Bacterial secondary metabolites, encoded by biosynthetic gene clusters (BGCs), can underlie microbiome homeostasis and be developed into high-value commercialized products, which have historically been mined from a select group of taxa. Despite this, dedicated bioinformatics tools for comparative analysis of BGCs are limited. We have thus developed lsaBGC to aid exploration of microdiversity and evolutionary trends across BGCs in any bacterial taxa of interest through calculation of population genetic statistics and metagenomic exploration. As a proof of concept, we applied lsaBGC to four genera commonly found in skin microbiomes to reveal novel insights on both well and less studied taxa and their secondary metabolites. We find evidence of horizontal gene transfer (HGT) within multiple genera. The BGC encoding for the carotenoid staphyloxanthin, a virulence factor in S. aureus, is ubiquitous across the genus of Staphylococcus and exhibits signatures of inter-species HGT, including mobilization onto plasmids. We also identified a non-ribosomal peptide synthetase (NRPS) BGC flanked by transposable elements, encoding for a predicted siderophore, which is highly conserved across several divergent Corynebacterium species commonly isolated from skin such as C. kefirresidentii. From strain-resolution metagenomics, we further determined that the C. kefirresidentii species complex is the most prevalent clade of Corynebacterium in skin metagenomes and is found in the skin microbiome of every participant surveyed. While ubiquitous across skin, the number of publicly-available genomes for this species complex is currently limited. Using lsaBGC’s framework for metagenomic mining, we identified 34,545 novel single nucleotide variants (SNVs) in predicted BGCs of the species complex, including several novel, non-synonymous SNVs within highly conserved sites of enzymes. Ultimately, we envision that application of lsaBGC can highlight important, yet poorly studied, secondary metabolites as well as aid in the discovery and design of more efficacious commercialized metabolites.
Bacterial secondary metabolites, synthesized by enzymes encoded in biosynthetic gene clusters (BGCs), can underlie microbiome homeostasis and serve as commercialized products, which have historically been mined from a select group of taxa. While evolutionary approaches have proven beneficial for prioritizing BGCs for experimental characterization efforts to uncover new natural products, dedicated bioinformatics tools designed for comparative and evolutionary analysis of BGCs within focal taxa are limited. We thus developed lineage specific analysis of BGCs (lsaBGC; https://github.com/Kalan-Lab/lsaBGC) to aid exploration of microdiversity and evolutionary trends across homologous groupings of BGCs, gene cluster families (GCFs), in any bacterial taxa of interest. lsaBGC enables rapid and direct identification of GCFs in genomes, calculates evolutionary statistics and conservation for BGC genes, and builds a framework to allow for base resolution mining of novel variants through metagenomic exploration. Through application of the suite to four genera commonly found in skin microbiomes, we uncover new insights into the evolution and diversity of their BGCs. We show that the BGC of the virulence-associated carotenoid staphyloxanthin in Staphylococcus aureus is ubiquitous across the genus Staphylococcus . While one GCF encoding the biosynthesis of staphyloxanthin showcases evidence for plasmid-mediated horizontal gene transfer (HGT) between species, another GCF appears to be transmitted vertically amongst a sub-clade of skin-associated Staphylococcus . Further, the latter GCF, which is well conserved in S. aureus , has been lost in most Staphylococcus epidermidis , which is the most common Staphylococcus species on human skin and is also regarded as a commensal. We also identify thousands of novel single-nucleotide variants (SNVs) within BGCs from the Corynebacterium tuberculostearicum sp. complex, a narrow, multi-species clade that features the most prevalent Corynebacterium in healthy skin microbiomes. Although novel SNVs were approximately 10 times as likely to correspond to synonymous changes when located in the top five percentile of conserved sites, lsaBGC identified SNVs that defied this trend and are predicted to underlie amino acid changes within functionally key enzymatic domains. Ultimately, beyond supporting evolutionary investigations of BGCs, lsaBGC also provides important functionalities to aid efforts for the discovery or directed modification of natural products.
Quantification of asthma symptoms during acute events is needed to develop exacerbation-related biomarkers. Existing tools are limited in scale and/or temporal sensitivity. We sought to validate the newly designed Acute Asthma Exacerbation Assessment Survey (AAEAS) with a short recall period. METHODS:This was an IRB-approved ancillary study at two sites of the Severe Asthma Research Program (SARP-3). Baseline visits for this analysis were conducted at an annual longitudinal visit of the SARP3 protocol during a period of stability. Participants were encouraged to call the coordinators at the first sign of new upper respiratory symptoms and complete an acute visit. Recovery visits were scheduled when the participant was feeling back to baseline. Data gathered at each visit included the experimental AAEAS, and the previously validated Wisconsin Upper Respiratory Symptom Survey-21 (WURSS-21). The AAEAS is a 6-question multiple-choice survey to quantify asthma symptoms, rescue medication use, and overall burden during the past 3 days. Each item is scored 1 to 5, with 5 being most severe after scale inversion. Difference between groups was assessed using Kruskal-Wallis test of difference. Correlation was assessed using Spearman's r. Reliability was assessed using Cronbach's alpha.
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