Many microorganisms produce natural products that form the basis of antimicrobials, antivirals, and other drugs. Genome mining is routinely used to complement screening-based workflows to discover novel natural products. Since 2011, the "antibiotics and secondary metabolite analysis shell—antiSMASH" (https://antismash.secondarymetabolites.org/) has supported researchers in their microbial genome mining tasks, both as a free-to-use web server and as a standalone tool under an OSI-approved open-source license. It is currently the most widely used tool for detecting and characterising biosynthetic gene clusters (BGCs) in bacteria and fungi. Here, we present the updated version 6 of antiSMASH. antiSMASH 6 increases the number of supported cluster types from 58 to 71, displays the modular structure of multi-modular BGCs, adds a new BGC comparison algorithm, allows for the integration of results from other prediction tools, and more effectively detects tailoring enzymes in RiPP clusters.

Despite the wide availability of antibiotics, infectious diseases remain a leading cause of death worldwide.1 In the absence of new therapies, mortality rates due to untreatable infections are predicted to rise more than 10-fold by 2050. Natural products (NPs) made by cultured bacteria have been a major source of clinically useful antibiotics. In spite of decades of productivity, the use of bacteria in the search for new antibiotics was largely abandoned due to high rediscovery rates.2, 3 As only a fraction of bacterial diversity is regularly cultivated in the laboratory and just a fraction of the chemistries encoded by cultured bacteria is detected in fermentation experiments, most bacterial NPs remain hidden in the global microbiome. In an effort to access these hidden NPs, we have developed a culture-independent NP discovery platform that involves sequencing, bioinformatic analysis, and heterologous expression of biosynthetic gene clusters (BGCs) captured on DNA extracted from environmental samples (eDNA). Here, we describe the application of this platform to the discovery of the malacidins, a distinctive class of antibiotics that are commonly encoded in soil microbiomes but have never been reported in culture-based NP discovery efforts. The malacidins are active against multidrug-resistant (MDR) pathogens, sterilize MRSA skin infections in an animal wound model, and did not select for resistance under our laboratory conditions.

Nonmammalian glycan structures from helminths act as Th2 adjuvants. Some of these structures are also common on plant glycoproteins. We hypothesized that glycan structures present on peanut glycoallergens act as Th2 adjuvants. Peanut Ag (PNAg), but not deglycosylated PNAg, activated monocyte-derived dendritic cells (MDDCs) as measured by MHC/costimulatory molecule up-regulation, and by their ability to drive T cell proliferation. Furthermore, PNAg-activated MDDCs induced 2- to 3-fold more IL-4- and IL-13-secreting Th2 cells than immature or TNF/IL-1-activated MDDCs when cultured with naive CD4+ T cells. Human MDDCs rapidly internalized Ag in a calcium- and glycan-dependent manner consistent with recognition by C-type lectin. Dendritic cell (DC)-specific ICAM-grabbing nonintegrin (DC-SIGN) (CD209) was shown to recognize PNAg by enhanced uptake in transfected cell lines. To identify the DC-SIGN ligand from unfractionated PNAg, we expressed the extracellular portion of DC-SIGN as an Fc-fusion protein and used it to immunoprecipitate PNAg. A single glycoprotein was pulled down in a calcium-dependent manner, and its identity as Ara h 1 was proven by immunolabeling and mass spectrometry. Purified Ara h 1 was found to be sufficient for the induction of MDDCs that prime Th2-skewed T cell responses. Both PNAg and purified Ara h 1 induced Erk 1/2 phosphorylation of MDDCs, consistent with previous reports on the effect of Th2 adjuvants on DCs.

The difficulty of censusing marine animal populations hampers effective ocean management. Analyzing water for DNA traces shed by organisms may aid assessment. Here we tested aquatic environmental DNA (eDNA) as an indicator of fish presence in the lower Hudson River estuary. A checklist of local marine fish and their relative abundance was prepared by compiling 12 traditional surveys conducted between 1988–2015. To improve eDNA identification success, 31 specimens representing 18 marine fish species were sequenced for two mitochondrial gene regions, boosting coverage of the 12S eDNA target sequence to 80% of local taxa. We collected 76 one-liter shoreline surface water samples at two contrasting estuary locations over six months beginning in January 2016. eDNA was amplified with vertebrate-specific 12S primers. Bioinformatic analysis of amplified DNA, using a reference library of GenBank and our newly generated 12S sequences, detected most (81%) locally abundant or common species and relatively few (23%) uncommon taxa, and corresponded to seasonal presence and habitat preference as determined by traditional surveys. Approximately 2% of fish reads were commonly consumed species that are rare or absent in local waters, consistent with wastewater input. Freshwater species were rarely detected despite Hudson River inflow. These results support further exploration and suggest eDNA will facilitate fine-scale geographic and temporal mapping of marine fish populations at relatively low cost.

Here, we present a natural product discovery approach whereby structures are bioinformatically predicted from primary sequence and produced by chemical synthesis (synthetic-bioinformatic natural products, syn-BNPs), circumventing the need for bacterial culture and gene expression. When applied to nonribosomal peptide synthetase gene clusters from human-associated bacteria we identified the humimycins. These antibiotics inhibit lipid II flippase and potentiate β-lactam activity against methicillin-resistant Staphylococcus aureus in mice, potentially providing a new treatment regimen.

Environmental DNA (eDNA) technology potentially improves the monitoring of marine fish populations. Realizing this promise awaits better understanding of how eDNA relates to fish presence and abundance. Here, we evaluate performance by comparing bottom trawl catches to eDNA from concurrent water samples. In conjunction with New Jersey Ocean Trawl Survey, 1-l water samples were collected at surface and depth prior to tows at about one-fourth of Survey sites in January, June, August, and November 2019. eDNA fish diversity from 1 l was same as or higher than trawl fish diversity from 66 M litres swept by one tow. Most (70–87%) species detected by trawl in a given month were also detected by eDNA, and vice versa, including nearly all (92–100%) abundant species. Trawl and eDNA peak seasonal abundance agreed for ∼70% of fish species. In log-scale comparisons by month, eDNA species reads correlated with species biomass, and more strongly with an allometric index calculated from biomass. In this 1-year study, eDNA reporting largely concorded with monthly trawl estimates of marine fish species richness, composition, seasonality, and relative abundance. Piggybacking eDNA onto an existing survey provided a relatively low-cost approach to better understand eDNA for marine fish stock assessment.

In this study, we compare biosynthetic gene richness and diversity of 96 soil microbiomes from diverse environments found throughout the southwestern and northeastern regions of the United States. The 454-pyroseqencing of nonribosomal peptide adenylation (AD) and polyketide ketosynthase (KS) domain fragments amplified from these microbiomes provide a means to evaluate the variation of secondary metabolite biosynthetic diversity in different soil environments. Through soil composition and AD- and KS-amplicon richness analysis, we identify soil types with elevated biosynthetic potential. In general, arid soils show the richest observed biosynthetic diversity, whereas brackish sediments and pine forest soils show the least. By mapping individual environmental amplicon sequences to sequences derived from functionally characterized biosynthetic gene clusters, we identified conserved soil type–specific secondary metabolome enrichment patterns despite significant sample-to-sample sequence variation. These data are used to create chemical biogeographic distribution maps for biomedically valuable families of natural products in the environment that should prove useful for directing the discovery of bioactive natural products in the future.

Complex microbial ecosystems contain large reservoirs of unexplored biosynthetic diversity. Here we provide an experimental framework and data analysis tool to facilitate the targeted discovery of natural-product biosynthetic gene clusters from the environment. Multiplex sequencing of barcoded PCR amplicons is followed by sequence similarity directed data parsing to identify sequences bearing close resemblance to biosynthetically or biomedically interesting gene clusters. Amplicons are then mapped onto arrayed metagenomic libraries to guide the recovery of targeted gene clusters. When applied to adenylation- and ketosynthase-domain amplicons derived from saturating soil DNA libraries, our analysis pipeline led to the recovery of biosynthetic clusters predicted to encode for previously uncharacterized glycopeptide- and lipopeptide-like antibiotics; thiocoraline-, azinomycin-, and bleomycin-like antitumor agents; and a rapamycin-like immunosuppressant. The utility of the approach is demonstrated by using recovered eDNA sequences to generate glycopeptide derivatives. The experiments described here constitute a systematic interrogation of a soil metagenome for gene clusters capable of encoding naturally occurring derivatives of biomedically relevant natural products. Our results show that previously undetected biosynthetic gene clusters with potential biomedical relevance are very common in the environment. This general process should permit the routine screening of environmental samples for gene clusters capable of encoding the systematic expansion of the structural diversity seen in biomedically relevant families of natural products.