Biosurfactants produced by Bacillus subtilis A1 and Pseudomonas stutzeri NA3 reduce longevity and fecundity of Anopheles stephensi and show high toxicity against young instars

Parthipan, Punniyakotti; Sarankumar, Raja Kumaresan; Anitha, Jaganathan; Amuthavalli, Pandian; Babujanarthanam, Ranganathan; Rahman, Pattanathu; Murugan, Kadarkarai; Higuchi, Akon; Benelli, Giovanni; Rajasekar, Aruliah

doi:10.1007/s11356-017-0105-0

Cited by 35 publications

(14 citation statements)

References 54 publications

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“…We found that biomass synthesis and rhamnolipids production increased linearly with the rate of metabolite uptake. Our simulation-based predictive results are in keeping with our labbased fermentation work previously carried out with Pseudomonas strains (Rahman et al, 2002;Rahman et al, 2009;Rahman et al, 2010;Joy et al, 2017;Parthipan et al, 2018). In addition, we also identified that myristic acid (C-14) provided optimal growth rate and rhamnolipids production compared to the other carbon sources in this study.…”

Section: Resultssupporting

confidence: 85%

Peer Review #1 of "In silico engineering of Pseudomonas metabolism reveals new biomarkers for increased biosurfactant production (v0.1)"

2018

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Background. Rhamnolipids, biosurfactants with a wide range of biomedical applications, are amphiphilic molecules produced on the surfaces of or excreted extracellularly by bacteria including Pseudomonas aeruginosa. However, Pseudomonas putida is a non-pathogenic model organism with greater metabolic versatility and potential for industrial applications. Methods. We investigate in silico the metabolic capabilities of P. putida for rhamnolipids biosynthesis using statistical, metabolic and synthetic engineering approaches after introducing key genes (RhlA and RhlB) from P. aeruginosa into a genome-scale model of P. putida. This pipeline combines machine learning methods with multi-omic modelling, and drives the engineered P. putida model towards an optimal production and export of rhamnolipids out of the membrane. Results. We identify a substantial increase in synthesis of rhamnolipids by the engineered model compared to the control model. We apply statistical and machine learning techniques on the metabolic reaction rates to identify distinct features on the structure of the variables and individual components driving the variation of growth and rhamnolipids production. We finally provide a computational framework for integrating multi-omics data and identifying latent pathways and genes for the production of rhamnolipids in P. putida. Conclusions. We anticipate that our results will provide a versatile methodology for integrating multiomics data for topological and functional analysis of P. putida towards maximization of biosurfactant production.

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Section: Resultssupporting

confidence: 85%

Peer Review #1 of "In silico engineering of Pseudomonas metabolism reveals new biomarkers for increased biosurfactant production (v0.1)"

2018

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“…We found that biomass synthesis and rhamnolipids production increased linearly with the rate of metabolite uptake. Our simulation-based predictive results are in keeping with our lab-based fermentation work previously carried out with Pseudomonas strains (Rahman et al, 2002, 2009, 2010; Joy, Rahman & Sharma, 2017; Parthipan et al, 2018). In addition, we also identified that myristic acid (C-14) provided optimal growth rate and rhamnolipids production compared to the other carbon sources in this study.…”

Section: Resultssupporting

confidence: 79%

In silico engineering ofPseudomonasmetabolism reveals new biomarkers for increased biosurfactant production

Occhipinti

Eyassu

Rahman

et al. 2018

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BackgroundRhamnolipids, biosurfactants with a wide range of biomedical applications, are amphiphilic molecules produced on the surfaces of or excreted extracellularly by bacteria including Pseudomonas aeruginosa. However, Pseudomonas putida is a non-pathogenic model organism with greater metabolic versatility and potential for industrial applications.MethodsWe investigate in silico the metabolic capabilities of P. putida for rhamnolipids biosynthesis using statistical, metabolic and synthetic engineering approaches after introducing key genes (RhlA and RhlB) from P. aeruginosa into a genome-scale model of P. putida. This pipeline combines machine learning methods with multi-omic modelling, and drives the engineered P. putida model toward an optimal production and export of rhamnolipids out of the membrane.ResultsWe identify a substantial increase in synthesis of rhamnolipids by the engineered model compared to the control model. We apply statistical and machine learning techniques on the metabolic reaction rates to identify distinct features on the structure of the variables and individual components driving the variation of growth and rhamnolipids production. We finally provide a computational framework for integrating multi-omics data and identifying latent pathways and genes for the production of rhamnolipids in P. putida.ConclusionsWe anticipate that our results will provide a versatile methodology for integrating multi-omics data for topological and functional analysis of P. putida toward maximization of biosurfactant production.

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“…In contrast, little is known about the role of the Pseudomonadacea family, highly abundant in BAG mosquitoes, in the development of the malaria parasite. However, specific products extracted from different species of Pseudomonas have shown to reduce the longevity and fecundity of A. stephensi mosquitoes [ 50 , 51 ].…”

Section: Discussionmentioning

confidence: 99%

Factors shaping the gut bacterial community assembly in two main Colombian malaria vectors

et al. 2018

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BackgroundThe understanding of the roles of gut bacteria in the fitness and vectorial capacity of mosquitoes that transmit malaria, is improving; however, the factors shaping the composition and structure of such bacterial communities remain elusive. In this study, a high-throughput 16S rRNA gene sequencing was conducted to understand the effect of developmental stage, feeding status, species, and geography on the composition of the gut bacterial microbiota of two main Colombian malaria vectors, Anopheles nuneztovari and Anopheles darlingi.ResultsThe results revealed that mosquito developmental stage, followed by geographical location, are more important determinants of the gut bacterial composition than mosquito species or adult feeding status. Further, they showed that mosquito gut is a major filter for environmental bacteria colonization.ConclusionsThe sampling design and analytical approach of this study allowed to untangle the influence of factors that are simultaneously shaping the microbiota composition of two Latin-American malaria vectors, essential aspect for the design of vector biocontrol strategies.Electronic supplementary materialThe online version of this article (10.1186/s40168-018-0528-y) contains supplementary material, which is available to authorized users.

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Biosurfactants produced by Bacillus subtilis A1 and Pseudomonas stutzeri NA3 reduce longevity and fecundity of Anopheles stephensi and show high toxicity against young instars

Cited by 35 publications

References 54 publications

Peer Review #1 of "In silico engineering of Pseudomonas metabolism reveals new biomarkers for increased biosurfactant production (v0.1)"

Peer Review #1 of "In silico engineering of Pseudomonas metabolism reveals new biomarkers for increased biosurfactant production (v0.1)"

In silico engineering ofPseudomonasmetabolism reveals new biomarkers for increased biosurfactant production

Factors shaping the gut bacterial community assembly in two main Colombian malaria vectors

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