Transporter genes in biosynthetic gene clusters predict metabolite characteristics and siderophore activity

Identification of clusters of secondary metabolite biosynthetic genes in the Camelina sativa genome

Multidrug-resistant pathogens pose an earnest risk to human health. Therefore, new antibiotics need to be developed quickly. Most of the antibiotics we use today are derived from secondary metabolites, which are produced by plants. Genome mining tools allow us to detect biosynthetic gene clusters (BGCs) responsible for the production of secondary metabolites. Focusing on the most promising BGCs-coding antibiotics with unique pathways is currently a challenge. In silico approach like genome mining are used to visualise the action of these bioactive chemicals. Camelina sativa is a well-known medicinal plant and it would be interesting to study its secondary metabolites. In this work, we found seven bioactive compounds in this plant using the genome mining approach. Further, the clusters of genes involved in the biosynthesis of these compounds were analysed with their metabolic pathways. This work illuminates new ground on the evolution of BGCs for the nutritional improvement of C. sativa.

A treasure trove of 1034 actinomycete genomes

Filamentous Actinobacteria, recently renamed Actinomycetia, are the most prolific source of microbial bioactive natural products. Studies on biosynthetic gene clusters benefit from or require chromosome-level assemblies. Here, we provide DNA sequences from >1000 isolates: 881 complete genomes and 153 near-complete genomes, representing 28 genera and 389 species, including 244 likely novel species. All genomes are from filamentous isolates of the class Actinomycetia from the NBC culture collection. The largest genus is Streptomyces with 886 genomes including 742 complete assemblies. We use this data to show that analysis of complete genomes can bring biological understanding not previously derived from more fragmented sequences or less systematic datasets. We document the central and structured location of core genes and distal location of specialized metabolite biosynthetic gene clusters and duplicate core genes on the linear Streptomyces chromosome, and analyze the content and length of the terminal inverted repeats which are characteristic for Streptomyces. We then analyze the diversity of trans-AT polyketide synthase biosynthetic gene clusters, which encodes the machinery of a biotechnologically highly interesting compound class. These insights have both ecological and biotechnological implications in understanding the importance of high quality genomic resources and the complex role synteny plays in Actinomycetia biology.

AnnoView enables large-scale analysis, comparison, and visualization of microbial gene neighborhoods

The analysis and comparison of gene neighborhoods is a powerful approach for exploring microbial genome structure, function, and evolution. Although numerous tools exist for genome visualization and comparison, genome exploration across large genomic databases or user-generated datasets remains a challenge. Here, we introduce AnnoView, a web server designed for interactive exploration of gene neighborhoods across the bacterial and archaeal tree of life. Our server offers users the ability to identify, compare, and visualize gene neighborhoods of interest from 30 238 bacterial genomes and 1672 archaeal genomes, through integration with the comprehensive Genome Taxonomy Database and AnnoTree databases. Identified gene neighborhoods can be visualized using pre-computed functional annotations from different sources such as KEGG, Pfam and TIGRFAM, or clustered based on similarity. Alternatively, users can upload and explore their own custom genomic datasets in GBK, GFF or CSV format, or use AnnoView as a genome browser for relatively small genomes (e.g. viruses and plasmids). Ultimately, we anticipate that AnnoView will catalyze biological discovery by enabling user-friendly search, comparison, and visualization of genomic data. AnnoView is available at http://annoview.uwaterloo.ca.

Genomic insights and anti-phytopathogenic potential of siderophore metabolome of endolithic Nocardia mangyaensis NH1

Actinobacteria are one of the predominant groups that successfully colonize and survive in various aquatic, terrestrial and rhizhospheric ecosystems. Among actinobacteria, Nocardia is one of the most important agricultural and industrial bacteria. Screening and isolation of Nocardia related bacteria from extreme habitats such as endolithic environments are beneficial for practical applications in agricultural and environmental biotechnology. In this work, bioinformatics analysis revealed that a novel strain Nocardia mangyaensis NH1 has the capacity to produce structurally varied bioactive compounds, which encoded by non-ribosomal peptide synthases (NRPS), polyketide synthase (PKS), and post-translationally modified peptides (RiPPs). Among NRPS, five gene clusters have a sequence homology with clusters encoding for siderophore synthesis. We also show that N. mangyaensis NH1 accumulates both catechol- and hydroxamate-type siderophores simultaneously under iron-deficient conditions. Untargeted LC-MS/MS analysis revealed a variety of metabolites, including siderophores, lipopeptides, cyclic peptides, and indole-3-acetic acid (IAA) in the culture medium of N. mangyaensis NH1 grown under iron deficiency. We demonstrate that four CAS (chrome azurol S)-positive fractions display variable affinity to metals, with a high Fe3+ chelating capability. Additionally, three of these fractions exhibit antioxidant activity. A combination of iron scavenging metabolites produced by N. mangyaensis NH1 showed antifungal activity against several plant pathogenic fungi. We have shown that the pure culture of N. mangyaensis NH1 and its metabolites have no adverse impact on Arabidopsis seedlings. The ability of N. mangyaensis NH1 to produce siderophores with antifungal, metal-chelating, and antioxidant properties, when supplemented with phytohormones, has the potential to improve the release of macro- and micronutrients, increase soil fertility, promote plant growth and development, and enable the production of biofertilizers across diverse soil systems.

Weathered granites and soils harbour microbes with lanthanide-dependent methylotrophic enzymes

BACKGROUND

Prior to soil formation, phosphate liberated by rock weathering is often sequestered into highly insoluble lanthanide phosphate minerals. Dissolution of these minerals releases phosphate and lanthanides to the biosphere. Currently, the microorganisms involved in phosphate mineral dissolution and the role of lanthanides in microbial metabolism are poorly understood.

RESULTS

Although there have been many studies of soil microbiology, very little research has investigated microbiomes of weathered rock. Here, we sampled weathered granite and associated soil to identify the zones of lanthanide phosphate mineral solubilisation and genomically define the organisms implicated in lanthanide utilisation. We reconstructed 136 genomes from 11 bacterial phyla and found that gene clusters implicated in lanthanide-based metabolism of methanol (primarily xoxF3 and xoxF5) are surprisingly common in microbial communities in moderately weathered granite. Notably, xoxF3 systems were found in Verrucomicrobia for the first time, and in Acidobacteria, Gemmatimonadetes and Alphaproteobacteria. The xoxF-containing gene clusters are shared by diverse Acidobacteria and Gemmatimonadetes, and include conserved hypothetical proteins and transporters not associated with the few well studied xoxF systems. Given that siderophore-like molecules that strongly bind lanthanides may be required to solubilise lanthanide phosphates, it is notable that candidate metallophore biosynthesis systems were most prevalent in bacteria in moderately weathered rock, especially in Acidobacteria with lanthanide-based systems.

CONCLUSIONS

Phosphate mineral dissolution, putative metallophore production and lanthanide utilisation by enzymes involved in methanol oxidation linked to carbonic acid production co-occur in the zone of moderate granite weathering. In combination, these microbial processes likely accelerate the conversion of granitic rock to soil.

Global characterization of biosynthetic gene clusters in non-model eukaryotes using domain architectures

The majority of pharmaceuticals are derived from natural products, bioactive compounds naturally synthesized by organisms to provide evolutionary advantages. Although the rich evolutionary history of eukaryotic algal species implicates a high potential for natural product-based drug discovery, it remains largely untouched. This study investigates 2762 putative biosynthetic gene clusters (BGCs) from 212 eukaryotic algal genomes. To analyze a vast set of structurally diverse BGCs, we employed comparative analysis based on the vectorization of biosynthetic domains, referred to as biosynthetic domain architecture (BDA). By characterizing core biosynthetic machineries through BDA, we identified key BDAs of modular BGCs in diverse eukaryotes and introduced 16 candidate modular BGCs with similar BDAs to previously validated BGCs. This study provides a global characterization of eukaryotic algal BGCs, offering an alternative to laborious manual curation for BGC prioritization.

Unveiling the Pool of Metallophores in Native Environments and Correlation with Their Potential Producers

For many organisms, metallophores are essential biogenic ligands that ensure metal scavenging and acquisition from their environment. Their identification is challenging in highly organic matter rich environments like peatlands due to low solubilization and metal scarcity and high matrix complexity. In contrast to common approaches based on sample modification by spiking of metal isotope tags, we have developed a two-dimensional (2D) Solid-phase extraction-Liquid chromatography-mass spectrometry (SPE-LC-MS) approach for the highly sensitive (LOD 40 fmol per g of soil), high-resolution direct detection and identification of metallophores in both their noncomplexed (apo) and metal-complexed forms in native environments. The characterization of peat collected in the Bernadouze (France) peatland resulted in the identification of 53 metallophores by a database mass-based search, 36 among which are bacterial. Furthermore, the detection of the characteristic (natural) metal isotope patterns in MS resulted in the detection of both Fe and Cu potential complexes. A taxonomic-based inference method was implemented based on literature and public database (antiSMASH database version 3.0) searches, enabling to associate over 40% of the identified bacterial metallophores with potential producers. In some cases, low completeness with the MIBiG reference BCG might be indicative of alternative producers in the ecosystem. Thus, coupling of metallophore detection and producers' inference could pave a new way to investigate poorly documented environment searching for new metallophores and their producers yet unknown.

Robbing the thief

Salmonella employs an arsenal of different tools to obtain iron. In this issue of Cell Host & Microbe, Spiga et al. add to these mechanisms, revealing that commensal Bacteroides species use a specialized lipoprotein to acquire catecholate siderophores from Enterobacteriaceae, only to have them reacquired by Salmonella.

Fungal BGCs for Production of Secondary Metabolites: Main Types, Central Roles in Strain Improvement, and Regulation According to the Piano Principle

Filamentous fungi are one of the most important producers of secondary metabolites. Some of them can have a toxic effect on the human body, leading to diseases. On the other hand, they are widely used as pharmaceutically significant drugs, such as antibiotics, statins, and immunosuppressants. A single fungus species in response to various signals can produce 100 or more secondary metabolites. Such signaling is possible due to the coordinated regulation of several dozen biosynthetic gene clusters (BGCs), which are mosaically localized in different regions of fungal chromosomes. Their regulation includes several levels, from pathway-specific regulators, whose genes are localized inside BGCs, to global regulators of the cell (taking into account changes in pH, carbon consumption, etc.) and global regulators of secondary metabolism (affecting epigenetic changes driven by velvet family proteins, LaeA, etc.). In addition, various low-molecular-weight substances can have a mediating effect on such regulatory processes. This review is devoted to a critical analysis of the available data on the "turning on" and "off" of the biosynthesis of secondary metabolites in response to signals in filamentous fungi. To describe the ongoing processes, the model of "piano regulation" is proposed, whereby pressing a certain key (signal) leads to the extraction of a certain sound from the "musical instrument of the fungus cell", which is expressed in the production of a specific secondary metabolite.

Advanced Methods for Natural Products Discovery: Bioactivity Screening, Dereplication, Metabolomics Profiling, Genomic Sequencing, Databases and Informatic Tools, and Structure Elucidation

Natural Products (NP) are essential for the discovery of novel drugs and products for numerous biotechnological applications. The NP discovery process is expensive and time-consuming, having as major hurdles dereplication (early identification of known compounds) and structure elucidation, particularly the determination of the absolute configuration of metabolites with stereogenic centers. This review comprehensively focuses on recent technological and instrumental advances, highlighting the development of methods that alleviate these obstacles, paving the way for accelerating NP discovery towards biotechnological applications. Herein, we emphasize the most innovative high-throughput tools and methods for advancing bioactivity screening, NP chemical analysis, dereplication, metabolite profiling, metabolomics, genome sequencing and/or genomics approaches, databases, bioinformatics, chemoinformatics, and three-dimensional NP structure elucidation.

On the evolution of natural product biosynthesis

Natural products are the raw material for drug discovery programmes. Bioactive natural products are used extensively in medicine and agriculture and have found utility as antibiotics, immunosuppressives, anti-cancer drugs and anthelminthics. Remarkably, the natural role and what mechanisms drive evolution of these molecules is relatively poorly understood. The exponential increase in genome and chemical data in recent years, coupled with technical advances in bioinformatics and genetics have enabled progress to be made in understanding the evolution of biosynthetic gene clusters and the products of their enzymatic machinery. Here we discuss the diversity of natural products, incorporating the mechanisms that govern evolution of metabolic pathways and how this can be applied to biosynthetic gene clusters. We build on the nomenclature of natural products in terms of primary, integrated, secondary and specialised metabolism and place this within an ecology-evolutionary-developmental biology framework. This eco-evo-devo framework we believe will help to clarify the nature and use of the term specialised metabolites in the future.

CAGECAT: The CompArative GEne Cluster Analysis Toolbox for rapid search and visualisation of homologous gene clusters

BACKGROUND

Co-localized sets of genes that encode specialized functions are common across microbial genomes and occur in genomes of larger eukaryotes as well. Important examples include Biosynthetic Gene Clusters (BGCs) that produce specialized metabolites with medicinal, agricultural, and industrial value (e.g. antimicrobials). Comparative analysis of BGCs can aid in the discovery of novel metabolites by highlighting distribution and identifying variants in public genomes. Unfortunately, gene-cluster-level homology detection remains inaccessible, time-consuming and difficult to interpret.

RESULTS

The comparative gene cluster analysis toolbox (CAGECAT) is a rapid and user-friendly platform to mitigate difficulties in comparative analysis of whole gene clusters. The software provides homology searches and downstream analyses without the need for command-line or programming expertise. By leveraging remote BLAST databases, which always provide up-to-date results, CAGECAT can yield relevant matches that aid in the comparison, taxonomic distribution, or evolution of an unknown query. The service is extensible and interoperable and implements the cblaster and clinker pipelines to perform homology search, filtering, gene neighbourhood estimation, and dynamic visualisation of resulting variant BGCs. With the visualisation module, publication-quality figures can be customized directly from a web-browser, which greatly accelerates their interpretation via informative overlays to identify conserved genes in a BGC query.

CONCLUSION

Overall, CAGECAT is an extensible software that can be interfaced via a standard web-browser for whole region homology searches and comparison on continually updated genomes from NCBI. The public web server and installable docker image are open source and freely available without registration at: https://cagecat.bioinformatics.nl .

Genome mining strategies for metallophore discovery

Many bacteria use small-molecule chelators called metallophores to acquire trace metals from their environment. These molecules play a central role in interactions between bacteria, plants, and animals. Hence, knowing their full diversity is key to combatting infectious diseases as well as harnessing beneficial microbial communities. Metallophore discovery has been streamlined by advances in genome mining, where genomes are scanned for genes involved in metallophore biosynthesis. This review highlights recent trends and advances in predicting the presence and structure of metallophores based solely on genomic information. Recent work suggests new families of metallophores remain hidden from current homology-based approaches. Their discovery will require new genome mining approaches that move beyond biosynthesis to consider metallophore transporters, regulation, and evolution.

Disentangling the genetic basis of rhizosphere microbiome assembly in tomato

Microbiomes play a pivotal role in plant growth and health, but the genetic factors involved in microbiome assembly remain largely elusive. Here, we map the molecular features of the rhizosphere microbiome as quantitative traits of a diverse hybrid population of wild and domesticated tomato. Gene content analysis of prioritized tomato quantitative trait loci suggests a genetic basis for differential recruitment of various rhizobacterial lineages, including a Streptomyces-associated 6.31 Mbp region harboring tomato domestication sweeps and encoding, among others, the iron regulator FIT and the water channel aquaporin SlTIP2.3. Within metagenome-assembled genomes of root-associated Streptomyces and Cellvibrio, we identify bacterial genes involved in metabolism of plant polysaccharides, iron, sulfur, trehalose, and vitamins, whose genetic variation associates with specific tomato QTLs. By integrating 'microbiomics' and quantitative plant genetics, we pinpoint putative plant and reciprocal rhizobacterial traits underlying microbiome assembly, thereby providing a first step towards plant-microbiome breeding programs.

From the soil to the clinic: the impact of microbial secondary metabolites on antibiotic tolerance and resistance

Secondary metabolites profoundly affect microbial physiology, metabolism and stress responses. Increasing evidence suggests that these molecules can modulate microbial susceptibility to commonly used antibiotics; however, secondary metabolites are typically excluded from standard antimicrobial susceptibility assays. This may in part account for why infections by diverse opportunistic bacteria that produce secondary metabolites often exhibit discrepancies between clinical antimicrobial susceptibility testing results and clinical treatment outcomes. In this Review, we explore which types of secondary metabolite alter antimicrobial susceptibility, as well as how and why this phenomenon occurs. We discuss examples of molecules that opportunistic and enteric pathogens either generate themselves or are exposed to from their neighbours, and the nuanced impacts these molecules can have on tolerance and resistance to certain antibiotics.

The confluence of big data and evolutionary genome mining for the discovery of natural products

This review covers literature between 2003-2021The development and application of genome mining tools has given rise to ever-growing genetic and chemical databases and propelled natural products research into the modern age of Big Data. Likewise, an explosion of evolutionary studies has unveiled genetic patterns of natural products biosynthesis and function that support Darwin's theory of natural selection and other theories of adaptation and diversification. In this review, we aim to highlight how Big Data and evolutionary thinking converge in the study of natural products, and how this has led to an emerging sub-discipline of evolutionary genome mining of natural products. First, we outline general principles to best utilize Big Data in natural products research, addressing key considerations needed to provide evolutionary context. We then highlight successful examples where Big Data and evolutionary analyses have been combined to provide bioinformatic resources and tools for the discovery of novel natural products and their biosynthetic enzymes. Rather than an exhaustive list of evolution-driven discoveries, we highlight examples where Big Data and evolutionary thinking have been embraced for the evolutionary genome mining of natural products. After reviewing the nascent history of this sub-discipline, we discuss the challenges and opportunities of genomic and metabolomic tools with evolutionary foundations and/or implications and provide a future outlook for this emerging and exciting field of natural product research.

Transporter Gene-mediated Typing for Detection and Genome Mining of Lipopeptide-producing Pseudomonas

Pseudomonas lipopeptides (LPs) are involved in diverse ecological functions and have biotechnological application potential associated with their antimicrobial and/or antiproliferative activities. They are synthesized by multimodular nonribosomal peptide synthetases which, together with transport and regulatory proteins, are encoded by large biosynthetic gene clusters (BGCs). These secondary metabolites are classified in distinct families based on the sequence and length of the oligopeptide and size of the macrocycle, if present. The phylogeny of PleB, the MacB-like transporter that is part of a dedicated ATP-dependent tripartite efflux system driving export of Pseudomonas LPs, revealed a strong correlation with LP chemical diversity. As each LP BGC carries its cognate pleB, PleB is suitable as a diagnostic sequence for genome mining, allowing assignment of the putative metabolite to a particular LP family. In addition, pleB proved to be a suitable target gene for an alternative PCR method for detecting LP-producing Pseudomonas sp. and did not rely on amplification of catalytic domains of the biosynthetic enzymes. Combined with amplicon sequencing, this approach enabled typing of Pseudomonas strains as potential producers of a LP belonging to one of the known LP families, underscoring its value for strain prioritization. This finding was validated by chemical characterization of known LPs from three different families secreted by novel producers isolated from the rice or maize rhizosphere, namely, the type strains of Pseudomonas fulva (putisolvin), Pseudomonas zeae (tensin), and Pseudomonas xantholysinigenes (xantholysin). In addition, a new member of the Bananamide family, prosekin, was discovered in the type strain of Pseudomonas prosekii, which is an Antarctic isolate.

IMPORTANCEPseudomonas spp. are ubiquitous bacteria able to thrive in a wide range of ecological niches, and lipopeptides often support their lifestyle but also their interaction with other micro- and macro-organisms. Therefore, the production of lipopeptides is widespread among Pseudomonas strains. Consequently, Pseudomonas lipopeptide research not only affects chemists and microbiologists but also touches a much broader audience, including biochemists, ecologists, and plant biologists. In this study, we present a reliable transporter gene-guided approach for the detection and/or typing of Pseudomonas lipopeptide producers. Indeed, it allows us to readily assess the lipopeptide diversity among sets of Pseudomonas isolates and differentiate strains likely to produce known lipopeptides from producers of potentially novel lipopeptides. This work provides a valuable tool that can also be integrated in a genome mining strategy and adapted for the typing of other specialized metabolites.

Mining genomes to illuminate the specialized chemistry of life

All organisms produce specialized organic molecules, ranging from small volatile chemicals to large gene-encoded peptides, that have evolved to provide them with diverse cellular and ecological functions. As natural products, they are broadly applied in medicine, agriculture and nutrition. The rapid accumulation of genomic information has revealed that the metabolic capacity of virtually all organisms is vastly underappreciated. Pioneered mainly in bacteria and fungi, genome mining technologies are accelerating metabolite discovery. Recent efforts are now being expanded to all life forms, including protists, plants and animals, and new integrative omics technologies are enabling the increasingly effective mining of this molecular diversity.

Genome Evolutionary Dynamics Meets Functional Genomics: A Case Story on the Identification of SLC25A44

Gene clusters are becoming promising tools for gene identification. The study reveals the purposive genomic distribution of genes toward higher inheritance rates of intact metabolic pathways/phenotypes and, thereby, higher fitness. The co-localization of co-expressed, co-interacting, and functionally related genes was found as genome-wide trends in humans, mouse, golden eagle, rice fish, Drosophila, peanut, and Arabidopsis. As anticipated, the analyses verified the co-segregation of co-localized events. A negative correlation was notable between the likelihood of co-localization events and the inter-loci distances. The evolution of genomic blocks was also found convergent and uniform along the chromosomal arms. Calling a genomic block responsible for adjacent metabolic reactions is therefore recommended for identification of candidate genes and interpretation of cellular functions. As a case story, a function in the metabolism of energy and secondary metabolites was proposed for Slc25A44, based on its genomic local information. Slc25A44 was further characterized as an essential housekeeping gene which has been under evolutionary purifying pressure and belongs to the phylogenetic ETC-clade of SLC25s. Pathway enrichment mapped the Slc25A44s to the energy metabolism. The expression of peanut and human Slc25A44s in oocytes and Saccharomyces cerevisiae strains confirmed the transport of common precursors for secondary metabolites and ubiquinone. These results suggest that SLC25A44 is a mitochondrion-ER-nucleus zone transporter with biotechnological applications. Finally, a conserved three-amino acid signature on the cytosolic face of transport cavity was found important for rational engineering of SLC25s.

The year 2020 in natural product bioinformatics: an overview of the latest tools and databases

Covering: 2020 Bioinformatic approaches to document and analyse chemical structures, biosynthetic gene clusters and analytical data play an important role in the study of natural products. Every year, such a large number of new algorithms, tools and databases are released, that it is difficult to keep track of all the latest developments. The aim of this short article is to provide a concise overview of and reference to the major tools, methods and databases that have been released in the past year.