Metaboverse enables automated discovery and visualization of diverse metabolic regulatory patterns.

Metabolism is intertwined with various cellular processes, including controlling cell fate, influencing tumorigenesis, participating in stress responses and more. Metabolism is a complex, interdependent network, and local perturbations can have indirect effects that are pervasive across the metabolic network. Current analytical and technical limitations have long created a bottleneck in metabolic data interpretation. To address these shortcomings, we developed Metaboverse, a user-friendly tool to facilitate data exploration and hypothesis generation. Here we introduce algorithms that leverage the metabolic network to extract complex reaction patterns from data. To minimize the impact of missing measurements within the network, we introduce methods that enable pattern recognition across multiple reactions. Using Metaboverse, we identify a previously undescribed metabolite signature that correlated with survival outcomes in early stage lung adenocarcinoma patients. Using a yeast model, we identify metabolic responses suggesting an adaptive role of citrate homeostasis during mitochondrial dysfunction facilitated by the citrate transporter, Ctp1. We demonstrate that Metaboverse augments the user's ability to extract meaningful patterns from multi-omics datasets to develop actionable hypotheses.

TXNIP loss expands Myc-dependent transcriptional programs by increasing Myc genomic binding.

The c-Myc protooncogene places a demand on glucose uptake to drive glucose-dependent biosynthetic pathways. To meet this demand, c-Myc protein (Myc henceforth) drives the expression of glucose transporters, glycolytic enzymes, and represses the expression of thioredoxin interacting protein (TXNIP), which is a potent negative regulator of glucose uptake. A Mychigh/TXNIPlow gene signature is clinically significant as it correlates with poor clinical prognosis in triple-negative breast cancer (TNBC) but not in other subtypes of breast cancer, suggesting a functional relationship between Myc and TXNIP. To better understand how TXNIP contributes to the aggressive behavior of TNBC, we generated TXNIP null MDA-MB-231 (231:TKO) cells for our study. We show that TXNIP loss drives a transcriptional program that resembles those driven by Myc and increases global Myc genome occupancy. TXNIP loss allows Myc to invade the promoters and enhancers of target genes that are potentially relevant to cell transformation. Together, these findings suggest that TXNIP is a broad repressor of Myc genomic binding. The increase in Myc genomic binding in the 231:TKO cells expands the Myc-dependent transcriptome we identified in parental MDA-MB-231 cells. This expansion of Myc-dependent transcription following TXNIP loss occurs without an apparent increase in Myc's intrinsic capacity to activate transcription and without increasing Myc levels. Together, our findings suggest that TXNIP loss mimics Myc overexpression, connecting Myc genomic binding and transcriptional programs to the nutrient and progrowth signals that control TXNIP expression.

STAT3 and GR Cooperate to Drive Gene Expression and Growth of Basal-Like Triple-Negative Breast Cancer.

Breast cancers are divided into subtypes with different prognoses and treatment responses based on global differences in gene expression. Luminal breast cancer gene expression and proliferation are driven by estrogen receptor alpha, and targeting this transcription factor is the most effective therapy for this subtype. By contrast, it remains unclear which transcription factors drive the gene expression signature that defines basal-like triple-negative breast cancer, and there are no targeted therapies approved to treat this aggressive subtype. In this study, we utilized integrated genomic analysis of DNA methylation, chromatin accessibility, transcription factor binding, and gene expression in large collections of breast cancer cell lines and patient tumors to identify transcription factors responsible for the basal-like gene expression program. Glucocorticoid receptor (GR) and STAT3 bind to the same genomic regulatory regions, which were specifically open and unmethylated in basal-like breast cancer. These transcription factors cooperated to regulate expression of hundreds of genes in the basal-like gene expression signature, which were associated with poor prognosis. Combination treatment with small-molecule inhibitors of both transcription factors resulted in synergistic decreases in cell growth in cell lines and patient-derived organoid models. This study demonstrates that GR and STAT3 cooperate to regulate the basal-like breast cancer gene expression program and provides the basis for improved therapy for basal-like triple-negative breast cancer through rational combination of STAT3 and GR inhibitors. SIGNIFICANCE: This study demonstrates that GR and STAT3 cooperate to activate the canonical gene expression signature of basal-like triple-negative breast cancer and that combination treatment with STAT3 and GR inhibitors could provide synergistic therapeutic efficacy.

SV-plaudit: A cloud-based framework for manually curating thousands of structural variants.

SV-plaudit is a framework for rapidly curating structural variant (SV) predictions. For each SV, we generate an image that visualizes the coverage and alignment signals from a set of samples. Images are uploaded to our cloud framework where users assess the quality of each image using a client-side web application. Reports can then be generated as a tab-delimited file or annotated Variant Call Format (VCF) file. As a proof of principle, nine researchers collaborated for 1 hour to evaluate 1,350 SVs each. We anticipate that SV-plaudit will become a standard step in variant calling pipelines and the crowd-sourced curation of other biological results.Code available at https://github.com/jbelyeu/SV-plauditDemonstration video available at https://www.youtube.com/watch?v=ono8kHMKxDs.

Differential iridoid production as revealed by a diversity panel of 84 cultivated and wild blueberry species.

Cultivated blueberry (Vaccinium corymbosum, Vaccinium angustifolium, Vaccinium darrowii, and Vaccinium virgatum) is an economically important fruit crop native to North America and a member of the Ericaceae family. Several species in the Ericaceae family including cranberry, lignonberry, bilberry, and neotropical blueberry species have been shown to produce iridoids, a class of pharmacologically important compounds present in over 15 plant families demonstrated to have a wide range of biological activities in humans including anti-cancer, anti-bacterial, and anti-inflammatory. While the antioxidant capacity of cultivated blueberry has been well studied, surveys of iridoid production in blueberry have been restricted to fruit of a very limited number of accessions of V. corymbosum, V. angustifolium and V. virgatum; none of these analyses have detected iridoids. To provide a broader survey of iridoid biosynthesis in cultivated blueberry, we constructed a panel of 84 accessions representing a wide range of cultivated market classes, as well as wild blueberry species, and surveyed these for the presence of iridoids. We identified the iridoid glycoside monotropein in fruits and leaves of all 13 wild Vaccinium species, yet only five of the 71 cultivars. Monotropein positive cultivars all had recent introgressions from wild species, suggesting that iridoid production can be targeted through breeding efforts that incorporate wild germplasm. A series of diverse developmental tissues was also surveyed in the diversity panel, demonstrating a wide range in iridoid content across tissues. Taken together, this data provides the foundation to dissect the molecular and genetic basis of iridoid production in blueberry.