Detection of cell surface ligands for human synovial γδ T cells.

Lack of understanding of the nature and physiological regulation of γδ T cell ligands has considerably hampered full understanding of the function of these cells. We developed an unbiased approach to identify human γδ T cells ligands by the production of a soluble TCR-γδ (sTCR-γδ) tetramer from a synovial Vδ1 γδ T cell clone from a Lyme arthritis patient. The sTCR-γδ was used in flow cytometry to initially define the spectrum of ligand expression by both human tumor cell lines and certain human primary cells. Analysis of diverse tumor cell lines revealed high ligand expression on several of epithelial or fibroblast origin, whereas those of hematopoietic origin were largely devoid of ligand. This allowed a bioinformatics-based identification of candidate ligands using RNAseq data from each tumor line. We further observed that whereas fresh monocytes and T cells expressed low to negligible levels of TCR-γδ ligands, activation of these cells resulted in upregulation of surface ligand expression. Ligand upregulation on monocytes was partly dependent upon IL-1β. The sTCR-γδ tetramer was then used to bind candidate ligands from lysates of activated monocytes and analyzed by mass spectrometry. Surface TCR-γδ ligand was eliminated by treatment with trypsin or removal of glycosaminoglycans, and also suppressed by inhibition of endoplasmic reticulum-Golgi transport. Of particular interest was that inhibition of glycolysis also blocked TCR-γδ ligand expression. These findings demonstrate the spectrum of ligand(s) expression for human synovial Vδ1 γδ T cells as well as the physiology that regulates their expression. Copyright © 2019 The Authors

A graph-based algorithm for RNA-seq data normalization.

The use of RNA-sequencing has garnered much attention in recent years for characterizing and understanding various biological systems. However, it remains a major challenge to gain insights from a large number of RNA-seq experiments collectively, due to the normalization problem. Normalization has been challenging due to an inherent circularity, requiring that RNA-seq data be normalized before any pattern of differential (or non-differential) expression can be ascertained; meanwhile, the prior knowledge of non-differential transcripts is crucial to the normalization process. Some methods have successfully overcome this problem by the assumption that most transcripts are not differentially expressed. However, when RNA-seq profiles become more abundant and heterogeneous, this assumption fails to hold, leading to erroneous normalization. We present a normalization procedure that does not rely on this assumption, nor prior knowledge about the reference transcripts. This algorithm is based on a graph constructed from intrinsic correlations among RNA-seq transcripts and seeks to identify a set of densely connected vertices as references. Application of this algorithm on our synthesized validation data showed that it could recover the reference transcripts with high precision, thus resulting in high-quality normalization. On a realistic data set from the ENCODE project, this algorithm gave good results and could finish in a reasonable time. These preliminary results imply that we may be able to break the long persisting circularity problem in RNA-seq normalization

Polyunsaturated fatty acyl-coenzyme As are inhibitors of cholesterol biosynthesis in zebrafish and mice

SUMMARY Lipid disorders pose therapeutic challenges. Previously we discovered that mutation of the hepatocyte β-hydroxybutyrate transporter Slc16a6a in zebrafish causes hepatic steatosis during fasting, marked by increased hepatic triacylglycerol, but not cholesterol. This selective diversion of trapped ketogenic carbon atoms is surprising because acetate and acetoacetate can exit mitochondria and can be incorporated into both fatty acids and cholesterol in normal hepatocytes. To elucidate the mechanism of this selective diversion of carbon atoms to fatty acids, we fed wild-type and slc16a6a mutant animals high-protein ketogenic diets. We find that slc16a6a mutants have decreased activity of the rate-limiting enzyme of cholesterol biosynthesis, 3-hydroxy-3-methylglutaryl-coenzyme A reductase (Hmgcr), despite increased Hmgcr protein abundance and relative incorporation of mevalonate into cholesterol. These observations suggest the presence of an endogenous Hmgcr inhibitor. We took a candidate approach to identify such inhibitors. First, we found that mutant livers accumulate multiple polyunsaturated fatty acids (PUFAs) and PUFA-CoAs, and we showed that human HMGCR is inhibited by PUFA-CoAs in vitro. Second, we injected mice with an ethyl ester of the PUFA eicosapentaenoic acid and observed an acute decrease in hepatic Hmgcr activity, without alteration in Hmgcr protein abundance. These results elucidate a mechanism for PUFA-mediated cholesterol lowering through direct inhibition of Hmgcr

Investigating the mechanism of the assembly of FGF1-binding heparan sulfate motifs

AbstractHeparan sulfate (HS) chains play crucial biological roles by binding to various signaling molecules including fibroblast growth factors (FGFs). Distinct sulfation patterns of HS chains are required for their binding to FGFs/FGF receptors (FGFRs). These sulfation patterns are putatively regulated by biosynthetic enzyme complexes, called GAGOSOMES, in the Golgi. While the structural requirements of HS–FGF interactions have been described previously, it is still unclear how the FGF-binding motif is assembled in vivo. In this study, we generated HS structures using biosynthetic enzymes in a sequential or concurrent manner to elucidate the potential mechanism by which the FGF1-binding HS motif is assembled. Our results indicate that the HS chains form ternary complexes with FGF1/FGFR when enzymes carry out modifications in a specific manner

Sulfation Patterns Determine Cellular Internalization of Heparin-Like Polysaccharides

Heparin is a highly sulfated polysaccharide that serves biologically relevant roles as an anticoagulant and anticancer agent. While it is well-known that modification of heparin’s sulfation pattern can drastically influence its ability to bind growth factors and other extracellular molecules, very little is known about the cellular uptake of heparin and the role sulfation patterns serve in affecting its internalization. In this study, we chemically synthesized several fluorescently labeled heparins consisting of a variety of sulfation patterns. These polysaccharides were thoroughly characterized using anion exchange chromatography and size exclusion chromatography. Subsequently, we utilized flow cytometry and confocal imaging to show that sulfation patterns differentially affect the amount of heparin uptake in multiple cell types. This study provides the first comprehensive analysis of the effect of sulfation pattern on the cellular internalization of heparin or heparan sulfate like polysaccharides. The results of this study expand current knowledge regarding heparin internalization and provide insights into developing more effective heparin-based drug conjugates for applications in intracellular drug delivery