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The use of digital pathology for the histomorphologic profiling of pathological specimens is expanding the precision and specificity of quantitative tissue analysis at an unprecedented scale; thus, enabling the discovery of new and functionally relevant histological features of both predictive and prognostic significance. In this study, we apply quantitative automated image processing and computational methods to profile the subcellular distribution of the multi-functional transcriptional regulator, Kaiso (ZBTB33), in the tumors of a large racially diverse breast cancer cohort from a designated health disparities region in the United States. Multiplex multivariate analysis of the association of Kaiso’s subcellular distribution with other breast cancer biomarkers reveals novel functional and predictive linkages between Kaiso and the autophagy-related proteins, LC3A/B, that are associated with features of the tumor immune microenvironment, survival, and race. These findings identify effective modalities of Kaiso biomarker assessment and uncover unanticipated insights into Kaiso’s role in breast cancer progression.Through automated image analysis, Singhal et al quantify nuclear versus cytoplasmic distribution of the Kaiso transcription factor in breast cancer patient tissue. They find that Kaiso distribution correlates with breast cancer subtype and overall survival, and discover a link between cytoplasmic Kaiso and autophagy marker LC3.

Women of African ancestry suffer higher rates of breast cancer mortality compared with all other groups in the United States. Though the precise reasons for these disparities remain unclear, many recent studies have implicated a role for differences in tumor biology. Using an epitope-validated antibody against the endoplasmic reticulum–associated E3 ligase, gp78, we show that elevated levels of gp78 in patient breast cancer cells predict poor survival. Moreover, high levels of gp78 are associated with poor outcomes in both ER + and ER – tumors, and breast cancers expressing elevated amounts of gp78 protein are enriched in gene expression pathways that influence cell cycle, metabolism, receptor-mediated signaling, and cell stress response pathways. In multivariate analysis adjusted for subtype and grade, gp78 protein is an independent predictor of poor outcomes in women of African ancestry. Furthermore, gene expression signatures, derived from patients stratified by gp78 protein expression, are strong predictors of recurrence and pathological complete response in retrospective clinical trial data and share many common features with gene sets previously identified to be overrepresented in breast cancers based on race. These findings implicate a prominent role for gp78 in tumor progression and offer insights into our understanding of racial differences in breast cancer outcomes.

A microcosm study was performed to investigate the effect of ethanol and acetate on uranium(VI) biological reduction and microbial community changes under various geochemical conditions. Each microcosm contained an uranium-contaminated sediment (up to 2.8 g U/kg) suspended in buffer with bicarbonate at concentrations of either 1 or 40 mM and sulfate at either 1.1 or 3.2 mM. Ethanol or acetate was used as an electron donor. Results indicate that ethanol yielded in significantly higher U(VI) reduction rates than acetate. A low bicarbonate concentration (1 mM) was favored for U(VI) bioreduction to occur in sediments, but high concentrations of bicarbonate (40 mM) and sulfate (3.2 mM) decreased the reduction rates of U(VI). Microbial communities were dominated by species from the Geothrix genus and Proteobacteria phylum in all microcosms. However, species in the Geobacteraceae family capable of reducing U(VI) were significantly enriched by ethanol and acetate in low-bicarbonate buffer. Ethanol increased the population of unclassified Desulfuromonales, while acetate increased the population of Desulfovibrio. Additionally, species in the Geobacteraceae family were not enriched in high-bicarbonate buffer, but the Geothrix and the unclassified Betaproteobacteria species were enriched. This study concludes that ethanol could be a better electron donor than acetate for reducing U(VI) under given experimental conditions, and electron donor and groundwater geochemistry alter microbial communities responsible for U(VI) reduction.

Microbial communities were characterized at contaminated sites that had elevated levels of nitrate, nickel, aluminum, and uranium (up to 690 mM, 310 μM, 42 mM, and 30 μM, respectively). The bacterial community structure based upon clonal libraries of the SSU rRNA genes (screened clones = 876) was diverse at the background site, but the three acidic samples had decreased diversity and the majority of clones were closely related to Azoarcus and Pseudomonas species. Arthrobacter and Novosphingobium sequences were recovered from the background samples but not the acidic sites, and similar pseudomonad populations were present at the background and acidic sites albeit at different relative abundances. Heterologous sequence coverage analyses indicated the microbial communities at the contaminated sites were very similar ( p = 0.001) but different from the background site. Bacterial isolates ( n = 67) classified as β-or γ- Proteobacteria, high G+C Gram-positive or low G+C Gram-positive were obtained from the background and one contaminated sample, and some of the isolates had less than 95% sequence identity with previously observed microorganisms. Despite variations in nitrate and heavy metal levels and different proximities to the source ponds, the three acidic samples had similar microbial populations. However, the least contaminated site (lowest nitrate and aluminum) had increased diversity compared to the other acidic samples. The results suggested that the combined contamination has decreased the microbial diversity, and Azoarcus populations were observed at a drastically increased frequency compared to the background site that had a more even distribution of multiple taxa.

Abstract The transcriptome of Nitrosomonas europaea was analyzed with whole-genome microarrays. Growing cells were compared to cells deprived of (NH4)2SO4 and Na2CO3. Hybridization signals were detected for 76% of the genes represented on the array under either or both conditions. Transcript levels for 68% of the genes were at least twofold higher in growing cells than in deprived cells, while only 0.42% of the genes were present at more than twofold higher levels in deprived cells. Transcript levels for the remaining 7% of the genes did not change significantly with the treatments. These trends were confirmed for selected genes by Northern hybridizations and quantitative RT-PCR. Compared to heterotrophic bacteria, N. europaea downregulates a greater proportion of its genes and fewer genes appear to be associated with the adaptation to starvation.

Genetic studies have identified ≥240 loci associated with the risk of type 2 diabetes (T2D), yet most of these loci lie in non-coding regions, masking the underlying molecular mechanisms. Recent studies investigating mRNA expression in human pancreatic islets have yielded important insights into the molecular drivers of normal islet function and T2D pathophysiology. However, similar studies investigating microRNA (miRNA) expression remain limited. Here, we present data from 63 individuals, the largest sequencing-based analysis of miRNA expression in human islets to date. We characterized the genetic regulation of miRNA expression by decomposing the expression of highly heritable miRNAs into cis- and trans-acting genetic components and mapping cis-acting loci associated with miRNA expression [miRNA-expression quantitative trait loci (eQTLs)]. We found i) 84 heritable miRNAs, primarily regulated by trans-acting genetic effects, and ii) 5 miRNA-eQTLs. We also used several different strategies to identify T2D-associated miRNAs. First, we colocalized miRNA-eQTLs with genetic loci associated with T2D and multiple glycemic traits, identifying one miRNA, miR-1908, that shares genetic signals for blood glucose and glycated hemoglobin (HbA1c). Next, we intersected miRNA seed regions and predicted target sites with credible set SNPs associated with T2D and glycemic traits and found 32 miRNAs that may have altered binding and function due to disrupted seed regions. Finally, we performed differential expression analysis and identified 14 miRNAs associated with T2D status—including miR-187-3p, miR-21-5p, miR-668, and miR-199b-5p—and 4 miRNAs associated with a polygenic score for HbA1c levels—miR-216a, miR-25, miR-30a-3p, and miR-30a-5p.

Complete characterization of the genetic effects on gene expression is needed to elucidate tissue biology and the etiology of complex traits. In the present study, we analyzed 2,344 subcutaneous adipose tissue samples and identified 34,774 conditionally distinct expression quantitative trait locus (eQTL) signals at 18,476 genes. Over half of eQTL genes exhibited at least two eQTL signals. Compared with primary eQTL signals, nonprimary eQTL signals had lower effect sizes, lower minor allele frequencies and less promoter enrichment; they corresponded to genes with higher heritability and higher tolerance for loss of function. Colocalization of eQTLs with genome-wide association study (GWAS) signals for 28 cardiometabolic traits identified 1,835 genes. Inclusion of nonprimary eQTL signals increased discovery of colocalized GWAS–eQTL signals by 46%. Furthermore, 21 genes with ≥2 colocalized GWAS–eQTL signals showed a mediating gene dosage effect on the GWAS trait. Thus, expanded eQTL identification reveals more mechanisms underlying complex traits and improves understanding of the complexity of gene expression regulation. This study introduces AdipoExpress, an eQTL meta-analysis of 2,344 subcutaneous adipose tissue samples, which triples the size of previous studies and expands the discovery of eQTLs colocalized with GWAS signals for cardiometabolic traits.

Aims/hypothesis Disruption of pancreatic islet function and glucose homeostasis can lead to the development of sustained hyperglycaemia, beta cell glucotoxicity and subsequently type 2 diabetes. In this study, we explored the effects of in vitro hyperglycaemic conditions on human pancreatic islet gene expression across 24 h in six pancreatic cell types: alpha; beta; gamma; delta; ductal; and acinar. We hypothesised that genes associated with hyperglycaemic conditions may be relevant to the onset and progression of diabetes. Methods We exposed human pancreatic islets from two donors to low (2.8 mmol/l) and high (15.0 mmol/l) glucose concentrations over 24 h in vitro. To assess the transcriptome, we performed single-cell RNA-seq (scRNA-seq) at seven time points. We modelled time as both a discrete and continuous variable to determine momentary and longitudinal changes in transcription associated with islet time in culture or glucose exposure. Additionally, we integrated genomic features and genetic summary statistics to nominate candidate effector genes. For three of these genes, we functionally characterised the effect on insulin production and secretion using CRISPR interference to knock down gene expression in EndoC-βH1 cells, followed by a glucose-stimulated insulin secretion assay. Results In the discrete time models, we identified 1344 genes associated with time and 668 genes associated with glucose exposure across all cell types and time points. In the continuous time models, we identified 1311 genes associated with time, 345 genes associated with glucose exposure and 418 genes associated with interaction effects between time and glucose across all cell types. By integrating these expression profiles with summary statistics from genetic association studies, we identified 2449 candidate effector genes for type 2 diabetes, HbA 1c , random blood glucose and fasting blood glucose. Of these candidate effector genes, we showed that three ( ERO1B , HNRNPA2B1 and RHOBTB3 ) exhibited an effect on glucose-stimulated insulin production and secretion in EndoC-βH1 cells. Conclusions/interpretation The findings of our study provide an in-depth characterisation of the 24 h transcriptomic response of human pancreatic islets to glucose exposure at a single-cell resolution. By integrating differentially expressed genes with genetic signals for type 2 diabetes and glucose-related traits, we provide insights into the molecular mechanisms underlying glucose homeostasis. Finally, we provide functional evidence to support the role of three candidate effector genes in insulin secretion and production. Data availability The scRNA-seq data from the 24 h glucose exposure experiment performed in this study are available in the database of Genotypes and Phenotypes (dbGap; https://www.ncbi.nlm.nih.gov/gap/ ) with accession no. phs001188.v3.p1. Study metadata and summary statistics for the differential expression, gene set enrichment and candidate effector gene prediction analyses are available in the Zenodo data repository ( https://zenodo.org/ ) under accession number 11123248. The code used in this study is publicly available at https://github.com/CollinsLabBioComp/publication-islet_glucose_timecourse . Graphical Abstract

A comprehensive gene collection for S. oneidensis was constructed using the lambda recombinase (Gateway) cloning system. A total of 3584 individual ORFs (85%) have been successfully cloned into the entry plasmids. To validate the use of the clone set, three sets of ORFs were examined within three different destination vectors constructed in this study. Success rates for heterologous protein expression of S. oneidensis His- or His/GST-tagged proteins in E. coli were approximately 70%. The ArcA and NarP transcription factor proteins were tested in an in vitro binding assay to demonstrate that functional proteins can be successfully produced using the clone set. Further functional validation of the clone set was obtained from phage display experiments in which a phage encoding thioredoxin was successfully isolated from a pool of 80 different clones after three rounds of biopanning using immobilized anti-thioredoxin antibody as a target. This clone set complements existing genomic (e.g., whole-genome microarray) and other proteomic tools (e.g., mass spectrometry-based proteomic analysis), and facilitates a wide variety of integrated studies, including protein expression, purification, and functional analyses of proteins both in vivo and in vitro.

Hutchinson‐Gilford progeria syndrome (HGPS) is a premature aging disorder affecting tissues of mesenchymal origin. Most individuals with HGPS harbor a de novo c.1824C > T (p.G608G) mutation in the gene encoding lamin A ( LMNA ), which activates a cryptic splice donor site resulting in production of the toxic “progerin” protein. Clinical manifestations include growth deficiency, lipodystrophy, sclerotic dermis, cardiovascular defects, and bone dysplasia. Here we utilized the Lmna G609G knock‐in (KI) mouse model of HGPS to further define mechanisms of bone loss associated with normal and premature aging disorders. Newborn skeletal staining of KI mice revealed altered rib cage shape and spinal curvature, and delayed calvarial mineralization with increased craniofacial and mandibular cartilage content. MicroCT analysis and mechanical testing of adult femurs indicated increased fragility associated with reduced bone mass, recapitulating the progressive bone deterioration that occurs in HGPS patients. We investigated mechanisms of bone loss in KI mice at the cellular level in bone cell populations. Formation of wild‐type and KI osteoclasts from marrow‐derived precursors was inhibited by KI osteoblast‐conditioned media in vitro, suggesting a secreted factor(s) responsible for decreased osteoclasts on KI trabecular surfaces in vivo. Cultured KI osteoblasts exhibited abnormal differentiation characterized by reduced deposition and mineralization of extracellular matrix with increased lipid accumulation compared to wild‐type, providing a mechanism for altered bone formation. Furthermore, quantitative analyses of KI transcripts confirmed upregulation of adipogenic genes both in vitro and in vivo. Thus, osteoblast phenotypic plasticity, inflammation and altered cellular cross‐talk contribute to abnormal bone formation in HGPS mice.