Autometa: automated extraction of microbial genomes from individual shotgun metagenomes.

Shotgun metagenomics is a powerful, high-resolution technique enabling the study of microbial communities in situ. However, species-level resolution is only achieved after a process of 'binning' where contigs predicted to originate from the same genome are clustered. Such culture-independent sequencing frequently unearths novel microbes, and so various methods have been devised for reference-free binning. As novel microbiomes of increasing complexity are explored, sometimes associated with non-model hosts, robust automated binning methods are required. Existing methods struggle with eukaryotic contamination and cannot handle highly complex single metagenomes. We therefore developed an automated binning pipeline, termed 'Autometa', to address these issues. This command-line application integrates sequence homology, nucleotide composition, coverage and the presence of single-copy marker genes to separate microbial genomes from non-model host genomes and other eukaryotic contaminants, before deconvoluting individual genomes from single metagenomes. The method is able to effectively separate over 1000 genomes from a metagenome, allowing the study of previously intractably complex environments at the level of single species. Autometa is freely available at https://bitbucket.org/jason_c_kwan/autometa and as a docker image at https://hub.docker.com/r/jasonkwan/autometa under the GNU Affero General Public License 3 (AGPL 3).

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.

QTL mapping and genomic analyses of earliness and fruit ripening traits in a melon Recombinant Inbred Lines population supported by de novo assembly of their parental genomes.

Earliness and ripening behavior are important attributes of fruits on and off the vine, and affect quality and preference of both growers and consumers. Fruit ripening is a complex physiological process that involves metabolic shifts affecting fruit color, firmness, and aroma production. Melon is a promising model crop for the study of fruit ripening, as the full spectrum of climacteric behavior is represented across the natural variation. Using Recombinant Inbred Lines (RILs) population derived from the parental lines "Dulce" (reticulatus, climacteric) and "Tam Dew" (inodorus, non-climacteric) that vary in earliness and ripening traits, we mapped QTLs for ethylene emission, fruit firmness and days to flowering and maturity. To further annotate the main QTL intervals and identify candidate genes, we used Oxford Nanopore long-read sequencing in combination with Illumina short-read resequencing, to assemble the parental genomes de-novo. In addition to 2.5 million genome-wide SNPs and short InDels detected between the parents, we also highlight here the structural variation between these lines and the reference melon genome. Through systematic multi-layered prioritization process, we identified 18 potential polymorphisms in candidate genes within multi-trait QTLs. The associations of selected SNPs with earliness and ripening traits were further validated across a panel of 177 diverse melon accessions and across a diallel population of 190 F1 hybrids derived from a core subset of 20 diverse parents. The combination of advanced genomic tools with diverse germplasm and targeted mapping populations is demonstrated as a way to leverage forward genetics strategies to dissect complex horticulturally important traits.

Conserved bacterial genomes from two geographically isolated peritidal stromatolite formations shed light on potential functional guilds.

Stromatolites are complex microbial mats that form lithified layers. Fossilized stromatolites are the oldest evidence of cellular life on Earth, dating back over 3.4 billion years. Modern stromatolites are relatively rare but may provide clues about the function and evolution of their ancient counterparts. In this study, we focus on peritidal stromatolites occurring at Cape Recife and Schoenmakerskop on the southeastern South African coastline, the former being morphologically and structurally similar to fossilized phosphatic stromatolites formations. Using assembled shotgun metagenomic analysis, we obtained 183 genomic bins, of which the most dominant taxa were from the Cyanobacteria phylum. We identified functional gene sets in genomic bins conserved across two geographically isolated stromatolite formations, which included relatively high copy numbers of genes involved in the reduction of nitrates and phosphatic compounds. Additionally, we found little evidence of Archaeal species in these stromatolites, suggesting that they may not play an important role in peritidal stromatolite formations, as proposed for hypersaline formations.

Horizontal Gene Transfer to a Defensive Symbiont with a Reduced Genome in a Multipartite Beetle Microbiome.

Symbiotic mutualisms of bacteria and animals are ubiquitous in nature, running a continuum from facultative to obligate from the perspectives of both partners. The loss of functions required for living independently but not within a host gives rise to reduced genomes in many symbionts. Although the phenomenon of genome reduction can be explained by existing evolutionary models, the initiation of the process is not well understood. Here, we describe the microbiome associated with the eggs of the beetle Lagria villosa, consisting of multiple bacterial symbionts related to Burkholderia gladioli, including a reduced-genome symbiont thought to be the exclusive producer of the defensive compound lagriamide. We show that the putative lagriamide-producing symbiont is the only member of the microbiome undergoing genome reduction and that it has already lost the majority of its primary metabolism and DNA repair pathways. The key step preceding genome reduction in the symbiont was likely the horizontal acquisition of the putative lagriamide lga biosynthetic gene cluster. Unexpectedly, we uncovered evidence of additional horizontal transfers to the symbiont's genome while genome reduction was occurring and despite a current lack of genes needed for homologous recombination. These gene gains may have given the genome-reduced symbiont a selective advantage in the microbiome, especially given the maintenance of the large lga gene cluster despite ongoing genome reduction.IMPORTANCE Associations between microorganisms and an animal, plant, or fungal host can result in increased dependence over time. This process is due partly to the bacterium not needing to produce nutrients that the host provides, leading to loss of genes that it would need to live independently and to a consequent reduction in genome size. It is often thought that genome reduction is aided by genetic isolation-bacteria that live in monocultures in special host organs, or inside host cells, have less access to other bacterial species from which they can obtain genes. Here, we describe exposure of a genome-reduced beetle symbiont to a community of related bacteria with nonreduced genomes. We show that the symbiont has acquired genes from other bacteria despite going through genome reduction, suggesting that isolation has not yet played a major role in this case of genome reduction, with horizontal gene gains still offering a potential route for adaptation.

In situ mass spectrometry monitoring of fungal cultures led to the identification of four peptaibols with a rare threonine residue.

Peptaibols are an intriguing class of fungal metabolites due both to their wide range of reported bioactivities and to the structural variability that can be generated by the exchange of variable amino acid building blocks. In an effort to streamline the discovery of structurally diverse peptaibols, a mass spectrometry surface sampling technique was applied to screen the chemistry of fungal cultures in situ. Four previously undescribed peptaibols, all containing a rare threonine residue, were identified from a fungal culture (MSX53554), which was identified as Nectriopsis Maire (Bionectriaceae, Hypocreales, Ascomycota). These compounds not only increased the known threonine-containing peptaibols by nearly 20%, but also, the threonine residue was situated in a unique place compared to the other reported threonine-containing peptaibols. After the initial in situ detection and characterization, a large-scale solid fermentation culture was grown. The four peptaibols were isolated and characterized by mass spectrometry. In addition, one of the peptaibols was fully characterized by NMR and amino acid analysis using Marfey's reagent and exhibited moderate in vitro anticancer activity.

Spatial and Temporal Profiling of Griseofulvin Production in Xylaria cubensis Using Mass Spectrometry Mapping.

A large portion of natural products research revolves around the discovery of new, bioactive chemical entities; however, studies to probe the biological purpose of such secondary metabolites for the host organism are often limited. Mass spectrometry mapping of secondary metabolite biosynthesis in situ can be used to probe a series of ecological questions about fungi that may be lost through traditional natural products chemistry extraction protocols. A griseofulvin-producing fungal culture of the Xylariaceae family, isolated as an endophyte of the tree Asimina triloba, was analyzed through a series of spatial and temporal mapping experiments. This fungus produced unique fungal characteristics, such as guttates and stroma, both of which were explored spatially. The distribution of griseofulvin on this culture in isolation was compared to its dispersal when grown in co-culture with a competing Penicillium species via a droplet-based surface sampling system. The fungistatic properties of griseofulvin were visualized, including the consequences for biosynthesis of polyhydroxyanthraquinones in a rival culture.