SaVanT: a web-based tool for the sample-level visualization of molecular signatures in gene expression profiles

CATD: a reproducible pipeline for selecting cell-type deconvolution methods across tissues

Motivation

Cell-type deconvolution methods aim to infer cell composition from bulk transcriptomic data. The proliferation of developed methods coupled with inconsistent results obtained in many cases, highlights the pressing need for guidance in the selection of appropriate methods. Additionally, the growing accessibility of single-cell RNA sequencing datasets, often accompanied by bulk expression from related samples enable the benchmark of existing methods.

Results

In this study, we conduct a comprehensive assessment of 31 methods, utilizing single-cell RNA-sequencing data from diverse human and mouse tissues. Employing various simulation scenarios, we reveal the efficacy of regression-based deconvolution methods, highlighting their sensitivity to reference choices. We investigate the impact of bulk-reference differences, incorporating variables such as sample, study and technology. We provide validation using a gold standard dataset from mononuclear cells and suggest a consensus prediction of proportions when ground truth is not available. We validated the consensus method on data from the stomach and studied its spillover effect. Importantly, we propose the use of the critical assessment of transcriptomic deconvolution (CATD) pipeline which encompasses functionalities for generating references and pseudo-bulks and running implemented deconvolution methods. CATD streamlines simultaneous deconvolution of numerous bulk samples, providing a practical solution for speeding up the evaluation of newly developed methods.

Availability and implementation

https://github.com/Papatheodorou-Group/CATD_snakemake.

Fasting-Mimicking Diet Inhibits Autophagy and Synergizes with Chemotherapy to Promote T-Cell-Dependent Leukemia-Free Survival

Fasting mimicking diets (FMDs) are effective in the treatment of many solid tumors in mouse models, but their effect on hematologic malignancies is poorly understood, particularly in combination with standard therapies. Here we show that cycles of a 3-day FMD given to high-fat-diet-fed mice once a week increased the efficacy of vincristine to improve survival from BCR-ABL B acute lymphoblastic leukemia (ALL). In mice fed a standard diet, FMD cycles in combination with vincristine promoted cancer-free survival. RNA seq and protein assays revealed a vincristine-dependent decrease in the expression of multiple autophagy markers, which was exacerbated by the fasting/FMD conditions. The autophagy inhibitor chloroquine could substitute for fasting/FMD to promote cancer-free survival in combination with vincristine. In vitro, targeted inhibition of autophagy genes ULK1 and ATG9a strongly potentiated vincristine's toxicity. Moreover, anti-CD8 antibodies reversed the effects of vincristine plus fasting/FMD in promoting leukemia-free survival in mice, indicating a central role of the immune system in this response. Thus, the inhibition of autophagy and enhancement of immune responses appear to be mediators of the fasting/FMD-dependent cancer-free survival in ALL mice.

A Review of Single-Cell RNA-Seq Annotation, Integration, and Cell-Cell Communication

Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for investigating cellular biology at an unprecedented resolution, enabling the characterization of cellular heterogeneity, identification of rare but significant cell types, and exploration of cell-cell communications and interactions. Its broad applications span both basic and clinical research domains. In this comprehensive review, we survey the current landscape of scRNA-seq analysis methods and tools, focusing on count modeling, cell-type annotation, data integration, including spatial transcriptomics, and the inference of cell-cell communication. We review the challenges encountered in scRNA-seq analysis, including issues of sparsity or low expression, reliability of cell annotation, and assumptions in data integration, and discuss the potential impact of suboptimal clustering and differential expression analysis tools on downstream analyses, particularly in identifying cell subpopulations. Finally, we discuss recent advancements and future directions for enhancing scRNA-seq analysis. Specifically, we highlight the development of novel tools for annotating single-cell data, integrating and interpreting multimodal datasets covering transcriptomics, epigenomics, and proteomics, and inferring cellular communication networks. By elucidating the latest progress and innovation, we provide a comprehensive overview of the rapidly advancing field of scRNA-seq analysis.

Graph Visualization: Alternative Models Inspired by Bioinformatics

Currently, the methods and means of human-machine interaction and visualization as its integral part are being increasingly developed. In various fields of scientific knowledge and technology, there is a need to find and select the most effective visualization models for various types of data, as well as to develop automation tools for the process of choosing the best visualization model for a specific case. There are many data visualization tools in various application fields, but at the same time, the main difficulty lies in presenting data of an interconnected (node-link) structure, i.e., networks. Typically, a lot of software means use graphs as the most straightforward and versatile models. To facilitate visual analysis, researchers are developing ways to arrange graph elements to make comparing, searching, and navigating data easier. However, in addition to graphs, there are many other visualization models that are less versatile but have the potential to expand the capabilities of the analyst and provide alternative solutions. In this work, we collected a variety of visualization models, which we call alternative models, to demonstrate how different concepts of information representation can be realized. We believe that adapting these models to improve the means of human-machine interaction will help analysts make significant progress in solving the problems researchers face when working with graphs.

TREM2 macrophages induced by human lipids drive inflammation in acne lesions

Acne affects 1 in 10 people globally, often resulting in disfigurement. The disease involves excess production of lipids, particularly squalene, increased growth of Cutibacterium acnes, and a host inflammatory response with foamy macrophages. By combining single-cell and spatial RNA sequencing as well as ultrahigh-resolution Seq-Scope analyses of early acne lesions on back skin, we identified TREM2 macrophages expressing lipid metabolism and proinflammatory gene programs in proximity to hair follicle epithelium expressing squalene epoxidase. We established that the addition of squalene induced differentiation of TREM2 macrophages in vitro, which were unable to kill C. acnes. The addition of squalene to macrophages inhibited induction of oxidative enzymes and scavenged oxygen free radicals, providing an explanation for the efficacy of topical benzoyl peroxide in the clinical treatment of acne. The present work has elucidated the mechanisms by which TREM2 macrophages and unsaturated lipids, similar to their involvement in atherosclerosis, may contribute to the pathogenesis of acne.

Multimodal profiling of lung granulomas in macaques reveals cellular correlates of tuberculosis control

Mycobacterium tuberculosis lung infection results in a complex multicellular structure: the granuloma. In some granulomas, immune activity promotes bacterial clearance, but in others, bacteria persist and grow. We identified correlates of bacterial control in cynomolgus macaque lung granulomas by co-registering longitudinal positron emission tomography and computed tomography imaging, single-cell RNA sequencing, and measures of bacterial clearance. Bacterial persistence occurred in granulomas enriched for mast, endothelial, fibroblast, and plasma cells, signaling amongst themselves via type 2 immunity and wound-healing pathways. Granulomas that drove bacterial control were characterized by cellular ecosystems enriched for type 1-type 17, stem-like, and cytotoxic T cells engaged in pro-inflammatory signaling networks involving diverse cell populations. Granulomas that arose later in infection displayed functional characteristics of restrictive granulomas and were more capable of killing Mtb. Our results define the complex multicellular ecosystems underlying (lack of) granuloma resolution and highlight host immune targets that can be leveraged to develop new vaccine and therapeutic strategies for TB.

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Timing of granuloma formation influences local microenvironment and bacterial burden

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Mast cells, type 2 immunity, and tissue remodeling underlie early, high-burden granulomas

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Type1-type17 and cytotoxic T cells associate with late-forming, low-burden granulomas

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Distinct interaction circuits across granuloma phenotypes nominate therapeutic targets

Systematic evaluation of transcriptomics-based deconvolution methods and references using thousands of clinical samples

Estimating cell type composition of blood and tissue samples is a biological challenge relevant in both laboratory studies and clinical care. In recent years, a number of computational tools have been developed to estimate cell type abundance using gene expression data. Although these tools use a variety of approaches, they all leverage expression profiles from purified cell types to evaluate the cell type composition within samples. In this study, we compare 12 cell type quantification tools and evaluate their performance while using each of 10 separate reference profiles. Specifically, we have run each tool on over 4000 samples with known cell type proportions, spanning both immune and stromal cell types. A total of 12 of these represent in vitro synthetic mixtures and 300 represent in silico synthetic mixtures prepared using single-cell data. A final 3728 clinical samples have been collected from the Framingham cohort, for which cell populations have been quantified using electrical impedance cell counting. When tools are applied to the Framingham dataset, the tool Estimating the Proportions of Immune and Cancer cells (EPIC) produces the highest correlation, whereas Gene Expression Deconvolution Interactive Tool (GEDIT) produces the lowest error. The best tool for other datasets is varied, but CIBERSORT and GEDIT most consistently produce accurate results. We find that optimal reference depends on the tool used, and report suggested references to be used with each tool. Most tools return results within minutes, but on large datasets runtimes for CIBERSORT can exceed hours or even days. We conclude that deconvolution methods are capable of returning high-quality results, but that proper reference selection is critical.

Kynureninase contributes to the pathogenesis of psoriasis through pro-inflammatory effect

Kynureninase (KYNU) is a key enzyme in the tryptophan metabolism pathway with elevated expression in psoriatic lesions relative to normal skin. However, whether KYNU contributes to the pathogenesis of psoriasis remains unknown. We sought to investigate the role of KYNU in psoriasis and its possible regulation mechanism. In the results, KYNU is upregulated in psoriatic skin samples from patients or animal models compared with normal skin control which was assayed in psoriatic patient samples, IMQ-induced psoriasis-like skin inflammation in BABL/c mice and M5-stimulated keratinocyte cell lines by immunohistochemistry (IHC). KYNU knockdown had a trivial impact on keratinocyte proliferation, but significantly inhibited the production of inflammatory cytokines in HaCaT, HEKα, and HEKn cells by quantitative reverse-transcription polymerase chain reaction, enzyme-linked immunosorbent assay, and western blot analysis. The 3'-untranslated region of KYNU contains a conserved target site of a skin-specific microRNA (miRNA), miR-203a, as predicted by TargetScan software. Furthermore, miR-203a exhibited an inversed expression kinetics to KYNU during the development of IMQ-induced psoriasis-like skin inflammation in BABL/c mice. Overexpression of miR-203 subsequently leading to the inhibition of KYNU, could significantly reduce the production of M5-induced, psoriasis-related inflammatory factors in keratinocytes. Finally, KYNU inhibitors could alleviate the pathological phenotypes in IMQ-mice. Our study supported the contributive role of KYNU in the development of psoriasis and provided preliminary evidence for KYNU as a potential therapeutic target in psoriasis.

The CD94/NKG2A inhibitory receptor educates uterine NK cells to optimize pregnancy outcomes in humans and mice

The conserved CD94/NKG2A inhibitory receptor is expressed by nearly all human and ∼50% of mouse uterine natural killer (uNK) cells. Binding human HLA-E and mouse Qa-1, NKG2A drives NK cell education, a process of unknown physiological importance influenced by HLA-B alleles. Here, we show that NKG2A genetic ablation in dams mated with wild-type males caused suboptimal maternal vascular responses in pregnancy, accompanied by perturbed placental gene expression, reduced fetal weight, greater rates of smaller fetuses with asymmetric growth, and abnormal brain development. These are features of the human syndrome pre-eclampsia. In a genome-wide association study of 7,219 pre-eclampsia cases, we found a 7% greater relative risk associated with the maternal HLA-B allele that does not favor NKG2A education. These results show that the maternal HLA-B→HLA-E→NKG2A pathway contributes to healthy pregnancy and may have repercussions on offspring health, thus establishing the physiological relevance for NK cell education.

Video Abstract

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CD94/NKG2A educates uterine NK cells

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NKG2A-deficient dams display reduced utero-placental hemodynamic adaptations

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Asymmetric growth restriction and abnormal brain development in NKG2A-deficient dams

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Non-functional HLA-B→HLA-E→NKG2A pathway exposes women to greater pre-eclampsia risk

The Gene Expression Deconvolution Interactive Tool (GEDIT): accurate cell type quantification from gene expression data

Background

The cell type composition of heterogeneous tissue samples can be a critical variable in both clinical and laboratory settings. However, current experimental methods of cell type quantification (e.g., cell flow cytometry) are costly, time consuming and have potential to introduce bias. Computational approaches that use expression data to infer cell type abundance offer an alternative solution. While these methods have gained popularity, most fail to produce accurate predictions for the full range of platforms currently used by researchers or for the wide variety of tissue types often studied.

Results

We present the Gene Expression Deconvolution Interactive Tool (GEDIT), a flexible tool that utilizes gene expression data to accurately predict cell type abundances. Using both simulated and experimental data, we extensively evaluate the performance of GEDIT and demonstrate that it returns robust results under a wide variety of conditions. These conditions include multiple platforms (microarray and RNA-seq), tissue types (blood and stromal), and species (human and mouse). Finally, we provide reference data from 8 sources spanning a broad range of stromal and hematopoietic types in both human and mouse. GEDIT also accepts user-submitted reference data, thus allowing the estimation of any cell type or subtype, provided that reference data are available.

Conclusions

GEDIT is a powerful method for evaluating the cell type composition of tissue samples and provides excellent accuracy and versatility compared to similar tools. The reference database provided here also allows users to obtain estimates for a wide variety of tissue samples without having to provide their own data.

Proximal colon-derived O-glycosylated mucus encapsulates and modulates the microbiota

Colon mucus segregates the intestinal microbiota from host tissues, but how it organizes to function throughout the colon is unclear. In mice, we found that colon mucus consists of two distinct O-glycosylated entities of Muc2: a major form produced by the proximal colon, which encapsulates the fecal material including the microbiota, and a minor form derived from the distal colon, which adheres to the major form. The microbiota directs its own encapsulation by inducing Muc2 production from proximal colon goblet cells. In turn, O-glycans on proximal colon-derived Muc2 modulate the structure and function of the microbiota as well as transcription in the colon mucosa. Our work shows how proximal colon control of mucin production is an important element in the regulation of host-microbiota symbiosis.

Cell-free DNA Methylation and Transcriptomic Signature Prediction of Pregnancies with Adverse Outcomes

Although analysis of maternal plasma cell-free content has been employed for screening of genetic abnormalities within a pregnancy, limited attention has been paid to its use for the detection of adverse pregnancy outcomes (APOs) based on placental function. Here we investigated cell-free DNA and RNA content of 102 maternal and 25 cord plasma samples. Employing a novel deconvolution methodology, we found that during the first trimester, placenta-specific DNA increased prior to the subsequent development of gestational diabetes with no change in patients with preeclampsia while decreasing with maternal obesity. Moreover, using cell-free RNA sequencing, APOs revealed 71 differentially expressed genes early in pregnancy. We noticed the upregulation of S100A8, MS4A3, and MMP8 that have been already associated with APOs but also the upregulation of BCL2L15 and the downregulation of ALPL that have never been associated with APOs. We constructed a classifier with a positive predictive ability (AUC) of 0.91 for APOs, 0.86 for preeclampsia alone and 0.64 for GDM. We conclude that placenta-specific cell-free nucleic acids during early gestation provide the possibility of predicting APOs prior to the emergence of characteristic clinical features.

Second-Strand Synthesis-Based Massively Parallel scRNA-Seq Reveals Cellular States and Molecular Features of Human Inflammatory Skin Pathologies

High-throughput single-cell RNA-sequencing (scRNA-seq) methodologies enable characterization of complex biological samples by increasing the number of cells that can be profiled contemporaneously. Nevertheless, these approaches recover less information per cell than low-throughput strategies. To accurately report the expression of key phenotypic features of cells, scRNA-seq platforms are needed that are both high fidelity and high throughput. To address this need, we created Seq-Well S3 ("Second-Strand Synthesis"), a massively parallel scRNA-seq protocol that uses a randomly primed second-strand synthesis to recover complementary DNA (cDNA) molecules that were successfully reverse transcribed but to which a second oligonucleotide handle, necessary for subsequent whole transcriptome amplification, was not appended due to inefficient template switching. Seq-Well S3 increased the efficiency of transcript capture and gene detection compared with that of previous iterations by up to 10- and 5-fold, respectively. We used Seq-Well S3 to chart the transcriptional landscape of five human inflammatory skin diseases, thus providing a resource for the further study of human skin inflammation.

Profiling immunoglobulin repertoires across multiple human tissues using RNA sequencing

Profiling immunoglobulin (Ig) receptor repertoires with specialized assays can be cost-ineffective and time-consuming. Here we report ImReP, a computational method for rapid and accurate profiling of the Ig repertoire, including the complementary-determining region 3 (CDR3), using regular RNA sequencing data such as those from 8,555 samples across 53 tissues types from 544 individuals in the Genotype-Tissue Expression (GTEx v6) project. Using ImReP and GTEx v6 data, we generate a collection of 3.6 million Ig sequences, termed the atlas of immunoglobulin repertoires (TAIR), across a broad range of tissue types that often do not have reported Ig repertoires information. Moreover, the flow of Ig clonotypes and inter-tissue repertoire similarities across immune-related tissues are also evaluated. In summary, TAIR is one of the largest collections of CDR3 sequences and tissue types, and should serve as an important resource for studying immunological diseases.

Information on immune receptor repertoire provides important insights on disease progression and therapy development, but can be expensive and time-consuming to obtain. Here the authors report ImReP, a computational method that can extract detailed immune repertoire information from existing tissue-specific RNA sequencing data.

Molecular signatures for inflammation vary across cancer types and correlate significantly with tumor stage, sex and vital status of patients

Cancer affects millions of individuals worldwide. One shortcoming of traditional cancer classification systems is that, even for tumors affecting a single organ, there is significant molecular heterogeneity. Precise molecular classification of tumors could be beneficial in personalizing patients’ therapy and predicting prognosis. To this end, here we propose to use molecular signatures to further refine cancer classification. Molecular signatures are collections of genes characterizing particular cell types, tissues or disease. Signatures can be used to interpret expression profiles from heterogeneous samples. Large collections of gene signatures have previously been cataloged in the MSigDB database. We have developed a web-based Signature Visualization Tool (SaVanT) to display signature scores in user-generated expression data. Here we have undertaken a systematic analysis of correlations between inflammatory signatures and cancer samples, to test whether inflammation can differentiate cancer types. Inflammatory response signatures were obtained from MsigDB and SaVanT and a signature score was computed for samples associated with 7 different cancer types. We first identified types of cancers that had high inflammation levels as measured by these signatures. The correlation between signature scores and metadata of these patients (sex, age at initial cancer diagnosis, cancer stage, and vital status) was then computed. We sought to evaluate correlations between inflammation with other clinical parameters and identified four cancer types that had statistically significant association (p-value < 0.05) with at least one clinical characteristic: pancreas adenocarcinoma (PAAD), cholangiocarcinoma (CHOL), kidney chromophobe (KICH), and uveal melanoma (UVM). These results may allow future studies to use these approaches to further refine cancer subtyping and ultimately treatment.

Cellular, Molecular, and Immunological Characteristics of Langhans Multinucleated Giant Cells Programmed by IL-15

Langhans multinucleated giant cells (LGCs) are a specific type of multinucleated giant cell containing a characteristic horseshoe-shaped ring of nuclei that are present within granulomas of infectious etiology. Although cytokines that trigger macrophage activation (such as IFN-γ) induce LGC formation, it is not clear whether cytokines that trigger macrophage differentiation contribute to LGC formation. Here, we found that IL-15, a cytokine that induces M1 macrophage differentiation, programs human peripheral blood adherent cells to form LGCs. Analysis of the IL-15‒treated adherent cell transcriptome identified gene networks for T cells, DNA damage and replication, and IFN-inducible genes that correlated with IL-15 treatment and LGC-type multinucleated giant cell formation. Gene networks enriched for myeloid cells were anticorrelated with IL-15 treatment and LGC formation. Functional studies revealed that T cells were required for IL-15‒induced LGC formation, involving a direct contact with myeloid cells through CD40L-CD40 interaction and IFN-γ release. These data indicate that IL-15 induces LGC formation through the direct interaction of activated T cells and myeloid cells.

Epithelial Membrane Protein 2 (EMP2) Promotes VEGF-Induced Pathological Neovascularization in Murine Oxygen-Induced Retinopathy

Purpose

Retinopathy of prematurity (ROP) is a leading cause of childhood blindness. ROP occurs as a consequence of postnatal hyperoxia exposure in premature infants, resulting in vasoproliferation in the retina. The tetraspan protein epithelial membrane protein-2 (EMP2) is highly expressed in the retinal pigment epithelium (RPE) in adults, and it controls vascular endothelial growth factor (VEGF) production in the ARPE-19 cell line. We, therefore, hypothesized that Emp2 knockout (Emp2 KO) protects against neovascularization in murine oxygen-induced retinopathy (OIR).

Methods

Eyes were obtained from wildtype (WT) and Emp2 KO mouse pups at P7, P12, P17, and P21 after normoxia or hyperoxia (P7-P12) exposure. Following hyperoxia exposure, RNA sequencing was performed using the retina/choroid layers obtained from WT and Emp2 KO at P17. Retinal sections from P7, P12, P17, and P21 were evaluated for Emp2, hypoxia-inducible factor 1α (Hif1α), and VEGF expression. Whole mount images were generated to assess vaso-obliteration at P12 and neovascularization at P17.

Results

Emp2 KO OIR mice demonstrated a decrease in pathologic neovascularization at P17 compared with WT OIR mice through evaluation of retinal vascular whole mount images. This protection was accompanied by a decrease in Hif1α at P12 and VEGFA expression at P17 in Emp2 KO animals compared with the WT animals in OIR conditions. Collectively, our results suggest that EMP2 enhances the effects of neovascularization through modulation of angiogenic signaling.

Conclusions

The protection of Emp2 KO mice against pathologic neovascularization through attenuation of HIF and VEGF upregulation in OIR suggests that hypoxia-induced upregulation of EMP2 expression in the neuroretina modulates HIF-mediated neuroretinal VEGF expression.

Identification of a systemic interferon-γ inducible antimicrobial gene signature in leprosy patients undergoing reversal reaction

Reversal reactions (RRs) in leprosy are characterized by a reduction in the number of bacilli in lesions associated with an increase in cell-mediated immunity against the intracellular bacterium Mycobacterium leprae, the causative pathogen of leprosy. To identify the mechanisms that contribute to cell-mediated immunity in leprosy, we measured changes in the whole blood-derived transcriptome of patients with leprosy before, during and after RR. We identified an ‘RR signature’ of 1017 genes that were upregulated at the time of the clinical diagnosis of RR. Using weighted gene correlated network analysis (WGCNA), we detected a module of 794 genes, bisque4, that was significantly correlated with RR, of which 434 genes were part of the RR signature. An enrichment for both IFN-γ and IFN-β downstream gene pathways was present in the RR signature as well as the RR upregulated genes in the bisque4 module, including those encoding proteins of the guanylate binding protein (GBP) family that contributes to antimicrobial responses against mycobacteria. Specifically, GBP1, GBP2, GBP3 and GBP5 mRNAs were upregulated in the RR peripheral blood transcriptome, with GBP1, GBP2 and GBP5 mRNAs also upregulated in the RR disease lesion transcriptome. These data indicate that RRs involve a systemic upregulation of IFN-γ downstream genes including GBP family members as part of the host antimicrobial response against mycobacteria.

Reversal reaction (RR) is a major cause of tissue injury and disabilities in leprosy, resulting from the rapid onset of cell-mediated immune responses to the intracellular bacterium Mycobacterium leprae. To identify the mechanisms related to the increase in cell-mediated immunity in RR, we measured changes in the whole blood-derived transcriptome of patients with leprosy before, during and after RR. We identified that RRs are associated with an IFN-γ induced inflammatory response including an antimicrobial gene network containing the GBP1, GBP2, GBP3 and GBP5 mRNAs in the peripheral blood. Furthermore, we show that GBP1, GBP2 and GBP5 mRNAs are also upregulated at the site of disease in RR patients. In summary, our study suggests that RR involves a systemic induction of IFN-γ regulated genes that contributes to an antimicrobial response against the pathogen, releasing ligands and antigens that can further amplify the inflammatory response.

Plasma Cells Are Obligate Effectors of Enhanced Myelopoiesis in Aging Bone Marrow

Aging results in increased myelopoiesis, which is linked to the increased incidence of myeloid leukemias and production of myeloid-derived suppressor cells. Here, we examined the contribution of plasma cells (PCs) to age-related increases in myelopoiesis, as PCs exhibit immune regulatory function and sequester in bone marrow (BM). PC number was increased in old BM, and they exhibited high expression of genes encoding inflammatory cytokines and pathogen sensors. Antibody-mediated depletion of PCs from old mice reduced the number of myeloid-biased hematopoietic stem cells and mature myeloid cells to levels in young animals, but lymphopoiesis was not rejuvenated, indicating that redundant mechanisms inhibit that process. PCs also regulated the production of inflammatory factors from BM stromal cells, and disruption of the PC-stromal cell circuitry with inhibitors of the cytokines IL-1 and TNF-α attenuated myelopoiesis in old mice. Thus, the age-related increase in myelopoiesis is driven by an inflammatory network orchestrated by PCs.

Dedifferentiation by adenovirus E1A due to inactivation of Hippo pathway effectors YAP and TAZ

In this study, Zemke et al. show that E1A inactivates the Hippo pathway-regulated TEAD coactivators YAP and TAZ by causing their sequestration in the cytoplasm. Their findings suggest that YAP/TAZ function in a developmental checkpoint controlled by signaling from the actin cytoskeleton that prevents differentiation of a progenitor cell until it is in the correct cellular and tissue environment.

Adenovirus transformed cells have a dedifferentiated phenotype. Eliminating E1A in transformed human embryonic kidney cells derepressed ∼2600 genes, generating a gene expression profile closely resembling mesenchymal stem cells (MSCs). This was associated with a dramatic change in cell morphology from one with scant cytoplasm and a globular nucleus to one with increased cytoplasm, extensive actin stress fibers, and actomyosin-dependent flattening against the substratum. E1A-induced hypoacetylation at histone H3 Lys27 and Lys18 (H3K27/18) was reversed. Most of the increase in H3K27/18ac was in enhancers near TEAD transcription factors bound by Hippo signaling-regulated coactivators YAP and TAZ. E1A causes YAP/TAZ cytoplasmic sequestration. After eliminating E1A, YAP/TAZ were transported into nuclei, where they associated with poised enhancers with DNA-bound TEAD4 and H3K4me1. This activation of YAP/TAZ required RHO family GTPase signaling and caused histone acetylation by p300/CBP, chromatin remodeling, and cohesin loading to establish MSC-associated enhancers and then superenhancers. Consistent results were also observed in primary rat embryo kidney cells, human fibroblasts, and human respiratory tract epithelial cells. These results together with earlier studies suggest that YAP/TAZ function in a developmental checkpoint controlled by signaling from the actin cytoskeleton that prevents differentiation of a progenitor cell until it is in the correct cellular and tissue environment.

Dual RNA-Seq of Human Leprosy Lesions Identifies Bacterial Determinants Linked to Host Immune Response

To understand how the interaction between an intracellular bacterium and the host immune system contributes to outcome at the site of infection, we studied leprosy, a disease that forms a clinical spectrum, in which progressive infection by the intracellular bacterium Mycobacterium leprae is characterized by the production of type I IFNs and antibody production. Dual RNA-seq on patient lesions identifies two independent molecular measures of M. leprae, each of which correlates with distinct aspects of the host immune response. The fraction of bacterial transcripts, reflecting bacterial burden, correlates with a host type I IFN gene signature, known to inhibit antimicrobial responses. Second, the bacterial mRNA:rRNA ratio, reflecting bacterial viability, links bacterial heat shock proteins with the BAFF-BCMA host antibody response pathway. Our findings provide a platform for the interrogation of host and pathogen transcriptomes at the site of infection, allowing insight into mechanisms of inflammation in human disease.

Lymphoid-Biased Hematopoietic Stem Cells Are Maintained with Age and Efficiently Generate Lymphoid Progeny

Current models propose that reductions in the number of lymphoid-biased hematopoietic stem cells (Ly-HSCs) underlie age-related declines in lymphopoiesis. We show that Ly-HSCs do not decline in number with age. Old Ly-HSCs exhibit changes in gene expression and a myeloid-biased genetic profile, but we demonstrate that they retain normal lymphoid potential when removed from the old in vivo environment. Additional studies showing that interleukin-1 inhibits Ly-HSC lymphoid potential provide support for the hypothesis that increased production of inflammatory cytokines during aging underlies declines in lymphocyte production. These results indicate that current models proposing that lymphopoiesis declines with age due to loss of Ly-HSCs require revision and provide an additional perspective on why lymphocyte development in the elderly is attenuated.

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Ly-HSCs do not decline in number with age

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Transcriptome changes in old Ly-HSCs result in the acquisition of a myeloid signature

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Ly-HSCs efficiently generate lymphocytes when removed from the old environment

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IL-1 blocks lymphoid potential from Ly-HSCs and My-HSCs

The Placental Transcriptome in Late Gestational Hypoxia Resulting in Murine Intrauterine Growth Restriction Parallels Increased Risk of Adult Cardiometabolic Disease

Intrauterine growth restriction (IUGR) enhances risk for adult onset cardiovascular disease (CVD). The mechanisms underlying IUGR are poorly understood, though inadequate blood flow and oxygen/nutrient provision are considered common endpoints. Based on evidence in humans linking IUGR to adult CVD, we hypothesized that in murine pregnancy, maternal late gestational hypoxia (LG-H) exposure resulting in IUGR would result in (1) placental transcriptome changes linked to risk for later CVD, and 2) adult phenotypes of CVD in the IUGR offspring. After subjecting pregnant mice to hypoxia (10.5% oxygen) from gestational day (GD) 14.5 to 18.5, we undertook RNA sequencing from GD19 placentas. Functional analysis suggested multiple changes in structural and functional genes important for placental health and function, with maximal dysregulation involving vascular and nutrient transport pathways. Concordantly, a ~10% decrease in birthweights and ~30% decrease in litter size was observed, supportive of placental insufficiency. We also found that the LG-H IUGR offspring exhibit increased risk for CVD at 4 months of age, manifesting as hypertension, increased abdominal fat, elevated leptin and total cholesterol concentrations. In summary, this animal model of IUGR links the placental transcriptional response to the stressor of gestational hypoxia to increased risk of developing cardiometabolic disease.

Organoid-Induced Differentiation of Conventional T Cells from Human Pluripotent Stem Cells

The ability to generate T cells from pluripotent stem cells (PSCs) has the potential to transform autologous T cell immunotherapy by facilitating universal, off-the-shelf cell products. However, differentiation of human PSCs into mature, conventional T cells has been challenging with existing methods. We report that a continuous 3D organoid system induced an orderly sequence of commitment and differentiation from PSC-derived embryonic mesoderm through hematopoietic specification and efficient terminal differentiation to naive CD3⁺CD8αβ⁺ and CD3⁺CD4⁺ conventional T cells with a diverse T cell receptor (TCR) repertoire. Introduction of an MHC class I-restricted TCR in PSCs produced naive, antigen-specific CD8αβ⁺ T cells that lacked endogenous TCR expression and showed anti-tumor efficacy in vitro and in vivo. Functional assays and RNA sequencing aligned PSC-derived T cells with primary naive CD8⁺ T cells. The PSC-artificial thymic organoid (ATO) system presented here is an efficient platform for generating functional, mature T cells from human PSCs.

From Big Data to Precision Medicine

For over a decade the term "Big data" has been used to describe the rapid increase in volume, variety and velocity of information available, not just in medical research but in almost every aspect of our lives. As scientists, we now have the capacity to rapidly generate, store and analyse data that, only a few years ago, would have taken many years to compile. However, "Big data" no longer means what it once did. The term has expanded and now refers not to just large data volume, but to our increasing ability to analyse and interpret those data. Tautologies such as "data analytics" and "data science" have emerged to describe approaches to the volume of available information as it grows ever larger. New methods dedicated to improving data collection, storage, cleaning, processing and interpretation continue to be developed, although not always by, or for, medical researchers. Exploiting new tools to extract meaning from large volume information has the potential to drive real change in clinical practice, from personalized therapy and intelligent drug design to population screening and electronic health record mining. As ever, where new technology promises "Big Advances," significant challenges remain. Here we discuss both the opportunities and challenges posed to biomedical research by our increasing ability to tackle large datasets. Important challenges include the need for standardization of data content, format, and clinical definitions, a heightened need for collaborative networks with sharing of both data and expertise and, perhaps most importantly, a need to reconsider how and when analytic methodology is taught to medical researchers. We also set "Big data" analytics in context: recent advances may appear to promise a revolution, sweeping away conventional approaches to medical science. However, their real promise lies in their synergy with, not replacement of, classical hypothesis-driven methods. The generation of novel, data-driven hypotheses based on interpretable models will always require stringent validation and experimental testing. Thus, hypothesis-generating research founded on large datasets adds to, rather than replaces, traditional hypothesis driven science. Each can benefit from the other and it is through using both that we can improve clinical practice.