A Pimarane Diterpene and Cytotoxic Angucyclines from a Marine-Derived Micromonospora sp. in Vietnam’s East Sea

A screening of our actinomycete fraction library against the NCI-60 SKOV3 human tumor cell line led to the isolation of isopimara-2-one-3-ol-8,15-diene (1), lagumycin B (2), dehydrorabelomycin (3), phenanthroviridone (4), and WS-5995 A (5). These secondary metabolites were produced by a Micromonospora sp. isolated from sediment collected off the Cát Bà peninsula in the East Sea of Vietnam. Compound 1 is a novel Δ8,9-pimarane diterpene, representing one of approximately 20 actinomycete-produced diterpenes reported to date, while compound 2 is an angucycline antibiotic that has yet to receive formal characterization. The structures of 1 and 2 were elucidated by combined NMR and MS analysis and the absolute configuration of 1 was assigned by analysis of NOESY NMR and CD spectroscopic data. Compounds 2–5 exhibited varying degrees of cytotoxicity against a panel of cancerous and non-cancerous cell lines. Overall, this study highlights our collaborative efforts to discover novel biologically active molecules from the large, underexplored, and biodiversity-rich waters of Vietnam’s East Sea

The prevalence of clinical features associated with primary ciliary dyskinesia in a heterotaxy population: results of a web-based survey

Primary ciliary dyskinesia and heterotaxy are rare but not mutually exclusive disorders, which result from cilia dysfunction. Heterotaxy occurs in at least 12.1% of primary ciliary dyskinesia patients, but the prevalence of primary ciliary dyskinesia within the heterotaxy population is unknown. We designed and distributed a web-based survey to members of an international heterotaxy organisation to determine the prevalence of respiratory features that are common in primary ciliary dyskinesia and that might suggest the possibility of primary ciliary dyskinesia. A total of 49 members (25%) responded, and 37% of the respondents have features suggesting the possibility of primary ciliary dyskinesia, defined as (1) the presence of at least two chronic respiratory symptoms, or (2) bronchiectasis or history of respiratory pathogens suggesting primary ciliary dyskinesia. Of the respondents, four completed comprehensive, in-person evaluations, with definitive primary ciliary dyskinesia confirmed in one individual, and probable primary ciliary dyskinesia identified in two others. The high prevalence of respiratory features compatible with primary ciliary dyskinesia in this heterotaxy population suggests that a subset of heterotaxy patients have dysfunction of respiratory, as well as embryonic nodal cilia. To better assess the possibility of primary ciliary dyskinesia, heterotaxy patients with chronic oto-sino-respiratory symptoms should be referred for a primary ciliary dyskinesia evaluation

Microbially catalyzed conjugation of GABA and tyramine to bile acids

Bile acids (BAs) are cholesterol-derived molecules that aid in digestion and nutrient absorption, regulate host metabolic processes, and influence physiology of the gut microbiota. Both the host and its microbiome contribute to enzymatic modifications that shape the chemical diversity of BAs in the gut. Several bacterial species have been reported to conjugate standard amino acids to BAs, but it was not known if bacteria conjugate BAs to other amine classes. Here, we show that Bacteroides fragilis strain P207, isolated from a bacterial bloom in the J-pouch of a patient with ulcerative colitis pouchitis, conjugates standard amino acids and the neuroactive amines γ-aminobutyric acid (GABA) and tyramine to deoxycholic acid. We extended this analysis to other human gut isolates and identified species that are competent to conjugate GABA and tyramine to primary and secondary BAs, and further identified diverse BA-GABA and BA-tyramine amides in human stool. A longitudinal metabolomic analysis of J-pouch contents of the patient from whom B. fragilis P207 was isolated revealed highly reduced levels of secondary bile acids and a shifting BA amide profile before, during, and after onset of pouchitis, including temporal changes in several BA-GABA amides. Treatment of pouchitis with ciprofloxacin was associated with a marked reduction of nearly all BA amides in the J-pouch. Our study expands the known repertoire of conjugated bile acids produced by bacteria to include BA conjugates to GABA and tyramine and demonstrates that these molecules are present in the human gut. IMPORTANCE BAs are modified in multiple ways by host enzymes and the microbiota to produce a chemically diverse set of molecules that assist in the digestive process and impact many physiological functions. This study reports the discovery of bacterial species that conjugate the neuroactive amines, GABA and tyramine, to primary and secondary BAs. We further present evidence that BA-GABA and BA-tyramine conjugates are present in the human gut, and document a shifting BA-GABA profile in a human pouchitis patient before, during, and after inflammation and antibiotic treatment. GABA and tyramine are common metabolic products of the gut microbiota and potent neuroactive molecules. GABA- and tyramine-conjugated BAs may influence receptor-mediated regulatory mechanisms of humans and their gut microbes, and absorption of these molecules and their entry into enterohepatic circulation may impact host physiology at distal tissue sites. This study defines new conjugated bile acids in the human gut.</p

A computational framework to explore large-scale biosynthetic diversity

Genome mining has become a key technology to exploit natural product diversity. Although initially performed on a single-genome basis, the process is now being scaled up to mine entire genera, strain collections and microbiomes. However, no bioinformatic framework is currently available for effectively analyzing datasets of this size and complexity. In the present study, a streamlined computational workflow is provided, consisting of two new software tools: the ‘biosynthetic gene similarity clustering and prospecting engine’ (BiG-SCAPE), which facilitates fast and interactive sequence similarity network analysis of biosynthetic gene clusters and gene cluster families; and the ‘core analysis of syntenic orthologues to prioritize natural product gene clusters’ (CORASON), which elucidates phylogenetic relationships within and across these families. BiG-SCAPE is validated by correlating its output to metabolomic data across 363 actinobacterial strains and the discovery potential of CORASON is demonstrated by comprehensively mapping biosynthetic diversity across a range of detoxin/rimosamide-related gene cluster families, culminating in the characterization of seven detoxin analogues.</p

Dietary- and host-derived metabolites are used by diverse gut bacteria for anaerobic respiration

Respiratory reductases enable microorganisms to use molecules present in anaerobic ecosystems as energy-generating respiratory electron acceptors. Here we identify three taxonomically distinct families of human gut bacteria (Burkholderiaceae, Eggerthellaceae and Erysipelotrichaceae) that encode large arsenals of tens to hundreds of respiratory-like reductases per genome. Screening species from each family (Sutterella wadsworthensis, Eggerthella lenta and Holdemania filiformis), we discover 22 metabolites used as respiratory electron acceptors in a species-specific manner. Identified reactions transform multiple classes of dietary- and host-derived metabolites, including bioactive molecules resveratrol and itaconate. Products of identified respiratory metabolisms highlight poorly characterized compounds, such as the itaconate-derived 2-methylsuccinate. Reductase substrate profiling defines enzyme–substrate pairs and reveals a complex picture of reductase evolution, providing evidence that reductases with specificities for related cinnamate substrates independently emerged at least four times. These studies thus establish an exceptionally versatile form of anaerobic respiration that directly links microbial energy metabolism to the gut metabolome

Artificial intelligence for natural product drug discovery

Developments in computational omics technologies have provided new means to access the hidden diversity of natural products, unearthing new potential for drug discovery. In parallel, artificial intelligence approaches such as machine learning have led to exciting developments in the computational drug design field, facilitating biological activity prediction and de novo drug design for molecular targets of interest. Here, we describe current and future synergies between these developments to effectively identify drug candidates from the plethora of molecules produced by nature. We also discuss how to address key challenges in realizing the potential of these synergies, such as the need for high-quality datasets to train deep learning algorithms and appropriate strategies for algorithm validation.ISSN:1474-1776ISSN:1474-178

Immunomodulatory fecal metabolites are associated with mortality in COVID-19 patients with respiratory failure

Respiratory failure and mortality from COVID-19 result from virus- and inflammation-induced lung tissue damage. The intestinal microbiome and associated metabolites are implicated in immune responses to respiratory viral infections, however their impact on progression of severe COVID-19 remains unclear. We prospectively enrolled 71 patients with COVID-19 associated critical illness, collected fecal specimens within 3 days of medical intensive care unit admission, defined microbiome compositions by shotgun metagenomic sequencing, and quantified microbiota-derived metabolites (NCT #04552834). Of the 71 patients, 39 survived and 32 died. Mortality was associated with increased representation of Proteobacteria in the fecal microbiota and decreased concentrations of fecal secondary bile acids and desaminotyrosine (DAT). A microbiome metabolic profile (MMP) that accounts for fecal secondary bile acids and desaminotyrosine concentrations was independently associated with progression of respiratory failure leading to mechanical ventilation. Our findings demonstrate that fecal microbiota composition and microbiota-derived metabolite concentrations can predict the trajectory of respiratory function and death in patients with severe SARS-Cov-2 infection and suggest that the gut-lung axis plays an important role in the recovery from COVID-19

Diaza-anthracene Antibiotics from a Freshwater-Derived Actinomycete with Selective Antibacterial Activity toward Mycobacterium tuberculosis

Multidrug- and extensively drug-resistant strains of Mycobacterium tuberculosis are resistant to first- and second-line drug regimens and resulted in 210,000 fatalities in 2013. In the current study, we screened a library of aquatic bacterial natural product fractions for their ability to inhibit this pathogen. A fraction from a Lake Michigan bacterium exhibited significant inhibitory activity, from which we characterized novel diazaquinomycins H and J. This antibiotic class displayed an in vitro activity profile similar or superior to clinically used anti-tuberculosis agents and maintained this potency against a panel of drug-resistant <i>M. tuberculosis</i> strains. Importantly, these are among the only freshwater-derived actinomycete bacterial metabolites described to date. Further in vitro profiling against a broad panel of bacteria indicated that this antibiotic class selectively targets <i>M. tuberculosis</i>. Additionally, in the case of this pathogen we present evidence counter to previous reports that claim the diazaquinomycins target thymidylate synthase in Gram-positive bacteria. Thus, we establish freshwater environments as potential sources for novel antibiotic leads and present the diazaquinomycins as potent and selective inhibitors of <i>M. tuberculosis</i>

Artificial intelligence for natural product drug discovery

Developments in computational omics technologies have provided new means to access the hidden diversity of natural products, unearthing new potential for drug discovery. In parallel, artificial intelligence approaches such as machine learning have led to exciting developments in the computational drug design field, facilitating biological activity prediction and de novo drug design for molecular targets of interest. Here, we describe current and future synergies between these developments to effectively identify drug candidates from the plethora of molecules produced by nature. We also discuss how to address key challenges in realizing the potential of these synergies, such as the need for high-quality datasets to train deep learning algorithms and appropriate strategies for algorithm validation