Macrolactin S, a New Antibacterial Agent with Fab G-inhibitory Activity from Bacillus sp. AT28

BackgroundIdentifying essential genes in bacteria supports to identify potential drug targets and an understanding of minimal requirements for a synthetic cell. However, experimentally assaying the essentiality of their coding genes is resource intensive and not feasible for all bacterial organisms, in particular if they are infective.ResultsWe developed a machine learning technique to identify essential genes using the experimental data of genome-wide knock-out screens from one bacterial organism to infer essential genes of another related bacterial organism. We used a broad variety of topological features, sequence characteristics and co-expression properties potentially associated with essentiality, such as flux deviations, centrality, codon frequencies of the sequences, co-regulation and phyletic retention. An organism-wise cross-validation on bacterial species yielded reliable results with good accuracies (area under the receiver-operator-curve of 75% - 81%). Finally, it was applied to drug target predictions for Salmonella typhimurium. We compared our predictions to the viability of experimental knock-outs of S. typhimurium and identified 35 enzymes, which are highly relevant to be considered as potential drug targets. Specifically, we detected promising drug targets in the non-mevalonate pathway.ConclusionsUsing elaborated features characterizing network topology, sequence information and microarray data enables to predict essential genes from a bacterial reference organism to a related query organism without any knowledge about the essentiality of genes of the query organism. In general, such a method is beneficial for inferring drug targets when experimental data about genome-wide knockout screens is not available for the investigated organism.

show abstract

“…** fabG: 3-ketoacyl-(acyl-carrier-protein) reductase is a well-known drug target of E. coli, B. subtilis , and S. aureus [40]. …”

Section: Resultsmentioning

confidence: 99%

Identifying essential genes in bacterial metabolic networks with machine learning methods

2010

View full text Add to dashboard Cite

show abstract

“…[34], the activity of Macrolactin S isolated from Bacillus sp. AT 28 that inhibited the growth of S. aureus , Bacillus subtilis , and Escherichia coli [35], and the antimicrobial activity of Bacillus sp. strain FAS1 isolated from soil was demonstrated on the standard indicator species [36].…”

Section: Discussionmentioning

confidence: 99%

Antiviral Activity of Bacillus sp. Isolated from the Marine Sponge Petromica citrina against Bovine Viral Diarrhea Virus, a Surrogate Model of the Hepatitis C Virus

Bastos

Kohn

Fantinatti-Garboggini

et al. 2013

Viruses

View full text Add to dashboard Cite

The Hepatitis C virus causes chronic infections in humans, which can develop to liver cirrhosis and hepatocellular carcinoma. The Bovine viral diarrhea virus is used as a surrogate model for antiviral assays for the HCV. From marine invertebrates and microorganisms isolated from them, extracts were prepared for assessment of their possible antiviral activity. Of the 128 tested, 2 were considered active and 1 was considered promising. The best result was obtained from the extracts produced from the Bacillus sp. isolated from the sponge Petromica citrina. The extracts 555 (500 µg/mL, SI>18) and 584 (150 µg/mL, SI 27) showed a percentage of protection of 98% against BVDV, and the extract 616, 90% of protection. All of them showed activity during the viral adsorption. Thus, various substances are active on these studied organisms and may lead to the development of drugs which ensure an alternative therapy for the treatment of hepatitis C.

show abstract

“…However, FabG does not appear to have a rate-controlling role in fatty acid synthesis, making it less desirable as a target. While several natural product FabG inhibitors have been reported [72,73], there has been very little follow through research to validate the selectivity of these inhibitors or develop the compounds further. FabG remains to be validated as a suitable target for drug discovery.…”

Section: Antibiotic Targets In Fatty Acid Metabolismmentioning

confidence: 99%

Bacterial fatty acid metabolism in modern antibiotic discovery

Yao

Rock

2017

Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biolog

View full text Add to dashboard Cite

Bacterial fatty acid synthesis is essential for many pathogens and different from the mammalian counterpart. These features make bacterial fatty acid synthesis a desirable target for antibiotic discovery. The structural divergence of the conserved enzymes and the presence of different isozymes catalyzing the same reactions in the pathway make bacterial fatty acid synthesis a narrow spectrum target rather than the traditional broad spectrum target. Furthermore, bacterial fatty acid synthesis inhibitors are single-targeting, rather than multi-targeting like traditional monotherapeutic, broad-spectrum antibiotics. The single-targeting nature of bacterial fatty acid synthesis inhibitors makes overcoming fast-developing, target-based resistance a necessary consideration for antibiotic development. Target-based resistance can be overcome through multi-targeting inhibitors, a cocktail of single-targeting inhibitors, or by making the single targeting inhibitor sufficiently high affinity through a pathogen selective approach such that target-based mutants are still susceptible to therapeutic concentrations of drug. Many of the pathogens requiring new antibiotic treatment options encode for essential bacterial fatty acid synthesis enzymes. This review will evaluate the most promising targets in bacterial fatty acid metabolism for antibiotic therapeutics development and review the potential and challenges in advancing each of these targets to the clinic and circumventing target-based resistance.

show abstract

Macrolactin S, a New Antibacterial Agent with Fab G-inhibitory Activity from Bacillus sp. AT28

Cited by 34 publications

References 20 publications

Identifying essential genes in bacterial metabolic networks with machine learning methods

Identifying essential genes in bacterial metabolic networks with machine learning methods

Antiviral Activity of Bacillus sp. Isolated from the Marine Sponge Petromica citrina against Bovine Viral Diarrhea Virus, a Surrogate Model of the Hepatitis C Virus

Bacterial fatty acid metabolism in modern antibiotic discovery

Contact Info

Product

Resources

About