scholarly journals Activation of Cryptic Antibiotic Biosynthetic Gene Clusters Guided by RNA-seq Data from Both Streptomyces ansochromogenes and ΔwblA

Antibiotics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1097
Author(s):  
Yue Li ◽  
Haiying Yu ◽  
Hanye Guan ◽  
Jingjing Li ◽  
Jihui Zhang ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Regulatory Gene ◽  
Gene Clusters ◽  
Differentially Expressed ◽  
Human Beings ◽  
Biosynthetic Gene ◽  
Rna Seq ◽  
Biosynthetic Gene Clusters ◽  
Health Crisis ◽  
Streptomyces Ansochromogenes

With the increase of drug resistance caused by the improper use and abuse of antibiotics, human beings are facing a global health crisis. Sequencing of Streptomyces genomes revealed the presence of an important reservoir of secondary metabolic gene clusters for previously unsuspected products with potentially valuable bioactivity. It has therefore become necessary to activate these cryptic pathways through various strategies. Here, we used RNA-seq data to perform a comparative transcriptome analysis of Streptomyces ansochromogenes (wild-type, WT) and its global regulatory gene disruption mutant ΔwblA, in which some differentially expressed genes are associated with the abolished nikkomycin biosynthesis and activated tylosin analogue compounds (TACs) production, and also with the oviedomycin production that is induced by the genetic manipulation of two differentially expressed genes (san7324 and san7324L) encoding RsbR. These results provide a significant clue for the discovery of new drug candidates and the activation of cryptic biosynthetic gene clusters.

scholarly journals Gene Modules Co-regulated with Biosynthetic Gene Clusters for Allelopathy between Rice and Barnyardgrass

2019 ◽  
Vol 20 (16) ◽  
pp. 3846 ◽  
Author(s):  
Most. Humaira Sultana ◽  
Fangjie Liu ◽  
Md. Alamin ◽  
Lingfeng Mao ◽  
Lei Jia ◽  
...  
Keyword(s):  
Gene Networks ◽  
Regulatory Gene ◽  
Crop Protection ◽  
Gene Clusters ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Central Process ◽  
Coordinated Expression ◽  
Gene Modules ◽  
Allelopathic Interactions

Allelopathy is a central process in crop–weed interactions and is mediated by the release of allelochemicals that result in adverse growth effects on one or the other plant in the interaction. The genomic mechanism for the biosynthesis of many critical allelochemicals is unknown but may involve the clustering of non-homologous biosynthetic genes involved in their formation and regulatory gene modules involved in controlling the coordinated expression within these gene clusters. In this study, we used the transcriptomes from mono- or co-cultured rice and barnyardgrass to investigate the nature of the gene clusters and their regulatory gene modules involved in the allelopathic interactions of these two plants. In addition to the already known biosynthetic gene clusters in barnyardgrass we identified three potential new clusters including one for quercetin biosynthesis and potentially involved in allelopathic interaction with rice. Based on the construction of gene networks, we identified one gene regulatory module containing hub transcription factors, significantly positively co-regulated with both the momilactone A and phytocassane clusters in rice. In barnyardgrass, gene modules and hub genes co-expressed with the gene clusters responsible for 2,4-dihydroxy-7-methoxy-1,4-benzoxazin-3-one (DIMBOA) biosynthesis were also identified. In addition, we found three genes in barnyardgrass encoding indole-3-glycerolphosphate synthase that regulate the expression of the DIMBOA cluster. Our findings offer new insights into the regulatory mechanisms of biosynthetic gene clusters involved in allelopathic interactions between rice and barnyardgrass, and have potential implications in controlling weeds for crop protection.

scholarly journals Comparative Genomics and Transcriptomics Depict Marine Algicolous Arthrinium Species as Endosymbionts That Help Regulate Oxidative Stress in Brown Algae

2021 ◽  
Vol 8 ◽  
Author(s):  
Young Mok Heo ◽  
Seung-Yoon Oh ◽  
Kyeongwon Kim ◽  
Sang-Il Han ◽  
Sun Lul Kwon ◽  
...  
Keyword(s):  
Brown Algae ◽  
Plant Pathogens ◽  
Gene Clusters ◽  
Whole Genome ◽  
Biosynthetic Gene ◽  
Rna Seq ◽  
Interspecies Interactions ◽  
Biosynthetic Gene Clusters ◽  
Alcohol Production ◽  
Fungal Secondary Metabolite

The whole genome and transcriptome analyses were performed for prediction of the ecological characteristics of Arthrinium and the genes involved in gentisyl alcohol biosynthesis. Whole genome sequences of A. koreanum KUC21332 and A. saccharicola KUC21221 were analyzed, and the genes involved in interspecies interaction, carbohydrate-active enzymes, and secondary metabolites were investigated. Three of the seven genes associated with interspecies interactions shared by four Arthrinium spp. were involved in pathogenesis. A. koreanum and A. saccharicola exhibit the enzyme profiles similar to those observed in plant pathogens and endophytes rather than saprobes. Furthermore, six of the seven metabolites of known clusters identified in the genomes of the four Arthrinium spp. are associated with plant virulence. These results indicate that Arthrinium spp. are potentially pathogenic to plants. Subsequently, different conditions for gentisyl alcohol production in A. koreanum were established, and mRNA extracted from cultures of each condition was subjected to RNA-Seq to analyze the differentially-expressed genes. The gentisyl alcohol biosynthetic pathway and related biosynthetic gene clusters were identified, and gentisyl alcohol biosynthesis was significantly downregulated in the mannitol-supplemented group where remarkably low antioxidant activity was observed. These results indicate that gentisyl alcohol production in algicolous Arthrinium spp. is influenced by mannitol. It was suggested that the algicolous Arthrinium spp. form a symbiotic relationship that provides antioxidants when the photosynthetic activity of brown algae decreases in exchange for receiving mannitol. This is the first study to analyze the lifestyle of marine algicolous Arthrinium spp. at the molecular level and suggests a symbiotic mechanism with brown algae. It also improves the understanding of fungal secondary metabolite production via identification of the gentisyl alcohol biosynthetic gene clusters in Arthrinium spp.

scholarly journals The Integration of Genome Mining, Comparative Genomics, and Functional Genetics for Biosynthetic Gene Cluster Identification

2020 ◽  
Vol 11 ◽  
Author(s):  
Ashley N. Williams ◽  
Naveen Sorout ◽  
Alexander J. Cameron ◽  
John Stavrinides
Keyword(s):  
Comparative Genomics ◽  
Gene Cluster ◽  
Antibiotic Production ◽  
Genome Mining ◽  
Gene Clusters ◽  
Integrated Approach ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Health Crisis ◽  
Functional Genetics

Antimicrobial resistance is a worldwide health crisis for which new antibiotics are needed. One strategy for antibiotic discovery is identifying unique antibiotic biosynthetic gene clusters that may produce novel compounds. The aim of this study was to demonstrate how an integrated approach that combines genome mining, comparative genomics, and functional genetics can be used to successfully identify novel biosynthetic gene clusters that produce antimicrobial natural products. Secondary metabolite clusters of an antibiotic producer are first predicted using genome mining tools, generating a list of candidates. Comparative genomic approaches are then used to identify gene suites present in the antibiotic producer that are absent in closely related non-producers. Gene sets that are common to the two lists represent leading candidates, which can then be confirmed using functional genetics approaches. To validate this strategy, we identified the genes responsible for antibiotic production in Pantoea agglomerans B025670, a strain identified in a large-scale bioactivity survey. The genome of B025670 was first mined with antiSMASH, which identified 24 candidate regions. We then used the comparative genomics platform, EDGAR, to identify genes unique to B025670 that were not present in closely related strains with contrasting antibiotic production profiles. The candidate lists generated by antiSMASH and EDGAR were compared with standalone BLAST. Among the common regions was a 14 kb cluster consisting of 14 genes with predicted enzymatic, transport, and unknown functions. Site-directed mutagenesis of the gene cluster resulted in a reduction in antimicrobial activity, suggesting involvement in antibiotic production. An integrated approach that combines genome mining, comparative genomics, and functional genetics yields a powerful, yet simple strategy for identifying potentially novel antibiotics.

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 Global biogeographic sampling of bacterial secondary metabolism

eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
Zachary Charlop-Powers ◽  
Jeremy G Owen ◽  
Boojala Vijay B Reddy ◽  
Melinda A Ternei ◽  
Denise O Guimarães ◽  
...  
Keyword(s):  
Secondary Metabolites ◽  
Genome Sequencing ◽  
Geographic Distance ◽  
Gene Clusters ◽  
Natural World ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Road Map ◽  
Two Factors ◽  
Natural Products Discovery

Recent bacterial (meta)genome sequencing efforts suggest the existence of an enormous untapped reservoir of natural-product-encoding biosynthetic gene clusters in the environment. Here we use the pyro-sequencing of PCR amplicons derived from both nonribosomal peptide adenylation domains and polyketide ketosynthase domains to compare biosynthetic diversity in soil microbiomes from around the globe. We see large differences in domain populations from all except the most proximal and biome-similar samples, suggesting that most microbiomes will encode largely distinct collections of bacterial secondary metabolites. Our data indicate a correlation between two factors, geographic distance and biome-type, and the biosynthetic diversity found in soil environments. By assigning reads to known gene clusters we identify hotspots of biomedically relevant biosynthetic diversity. These observations not only provide new insights into the natural world, they also provide a road map for guiding future natural products discovery efforts.

Biosynthetic strategies for tetramic acid formation

2021 ◽  
Author(s):  
Xuhua Mo ◽  
Tobias A. M. Gulder
Keyword(s):  
Molecular Mechanism ◽  
Gene Clusters ◽  
Acid Formation ◽  
Biosynthetic Gene ◽  
Tetramic Acid ◽  
Biosynthetic Gene Clusters ◽  
The Individual ◽  
First Time ◽  
Acid Unit

Over 30 biosynthetic gene clusters for natural tetramate have been identified. This highlight reviews the biosynthetic strategies for formation of tetramic acid unit for the first time, discussing the individual molecular mechanism in detail.

Challenges of functional expression of complex polyketide biosynthetic gene clusters

2021 ◽  
Vol 69 ◽  
pp. 103-111
Author(s):  
Yaojie Gao ◽  
Yuchun Zhao ◽  
Xinyi He ◽  
Zixin Deng ◽  
Ming Jiang
Keyword(s):  
Gene Clusters ◽  
Functional Expression ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters
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