SummaryReprogrammed cellular metabolism is a common characteristic observed in various cancers1,2. However, whether metabolic changes directly regulate cancer development and progression remains poorly understood. Here we show that BCAT1, a cytosolic aminotransferase for the branched-chain amino acids (BCAAs), is aberrantly activated and functionally required for chronic myeloid leukemia (CML). BCAT1 is up-regulated during CML progression and promotes BCAA production in leukemia cells by aminating the branched-chain keto acids. Blocking BCAT1 expression or enzymatic activity induces cellular differentiation and impairs the propagation of blast crisis CML (BC-CML) both in vitro and in vivo. Stable isotope tracer experiments combined with NMR-based metabolic analysis demonstrate the intracellular production of BCAAs by BCAT1. Direct supplementation with BCAAs ameliorates the defects caused by BCAT1 knockdown, indicating that BCAT1 exerts its oncogenic function via BCAA production in BC-CML cells. Importantly, BCAT1 expression not only is activated in human BC-CML and de novo acute myeloid leukemia but also predicts disease outcome in patients. As an upstream regulator of BCAT1 expression, we identified Musashi2 (MSI2), an oncogenic RNA binding protein that is required for BC-CML. MSI2 is physically associated with the BCAT1 transcript and positively regulates its protein expression in leukemia. Taken together, this work reveals that altered BCAA metabolism activated through the MSI2-BCAT1 axis drives cancer progression in myeloid leukemia.

Dynamic interactions between gut microbiota and a host’s innate and adaptive immune systems play key roles in maintaining intestinal homeostasis and inhibiting inflammation. The gut microbiota metabolizes proteins and complex carbohydrates, synthesize vitamins, and produce an enormous number of metabolic products that can mediate cross-talk between gut epithelial and immune cells. As a defense mechanism, gut epithelial cells produce a mucosal barrier to segregate microbiota from host immune cells and reduce intestinal permeability. An impaired interaction between gut microbiota and the mucosal immune system can lead to an increased abundance of potentially pathogenic gram-negative bacteria and their associated metabolic changes, disrupting the epithelial barrier and increasing susceptibility to infections. Gut dysbiosis, or negative alterations in gut microbial composition, can also dysregulate immune responses, causing inflammation, oxidative stress, and insulin resistance. Over time, chronic dysbiosis and the translocation of bacteria and their metabolic products across the mucosal barrier may increase prevalence of type 2 diabetes, cardiovascular disease, inflammatory bowel disease, autoimmune disease, and a variety of cancers. In this paper, we highlight the pivotal role gut microbiota and their metabolites (short-chain fatty acids (SCFAs)) play in mucosal immunity.

BackgroundSignaling proteins such as protein kinases adopt a diverse array of conformations to respond to regulatory signals in signaling pathways. Perhaps the most fundamental conformational change of a kinase is the transition between active and inactive states, and defining the conformational features associated with kinase activation is critical for selectively targeting abnormally regulated kinases in diseases. While manual examination of crystal structures have led to the identification of key structural features associated with kinase activation, the large number of kinase crystal structures (~3,500) and extensive conformational diversity displayed by the protein kinase superfamily poses unique challenges in fully defining the conformational features associated with kinase activation. Although some computational approaches have been proposed, they are typically based on a small subset of crystal structures using measurements biased towards the active site geometry.ResultsWe utilize an unbiased informatics based machine learning approach to classify all eukaryotic protein kinase conformations deposited in the PDB. We show that the orientation of the activation segment, measured by φ, ψ, χ1, and pseudo-dihedral angles more accurately classify kinase crystal conformations than existing methods. We show that the formation of the K-E salt bridge is statistically dependent upon the activation segment orientation and identify evolutionary differences between the activation segment conformation of tyrosine and serine/threonine kinases. We provide evidence that our method can identify conformational changes associated with the binding of allosteric regulatory proteins, and show that the greatest variation in inactive structures comes from kinase group and family specific side chain orientations.ConclusionWe have provided the first comprehensive machine learning based classification of protein kinase active/inactive conformations, taking into account more structures and measurements than any previous classification effort. Further, our unbiased classification of inactive structures reveals residues associated with kinase functional specificity. To enable classification of new crystal structures, we have made our classifier publicly accessible through a stand-alone program housed at https://github.com/esbg/kinconform [DOI:10.5281/zenodo.249090].Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-017-1506-2) contains supplementary material, which is available to authorized users.

Several lines of evidence suggest that gut bacterial microbiota is altered in patients with chronic kidney disease (CKD), though the mechanism of which this dysbiosis takes place is not well understood. Recent studies delineated changes in gut microbiota in both CKD patients and experimental animal models using microarray chips. We present 16S ribosomal RNA gene sequencing of both stool pellets and small bowel contents of C57BL/6J mice that underwent a remnant kidney model and establish that changes in microbiota take place in the early gastrointestinal tract. Increased intestinal urea concentration has been hypothesized as a leading contributor to dysbiotic changes in CKD. We show that urea transporters (UT)-A and UT-B mRNA are both expressed throughout the whole gastrointestinal tract. The noted increase in intestinal urea concentration appears to be independent of UTs' expression. Urea supplementation in drinking water resulted in alteration in bacterial gut microbiota that is quite different than that seen in CKD. This indicates that increased intestinal urea concentration might not fully explain the CKD- associated dysbiosis.