The PathoSystems Resource Integration Center (PATRIC) is the bacterial Bioinformatics Resource Center funded by the National Institute of Allergy and Infectious Diseases (https://www.patricbrc.org). PATRIC supports bioinformatic analyses of all bacteria with a special emphasis on pathogens, offering a rich comparative analysis environment that provides users with access to over 250 000 uniformly annotated and publicly available genomes with curated metadata. PATRIC offers web-based visualization and comparative analysis tools, a private workspace in which users can analyze their own data in the context of the public collections, services that streamline complex bioinformatic workflows and command-line tools for bulk data analysis. Over the past several years, as genomic and other omics-related experiments have become more cost-effective and widespread, we have observed considerable growth in the usage of and demand for easy-to-use, publicly available bioinformatic tools and services. Here we report the recent updates to the PATRIC resource, including new web-based comparative analysis tools, eight new services and the release of a command-line interface to access, query and analyze data.

Control of the renin cell phenotype is crucial for the regulation of blood pressure and fluid- electrolyte homeostasis. Enhancers are cis -acting DNA sequences that harbor distinct chromatin features and regulate gene expression in an orientation-independent manner. Recently, clusters of enhancers or super-enhancers (SE) highly enriched with master transcription factors, possessing open chromatin configuration and in close proximity to cell-identity genes have been proposed. We tested the hypothesis that renin cells have unique repertoires of enhancers and super-enhancers, distinct from other cell types. Those regulatory clusters may in turn confer the identity of renin cells. To define the genome-wide enhancer landscape characteristic of renin cells, we studied As4.1 cells, kidney tumor cells that express renin constitutively, and native renin cells sorted from the kidneys of Ren1cKO-YFP + mice. In these mice, the renin promoter drives YFP expression thus marking the renin cells. We used genome-wide ChIP-Seq for Med1 (subunit 1 of the Mediator complex), H3K27Ac (active enhancers) and Pol II (to visualize putative genomic areas undergoing transcription). The ROSE algorithm we used to ascertain super-enhancers. Chromatin accessibility genome-wide was assessed using ATAC-Seq. The results were compared to twenty-one other cell types that do not express renin. In As4.1 cells, we identified 14,871 enhancers based on H3K27Ac. Of those, 888 were classified as super-enhancers. The Med1 signal in As4.1 cells showed a SE localized 5kb upstream the Ren1 gene, which was ranked at position 25 among other SEs. The H3K27Ac signal showed highest occupancy in the same region. ChIP-Seq for H3K27Ac in YFP + cells showed 211 SEs of 2,987 peaks. The SE for the renin gene possessed the highest signal and ranked number 1, indicating its importance in renin cells. One hundred and thirteen SEs were unique to renin cells, including the SE associated with the renin gene. ATAC-Seq signals overlapped with the renin SE and the classical enhancer indicating that the chromatin was accessible for transcription. In summary, renin-expressing cells possess distinct repertoires of unique enhancers and super-enhancers that acting in concert are likely to determine the renin phenotype.