Li, R.-J. | Search bioRxiv

bioRxiv2023

Genomics-Driven Discovery of Myxopyromides, a Class of Polyketidic Amides Associated with Predation of Myxococcus sp. SDU36

Myxobacteria are renowned for their genuine prowess to deliver multifarious bioactive natural products. Genome mining of Myxococcus sp. SDU36 identified a hybrid PKS-NRPS BGC (mpd) that presumably specified previously uncharacterized molecules. The expression of mpd was activated by exchanging the innate promoter of core PKS-NRPS genes with our recently characterized strong constitutive promoter BBa_J23104. Comparative metabolic profiling allowed facile isolation of the elicited compounds 1-5 designated myxopyromides A-E, a group of structurally related polyketidic amides. Especially, myxopyromides D was appended with an uncommon pyrrolinone warhead at the carboxylic terminus, whereas myxopyromide C was instead decorated with a rare structural unit of aminobutanone. Although myxopyromides basically follow a textbook modular PKS-NRPS biosynthetic trajectory, an anteriorly unappreciated flexible chain release strategy is adopted to enrich the chemical repertoire of mpd BGC. Interestingly, myxopyromides were associated with the predation of Myxococcus sp. SDU36. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/535179v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@29d791org.highwire.dtl.DTLVardef@1079fdcorg.highwire.dtl.DTLVardef@19044d8org.highwire.dtl.DTLVardef@97c7dc_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2019

Integration of gut microbiome, host biomarkers, and urine metabolome data reveals networks of interactions associated with distinct clinical phenotypes

BackgroundComprehensive analyses of multi-omics data may provide insights into interactions between different biological layers in relation to distinct clinical features. Here we integrated data on the gut microbiota, blood parameters and urine metabolites of treatment-naive individuals presenting a wide range of metabolic disease phenotypes to delineate clinically meaningful associations.\n\nResultsTrans-omics correlation networks revealed that candidate gut microbial biomarkers and urine metabolite features covaried with distinct clinical phenotypes. Integration of the gut microbiome, the urine metabolome and the phenome revealed that variations in one of these three systems correlated with changes in the other two. Of specific note in relation to clinical parameters of liver function, we identified Eubacterium eligens, Faecalibacterium prausnitzii and Ruminococcus lactaris to be associated with a healthy liver function, whereas Clostridium bolteae, Tyzzerella nexills, Ruminococcus gnavus, Blautia hansenii, and Atopobium parvulum were associated with blood biomarkers for liver diseases. Variations in these microbiota features paralleled changes in specific urine metabolites. Network modeling yielded two core clusters including one large gut microbe-urine metabolite close-knit cluster and one triangular cluster composed of a gut microbe-blood-urine network, demonstrating close inter-system crosstalk especially between the gut microbiome and the urine metabolome.\n\nConclusionsDistinct clinical phenotypes are manifested in both the gut microbiome and the urine metabolome, and inter-domain connectivity takes the form of high-dimensional networks. Such networks may further our understanding of complex biological systems, and may provide a basis for identifying biomarkers for diseases.

microbiology↗