SpatialView: an interactive web application for visualization of multiple samples in spatial transcriptomics experiments.

MOTIVATION: Spatial transcriptomics (ST) experiments provide spatially localized measurements of genome-wide gene expression allowing for an unprecedented opportunity to investigate cellular heterogeneity and organization within a tissue. Statistical and computational frameworks exist that implement robust methods for pre-processing and analyzing data in ST experiments. However, the lack of an interactive suite of tools for visualizing ST data and results currently limits the full potential of ST experiments. RESULTS: To fill the gap, we developed SpatialView, an open-source web browser-based interactive application for visualizing data and results from multiple 10× Genomics Visium ST experiments. We anticipate SpatialView will be useful to a broad array of clinical and basic science investigators utilizing ST to study disease. AVAILABILITY AND IMPLEMENTATION: SpatialView is available at https://github.com/kendziorski-lab/SpatialView (and https://doi.org/10.5281/zenodo.10223907); a demo application is available at https://www.biostat.wisc.edu/˜kendzior/spatialviewdemo/.

Enhancing biological signals and detection rates in single-cell RNA-seq experiments with cDNA library equalization.

Considerable effort has been devoted to refining experimental protocols to reduce levels of technical variability and artifacts in single-cell RNA-sequencing data (scRNA-seq). We here present evidence that equalizing the concentration of cDNA libraries prior to pooling, a step not consistently performed in single-cell experiments, improves gene detection rates, enhances biological signals, and reduces technical artifacts in scRNA-seq data. To evaluate the effect of equalization on various protocols, we developed Scaffold, a simulation framework that models each step of an scRNA-seq experiment. Numerical experiments demonstrate that equalization reduces variation in sequencing depth and gene-specific expression variability. We then performed a set of experiments in vitro with and without the equalization step and found that equalization increases the number of genes that are detected in every cell by 17-31%, improves discovery of biologically relevant genes, and reduces nuisance signals associated with cell cycle. Further support is provided in an analysis of publicly available data.

Regionally specified human pluripotent stem cell-derived astrocytes exhibit different molecular signatures and functional properties.

Astrocytes display diverse morphologies in different regions of the central nervous system. Whether astrocyte diversity is attributable to developmental processes and bears functional consequences, especially in humans, is unknown. RNA-seq of human pluripotent stem cell-derived regional astrocytes revealed distinct transcript profiles, suggesting differential functional properties. This was confirmed by differential calcium signaling as well as effects on neurite growth and blood-brain barrier formation. Distinct transcriptional profiles and functional properties of human astrocytes generated from regionally specified neural progenitors under the same conditions strongly implicate the developmental impact on astrocyte diversity. These findings provide a rationale for renewed examination of regional astrocytes and their role in the pathogenesis of psychiatric and neurological disorders.

Normalization by distributional resampling of high throughput single-cell RNA-sequencing data.

MOTIVATION: Normalization to remove technical or experimental artifacts is critical in the analysis of single-cell RNA-sequencing experiments, even those for which unique molecular identifiers are available. The majority of methods for normalizing single-cell RNA-sequencing data adjust average expression for library size (LS), allowing the variance and other properties of the gene-specific expression distribution to be non-constant in LS. This often results in reduced power and increased false discoveries in downstream analyses, a problem which is exacerbated by the high proportion of zeros present in most datasets. RESULTS: To address this, we present Dino, a normalization method based on a flexible negative-binomial mixture model of gene expression. As demonstrated in both simulated and case study datasets, by normalizing the entire gene expression distribution, Dino is robust to shallow sequencing, sample heterogeneity and varying zero proportions, leading to improved performance in downstream analyses in a number of settings. AVAILABILITY AND IMPLEMENTATION: The R package, Dino, is available on GitHub at https://github.com/JBrownBiostat/Dino. The Dino package is further archived and freely available on Zenodo at https://doi.org/10.5281/zenodo.4897558. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Novel immortalized human vocal fold epithelial cell line: In vitro tool for mucosal biology.

Study of vocal fold (VF) mucosal biology requires essential human vocal fold epithelial cell (hVFE) lines for use in appropriate model systems. We steadily transfected a retroviral construct containing human telomerase reverse transcriptase (hTERT) into primary normal hVFE to establish a continuously replicating hVFE cell line. Immortalized hVFE across passages have cobblestone morphology, express epithelial markers cytokeratin 4, 13 and 14, induced hTERT gene and protein expression, have similar RNAseq profiling, and can continuously grow for more than 8 months. DNA fingerprinting and karyotype analysis demonstrated that immortalized hVFE were consistent with the presence of a single cell line. Validation of the hVFE, in a three-dimensional in vitro VF mucosal construct revealed a multilayered epithelial structure with VF epithelial cell markers. Wound scratch assay revealed higher migration capability of the immortalized hVFE on the surface of collagen-fibronectin and collagen gel containing human vocal fold fibroblasts (hVFF). Collectively, our report demonstrates the first immortalized hVFE from true VFs providing a novel and invaluable tool for the study of epithelial cell-fibroblast interactions that dictate disease and health of this specialized tissue.

Interspecies chimeric conditions affect the developmental rate of human pluripotent stem cells.

Human pluripotent stem cells hold significant promise for regenerative medicine. However, long differentiation protocols and immature characteristics of stem cell-derived cell types remain challenges to the development of many therapeutic applications. In contrast to the slow differentiation of human stem cells in vitro that mirrors a nine-month gestation period, mouse stem cells develop according to a much faster three-week gestation timeline. Here, we tested if co-differentiation with mouse pluripotent stem cells could accelerate the differentiation speed of human embryonic stem cells. Following a six-week RNA-sequencing time course of neural differentiation, we identified 929 human genes that were upregulated earlier and 535 genes that exhibited earlier peaked expression profiles in chimeric cell cultures than in human cell cultures alone. Genes with accelerated upregulation were significantly enriched in Gene Ontology terms associated with neurogenesis, neuron differentiation and maturation, and synapse signaling. Moreover, chimeric mixed samples correlated with in utero human embryonic samples earlier than human cells alone, and acceleration was dose-dependent on human-mouse co-culture ratios. The altered gene expression patterns and developmental rates described in this report have implications for accelerating human stem cell differentiation and the use of interspecies chimeric embryos in developing human organs for transplantation.

CHARTS: a web application for characterizing and comparing tumor subpopulations in publicly available single-cell RNA-seq data sets.

BACKGROUND: Single-cell RNA-seq (scRNA-seq) enables the profiling of genome-wide gene expression at the single-cell level and in so doing facilitates insight into and information about cellular heterogeneity within a tissue. This is especially important in cancer, where tumor and tumor microenvironment heterogeneity directly impact development, maintenance, and progression of disease. While publicly available scRNA-seq cancer data sets offer unprecedented opportunity to better understand the mechanisms underlying tumor progression, metastasis, drug resistance, and immune evasion, much of the available information has been underutilized, in part, due to the lack of tools available for aggregating and analysing these data. RESULTS: We present CHARacterizing Tumor Subpopulations (CHARTS), a web application for exploring publicly available scRNA-seq cancer data sets in the NCBI's Gene Expression Omnibus. More specifically, CHARTS enables the exploration of individual gene expression, cell type, malignancy-status, differentially expressed genes, and gene set enrichment results in subpopulations of cells across tumors and data sets. Along with the web application, we also make available the backend computational pipeline that was used to produce the analyses that are available for exploration in the web application. CONCLUSION: CHARTS is an easy to use, comprehensive platform for exploring single-cell subpopulations within tumors across the ever-growing collection of public scRNA-seq cancer data sets. CHARTS is freely available at charts.morgridge.org.

Microglial responses to CSF1 overexpression do not promote the expansion of other glial lineages.

BACKGROUND: Colony-stimulating factor 1 (CSF1) expression in the central nervous system (CNS) increases in response to a variety of stimuli, and CSF1 is overexpressed in many CNS diseases. In young adult mice, we previously showed that CSF1 overexpression in the CNS caused the proliferation of IBA1+ microglia without promoting the expression of M2 polarization markers. METHODS: Immunohistochemical and molecular analyses were performed to further examine the impact of CSF1 overexpression on glia in both young and aged mice. RESULTS: As CSF1 overexpressing mice age, IBA1+ cell numbers are constrained by a decline in proliferation rate. Compared to controls, there were no differences in expression of the M2 markers ARG1 and MRC1 (CD206) in CSF1 overexpressing mice of any age, indicating that even prolonged exposure to increased CSF1 does not impact M2 polarization status in vivo. Moreover, RNA-sequencing confirmed the lack of increased expression of markers of M2 polarization in microglia exposed to CSF1 overexpression but did reveal changes in expression of other immune-related genes. Although treatment with inhibitors of the CSF1 receptor, CSF1R, has been shown to impact other glia, no increased expression of oligodendrocyte lineage or astrocyte markers was observed in CSF1 overexpressing mice. CONCLUSIONS: Our study indicates that microglia are the primary glial lineage impacted by CSF1 overexpression in the CNS and that microglia ultimately adapt to the presence of the CSF1 mitogenic signal.

SCnorm: robust normalization of single-cell RNA-seq data.

The normalization of RNA-seq data is essential for accurate downstream inference, but the assumptions upon which most normalization methods are based are not applicable in the single-cell setting. Consequently, applying existing normalization methods to single-cell RNA-seq data introduces artifacts that bias downstream analyses. To address this, we introduce SCnorm for accurate and efficient normalization of single-cell RNA-seq data.

Ovarian cancer cells direct monocyte differentiation through a non-canonical pathway.

BACKGROUND: Alternatively-activated macrophages (AAMs), an anti-inflammatory macrophage subpopulation, have been implicated in the progression of high grade serous ovarian carcinoma (HGSOC). Increased levels of AAMs are correlated with poor HGSOC survival rates, and AAMs increase the attachment and spread of HGSOC cells in vitro. However, the mechanism by which monocytes in the HGSOC tumor microenvironment are differentiated and polarized to AAMs remains unknown. METHODS: Using an in vitro co-culture device, we cultured naïve, primary human monocytes with a panel of five HGSOC cell lines over the course of 7 days. An empirical Bayesian statistical method, EBSeq, was used to couple RNA-seq with observed monocyte-derived cell phenotype to explore which HGSOC-derived soluble factors supported differentiation to CD68+ macrophages and subsequent polarization towards CD163+ AAMs. Pathways of interest were interrogated using small molecule inhibitors, neutralizing antibodies, and CRISPR knockout cell lines. RESULTS: HGSOC cell lines displayed a wide range of abilities to generate AAMs from naïve monocytes. Much of this variation appeared to result from differential ability to generate CD68+ macrophages, as most CD68+ cells were also CD163+. Differences in tumor cell potential to generate macrophages was not due to a MCSF-dependent mechanism, nor variance in established pro-AAM factors. TGFα was implicated as a potential signaling molecule produced by tumor cells that could induce macrophage differentiation, which was validated using a CRISPR knockout of TGFA in the OVCAR5 cell line. CONCLUSIONS: HGSOC production of TGFα drives monocytes to differentiate into macrophages, representing a central arm of the mechanism by which AAMs are generated in the tumor microenvironment.

Single-cell RNA sequencing reveals intrinsic and extrinsic regulatory heterogeneity in yeast responding to stress.

From bacteria to humans, individual cells within isogenic populations can show significant variation in stress tolerance, but the nature of this heterogeneity is not clear. To investigate this, we used single-cell RNA sequencing to quantify transcript heterogeneity in single Saccharomyces cerevisiae cells treated with and without salt stress to explore population variation and identify cellular covariates that influence the stress-responsive transcriptome. Leveraging the extensive knowledge of yeast transcriptional regulation, we uncovered significant regulatory variation in individual yeast cells, both before and after stress. We also discovered that a subset of cells appears to decouple expression of ribosomal protein genes from the environmental stress response in a manner partly correlated with the cell cycle but unrelated to the yeast ultradian metabolic cycle. Live-cell imaging of cells expressing pairs of fluorescent regulators, including the transcription factor Msn2 with Dot6, Sfp1, or MAP kinase Hog1, revealed both coordinated and decoupled nucleocytoplasmic shuttling. Together with transcriptomic analysis, our results suggest that cells maintain a cellular filter against decoupled bursts of transcription factor activation but mount a stress response upon coordinated regulation, even in a subset of unstressed cells.

Automated minute scale RNA-seq of pluripotent stem cell differentiation reveals early divergence of human and mouse gene expression kinetics.

Pluripotent stem cells retain the developmental timing of their species of origin in vitro, an observation that suggests the existence of a cell-intrinsic developmental clock, yet the nature and machinery of the clock remain a mystery. We hypothesize that one possible component may lie in species-specific differences in the kinetics of transcriptional responses to differentiation signals. Using a liquid-handling robot, mouse and human pluripotent stem cells were exposed to identical neural differentiation conditions and sampled for RNA-sequencing at high frequency, every 4 or 10 minutes, for the first 10 hours of differentiation to test for differences in transcriptomic response rates. The majority of initial transcriptional responses occurred within a rapid window in the first minutes of differentiation for both human and mouse stem cells. Despite similarly early onsets of gene expression changes, we observed shortened and condensed gene expression patterns in mouse pluripotent stem cells compared to protracted trends in human pluripotent stem cells. Moreover, the speed at which individual genes were upregulated, as measured by the slopes of gene expression changes over time, was significantly faster in mouse compared to human cells. These results suggest that downstream transcriptomic response kinetics to signaling cues are faster in mouse versus human cells, and may offer a partial account for the vast differences in developmental rates across species.

Tissue specific human fibroblast differential expression based on RNAsequencing analysis.

BACKGROUND: Physical forces, such as mechanical stress, are essential for tissue homeostasis and influence gene expression of cells. In particular, the fibroblast has demonstrated sensitivity to extracellular matrices with assumed adaptation upon various mechanical loads. The purpose of this study was to compare the vocal fold fibroblast genotype, known for its unique mechanically stressful tissue environment, with cellular counterparts at various other anatomic locales to identify differences in functional gene expression profiles. RESULTS: By using RNA-seq technology, we identified differentially expressed gene programs (DEseq2) among seven normal human fibroblast primary cell lines from healthy cadavers, which included: vocal fold, trachea, lung, abdomen, scalp, upper gingiva, and soft palate. Unsupervised gene expression analysis yielded 6216 genes differentially expressed across all anatomic sites. Hierarchical cluster analysis revealed grouping based on anatomic site origin rather than donor, suggesting global fibroblast phenotype heterogeneity. Sex and age-related effects were negligible. Functional enrichment analyses based on separate post-hoc 2-group comparisons revealed several functional themes within the vocal fold fibroblast related to transcription factors for signaling pathways regulating pluripotency of stem cells and extracellular matrix components such as cell signaling, migration, proliferation, and differentiation potential. CONCLUSIONS: Human fibroblasts display a phenomenon of global topographic differentiation, which is maintained in isolation via in vitro assays. Epigenetic mechanical influences on vocal fold tissue may play a role in uniquely modelling and maintaining the local environmental cellular niche during homeostasis with vocal fold fibroblasts distinctly specialized related to their anatomic positional and developmental origins established during embryogenesis.

Discordance between histologic and visual assessment of tissue viability in excised burn wound tissue.

The regenerative capacity of burn wounds, and the need for surgical intervention, depends on wound depth. Clinical visual assessment is considered the gold standard for burn depth assessment but it remains a subjective and inaccurate method for tissue evaluation. The purpose of this study was to compare visual assessment with microscopic and molecular techniques for human burn depth determination, and illustrate differences in the evaluation of tissue for potential regenerative capacity. Using intraoperative visual assessment, patients were identified as having deep partial thickness or full thickness burn wounds. Tangential excisions of burn tissue were processed with hematoxylin and eosin to visualize tissue morphology, lactate dehydrogenase assay to ascertain cellular viability, and Keratin-15 and Ki67 to identify epidermal progenitor cells and proliferative capacity, respectively. RNA from deep partial and full thickness burn tissue as well as normal tissue controls were submitted for RNA sequencing. Lactate dehydrogenase, Keratin-15, and Ki67 were found throughout the excised burn wound tissue in both deep partial thickness burn tissues and in the second tangential excision of full thickness burn tissues. RNA sequencing demonstrated regenerative capacity in both deep partial and full thickness burn tissue, however a greater capacity for regeneration was present in deep partial thickness compared with full thickness burn tissues. In this study, we highlight the discordance that exists between the intraoperative clinical identification of burn injury depth, and microscopic and molecular determination of viability and regenerative capacity. Current methods utilizing visual assessment for depth of injury are imprecise, and can lead to removal of viable tissue. Additionally, hematoxylin and eosin microscopic analysis should not be used as the sole method in research or clinical determination of depth, as there are no differences in staining between viable and nonviable tissue.

The Transcription Factor Nfatc2 Regulates ß-Cell Proliferation and Genes Associated with Type 2 Diabetes in Mouse and Human Islets.

Human genome-wide association studies (GWAS) have shown that genetic variation at >130 gene loci is associated with type 2 diabetes (T2D). We asked if the expression of the candidate T2D-associated genes within these loci is regulated by a common locus in pancreatic islets. Using an obese F2 mouse intercross segregating for T2D, we show that the expression of ~40% of the T2D-associated genes is linked to a broad region on mouse chromosome (Chr) 2. As all but 9 of these genes are not physically located on Chr 2, linkage to Chr 2 suggests a genomic factor(s) located on Chr 2 regulates their expression in trans. The transcription factor Nfatc2 is physically located on Chr 2 and its expression demonstrates cis linkage; i.e., its expression maps to itself. When conditioned on the expression of Nfatc2, linkage for the T2D-associated genes was greatly diminished, supporting Nfatc2 as a driver of their expression. Plasma insulin also showed linkage to the same broad region on Chr 2. Overexpression of a constitutively active (ca) form of Nfatc2 induced ß-cell proliferation in mouse and human islets, and transcriptionally regulated more than half of the T2D-associated genes. Overexpression of either ca-Nfatc2 or ca-Nfatc1 in mouse islets enhanced insulin secretion, whereas only ca-Nfatc2 was able to promote ß-cell proliferation, suggesting distinct molecular pathways mediating insulin secretion vs. ß-cell proliferation are regulated by NFAT. Our results suggest that many of the T2D-associated genes are downstream transcriptional targets of NFAT, and may act coordinately in a pathway through which NFAT regulates ß-cell proliferation in both mouse and human islets.

Trendy: segmented regression analysis of expression dynamics in high-throughput ordered profiling experiments.

BACKGROUND: High-throughput expression profiling experiments with ordered conditions (e.g. time-course or spatial-course) are becoming more common for studying detailed differentiation processes or spatial patterns. Identifying dynamic changes at both the individual gene and whole transcriptome level can provide important insights about genes, pathways, and critical time points. RESULTS: We present an R package, Trendy, which utilizes segmented regression models to simultaneously characterize each gene's expression pattern and summarize overall dynamic activity in ordered condition experiments. For each gene, Trendy finds the optimal segmented regression model and provides the location and direction of dynamic changes in expression. We demonstrate the utility of Trendy to provide biologically relevant results on both microarray and RNA-sequencing (RNA-seq) datasets. CONCLUSIONS: Trendy is a flexible R package which characterizes gene-specific expression patterns and summarizes changes of global dynamics over ordered conditions. Trendy is freely available on Bioconductor with a full vignette at https://bioconductor.org/packages/release/bioc/html/Trendy.html .

Oscope identifies oscillatory genes in unsynchronized single-cell RNA-seq experiments.

Oscillatory gene expression is fundamental to development, but technologies for monitoring expression oscillations are limited. We have developed a statistical approach called Oscope to identify and characterize the transcriptional dynamics of oscillating genes in single-cell RNA-seq data from an unsynchronized cell population. Applying Oscope to a number of data sets, we demonstrated its utility and also identified a potential artifact in the Fluidigm C1 platform.

OEFinder: a user interface to identify and visualize ordering effects in single-cell RNA-seq data.

UNLABELLED: A recent article identified an artifact in multiple single-cell RNA-seq (scRNA-seq) datasets generated by the Fluidigm C1 platform. Specifically, Leng et al. showed significantly increased gene expression in cells captured from sites with small or large plate output IDs. We refer to this artifact as an ordering effect (OE). Including OE genes in downstream analyses could lead to biased results. To address this problem, we developed a statistical method and software called OEFinder to identify a sorted list of OE genes. OEFinder is available as an R package along with user-friendly graphical interface implementations which allows users to check for potential artifacts in scRNA-seq data generated by the Fluidigm C1 platform. AVAILABILITY AND IMPLEMENTATION: OEFinder is freely available at https://github.com/lengning/OEFinder CONTACT: rstewart@morgridge.org or lengning1@gmail.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Fungal Morphology, Iron Homeostasis, and Lipid Metabolism Regulated by a GATA Transcription Factor in Blastomyces dermatitidis.

In response to temperature, Blastomyces dermatitidis converts between yeast and mold forms. Knowledge of the mechanism(s) underlying this response to temperature remains limited. In B. dermatitidis, we identified a GATA transcription factor, SREB, important for the transition to mold. Null mutants (SREBΔ) fail to fully complete the conversion to mold and cannot properly regulate siderophore biosynthesis. To capture the transcriptional response regulated by SREB early in the phase transition (0-48 hours), gene expression microarrays were used to compare SREB∆ to an isogenic wild type isolate. Analysis of the time course microarray data demonstrated SREB functioned as a transcriptional regulator at 37°C and 22°C. Bioinformatic and biochemical analyses indicated SREB was involved in diverse biological processes including iron homeostasis, biosynthesis of triacylglycerol and ergosterol, and lipid droplet formation. Integration of microarray data, bioinformatics, and chromatin immunoprecipitation identified a subset of genes directly bound and regulated by SREB in vivo in yeast (37°C) and during the phase transition to mold (22°C). This included genes involved with siderophore biosynthesis and uptake, iron homeostasis, and genes unrelated to iron assimilation. Functional analysis suggested that lipid droplets were actively metabolized during the phase transition and lipid metabolism may contribute to filamentous growth at 22°C. Chromatin immunoprecipitation, RNA interference, and overexpression analyses suggested that SREB was in a negative regulatory circuit with the bZIP transcription factor encoded by HAPX. Both SREB and HAPX affected morphogenesis at 22°C; however, large changes in transcript abundance by gene deletion for SREB or strong overexpression for HAPX were required to alter the phase transition.

Modeling fibrosis using fibroblasts isolated from scarred rat vocal folds.

Following injury, pathologically activated vocal fold fibroblasts (VFFs) can engage in disordered extracellular matrix (ECM) remodeling, leading to VF fibrosis and impaired voice function. Given the importance of scar VFFs to phenotypically appropriate in vitro modeling of VF fibrosis, we pursued detailed characterization of scar VFFs obtained from surgically injured rat VF mucosae, compared with those obtained from experimentally naïve, age-matched tissue. Scar VFFs initially exhibited a myofibroblast phenotype characterized by increased proliferation, increased Col1a1 transcription and collagen, type I synthesis, increased Acta2 transcription and α-smooth muscle actin synthesis, and enhanced contractile function. These features were most distinct at passage 1 (P1); we observed a coalescence of the scar and naïve VFF phenotypes at later passages. An empirical Bayes statistical analysis of the P1 cell transcriptome identified 421 genes that were differentially expressed by scar, compared with naïve, VFFs. These genes were primarily associated with the wound response, ECM regulation, and cell proliferation. Follow-up comparison of P1 scar VFFs and their in vivo tissue source showed substantial transcriptomic differences. Finally, P1 scar VFFs responded to treatment with hepatocyte growth factor and transforming growth factor-ß3, two biologics with reported therapeutic value. Despite the practical limitations inherent to working with early passage cells, this experimental model is easily implemented in any suitably equipped laboratory and has the potential to improve the applicability of preclinical VF fibrosis research.