A metabolic switch orchestrated by IL-18 and the cyclic dinucleotide cGAMP programs intestinal tolerance.

Tissues are exposed to diverse inflammatory challenges that shape future inflammatory responses. While cellular metabolism regulates immune function, how metabolism programs and stabilizes immune states within tissues and tunes susceptibility to inflammation is poorly understood. Here, we describe an innate immune metabolic switch that programs long-term intestinal tolerance. Intestinal interleukin-18 (IL-18) stimulation elicited tolerogenic macrophages by preventing their proinflammatory glycolytic polarization via metabolic reprogramming to fatty acid oxidation (FAO). FAO reprogramming was triggered by IL-18 activation of SLC12A3 (NCC), leading to sodium influx, release of mitochondrial DNA, and activation of stimulator of interferon genes (STING). FAO was maintained in macrophages by a bistable switch that encoded memory of IL-18 stimulation and by intercellular positive feedback that sustained the production of macrophage-derived 2'3'-cyclic GMP-AMP (cGAMP) and epithelial-derived IL-18. Thus, a tissue-reinforced metabolic switch encodes durable immune tolerance in the gut and may enable reconstructing compromised immune tolerance in chronic inflammation.

Single-cell analysis reveals cellular and molecular factors counteracting HPV-positive oropharyngeal cancer immunotherapy outcomes.

BACKGROUND: Oropharyngeal squamous cell carcinoma (OPSCC) induced by human papillomavirus (HPV-positive) is associated with better clinical outcomes than HPV-negative OPSCC. However, the clinical benefits of immunotherapy in patients with HPV-positive OPSCC remain unclear. METHODS: To identify the cellular and molecular factors that limited the benefits associated with HPV in OPSCC immunotherapy, we performed single-cell RNA (n=20) and T-cell receptor sequencing (n=10) analyses of tonsil or base of tongue tumor biopsies prior to immunotherapy. Primary findings from our single-cell analysis were confirmed through immunofluorescence experiments, and secondary validation analysis were performed via publicly available transcriptomics data sets. RESULTS: We found significantly higher transcriptional diversity of malignant cells among non-responders to immunotherapy, regardless of HPV infection status. We also observed a significantly larger proportion of CD4+ follicular helper T cells (Tfh) in HPV-positive tumors, potentially due to enhanced Tfh differentiation. Most importantly, CD8+ resident memory T cells (Trm) with elevated KLRB1 (encoding CD161) expression showed an association with dampened antitumor activity in patients with HPV-positive OPSCC, which may explain their heterogeneous clinical outcomes. Notably, all HPV-positive patients, whose Trm presented elevated KLRB1 levels, showed low expression of CLEC2D (encoding the CD161 ligand) in B cells, which may reduce tertiary lymphoid structure activity. Immunofluorescence of HPV-positive tumors treated with immune checkpoint blockade showed an inverse correlation between the density of CD161+ Trm and changes in tumor size. CONCLUSIONS: We found that CD161+ Trm counteracts clinical benefits associated with HPV in OPSCC immunotherapy. This suggests that targeted inhibition of CD161 in Trm could enhance the efficacy of immunotherapy in HPV-positive oropharyngeal cancers. TRIAL REGISTRATION NUMBER: NCT03737968.

Integrative single-cell characterization of a frugivorous and an insectivorous bat kidney and pancreas.

Frugivory evolved multiple times in mammals, including bats. However, the cellular and molecular components driving it remain largely unknown. Here, we use integrative single-cell sequencing (scRNA-seq and scATAC-seq) on insectivorous (Eptesicus fuscus; big brown bat) and frugivorous (Artibeus jamaicensis; Jamaican fruit bat) bat kidneys and pancreases and identify key cell population, gene expression and regulatory differences associated with the Jamaican fruit bat that also relate to human disease, particularly diabetes. We find a decrease in loop of Henle and an increase in collecting duct cells, and differentially active genes and regulatory elements involved in fluid and electrolyte balance in the Jamaican fruit bat kidney. The Jamaican fruit bat pancreas shows an increase in endocrine and a decrease in exocrine cells, and differences in genes and regulatory elements involved in insulin regulation. We also find that these frugivorous bats share several molecular characteristics with human diabetes. Combined, our work provides insights from a frugivorous mammal that could be leveraged for therapeutic purposes.

Integrative single-cell characterization of frugivory adaptations in the bat kidney and pancreas.

Frugivory evolved multiple times in mammals, including bats. However, the cellular and molecular components driving it remain largely unknown. Here, we used integrative single-cell sequencing on insectivorous and frugivorous bat kidneys and pancreases and identified key cell population, gene expression and regulatory element differences associated with frugivorous adaptation that also relate to human disease, particularly diabetes. We found an increase in collecting duct cells and differentially active genes and regulatory elements involved in fluid and electrolyte balance in the frugivore kidney. In the frugivorous pancreas, we observed an increase in endocrine and a decrease in exocrine cells and differences in genes and regulatory elements involved in insulin regulation. Combined, our work provides novel insights into frugivorous adaptation that also could be leveraged for therapeutic purposes.

COVID-GWAB: A Web-Based Prediction of COVID-19 Host Genes via Network Boosting of Genome-Wide Association Data.

Host genetics affect both the susceptibility and response to viral infection. Searching for host genes that contribute to COVID-19, the Host Genetics Initiative (HGI) was formed to investigate the genetic factors involved in COVID-19 via genome-wide association studies (GWAS). The GWAS suffer from limited statistical power and in general, only a few genes can pass the conventional significance thresholds. This statistical limitation may be overcome by boosting weak association signals through integrating independent functional information such as molecular interactions. Additionally, the boosted results can be evaluated by various independent data for further connections to COVID-19. We present COVID-GWAB, a web-based tool to boost original GWAS signals from COVID-19 patients by taking the signals of the interactome neighbors. COVID-GWAB takes summary statistics from the COVID-19 HGI or user input data and reprioritizes candidate host genes for COVID-19 using HumanNet, a co-functional human gene network. The current version of COVID-GWAB provides the pre-processed data of releases 5, 6, and 7 of the HGI. Additionally, COVID-GWAB provides web interfaces for a summary of augmented GWAS signals, prediction evaluations by appearance frequency in COVID-19 literature, single-cell transcriptome data, and associated pathways. The web server also enables browsing the candidate gene networks.

HumanNet v3: an improved database of human gene networks for disease research.

Network medicine has proven useful for dissecting genetic organization of complex human diseases. We have previously published HumanNet, an integrated network of human genes for disease studies. Since the release of the last version of HumanNet, many large-scale protein-protein interaction datasets have accumulated in public depositories. Additionally, the numbers of research papers and functional annotations for gene-phenotype associations have increased significantly. Therefore, updating HumanNet is a timely task for further improvement of network-based research into diseases. Here, we present HumanNet v3 (https://www.inetbio.org/humannet/, covering 99.8% of human protein coding genes) constructed by means of the expanded data with improved network inference algorithms. HumanNet v3 supports a three-tier model: HumanNet-PI (a protein-protein physical interaction network), HumanNet-FN (a functional gene network), and HumanNet-XC (a functional network extended by co-citation). Users can select a suitable tier of HumanNet for their study purpose. We showed that on disease gene predictions, HumanNet v3 outperforms both the previous HumanNet version and other integrated human gene networks. Furthermore, we demonstrated that HumanNet provides a feasible approach for selecting host genes likely to be associated with COVID-19.

Single-cell ATAC sequencing analysis: From data preprocessing to hypothesis generation.

Most genetic variations associated with human complex traits are located in non-coding genomic regions. Therefore, understanding the genotype-to-phenotype axis requires a comprehensive catalog of functional non-coding genomic elements, most of which are involved in epigenetic regulation of gene expression. Genome-wide maps of open chromatin regions can facilitate functional analysis of cis- and trans-regulatory elements via their connections with trait-associated sequence variants. Currently, Assay for Transposase Accessible Chromatin with high-throughput sequencing (ATAC-seq) is considered the most accessible and cost-effective strategy for genome-wide profiling of chromatin accessibility. Single-cell ATAC-seq (scATAC-seq) technology has also been developed to study cell type-specific chromatin accessibility in tissue samples containing a heterogeneous cellular population. However, due to the intrinsic nature of scATAC-seq data, which are highly noisy and sparse, accurate extraction of biological signals and devising effective biological hypothesis are difficult. To overcome such limitations in scATAC-seq data analysis, new methods and software tools have been developed over the past few years. Nevertheless, there is no consensus for the best practice of scATAC-seq data analysis yet. In this review, we discuss scATAC-seq technology and data analysis methods, ranging from preprocessing to downstream analysis, along with an up-to-date list of published studies that involved the application of this method. We expect this review will provide a guideline for successful data generation and analysis methods using appropriate software tools and databases for the study of chromatin accessibility at single-cell resolution.