Detecting and prioritizing biosynthetic gene clusters for bioactive compounds in bacteria and fungi

Serratia strains are ubiquitous microorganisms with the ability to produce serratomolides, such as serrawettins. These extracellular lipopeptides are described as biocides against many bacteria and fungi and may have a nematicidal activity against phytopathogenic nematodes. Serrawettins W1 and W2 from different strains have different structures that might be correlated with distinct genomic organizations. This work used comparative genomics to determine the distribution and the organization of the serrawettins biosynthetic gene clusters in all the 84 publicly available genomes of the Serratia genus. The serrawettin W1 and W2 gene clusters’ organization was established using antiSMASH software and compared with single and short data previously described for YD25TSerratia. Here, the serrawettin W1 gene clusters’ organization is reported for the first time. The serrawettin W1 biosynthetic gene swrW was present in 17 Serratia genomes. Eighty different coding sequence (CDS) were assigned to the W1 gene cluster, 13 being common to all clusters. The serrawettin W2 swrA gene was present in 11 Serratia genomes. The W2 gene clusters included 68 CDS with 24 present in all the clusters. The genomic analysis showed the swrA gene constitutes five modules, four with three domains and one with four domains, while the swrW gene constitutes one module with four domains. This work identified four genes common to all serrawettin gene clusters, highlighting their essential potential in the serrawettins biosynthetic process.

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Endophytic microbes from Nigerian ethnomedicinal plants: a potential source for bioactive secondary metabolites—a review

Bulletin of the National Research Centre ◽

10.1186/s42269-021-00561-7 ◽

2021 ◽

Vol 45 (1) ◽

Author(s):

Chijioke E. Ezeobiora ◽

Nwamaka H. Igbokwe ◽

Dina H. Amin ◽

Udoma E. Mendie

Keyword(s):

Infectious Diseases ◽

Anticancer Agents ◽

Gene Clusters ◽

Emerging Diseases ◽

Bioactive Molecules ◽

Main Body ◽

Biosynthetic Gene ◽

Biosynthetic Gene Clusters ◽

Ethnomedicinal Plants ◽

Bacteria And Fungi

Abstract Background Endophytes are highly beneficial species of microbes that live in symbiosis with plant tissues in the setting. Endophytes are difficult to isolate in their natural environment, and they are understudied despite being a rich source of bioactive molecules. There are varieties of new infectious diseases emerging across the world, necessitating a constant and expanded search for newer and more efficient bioactive molecules. Nigeria is known for its biodiversity in ethnomedicinal plants, yet these plants are understudied for endophytic microbes harbouring novel bioactive molecules. Main body Endophytes are a source of novel organic natural molecules and are thought to be drug discovery frontiers. Endophyte research has contributed to the discovery of possible anticancer agents following the discovery of taxol. Endophyte research has contributed to the discovery of possible drug compounds with antimicrobial, antioxidant, antiviral, antidiabetic, anti-Alzheimers disease and immunosuppressive properties among others. These breakthroughs provide hope for combating incurable diseases, drug resistance, the emergence of new infectious diseases, and other human health issues. Finding new medicines that may be effective candidates for treating newly emerging diseases in humans has a lot of promise. Most studies have been on fungi endophytes, with just a few reports on bacterial endophytes. The biology of endophytic bacteria and fungi, as well as endophytic microbes isolated from Nigerian medicinal plants, their isolation methods, identification by morphological and molecular methods, fermentation, purification, identification of bioactive compounds and biosynthetic gene clusters are all covered in this study. Conclusion In Nigeria, the sourcing and isolation of endophytes harboring biosynthetic gene clusters are still understudied, necessitating a rigorous quest for bioactive molecules in endophytes inhabiting various ethnomedicinal plants.

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Reclassification of the Specialized Metabolite Producer Pseudomonas mesoacidophila ATCC 31433 as a Member of the Burkholderia cepacia Complex

Journal of Bacteriology ◽

10.1128/jb.00125-17 ◽

2017 ◽

Vol 199 (13) ◽

Cited By ~ 14

Author(s):

E. Joel Loveridge ◽

Cerith Jones ◽

Matthew J. Bull ◽

Suzy C. Moody ◽

Małgorzata W. Kahl ◽

...

Keyword(s):

Phylogenetic Analysis ◽

Bioactive Compounds ◽

Single Molecule ◽

Complete Genome ◽

Burkholderia Cepacia ◽

Gene Clusters ◽

Burkholderia Cepacia Complex ◽

Biosynthetic Gene ◽

Biosynthetic Gene Clusters ◽

Content Type

ABSTRACT Pseudomonas mesoacidophila ATCC 31433 is a Gram-negative bacterium, first isolated from Japanese soil samples, that produces the monobactam isosulfazecin and the β-lactam-potentiating bulgecins. To characterize the biosynthetic potential of P. mesoacidophila ATCC 31433, its complete genome was determined using single-molecule real-time DNA sequence analysis. The 7.8-Mb genome comprised four replicons, three chromosomal (each encoding rRNA) and one plasmid. Phylogenetic analysis demonstrated that P. mesoacidophila ATCC 31433 was misclassified at the time of its deposition and is a member of the Burkholderia cepacia complex, most closely related to Burkholderia ubonensis. The sequenced genome shows considerable additional biosynthetic potential; known gene clusters for malleilactone, ornibactin, isosulfazecin, alkylhydroxyquinoline, and pyrrolnitrin biosynthesis and several uncharacterized biosynthetic gene clusters for polyketides, nonribosomal peptides, and other metabolites were identified. Furthermore, P. mesoacidophila ATCC 31433 harbors many genes associated with environmental resilience and antibiotic resistance and was resistant to a range of antibiotics and metal ions. In summary, this bioactive strain should be designated B. cepacia complex strain ATCC 31433, pending further detailed taxonomic characterization. IMPORTANCE This work reports the complete genome sequence of Pseudomonas mesoacidophila ATCC 31433, a known producer of bioactive compounds. Large numbers of both known and novel biosynthetic gene clusters were identified, indicating that P. mesoacidophila ATCC 31433 is an untapped resource for discovery of novel bioactive compounds. Phylogenetic analysis demonstrated that P. mesoacidophila ATCC 31433 is in fact a member of the Burkholderia cepacia complex, most closely related to the species Burkholderia ubonensis. Further investigation of the classification and biosynthetic potential of P. mesoacidophila ATCC 31433 is warranted.

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Deciphering the Microbial Taxonomy and Functionality of Two Diverse Mangrove Ecosystems and Their Potential Abilities To Produce Bioactive Compounds

mSystems ◽

10.1128/msystems.00851-19 ◽

2020 ◽

Vol 5 (5) ◽

Author(s):

Shuilin Liao ◽

Yayu Wang ◽

Huan Liu ◽

Guangyi Fan ◽

Sunil Kumar Sahu ◽

...

Keyword(s):

Bioactive Compounds ◽

De Novo ◽

Southern China ◽

Sulfur Metabolism ◽

Gene Clusters ◽

Metagenomic Sequencing ◽

Biosynthetic Gene ◽

Biosynthetic Gene Clusters ◽

Mangrove Ecosystems ◽

Unique Genes

ABSTRACT Mangroves, as important and special ecosystems, create unique ecological environments for examining the microbial gene capacity and potential for producing bioactive compounds. However, little is known about the biogeochemical implications of microbiomes in mangrove ecosystems, especially the variations between pristine and anthropogenic mangroves. To elucidate this, we investigated the microbial taxonomic and functional shifts of the mangrove microbiomes and their potential for bioactive compounds in two different coastal mangrove ecosystems in southern China. A gene catalogue, including 87 million unique genes, was constructed, based on deep shotgun metagenomic sequencing. Differentially enriched bacterial and archaeal taxa between pristine mangroves (Guangxi) and anthropogenic mangroves (Shenzhen) were found. The Nitrospira and ammonia-oxidizing archaea, specifically, were more abundant in Shenzhen mangroves, while sulfate-reducing bacteria and methanogens were more abundant in Guangxi mangroves. The results of functional analysis were consistent with the taxonomic results, indicating that the Shenzhen mangrove microbiome has a higher abundance of genes involved in nitrogen metabolism while the Guangxi mangrove microbiome has a higher capacity for sulfur metabolism and methanogenesis. Biosynthetic gene clusters were identified in the metagenome data and in hundreds of de novo reconstructed nonredundant microbial genomes, respectively. Notably, we found different biosynthetic potential in different taxa, and we identified three high quality and novel Acidobacteria genomes with a large number of BGCs. In total, 67,278 unique genes were annotated with antibiotic resistance, indicating the prevalence and persistence in multidrug-resistant genes in the mangrove microbiome. IMPORTANCE This study comprehensively described the taxonomy and functionality of mangrove microbiomes, including their capacity for secondary metabolite biosynthesis and their ability to resist antibiotics. The microbial taxonomic and functional characteristics differed between geographical locations, corresponding to the environmental condition of two diverse mangrove regions. A large number of microbial biosynthetic gene clusters encoding novel bioactivities were found, and this can serve as a valuable resource to guide novel bioactive compound discovery for potential clinical uses.

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Secondary metabolites from hypocrealean entomopathogenic fungi: genomics as a tool to elucidate the encoded parvome

Natural Product Reports ◽

10.1039/d0np00007h ◽

2020 ◽

Vol 37 (9) ◽

pp. 1164-1180 ◽

Cited By ~ 3

Author(s):

Liwen Zhang ◽

Qun Yue ◽

Chen Wang ◽

Yuquan Xu ◽

István Molnár

Keyword(s):

Secondary Metabolites ◽

Whole Genome Sequencing ◽

Genome Sequencing ◽

Bioactive Compounds ◽

Entomopathogenic Fungi ◽

Gene Clusters ◽

Whole Genome ◽

Biosynthetic Gene ◽

Biosynthetic Gene Clusters

Whole genome sequencing allows the cataloguing of the parvome (secondary metabolome) of hypocrealean entomopathogenic fungi, uncovering biosynthetic gene clusters for known and novel bioactive compounds with ecological and pharmaceutical significance.

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Automatic reconstruction of metabolic pathways from identified biosynthetic gene clusters

BMC Bioinformatics ◽

10.1186/s12859-021-03985-0 ◽

2021 ◽

Vol 22 (1) ◽

Cited By ~ 1

Author(s):

Snorre Sulheim ◽

Fredrik A. Fossheim ◽

Alexander Wentzel ◽

Eivind Almaas

Keyword(s):

Heterologous Expression ◽

Bioactive Compounds ◽

Metabolic Pathways ◽

Gene Clusters ◽

Strain Engineering ◽

Biosynthetic Gene ◽

Biosynthetic Gene Clusters ◽

Wide Range ◽

Metabolic Models ◽

Genome Scale

Abstract Background A wide range of bioactive compounds is produced by enzymes and enzymatic complexes encoded in biosynthetic gene clusters (BGCs). These BGCs can be identified and functionally annotated based on their DNA sequence. Candidates for further research and development may be prioritized based on properties such as their functional annotation, (dis)similarity to known BGCs, and bioactivity assays. Production of the target compound in the native strain is often not achievable, rendering heterologous expression in an optimized host strain as a promising alternative. Genome-scale metabolic models are frequently used to guide strain development, but large-scale incorporation and testing of heterologous production of complex natural products in this framework is hampered by the amount of manual work required to translate annotated BGCs to metabolic pathways. To this end, we have developed a pipeline for an automated reconstruction of BGC associated metabolic pathways responsible for the synthesis of non-ribosomal peptides and polyketides, two of the dominant classes of bioactive compounds. Results The developed pipeline correctly predicts 72.8% of the metabolic reactions in a detailed evaluation of 8 different BGCs comprising 228 functional domains. By introducing the reconstructed pathways into a genome-scale metabolic model we demonstrate that this level of accuracy is sufficient to make reliable in silico predictions with respect to production rate and gene knockout targets. Furthermore, we apply the pipeline to a large BGC database and reconstruct 943 metabolic pathways. We identify 17 enzymatic reactions using high-throughput assessment of potential knockout targets for increasing the production of any of the associated compounds. However, the targets only provide a relative increase of up to 6% compared to wild-type production rates. Conclusion With this pipeline we pave the way for an extended use of genome-scale metabolic models in strain design of heterologous expression hosts. In this context, we identified generic knockout targets for the increased production of heterologous compounds. However, as the predicted increase is minor for any of the single-reaction knockout targets, these results indicate that more sophisticated strain-engineering strategies are necessary for the development of efficient BGC expression hosts.

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Epigenetic modification, co-culture and genomic methods for natural product discovery

Physical Sciences Reviews ◽

10.1515/psr-2018-0118 ◽

2018 ◽

Vol 4 (4) ◽

Author(s):

Sergi Herve Akone ◽

Cong-Dat Pham ◽

Huiqin Chen ◽

Antonius R. B. Ola ◽

Fidele Ntie-Kang ◽

...

Keyword(s):

Secondary Metabolites ◽

Bioactive Compounds ◽

Epigenetic Modification ◽

Gene Clusters ◽

Histone Deacetylation ◽

Biosynthetic Gene ◽

Biosynthetic Gene Clusters ◽

Mixed Fermentation ◽

Silent Genes ◽

Promising Source

Abstract Fungi and bacteria are encountered in many habitats where they live in complex communities interacting with one another mainly by producing secondary metabolites, which are organic compounds that are not directly involved in the normal growth, development, or reproduction of the organism. These organisms appear as a promising source for the discovery of novel bioactive natural products that may find their application in medicine. However, the production of secondary metabolites by those organisms when cultured axenically is limited as only a subset of biosynthetic genes is expressed under standard laboratory conditions leading to the search of new methods for the activation of the silent genes including epigenetic modification and co-cultivation. Biosynthetic gene clusters which produce secondary metabolites are known to be present in a heterochromatin state in which the transcription of constitutive genes is usually regulated by epigenetic modification including DNA methylation and histone deacetylation. Therefore, small-molecule epigenetic modifiers which promote changes in the structure of chromatin could control the expression of silent genes and may be rationally employed for the discovery of novel bioactive compounds. Co-cultivation, which is also known as mixed-fermentation, usually implies two or more microorganisms in the same medium in which the resulting competition is known to enhance the production of constitutively present compounds and/or to lead to the induction of cryptic metabolites that were not detected in axenic cultures of the considered axenic microorganism. Genomic strategies could help to identify biosynthetic gene clusters in fungal genomes and link them to their products by the means of novel algorithms as well as integrative pan-genomic approaches. Despite that all these techniques are still in their infancy, they appear as promising sources for the discovery of new bioactive compounds. This chapter presents recent ecological techniques for the discovery of new secondary metabolites that might find application in medicine.

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Recent Advances in Strategies for Activation and Discovery/Characterization of Cryptic Biosynthetic Gene Clusters in Streptomyces

Microorganisms ◽

10.3390/microorganisms8040616 ◽

2020 ◽

Vol 8 (4) ◽

pp. 616 ◽

Cited By ~ 5

Author(s):

Chung Thanh Nguyen ◽

Dipesh Dhakal ◽

Van Thuy Thi Pham ◽

Hue Thi Nguyen ◽

Jae-Kyung Sohng

Keyword(s):

Bioactive Compounds ◽

State Of The Art ◽

Rapid Development ◽

Gene Clusters ◽

Biosynthetic Gene ◽

Biosynthetic Gene Clusters ◽

Microbial Genomes ◽

Streptomyces Spp ◽

Pharmaceutical Industries

Streptomyces spp. are prolific sources of valuable natural products (NPs) that are of great interest in pharmaceutical industries such as antibiotics, anticancer chemotherapeutics, immunosuppressants, etc. Approximately two-thirds of all known antibiotics are produced by actinomycetes, most predominantly by Streptomyces. Nevertheless, in recent years, the chances of the discovery of novel and bioactive compounds from Streptomyces have significantly declined. The major hindrance for obtaining such bioactive compounds from Streptomyces is that most of the compounds are not produced in significant titers, or the biosynthetic gene clusters (BGCs) are cryptic. The rapid development of genome sequencing has provided access to a tremendous number of NP-BGCs embedded in the microbial genomes. In addition, the studies of metabolomics provide a portfolio of entire metabolites produced from the strain of interest. Therefore, through the integrated approaches of different-omics techniques, the connection between gene expression and metabolism can be established. Hence, in this review we summarized recent advancements in strategies for activating cryptic BGCs in Streptomyces by utilizing diverse state-of-the-art techniques.

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Automatic reconstruction of metabolic pathways from identified biosynthetic gene clusters

10.1101/2020.11.24.395400 ◽

2020 ◽

Author(s):

Snorre Sulheim ◽

Fredrik A. Fossheim ◽

Alexander Wentzel ◽

Eivind Almaas

Keyword(s):

Heterologous Expression ◽

Bioactive Compounds ◽

Metabolic Pathways ◽

Gene Clusters ◽

Strain Engineering ◽

Biosynthetic Gene ◽

Biosynthetic Gene Clusters ◽

Wide Range ◽

Metabolic Models ◽

Genome Scale

AbstractBackgroundA wide range of bioactive compounds are produced by enzymes and enzymatic complexes encoded in biosynthetic gene clusters (BGCs). These BGCs can be identified and functionally annotated based on their DNA sequence. Candidates for further research and development may be prioritized based on properties such as their functional annotation, (dis)similarity to known BGCs, and bioactivity assays. Production of the target compound in the native strain is often not achievable, rendering heterologous expression in an optimized host strain as a promising alternative. Genome-scale metabolic models are frequently used to guide strain development, but large-scale incorporation and testing of heterologous production of complex natural products in this framework is hampered by the amount of manual work required to translate annotated BGCs to metabolic pathways. To this end, we have developed a pipeline for an automated reconstruction of BGC associated metabolic pathways responsible for the synthesis of non-ribosomal peptides and polyketides, two of the dominant classes of bioactive compounds.ResultsThe developed pipeline correctly predicts 72.8% of the metabolic reactions in a detailed evaluation of 8 different BGCs comprising 228 functional domains. By introducing the reconstructed pathways into a genome-scale metabolic model we demonstrate that this level of accuracy is sufficient to make reliable in silico predictions with respect to production rate and gene knockout targets. Furthermore, we apply the pipeline to a large BGC database and reconstruct 943 metabolic pathways. We identify 17 enzymatic reactions using high-throughput assessment of potential knockout targets for increasing the production of any of the associated compounds. However, the targets only provide a relative increase of up to 6% compared to wild-type production rates.ConclusionsWith this pipeline we pave the way for an extended use of genome-scale metabolic models in strain design of heterologous expression hosts. In this context, we identified generic knockout targets for the increased production of heterologous compounds. However, as the predicted increase is minor for any of the single-reaction knockout targets, these results indicate that more sophisticated strain-engineering strategies are necessary for the development of efficient BGC expression hosts.

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