Single-Cell Transcriptome Atlas of Murine Endothelial Cells.

The heterogeneity of endothelial cells (ECs) across tissues remains incompletely inventoried. We constructed an atlas of >32,000 single-EC transcriptomes from 11 mouse tissues and identified 78 EC subclusters, including Aqp7+ intestinal capillaries and angiogenic ECs in healthy tissues. ECs from brain/testis, liver/spleen, small intestine/colon, and skeletal muscle/heart pairwise expressed partially overlapping marker genes. Arterial, venous, and lymphatic ECs shared more markers in more tissues than did heterogeneous capillary ECs. ECs from different vascular beds (arteries, capillaries, veins, lymphatics) exhibited transcriptome similarity across tissues, but the tissue (rather than the vessel) type contributed to the EC heterogeneity. Metabolic transcriptome analysis revealed a similar tissue-grouping phenomenon of ECs and heterogeneous metabolic gene signatures in ECs between tissues and between vascular beds within a single tissue in a tissue-type-dependent pattern. The EC atlas taxonomy enabled identification of EC subclusters in public scRNA-seq datasets and provides a powerful discovery tool and resource value.

Error modelled gene expression analysis (EMOGEA) provides a superior overview of time course RNA-seq measurements and low count gene expression.

Temporal RNA-sequencing (RNA-seq) studies of bulk samples provide an opportunity for improved understanding of gene regulation during dynamic phenomena such as development, tumor progression or response to an incremental dose of a pharmacotherapeutic. Moreover, single-cell RNA-seq (scRNA-seq) data implicitly exhibit temporal characteristics because gene expression values recapitulate dynamic processes such as cellular transitions. Unfortunately, temporal RNA-seq data continue to be analyzed by methods that ignore this ordinal structure and yield results that are often difficult to interpret. Here, we present Error Modelled Gene Expression Analysis (EMOGEA), a framework for analyzing RNA-seq data that incorporates measurement uncertainty, while introducing a special formulation for those acquired to monitor dynamic phenomena. This method is specifically suited for RNA-seq studies in which low-count transcripts with small-fold changes lead to significant biological effects. Such transcripts include genes involved in signaling and non-coding RNAs that inherently exhibit low levels of expression. Using simulation studies, we show that this framework down-weights samples that exhibit extreme responses such as batch effects allowing them to be modeled with the rest of the samples and maintain the degrees of freedom originally envisioned for a study. Using temporal experimental data, we demonstrate the framework by extracting a cascade of gene expression waves from a well-designed RNA-seq study of zebrafish embryogenesis and an scRNA-seq study of mouse pre-implantation and provide unique biological insights into the regulation of genes in each wave. For non-ordinal measurements, we show that EMOGEA has a much higher rate of true positive calls and a vanishingly small rate of false negative discoveries compared to common approaches. Finally, we provide two packages in Python and R that are self-contained and easy to use, including test data.

Valvular Prostaglandins Are Elevated in Severe Human Aortic Valve Stenosis.

BACKGROUND: Aortic valve stenosis (AVS) is the most common valvular disease in the developed world. AVS involves the progressive fibrocalcific remodeling of the aortic valve (AV), which impairs function and can ultimately lead to heart failure. Due to gaps in our understanding of the underlying mechanisms of AVS, there are no pharmacological treatments or dietary interventions known to slow AVS progression. Recent studies have begun to suggest oxylipins-a class of bioactive lipids-may be dysregulated in the valves of patients with AVS. METHODS: We utilized high-performance liquid chromatography-tandem mass spectrometry to conduct a targeted oxylipin analysis on human AV tissue and plasma from a cohort of 110 patients undergoing AV surgery. RESULTS: We identified 36 oxylipins in human AV tissue with all showing significant increase in patients with severe AVS. A multivariate model including patient characteristics and valvular oxylipins identified the arachidonic acid-COX (cyclooxygenase) pathway-derived prostanoids to be the most associated with AVS severity. Plasma oxylipin levels were measured in a subset of AV surgery patients and compared with a control group of healthy participants, showing distinct oxylipin profiles between control and disease. CONCLUSIONS: Our comprehensive analysis of oxylipins in the human AV identified the inflammatory and osteogenic regulating prostanoids to be positively correlated with AVS severity. This elucidation of prostanoid dysregulation warrants further research into COX inhibition to mitigate AVS.

BIOMEX: an interactive workflow for (single cell) omics data interpretation and visualization.

The amount of biological data, generated with (single cell) omics technologies, is rapidly increasing, thereby exacerbating bottlenecks in the data analysis and interpretation of omics experiments. Data mining platforms that facilitate non-bioinformatician experimental scientists to analyze a wide range of experimental designs and data types can alleviate such bottlenecks, aiding in the exploration of (newly generated or publicly available) omics datasets. Here, we present BIOMEX, a browser-based software, designed to facilitate the Biological Interpretation Of Multi-omics EXperiments by bench scientists. BIOMEX integrates state-of-the-art statistical tools and field-tested algorithms into a flexible but well-defined workflow that accommodates metabolomics, transcriptomics, proteomics, mass cytometry and single cell data from different platforms and organisms. The BIOMEX workflow is accompanied by a manual and video tutorials that provide the necessary background to navigate the interface and get acquainted with the employed methods. BIOMEX guides the user through omics-tailored analyses, such as data pretreatment and normalization, dimensionality reduction, differential and enrichment analysis, pathway mapping, clustering, marker analysis, trajectory inference, meta-analysis and others. BIOMEX is fully interactive, allowing users to easily change parameters and generate customized plots exportable as high-quality publication-ready figures. BIOMEX is open source and freely available at https://www.vibcancer.be/software-tools/biomex.

EndoDB: a database of endothelial cell transcriptomics data.

Endothelial cells (ECs) line blood vessels, regulate homeostatic processes (blood flow, immune cell trafficking), but are also involved in many prevalent diseases. The increasing use of high-throughput technologies such as gene expression microarrays and (single cell) RNA sequencing generated a wealth of data on the molecular basis of EC (dys-)function. Extracting biological insight from these datasets is challenging for scientists who are not proficient in bioinformatics. To facilitate the re-use of publicly available EC transcriptomics data, we developed the endothelial database EndoDB, a web-accessible collection of expert curated, quality assured and pre-analyzed data collected from 360 datasets comprising a total of 4741 bulk and 5847 single cell endothelial transcriptomes from six different organisms. Unlike other added-value databases, EndoDB allows to easily retrieve and explore data of specific studies, determine under which conditions genes and pathways of interest are deregulated and assess reprogramming of metabolism via principal component analysis, differential gene expression analysis, gene set enrichment analysis, heatmaps and metabolic and transcription factor analysis, while single cell data are visualized as gene expression color-coded t-SNE plots. Plots and tables in EndoDB are customizable, downloadable and interactive. EndoDB is freely available at https://vibcancer.be/software-tools/endodb, and will be updated to include new studies.

Single-Cell RNA Sequencing Reveals Renal Endothelium Heterogeneity and Metabolic Adaptation to Water Deprivation.

BACKGROUND: Renal endothelial cells from glomerular, cortical, and medullary kidney compartments are exposed to different microenvironmental conditions and support specific kidney processes. However, the heterogeneous phenotypes of these cells remain incompletely inventoried. Osmotic homeostasis is vitally important for regulating cell volume and function, and in mammals, osmotic equilibrium is regulated through the countercurrent system in the renal medulla, where water exchange through endothelium occurs against an osmotic pressure gradient. Dehydration exposes medullary renal endothelial cells to extreme hyperosmolarity, and how these cells adapt to and survive in this hypertonic milieu is unknown. METHODS: We inventoried renal endothelial cell heterogeneity by single-cell RNA sequencing >40,000 mouse renal endothelial cells, and studied transcriptome changes during osmotic adaptation upon water deprivation. We validated our findings by immunostaining and functionally by targeting oxidative phosphorylation in a hyperosmolarity model in vitro and in dehydrated mice in vivo. RESULTS: We identified 24 renal endothelial cell phenotypes (of which eight were novel), highlighting extensive heterogeneity of these cells between and within the cortex, glomeruli, and medulla. In response to dehydration and hypertonicity, medullary renal endothelial cells upregulated the expression of genes involved in the hypoxia response, glycolysis, and-surprisingly-oxidative phosphorylation. Endothelial cells increased oxygen consumption when exposed to hyperosmolarity, whereas blocking oxidative phosphorylation compromised endothelial cell viability during hyperosmotic stress and impaired urine concentration during dehydration. CONCLUSIONS: This study provides a high-resolution atlas of the renal endothelium and highlights extensive renal endothelial cell phenotypic heterogeneity, as well as a previously unrecognized role of oxidative phosphorylation in the metabolic adaptation of medullary renal endothelial cells to water deprivation.

Prebiotic effects of diet supplemented with the cultivated red seaweed Chondrus crispus or with fructo-oligo-saccharide on host immunity, colonic microbiota and gut microbial metabolites.

BACKGROUND: Gastrointestinal microbial communities are diverse and are composed of both beneficial and pathogenic groups. Prebiotics, such as digestion-resistant fibers, influence the composition of gut microbiota, and can contribute to the improvement of host health. The red seaweed Chondrus crispus is rich in dietary fiber and oligosaccharides, however its prebiotic potential has not been studied to date. METHODS: Prebiotic effects were investigated with weaning rats fed a cultivated C. crispus-supplemented diet. Comparison standards included a fructo-oligo-saccharide (FOS) diet and a basal diet. The colonic microbiome was profiled with a 16S rRNA sequencing-based Phylochip array. Concentrations of short chain fatty acids (SCFAs) in the feacal samples were determined by gas chromatography with a flame ionization detector (GC-FID) analysis. Immunoglobulin levels in the blood plasma were analyzed with an enzyme-linked immunosorbent assay (ELISA). Histo-morphological parameters of the proximal colon tissue were characterized by hematoxylin and eosin (H&E) staining. RESULTS: Phylochip array analysis indicated differing microbiome composition among the diet-supplemented and the control groups, with the C. crispus group (2.5% supplementation) showing larger separation from the control than other treatment groups. In the 2.5% C. crispus group, the population of beneficial bacteria such as Bifidobacterium breve increased (4.9-fold, p=0.001), and the abundance of pathogenic species such as Clostridium septicum and Streptococcus pneumonia decreased. Higher concentrations of short chain fatty acids (i.e., gut microbial metabolites), including acetic, propionic and butyric acids, were found in faecal samples of the C. crispus-fed rats. Furthermore, both C. crispus and FOS supplemented rats showed significant improvements in proximal colon histo-morphology. Higher faecal moisture was noted in the 2.5% C. crispus group, and elevated plasma immunoglobulin (IgA and IgG) levels were observed in the 0.5% C. crispus group, as compared to the basal feed group. CONCLUSIONS: The results suggest multiple prebiotic effects, such as influencing the composition of gut microbial communities, improvement of gut health and immune modulation in rats supplemented with cultivated C. crispus.

2D NMR barcoding and differential analysis of complex mixtures for chemical identification: the Actaea triterpenes.

The interpretation of NMR spectroscopic information for structure elucidation involves decoding of complex resonance patterns that contain valuable molecular information (δ and J), which is not readily accessible otherwise. We introduce a new concept of 2D-NMR barcoding that uses clusters of fingerprint signals and their spatial relationships in the δ-δ coordinate space to facilitate the chemical identification of complex mixtures. Similar to widely used general barcoding technology, the structural information of individual compounds is encoded as a specifics pattern of their C,H correlation signals. Software-based recognition of these patterns enables the structural identification of the compounds and their discrimination in mixtures. Using the triterpenes from various Actaea (syn. Cimicifuga) species as a test case, heteronuclear multiple-bond correlation (HMBC) barcodes were generated on the basis of their structural subtypes from a statistical investigation of their δH and δC data in the literature. These reference barcodes allowed in silico identification of known triterpenes in enriched fractions obtained from an extract of A. racemosa (black cohosh). After dereplication, a differential analysis of heteronuclear single-quantum correlation (HSQC) spectra even allowed for the discovery of a new triterpene. The 2D barcoding concept has potential application in a natural product discovery project, allowing for the rapid dereplication of known compounds and as a tool in the search for structural novelty within compound classes with established barcodes.

Distinguishing Vaccinium species by chemical fingerprinting based on NMR spectra, validated with spectra collected in different laboratories.

A method was developed to distinguish Vaccinium species based on leaf extracts using nuclear magnetic resonance spectroscopy. Reference spectra were measured on leaf extracts from several species, including lowbush blueberry (Vaccinium angustifolium), oval leaf huckleberry (Vaccinium ovalifolium), and cranberry (Vaccinium macrocarpon). Using principal component analysis, these leaf extracts were resolved in the scores plot. Analysis of variance statistical tests demonstrated that the three groups differ significantly on PC2, establishing that the three species can be distinguished by nuclear magnetic resonance. Soft independent modeling of class analogies models for each species also showed discrimination between species. To demonstrate the robustness of nuclear magnetic resonance spectroscopy for botanical identification, spectra of a sample of lowbush blueberry leaf extract were measured at five different sites, with different field strengths (600 versus 700 MHz), different probe types (cryogenic versus room temperature probes), different sample diameters (1.7 mm versus 5 mm), and different consoles (Avance I versus Avance III). Each laboratory independently demonstrated the linearity of their NMR measurements by acquiring a standard curve for chlorogenic acid (R(2) = 0.9782 to 0.9998). Spectra acquired on different spectrometers at different sites classifed into the expected group for the Vaccinium spp., confirming the utility of the method to distinguish Vaccinium species and demonstrating nuclear magnetic resonance fingerprinting for material validation of a natural health product.

Consumption of Apigenin Prevents Radiation-induced Gut Dysbiosis in Male C57BL/6J Mice Exposed to Silicon Ions.

The search for medical treatments to prevent radiation-induced damage to gastrointestinal tissue is crucial as such injuries can be fatal. This study aimed to investigate the effects of apigenin (AP) on the gut microbiome of irradiated mice, as it is a promising radiation countermeasure. Male C57BL/6J mice were divided into four groups, with six mice in each group. Two groups were given food with apigenin (20 mg/kg body weight or AP 20) before and after exposure to 0 or 50 cGy of silicon (28Si) ions, while another two groups of mice received regular diet without apigenin (0 mg/kg body weight or AP 0) before and after irradiation. The duodenum, the primary site for oral AP absorption, was collected from each mouse seven days after radiation exposure. Using 16S rRNA amplicon sequencing, we found significant differences in microbial diversity among groups. Firmicutes and Bacteroidetes were the major phyla for all groups, while actinobacterial and proteobacterial sequences represented only a small percentage. Mice not given dietary apigenin had a higher Firmicutes and Bacteroidetes (F/B) ratio and an imbalanced duodenal microbiota after exposure to radiation, while irradiated mice given apigenin had maintained homeostasis of the microbiota. Additionally, irradiated mice not given apigenin had decreased probiotic bacteria abundance and increased inflammation, while apigenin-supplemented mice had reduced inflammation and restored normal histological structure. In conclusion, our results demonstrate the potential of dietary apigenin as a countermeasure against radiation-induced gut injuries due to its anti-inflammatory activity, reduction of gut microbiota dysbiosis, and increase in probiotic bacteria (e.g., Lachnospiraceae, Muribaculaceae and Bifidobacteriaceae).

Intron retention is a mechanism of erythropoietin regulation in brain cell models.

Intron retention is a mechanism of post-transcriptional gene regulation, including genes involved in erythropoiesis. Erythropoietin (EPO) is a hormone without evidence of intracellular vesicle storage that regulates erythropoiesis. We hypothesize that EPO uses intron retention as a mechanism of post-transcriptional regulation in response to hypoxia and ischemia. Cell models of hypoxia and ischemia for kidney, liver, and brain cells were examined for intron retention by real time quantitative PCR. EPO expression increased in most cells except for blood brain barrier and liver cells. The intron retained transcript ratio decreased in brain cells, except for Astrocytes, but showed no change in kidney or liver after 24 h of ischemia. The shift in intron ratio was maintained when using poly (A) enriched cDNA, suggesting that intron retention is not due to immature transcripts. The expression of EPO was elevated at variable time points amongst cell models with the intron ratio also changing over a time course of 2 to 16 h after ischemia. We conclude that intron retention is a mechanism regulating EPO expression in response to ischemia in a tissue specific manner.

Immuno-informatics study identifies conserved T cell epitopes in non-structural proteins of Bluetongue virus serotypes: formulation of a computationally optimized next-generation broad-spectrum multi-epitope vaccine.

Introduction: Bluetongue (BT) poses a significant threat to the livestock industry, affecting various animal species and resulting in substantial economic losses. The existence of numerous BT virus (BTV) serotypes has hindered control efforts, highlighting the need for broad-spectrum vaccines. Methodology: In this study, we evaluated the conserved amino acid sequences within key non-structural (NS) proteins of BTV and identified numerous highly conserved murine- and bovine-specific MHC class I-restricted (MHC-I) CD8+ and MHC-II-restricted CD4+ epitopes. We then screened these conserved epitopes for antigenicity, allergenicity, toxicity, and solubility. Using these epitopes, we developed in silico-based broad-spectrum multiepitope vaccines with Toll-like receptor (TLR-4) agonists. The predicted proinflammatory cytokine response was assessed in silico using the C-IMMSIM server. Structural modeling and refinement were achieved using Robetta and GalaxyWEB servers. Finally, we assessed the stability of the docking complexes through extensive 100-nanosecond molecular dynamics simulations before considering the vaccines for codon optimization and in silico cloning. Results: We found many epitopes that meet these criteria within NS1 and NS2 proteins and developed in silico broad-spectrum vaccines. The immune simulation studies revealed that these vaccines induce high levels of IFN-γ and IL-2 in the vaccinated groups. Protein-protein docking analysis demonstrated promising epitopes with strong binding affinities to TLR-4. The docked complexes were stable, with minimal Root Mean Square Deviation and Root Mean Square Fluctuation values. Finally, the in silico-cloned plasmids have high % of GC content with > 0.8 codon adaptation index, suggesting they are suitable for expressing the protein vaccines in prokaryotic system. Discussion: These next-generation vaccine designs are promising and warrant further investigation in wet lab experiments to assess their immunogenicity, safety, and efficacy for practical application in livestock. Our findings offer a robust framework for developing a comprehensive, broad-spectrum vaccine, potentially revolutionizing BT control and prevention strategies in the livestock industry.

Peroxisome deficiency underlies failures in hepatic immune cell development and antigen presentation in a severe Zellweger disease model.

Peroxisome biogenesis disorders (PBDs) represent a group of metabolic conditions that cause severe developmental defects. Peroxisomes are essential metabolic organelles, present in virtually every eukaryotic cell and mediating key processes in immunometabolism. To date, the full spectrum of PBDs remains to be identified, and the impact PBDs have on immune function is unexplored. This study presents a characterization of the hepatic immune compartment of a neonatal PBD mouse model at single-cell resolution to establish the importance and function of peroxisomes in developmental hematopoiesis. We report that hematopoietic defects are a feature in a severe PBD murine model. Finally, we identify a role for peroxisomes in the regulation of the major histocompatibility class II expression and antigen presentation to CD4+ T cells in dendritic cells. This study adds to our understanding of the mechanisms of PBDs and expands our knowledge of the role of peroxisomes in immunometabolism.

Dereplication, residual complexity, and rational naming: the case of the Actaea triterpenes.

The genus Actaea (including Cimicifuga) has been the source of ∼200 cycloartane triterpenes. While they are major bioactive constituents of complementary and alternative medicines, their structural similarity is a major dereplication problem. Moreover, their trivial names seldom indicate the actual structure. This project develops two new tools for Actaea triterpenes that enable rapid dereplication of more than 170 known triterpenes and facilitates elucidation of new compounds. A predictive computational model based on classification binary trees (CBTs) allows in silico determination of the aglycone type. This tool utilizes the Me (1)H NMR chemical shifts and has potential to be applicable to other natural products. Actaea triterpene dereplication is supported by a new systematic naming scheme. A combination of CBTs, (1)H NMR deconvolution, characteristic (1)H NMR signals, and quantitative (1)H NMR (qHNMR) led to the unambiguous identification of minor constituents in residually complex triterpene samples. Utilizing a 1.7 mm cryo-microprobe at 700 MHz, qHNMR enabled characterization of residual complexity at the 10-20 µg level in a 1-5 mg sample. The identification of five co-occurring minor constituents, belonging to four different triterpene skeleton types, in a repeatedly purified natural product emphasizes the critical need for the evaluation of residual complexity of reference materials, especially when used for biological assessment.

CD8+ T cell metabolic rewiring defined by scRNA-seq identifies a critical role of ASNS expression dynamics in T cell differentiation.

T cells dynamically rewire their metabolism during an immune response. We applied single-cell RNA sequencing to CD8+ T cells activated and differentiated in vitro in physiological medium to resolve these metabolic dynamics. We identify a differential time-dependent reliance of activating T cells on the synthesis versus uptake of various non-essential amino acids, which we corroborate with functional assays. We also identify metabolic genes that potentially dictate the outcome of T cell differentiation, by ranking them based on their expression dynamics. Among them, we find asparagine synthetase (Asns), whose expression peaks for effector T cells and decays toward memory formation. Disrupting these expression dynamics by ASNS overexpression promotes an effector phenotype, enhancing the anti-tumor response of adoptively transferred CD8+ T cells in a mouse melanoma model. We thus provide a resource of dynamic expression changes during CD8+ T cell activation and differentiation, and identify ASNS expression dynamics as a modulator of CD8+ T cell differentiation.

Molecular characterization of zebrafish embryogenesis via DNA microarrays and multiplatform time course metabolomics studies.

One of the greatest strengths of "-omics" technologies is their ability to capture a molecular snapshot of multiple cellular processes simultaneously. Transcriptomics, proteomics, and metabolomics have, individually, been used in wide-ranging studies involving cell lines, tissues, model organisms, and human subjects. Nonetheless, despite the fact that their power lies in the global acquisition of parallel data streams, these methods continue to be employed separately. We highlight work done to merge transcriptomics and metabolomics technologies to study zebrafish (Danio rerio) embryogenesis. We combine information from three bioanalytical platforms, that is, DNA microarrays, (1)H nuclear magnetic resonance ((1)H NMR), and mass spectrometry (MS)-based metabolomics, to identify and provide insights into the organism's developmental regulators. We apply a customized approach to the analysis of such time-ordered measurements to provide temporal profiles that depict the modulation of metabolites and gene transcription. Initially, the three data sets were analyzed individually but later they were fused to highlight the advantages gained through such an integrated approach. Unique challenges posed by fusion of such data are discussed given differences in the measurement error structures, the wide dynamic range for the molecular species, and the analytical platforms used to measure them (i.e., fluorescence ratios, NMR, and MS intensities). Our data analysis reveals that changes in transcript levels at specific developmental stages correlate with previously published data with over 90% accuracy. In addition, transcript profiles exhibited trends that were similar to the accumulation of metabolites over time. Profiles for metabolites such as choline-like compounds (Trimethylamine-N-oxide, phosphocholine, betaine), creatinine/creatine, and other metabolites involved in energy metabolism exhibited a steady increase from 15 hours post fertilization (hpf) to 48 hpf. Other metabolite and transcript profiles were transiently rising and then falling back to baseline. The "house keeping" metabolites such as branched chain amino acids exhibited a steady presence throughout embryogenesis. Although the transcript profiling corresponds to only 16 384 genes, a subset of the total number of genes in the zebrafish genome, we identified examples where gene transcript and metabolite profiles correlate with one another, reflective of a relationship between gene and metabolite regulation over the course of embryogenesis.

Integrating Proteomes for Lung Tissues and Lavage Reveals Pathways That Link Responses in Allergen-Challenged Mice.

To capture interplay between biological pathways, we analyzed the proteome from matched lung tissues and bronchoalveolar lavage fluid (BALF) of individual allergen-naïve and house dust mite (HDM)-challenged BALB/c mice, a model of allergic asthma. Unbiased label-free liquid chromatography with tandem mass spectrometry (LC-MS/MS) analysis quantified 2675 proteins from tissues and BALF of allergen-naïve and HDM-exposed mice. In comparing the four datasets, we found significantly greater diversity in proteins between lung tissues and BALF than in the changes induced by HDM challenge. The biological pathways enriched after allergen exposure were compartment-dependent. Lung tissues featured innate immune responses and oxidative stress, while BALF most strongly revealed changes in metabolism. We combined lung tissues and BALF proteomes, which principally highlighted oxidation reduction (redox) pathways, a finding influenced chiefly by the lung tissue dataset. Integrating lung and BALF proteomes also uncovered new proteins and biological pathways that may mediate lung tissue and BALF interactions after allergen challenge, for example, B-cell receptor signaling. We demonstrate that enhanced insight is fostered when different biological compartments from the lung are investigated in parallel. Integration of proteomes from lung tissues and BALF compartments reveals new information about protein networks in response to environmental challenge and interaction between intracellular and extracellular processes.

Tumor vessel co-option probed by single-cell analysis.

Tumor vessel co-option is poorly understood, yet it is a resistance mechanism against anti-angiogenic therapy (AAT). The heterogeneity of co-opted endothelial cells (ECs) and pericytes, co-opting cancer and myeloid cells in tumors growing via vessel co-option, has not been investigated at the single-cell level. Here, we use a murine AAT-resistant lung tumor model, in which VEGF-targeting induces vessel co-option for continued growth. Single-cell RNA sequencing (scRNA-seq) of 31,964 cells reveals, unexpectedly, a largely similar transcriptome of co-opted tumor ECs (TECs) and pericytes as their healthy counterparts. Notably, we identify cell types that might contribute to vessel co-option, i.e., an invasive cancer-cell subtype, possibly assisted by a matrix-remodeling macrophage population, and another M1-like macrophage subtype, possibly involved in keeping or rendering vascular cells quiescent.

Integrator restrains paraspeckles assembly by promoting isoform switching of the lncRNA NEAT1.

RNA 3' end processing provides a source of transcriptome diversification which affects various (patho)-physiological processes. A prime example is the transcript isoform switch that leads to the read-through expression of the long non-coding RNA NEAT1_2, at the expense of the shorter polyadenylated transcript NEAT1_1. NEAT1_2 is required for assembly of paraspeckles (PS), nuclear bodies that protect cancer cells from oncogene-induced replication stress and chemotherapy. Searching for proteins that modulate this event, we identified factors involved in the 3' end processing of polyadenylated RNA and components of the Integrator complex. Perturbation experiments established that, by promoting the cleavage of NEAT1_2, Integrator forces NEAT1_2 to NEAT1_1 isoform switching and, thereby, restrains PS assembly. Consistently, low levels of Integrator subunits correlated with poorer prognosis of cancer patients exposed to chemotherapeutics. Our study establishes that Integrator regulates PS biogenesis and a link between Integrator, cancer biology, and chemosensitivity, which may be exploited therapeutically.

Heterogeneous Effects of Calorie Content and Nutritional Components Underlie Dietary Influence on Pancreatic Cancer Susceptibility.

Pancreatic cancer is a rare but fatal form of cancer, the fourth highest in absolute mortality. Known risk factors include obesity, diet, and type 2 diabetes; however, the low incidence rate and interconnection of these factors confound the isolation of individual effects. Here, we use epidemiological analysis of prospective human cohorts and parallel tracking of pancreatic cancer in mice to dissect the effects of obesity, diet, and diabetes on pancreatic cancer. Through longitudinal monitoring and multi-omics analysis in mice, we found distinct effects of protein, sugar, and fat dietary components, with dietary sugars increasing Mad2l1 expression and tumor proliferation. Using epidemiological approaches in humans, we find that dietary sugars give a MAD2L1 genotype-dependent increased susceptibility to pancreatic cancer. The translation of these results to a clinical setting could aid in the identification of the at-risk population for screening and potentially harness dietary modification as a therapeutic measure.