Genetics of antibiotic production.

Hopwood, D A; Merrick, M J

doi:10.1128/mmbr.41.3.595-635.1977

Cited by 88 publications

(12 citation statements)

References 146 publications

(207 reference statements)

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“…The actinomycetes differ from many prokaryotes in their ability to exhibit highly variable phenotypes, including undergoing complex morphological differentiation and producing a multitude of secondary metabolites, generally under conditions that are not favourable for growth. For organisms that thrive in environments of diverse nutrient input, the ability to produce a variety of broad-specificity enzymes may represent part of an overall strategy to cope with a constantly changing environment (Hopwood and Merrick, 1977). With this in mind, the roles of the P450S described here seem clearer; the P450 can participate in a multi-enzyme pathway to synthesize a 'useful' secondary metabolite (e.g.…”

Section: Discussionmentioning

confidence: 98%

Occurrence and biological function of cytochrome P450 monooxygenases in the actinomycetes

O’Keefe

Harder

1991

Molecular Microbiology

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Many species within the order Actinomycetales contain one or more soluble cytochrome P450 monooxygenases, often substrate-inducible and responsible for a variety of xenobiotic transformations. The individual cytochromes exhibit a relatively broad substrate specificity, and some strains have the capacity to synthesize large amounts of the protein(s) to compensate for low catalytic turnover with some substrates. All three of the Streptomyces cytochromes sequenced to date are exclusive members of one P450 family, CYP105. In several instances, monooxygenase activity arises from induction of a P450 and associated ferredoxin, or of a P450 only, suggesting that some essential electron donor proteins (reductase and ferredoxin) are not co-ordinately regulated with the cytochrome. The overall properties of these systems suggest an adaptive strategy whose twofold purpose is to maintain a competitive advantage via the production of secondary metabolites, and, whenever possible, to utilize unusual growth substrates by introducing metabolites from these reactions into the more substrate-specific primary metabolic pathways.

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Section: Discussionmentioning

confidence: 98%

Occurrence and biological function of cytochrome P450 monooxygenases in the actinomycetes

O’Keefe

Harder

1991

Molecular Microbiology

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“…Therefore, such properties can be easily transmitted to susceptible organisms. Also, production of and resistance to antibiotics in producing organisms can be controlled, in some cases, by extrachromosomal genetic elements, either directly or indirectly (79,80,132,156,164). Thus, the extrachromosomal genetic elements also demonstrate two conflicting properties: the resistance trait in pathogenic and producing bac-teria and the production control trait in producing organisms.…”

Section: Introductionmentioning

confidence: 99%

Antibiotic resistance in pathogenic and producing bacteria, with special reference to beta-lactam antibiotics.

Ogawara¹

1981

Microbiological Reviews

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“…Early genetic work in the field of natural product discovery showed that bioactive molecules are microbial secondary metabolites whose synthesis is primarily orchestrated by genomically colocalized genes termed Biosynthetic Gene Clusters (BGCs) [9][10][11] . While these early insights were born out of forward genetic approaches (progressing from phenotype to sequence), the advent of next generation sequencing technologies and genomic approaches provided opportunities for reverse genetic approaches (progression from sequence to phenotype) in BGC discovery, synthesis, and characterization 2 .…”

Section: Introductionmentioning

confidence: 99%

A Deep Learning Genome-Mining Strategy Improves Biosynthetic Gene Cluster Prediction

Hannigan

Prihoda²,

Palička³

et al. 2018

Preprint

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Natural products represent a rich reservoir of small molecule drug candidates utilized as antimicrobial drugs, anticancer therapies, and immunomodulatory agents. These molecules are microbial secondary metabolites synthesized by co-localized genes termed Biosynthetic Gene Clusters (BGCs). The increase in full microbial genomes and similar resources has led to development of BGC prediction algorithms, although their precision and ability to identify novel BGC classes could be improved. Here we present a deep learning strategy (DeepBGC) that offers more accurate BGC identification and an improved ability to extrapolate and identify novel BGC classes compared to existing tools. We supplemented this with downstream random forest classifiers that accurately predicted BGC product classes and potential chemical activity.Application of DeepBGC to bacterial genomes uncovered previously undetectable BGCs that may code for natural products with novel biologic activities. The improved accuracy and classification ability of DeepBGC represents a significant step forward for in-silico BGC identification.

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Genetics of antibiotic production.

Cited by 88 publications

References 146 publications

Occurrence and biological function of cytochrome P450 monooxygenases in the actinomycetes

Occurrence and biological function of cytochrome P450 monooxygenases in the actinomycetes

Antibiotic resistance in pathogenic and producing bacteria, with special reference to beta-lactam antibiotics.

A Deep Learning Genome-Mining Strategy Improves Biosynthetic Gene Cluster Prediction

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