Buried ionizable networks are an ancient hallmark of G protein-coupled receptor activation

In the early 1980s, scientists began searching for cell-surface receptors that bind to hormones and neurotransmitters. Among the first was the β-adrenergic receptor, a G protein-coupled receptor (GPCR) that is activated by norepinephrine and epinephrine. Recent breakthroughs have provided more than 100 new GPCR structures, including several in activated conformations. This new structural information presents an opportunity to identify features that distinguish unactivated and activated receptors. Here we use a computational approach to identify structural signatures unique to activated GPCRs. Remarkably, we find that these signatures also are present in distantly related receptors from archaea and bacteria. We propose that these new structural indicators are central to GPCR function and are indicative of GPCR activation

Protons as Second Messenger Regulators of G Protein Signaling

In response to environmental stress cells often generate pH signals that serve to protect vital cellular components and reprogram gene expression for survival. A major barrier to our understanding of this process has been the identification of signaling proteins that detect changes in intracellular pH. To identify candidate pH sensors we developed a computer algorithm that searches proteins for networks of proton-binding sidechains. This analysis indicates that Gα subunits, the principal transducers of G protein-coupled receptor signals, are pH sensors. Our structure-based calculations and biophysical investigations reveal that Gα subunits contain networks of pH-sensing sidechains buried between their Ras and helical domains. We show further that proton binding induces changes in conformation that promote Gα phosphorylation and suppress receptor-initiated signaling. Together, our computational, biophysical and cellular analyses reveal a new and unexpected function for G proteins as mediators of stress-response signaling

Differences in the Regulation of K-Ras and H-Ras Isoforms by Monoubiquitination

Ras GTPases are signaling switches that control critical cellular processes including gene expression, differentiation, and apoptosis. The major Ras isoforms (K, H, and N) contain a conserved core GTPase domain, but have distinct biological functions. Among the three Ras isoforms there are clear differences in post-translational regulation, which contribute to differences in localization and signaling output. Modification by ubiquitination was recently reported to activate Ras signaling in cells, but the mechanisms of activation are not well understood. Here, we show that H-Ras is activated by monoubiquitination and that ubiquitination at Lys-117 accelerates intrinsic nucleotide exchange, thereby promoting GTP loading. This mechanism of Ras activation is distinct from K-Ras monoubiquitination at Lys-147, which leads to impaired regulator-mediated GTP hydrolysis. These findings reveal that different Ras isoforms are monoubiquitinated at distinct sites, with distinct mechanisms of action, but with a common ability to chronically activate the protein in the absence of a receptor signal or oncogenic mutation

Association of Preoperative Risk Factors With Malignancy in Pancreatic Mucinous Cystic Neoplasms: A Multicenter Study

Pancreatic mucinous cystic neoplasms (MCNs) harbor malignant potential, and current guidelines recommend resection. However, data are limited on preoperative risk factors for malignancy (adenocarcinoma or high-grade dysplasia) occurring in the setting of an MCN

The diagnosis of pancreatic mucinous cystic neoplasm and associated adenocarcinoma in males: An eight‐institution study of 349 patients over 15 years

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/137278/1/jso24582_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/137278/2/jso24582.pd

One Year of SARS-CoV-2: How Much Has the Virus Changed?

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a worldwide crisis with profound effects on both public health and the economy. In order to combat the COVID-19 pandemic, research groups have shared viral genome sequence data through the Global Initiative on Sharing All Influenza Data (GISAID). Over the past year, ≈290,000 full SARS-CoV-2 proteome sequences have been deposited in the GISAID. Here, we used these sequences to assess the rate of nonsynonymous mutants over the entire viral proteome. Our analysis shows that SARS-CoV-2 proteins are mutating at substantially different rates, with most of the viral proteins exhibiting little mutational variability. As anticipated, our calculations capture previously reported mutations that arose in the first months of the pandemic, such as D614G (Spike), P323L (NSP12), and R203K/G204R (Nucleocapsid), but they also identify more recent mutations, such as A222V and L18F (Spike) and A220V (Nucleocapsid), among others. Our comprehensive temporal and geographical analyses show two distinct periods with different proteome mutation rates: December 2019 to July 2020 and August to December 2020. Notably, some mutation rates differ by geography, primarily during the latter half of 2020 in Europe. Furthermore, our structure-based molecular analysis provides an exhaustive assessment of SARS-CoV-2 mutation rates in the context of the current set of 3D structures available for SARS-CoV-2 proteins. This emerging sequence-to-structure insight is beginning to illuminate the site-specific mutational (in)tolerance of SARS-CoV-2 proteins as the virus continues to spread around the globe

One Year of SARS-CoV-2: How Much Has the Virus Changed?

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a worldwide crisis with profound effects on both public health and the economy. In order to combat the COVID-19 pandemic, research groups have shared viral genome sequence data through the Global Initiative on Sharing All Influenza Data (GISAID). Over the past year, ≈290,000 full SARS-CoV-2 proteome sequences have been deposited in the GISAID. Here, we used these sequences to assess the rate of nonsynonymous mutants over the entire viral proteome. Our analysis shows that SARS-CoV-2 proteins are mutating at substantially different rates, with most of the viral proteins exhibiting little mutational variability. As anticipated, our calculations capture previously reported mutations that arose in the first months of the pandemic, such as D614G (Spike), P323L (NSP12), and R203K/G204R (Nucleocapsid), but they also identify more recent mutations, such as A222V and L18F (Spike) and A220V (Nucleocapsid), among others. Our comprehensive temporal and geographical analyses show two distinct periods with different proteome mutation rates: December 2019 to July 2020 and August to December 2020. Notably, some mutation rates differ by geography, primarily during the latter half of 2020 in Europe. Furthermore, our structure-based molecular analysis provides an exhaustive assessment of SARS-CoV-2 mutation rates in the context of the current set of 3D structures available for SARS-CoV-2 proteins. This emerging sequence-to-structure insight is beginning to illuminate the site-specific mutational (in)tolerance of SARS-CoV-2 proteins as the virus continues to spread around the globe

Buried ionizable networks are an ancient hallmark of G protein-coupled receptor activation

Seven-transmembrane receptors (7TMRs) have evolved in prokaryotes and eukaryotes over hundreds of millions of years. Comparative structural analysis suggests that these receptors may share a remote evolutionary origin, despite their lack of sequence similarity. Here we used structure-based computations to compare 221 7TMRs from all domains of life. Unexpectedly, we discovered that these receptors contain spatially conserved networks of buried ionizable groups. In microbial 7TMRs these networks are used to pump ions across the cell membrane in response to light. In animal 7TMRs, which include light- and ligand-activated G protein-coupled receptors (GPCRs), homologous networks were found to be characteristic of activated receptor conformations. These networks are likely relevant to receptor function because they connect the ligand-binding pocket of the receptor to the nucleotide-binding pocket of the G protein. We propose that agonist and G protein binding facilitate the formation of these electrostatic networks and promote important structural rearrangements such as the displacement of transmembrane helix-6. We anticipate that robust classification of activated GPCR structures will aid the identification of ligands that target activated GPCR structural states