Analysis of Genetically Diverse Macrophages Reveals Local and Domain-wide Mechanisms that Control Transcription Factor Binding and Function.

Non-coding genetic variation is a major driver of phenotypic diversity and allows the investigation of mechanisms that control gene expression. Here, we systematically investigated the effects of >50 million variations from five strains of mice on mRNA, nascent transcription, transcription start sites, and transcription factor binding in resting and activated macrophages. We observed substantial differences associated with distinct molecular pathways. Evaluating genetic variation provided evidence for roles of ∼100 TFs in shaping lineage-determining factor binding. Unexpectedly, a substantial fraction of strain-specific factor binding could not be explained by local mutations. Integration of genomic features with chromatin interaction data provided evidence for hundreds of connected cis-regulatory domains associated with differences in transcription factor binding and gene expression. This system and the >250 datasets establish a substantial new resource for investigation of how genetic variation affects cellular phenotypes.

Histone demethylase LSD1 regulates hematopoietic stem cells homeostasis and protects from death by endotoxic shock.

Hematopoietic stem cells (HSCs) maintain a quiescent state during homeostasis, but with acute infection, they exit the quiescent state to increase the output of immune cells, the so-called "emergency hematopoiesis." However, HSCs' response to severe infection during septic shock and the pathological impact remain poorly elucidated. Here, we report that the histone demethylase KDM1A/LSD1, serving as a critical regulator of mammalian hematopoiesis, is a negative regulator of the response to inflammation in HSCs during endotoxic shock typically observed during acute bacterial or viral infection. Inflammation-induced LSD1 deficiency results in an acute expansion of a pathological population of hyperproliferative and hyperinflammatory myeloid progenitors, resulting in a septic shock phenotype and acute death. Unexpectedly, in vivo administration of bacterial lipopolysaccharide (LPS) to wild-type mice results in acute suppression of LSD1 in HSCs with a septic shock phenotype that resembles that observed following induced deletion of LSD1 The suppression of LSD1 in HSCs is caused, at least in large part, by a cohort of inflammation-induced microRNAs. Significantly, reconstitution of mice with bone marrow progenitor cells expressing inhibitors of these inflammation-induced microRNAs blocked the suppression of LSD1 in vivo following acute LPS administration and prevented mortality from endotoxic shock. Our results indicate that LSD1 activators or miRNA antagonists could serve as a therapeutic approach for life-threatening septic shock characterized by dysfunction of HSCs.

Systemic Influences of Mammary Cancer on Monocytes in Mice.

There is a growing body of evidence that cancer causes systemic changes. These influences are most evident in the bone marrow and the blood, particularly in the myeloid compartment. Here, we show that there is an increase in the number of bone marrow, circulating and splenic monocytes by using mouse models of breast cancer caused by the mammary epithelial expression of the polyoma middle T antigen. Cancer does not affect ratios of classical to non-classical populations of monocytes in the circulation nor does it affect their half-lives. Single cell RNA sequencing also indicates that cancer does not induce any new monocyte populations. Cancer does not change the monocytic progenitor number in the bone marrow, but the proliferation rate of monocytes is higher, thus providing an explanation for the expansion of the circulating numbers. Deep RNA sequencing of these monocytic populations reveals that cancer causes changes in the classical monocyte compartment, with changes evident in bone marrow monocytes and even more so in the blood, suggesting influences in both compartments, with the down-regulation of interferon type 1 signaling and antigen presentation being the most prominent of these. Consistent with this analysis, down-regulated genes are enriched with STAT1/STAT2 binding sites in their promoter, which are transcription factors required for type 1 interferon signaling. However, these transcriptome changes in mice did not replicate those found in patients with breast cancer. Consequently, this mouse model of breast cancer may be insufficient to study the systemic influences of human cancer.

Increasing metadata coverage of SRA BioSample entries using deep learning-based named entity recognition.

High-quality metadata annotations for data hosted in large public repositories are essential for research reproducibility and for conducting fast, powerful and scalable meta-analyses. Currently, a majority of sequencing samples in the National Center for Biotechnology Information's Sequence Read Archive (SRA) are missing metadata across several categories. In an effort to improve the metadata coverage of these samples, we leveraged almost 44 million attribute-value pairs from SRA BioSample to train a scalable, recurrent neural network that predicts missing metadata via named entity recognition (NER). The network was first trained to classify short text phrases according to 11 metadata categories and achieved an overall accuracy and area under the receiver operating characteristic curve of 85.2% and 0.977, respectively. We then applied our classifier to predict 11 metadata categories from the longer TITLE attribute of samples, evaluating performance on a set of samples withheld from model training. Prediction accuracies were high when extracting sample Genus/Species (94.85%), Condition/Disease (95.65%) and Strain (82.03%) from TITLEs, with lower accuracies and lack of predictions for other categories highlighting multiple issues with the current metadata annotations in BioSample. These results indicate the utility of recurrent neural networks for NER-based metadata prediction and the potential for models such as the one presented here to increase metadata coverage in BioSample while minimizing the need for manual curation. Database URL: https://github.com/cartercompbio/PredictMEE.

Macrophage Syk-PI3Kγ Inhibits Antitumor Immunity: SRX3207, a Novel Dual Syk-PI3K Inhibitory Chemotype Relieves Tumor Immunosuppression.

Macrophages (MΦ) play a critical role in tumor growth, immunosuppression, and inhibition of adaptive immune responses in cancer. Hence, targeting signaling pathways in MΦs that promote tumor immunosuppression will provide therapeutic benefit. PI3Kγ has been recently established by our group and others as a novel immuno-oncology target. Herein, we report that an MΦ Syk-PI3K axis drives polarization of immunosuppressive MΦs that establish an immunosuppressive tumor microenvironment in in vivo syngeneic tumor models. Genetic or pharmacologic inhibition of Syk and/or PI3Kγ in MΦs promotes a proinflammatory MΦ phenotype, restores CD8+ T-cell activity, destabilizes HIF under hypoxia, and stimulates an antitumor immune response. Assay for transposase-accessible Chromatin using Sequencing (ATAC-seq) analyses on the bone marrow-derived macrophages (BMDM) show that inhibition of Syk kinase promotes activation and binding of NF-κB motif in SykMC-KO BMDMs, thus stimulating immunostimulatory transcriptional programming in MΦs to suppress tumor growth. Finally, we have developed in silico the "first-in-class" dual Syk/PI3K inhibitor, SRX3207, for the combinatorial inhibition of Syk and PI3K in one small molecule. This chemotype demonstrates efficacy in multiple tumor models and represents a novel combinatorial approach to activate antitumor immunity.

Extracting allelic read counts from 250,000 human sequencing runs in Sequence Read Archive.

The Sequence Read Archive (SRA) contains over one million publicly available sequencing runs from various studies using a variety of sequencing library strategies. These data inherently contain information about underlying genomic sequence variants which we exploit to extract allelic read counts on an unprecedented scale. We reprocessed over 250,000 human sequencing runs (>1000 TB data worth of raw sequence data) into a single unified dataset of allelic read counts for nearly 300,000 variants of biomedical relevance curated by NCBI dbSNP, where germline variants were detected in a median of 912 sequencing runs, and somatic variants were detected in a median of 4,876 sequencing runs, suggesting that this dataset facilitates identification of sequencing runs that harbor variants of interest. Allelic read counts obtained using a targeted alignment were very similar to read counts obtained from whole-genome alignment. Analyzing allelic read count data for matched DNA and RNA samples from tumors, we find that RNA-seq can also recover variants identified by Whole Exome Sequencing (WXS), suggesting that reprocessed allelic read counts can support variant detection across different library strategies in SRA. This study provides a rich database of known human variants across SRA samples that can support future meta-analyses of human sequence variation.

SF2523: Dual PI3K/BRD4 Inhibitor Blocks Tumor Immunosuppression and Promotes Adaptive Immune Responses in Cancer.

Macrophages (MΘs) are key immune infiltrates in solid tumors and serve as major drivers behind tumor growth, immune suppression, and inhibition of adaptive immune responses in the tumor microenvironment (TME). Bromodomain and extraterminal (BET) protein, BRD4, which binds to acetylated lysine on histone tails, has recently been reported to promote gene transcription of proinflammatory cytokines but has rarely been explored for its role in IL4-driven MΘ transcriptional programming and MΘ-mediated immunosuppression in the TME. Herein, we report that BET bromodomain inhibitor, JQ1, blocks association of BRD4 with promoters of arginase and other IL4-driven MΘ genes, which promote immunosuppression in TME. Pharmacologic inhibition of BRD4 using JQ1 and/or PI3K using dual PI3K/BRD4 inhibitor SF2523 (previously reported by our group as a potent inhibitor to block tumor growth and metastasis in various cancer models) suppresses tumor growth in syngeneic and spontaneous murine cancer models; reduces infiltration of myeloid-derived suppressor cells; blocks polarization of immunosuppressive MΘs; restores CD8+ T-cell activity; and stimulates antitumor immune responses. Finally, our results suggest that BRD4 regulates the immunosuppressive myeloid TME, and BET inhibitors and dual PI3K/BRD4 inhibitors are therapeutic strategies for cancers driven by the MΘ-dependent immunosuppressive TME.

Transcriptional control of microglia phenotypes in health and disease.

Microglia are the main resident macrophage population of the CNS and perform numerous functions required for CNS development, homeostasis, immunity, and repair. Many lines of evidence also indicate that dysregulation of microglia contributes to the pathogenesis of neurodegenerative and behavioral diseases. These observations provide a compelling argument to more clearly define the mechanisms that control microglia identity and function in health and disease. In this Review, we present a conceptual framework for how different classes of transcription factors interact to select and activate regulatory elements that control microglia development and their responses to internal and external signals. We then describe functions of specific transcription factors in normal and pathological contexts and conclude with a consideration of open questions to be addressed in the future.

An environment-dependent transcriptional network specifies human microglia identity.

Microglia play essential roles in central nervous system (CNS) homeostasis and influence diverse aspects of neuronal function. However, the transcriptional mechanisms that specify human microglia phenotypes are largely unknown. We examined the transcriptomes and epigenetic landscapes of human microglia isolated from surgically resected brain tissue ex vivo and after transition to an in vitro environment. Transfer to a tissue culture environment resulted in rapid and extensive down-regulation of microglia-specific genes that were induced in primitive mouse macrophages after migration into the fetal brain. Substantial subsets of these genes exhibited altered expression in neurodegenerative and behavioral diseases and were associated with noncoding risk variants. These findings reveal an environment-dependent transcriptional network specifying microglia-specific programs of gene expression and facilitate efforts to understand the roles of microglia in human brain diseases.

Evidence for a common evolutionary rate in metazoan transcriptional networks.

Genome sequences diverge more rapidly in mammals than in other animal lineages, such as birds or insects. However, the effect of this rapid divergence on transcriptional evolution remains unclear. Recent reports have indicated a faster divergence of transcription factor binding in mammals than in insects, but others found the reverse for mRNA expression. Here, we show that these conflicting interpretations resulted from differing methodologies. We performed an integrated analysis of transcriptional network evolution by examining mRNA expression, transcription factor binding and cis-regulatory motifs across >25 animal species, including mammals, birds and insects. Strikingly, we found that transcriptional networks evolve at a common rate across the three animal lineages. Furthermore, differences in rates of genome divergence were greatly reduced when restricting comparisons to chromatin-accessible sequences. The evolution of transcription is thus decoupled from the global rate of genome sequence evolution, suggesting that a small fraction of the genome regulates transcription.