Methyl-coenzyme M reductase (MCR) is an essential enzyme found strictly in methanogenic and methanotrophic archaea. MCR catalyzes a reversible reaction involved in the production and consumption of the potent greenhouse gas methane. The α-subunit of this enzyme (McrA) contains several unusual posttranslational modifications, including the only known naturally occurring example of protein thioamidation. We have recently demonstrated by genetic deletion and mass spectrometry that the and genes of are involved in thioamidation of Gly465 in the MCR active site. Modification to thioGly has been postulated to stabilize the active site structure of MCR. Herein, we report the in vitro reconstitution of ribosomal peptide thioamidation using heterologously expressed and purified YcaO and TfuA proteins from Like other reported YcaO proteins, this reaction is ATP-dependent but requires an external sulfide source. We also reconstitute the thioamidation activity of two TfuA-independent YcaOs from the hyperthermophilic methanogenic archaea and Using these proteins, we demonstrate the basis for substrate recognition and regioselectivity of thioamide formation based on extensive mutagenesis, biochemical, and binding studies. Finally, we report nucleotide-free and nucleotide-bound crystal structures for the YcaO proteins from Sequence and structure-guided mutagenesis with subsequent biochemical evaluation have allowed us to assign roles for residues involved in thioamidation and confirm that the reaction proceeds via backbone-phosphorylation. These data assign a new biochemical reaction to the YcaO superfamily and paves the way for further characterization of additional peptide backbone posttranslational modifications.

YcaO enzymes are known to catalyze the ATP-dependent formation of azoline heterocycles, thioamides, and (macro)lactamidines on peptide substrates. These enzymes are found in multiple biosynthetic pathways, including those for several different classes of ribosomally synthesized and post-translationally modified peptides (RiPPs). However, there are major knowledge gaps in the mechanistic and structural underpinnings that govern each of the known YcaO-mediated modifications. Here, we present the first structure of any YcaO enzyme bound to its peptide substrate in the active site, specifically that from Methanocaldococcus jannaschii which is involved in the thioamidation of the α-subunit of methyl-coenzyme M reductase (McrA). The structural data are leveraged to identify and test the residues involved in substrate binding and catalysis by site-directed mutagenesis. We also show that thioamide-forming YcaOs can carry out the cyclodehydration of a related peptide substrate, which underscores the mechanistic conservation across the YcaO family and allows for the extrapolation of mechanistic details to azoline-forming YcaOs involved in RiPP biosynthesis. A bioinformatic survey of all YcaOs highlights the diverse sequence space in azoline-forming YcaOs and suggests their early divergence from a common ancestor. The data presented within provide a detailed molecular framework for understanding this family of enzymes, which reconcile several decades of prior data on RiPP cyclodehydratases. These studies also provide the foundational knowledge to impact our mechanistic understanding of additional RiPP biosynthetic classes.

Human complex traits and common diseases show tissue- and cell-type- specificity. Recently, single-cell RNA sequencing (scRNA-seq) technology has successfully depicted cellular heterogeneity in human tissue, providing an unprecedented opportunity to understand the context-specific expression of complex trait-associated genes in human tissue-cell types (TCs). Here, we present the first web-based application to quickly assess the cell-type-specificity of genes, named Web-based Cell-type Specific Enrichment Analysis of Genes (WebCSEA, available at https://bioinfo.uth.edu/webcsea/). Specifically, we curated a total of 111 scRNA-seq panels of human tissues and 1,355 TCs from 61 different general tissues across 11 human organ systems. We adapted our previous decoding tissue-specificity (deTS) algorithm to measure the enrichment for each tissue-cell type (TC). To overcome the potential bias from the number of signature genes between different TCs, we further developed a permutation-based method that accurately estimates the TC-specificity of a given inquiry gene list. WebCSEA also provides an interactive heatmap that displays the cell-type specificity across 1355 human TCs, and other interactive and static visualizations of cell-type specificity by human organ system, developmental stage, and top-ranked tissues and cell types. In short, WebCSEA is a one-click application that provides a comprehensive exploration of the TC-specificity of genes among human major TC map.

During the past decade, genome-wide association studies (GWAS) have identified many genetic variants with susceptibility to several thousands of complex diseases or traits. The genetic regulation of gene expression is highly tissue-specific and cell type-specific. Recently, single-cell technology has paved the way to dissect cellular heterogeneity in human tissues. Here, we present a reference database for GWAS trait-associated cell type-specificity, named Cell type-Specific Enrichment Analysis DataBase (CSEA-DB, available at https://bioinfo.uth.edu/CSEADB/). Specifically, we curated total of 5120 GWAS summary statistics data for a wide range of human traits and diseases followed by rigorous quality control. We further collected >900 000 cells from the leading consortia such as Human Cell Landscape, Human Cell Atlas, and extensive literature mining, including 752 tissue cell types from 71 adult and fetal tissues across 11 human organ systems. The tissues and cell types were annotated with Uberon and Cell Ontology. By applying our deTS algorithm, we conducted 10 250 480 times of trait-cell type associations, reporting a total of 598 (11.68%) GWAS traits with at least one significantly associated cell type. In summary, CSEA-DB could serve as a repository of association map for human complex traits and their underlying cell types, manually curated GWAS, and single-cell transcriptome resources.