Comparative analysis of proteome and transcriptome variation in mouse

Cellular translational enhancer elements that recruit eukaryotic initiation factor 3

Translation initiation is a highly regulated process that broadly affects eukaryotic gene expression. Eukaryotic initiation factor 3 (eIF3) is a central player in canonical and alternative pathways for ribosome recruitment. Here, we have investigated how direct binding of eIF3 contributes to the large and regulated differences in protein output conferred by different 5'-untranslated regions (5' UTRs) of cellular mRNAs. Using an unbiased high-throughput approach to determine the affinity of budding yeast eIF3 for native 5' UTRs from 4252 genes, we demonstrate that eIF3 binds specifically to a subset of 5' UTRs that contain a short unstructured binding motif, AMAYAA. eIF3-binding mRNAs have higher ribosome density in growing cells and are preferentially translated under certain stress conditions, supporting the functional relevance of this interaction. Our results reveal a new class of translational enhancers and suggest a mechanism by which changes in core initiation factor activity enact mRNA-specific translation programs.

The role and the determination of the LuxI protein binding targets in the formation of biogenic amines in Hafnia alvei H4

Hafnia alvei is a spoilage microorganism that possesses the LuxI/LuxR-type quorum sensing (QS) system. Biogenic amines (BAs) are important in food spoilage and safety, yet the role of QS in BA formation remains poorly understood. This study investigated the ability of H. alvei H4 to produce BAs in fish flesh and decarboxylase culture media. The findings showed that H. alvei H4 produced substantial amounts of putrescine and cadaverine in turbot flesh, with its enhanced amine-producing capacity potentially leading to the eventual deterioration of the fish. Furthermore, the deletion of the QS element-AHL synthase gene luxI-affected the concentrations of both BAs. Based on these observations, the present study conducted multifaceted experiments, including phenotypic assessments and analyses of gene expression, to explore the role of luxI and to identify its specific binding targets. The results indicated that putrescine formation in H. alvei H4 primarily occurred via the arginine deiminase (ADI) pathway, with luxI playing a positive role in the conversion of arginine to ornithine and subsequently to putrescine. The reduction in putrescine content observed in a luxI mutant (ΔluxI) was attributed to the direct binding of the LuxI protein to the promoters of the argF and speC genes, which code for ornithine carbamoyltransferase and ornithine decarboxylase, respectively. The findings of this study provided the basis to understand the influence of QS on BA production in H. alvei, by specifically demonstrating the involvement of the luxI gene on putrescine and cadaverine production.

ZNF143 is a transcriptional regulator of nuclear-encoded mitochondrial genes that acts independently of looping and CTCF

Gene expression is orchestrated by transcription factors, which function within the context of a three-dimensional genome. Zinc-finger protein 143 (ZNF143/ZFP143) is a transcription factor that has been implicated in both gene activation and chromatin looping. To study the direct consequences of ZNF143/ZFP143 loss, we generated a ZNF143/ZFP143 depletion system in mouse embryonic stem cells. Our results show that ZNF143/ZFP143 degradation has no effect on chromatin looping. Systematic analysis of ZNF143/ZFP143 occupancy data revealed that a commonly used antibody cross-reacts with CTCF, leading to its incorrect association with chromatin loops. Nevertheless, ZNF143/ZFP143 specifically activates nuclear-encoded mitochondrial genes, and its loss leads to severe mitochondrial dysfunction. Using an in vitro embryo model, we find that ZNF143/ZFP143 is an essential regulator of organismal development. Our results establish ZNF143/ZFP143 as a conserved transcriptional regulator of cell proliferation and differentiation by safeguarding mitochondrial activity.

Lessons learned from 20 years of preclinical testing in pediatric cancers

Programs for preclinical testing of targeted cancer agents in murine models of childhood cancers have been supported by the National Cancer Institute (NCI) since 2004. These programs were established to work collaboratively with industry partners to address the paucity of targeted agents for pediatric cancers compared with the large number of agents developed and approved for malignancies primarily affecting adults. The distinctive biology of pediatric cancers and the relatively small numbers of pediatric cancer patients are major challenges for pediatric oncology drug development. These factors are exacerbated by the division of cancers into multiple subtypes that are further sub-classified by their genomic properties. The imbalance between the large number of candidate agents and small patient populations requires careful prioritization of agents developed for adult cancers for clinical evaluation in children with cancer. The NCI-supported preclinical pediatric programs have published positive and negative results of efficacy testing for over 100 agents to aid the pediatric research community in identifying the most promising candidates to move forward for clinical testing in pediatric oncology. Here, we review and summarize lessons learned from two decades of experience with the design and execution of preclinical trials of antineoplastic agents in murine models of childhood cancers.

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.

Single-cell chemoproteomics identifies metastatic activity signatures in breast cancer

Protein activity state, rather than protein or mRNA abundance, is a biologically regulated and relevant input to many processes in signaling, differentiation, development, and diseases such as cancer. While there are numerous methods to detect and quantify mRNA and protein abundance in biological samples, there are no general approaches to detect and quantify endogenous protein activity with single-cell resolution. Here, we report the development of a chemoproteomic platform, single-cell activity-dependent proximity ligation, which uses automated, microfluidics-based single-cell capture and nanoliter volume manipulations to convert the interactions of family-wide chemical activity probes with native protein targets into multiplexed, amplifiable oligonucleotide barcodes. We demonstrate accurate, reproducible, and multiplexed quantitation of a six-enzyme (Ag-6) panel with known ties to cancer cell aggressiveness directly in single cells. We further identified increased Ag-6 enzyme activity across breast cancer cell lines of increasing metastatic potential, as well as in primary patient-derived tumor cells and organoids from patients with breast cancer.

The Translatome Map: RNC-Seq vs. Ribo-Seq for Profiling of HBE, A549, and MCF-7 Cell Lines

Gene expression is a tightly regulated process that involves multiple layers of control, including transcriptional, post-transcriptional, and translational regulation. To gain a comprehensive understanding of gene expression dynamics and its functional implications, it is crucial to compare translatomic, transcriptomic, and proteomic data. The two most common analysis methods, Ribo-seq and RNC-Seq, were used to analyze the translatome of the same sample, whose datasets were downloaded from the TranslatomeDB database. The resulting translatome maps obtained for three cell lines (HBE, A549, and MCF-7) using these two methods were comparatively analyzed. The two methods of translatome analysis were shown to provide comparable results and can be used interchangeably. The obtained mRNA translation patterns were annotated in the transcriptome and proteome context for the same sample, which may become the basis for the reconstruction of the molecular mechanisms of pathological process development in the future.

Proteomic and Transcriptomic Profiling Revealed Vital Molecular Events in the Transition from Goat Colostrum to Mature Milk

As an important nutrient source in large areas of the world, goat milk is favored by more and more consumers; however, the composition, nutritional value, and regulation mechanism of goat milk are not fully characterized. Mammary gland development is as important as detailed annotation of protein composition to address the physiological and nutritional values of goat milk. In the present study, 4353 colostrum and mature goat milk proteins were identified. The abundance of 118 proteins was significantly different between colostrum and mature milk proteins. Our results indicate that the milk protein changes were associated with a network of mammary gene expression changes; importantly, the prime factors include enhanced mammary growth/development, decreased protein translation, attenuated protein folding, and lower lip/carbohydrate metabolism. The present study provides insights into the changes in mammary metabolisms during the transition from colostrum to mature milk, which can help deeply explore the difference and regulation mechanism of active milk protein in colostrum and mature milk and provide references for the identification and functional study of bioactive milk proteins in colostrum.

Hippocampal dentate granule cells in temporal lobe epilepsy: A morphometry and transcriptomic study

The dentate gyrus (DG) plays a critical role in hippocampal circuitry, providing a "gate-like" function to the downstream cornu ammonis (CA) sectors. Despite this critical role, pathologies in DG are less commonly described than those in the CA sectors in the diagnosis of mesial temporal lobe epilepsy (mTLE). To elucidate the role of the DG in mTLE, we analysed hippocampal sclerosis (HS), no-HS, non-TLE epilepsy control, and non-epilepsy control cohorts using morphometry and gene expression profiling techniques. Morphometry techniques analysed DG cell spacing, nucleus size, and nucleus circularity. Our data show distinct DG morphometry and RNA expression profiles between HS and No-HS. Dentate granule cells are more dispersed in patients with HS, and the DG shows an elevated expression of the complement system, apoptosis, and extracellular matrix remodelling-related RNA. We also observe an overall decrease in neurogenesis-related RNA in HS DG. Interestingly, regardless of the pathological diagnosis, the DG morphometry correlates with post-operative outcomes. Increased cell spacing is observed in the DG of mTLE cases that achieve seizure freedom post-operatively. This study reveals the possible prognostic value of DG morphometry, as well as supporting the notion that HS and no-HS TLE may be distinct disease entities with differing contributing mechanisms.

Cell-surface Milieu Remodeling in Human Dendritic Cell Activation

Dendritic cells (DCs) are specialized sentinel and APCs coordinating innate and adaptive immunity. Through proteins on their cell surface, DCs sense changes in the environment, internalize pathogens, present processed Ags, and communicate with other immune cells. By combining chemical labeling and quantitative mass spectrometry, we systematically profiled and compared the cell-surface proteomes of human primary conventional DCs (cDCs) in their resting and activated states. TLR activation by a lipopeptide globally reshaped the cell-surface proteome of cDCs, with >100 proteins upregulated or downregulated. By simultaneously elevating positive regulators and reducing inhibitory signals across multiple protein families, the remodeling creates a cell-surface milieu promoting immune responses. Still, cDCs maintain the stimulatory-to-inhibitory balance by leveraging a distinct set of inhibitory molecules. This analysis thus uncovers the molecular complexity and plasticity of the cDC cell surface and provides a roadmap for understanding cDC activation and signaling.

Advancements in Omics and Breakthrough Gene Therapies: A Glimpse into the Future of Peripheral Artery Disease

Peripheral artery disease (PAD), a highly prevalent global disease, associates with significant morbidity and mortality in affected patients. Despite progress in endovascular and open revascularization techniques for advanced PAD, these interventions grapple with elevated rates of arterial restenosis and vein graft failure attributed to intimal hyperplasia (IH). Novel multiomics technologies, coupled with sophisticated analyses tools recently powered by advances in artificial intelligence, have enabled the study of atherosclerosis and IH with unprecedented single-cell and spatial precision. Numerous studies have pinpointed gene hubs regulating pivotal atherogenic and atheroprotective signaling pathways as potential therapeutic candidates. Leveraging advancements in viral and nonviral gene therapy (GT) platforms, gene editing technologies, and cutting-edge biomaterial reservoirs for delivery uniquely positions us to develop safe, efficient, and targeted GTs for PAD-related diseases. Gene therapies appear particularly fitting for ex vivo genetic engineering of IH-resistant vein grafts. This manuscript highlights currently available state-of-the-art multiomics approaches, explores promising GT-based candidates, and details GT delivery modalities employed by our laboratory and others to thwart mid-term vein graft failure caused by IH, as well as other PAD-related conditions. The potential clinical translation of these targeted GTs holds the promise to revolutionize PAD treatment, thereby enhancing patients' quality of life and life expectancy.

Cardiomyocyte-derived circulating extracellular vesicles allow a non-invasive liquid biopsy of myocardium in health and disease

The ability to track disease without tissue biopsy in patients is a major goal in biology and medicine. Here, we identify and characterize cardiomyocyte-derived extracellular vesicles in circulation (EVs; "cardiovesicles") through comprehensive studies of induced pluripotent stem cell-derived cardiomyocytes, genetic mouse models, and state-of-the-art mass spectrometry and low-input transcriptomics. These studies identified two markers (POPDC2, CHRNE) enriched on cardiovesicles for biotinylated antibody-based immunocapture. Captured cardiovesicles were enriched in canonical cardiomyocyte transcripts/pathways with distinct profiles based on human disease type (heart failure, myocardial infarction). In paired myocardial tissue-plasma from patients, highly expressed genes in cardiovesicles were largely cardiac-enriched (vs. "bulk" EVs, which were more organ non-specific) with high expression in myocardial tissue by single nuclear RNA-seq, largely in cardiomyocytes. These results demonstrate the first "liquid" biopsy discovery platform to interrogate cardiomyocyte states noninvasively in model systems and in human disease, allowing non-invasive characterization of cardiomyocyte biology for discovery and therapeutic applications.

Multiomics2Targets identifies targets from cancer cohorts profiled with transcriptomics, proteomics, and phosphoproteomics

The availability of data from profiling of cancer patients with multiomics is rapidly increasing. However, integrative analysis of such data for personalized target identification is not trivial. Multiomics2Targets is a platform that enables users to upload transcriptomics, proteomics, and phosphoproteomics data matrices collected from the same cohort of cancer patients. After uploading the data, Multiomics2Targets produces a report that resembles a research publication. The uploaded matrices are processed, analyzed, and visualized using the tools Enrichr, KEA3, ChEA3, Expression2Kinases, and TargetRanger to identify and prioritize proteins, genes, and transcripts as potential targets. Figures and tables, as well as descriptions of the methods and results, are automatically generated. Reports include an abstract, introduction, methods, results, discussion, conclusions, and references and are exportable as citable PDFs and Jupyter Notebooks. Multiomics2Targets is applied to analyze version 3 of the Clinical Proteomic Tumor Analysis Consortium (CPTAC3) pan-cancer cohort, identifying potential targets for each CPTAC3 cancer subtype. Multiomics2Targets is available from https://multiomics2targets.maayanlab.cloud/.

Selection Across the Three-Dimensional Structure of Venom Proteins from North American Scolopendromorph Centipedes

Gene duplication followed by nucleotide differentiation is one of the simplest mechanisms to develop new functions for genes. However, the evolutionary processes underlying the divergence of multigene families remain controversial. We used multigene families found within the diversity of toxic proteins in centipede venom to test two hypotheses related to venom evolution: the two-speed mode of venom evolution and the rapid accumulation of variation in exposed residues (RAVER) model. The two-speed mode of venom evolution proposes that different types of selection impact ancient and younger venomous lineages with negative selection being the predominant form in ancient lineages and positive selection being the dominant form in younger lineages. The RAVER hypothesis proposes that, instead of different types of selection acting on different ages of venomous lineages, the different types of selection will selectively contribute to amino acid variation based on whether the residue is exposed to the solvent where it can potentially interact directly with toxin targets. This hypothesis parallels the longstanding understanding of protein evolution that suggests that residues found within the structural or active regions of the protein will be under negative or purifying selection, and residues that do not form part of these areas will be more prone to positive selection. To test these two hypotheses, we compared the venom of 26 centipedes from the order Scolopendromorpha from six currently recognized species from across North America using both transcriptomics and proteomics. We first estimated their phylogenetic relationships and uncovered paraphyly among the genus Scolopendra and evidence for cryptic diversity among currently recognized species. Using our phylogeny, we then characterized the diverse venom components from across the identified clades using a combination of transcriptomics and proteomics. We conducted selection-based analyses in the context of predicted three-dimensional properties of the venom proteins and found support for both hypotheses. Consistent with the two-speed hypothesis, we found a prevalence of negative selection across all proteins. Consistent with the RAVER hypothesis, we found evidence of positive selection on solvent-exposed residues, with structural and less-exposed residues showing stronger signal for negative selection. Through the use of phylogenetics, transcriptomics, proteomics, and selection-based analyses, we were able to describe the evolution of venom from an ancient venomous lineage and support principles of protein evolution that directly relate to multigene family evolution.

Proteome allocation is linked to transcriptional regulation through a modularized transcriptome

It has proved challenging to quantitatively relate the proteome to the transcriptome on a per-gene basis. Recent advances in data analytics have enabled a biologically meaningful modularization of the bacterial transcriptome. We thus investigate whether matched datasets of transcriptomes and proteomes from bacteria under diverse conditions can be modularized in the same way to reveal novel relationships between their compositions. We find that; (1) the modules of the proteome and the transcriptome are comprised of a similar list of gene products, (2) the modules in the proteome often represent combinations of modules from the transcriptome, (3) known transcriptional and post-translational regulation is reflected in differences between two sets of modules, allowing for knowledge-mapping when interpreting module functions, and (4) through statistical modeling, absolute proteome allocation can be inferred from the transcriptome alone. Quantitative and knowledge-based relationships can thus be found at the genome-scale between the proteome and transcriptome in bacteria.

Phosphoenolpyruvate carboxykinase-1 targeted siRNA promotes wound healing in type 2 diabetic mice by restoring glucose homeostasis

It is well-accepted that the liver plays a vital role in the metabolism of glucose and its homeostasis. Dysregulated hepatic glucose production and utilization, leads to type 2 diabetes (T2DM). In the current study, RNA sequencing and qRT-PCR analysis of nanoformulation-treated T2DM mice (TGthr group) revealed beneficial crosstalk of PCK-1 silencing with other pathways involved in T2DM. The comparison of precise genetic expression profiles of the different experimental groups showed significantly improved hepatic glucose, fatty acid metabolism and several other T2DM-associated crucial markers after the nanoformulation treatment. As a result of these improvements, we observed a significant acceleration in wound healing and improved insulin signaling in vascular endothelial cells in the TGthr group as compared to the T2DM group. Enhanced phosphorylation of PI3K/Akt pathway proteins in the TGthr group resulted in increased angiogenesis as observed by the increased expression of endothelial cell markers (CD31, CD34) thereby improving endothelial dysfunctions in the TGthr group. Additionally, therapeutic nanoformulation has been observed to improve the inflammatory cytokine profile in the TGthr group. Overall, our results demonstrated that the synthesized therapeutic nanoformulation referred to as GPR8:PCK-1siRNA holds the potential in ameliorating hyperglycemia-associated complications such as delayed wound healing in diabetes.

Establishing a conceptual framework for holistic cell states and state transitions

Cell states were traditionally defined by how they looked, where they were located, and what functions they performed. In this post-genomic era, the field is largely focused on a molecular view of cell state. Moving forward, we anticipate that the observables used to define cell states will evolve again as single-cell imaging and analytics are advancing at a breakneck pace via the collection of large-scale, systematic cell image datasets and the application of quantitative image-based data science methods. This is, therefore, a key moment in the arc of cell biological research to develop approaches that integrate the spatiotemporal observables of the physical structure and organization of the cell with molecular observables toward the concept of a holistic cell state. In this perspective, we propose a conceptual framework for holistic cell states and state transitions that is data-driven, practical, and useful to enable integrative analyses and modeling across many data types.

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.

Mesenchymal stromal/stem cells promote intestinal epithelium regeneration after chemotherapy-induced damage

BACKGROUND

Allogeneic hematopoietic stem cell transplantation (HSCT) is a curative treatment for leukemia and a range of non-malignant disorders. The success of the therapy is hampered by occurrence of acute graft-versus-host disease (aGvHD); an inflammatory response damaging recipient organs, with gut, liver, and skin being the most susceptible. Intestinal GvHD injury is often a life-threatening complication in patients unresponsive to steroid treatment. Allogeneic mesenchymal stromal/stem cell (MSC) infusions are a promising potential treatment for steroid-resistant aGvHD. Data from our institution and others demonstrate rescue of approximately 40-50% of aGvHD patients with MSCs in Phase I, II studies and minor side effects. Although promising, better understanding of MSC mode of action and patient response to MSC-based therapy is essential to improve this lifesaving treatment.

METHODS

Single cell human small intestine organoids were embedded in Matrigel, grown for 5 days and treated with busulfan for 48 h. Organoids damaged by treatment with busulfan or control organoids were co-cultured with 5000, 10,000, and 50,000 MSCs for 24 h, 48 h or 7 days and the analyses such as surface area determination, proliferation and apoptosis assessment, RNA sequencing and proteomics were performed.

RESULTS

Here, we developed a 3D co-culture model of human small intestinal organoids and MSCs, which allows to study the regenerative effects of MSCs on intestinal epithelium in a more physiologically relevant setting than existing in vitro systems. Using this model we mimicked chemotherapy-mediated damage of the intestinal epithelium. The treatment with busulfan, the chemotherapeutic commonly used as conditioning regiment before the HSCT, affected pathways regulating epithelial to mesenchymal transition, proliferation, and apoptosis in small intestinal organoids, as shown by transcriptomic and proteomic analysis. The co-culture of busulfan-treated intestinal organoids with MSCs reversed the effects of busulfan on the transcriptome and proteome of intestinal epithelium, which we also confirmed by functional evaluation of proliferation and apoptosis.

CONCLUSIONS

Collectively, we demonstrate that our in vitro co-culture system is a new valuable tool to facilitate the investigation of the molecular mechanisms behind the therapeutic effects of MSCs on damaged intestinal epithelium. This could benefit further optimization of the use of MSCs in HSCT patients.

Single-cell biclustering for cell-specific transcriptomic perturbation detection in AD progression

The pathogenesis of Alzheimer disease (AD) involves complex gene regulatory changes across different cell types. To help decipher this complexity, we introduce single-cell Bayesian biclustering (scBC), a framework for identifying cell-specific gene network biomarkers in scRNA and snRNA-seq data. Through biclustering, scBC enables the analysis of perturbations in functional gene modules at the single-cell level. Applying the scBC framework to AD snRNA-seq data reveals the perturbations within gene modules across distinct cell groups and sheds light on gene-cell correlations during AD progression. Notably, our method helps to overcome common challenges in single-cell data analysis, including batch effects and dropout events. Incorporating prior knowledge further enables the framework to yield more biologically interpretable results. Comparative analyses on simulated and real-world datasets demonstrate the precision and robustness of our approach compared to other state-of-the-art biclustering methods. scBC holds potential for unraveling the mechanisms underlying polygenic diseases characterized by intricate gene coexpression patterns.

A Workflow for Meaningful Interpretation of Classification Results from Handheld Ambient Mass Spectrometry Analysis Probes

While untargeted analysis of biological tissues with ambient mass spectrometry analysis probes has been widely reported in the literature, there are currently no guidelines to standardize the workflows for the experimental design, creation, and validation of molecular models that are utilized in these methods to perform class predictions. By drawing parallels with hurdles that are faced in the field of food fraud detection with untargeted mass spectrometry, we provide a stepwise workflow for the creation, refinement, evaluation, and assessment of the robustness of molecular models, aimed at meaningful interpretation of mass spectrometry-based tissue classification results. We propose strategies to obtain a sufficient number of samples for the creation of molecular models and discuss the potential overfitting of data, emphasizing both the need for model validation using an independent cohort of test samples, as well as the use of a fully characterized feature-based approach that verifies the biological relevance of the features that are used to avoid false discoveries. We additionally highlight the need to treat molecular models as "dynamic" and "living" entities and to further refine them as new knowledge concerning disease pathways and classifier feature noise becomes apparent in large(r) population studies. Where appropriate, we have provided a discussion of the challenges that we faced in our development of a 10 s cancer classification method using picosecond infrared laser mass spectrometry (PIRL-MS) to facilitate clinical decision-making at the bedside.

Mining cholesterol genes from thousands of mouse livers identifies aldolase C as a regulator of cholesterol biosynthesis

The availability of genome-wide transcriptomic and proteomic datasets is ever-increasing and often not used beyond initial publication. Here, we applied module-based coexpression network analysis to a comprehensive catalog of 35 mouse genome-wide liver expression datasets (encompassing more than 3800 mice) with the goal of identifying and validating unknown genes involved in cholesterol metabolism. From these 35 datasets, we identified a conserved module of genes enriched with cholesterol biosynthetic genes. Using a systematic approach across the 35 datasets, we identified three genes (Rdh11, Echdc1, and Aldoc) with no known role in cholesterol metabolism. We then performed functional validation studies and show that each gene is capable of regulating cholesterol metabolism. For the glycolytic gene, Aldoc, we demonstrate that it contributes to de novo cholesterol biosynthesis and regulates cholesterol and triglyceride levels in mice. As Aldoc is located within a genome-wide significant genome-wide association studies locus for human plasma cholesterol levels, our studies establish Aldoc as a causal gene within this locus. Through our work, we develop a framework for leveraging mouse genome-wide liver datasets for identifying and validating genes involved in cholesterol metabolism.

Technical optimization of spatially resolved single-cell transcriptomic datasets to study clinical liver disease

Single cell and spatially resolved 'omic' techniques have enabled deep characterization of clinical pathologies that remain poorly understood, providing unprecedented insights into molecular mechanisms of disease. However, transcriptomic platforms are costly, limiting sample size, which increases the possibility of pre-analytical variables such as tissue processing and storage procedures impacting RNA quality and downstream analyses. Furthermore, spatial transcriptomics have not yet reached single cell resolution, leading to the development of multiple deconvolution methods to predict individual cell types within each transcriptome 'spot' on tissue sections. In this study, we performed spatial transcriptomics and single nucleus RNA sequencing (snRNAseq) on matched specimens from patients with either histologically normal or advanced fibrosis to establish important aspects of tissue handling, data processing, and downstream analyses of biobanked liver samples. We observed that tissue preservation technique impacts transcriptomic data, especially in fibrotic liver. Single cell mapping of the spatial transcriptome using paired snRNAseq data generated a spatially resolved, single cell dataset with 24 unique liver cell phenotypes. We determined that cell-cell interactions predicted using ligand-receptor analysis of snRNAseq data poorly correlated with cellular relationships identified using spatial transcriptomics. Our study provides a framework for generating spatially resolved, single cell datasets to study gene expression and cell-cell interactions in biobanked clinical samples with advanced liver disease.

Characterisation of the forest cobra (Naja melanoleuca) venom using a multifaceted mass spectrometric-based approach

Snake venoms consist of highly biologically active proteins and peptides that are responsible for the lethal physiological effects of snakebite envenomation. In order to guide the development of targeted antivenom strategies, comprehensive understanding of venom compositions and in-depth characterisation of various proteoforms, often not captured by traditional bottom-up proteomic workflows, is necessary. Here, we employ an integrated 'omics' and intact mass spectrometry (MS)-based approach to profile the heterogeneity within the venom of the forest cobra (Naja melanoleuca), adopting different analytical strategies to accommodate for the dynamic molecular mass range of venom proteins present. The venom proteome of N. melanoleuca was catalogued using a venom gland transcriptome-guided bottom-up proteomics approach, revealing a venom consisting of six toxin superfamilies. The subtle diversity present in the venom components was further explored using reversed phase-ultra performance liquid chromatography (RP-UPLC) coupled to intact MS. This approach showed a significant increase in the number of venom proteoforms within various toxin families that were not captured in previous studies. Furthermore, we probed at the higher-order structures of the larger venom proteins using a combination of native MS and mass photometry and revealed significant structural heterogeneity along with extensive post-translational modifications in the form of glycosylation in these larger toxins. Here, we show the diverse structural heterogeneity of snake venom proteins in the venom of N. melanoleuca using an integrated workflow that incorporates analytical strategies that profile snake venom at the proteoform level, complementing traditional venom characterisation approaches.

Depicting the molecular features of suicidal behavior: a review from an "omics" perspective

Background Suicide is one of the leading global causes of death. Behavior patterns from suicide ideation to completion are complex, involving multiple risk factors. Advances in technologies and large-scale bioinformatic tools are changing how we approach biomedical problems. The "omics" field may provide new knowledge about suicidal behavior to improve identification of relevant biological pathways associated with suicidal behavior. Methods We reviewed transcriptomic, proteomic, and metabolomic studies conducted in blood and post-mortem brains from individuals who experienced suicide or suicidal behavior. Omics data were combined using systems biology in silico, aiming at identifying major biological mechanisms and key molecules associated with suicide. Results Post-mortem samples of suicide completers indicate major dysregulations in pathways associated with glial cells (astrocytes and microglia), neurotransmission (GABAergic and glutamatergic systems), neuroplasticity and cell survivor, immune responses and energy homeostasis. In the periphery, studies found alterations in molecules involved in immune responses, polyamines, lipid transport, energy homeostasis, and amino and nucleic acid metabolism. Limitations We included only exploratory, non-hypothesis-driven studies; most studies only included one brain region and whole tissue analysis, and focused on suicide completers who were white males with almost none confounding factors. Conclusions We can highlight the importance of synaptic function, especially the balance between the inhibitory and excitatory synapses, and mechanisms associated with neuroplasticity, common pathways associated with psychiatric disorders. However, some of the pathways highlighted in this review, such as transcriptional factors associated with RNA splicing, formation of cortical connections, and gliogenesis, point to mechanisms that still need to be explored.

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

Cancer immunotherapies have produced 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 specimens along with normal tissues to identify biologically relevant cell surface proteins that can serve as immunotherapeutic targets for neuroblastoma, an often-fatal childhood cancer of the developing nervous system. We apply this approach to human-derived cell lines (N=9) and cell/patient-derived xenograft (N=12) models of neuroblastoma. Plasma membrane-enriched mass spectrometry identified 1,461 cell surface proteins in cell lines and 1,401 in xenograft models, respectively. Additional proteogenomic analyses revealed 60 high-confidence candidate immunotherapeutic targets and we prioritized Delta-like canonical notch ligand 1 (DLK1) for further study. High expression of DLK1 directly correlated with the presence of a super-enhancer spanning the DLK1 locus. Robust cell surface expression of DLK1 was validated by immunofluorescence, flow cytometry, and immunohistochemistry. Short hairpin RNA mediated silencing of DLK1 in neuroblastoma cells resulted in increased cellular differentiation. ADCT-701, a DLK1-targeting antibody-drug conjugate (ADC), showed potent and specific cytotoxicity in DLK1-expressing neuroblastoma xenograft models. Moreover, DLK1 is highly expressed in several adult cancer types, including adrenocortical carcinoma (ACC), pheochromocytoma/paraganglioma (PCPG), hepatoblastoma, and small cell lung cancer (SCLC), suggesting potential clinical benefit beyond neuroblastoma. Taken together, our study demonstrates the utility of comprehensive cancer surfaceome characterization and credentials DLK1 as an immunotherapeutic target.

Highlights

Plasma membrane enriched proteomics defines surfaceome of neuroblastomaMulti-omic data integration prioritizes DLK1 as a candidate immunotherapeutic target in neuroblastoma and other cancersDLK1 expression is driven by a super-enhancer DLK1 silencing in neuroblastoma cells results in cellular differentiation ADCT-701, a DLK1-targeting antibody-drug conjugate, shows potent and specific cytotoxicity in DLK1-expressing neuroblastoma preclinical models.

Effects of miR-722 on gene expression and alternative splicing in the liver of half-smooth tongue sole after infection with Vibrio anguillarum

MicroRNAs play crucial roles in various biological processes, including but not limited to differentiation, development, disease, and immunity. However, their immunoregulatory roles in half-smooth tongue sole are lacking. Our previous studies indicated that miR-722 could target C5aR1 to modulate the complement pathway to alleviate inflammatory response and even affect the mortality after the bacterial infection with Vibrio anguillarum. Driven by the purpose of revealing the underlying mechanisms, in this study, we investigated the effects of miR-722 on the gene expression and alternative splicing (AS) in the liver of half-smooth tongue sole after Vibrio anguillarum infection, with the approach of miR-722 overexpression/silencing and subsequent RNA-seq. Among the different comparisons, the I group (miR-722 inhibitor and V. anguillarum) versus blank control (PBS) exhibited the highest number of differentially expressed genes (DEGs), suggesting that the immune response was overactivated after inhibiting the miR-722. In addition, enrichment analyses were performed to reveal the functions of DEGs and differential AS (DAS) genes, reflecting the enrichment of RNA splicing and immune-related pathways including NF-κB and T cell receptor signaling pathway. Comparing the M group (miR-722 mimic and V. anguillarum) with the negative control (random sequence and V. anguillarum), two immune-related genes, cd48 and mapk8, were differentially expressed, of which mapk8 was also differentially spliced, indicating their importance in the immune response. Furthermore, representative gene analysis was performed, suggesting their corresponding functional changes due to AS. To verify the RNA-seq data, quantitative real-time PCR was employed with twenty pairs of primers for DEGs and DAS events. Overall, our results demonstrated that miR-722 could mediate the transcriptome-wide changes of gene expression and AS in half-smooth tongue sole, and provided insights into the regulatory role of miR-722 in immune responses, laying the foundation for further functional analyses and practical applications in aquaculture.

A review of the quantitative real-time PCR and Omics approaches applied to study the effects of dietary selenium nanoparticles (nano-Se) on fish

•Selenium is an essential microelement required for the health of humans and animals. •Nano-Se have been applied in aquafeeds to enhance fish immunity and growth. •Omics are used to discover molecular mechanisms underlying biological processes. •This article reviews the omics platforms used to study the nano-Se effects in fish.

Selenium (Se) is an essential trace microelement required for the overall health of humans and animals. The importance of Se is mainly related to its participation in the structure of selenoproteins with diverse biological functions, including antioxidant defense, immunity, and thyroid hormone metabolism. The functionality of Se depends on its chemical form (inorganic and organic Se). Due to low toxicity and higher efficacy, Se nanoparticles (nano-Se) have been recently applied in aquafeeds to enhance fish performance. New technological advances have offered different Omics approaches, such as transcriptomics, proteomics, and metabolomics, to realize molecular mechanisms underlying biological processes. In recent years, Omics approaches have been employed to study nano-Se effects on fish. The present article summarizes the impacts of nano-Se supplementation on fish performance, then reviews the qRT-PCR assay and Omics-based approaches used to study the dietary nano-Se supplementation effects in fish.

Mmp2 Deficiency Leads to Defective Parturition and High Dystocia Rates in Mice

Parturition is the final and essential step for mammalian reproduction. While the uterus is quiescent during pregnancy, fundamental changes arise in the myometrial contractility, inducing fetal expulsion. Extracellular matrix (ECM) remodeling is fundamental for these events. The gelatinases subgroup of matrix metalloproteinases (MMPs), MMP2 and MMP9, participate in uterine ECM remodeling throughout pregnancy and parturition. However, their loss-of-function effect is unknown. Here, we determined the result of eliminating Mmp2 and/or Mmp9 on parturition in vivo, using single- and double-knockout (dKO) mice. The dystocia rates were measured in each genotype, and uterine tissue was collected from nulliparous synchronized females at the ages of 2, 4, 9 and 12 months. Very high percentages of dystocia (40-55%) were found in the Mmp2-/- and dKO females, contrary to the Mmp9-/- and wild-type females. The histological analysis of the uterus and cervix revealed that Mmp2-/- tissues undergo marked structural alterations, including highly enlarged myometrial, endometrial and luminal cavity. Increased collagen deposition was also demonstrated, suggesting a mechanism of extensive fibrosis in the Mmp2-/- myometrium, which may result in dystocia. Overall, this study describes a new role for MMP2 in myometrium remodeling during mammalian parturition process, highlighting a novel cause for dystocia due to a loss in MMP2 activity in the uterine tissue.

Systems genetics approaches for understanding complex traits with relevance for human disease

Quantitative traits are often complex because of the contribution of many loci, with further complexity added by environmental factors. In medical research, systems genetics is a powerful approach for the study of complex traits, as it integrates intermediate phenotypes, such as RNA, protein, and metabolite levels, to understand molecular and physiological phenotypes linking discrete DNA sequence variation to complex clinical and physiological traits. The primary purpose of this review is to describe some of the resources and tools of systems genetics in humans and rodent models, so that researchers in many areas of biology and medicine can make use of the data.

Workability of mRNA Sequencing for Predicting Protein Abundance

Transcriptomics methods (RNA-Seq, PCR) today are more routine and reproducible than proteomics methods, i.e., both mass spectrometry and immunochemical analysis. For this reason, most scientific studies are limited to assessing the level of mRNA content. At the same time, protein content (and its post-translational status) largely determines the cell's state and behavior. Such a forced extrapolation of conclusions from the transcriptome to the proteome often seems unjustified. The ratios of "transcript-protein" pairs can vary by several orders of magnitude for different genes. As a rule, the correlation coefficient between transcriptome-proteome levels for different tissues does not exceed 0.3-0.5. Several characteristics determine the ratio between the content of mRNA and protein: among them, the rate of movement of the ribosome along the mRNA and the number of free ribosomes in the cell, the availability of tRNA, the secondary structure, and the localization of the transcript. The technical features of the experimental methods also significantly influence the levels of the transcript and protein of the corresponding gene on the outcome of the comparison. Given the above biological features and the performance of experimental and bioinformatic approaches, one may develop various models to predict proteomic profiles based on transcriptomic data. This review is devoted to the ability of RNA sequencing methods for protein abundance prediction.

Gene expression flux analysis reveals specific regulatory modalities of gene expression

The level of a given protein is determined by the synthesis and degradation rates of its mRNA and protein. While several studies have quantified the contribution of different gene expression steps in regulating protein levels, these are limited by using equilibrium approximations in out-of-equilibrium biological systems. Here, we introduce gene expression flux analysis to quantitatively dissect the dynamics of the expression level for specific proteins and use it to analyze published transcriptomics and proteomics datasets. Our analysis reveals distinct regulatory modalities shared by sets of genes with clear functional signatures. We also find that protein degradation plays a stronger role than expected in the adaptation of protein levels. These findings suggest that shared regulatory strategies can lead to versatile responses at the protein level and highlight the importance of going beyond equilibrium approximations to dissect the quantitative contribution of different steps of gene expression to protein dynamics.

Ubiquitylome analysis reveals the involvement of ubiquitination in the cold responses of banana seedling leaves

Low temperature is a crucial environmental factor limiting the productivity and distribution of banana. Ubiquitination (Kub) is one of the main posttranslational modifications (PTMs) involved in plant responses to abiotic stresses. However, little information is available on the effects of Kub on banana under cold stress. In this study, we used label-free quantification (LFQ) to identify changes in the protein expression and Kub levels in banana seedling leaves after chilling treatment. In total, 4156 proteins, 1089 ubiquitinated proteins and 2636 Kub sites were quantified. Western blot assays showed that Kub was abundant in leaves after low-temperature treatment. Our results show that the proteome and ubiquitylome were negatively correlated, indicating that Kub could be involved in the degradation of proteins in banana after chilling treatment. Based on bioinformatics analysis, low-temperature stress-related signals and metabolic pathways such as cold acclimation, glutathione metabolism, calcium signaling, and photosynthesis signaling were identified. In addition, we found that transcription factors and chromatin remodeling factors related to low-temperature stress were ubiquitinated. Overall, our work presents the first systematic analysis of the Kub proteome in banana under cold stress and provides support for future studies on the regulatory mechanisms of Kub during the cold stress response in plants. SIGNIFICANCE: Banana is a typical tropical fruit tree with poor low-temperature tolerance,however, the role of PTMs such as Kub in the cold response of banana remains unclear. This study highlights the fact that the effects of low-temperature on proteome and ubiquitylome in the banana seedling leaves, we discussed the correlation between transcriptome and proteome, ubiquitylome and proteome, and we analyzed the expression and the changes of ubiquitination levels of low-temperature related proteins and pathway after chilling treatment, and we found that transcription factors and chromatin remodeling factors related to low-temperature stress were ubiquitinated. This study provides new insights into the ubiquitination pathway of banana under cold stress.

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 co-expression 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 (3.6%). 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.

Highlights

At the level of individual genes, the abundance of transcripts and proteins is weakly correlated within a species ( ρ = 0.165). While the proteome is not imprinted by population structure, co-expression patterns recapitulate the cellular functional landscapeWild populations exhibit a higher abundance of respiration-related proteins compared to domesticated populationsLoci that influence protein abundance differ from those that impact transcript levels, likely because of protein turnover.

Technical optimization of spatially resolved single-cell transcriptomic datasets to study clinical liver disease

Single cell and spatially resolved 'omic' techniques have enabled deep characterization of clinical pathologies that remain poorly understood, providing unprecedented insights into molecular mechanisms of disease. However, transcriptomic platforms are costly, limiting sample size, which increases the possibility of pre-analytical variables such as tissue processing and storage procedures impacting RNA quality and downstream analyses. Furthermore, spatial transcriptomics have not yet reached single cell resolution, leading to the development of multiple deconvolution methods to predict individual cell types within each transcriptome 'spot' on tissue sections. In this study, we performed spatial transcriptomics and single nucleus RNA sequencing (snRNASeq) on matched specimens from patients with either histologically normal or advanced fibrosis to establish important aspects of tissue handling, data processing, and downstream analyses of biobanked liver samples. We observed that tissue preservation technique impacts transcriptomic data, especially in fibrotic liver. Deconvolution of the spatial transcriptome using paired snRNASeq data generated a spatially resolved, single cell dataset with 24 unique liver cell phenotypes. We determined that cell-cell interactions predicted using ligand-receptor analysis of snRNASeq data poorly correlated with celullar relationships identified using spatial transcriptomics. Our study provides a framework for generating spatially resolved, single cell datasets to study gene expression and cell-cell interactions in biobanked clinical samples with advanced liver disease.

Integrated transcriptomic and proteomic analyses of plerocercoid and adult Spirometra mansoni reveal potential important pathways in the development of the medical tapeworm

BACKGROUND

Spirometra mansoni can parasitize animals and humans through food and water, causing parasitic zoonosis. Knowledge of the developmental process of S. mansoni is crucial for effective treatment; thus, it is important to characterize differential and specific proteins and pathways associated with parasite development.

METHODS

In this study, we performed a comparative proteomic analysis of the plerocercoid and adult stages using a tandem mass tag-based quantitative proteomic approach. Additionally, integrated transcriptomic and proteomic analyses were conducted to obtain the full protein expression profiles of different life cycle stages of the tapeworm.

RESULTS

Approximately 1166 differentially expressed proteins (DEPs) were identified in adults versus plerocercoids, of which 641 DEPs were upregulated and 525 were downregulated. Gene Ontology (GO), Clusters of Orthologous groups (COG) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicated that most DEPs related to genetic information processing and metabolism of energy in adults seem to be more activated. In the plerocercoid stage, compared to metabolism, genetic information processing appears more dynamic. Protein-protein interaction (PPI) revealed six key proteins (phosphomannomutase, glutathione transferase, malate dehydrogenase, cytoplasmic, 40S ribosomal protein S15, ribosomal protein L15 and 60S acidic ribosomal protein P2) that may play active roles in the growth and development of S. mansoni. Finally, the combination of transcriptomic and proteomic data suggested that three pathways (ubiquitin-mediated proteolysis, phagosome and spliceosome) and five proteins closely related to these pathways might have a significant influence in S. mansoni.

CONCLUSIONS

These findings contribute to increasing the knowledge on the protein expression profiles of S. mansoni and provide new insights into functional studies on the molecular mechanisms of the neglected medical tapeworm.

Genetic pathways regulating the longitudinal acquisition of cocaine self-administration in a panel of inbred and recombinant inbred mice

To identify addiction genes, we evaluate intravenous self-administration of cocaine or saline in 84 inbred and recombinant inbred mouse strains over 10 days. We integrate the behavior data with brain RNA-seq data from 41 strains. The self-administration of cocaine and that of saline are genetically distinct. We maximize power to map loci for cocaine intake by using a linear mixed model to account for this longitudinal phenotype while correcting for population structure. A total of 15 unique significant loci are identified in the genome-wide association study. A transcriptome-wide association study highlights the Trpv2 ion channel as a key locus for cocaine self-administration as well as identifying 17 additional genes, including Arhgef26, Slc18b1, and Slco5a1. We find numerous instances where alternate splice site selection or RNA editing altered transcript abundance. Our work emphasizes the importance of Trpv2, an ionotropic cannabinoid receptor, for the response to cocaine.

Ten quick tips for avoiding pitfalls in multi-omics data integration analyses

Data are the most important elements of bioinformatics: Computational analysis of bioinformatics data, in fact, can help researchers infer new knowledge about biology, chemistry, biophysics, and sometimes even medicine, influencing treatments and therapies for patients. Bioinformatics and high-throughput biological data coming from different sources can even be more helpful, because each of these different data chunks can provide alternative, complementary information about a specific biological phenomenon, similar to multiple photos of the same subject taken from different angles. In this context, the integration of bioinformatics and high-throughput biological data gets a pivotal role in running a successful bioinformatics study. In the last decades, data originating from proteomics, metabolomics, metagenomics, phenomics, transcriptomics, and epigenomics have been labelled -omics data, as a unique name to refer to them, and the integration of these omics data has gained importance in all biological areas. Even if this omics data integration is useful and relevant, due to its heterogeneity, it is not uncommon to make mistakes during the integration phases. We therefore decided to present these ten quick tips to perform an omics data integration correctly, avoiding common mistakes we experienced or noticed in published studies in the past. Even if we designed our ten guidelines for beginners, by using a simple language that (we hope) can be understood by anyone, we believe our ten recommendations should be taken into account by all the bioinformaticians performing omics data integration, including experts.

Advances in proteomic phenotyping of microglia in neurodegeneration

Microglia are dynamic resident immune cells of the central nervous system (CNS) that sense, survey, and respond to changes in their environment. In disease states, microglia transform from homeostatic to diverse molecular phenotypic states that play complex and causal roles in neurologic disease pathogenesis, as evidenced by the identification of microglial genes as genetic risk factors for neurodegenerative disease. While advances in transcriptomic profiling of microglia from the CNS of humans and animal models have provided transformative insights, the transcriptome is only modestly reflective of the proteome. Proteomic profiling of microglia is therefore more likely to provide functionally and therapeutically relevant targets. In this review, we discuss molecular insights gained from transcriptomic studies of microglia in the context of Alzheimer's disease as a prototypic neurodegenerative disease, and highlight existing and emerging approaches for proteomic profiling of microglia derived from in vivo model systems and human brain.

Bromodomain-containing Protein 4 regulates innate inflammation via modulation of alternative splicing

Introduction

Bromodomain-containing Protein 4 (BRD4) is a transcriptional regulator which coordinates gene expression programs controlling cancer biology, inflammation, and fibrosis. In the context of airway viral infection, BRD4-specific inhibitors (BRD4i) block the release of pro-inflammatory cytokines and prevent downstream epithelial plasticity. Although the chromatin modifying functions of BRD4 in inducible gene expression have been extensively investigated, its roles in post-transcriptional regulation are not well understood. Given BRD4's interaction with the transcriptional elongation complex and spliceosome, we hypothesize that BRD4 is a functional regulator of mRNA processing.

Methods

To address this question, we combine data-independent analysis - parallel accumulation-serial fragmentation (diaPASEF) with RNA-sequencing to achieve deep and integrated coverage of the proteomic and transcriptomic landscapes of human small airway epithelial cells exposed to viral challenge and treated with BRD4i.

Results

We discover that BRD4 regulates alternative splicing of key genes, including Interferon-related Developmental Regulator 1 (IFRD1) and X-Box Binding Protein 1 (XBP1), related to the innate immune response and the unfolded protein response (UPR). We identify requirement of BRD4 for expression of serine-arginine splicing factors, splicosome components and the Inositol-Requiring Enzyme 1 IREα affecting immediate early innate response and the UPR.

Discussion

These findings extend the transcriptional elongation-facilitating actions of BRD4 in control of post-transcriptional RNA processing via modulating splicing factor expression in virus-induced innate signaling.

Allograft tissue under the microscope: only the beginning

PURPOSE OF REVIEW

To review novel modalities for interrogating a kidney allograft biopsy to complement the current Banff schema.

RECENT FINDINGS

Newer approaches of Artificial Intelligence (AI), Machine Learning (ML), digital pathology including Ex Vivo Microscopy, evaluation of the biopsy gene expression using bulk, single cell, and spatial transcriptomics and spatial proteomics are now available for tissue interrogation.

SUMMARY

Banff Schema of classification of allograft histology has standardized reporting of tissue pathology internationally greatly impacting clinical care and research. Inherent sampling error of biopsies, and lack of automated morphometric analysis with ordinal outputs limit its performance in prognostication of allograft health. Over the last decade, there has been an explosion of newer methods of evaluation of allograft tissue under the microscope. Digital pathology along with the application of AI and ML algorithms could revolutionize histopathological analyses. Novel molecular diagnostics such as spatially resolved single cell transcriptomics are identifying newer mechanisms underlying the pathologic diagnosis to delineate pathways of immunological activation, tissue injury, repair, and regeneration in allograft tissues. While these techniques are the future of tissue analysis, costs and complex logistics currently limit their clinical use.

Effect of selenium nanoparticles on alternative splicing in heat-stressed rainbow trout primary hepatocytes

Alternative splicing (AS) is a ubiquitous post-transcriptional regulatory mechanism in eukaryotes that generates multiple mRNA isoforms from a single gene, increasing diversity of mRNAs and proteins that are essential for eukaryotic developmental processes and responses to environmental stress. Results showed that a total of 37,463 AS events were identified in rainbow trout hepatocytes. In addition, a total of 364 differential alternative splicing (DAS) events were identified in hepatocytes under selenium nanoparticles (SeNPs) and 3632 DAS events were identified under a combination of SeNPs and heat stress (24 °C). Gene Ontology (GO) enrichment showed that some subcategories "immune effector processes", "response to stimuli" and "antioxidant activity" were associated with immunity, abiotic stimuli and antioxidants. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment showed that differentially expressed genes (DEGs) were significantly enriched in spliceosomes by adding SeNPs in heat-stressed hepatocytes. Splicing factor family (SRSF3, SRSF7, SRSF9, U2AF1 and U2AF2) and pre-RNA splicing factors (ACIN1 and PPRF18) were significantly upregulated and promoted AS. Furthermore, addition of SeNPs activated the phosphatidylinositol signaling system and upregulated the related genes PI4KA, DGKH, ITPK1 and Ocrl, and thus attenuated the inflammatory response to heat stress and enhanced resistance to heat stress by activating the adherent plaque kinase-PI3K-Akt signaling pathway and calcium channels. Those findings suggested that AS could be an essential regulatory mechanism in adaptation of rainbow trout to heat-stressed environments.

Cold-adapted amphipod species upon heat stress: Proteomic responses and their correlation with transcriptomic responses

The cellular heat shock response (HSR) comprises transcriptomic and proteomic reactions to thermal stress. It was here addressed, how the proteomic, together with the transcriptomic HSR, relate to the thermal sensitivities of three cold-adapted but differently thermo-sensitive freshwater amphipod species. The proteomes of thermosensitive Eulimnogammarus verrucosus and thermotolerant Eulimnogammarus cyaneus, both endemic to Lake Baikal, and of thermotolerant Holarctic Gammarus lacustris were investigated upon 24 h exposure to the species-specific 10 % lethal temperatures (LT10). Furthermore, correlations of heat stress induced changes in proteomes (this study) and transcriptomes (previous study with identical experimental design) were examined. Proteomes indicated that the HSR activated processes encompassed (i) proteostasis maintenance, (ii) maintenance of cell adhesion, (iii) oxygen transport, (iv) antioxidant response, and (v) regulation of protein synthesis. Thermo-sensitive E. verrucosus showed the most pronounced proteomic HSR and the lowest correlation of transcriptomic and proteomic HSRs. For proteins related to translation (ribosomal proteins, elongation factors), transcriptomic and proteomic changes were inconsistent: transcripts were downregulated in many cases, with levels of corresponding proteins remaining unchanged. In the Eulimnogammarus species, levels of hemocyanin protein but not transcript were increased upon heat stress, suggesting a HSR also directed to enhance oxygen transport. Thermosensitive E. verrucosus showed the most pronounced relocation of transcription/translation activity to proteostasis maintenance, which may indicate that the general species-specific stability of protein structure could be a fundamental determinant of thermotolerance. By combining transcriptomic and proteomic response data, this study provides a comprehensive picture of the cellular HSR components in the studied amphipods.

The role of the circadian clock in the development, progression, and treatment of non-alcoholic fatty liver disease

The circadian clock comprises a cellular endogenous timing system coordinating the alignment of physiological processes with geophysical time. Disruption of circadian rhythms has been associated with several metabolic diseases. In this review, we focus on liver as a major metabolic tissue and one of the most well-studied organs with regard to circadian regulation. We summarize current knowledge about the role of local and systemic clocks and rhythms in regulating biological functions of the liver. We discuss how the disruption of circadian rhythms influences the development of non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH). We also critically evaluate whether NAFLD/NASH may in turn result in chronodisruption. The last chapter focuses on potential roles of the clock system in prevention and treatment of NAFLD/NASH and the interaction of current NASH drug candidates with liver circadian rhythms and clocks. It becomes increasingly clear that paying attention to circadian timing may open new avenues for the optimization of NAFLD/NASH therapies and provide interesting targets for prevention and treatment of these increasingly prevalent disorders.

Proteome allocation is linked to transcriptional regulation through a modularized transcriptome

It has proved challenging to quantitatively relate the proteome to the transcriptome on a per-gene basis. Recent advances in data analytics have enabled a biologically meaningful modularization of the bacterial transcriptome. We thus investigated whether matched datasets of transcriptomes and proteomes from bacteria under diverse conditions could be modularized in the same way to reveal novel relationships between their compositions. We found that; 1) the modules of the proteome and the transcriptome are comprised of a similar list of gene products, 2) the modules in the proteome often represent combinations of modules from the transcriptome, 3) known transcriptional and post-translational regulation is reflected in differences between two sets of modules, allowing for knowledge-mapping when interpreting module functions, and 4) through statistical modeling, absolute proteome allocation can be inferred from the transcriptome alone. Quantitative and knowledge-based relationships can thus be found at the genome-scale between the proteome and transcriptome in bacteria.

The Elusive Trypanosoma cruzi Disperse Gene Protein Family (DGF-1)

Chagas disease, caused by Trypanosoma cruzi infections, is included in the group of neglected diseases, and efforts to develop new therapeutic or immunoprevention approaches have not been successful. After the publication of the T. cruzi genome, the number of molecular and biochemical studies on this parasite has increased considerably, many of which are focused on families of variant surface proteins, especially trans-sialidases, mucins, and mucin-associated proteins. The disperse gene protein 1 family (DGF-1) is one of the most abundant families in the T. cruzi genome; however, the large gene size, high copy numbers, and low antibody titers detected in infected humans make it an unattractive study target. However, here we argue that given the ubiquitous presence in all T. cruzi species, and physicochemical characteristics, the DGF-1 gene family may play and important role in host-parasite interactions.

Multi-omics analyses identify molecular signatures with prognostic values in different heart failure aetiologies

BACKGROUND

Heart failure (HF) is the leading cause of morbidity and mortality worldwide, and there is an urgent need for more global studies and data mining approaches to uncover its underlying mechanisms. Multiple omics techniques provide a more holistic molecular perspective to study pathophysiological events involved in the development of HF.

METHODS

In this study, we used a label-free whole myocardium multi-omics characterization from three commonly used mouse HF models: transverse aortic constriction (TAC), myocardial infarction (MI), and homozygous Phospholamban-R14del (PLN-R14^Δ/Δ). Genes, proteins, and metabolites were analysed for differential expression between each group and a corresponding control group. The core transcriptome and proteome datasets were used for enrichment analysis. For genes that were upregulated at both the RNA and protein levels in all models, clinical validation was performed by means of plasma level determination in patients with HF from the BIOSTAT-CHF cohort.

RESULTS

Cell death and tissue repair-related pathways were upregulated in all preclinical models. Fatty acid oxidation, ATP metabolism, and Energy derivation processes were downregulated in all investigated HF aetiologies. Putrescine, a metabolite known for its role in cell survival and apoptosis, demonstrated a 4.9-fold (p < 0.02) increase in PLN-R14^Δ/Δ, 2.7-fold (p < 0.005) increase in TAC mice, and 2.2-fold (p < 0.02) increase in MI mice. Four Biomarkers were associated with all-cause mortality (PRELP: Hazard ratio (95% confidence interval) 1.79(1.35, 2.39), p < 0.001; CKAP4: 1.38(1.21, 1.57), p < 0.001; S100A11: 1.37(1.13, 1.65), p = 0.001; Annexin A1 (ANXA1): 1.16(1.04, 1.29) p = 0.01), and three biomarkers were associated with HF-Related Rehospitalization, (PRELP: 1.88(1.4, 2.53), p < 0.001; CSTB: 1.15(1.05, 1.27), p = 0.003; CKAP4: 1.18(1.02, 1.35), P = 0.023).

CONCLUSIONS

Cell death and tissue repair pathways were significantly upregulated, and ATP and energy derivation processes were significantly downregulated in all models. Common pathways and biomarkers with potential clinical and prognostic associations merit further investigation to develop optimal management and therapeutic strategies for all HF aetiologies.

Using transcriptomics, proteomics and phosphoproteomics as new approach methodology (NAM) to define biological responses for chemical safety assessment

Omic-based technologies are of particular interest and importance for hazard identification and health risk characterization of chemicals. Their application in the new approach methodologies (NAMs) anchored on cellular toxicity pathways is based on the premise that any apical health endpoint change must be underpinned by some alterations at the omic levels. In the present study we examined the cellular responses to two chemicals, caffeine and coumarin, by generating and integrating multi-omic data from multi-dose and multi-time point transcriptomic, proteomic and phosphoproteomic experiments. We showed that the methodology presented here was able to capture the complete chain of events from the first chemical-induced changes at the phosphoproteome level, to changes in gene expression, and lastly to changes in protein abundance, each with vastly different points of departure (PODs). In HepG2 cells we found that the metabolism of lipids and general cellular stress response to be the dominant biological processes in response to caffeine and coumarin exposure, respectively. The phosphoproteomic changes were detected early in time, at very low doses and provided a fast, adaptive cellular response to chemical exposure with 7-37-fold lower points of departure comparing to the transcriptomics. Changes in protein abundance were found much less frequently than transcriptomic changes. While challenges remain, our study provides strong and novel evidence supporting the notion that these three omic technologies can be used in an integrated manner to facilitate a more complete understanding of pathway perturbations and POD determinations for risk assessment of chemical exposures.

Bromodomain-containing Protein 4 Regulates Innate Inflammation in Airway Epithelial Cells via Modulation of Alternative Splicing

Bromodomain-containing Protein 4 (BRD4) is a transcriptional regulator which coordinates gene expression programs controlling cancer biology, inflammation, and fibrosis. In airway viral infection, non-toxic BRD4-specific inhibitors (BRD4i) block the release of pro-inflammatory cytokines and prevent downstream remodeling. Although the chromatin modifying functions of BRD4 in inducible gene expression have been extensively investigated, its roles in post-transcriptional regulation are not as well understood. Based on its interaction with the transcriptional elongation complex and spliceosome, we hypothesize that BRD4 is a functional regulator of mRNA processing. To address this question, we combine data-independent analysis - parallel accumulation-serial fragmentation (diaPASEF) with RNA-sequencing to achieve deep and integrated coverage of the proteomic and transcriptomic landscapes of human small airway epithelial cells exposed to viral challenge and treated with BRD4i. The transcript-level data was further interrogated for alternative splicing analysis, and the resulting data sets were correlated to identify pathways subject to post-transcriptional regulation. We discover that BRD4 regulates alternative splicing of key genes, including Interferon-related Developmental Regulator 1 ( IFRD1 ) and X-Box Binding Protein 1 ( XBP1 ), related to the innate immune response and the unfolded protein response, respectively. These findings extend the transcriptional elongation-facilitating actions of BRD4 in control of post-transcriptional RNA processing in innate signaling.

Formation of low-density electrospun fibrous network integrated mesenchymal stem cell sheet

Cell sheets combined with electrospun fibrous mats represent an attractive approach for the repair and regeneration of injured tissues. However, the conventional dense electrospun mats as supportive substrates in forming "cell sheet on fiber mat" complexes suffer from problems of limiting the cellular function and eliciting a host response upon implantation. To give full play to the role of electrospun biomimicking fibers in forming quality cell sheets, this study proposed to develop a cell-fiber integrated sheet (CFIS) featuring a spatially homogeneous distribution of cells within the fiber structure by using a low-density fibrous network for cell sheet formation. A low-density electrospun polycaprolactone (PCL) fibrous network at a density of 103.8 ± 16.3 μg cm^-2 was produced by controlling the fiber deposition for a short period of 1 min and subsequently transferred onto polydimethylsiloxane rings for facilitating cell sheet formation, in which rat bone marrow-derived mesenchymal cells were used. Using a dense electrospun PCL fibrous mat (481.5 ± 7.5 μg cm^-2) as the control, it was found that cells on the low-density fibrous network (L-G) exhibited improved capacities in spreading, proliferation, stemness maintenance and matrix-remodeling during the process of CFIS formation. Structurally, the CFIS constructs revealed strong integration between the cells and the fibrous network, thus providing excellent cohesion and physical integrity to enable strengthening of the formed cell sheet. By contrast, the cell sheet formed on the dense fibrous mat (D-G) showed a two-layer (biphasic) structure due to the limitation of cellular invasion. Moreover, such engineered CFIS was identified with enhanced immunomodulatory effects by promoting LPS-stimulated macrophages towards an M2 phenotype in vitro. Our results suggest that the CFIS may be used as a native tissue equivalent "cell sheet" for improving the efficacy of the tissue engineering approach for the repair and regeneration of impaired tissues.