scholarly journals Structure-guided function discovery of an NRPS-like glycine betaine reductase for choline biosynthesis in fungi

2019 ◽  
Author(s):  
Yang Hai ◽  
Arthur Huang ◽  
Yi Tang
Keyword(s):  
Glycine Betaine ◽  
Genome Mining ◽  
Domain Architecture ◽  
Homology Model ◽  
Bioinformatic Analysis ◽  
Degradation Pathway ◽  
Substrate Analogs ◽  
Peptide Synthetases ◽  
Primary And Secondary Metabolism ◽  
Function Discovery

ABSTRACTNonribosomal peptide synthetases (NRPS) and NRPS-like enzymes have diverse functions in primary and secondary metabolism. By using a structure-guided approach, we uncovered the function of an NRPS-like enzyme with unusual domain architecture, catalyzing two sequential two-electron reductions of glycine betaine to choline. Structural analysis based on homology model suggests cation-π interactions as the major substrate specificity determinant, which was verified using substrate analogs and inhibitors. Bioinformatic analysis indicates this NRPS-like glycine betaine reductase is highly conserved and widespread in fungi kingdom. Genetic knockout experiments confirmed its role in choline biosynthesis and maintaining glycine betaine homeostasis in fungi. Our findings demonstrate that the oxidative choline-glycine betaine degradation pathway can operate in a fully reversible fashion and provide new insights in understanding fungal choline metabolism. The use of an NRPS-like enzyme for reductive choline formation is energetically efficient compared to known pathways. Our discovery also underscores the capabilities of structure-guided approach in assigning function of uncharacterized multidomain proteins, which can potentially aid functional discovery of new enzymes by genome mining.

scholarly journals Structure-guided function discovery of an NRPS-like glycine betaine reductase for choline biosynthesis in fungi

2019 ◽  
Vol 116 (21) ◽  
pp. 10348-10353 ◽  
Author(s):  
Yang Hai ◽  
Arthur M. Huang ◽  
Yi Tang
Keyword(s):  
Glycine Betaine ◽  
Genome Mining ◽  
Domain Architecture ◽  
Homology Model ◽  
Bioinformatic Analysis ◽  
Degradation Pathway ◽  
Substrate Analogs ◽  
Peptide Synthetases ◽  
Choline Metabolism ◽  
Function Discovery

Nonribosomal peptide synthetases (NRPSs) and NRPS-like enzymes have diverse functions in primary and secondary metabolisms. By using a structure-guided approach, we uncovered the function of a NRPS-like enzyme with unusual domain architecture, catalyzing two sequential two-electron reductions of glycine betaine to choline. Structural analysis based on the homology model suggests cation-π interactions as the major substrate specificity determinant, which was verified using substrate analogs and inhibitors. Bioinformatic analysis indicates this NRPS-like glycine betaine reductase is highly conserved and widespread in kingdom fungi. Genetic knockout experiments confirmed its role in choline biosynthesis and maintaining glycine betaine homeostasis in fungi. Our findings demonstrate that the oxidative choline-glycine betaine degradation pathway can operate in a fully reversible fashion and provide insight in understanding fungal choline metabolism. The use of an NRPS-like enzyme for reductive choline formation is energetically efficient compared with known pathways. Our discovery also underscores the capabilities of the structure-guided approach in assigning functions of uncharacterized multidomain proteins, which can potentially aid functional discovery of new enzymes by genome mining.

scholarly journals Synthaser: a CD-Search enabled Python toolkit for analysing domain architecture of fungal secondary metabolite megasynth(et)ases

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Cameron L. M. Gilchrist ◽  
Yit-Heng Chooi
Keyword(s):  
Web Application ◽  
Large Scale ◽  
Genome Mining ◽  
Domain Architecture ◽  
Fungal Genome ◽  
Peptide Synthetases ◽  
Link Type ◽  
Conserved Domain ◽  
Search Tool

Abstract Background Fungi are prolific producers of secondary metabolites (SMs), which are bioactive small molecules with important applications in medicine, agriculture and other industries. The backbones of a large proportion of fungal SMs are generated through the action of large, multi-domain megasynth(et)ases such as polyketide synthases (PKSs) and nonribosomal peptide synthetases (NRPSs). The structure of these backbones is determined by the domain architecture of the corresponding megasynth(et)ase, and thus accurate annotation and classification of these architectures is an important step in linking SMs to their biosynthetic origins in the genome. Results Here we report synthaser, a Python package leveraging the NCBI’s conserved domain search tool for remote prediction and classification of fungal megasynth(et)ase domain architectures. Synthaser is capable of batch sequence analysis, and produces rich textual output and interactive visualisations which allow for quick assessment of the megasynth(et)ase diversity of a fungal genome. Synthaser uses a hierarchical rule-based classification system, which can be extensively customised by the user through a web application (http://gamcil.github.io/synthaser). We show that synthaser provides more accurate domain architecture predictions than comparable tools which rely on curated profile hidden Markov model (pHMM)-based approaches; the utilisation of the NCBI conserved domain database also allows for significantly greater flexibility compared to pHMM approaches. In addition, we demonstrate how synthaser can be applied to large scale genome mining pipelines through the construction of an Aspergillus PKS similarity network. Conclusions Synthaser is an easy to use tool that represents a significant upgrade to previous domain architecture analysis tools. It is freely available under a MIT license from PyPI (https://pypi.org/project/synthaser) and GitHub (https://github.com/gamcil/synthaser).

scholarly journals Steroid Metabolism In Thermophilic Actinobacteria Saccharopolyspora Hirsuta Subsp. Hirsuta VKM Ac-666T

2021 ◽  
Author(s):  
Tatyana Gennadyevna Lobastova ◽  
Victoria V. Fokina ◽  
Sergey V. Tarlachkov ◽  
Andrey A. Shutov ◽  
Eugeny Yu. Bragin ◽  
...  
Keyword(s):  
Structural Modification ◽  
Thermophilic Bacteria ◽  
Cholesterol Oxidase ◽  
Bioinformatic Analysis ◽  
Degradation Pathway ◽  
Side Chain ◽  
P450 Monooxygenase ◽  
Key Genes ◽  
Saccharopolyspora Hirsuta ◽  
Steroid Catabolism

Abstract Application of thermophile microorganisms opens new prospects in steroid biotechnology, however little is known on steroid catabolism by the thermophile strains.The thermophilic Saccharopolyspora hirsuta subsp. hirsuta strain VKM Ac-666T is capable of structural modification of different steroids, and fully degrades cholesterol. The intermediates of the cholesterol degradation pathway were identified as cholest-4-en-3-one, cholesta-1,4-dien-3-one, 26-hydroxycholest-4-en-3-one, 3-oxo-cholest-4-en-26-oic acid, 3-oxo-cholesta-1,4-dien-26-oic acid, 26-hydroxycholesterol, 3β-hydroxy-cholest-5-en-26-oic acid by MS, and H1- and C13-NMR analyses. The data evidence sterol degradation by the strain occurs simultaneously through the aliphatic side chain hydroxylation at C26 and the A-ring modification that are putatively catalyzed by cytochrome P450 monooxygenase CYP125 and cholesterol oxidase, respectively.The genes orthologous to those related to the sterol side chain degradation, steroid core rings A/B and C/D disruption and the steroid uptake were revealed. Most of the genes related to steroid degradation are grouped in three clusters. The sets of the genes putatively involved in steroid catabolism and peculiarities of their organization in S. hirsuta are discussed.Despite steroids abundancy in the environments, the ability to degrade them is not widespread among thermophilic bacteria as follows from the bioinformatic analysis of 52 publicly available genomes. Only seven candidate strains were revealed to possess the key genes related to the only known 9(10)-seco pathway of steroid degradation.The results contribute to the knowledge on diversity of microbial steroid degraders, the features of sterol catabolism by thermophilic actinobacteria and could be useful for application in the pharmaceutical and environmental biotechnology.

scholarly journals Autotransporters of Escherichia coli: a sequence-based characterization

Microbiology ◽  
2010 ◽  
Vol 156 (8) ◽  
pp. 2459-2469 ◽  
Author(s):  
Timothy J. Wells ◽  
Makrina Totsika ◽  
Mark A. Schembri
Keyword(s):  
Escherichia Coli ◽  
Biofilm Formation ◽  
Domain Architecture ◽  
Bioinformatic Analysis ◽  
Tissue Tropism ◽  
Genome Sequences ◽  
E Coli ◽  
Disease Outcomes ◽  
High Degree ◽  
Encoding Genes

Autotransporter (AT) proteins are found in all Escherichia coli pathotypes and are often associated with virulence. In this study we took advantage of the large number of available E. coli genome sequences to perform an in-depth bioinformatic analysis of AT-encoding genes. Twenty-eight E. coli genome sequences were probed using an iterative approach, which revealed a total of 215 AT-encoding sequences that represented three major groups of distinct domain architecture: (i) serine protease AT proteins, (ii) trimeric AT adhesins and (iii) AIDA-I-type AT proteins. A number of subgroups were identified within each broad category, and most subgroups contained at least one characterized AT protein; however, seven subgroups contained no previously described proteins. The AIDA-I-type AT proteins represented the largest and most diverse group, with up to 16 subgroups identified from sequence-based comparisons. Nine of the AIDA-I-type AT protein subgroups contained at least one protein that possessed functional properties associated with aggregation and/or biofilm formation, suggesting a high degree of redundancy for this phenotype. The Ag43, YfaL/EhaC, EhaB/UpaC and UpaG subgroups were found in nearly all E. coli strains. Among the remaining subgroups, there was a tendency for AT proteins to be associated with individual E. coli pathotypes, suggesting that they contribute to tissue tropism or symptoms specific to different disease outcomes.

scholarly journals Synthaser: A CD-search Enabled Python Toolkit for Analysing Domain Architecture of Fungal Secondary Metabolite Megasynth(Et)ases and Beyond

2021 ◽  
Author(s):  
Cameron LM Gilchrist ◽  
Yit Heng Chooi
Keyword(s):  
Web Application ◽  
Large Scale ◽  
Polyketide Synthase ◽  
Genome Mining ◽  
Domain Architecture ◽  
Fungal Genome ◽  
Nonribosomal Peptide ◽  
Conserved Domain ◽  
Search Tool

Abstract Background: Fungi are prolific producers of secondary metabolites (SMs), which are bioactive small molecules with important applications in medicine, agriculture and other industries. The backbones of a large proportion of fungal SMs are generated through the action of large, multi-domain megasynth(et)ases such as polyketide synthases (PKSs) and nonribosomal peptide synthetases (NRPSs). The structure of these backbones is determined by the domain architecture of the corresponding megasynth(et)ase, and thus accurate annotation and classification of these architectures is an important step in linking SMs to their biosynthetic origins in the genome. Results: Here we report synthaser, a Python package leveraging the NCBI's conserved domain search tool for remote prediction and classification of fungal megasynth(et)ase domain architectures. synthaser is capable of batch sequence analysis, and produces rich textual output and interactive visualisations which allow for quick assessment of the megasynth(et)ase diversity of a fungal genome. synthaser uses a hierarchical rule-based classification system, which can be extensively customised by the user through a web application (http://gamcil.github.io/synthaser). We show that synthaser provides more accurate domain architecture predictions than comparable tools which rely on curated profile hidden Markov model (pHMM)-based approaches; the utilisation of the NCBI conserved domain database also allows for significantly greater flexibility compared to pHMM approaches. In addition, we demonstrate how synthaser can be applied to large scale genome mining pipelines through the construction of an Aspergillus PKS similarity network. Conclusions: synthaser is an easy to use tool that represents a significant upgrade to previous domain architecture analysis tools. synthaser is freely available under a MIT license from PyPI (https://pypi.org/project/synthaser) and GitHub (https://github.com/gamcil/synthaser). Keywords: secondary metabolism, domain architecture, polyketide synthase, nonribosomal peptide synthetase, bioinformatics, software

scholarly journals Genome Mining Revealed a High Biosynthetic Potential for Antifungal Streptomyces sp. S-2 Isolated from Black Soot

2020 ◽  
Vol 21 (7) ◽  
pp. 2558
Author(s):  
Piotr Siupka ◽  
Artur Piński ◽  
Dagmara Babicka ◽  
Zofia Piotrowska-Seget
Keyword(s):  
Fungal Pathogens ◽  
Plant Pathogens ◽  
Genome Mining ◽  
Extreme Environments ◽  
Gene Clusters ◽  
Hard Coal ◽  
Vast Number ◽  
Streptomyces Sp ◽  
Peptide Synthetases ◽  
Metabolites Production

The increasing resistance of fungal pathogens has heightened the necessity of searching for new organisms and compounds to combat their spread. Streptomyces are bacteria that are well-known for the production of many antibiotics. To find novel antibiotic agents, researchers have turned to previously neglected and extreme environments. Here, we isolated a new strain, Streptomyces sp. S-2, for the first time, from black soot after hard coal combustion (collected from an in-use household chimney). We examined its antifungal properties against plant pathogens and against fungi that potentially pose threat to human health (Fusarium avenaceum, Aspergillus niger and the environmental isolates Trichoderma citrinoviridae Cin-9, Nigrospora oryzae sp. roseF7, and Curvularia coatesieae sp. junF9). Furthermore, we obtained the genome sequence of S-2 and examined its potential for secondary metabolites production using anti-SMASH software. The S-2 strain shows activity against all of the tested fungi. Genome mining elucidated a vast number of biosynthetic gene clusters (55), which distinguish this strain from closely related strains. The majority of the predicted clusters were assigned to non-ribosomal peptide synthetases or type 1 polyketide synthetases, groups known to produce compounds with antimicrobial activity. A high number of the gene clusters showed no, or low similarity to those in the database, raising the possibility that S-2 could be a producer of novel antibiotics. Future studies on Streptomyces sp. S-2 will elucidate its full biotechnological potential.

scholarly journals Burkholderia genome mining for nonribosomal peptide synthetases reveals a great potential for novel siderophores and lipopeptides synthesis

2016 ◽  
Vol 5 (3) ◽  
pp. 512-526 ◽  
Author(s):  
Qassim Esmaeel ◽  
Maude Pupin ◽  
Nam Phuong Kieu ◽  
Gabrielle Chataigné ◽  
Max Béchet ◽  
...  
Keyword(s):  
Genome Mining ◽  
Nonribosomal Peptide ◽  
Nonribosomal Peptide Synthetases ◽  
Peptide Synthetases

scholarly journals Genome Mining, Microbial Interactions, and Molecular Networking Reveals New Dibromoalterochromides from Strains of Pseudoalteromonas of Coiba National Park-Panama

Marine Drugs ◽  
2020 ◽  
Vol 18 (9) ◽  
pp. 456
Author(s):  
Librada A. Atencio ◽  
Cristopher A. Boya P. ◽  
Christian Martin H. ◽  
Luis C. Mejía ◽  
Pieter C. Dorrestein ◽  
...  
Keyword(s):  
National Park ◽  
Genome Mining ◽  
Gene Clusters ◽  
Microbial Interactions ◽  
Antimicrobial Compounds ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Molecular Networking ◽  
Peptide Synthetases ◽  
Genomic Basis

The marine bacterial genus Pseudoalteromonas is known for their ability to produce antimicrobial compounds. The metabolite-producing capacity of Pseudoalteromonas has been associated with strain pigmentation; however, the genomic basis of their antimicrobial capacity remains to be explained. In this study, we sequenced the whole genome of six Pseudoalteromonas strains (three pigmented and three non-pigmented), with the purpose of identifying biosynthetic gene clusters (BGCs) associated to compounds we detected via microbial interactions along through MS-based molecular networking. The genomes were assembled and annotated using the SPAdes and RAST pipelines and mined for the identification of gene clusters involved in secondary metabolism using the antiSMASH database. Nineteen BGCs were detected for each non-pigmented strain, while more than thirty BGCs were found for two of the pigmented strains. Among these, the groups of genes of nonribosomal peptide synthetases (NRPS) that code for bromoalterochromides stand out the most. Our results show that all strains possess BGCs for the production of secondary metabolites, and a considerable number of distinct polyketide synthases (PKS) and NRPS clusters are present in pigmented strains. Furthermore, the molecular networking analyses revealed two new molecules produced during microbial interactions: the dibromoalterochromides D/D’ (11–12).

scholarly journals Discovery of 16-Demethylrifamycins by Removing the Predominant Polyketide Biosynthesis Pathway in Micromonospora sp. Strain TP-A0468

2018 ◽  
Vol 85 (4) ◽  
Author(s):  
Qiang Zhou ◽  
Guang-Cai Luo ◽  
Huizhan Zhang ◽  
Gong-Li Tang
Keyword(s):  
Natural Products ◽  
Transcriptional Activation ◽  
Metabolic Flux ◽  
Genome Mining ◽  
Gene Clusters ◽  
Bioinformatic Analysis ◽  
Transcriptional Analysis ◽  
Content Type ◽  
In The Wild ◽  
New Compounds

ABSTRACT A number of strategies have been developed to mine novel natural products based on biosynthetic gene clusters and there have been dozens of successful cases facilitated by the development of genomic sequencing. During our study on biosynthesis of the antitumor polyketide kosinostatin (KST), we found that the genome of Micromonospora sp. strain TP-A0468, the producer of KST, contains other potential polyketide gene clusters, with no encoded products detected. Deletion of kst cluster led to abolishment of KST and the enrichment of several new compounds, which were isolated and characterized as 16-demethylrifamycins (referred to here as compounds 3 to 6). Transcriptional analysis demonstrated that the expression of the essential genes related to the biosynthesis of compounds 3 to 6 was comparable to the level in the wild-type and in the kst cluster deletion strain. This indicates that the accumulation of these compounds was due to the redirection of metabolic flux rather than transcriptional activation. Genetic disruption, chemical complementation, and bioinformatic analysis revealed that the production of compounds 3 to 6 was accomplished by cross talk between the two distantly placed polyketide gene clusters pks3 and M-rif. This finding not only enriches the analogue pool and the biosynthetic diversity of rifamycins but also provides an auxiliary strategy for natural product discovery through genome mining in polyketide-producing microorganisms. IMPORTANCE Natural products are essential in the development of novel clinically used drugs. Discovering new natural products and modifying known compounds are still the two main ways to generate new candidates. Here, we have discovered several rifamycins with varied skeleton structures by redirecting the metabolic flux from the predominant polyketide biosynthetic pathway to the rifamycin pathway in the marine actinomycetes species Micromonospora sp. strain TP-A0468. Rifamycins are indispensable chemotherapeutics in the treatment of various diseases such as tuberculosis, leprosy, and AIDS-related mycobacterial infections. This study exemplifies a useful method for the discovery of cryptic natural products in genome-sequenced microbes. Moreover, the 16-demethylrifamycins and their genetically manipulable producer provide a new opportunity in the construction of novel rifamycin derivates to aid in the defense against the ever-growing drug resistance of Mycobacterium tuberculosis.

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