Gut dysbiosis and clinical phases of pancolitis in patients with ulcerative colitis

Ulcerative colitis (UC) is a frequent type of inflammatory bowel disease, characterized by periods of remission and exacerbation. Gut dysbiosis may influence pathophysiology and clinical response in UC. The purpose of this study was to evaluate whether gut microbiota is related to the active and remission phases of pancolitis in patients with UC as well as in healthy participants. Fecal samples were obtained from 18 patients with UC and clinical‐endoscopic evidenced pancolitis (active phase n = 9 and remission phase n = 9), as well as 15 healthy participants. After fecal DNA extraction, the 16S rRNA gene was amplified and sequenced (Illumina MiSeq), operational taxonomic units were analyzed with the QIIME software. Gut microbiota composition revealed a higher abundance of the phyla Proteobacteria and Fusobacteria in active pancolitis, as compared with remission and healthy participants. Likewise, a marked abundance of the genus Bilophila and Fusobacteria were present in active pancolitis, whereas a higher abundance of Faecalibacterium characterized both remission and healthy participants. LEfSe analysis showed that the genus Roseburia and Faecalibacterium were enriched in remission pancolitis, and genera Bilophila and Fusobacterium were enriched in active pancolitis. The relative abundance of Fecalibacterium and Roseburia showed a higher correlation with fecal calprotectin, while Bilophila and Fusobacterium showed AUCs (area under the curve) of 0.917 and 0.988 for active vs. remission pancolitis. The results of our study highlight the relation of gut dysbiosis with clinically relevant phases of pancolitis in patients with UC. Particularly, Fecalibacterium, Roseburia, Bilophila, and Fusobacterium were identified as genera highly related to the different clinical phases of pancolitis

A Taxonomically-informed Mass Spectrometry Search Tool for Microbial Metabolomics Data

MicrobeMASST, a taxonomically-informed mass spectrometry (MS) search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging a curated database of >60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns. Identification of microbial-derived metabolites and relative producers, without a priori knowledge, will vastly enhance the understanding of microorganisms’ role in ecology and human health

Control of chitin and N-acetylglucosamine utilization in Saccharopolyspora erythraea.

Chitin degradation and subsequentN-acetylglucosamine (GlcNAc) catabolism is thought to be a common trait of a large majority of actinomycetes. Utilization of aminosugars had been poorly investigated outside the model strainStreptomyces coelicolorA3(2), and we examined here the genetic setting of the erythromycin producerSaccharopolyspora erythraeafor GlcNAc and chitin utilization, as well as the transcriptional control thereof.Sacch. erythraeaefficiently utilize GlcNAc most likely via the phosphotransferase system (PTSGlcNAc); however, this strain is not able to grow when chitin orN,N′-diacetylchitobiose [(GlcNAc)2] is the sole nutrient source, despite a predicted extensive chitinolytic system (chigenes). The inability ofSacch. erythraeato utilize chitin and (GlcNAc)2is probably because of the loss of genes encoding the DasABC transporter for (GlcNAc)2import, and genes for intracellular degradation of (GlcNAc)2by β-N-acetylglucosaminidases. Transcription analyses revealed that inSacch. erythraeaall putativechiand GlcNAc utilization genes are repressed by DasR, whereas inStrep. coelicolorDasR displayed either activating or repressing functions whether it targets genes involved in the polymer degradation or genes for GlcNAc dimer and monomer utilization, respectively. A transcriptomic analysis further showed that GlcNAc not only activates the transcription of GlcNAc catabolism genes but also activateschigene expression, as opposed to the previously reported GlcNAc-mediated catabolite repression inStrep. coelicolor. Finally, synteny exploration revealed an identical genetic background for chitin utilization in other rare actinomycetes, which suggests that screening procedures that used only the chitin-based protocol for selective isolation of antibiotic-producing actinomycetes could have missed the isolation of many industrially promising strains.</jats:p

Phylogenetic classification of natural product biosynthetic gene clusters based on regulatory mechanisms

The natural products (NPs) biosynthetic gene clusters (BGCs) represent the adapting biochemical toolkit for microorganisms to thrive different microenvironments. Despite their high diversity, particularly at the genomic level, detecting them in a shake-flask is challenging and remains the primary obstacle limiting our access to valuable chemicals. Studying the molecular mechanisms that regulate BGC expression is crucial to design of artificial conditions that derive on their expression. Here, we propose a phylogenetic analysis of regulatory elements linked to biosynthesis gene clusters, to classify BGCs to regulatory mechanisms based on protein domain information. We utilized Hidden Markov Models from the Pfam database to retrieve regulatory elements, such as histidine kinases and transcription factors, from BGCs in the MIBiG database, focusing on actinobacterial strains from three distinct environments: oligotrophic basins, rainforests, and marine environments. Despite the environmental variations, our isolated microorganisms share similar regulatory mechanisms, suggesting the potential to activate new BGCs using activators known to affect previously characterized BGCs.</p

Isolation and structure determination of a new lantibiotic cinnamycin B from Actinomadura atramentaria based on genome mining

autho

Reconstruction of the Saccharopolyspora erythraea genome-scale model and its use for enhancing erythromycin production

Genome-scale metabolic reconstructions are routinely used for the analysis and design of metabolic engineering strategies for production of primary metabolites. The use of such reconstructions for metabolic engineering of antibiotic production is not common due to the lack of simple design algorithms in the absence of a cellular growth objective function. Here, we present the metabolic network reconstruction for the erythromycin producer Saccharopolyspora erythraea NRRL23338. The model was manually curated for primary and secondary metabolism pathways and consists of 1,482 reactions (2,075 genes) and 1,646 metabolites. As part of the model validation, we explored the potential benefits of supplying amino acids and identified five amino acids "compatible" with erythromycin production, whereby if glucose is supplemented with this amino acid on a carbon mole basis, the in silico model predicts that high erythromycin yield is possible without lowering biomass yield. Increased erythromycin titre was confirmed for four of the five amino acids, namely valine, isoleucine, threonine and proline. In bioreactor experiments, supplementation with 2.5 % carbon mole of valine increased the growth rate by 20 % and simultaneously the erythromycin yield on biomass by 50 %. The model presented here can be used as a framework for the future integration of high-throughput biological data sets in S. erythraea and ultimately to realise strain designs capable of increasing erythromycin production closer to the theoretical yield