A community resource for paired genomic and metabolomic data mining

Genomics and metabolomics are widely used to explore specialized metabolite diversity. The Paired Omics Data Platform is a community initiative to systematically document links between metabolome and (meta)genome data, aiding identification of natural product biosynthetic origins and metabolite structures.Peer reviewe

Comparative genomics and metabolomics in the genus Nocardia

Traditional methods for natural product discovery relied exclusively on cultivation of bacteria in the laboratory. Discovery of novel chemistry was laborious and time consuming and frequently resulted in the rediscovery of known natural products. The increasing availability of genomic sequences represents a huge treasure trove for researchers. Biosynthetic pathways can be readily identified from sequence data using genome mining tools such as antiSMASH. However, using automated bioinformatic genome analysis tools, it is often unclear to what degree genetic variability in homologous biosynthetic pathways relates to chemical structural diversity. This makes prioritization of microbial strains and compound identification extremely difficult and often leads to incorrect prediction of natural product structural diversity. In the scope of this thesis, the metabolic potential of Nocardia, an under-investigated but highly prolific actinobacterial genus, was assessed using a genomics-guided approach. Sequence similarity networks generated by BiG-SCAPE (Biosynthetic Genes Similarity Clustering and Prospecting Engine) showed the presence of distinct gene cluster families including a plethora of biosynthetic gene clusters of various classes including: polyketide; non-ribosomal peptide; and terpenoid pathways. Highly conserved biosynthetic pathways encoding for nocobactin-type siderophores were used to exemplify how specific differences in highly related gene clusters correlate to structural diversity in the produced compounds. Metabolic profiling of selected Nocardia strains using LC-MS (liquid chromatography-mass spectrometry) metabolomics data and GNPS (Global Natural Product Social Molecular Networking) revealed related nocobactin-type biosynthetic gene clusters that can indeed be assigned to distinct structural types of nocobactin-type siderophores. The new nocobactin-type siderophores terpenibactins A-C were characterized using LC-MS, NMR (nuclear magnetic resonance) spectroscopy and bioassays. Furthermore, novel soluble forms of nocobactin-type siderophores were identified using LC-MS. Interestingly, some Nocardia strains produced mycobactin-type siderophores, where NMR spectroscopy revealed a chemical structure highly similar to known virulence factors from mycobacteria. The subsequent comparative genomics and metabolomics approach highlights the potential of the highly promising genus Nocardia and points out the constitutive role of nocobactins. It can set the foundation for future Nocardia genome mining approaches and thorough assessment of other rare actinobacteria, circumventing rediscovery of natural products and facilitating strain prioritization

Comparative Genomics and Metabolomics in the Genus Nocardia.

Using automated genome analysis tools, it is often unclear to what degree genetic variability in homologous biosynthetic pathways relates to structural variation. This hampers strain prioritization and compound identification and can lead to overinterpretation of chemical diversity. Here, we assessed the metabolic potential of Nocardia, an underinvestigated actinobacterial genus that is known to comprise opportunistic human pathogens. Our analysis revealed a plethora of putative biosynthetic gene clusters of various classes, including polyketide, nonribosomal peptide, and terpenoid pathways. Furthermore, we used the highly conserved biosynthetic pathway for nocobactin-like siderophores to investigate how gene cluster differences correlate to structural differences in the produced compounds. Sequence similarity networks generated by BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) showed the presence of several distinct gene cluster families. Metabolic profiling of selected Nocardia strains using liquid chromatography-mass spectrometry (LC-MS) metabolomics data, nuclear magnetic resonance (NMR) spectroscopy, and GNPS (Global Natural Product Social molecular networking) revealed that nocobactin-like biosynthetic gene cluster (BGC) families above a BiG-SCAPE threshold of 70% can be assigned to distinct structural types of nocobactin-like siderophores.IMPORTANCE Our work emphasizes that Nocardia represent a prolific source for natural products rivaling better-characterized genera such as Streptomyces or Amycolatopsis Furthermore, we showed that large-scale analysis of biosynthetic gene clusters using similarity networks with high stringency allows the distinction and prediction of natural product structural variations. This will facilitate future genomics-driven drug discovery campaigns

Comparative Genomics and Metabolomics in the Genus Nocardia.

Using automated genome analysis tools, it is often unclear to what degree genetic variability in homologous biosynthetic pathways relates to structural variation. This hampers strain prioritization and compound identification and can lead to overinterpretation of chemical diversity. Here, we assessed the metabolic potential of Nocardia, an underinvestigated actinobacterial genus that is known to comprise opportunistic human pathogens. Our analysis revealed a plethora of putative biosynthetic gene clusters of various classes, including polyketide, nonribosomal peptide, and terpenoid pathways. Furthermore, we used the highly conserved biosynthetic pathway for nocobactin-like siderophores to investigate how gene cluster differences correlate to structural differences in the produced compounds. Sequence similarity networks generated by BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) showed the presence of several distinct gene cluster families. Metabolic profiling of selected Nocardia strains using liquid chromatography-mass spectrometry (LC-MS) metabolomics data, nuclear magnetic resonance (NMR) spectroscopy, and GNPS (Global Natural Product Social molecular networking) revealed that nocobactin-like biosynthetic gene cluster (BGC) families above a BiG-SCAPE threshold of 70% can be assigned to distinct structural types of nocobactin-like siderophores.IMPORTANCE Our work emphasizes that Nocardia represent a prolific source for natural products rivaling better-characterized genera such as Streptomyces or Amycolatopsis Furthermore, we showed that large-scale analysis of biosynthetic gene clusters using similarity networks with high stringency allows the distinction and prediction of natural product structural variations. This will facilitate future genomics-driven drug discovery campaigns

Effects of pre-operative isolation on postoperative pulmonary complications after elective surgery: an international prospective cohort study

We aimed to determine the impact of pre-operative isolation on postoperative pulmonary complications after elective surgery during the global SARS-CoV-2 pandemic. We performed an international prospective cohort study including patients undergoing elective surgery in October 2020. Isolation was defined as the period before surgery during which patients did not leave their house or receive visitors from outside their household. The primary outcome was postoperative pulmonary complications, adjusted in multivariable models for measured confounders. Pre-defined sub-group analyses were performed for the primary outcome. A total of 96,454 patients from 114 countries were included and overall, 26,948 (27.9%) patients isolated before surgery. Postoperative pulmonary complications were recorded in 1947 (2.0%) patients of which 227 (11.7%) were associated with SARS-CoV-2 infection. Patients who isolated pre-operatively were older, had more respiratory comorbidities and were more commonly from areas of high SARS-CoV-2 incidence and high-income countries. Although the overall rates of postoperative pulmonary complications were similar in those that isolated and those that did not (2.1% vs 2.0%, respectively), isolation was associated with higher rates of postoperative pulmonary complications after adjustment (adjusted OR 1.20, 95%CI 1.05-1.36, p = 0.005). Sensitivity analyses revealed no further differences when patients were categorised by: pre-operative testing; use of COVID-19-free pathways; or community SARS-CoV-2 prevalence. The rate of postoperative pulmonary complications increased with periods of isolation longer than 3 days, with an OR (95%CI) at 4-7 days or >= 8 days of 1.25 (1.04-1.48), p = 0.015 and 1.31 (1.11-1.55), p = 0.001, respectively. Isolation before elective surgery might be associated with a small but clinically important increased risk of postoperative pulmonary complications. Longer periods of isolation showed no reduction in the risk of postoperative pulmonary complications. These findings have significant implications for global provision of elective surgical care