The potential of the diverse chemistries present in natural products (NP) for biotechnology and medicine remains untapped because NP databases are not searchable with raw data and the NP community has no way to share data other than in published papers. Although mass spectrometry techniques are well-suited to high-throughput characterization of natural products, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social molecular networking (GNPS, http://gnps.ucsd.edu), an open-access knowledge base for community wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations. We also introduce the concept of ‘living data’ through continuous reanalysis of deposited data.

Natural products exhibit a broad range of biological properties and have been a crucial source of therapeutic agents and novel scaffolds. Although bacterial secondary metabolomes are widely explored, they remain incompletely cataloged by current isolation and characterization strategies. To identify metabolites residing in unexplored chemical space, we have developed an integrated discovery approach that combines bacterial growth perturbation, accurate mass spectrometry, comparative mass spectra data analysis, and fragmentation spectra clustering for the identification of low-abundant, novel compounds from complex biological matrices. In this investigation, we analyzed the secreted metabolome of the extensively studied Actinomycete, Streptomyces coelicolor M145, and discovered a low-abundant suite of 15 tri-hydroxamate, amphiphilic siderophores. Compounds in this class have primarily been observed in marine microorganisms making their detection in the soil-dwelling S. coelicolor M145 significant. At least ten of these ferrioxamine-based molecules are not known to be produced by any organism and none have previously been detected from S. coelicolor M145. In addition, we confirmed the production of ferrioxamine D1, a relatively hydrophilic family member that has not been shown to be biosynthesized by this organism. The identified molecules are part of only a small list of secondary metabolites that have been discovered since sequencing of S. coelicolor M145 revealed that it possessed numerous putative secondary metabolite-producing gene clusters with no known metabolites. Thus, the identified siderophores represent the unexplored metabolic potential of both well-studied and new organisms that could be uncovered with our sensitive and robust approach.

In preceding efforts, we demonstrated that antibiotic (ABX) cocktail-mediated perturbations of the gut microbiome in two independent transgenic lines, termed APPSWE/PS1ΔE9 and APPPS1-21, leads to a reduction in Aβ deposition in male mice. To determine whether these observed reductions of cerebral Aβ amyloidosis are specific to any individual antibiotic or require the synergistic effects of several antibiotics, we treated male APPPS1-21 transgenic mice with either individual ABX or an ABX cocktail and assessed amyloid deposition. Specifically, mice were subject to oral gavage with high dose kanamycin, gentamicin, colistin, metronidazole, vancomycin, individually or in a combination (ABX cocktail) from postnatal days (PND) 14 to 21, followed by ad libitum, low-dose individual ABX or ABX cocktail in the drinking water until the time of sacrifice. A control group was subject to gavage with water from PND 14 to 21 and received drinking water till the time of sacrifice. At the time of sacrifice, all groups showed distinct cecal microbiota profiles with the highest differences between control and ABX cocktail-treated animals. Surprisingly, only the ABX cocktail significantly reduced brain Aβ amyloidosis compared to vehicle-treated animals. In parallel studies, and to assess the potential exposure of ABX to the brain, we quantified the levels of each ABX in the brain by liquid chromatography-mass spectrometry (LC-MS) at PND 22 or at 7 weeks of age. With the exception of metronidazole (which was observed at less than 3% relative to the spiked control brains), we were unable to detect the other individual ABX in brain homogenates. Our findings suggest that synergistic alterations of gut microbial consortia, rather than individual antimicrobial agents, underlie the observed reductions in brain amyloidosis.

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.

The capillary electrophoresis (CE) conditions for a competitive immunoassay of glucagon were optimized for highest sensitivity of the immunoassay and resolution of the electrophoretic peaks using a Box-Behnken design. Injection time, voltage ramp time, and separation voltage were varied between three levels and two responses, bound-to-free (B/F) ratio of the immunoassay peaks and resolution between the peaks, were measured. Analysis of variance was applied to fit a predictive model, and a desirability function was used to simultaneously optimize both responses. A 10 sec injection, 1.6 min ramp time, and a 22 kV separation voltage were the conditions found when high B/F was given more emphasis than high resolution. To test the model, calibration curves of a glucagon immunoassay were measured at the optimum and least optimum CE conditions. Optimal conditions increased the sensitivity of the immunoassay by 388% compared to the least optimum conditions while maintaining adequate resolution.