scholarly journals Microbial Communities of Cladonia Lichens and Their Biosynthetic Gene Clusters Potentially Encoding Natural Products

2021 ◽  
Vol 9 (7) ◽  
pp. 1347
Author(s):  
Tânia Keiko Shishido ◽  
Matti Wahlsten ◽  
Pia Laine ◽  
Jouko Rikkinen ◽  
Taina Lundell ◽  
...  
Keyword(s):  
Natural Products ◽  
Microbial Communities ◽  
High Throughput Sequencing ◽  
Indigenous Communities ◽  
Gene Clusters ◽  
Amplicon Sequencing ◽  
Metagenomic Data ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Shotgun Metagenomics

Lichens have been widely used in traditional medicine, especially by indigenous communities worldwide. However, their slow growth and difficulties in the isolation of lichen symbionts and associated microbes have hindered the pharmaceutical utilisation of lichen-produced compounds. Advances in high-throughput sequencing techniques now permit detailed investigations of the complex microbial communities formed by fungi, green algae, cyanobacteria, and other bacteria within the lichen thalli. Here, we used amplicon sequencing, shotgun metagenomics, and in silico metabolomics together with compound extractions to study reindeer lichens collected from Southern Finland. Our aim was to evaluate the potential of Cladonia species as sources of novel natural products. We compared the predicted biosynthetic pathways of lichen compounds from isolated genome-sequenced lichen fungi and our environmental samples. Potential biosynthetic genes could then be further used to produce secondary metabolites in more tractable hosts. Furthermore, we detected multiple compounds by metabolite analyses, which revealed connections between the identified biosynthetic gene clusters and their products. Taken together, our results contribute to metagenomic data studies from complex lichen-symbiotic communities and provide valuable new information for use in further biochemical and pharmacological studies.

scholarly journals Mining metagenomes for natural product biosynthetic gene clusters: unlocking new potential with ultrafast techniques

2021 ◽  
Author(s):  
Emiliano Pereira-Flores ◽  
Marnix Medema ◽  
Pier Luigi Buttigieg ◽  
Peter Meinicke ◽  
Frank Oliver Glöckner ◽  
...  
Keyword(s):  
Natural Products ◽  
Natural Product ◽  
Human Microbiome ◽  
Gene Clusters ◽  
Human Microbiome Project ◽  
Biosynthetic Gene Cluster ◽  
Metagenomic Data ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Wide Range

Microorganisms produce an immense variety of natural products through the expression of Biosynthetic Gene Clusters (BGCs): physically clustered genes that encode the enzymes of a specialized metabolic pathway. These natural products cover a wide range of chemical classes (e.g., aminoglycosides, lantibiotics, nonribosomal peptides, oligosaccharides, polyketides, terpenes) that are highly valuable for industrial and medical applications1. Metagenomics, as a culture-independent approach, has greatly enhanced our ability to survey the functional potential of microorganisms and is growing in popularity for the mining of BGCs. However, to effectively exploit metagenomic data to this end, it will be crucial to more efficiently identify these genomic elements in highly complex and ever-increasing volumes of data2. Here, we address this challenge by developing the ultrafast Biosynthetic Gene cluster MEtagenomic eXploration toolbox (BiG-MEx). BiG-MEx rapidly identifies a broad range of BGC protein domains, assess their diversity and novelty, and predicts the abundance profile of natural product BGC classes in metagenomic data. We show the advantages of BiG-MEx compared to standard BGC-mining approaches, and use it to explore the BGC domain and class composition of samples in the TARA Oceans3 and Human Microbiome Project datasets4. In these analyses, we demonstrate BiG-MEx’s applicability to study the distribution, diversity, and ecological roles of BGCs in metagenomic data, and guide the exploration of natural products with clinical applications.

Expanding the Natural Products Heterologous Expression Repertoire in the Model Cyanobacterium Anabaena sp. Strain PCC 7120: Production of Pendolmycin and Teleocidin B-4

2019 ◽  
Author(s):  
Patrick Videau ◽  
Kaitlyn Wells ◽  
Arun Singh ◽  
Jessie Eiting ◽  
Philip Proteau ◽  
...  
Keyword(s):  
Natural Products ◽  
Genome Mining ◽  
Gene Clusters ◽  
Combinatorial Biosynthesis ◽  
Test Case ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Cyanobacterium Anabaena ◽  
Anabaena Sp ◽  
Pcc 7120

Cyanobacteria are prolific producers of natural products and genome mining has shown that many orphan biosynthetic gene clusters can be found in sequenced cyanobacterial genomes. New tools and methodologies are required to investigate these biosynthetic gene clusters and here we present the use of <i>Anabaena </i>sp. strain PCC 7120 as a host for combinatorial biosynthesis of natural products using the indolactam natural products (lyngbyatoxin A, pendolmycin, and teleocidin B-4) as a test case. We were able to successfully produce all three compounds using codon optimized genes from Actinobacteria. We also introduce a new plasmid backbone based on the native <i>Anabaena</i>7120 plasmid pCC7120ζ and show that production of teleocidin B-4 can be accomplished using a two-plasmid system, which can be introduced by co-conjugation.

scholarly journals Development of a time-series shotgun metagenomics database for monitoring microbial communities at the Pacific coast of Japan

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kazutoshi Yoshitake ◽  
Gaku Kimura ◽  
Tomoko Sakami ◽  
Tsuyoshi Watanabe ◽  
Yukiko Taniuchi ◽  
...  
Keyword(s):  
Time Series ◽  
Microbial Communities ◽  
Pacific Coast ◽  
Three Dimensional ◽  
Amplicon Sequencing ◽  
Metagenomic Data ◽  
Shotgun Metagenomics ◽  
Functional Features ◽  
Pacific Coast Of Japan ◽  
Marine Microbial Communities

AbstractAlthough numerous metagenome, amplicon sequencing-based studies have been conducted to date to characterize marine microbial communities, relatively few have employed full metagenome shotgun sequencing to obtain a broader picture of the functional features of these marine microbial communities. Moreover, most of these studies only performed sporadic sampling, which is insufficient to understand an ecosystem comprehensively. In this study, we regularly conducted seawater sampling along the northeastern Pacific coast of Japan between March 2012 and May 2016. We collected 213 seawater samples and prepared size-based fractions to generate 454 subsets of samples for shotgun metagenome sequencing and analysis. We also determined the sequences of 16S rRNA (n = 111) and 18S rRNA (n = 47) gene amplicons from smaller sample subsets. We thereafter developed the Ocean Monitoring Database for time-series metagenomic data (http://marine-meta.healthscience.sci.waseda.ac.jp/omd/), which provides a three-dimensional bird’s-eye view of the data. This database includes results of digital DNA chip analysis, a novel method for estimating ocean characteristics such as water temperature from metagenomic data. Furthermore, we developed a novel classification method that includes more information about viruses than that acquired using BLAST. We further report the discovery of a large number of previously overlooked (TAG)n repeat sequences in the genomes of marine microbes. We predict that the availability of this time-series database will lead to major discoveries in marine microbiome research.

scholarly journals Identification of a New Antimicrobial, Desertomycin H, Utilizing a Modified Crowded Plate Technique

Marine Drugs ◽  
2021 ◽  
Vol 19 (8) ◽  
pp. 424
Author(s):  
Osama G. Mohamed ◽  
Sadaf Dorandish ◽  
Rebecca Lindow ◽  
Megan Steltz ◽  
Ifrah Shoukat ◽  
...  
Keyword(s):  
Antibiotic Production ◽  
Gene Clusters ◽  
Multidrug Resistant ◽  
Microbial Interactions ◽  
Mass Spectrometry Data ◽  
Metagenomic Data ◽  
Resistant Bacteria ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Plate Technique

The antibiotic-resistant bacteria-associated infections are a major global healthcare threat. New classes of antimicrobial compounds are urgently needed as the frequency of infections caused by multidrug-resistant microbes continues to rise. Recent metagenomic data have demonstrated that there is still biosynthetic potential encoded in but transcriptionally silent in cultivatable bacterial genomes. However, the culture conditions required to identify and express silent biosynthetic gene clusters that yield natural products with antimicrobial activity are largely unknown. Here, we describe a new antibiotic discovery scheme, dubbed the modified crowded plate technique (mCPT), that utilizes complex microbial interactions to elicit antimicrobial production from otherwise silent biosynthetic gene clusters. Using the mCPT as part of the antibiotic crowdsourcing educational program Tiny Earth®, we isolated over 1400 antibiotic-producing microbes, including 62, showing activity against multidrug-resistant pathogens. The natural product extracts generated from six microbial isolates showed potent activity against vancomycin-intermediate resistant Staphylococcus aureus. We utilized a targeted approach that coupled mass spectrometry data with bioactivity, yielding a new macrolactone class of metabolite, desertomycin H. In this study, we successfully demonstrate a concept that significantly increased our ability to quickly and efficiently identify microbes capable of the silent antibiotic production.

scholarly journals Comprehensive curation and analysis of fungal biosynthetic gene clusters of published natural products

2016 ◽  
Vol 89 ◽  
pp. 18-28 ◽  
Author(s):  
Yong Fuga Li ◽  
Kathleen J.S. Tsai ◽  
Colin J.B. Harvey ◽  
James Jian Li ◽  
Beatrice E. Ary ◽  
...  
Keyword(s):  
Natural Products ◽  
Gene Clusters ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters

scholarly journals Phytoplankton trigger the production of cryptic metabolites in the marine actinobacteria Salinispora tropica

2020 ◽  
Author(s):  
Audam Chhun ◽  
Despoina Sousoni ◽  
Maria del Mar Aguiló-Ferretjans ◽  
Lijiang Song ◽  
Christophe Corre ◽  
...  
Keyword(s):  
Natural Products ◽  
Secondary Metabolites ◽  
Antibiotic Production ◽  
Antimicrobial Effect ◽  
Gene Clusters ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Marine Actinobacteria ◽  
Salinispora Tropica ◽  
Eukaryotic Phytoplankton

AbstractBacteria from the Actinomycete family are a remarkable source of natural products with pharmaceutical potential. The discovery of novel molecules from these organisms is, however, hindered because most of the biosynthetic gene clusters (BGCs) encoding these secondary metabolites are cryptic or silent and are referred to as orphan BGCs. While co-culture has proven to be a promising approach to unlock the biosynthetic potential of many microorganisms by activating the expression of these orphan BGCs, it still remains an underexplored technique. The marine actinobacteria Salinispora tropica, for instance, produces valuable compounds such as the anti-cancer molecule salinosporamide A but half of its putative BGCs are still orphan. Although previous studies have looked into using marine heterotrophs to induce orphan BGCs in Salinispora, the potential impact of co-culturing marine phototrophs with Salinispora has yet to be investigated. Following the observation of clear antimicrobial phenotype of the actinobacterium on a range of phytoplanktonic organisms, we here report the discovery of novel cryptic secondary metabolites produced by S. tropica in response to its co-culture with photosynthetic primary producers. An approach combining metabolomics and proteomics revealed that the photosynthate released by phytoplankton influences the biosynthetic capacities of S. tropica with both production of new molecules and the activation of orphan BGCs. Our work pioneers the use of phototrophs as a promising strategy to accelerate the discovery of novel natural products from actinobacteria.ImportanceThe alarming increase of antimicrobial resistance has generated an enormous interest in the discovery of novel active compounds. The isolation of new microbes to untap novel natural products is currently hampered because most biosynthetic gene clusters (BGC) encoded by these microorganisms are not expressed under standard laboratory conditions, i.e. mono-cultures. Here we show that co-culturing can be an easy way for triggering silent BGC. By combining state-of-the-art metabolomics and high-throughput proteomics, we characterized the activation of cryptic metabolites and silent biosynthetic gene clusters in the marine actinobacteria Salinispora tropica by the presence of phytoplankton photosynthate. We further suggest a mechanistic understanding of the antimicrobial effect this actinobacterium has on a broad range of prokaryotic and eukaryotic phytoplankton species and reveal a promising candidate for antibiotic production.

scholarly journals IMG-ABC: A Knowledge Base To Fuel Discovery of Biosynthetic Gene Clusters and Novel Secondary Metabolites

mBio ◽  
2015 ◽  
Vol 6 (4) ◽  
Author(s):  
Michalis Hadjithomas ◽  
I-Min Amy Chen ◽  
Ken Chu ◽  
Anna Ratner ◽  
Krishna Palaniappan ◽  
...  
Keyword(s):  
Secondary Metabolites ◽  
Secondary Metabolism ◽  
Genomic Data ◽  
Gene Clusters ◽  
Metagenomic Data ◽  
Integrated Analysis ◽  
Analysis Tool ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Analysis Tools

ABSTRACTIn the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In this work, we present IMG-ABC (https://img.jgi.doe.gov/abc), an atlas of biosynthetic gene clusters within the Integrated Microbial Genomes (IMG) system, which is aimed at harnessing the power of “big” genomic data for discovering small molecules. IMG-ABC relies on IMG's comprehensive integrated structural and functional genomic data for the analysis of biosynthetic gene clusters (BCs) and associated secondary metabolites (SMs). SMs and BCs serve as the two main classes of objects in IMG-ABC, each with a rich collection of attributes. A unique feature of IMG-ABC is the incorporation of both experimentally validated and computationally predicted BCs in genomes as well as metagenomes, thus identifying BCs in uncultured populations and rare taxa. We demonstrate the strength of IMG-ABC's focused integrated analysis tools in enabling the exploration of microbial secondary metabolism on a global scale, through the discovery of phenazine-producing clusters for the first time inAlphaproteobacteria. IMG-ABC strives to fill the long-existent void of resources for computational exploration of the secondary metabolism universe; its underlying scalable framework enables traversal of uncovered phylogenetic and chemical structure space, serving as a doorway to a new era in the discovery of novel molecules.IMPORTANCEIMG-ABC is the largest publicly available database of predicted and experimental biosynthetic gene clusters and the secondary metabolites they produce. The system also includes powerful search and analysis tools that are integrated with IMG's extensive genomic/metagenomic data and analysis tool kits. As new research on biosynthetic gene clusters and secondary metabolites is published and more genomes are sequenced, IMG-ABC will continue to expand, with the goal of becoming an essential component of any bioinformatic exploration of the secondary metabolism world.

scholarly journals New Approaches to Detect Biosynthetic Gene Clusters in the Environment

Medicines ◽  
2019 ◽  
Vol 6 (1) ◽  
pp. 32 ◽  
Author(s):  
Ray Chen ◽  
Hon Wong ◽  
Brendan Burns
Keyword(s):  
Natural Products ◽  
Secondary Metabolites ◽  
Gene Clusters ◽  
Screening Methods ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Diverse Range ◽  
Bioinformatic Tools ◽  
Culture Independent ◽  
Traditional Approaches

Microorganisms in the environment can produce a diverse range of secondary metabolites (SM), which are also known as natural products. Bioactive SMs have been crucial in the development of antibiotics and can also act as useful compounds in the biotechnology industry. These natural products are encoded by an extensive range of biosynthetic gene clusters (BGCs). The developments in omics technologies and bioinformatic tools are contributing to a paradigm shift from traditional culturing and screening methods to bioinformatic tools and genomics to uncover BGCs that were previously unknown or transcriptionally silent. Natural product discovery using bioinformatics and omics workflow in the environment has demonstrated an extensive distribution of BGCs in various environments, such as soil, aquatic ecosystems and host microbiome environments. Computational tools provide a feasible and culture-independent route to find new secondary metabolites where traditional approaches cannot. This review will highlight some of the advances in the approaches, primarily bioinformatic, in identifying new BGCs, especially in environments where microorganisms are rarely cultured. This has allowed us to tap into the huge potential of microbial dark matter.

scholarly journals A Comparative Analysis of Biosynthetic Gene Clusters in Lean and Obese Humans

2019 ◽  
Vol 2019 ◽  
pp. 1-7 ◽  
Author(s):  
Shengqin Wang ◽  
Na Li ◽  
Nan Li ◽  
Huixi Zou ◽  
Mingjiang Wu
Keyword(s):  
Gut Microbiome ◽  
Gene Clusters ◽  
Human Adipose Tissue ◽  
Taxonomic Diversity ◽  
Metagenomic Data ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Intestinal Microbes ◽  
Microbe Interactions ◽  
Treatment Of Obesity

Obesity is intrinsically linked with the gut microbiome, and studies have identified several obesity-associated microbes. The microbe-microbe interactions can alter the composition of the microbial community and influence host health by producing secondary metabolites (SMs). However, the contribution of these SMs in the prevention and treatment of obesity has been largely ignored. We identified several SM-encoding biosynthetic gene clusters (BGCs) from the metagenomic data of lean and obese individuals and found significant association between some BGCs, including those that produce hitherto unknown SM, and obesity. In addition, the mean abundance of BGCs was positively correlated with obesity, consistent with the lower taxonomic diversity in the gut microbiota of obese individuals. By comparing the BGCs of known SM between obese and nonobese samples, we found that menaquinone produced by Enterobacter cloacae showed the highest correlation with BMI, in agreement with a recent study on human adipose tissue composition. Furthermore, an obesity-related nonribosomal peptide synthetase (NRPS) was negatively associated with Bacteroidetes, indicating that the SMs produced by intestinal microbes in obese individuals can change the microbiome structure. This is the first systemic study of the association between gut microbiome BGCs and obesity and provides new insights into the causes of obesity.

scholarly journals Glutamic acid is a carrier for hydrazine during the biosyntheses of fosfazinomycin and kinamycin

2018 ◽  
Author(s):  
Kwo-Kwang Abraham Wang ◽  
Tai L. Ng ◽  
Peng Wang ◽  
Zedu Huang ◽  
Emily P. Balskus ◽  
...  
Keyword(s):  
Natural Products ◽  
Nitrous Acid ◽  
Bond Formation ◽  
Gene Clusters ◽  
Biosynthetic Pathways ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Structural Differences ◽  
Related Compounds ◽  
Made In

AbstractFosfazinomycin and kinamycin are natural products that contain nitrogen-nitrogen (N-N) bonds but that are otherwise structurally unrelated. Despite their considerable structural differences, their biosynthetic gene clusters share a set of genes predicted to facilitate N-N bond formation. In this study, we show that for both compounds, one of the nitrogen atoms in the N-N bond originates from nitrous acid. Furthermore, we show that for both compounds, an acetylhydrazine biosynthetic synthon is generated first and then funneled via a glutamyl carrier into the respective biosynthetic pathways. Therefore, unlike other pathways to NN bond-containing natural products wherein the N-N bond is formed directly on a biosynthetic intermediate, during the biosyntheses of fosfazinomycin, kinamycin, and related compounds, the N-N bond is made in an independent pathway that forms a branch of a convergent route to structurally complex natural products.

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