CITEViz: interactively classify cell populations in CITE-Seq via a flow cytometry-like gating workflow using R-Shiny.

BACKGROUND: The rapid advancement of new genomic sequencing technology has enabled the development of multi-omic single-cell sequencing assays. These assays profile multiple modalities in the same cell and can often yield new insights not revealed with a single modality. For example, Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-Seq) simultaneously profiles the RNA transcriptome and the surface protein expression. The surface protein markers in CITE-Seq can be used to identify cell populations similar to the iterative filtration process in flow cytometry, also called "gating", and is an essential step for downstream analyses and data interpretation. While several packages allow users to interactively gate cells, they often do not process multi-omic sequencing datasets and may require writing redundant code to specify gate boundaries. To streamline the gating process, we developed CITEViz which allows users to interactively gate cells in Seurat-processed CITE-Seq data. CITEViz can also visualize basic quality control (QC) metrics allowing for a rapid and holistic evaluation of CITE-Seq data. RESULTS: We applied CITEViz to a peripheral blood mononuclear cell CITE-Seq dataset and gated for several major blood cell populations (CD14 monocytes, CD4 T cells, CD8 T cells, NK cells, B cells, and platelets) using canonical surface protein markers. The visualization features of CITEViz were used to investigate cellular heterogeneity in CD14 and CD16-expressing monocytes and to detect differential numbers of detected antibodies per patient donor. These results highlight the utility of CITEViz to enable the robust classification of single cell populations. CONCLUSIONS: CITEViz is an R-Shiny app that standardizes the gating workflow in CITE-Seq data for efficient classification of cell populations. Its secondary function is to generate basic feature plots and QC figures specific to multi-omic data. The user interface and internal workflow of CITEViz uniquely work together to produce an organized workflow and sensible data structures for easy data retrieval. This package leverages the strengths of biologists and computational scientists to assess and analyze multi-omic single-cell datasets. In conclusion, CITEViz streamlines the flow cytometry gating workflow in CITE-Seq data to help facilitate novel hypothesis generation.

A framework for considering prior information in network-based approaches to omics data analysis.

For decades, molecular biologists have been uncovering the mechanics of biological systems. Efforts to bring their findings together have led to the development of multiple databases and information systems that capture and present pathway information in a computable network format. Concurrently, the advent of modern omics technologies has empowered researchers to systematically profile cellular processes across different modalities. Numerous algorithms, methodologies, and tools have been developed to use prior knowledge networks (PKNs) in the analysis of omics datasets. Interestingly, it has been repeatedly demonstrated that the source of prior knowledge can greatly impact the results of a given analysis. For these methods to be successful it is paramount that their selection of PKNs is amenable to the data type and the computational task they aim to accomplish. Here we present a five-level framework that broadly describes network models in terms of their scope, level of detail, and ability to inform causal predictions. To contextualize this framework, we review a handful of network-based omics analysis methods at each level, while also describing the computational tasks they aim to accomplish.

Disruption of the MYC Superenhancer Complex by Dual Targeting of FLT3 and LSD1 in Acute Myeloid Leukemia.

Mutations in Fms-like tyrosine kinase 3 (FLT3) are common drivers in acute myeloid leukemia (AML) yet FLT3 inhibitors only provide modest clinical benefit. Prior work has shown that inhibitors of lysine-specific demethylase 1 (LSD1) enhance kinase inhibitor activity in AML. Here we show that combined LSD1 and FLT3 inhibition induces synergistic cell death in FLT3-mutant AML. Multi-omic profiling revealed that the drug combination disrupts STAT5, LSD1, and GFI1 binding at the MYC blood superenhancer, suppressing superenhancer accessibility as well as MYC expression and activity. The drug combination simultaneously results in the accumulation of repressive H3K9me1 methylation, an LSD1 substrate, at MYC target genes. We validated these findings in 72 primary AML samples with the nearly every sample demonstrating synergistic responses to the drug combination. Collectively, these studies reveal how epigenetic therapies augment the activity of kinase inhibitors in FLT3-ITD (internal tandem duplication) AML. IMPLICATIONS: This work establishes the synergistic efficacy of combined FLT3 and LSD1 inhibition in FLT3-ITD AML by disrupting STAT5 and GFI1 binding at the MYC blood-specific superenhancer complex.

Cell-type-specific responses to the microbiota across all tissues of the larval zebrafish.

Animal development proceeds in the presence of intimate microbial associations, but the extent to which different host cells across the body respond to resident microbes remains to be fully explored. Using the vertebrate model organism, the larval zebrafish, we assessed transcriptional responses to the microbiota across the entire body at single-cell resolution. We find that cell types across the body, not limited to tissues at host-microbe interfaces, respond to the microbiota. Responses are cell-type-specific, but across many tissues the microbiota enhances cell proliferation, increases metabolism, and stimulates a diversity of cellular activities, revealing roles for the microbiota in promoting developmental plasticity. This work provides a resource for exploring transcriptional responses to the microbiota across all cell types of the vertebrate body and generating new hypotheses about the interactions between vertebrate hosts and their microbiota.

GoPeaks: histone modification peak calling for CUT&Tag.

Genome-wide mapping of histone modifications is critical to understanding transcriptional regulation. CUT&Tag is a new method for profiling histone modifications, offering improved sensitivity and decreased cost compared with ChIP-seq. Here, we present GoPeaks, a peak calling method specifically designed for histone modification CUT&Tag data. We compare the performance of GoPeaks against commonly used peak calling algorithms to detect histone modifications that display a range of peak profiles and are frequently used in epigenetic studies. We find that GoPeaks robustly detects genome-wide histone modifications and, notably, identifies a substantial number of H3K27ac peaks with improved sensitivity compared to other standard algorithms.

PU.1 and MYC transcriptional network defines synergistic drug responses to KIT and LSD1 inhibition in acute myeloid leukemia.

Responses to kinase-inhibitor therapy in AML are frequently short-lived due to the rapid development of resistance, limiting the clinical efficacy. Combination therapy may improve initial therapeutic responses by targeting pathways used by leukemia cells to escape monotherapy. Here we report that combined inhibition of KIT and lysine-specific demethylase 1 (LSD1) produces synergistic cell death in KIT-mutant AML cell lines and primary patient samples. This drug combination evicts both MYC and PU.1 from chromatin driving cell cycle exit. Using a live cell biosensor for AKT activity, we identify early adaptive changes in kinase signaling following KIT inhibition that are reversed with the addition of LSD1 inhibitor via modulation of the GSK3a/b axis. Multi-omic analyses, including scRNA-seq, ATAC-seq and CUT&Tag, confirm these mechanisms in primary KIT-mutant AML. Collectively, this work provides rational for a clinical trial to assess the efficacy of KIT and LSD1 inhibition in patients with KIT-mutant AML.

Mutated SETBP1 activates transcription of Myc programs to accelerate CSF3R-driven myeloproliferative neoplasms.

Colony stimulating factor 3 receptor (CSF3R) mutations lead to JAK pathway activation and are the molecular hallmark of chronic neutrophilic leukemia (CNL). Approximately half of patients with CNL also have mutations in SET binding protein 1 (SETBP1). In this study, we developed models of SETBP1-mutated leukemia to understand the role that SETBP1 plays in CNL. SETBP1 mutations promote self-renewal of CSF3R-mutated hematopoietic progenitors in vitro and prevent cells from undergoing terminal differentiation. In vivo, SETBP1 mutations accelerate leukemia progression, leading to the rapid development of hepatosplenomegaly and granulocytosis. Through transcriptomic and epigenomic profiling, we found that SETBP1 enhances progenitor-associated programs, most strongly upregulating Myc and Myc target genes. This upregulation of Myc can be reversed by LSD1 inhibitors. In summary, we found that SETBP1 mutations promote aggressive hematopoietic cell expansion when expressed with mutated CSF3R through the upregulation of Myc-associated gene expression programs.

Chronic cerebral lipocalin 2 exposure elicits hippocampal neuronal dysfunction and cognitive impairment.

Lipocalin 2 (LCN2) is a pleiotropic molecule that is induced in the central nervous system (CNS) in several acute and chronic pathologies. The acute induction of LCN2 evolved as a beneficial process, aimed at combating bacterial infection through the sequestration of iron from pathogens, while the role of LCN2 during chronic, non-infectious disease remains unclear, and recent studies suggest that LCN2 is neurotoxic. However, whether LCN2 is sufficient to induce behavioral and cognitive alterations remains unclear. In this paper, we sought to address the role of cerebral LCN2 on cognition in both acute and chronic settings. We demonstrate that LCN2 is robustly induced in the CNS during both acute and chronic inflammatory conditions, including LPS-based sepsis and cancer cachexia. In vivo, LPS challenge results in a global induction of LCN2 in the central nervous system, while cancer cachexia results in a distribution specific to the vasculature. Similar to these in vivo observations, in vitro modeling demonstrated that both glia and cerebral endothelium produce and secrete LCN2 when challenged with LPS, while only cerebral endothelium secrete LCN2 when challenged with cancer-conditioned medium. Chronic, but not short-term, cerebral LCN2 exposure resulted in reduced hippocampal neuron staining intensity, an increase in newborn neurons, microglial activation, and increased CNS immune cell infiltration, while gene set analyses suggested these effects were mediated through melanocortin-4 receptor independent mechanisms. RNA sequencing analyses of primary hippocampal neurons revealed a distinct transcriptome associated with prolonged LCN2 exposure, and ontology analysis was suggestive of altered neurite growth and abnormal spatial learning. Indeed, LCN2-treated hippocampal neurons display blunted neurite processes, and mice exposed to prolonged cerebral LCN2 levels experienced a reduction in spatial reference memory as indicated by Y-maze assessment. These findings implicate LCN2 as a pathologic mediator of cognitive decline in the setting of chronic disease.