Single-Cell Transcriptomics Reveals Early Emergence of Liver Parenchymal and Non-parenchymal Cell Lineages.

The cellular complexity and scale of the early liver have constrained analyses examining its emergence during organogenesis. To circumvent these issues, we analyzed 45,334 single-cell transcriptomes from embryonic day (E)7.5, when endoderm progenitors are specified, to E10.5 liver, when liver parenchymal and non-parenchymal cell lineages emerge. Our data detail divergence of vascular and sinusoidal endothelia, including a distinct transcriptional profile for sinusoidal endothelial specification by E8.75. We characterize two distinct mesothelial cell types as well as early hepatic stellate cells and reveal distinct spatiotemporal distributions for these populations. We capture transcriptional profiles for hepatoblast specification and migration, including the emergence of a hepatomesenchymal cell type and evidence for hepatoblast collective cell migration. Further, we identify cell-cell interactions during the organization of the primitive sinusoid. This study provides a comprehensive atlas of liver lineage establishment from the endoderm and mesoderm through to the organization of the primitive sinusoid at single-cell resolution.

High-throughput phenotyping reveals expansive genetic and structural underpinnings of immune variation.

By developing a high-density murine immunophenotyping platform compatible with high-throughput genetic screening, we have established profound contributions of genetics and structure to immune variation (http://www.immunophenotype.org). Specifically, high-throughput phenotyping of 530 unique mouse gene knockouts identified 140 monogenic 'hits', of which most had no previous immunologic association. Furthermore, hits were collectively enriched in genes for which humans show poor tolerance to loss of function. The immunophenotyping platform also exposed dense correlation networks linking immune parameters with each other and with specific physiologic traits. Such linkages limit freedom of movement for individual immune parameters, thereby imposing genetically regulated 'immunologic structures', the integrity of which was associated with immunocompetence. Hence, we provide an expanded genetic resource and structural perspective for understanding and monitoring immune variation in health and disease.

Signalling pathways and transcriptional regulators orchestrating liver development and cancer.

Liver development is controlled by key signals and transcription factors that drive cell proliferation, migration, differentiation and functional maturation. In the adult liver, cell maturity can be perturbed by genetic and environmental factors that disrupt hepatic identity and function. Developmental signals and fetal genetic programmes are often dysregulated or reactivated, leading to dedifferentiation and disease. Here, we highlight signalling pathways and transcriptional regulators that drive liver cell development and primary liver cancers. We also discuss emerging models derived from pluripotent stem cells, 3D organoids and bioengineering for improved studies of signalling pathways in liver cancer and regenerative medicine.

SOX9 reprograms endothelial cells by altering the chromatin landscape.

The transcription factor SOX9 is activated at the onset of endothelial-to-mesenchymal transition (EndMT) during embryonic development and in pathological conditions. Its roles in regulating these processes, however, are not clear. Using human umbilical vein endothelial cells (HUVECs) as an EndMT model, we show that SOX9 expression alone is sufficient to activate mesenchymal genes and steer endothelial cells towards a mesenchymal fate. By genome-wide mapping of the chromatin landscape, we show that SOX9 displays features of a pioneer transcription factor, such as opening of chromatin and leading to deposition of active histone modifications at silent chromatin regions, guided by SOX dimer motifs and H2A.Z enrichment. We further observe highly transient and dynamic SOX9 binding, possibly promoted through its eviction by histone phosphorylation. However, while SOX9 binding is dynamic, changes in the chromatin landscape and cell fate induced by SOX9 are persistent. Finally, our analysis of single-cell chromatin accessibility indicates that SOX9 opens chromatin to drive EndMT in atherosclerotic lesions in vivo. This study provides new insight into key molecular functions of SOX9 and mechanisms of EndMT and highlights the crucial developmental role of SOX9 and relevance to human disease.

High throughput automated analysis of big flow cytometry data.

The rapid expansion of flow cytometry applications has outpaced the functionality of traditional manual analysis tools used to interpret flow cytometry data. Scientists are faced with the daunting prospect of manually identifying interesting cell populations in 50-dimensional datasets, equalling the complexity previously only reached in mass cytometry. Data can no longer be analyzed or interpreted fully by manual approaches. While automated gating has been the focus of intense efforts, there are many significant additional steps to the analytical pipeline (e.g., cleaning the raw files, event outlier detection, extracting immunophenotypes). We review the components of a customized automated analysis pipeline that can be generally applied to large scale flow cytometry data. We demonstrate these methodologies on data collected by the International Mouse Phenotyping Consortium (IMPC).

Ca2+ transients in astrocyte fine processes occur via Ca2+ influx in the adult mouse hippocampus.

Astrocytes display complex morphologies with an array of fine extensions extending from the soma and the primary thick processes. Until the use of genetically encoded calcium indicators (GECIs) selectively expressed in astrocytes, Ca2+ signaling was only examined in soma and thick primary processes of astrocytes where Ca2+ -sensitive fluorescent dyes could be imaged. GECI imaging in astrocytes revealed a previously unsuspected pattern of spontaneous Ca2+ transients in fine processes that has not been observed without chronic expression of GECIs, raising potential concerns about the effects of GECI expression. Here, we perform two-photon imaging of Ca2+ transients in adult CA1 hippocampal astrocytes using a new single-cell patch-loading strategy to image Ca2+ -sensitive fluorescent dyes in the cytoplasm of fine processes. We observed that astrocyte fine processes exhibited a high frequency of spontaneous Ca2+ transients whereas astrocyte soma rarely showed spontaneous Ca2+ oscillations similar to previous reports using GECIs. We exploited this new approach to show these signals were independent of neuronal spiking, metabotropic glutamate receptor (mGluR) activity, TRPA1 channels, and L- or T-type voltage-gated calcium channels. Removal of extracellular Ca2+ almost completely and reversibly abolished the spontaneous signals while IP3 R2 KO mice also exhibited spontaneous and compartmentalized signals, suggesting they rely on influx of extracellular Ca2+ . The Ca2+ influx dependency of the spontaneous signals in patch-loaded astrocytes was also observed in astrocytes expressing GCaMP3, further highlighting the presence of Ca2+ influx pathways in astrocytes. The mechanisms underlying these localized Ca2+ signals are critical for understanding how astrocytes regulate important functions in the adult brain. GLIA 2016;64:2093-2103.

HNF4A guides the MLL4 complex to establish and maintain H3K4me1 at gene regulatory elements.

Hepatocyte nuclear factor 4A (HNF4A/NR2a1), a transcriptional regulator of hepatocyte identity, controls genes that are crucial for liver functions, primarily through binding to enhancers. In mammalian cells, active and primed enhancers are marked by monomethylation of histone 3 (H3) at lysine 4 (K4) (H3K4me1) in a cell type-specific manner. How this modification is established and maintained at enhancers in connection with transcription factors (TFs) remains unknown. Using analysis of genome-wide histone modifications, TF binding, chromatin accessibility and gene expression, we show that HNF4A is essential for an active chromatin state. Using HNF4A loss and gain of function experiments in vivo and in cell lines in vitro, we show that HNF4A affects H3K4me1, H3K27ac and chromatin accessibility, highlighting its contribution to the establishment and maintenance of a transcriptionally permissive epigenetic state. Mechanistically, HNF4A interacts with the mixed-lineage leukaemia 4 (MLL4) complex facilitating recruitment to HNF4A-bound regions. Our findings indicate that HNF4A enriches H3K4me1, H3K27ac and establishes chromatin opening at transcriptional regulatory regions.

Cell diversity and plasticity during atrioventricular heart valve EMTs.

Epithelial-to-mesenchymal transitions (EMTs) of both endocardium and epicardium guide atrioventricular heart valve formation, but the cellular complexity and small scale of this tissue have restricted analyses. To circumvent these issues, we analyzed over 50,000 murine single-cell transcriptomes from embryonic day (E)7.75 hearts to E12.5 atrioventricular canals. We delineate mesenchymal and endocardial bifurcation during endocardial EMT, identify a distinct, transdifferentiating epicardial population during epicardial EMT, and reveal the activation of epithelial-mesenchymal plasticity during both processes. In Sox9-deficient valves, we observe increased epithelial-mesenchymal plasticity, indicating a role for SOX9 in promoting endothelial and mesenchymal cell fate decisions. Lastly, we deconvolve cell interactions guiding the initiation and progression of cardiac valve EMTs. Overall, these data reveal mechanisms of emergence of mesenchyme from endocardium or epicardium at single-cell resolution and will serve as an atlas of EMT initiation and progression with broad implications in regenerative medicine and cancer biology.

Characterization of Adaptive-like γδ T Cells in Ugandan Infants during Primary Cytomegalovirus Infection.

Gamma-delta (γδ) T cells are unconventional T cells that help control cytomegalovirus (CMV) infection in adults. γδ T cells develop early in gestation, and a fetal public γδ T cell receptor (TCR) clonotype is detected in congenital CMV infections. However, age-dependent γδ T cell responses to primary CMV infection are not well-understood. Flow cytometry and TCR sequencing was used to comprehensively characterize γδ T cell responses to CMV infection in a cohort of 32 infants followed prospectively from birth. Peripheral blood γδ T cell frequencies increased during infancy, and were higher among CMV-infected infants relative to uninfected. Clustering analyses revealed associations between CMV infection and activation marker expression on adaptive-like Vδ1 and Vδ3, but not innate-like Vγ9Vδ2 γδ T cell subsets. Frequencies of NKG2C+CD57+ γδ T cells were temporally associated with the quantity of CMV shed in saliva by infants with primary infection. The public γδ TCR clonotype was only detected in CMV-infected infants <120 days old and at lower frequencies than previously described in fetal infections. Our findings support the notion that CMV infection drives age-dependent expansions of specific γδ T cell populations, and provide insight for novel strategies to prevent CMV transmission and disease.

"Age Related Differences in the Biology of Chronic Graft-Versus-Host Disease After Hematopoietic Stem Cell Transplantation".

It is established that pediatric hematopoietic stem cell transplant (HSCT) recipients have a lower rate of chronic graft-versus-host disease (cGvHD) compared to adults. Our group has previously published immune profiles changes associated with cGvHD of clinically well-defined adult and pediatric HSCT cohorts. Since all analyses were performed by the same research group and analyzed using identical methodology, we first compared our previous immune profile analyses between adults and children. We then performed additional analyses comparing the T cell populations across age groups, and a sub-analysis of the impact of the estimated pubertal status at time of HSCT in our pediatric cohort. In all analyses, we corrected for clinical covariates including total body irradiation and time of onset of cGvHD. Three consistent findings were seen in both children and adults, including elevations of ST2 and naive helper T (Th) cells and depression of NKreg cells. However, significant differences exist between children and adults in certain cytokines, B cell, and Treg populations. In children, we saw a broad suppression of newly formed B (NF-B) cells, whereas adults exhibited an increase in T1-CD21lo B cells and a decrease in T1-CD24hiCD38hi B cells. Prepubertal children had elevations of aminopeptidase N (sCD13) and ICAM-1. Treg abnormalities in children appeared to be primarily in memory Treg cells, whereas in adults the abnormalities were in naïve Treg cells. In adults, the loss of PD1 expression in naïve Treg and naïve Th cells was associated with cGvHD. We discuss the possible mechanisms for these age-related differences, and how they might theoretically impact on different therapeutic approaches to cGvHD between children and adults.

Multi-Omic Data Integration Allows Baseline Immune Signatures to Predict Hepatitis B Vaccine Response in a Small Cohort.

Background: Vaccination remains one of the most effective means of reducing the burden of infectious diseases globally. Improving our understanding of the molecular basis for effective vaccine response is of paramount importance if we are to ensure the success of future vaccine development efforts. Methods: We applied cutting edge multi-omics approaches to extensively characterize temporal molecular responses following vaccination with hepatitis B virus (HBV) vaccine. Data were integrated across cellular, epigenomic, transcriptomic, proteomic, and fecal microbiome profiles, and correlated to final HBV antibody titres. Results: Using both an unsupervised molecular-interaction network integration method (NetworkAnalyst) and a data-driven integration approach (DIABLO), we uncovered baseline molecular patterns and pathways associated with more effective vaccine responses to HBV. Biological associations were unravelled, with signalling pathways such as JAK-STAT and interleukin signalling, Toll-like receptor cascades, interferon signalling, and Th17 cell differentiation emerging as important pre-vaccination modulators of response. Conclusion: This study provides further evidence that baseline cellular and molecular characteristics of an individual's immune system influence vaccine responses, and highlights the utility of integrating information across many parallel molecular datasets.

Systems Biology Methods Applied to Blood and Tissue for a Comprehensive Analysis of Immune Response to Hepatitis B Vaccine in Adults.

Conventional vaccine design has been based on trial-and-error approaches, which have been generally successful. However, there have been some major failures in vaccine development and we still do not have highly effective licensed vaccines for tuberculosis, HIV, respiratory syncytial virus, and other major infections of global significance. Approaches at rational vaccine design have been limited by our understanding of the immune response to vaccination at the molecular level. Tools now exist to undertake in-depth analysis using systems biology approaches, but to be fully realized, studies are required in humans with intensive blood and tissue sampling. Methods that support this intensive sampling need to be developed and validated as feasible. To this end, we describe here a detailed approach that was applied in a study of 15 healthy adults, who were immunized with hepatitis B vaccine. Sampling included ~350 mL of blood, 12 microbiome samples, and lymph node fine needle aspirates obtained over a ~7-month period, enabling comprehensive analysis of the immune response at the molecular level, including single cell and tissue sample analysis. Samples were collected for analysis of immune phenotyping, whole blood and single cell gene expression, proteomics, lipidomics, epigenetics, whole blood response to key immune stimuli, cytokine responses, in vitro T cell responses, antibody repertoire analysis and the microbiome. Data integration was undertaken using different approaches-NetworkAnalyst and DIABLO. Our results demonstrate that such intensive sampling studies are feasible in healthy adults, and data integration tools exist to analyze the vast amount of data generated from a multi-omics systems biology approach. This will provide the basis for a better understanding of vaccine-induced immunity and accelerate future rational vaccine design.

ConsensusDriver Improves upon Individual Algorithms for Predicting Driver Alterations in Different Cancer Types and Individual Patients.

Existing cancer driver prediction methods are based on very different assumptions and each of them can detect only a particular subset of driver genes. Here we perform a comprehensive assessment of 18 driver prediction methods on more than 3,400 tumor samples from 15 cancer types, all to determine their suitability in guiding precision medicine efforts. We categorized these methods into five groups: functional impact on proteins in general (FI) or specific to cancer (FIC), cohort-based analysis for recurrent mutations (CBA), mutations with expression correlation (MEC), and methods that use gene interaction network-based analysis (INA). The performance of driver prediction methods varied considerably, with concordance with a gold standard varying from 9% to 68%. FI methods showed relatively poor performance (concordance <22%), while CBA methods provided conservative results but required large sample sizes for high sensitivity. INA methods, through the integration of genomic and transcriptomic data, and FIC methods, by training cancer-specific models, provided the best trade-off between sensitivity and specificity. As the methods were found to predict different subsets of driver genes, we propose a novel consensus-based approach, ConsensusDriver, which significantly improves the quality of predictions (20% increase in sensitivity) in patient subgroups or even individual patients. Consensus-based methods like ConsensusDriver promise to harness the strengths of different driver prediction paradigms.Significance: These findings assess state-of-the-art cancer driver prediction methods and develop a new and improved consensus-based approach for use in precision oncology. Cancer Res; 78(1); 290-301. ©2017 AACR.