Promising antimicrobial protein from Klebsiella
NOPR - NISCAIR Online Periodicals Repository
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Title |
Promising antimicrobial protein from Klebsiella
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Creator |
Shahadani, Ashwini A.
M, Rajyalakshmi Hadagali, Ashoka Vinjamuri, Saisha |
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Subject |
Antimicrobial peptides
APD3 software Bacteriocins CAMPR3 software |
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Description |
834-841
Increasing antibody resistance necessitates the use of new antimicrobial products. Antimicrobial peptides (AMP`s) And Proteins are a promising alternative to antibiotics currently being used due to their high degree of specificity & wide range of action Here we report a novel antimicrobial protein from iron reducing bacteria isolated from the coffee estate soils of Coorg district, Karnataka, India. Iron reducing bacteria are known to be antagonistic to others due to the presence of Pseuderophores. It makes them a good source of antimicrobial active principles. Fifteen isolates were obtained by selectively screening for iron reduction. These isolates were tested for antimicrobial activity against Gram positive [Staphylococcus aureus (MTCC3160), Bacillus cereus (MTCC6620)] & Gram negative [Escherichia coli (MTCC1650), Salmonella typhi (MTCC3224) and Pseudomonas aeruginosa (MTCC2453)] bacteria. Of the 15 isolates, one isolate, CBI-8, which showed good antimicrobial activity, was selected for further studies. The isolate was identified by MALDI-TOF & 16S rDNA sequencing as Klebsiella variicola/quasipneumonae (strain IS93) (genebank - MN814029). To induce and augment the production of antimicrobial molecules, CBI-8 was grown in the presence of Salmonella typhi and the spent medium was subjected to ammonium sulphate precipitation. The fractions which showed promising activity were further subjected to preparatory HPLC. The distinct bands obtained in the SDS-PAGE corresponding to the HPLC peak that showed antimicrobial activity from the induced sample was analyzed by Mass Spectrometry. Antimicrobial Peptide Database (APD3) calculator, Collection of Anti-Microbial Peptides (CAMPR3) software used to predict AMPs in the proteins identified from MS data. |
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Date |
2021-12-02T06:54:12Z
2021-12-02T06:54:12Z 2021-12 |
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Type |
Article
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Identifier |
0975-1009 (Online); 0019-5189 (Print)
http://nopr.niscair.res.in/handle/123456789/58573 |
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Language |
en
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Publisher |
NIScPR-CSIR, India
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Source |
IJEB Vol.59(12) [December 2021]
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