the disease development. Our approach provides a refinement of the EV composition and a resource for the scientific community.

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.

Potential mechanism of the AgNCs-hydrogel in promoting the regeneration of diabetic infectious wounds

Diabetic infectious wound treatment is challenging due to insistent wound infections. To treat such complicated pathological diabetic infectious wounds, multifunctional materials need to be developed, and their mechanisms need to be understood. Here, we developed a material termed AgNCs-hydrogel, which is a multifunctional DNA hydrogel used as dressings by integrating it with antibacterial silver nanoclusters. The AgNCs-hydrogel was applied to promote the regeneration of diabetic infectious wounds in mice because it exhibited superior antibacterial activity and effective ROS-scavenging properties. Based on skin proteomics, we explored the potential mechanism of the AgNCs-hydrogel in treating mouse skin wounds. We found that the AgNCs-hydrogel can regulate some key proteins located primarily in the extracellular exosomes, involved in the negative regulation of the apoptotic process, and perform ATP binding to accelerate diabetic infected wound closure. Therefore, this study provided a multifunctional AgNCs-hydrogel and revealed its potential mechanism in promoting the regeneration of diabetic infectious wounds.

Trade-offs inside the black box of neoantigen prediction

Success of precision neoantigen-based immunotherapies hinges on the selection of immunogenic neoantigens, yet currently neither large-scale datasets nor streamlined methods are available to achieve this goal. Müller et al. present a large experimental dataset resource along with machine learning-based models to classify immunogenic neoantigens.

Discovery adductomics provides a comprehensive portrait of tissue-, age- and sex-specific DNA modifications in rodents and humans

DNA damage causes genomic instability underlying many diseases, with traditional analytical approaches providing minimal insight into the spectrum of DNA lesions in vivo. Here we used untargeted chromatography-coupled tandem mass spectrometry-based adductomics (LC-MS/MS) to begin to define the landscape of DNA modifications in rat and human tissues. A basis set of 114 putative DNA adducts was identified in heart, liver, brain, and kidney in 1-26-month-old rats and 111 in human heart and brain by 'stepped MRM' LC-MS/MS. Subsequent targeted analysis of these species revealed species-, tissue-, age- and sex-biases. Structural characterization of 10 selected adductomic signals as known DNA modifications validated the method and established confidence in the DNA origins of the signals. Along with strong tissue biases, we observed significant age-dependence for 36 adducts, including N2-CMdG, 5-HMdC and 8-Oxo-dG in rats and 1,N6-ϵdA in human heart, as well as sex biases for 67 adducts in rat tissues. These results demonstrate the potential of adductomics for discovering the true spectrum of disease-driving DNA adducts. Our dataset of 114 putative adducts serves as a resource for characterizing dozens of new forms of DNA damage, defining mechanisms of their formation and repair, and developing them as biomarkers of aging and disease.