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Abstract We develop a large-scale single-cell ATAC-seq method by combining Tn5-based pre-indexing with 10× Genomics barcoding, enabling the indexing of up to 200,000 nuclei across multiple samples in a single reaction. We profile 449,953 nuclei across diverse tissues, including the human cortex, mouse brain, human lung, mouse lung, mouse liver, and lung tissue from a club cell secretory protein knockout (CC16−/−) model. Our study of CC16−/− nuclei uncovers previously underappreciated technical artifacts derived from remnant 129 mouse strain genetic material, which cause profound cell-type-specific changes in regulatory elements near many genes, thereby confounding the interpretation of this commonly referenced mouse model.

Chronic, systemic inflammation is a pathophysiological manifestation of metabolic disorders. Inflammatory signaling leads to elevated glycolytic flux and a metabolic shift towards aerobic glycolysis and lactate generation. This rise in lactate corresponds with increased generation of lactoylLys modifications on histones, mediating transcriptional responses to inflammatory stimuli. Lactoylation is also generated through a non-enzymatic S-to-N acyltransfer from the glyoxalase cycle intermediate, lactoylglutathione (LGSH). Here, we report a regulatory role for LGSH in mediating histone lactoylation and inflammatory signaling. In the absence of the primary LGSH hydrolase, glyoxalase 2 (GLO2), RAW264.7 macrophages display significant elevations in LGSH and histone lactoylation with a corresponding potentiation of the inflammatory response when exposed to lipopolysaccharides. An analysis of chromatin accessibility shows that lactoylation is associated with more compacted chromatin than acetylation in an unstimulated state; upon stimulation, however, regions of the genome associated with lactoylation become markedly more accessible. Lastly, we demonstrate a spontaneous S-to-S acyltransfer of lactate from LGSH to CoA, yielding lactoyl-CoA. This represents the first known mechanism for the generation of this metabolite. Collectively, these data suggest that LGSH, and not intracellular lactate, is the primary driving factor facilitating histone lactoylation and a major contributor to inflammatory signaling.

RationaleCC16 (Club Cell Secretory Protein) is a protein produced by club cells and other non-ciliated epithelial cells within the lungs. CC16 has been shown to protect against the development of obstructive lung diseases and attenuate pulmonary pathogen burden. Despite recent advances in understanding CC16 effects in circulation, the biological mechanisms of CC16 in pulmonary epithelial responses have not been elucidated.ObjectivesWe sought to determine if CC16 deficiency impairs epithelial-driven host responses and identify novel receptors expressed within the pulmonary epithelium through which CC16 imparts activity.MethodsWe utilized mass spectrometry and quantitative proteomics to investigate how CC16 deficiency impacts apically secreted pulmonary epithelial proteins. Mouse tracheal epithelial cells (MTECS), human nasal epithelial cells (HNECs) and mice were studied in naïve conditions and after Mp challenge.Measurements and main resultsWe identified 8 antimicrobial proteins significantly decreased by CC16-/- MTECS, 6 of which were validated by mRNA expression in Severe Asthma Research Program (SARP) cohorts. Short Palate Lung and Nasal Epithelial Clone 1 (SPLUNC1) was the most differentially expressed protein (66-fold) and was the focus of this study. Using a combination of MTECs and HNECs, we found that CC16 enhances pulmonary epithelial-driven SPLUNC1 expression via signaling through the receptor complex Very Late Antigen-2 (VLA-2) and that rCC16 given to mice enhances pulmonary SPLUNC1 production and decreases Mycoplasma pneumoniae (Mp) burden. Likewise, rSPLUNC1 results in decreased Mp burden in mice lacking CC16 mice. The VLA-2 integrin binding site within rCC16 is necessary for induction of SPLUNC1 and the reduction in Mp burden.ConclusionOur findings demonstrate a novel role for CC16 in epithelial-driven host defense by up-regulating antimicrobials and define a novel epithelial receptor for CC16, VLA-2, through which signaling is necessary for enhanced SPLUNC1 production.

Abstract Background The “Assay for Transposase Accessible Chromatin sequencing” (ATAC-seq) is an efficient and easy to implement protocol to measure chromatin accessibility that has been widely used in multiple applications studying gene regulation. While several modifications or variants of the protocol have been published since it was first described, there has not yet been an extensive evaluation of the effects of specific protocol choices head-to-head in a consistent experimental setting. In this study, we tested multiple protocol options for major ATAC-seq components (including three reaction buffers, two reaction temperatures, two enzyme sources, and the use of either native or fixed nuclei) in a well-characterized cell line. With all possible combinations of components, we created 24 experimental conditions with four replicates for each (a total of 96 samples). In addition, we tested the 12 native conditions in a primary sample type (mouse lung tissue) with two different input amounts. Through these extensive comparisons, we were able to observe the effect of different ATAC-seq conditions on data quality and to examine the utility and potential redundancy of various quality metrics. Results In general, native samples yielded more peaks (particularly at loci not overlapping transcription start sites) than fixed samples, and the temperature at which the enzymatic reaction was carried out had a major impact on data quality metrics for both fixed and native nuclei. However, the effect of various conditions tested was not always consistent between the native and fixed samples. For example, the Nextera and Omni buffers were largely interchangeable across all other conditions, while the THS buffer resulted in markedly different profiles in native samples. In-house and commercial enzymes performed similarly. Conclusions We found that the relationship between commonly used measures of library quality differed across temperature and fixation, and so evaluating multiple metrics in assessing the quality of a sample is recommended. Notably, we also found that these choices can bias the functional class of elements profiled and so we recommend evaluating several formulations in any new experiments. Finally, we hope the ATAC-seq workflow formulated in this study on crosslinked samples will help to profile archival clinical specimens.

Abstract The ongoing SARS-CoV-2 pandemic and subsequent demand for viral testing has led to issues in scaling diagnostic lab efforts and in securing basic supplies for collection and processing of samples. This has motivated efforts by the scientific community to establish improved protocols that are more scalable, less resource intensive, and less expensive. One such developmental effort has resulted in an assay called “Swab-Seq”, so named because it was originally developed to work with dry nasal swab samples. The existing gold standard test consists of RNA extracted from a nasopharyngeal (NP) swab that is subjected to quantitative reverse transcription polymerase chain reaction (qRT-PCR). Swab-Seq adapts this method to a next-generation sequencing readout. By pairing this modification with extraction-free sampling techniques, Swab-Seq achieves high scalability, low cost per sample, and a reasonable turnaround time. We evaluated the effectiveness of this assay in a community surveillance setting by testing samples collected from both symptomatic and asymptomatic individuals using the traditional NP swab. In addition, we evaluated extraction-free sampling techniques (both saliva and saline mouth gargle samples). We found the assay to be as clinically sensitive as the qRT-PCR assay, adaptable to multiple sample types, and able to easily accommodate hundreds of samples at a time. We thus provide independent validation of Swab-Seq and extend its utility regarding sample type and sample stability. Assays of this type greatly expand the possibility of routine, noninvasive, repeated testing of asymptomatic individuals suitable for current and potential future needs.

Objective: Type 2 diabetes (T2D) is a complex disease characterized by pancreatic islet dysfunction, insulin resistance, and disruption of blood glucose levels. Genome-wide association studies (GWAS) have identified > 400 independent signals that encode genetic predisposition. More than 90% of associated single-nucleotide polymorphisms (SNPs) localize to non-coding regions and are enriched in chromatin-defined islet enhancer elements, indicating a strong transcriptional regulatory component to disease susceptibility. Pancreatic islets are a mixture of cell types that express distinct hormonal programs, so each cell type may contribute differentially to the underlying regulatory processes that modulate T2D-associated transcriptional circuits. Existing chromatin profiling methods such as ATAC-seq and DNase-seq, applied to islets in bulk, produce aggregate profiles that mask important cellular and regulatory heterogeneity. Methods: We present genome-wide single-cell chromatin accessibility profiles in >1,600 cells derived from a human pancreatic islet sample using single-cell combinatorial indexing ATAC-seq (sci-ATAC-seq). We also developed a deep learning model based on U-Net architecture to accurately predict open chromatin peak calls in rare cell populations. Results: We show that sci-ATAC-seq profiles allow us to deconvolve alpha, beta, and delta cell populations and identify cell-type-specific regulatory signatures underlying T2D. Particularly, T2D GWAS SNPs are significantly enriched in beta cell-specific and across cell-type shared islet open chromatin, but not in alpha or delta cell-specific open chromatin. We also demonstrate, using less abundant delta cells, that deep learning models can improve signal recovery and feature reconstruction of rarer cell populations. Finally, we use co-accessibility measures to nominate the cell-specific target genes at 104 non-coding T2D GWAS signals. Conclusions: Collectively, we identify the islet cell type of action across genetic signals of T2D predisposition and provide higher-resolution mechanistic insights into genetically encoded risk pathways. Keywords: Islet, Epigenomics, Deep learning, Single cell, Chromatin, Type 2 diabetes

Summary: While the immediate and transitory response of breast cancer cells to pathological stiffness in their native microenvironment has been well explored, it remains unclear how stiffness-induced phenotypes are maintained over time after cancer cell dissemination in vivo. Here, we show that fibrotic-like matrix stiffness promotes distinct metastatic phenotypes in cancer cells, which are preserved after transition to softer microenvironments, such as bone marrow. Using differential gene expression analysis of stiffness-responsive breast cancer cells, we establish a multigenic score of mechanical conditioning (MeCo) and find that it is associated with bone metastasis in patients with breast cancer. The maintenance of mechanical conditioning is regulated by RUNX2, an osteogenic transcription factor, established driver of bone metastasis, and mitotic bookmarker that preserves chromatin accessibility at target gene loci. Using genetic and functional approaches, we demonstrate that mechanical conditioning maintenance can be simulated, repressed, or extended, with corresponding changes in bone metastatic potential.

Glycosylphosphatidylinositol-anchored high density lipoprotein–binding protein 1 (GPIHBP1), the protein that shuttles LPL to the capillary lumen, is essential for plasma triglyceride metabolism. When GPIHBP1 is absent, LPL remains stranded within the interstitial spaces and plasma triglyceride hydrolysis is impaired, resulting in severe hypertriglyceridemia. While the functions of GPIHBP1 in intravascular lipolysis are reasonably well understood, no one has yet identified DNA sequences regulating GPIHBP1 expression. In the current studies, we identified an enhancer element located ∼3.6 kb upstream from exon 1 of mouse Gpihbp1. To examine the importance of the enhancer, we used CRISPR/Cas9 genome editing to create mice lacking the enhancer (Gpihbp1 Enh/Enh). Removing the enhancer reduced Gpihbp1 expression by >90% in the liver and by ∼50% in heart and brown adipose tissue. The reduced expression of GPIHBP1 was insufficient to prevent LPL from reaching the capillary lumen, and it did not lead to hypertriglyceridemia–even when mice were fed a high-fat diet. Compound heterozygotes (Gpihbp1 Enh/− mice) displayed further reductions in Gpihbp1 expression and exhibited partial mislocalization of LPL (increased amounts of LPL within the interstitial spaces of the heart), but the plasma triglyceride levels were not perturbed. The enhancer element that we identified represents the first insight into DNA sequences controlling Gpihbp1 expression.

Heterogeneity in endothelial cell (EC) sub-phenotypes is becoming increasingly appreciated in atherosclerosis progression. Still, studies quantifying EC heterogeneity across whole transcriptomes and epigenomes in both in vitro and in vivo models are lacking. Multiomic profiling concurrently measuring transcriptomes and accessible chromatin in the same single cells was performed on six distinct primary cultures of human aortic ECs (HAECs) exposed to activating environments characteristic of the atherosclerotic microenvironment in vitro. Meta-analysis of single-cell transcriptomes across 17 human ex vivo arterial specimens was performed and two computational approaches quantitatively evaluated the similarity in molecular profiles between heterogeneous in vitro and ex vivo cell profiles. HAEC cultures were reproducibly populated by four major clusters with distinct pathway enrichment profiles and modest heterogeneous responses: EC1-angiogenic, EC2-proliferative, EC3-activated/mesenchymal-like, and EC4-mesenchymal. Quantitative comparisons between in vitro and ex vivo transcriptomes confirmed EC1 and EC2 as most canonically EC-like, and EC4 as most mesenchymal with minimal effects elicited by siERG and IL1B. Lastly, accessible chromatin regions unique to EC2 and EC4 were most enriched for coronary artery disease (CAD)-associated single-nucleotide polymorphisms from Genome Wide Association Studies (GWAS), suggesting that these cell phenotypes harbor CAD-modulating mechanisms. Primary EC cultures contain markedly heterogeneous cell subtypes defined by their molecular profiles. Surprisingly, the perturbations used here only modestly shifted cells between subpopulations, suggesting relatively stable molecular phenotypes in culture. Identifying consistently heterogeneous EC subpopulations between in vitro and ex vivo models should pave the way for improving in vitro systems while enabling the mechanisms governing heterogeneous cell state decisions.

The bacterial composition of the human fecal microbiome is influenced by many lifestyle factors, notably diet. It is less clear, however, what role host genetics plays in dictating the composition of bacteria living in the gut. In this study, we examined the association of ~200K host genotypes with the relative abundance of fecal bacterial taxa in a founder population, the Hutterites, during two seasons (n = 91 summer, n = 93 winter, n = 57 individuals collected in both). These individuals live and eat communally, minimizing variation due to environmental exposures, including diet, which could potentially mask small genetic effects. Using a GWAS approach that takes into account the relatedness between subjects, we identified at least 8 bacterial taxa whose abundances were associated with single nucleotide polymorphisms in the host genome in each season (at genome-wide FDR of 20%). For example, we identified an association between a taxon known to affect obesity (genus Akkermansia) and a variant near PLD1, a gene previously associated with body mass index. Moreover, we replicate a previously reported association from a quantitative trait locus (QTL) mapping study of fecal microbiome abundance in mice (genus Lactococcus, rs3747113, P = 3.13 x 10-7). Finally, based on the significance distribution of the associated microbiome QTLs in our study with respect to chromatin accessibility profiles, we identified tissues in which host genetic variation may be acting to influence bacterial abundance in the gut.

One goal of human genetics is to understand how the information for precise and dynamic gene expression programs is encoded in the genome. The interactions of transcription factors (TFs) with DNA regulatory elements clearly play an important role in determining gene expression outputs, yet the regulatory logic underlying functional transcription factor binding is poorly understood. Many studies have focused on characterizing the genomic locations of TF binding, yet it is unclear to what extent TF binding at any specific locus has functional consequences with respect to gene expression output. To evaluate the context of functional TF binding we knocked down 59 TFs and chromatin modifiers in one HapMap lymphoblastoid cell line. We then identified genes whose expression was affected by the knockdowns. We intersected the gene expression data with transcription factor binding data (based on ChIP-seq and DNase-seq) within 10 kb of the transcription start sites of expressed genes. This combination of data allowed us to infer functional TF binding. Using this approach, we found that only a small subset of genes bound by a factor were differentially expressed following the knockdown of that factor, suggesting that most interactions between TF and chromatin do not result in measurable changes in gene expression levels of putative target genes. We found that functional TF binding is enriched in regulatory elements that harbor a large number of TF binding sites, at sites with predicted higher binding affinity, and at sites that are enriched in genomic regions annotated as "active enhancers."