Position of the Third Na+ Site in the Aspartate Transporter GltPh and the Human Glutamate Transporter, EAAT1

Glutamate transport via the human excitatory amino acid transporters is coupled to the co-transport of three Na+ ions, one H+ and the counter-transport of one K+ ion. Transport by an archaeal homologue of the human glutamate transporters, GltPh, whose three dimensional structure is known is also coupled to three Na+ ions but only two Na+ ion binding sites have been observed in the crystal structure of GltPh. In order to fully utilize the GltPh structure in functional studies of the human glutamate transporters, it is essential to understand the transport mechanism of GltPh and accurately determine the number and location of Na+ ions coupled to transport. Several sites have been proposed for the binding of a third Na+ ion from electrostatic calculations and molecular dynamics simulations. In this study, we have performed detailed free energy simulations for GltPh and reveal a new site for the third Na+ ion involving the side chains of Threonine 92, Serine 93, Asparagine 310, Aspartate 312, and the backbone of Tyrosine 89. We have also studied the transport properties of alanine mutants of the coordinating residues Threonine 92 and Serine 93 in GltPh, and the corresponding residues in a human glutamate transporter, EAAT1. The mutant transporters have reduced affinity for Na+ compared to their wild type counterparts. These results confirm that Threonine 92 and Serine 93 are involved in the coordination of the third Na+ ion in GltPh and EAAT1

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations. Ubiquitinpathway genes tend to be upregulated in cancermediated by diverse mechanisms. By integratingpan-cancer multiomic data, we identify a group oftumor samples that exhibit worse prognosis. Thesesamples are consistently associated with the upre-gulation of cell-cycle and DNA repair pathways, char-acterized by mutatedTP53,MYC/TERTamplifica-tion, andAPC/PTENdeletion. Our analysishighlights the importance of the ubiquitin pathwayin cancer development and lays a foundation fordeveloping relevant therapeutic strategies

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

A genomic appraisal of invasive Salmonella Typhimurium and associated antibiotic resistance in sub-Saharan Africa

Invasive non-typhoidal Salmonella (iNTS) disease manifesting as bloodstream infection with high mortality is responsible for a huge public health burden in sub-Saharan Africa. Salmonella enterica serovar Typhimurium (S. Typhimurium) is the main cause of iNTS disease in Africa. By analysing whole genome sequence data from 1303 S. Typhimurium isolates originating from 19 African countries and isolated between 1979 and 2017, here we show a thorough scaled appraisal of the population structure of iNTS disease caused by S. Typhimurium across many of Africa’s most impacted countries. At least six invasive S. Typhimurium clades have already emerged, with ST313 lineage 2 or ST313-L2 driving the current pandemic. ST313-L2 likely emerged in the Democratic Republic of Congo around 1980 and further spread in the mid 1990s. We observed plasmid-borne as well as chromosomally encoded fluoroquinolone resistance underlying emergences of extensive-drug and pan-drug resistance. Our work provides an overview of the evolution of invasive S. Typhimurium disease, and can be exploited to target control measures

A genomic appraisal of invasive Salmonella Typhimurium and associated antibiotic resistance in sub-Saharan Africa

Invasive non-typhoidal Salmonella (iNTS) disease manifesting as bloodstream infection with high mortality is responsible for a huge public health burden in sub-Saharan Africa. Salmonella enterica serovar Typhimurium (S. Typhimurium) is the main cause of iNTS disease in Africa. By analysing whole genome sequence data from 1303 S. Typhimurium isolates originating from 19 African countries and isolated between 1979 and 2017, here we show a thorough scaled appraisal of the population structure of iNTS disease caused by S. Typhimurium across many of Africa’s most impacted countries. At least six invasive S. Typhimurium clades have already emerged, with ST313 lineage 2 or ST313-L2 driving the current pandemic. ST313-L2 likely emerged in the Democratic Republic of Congo around 1980 and further spread in the mid 1990s. We observed plasmid-borne as well as chromosomally encoded fluoroquinolone resistance underlying emergences of extensive-drug and pan-drug resistance. Our work provides an overview of the evolution of invasive S. Typhimurium disease, and can be exploited to target control measures