Dataset Information

Computational screening of antimicrobial peptides for Acinetobacter baumannii.

ABSTRACT: Acinetobacter baumannii, has been developing resistance to even the last line of drugs. Antimicrobial peptides (AMPs) to which bacteria do not develop resistance easily may be the last hope. A few independent experimental studies have designed and studied the activity of AMPs on A. baumannii, however the number of such studies are still limited. With the goal of developing a rational approach to the screening of AMPs against A. baumannii, we carefully curated the drug activity data from 75 cationic AMPs, all measured with a similar protocol, and on the same ATCC 19606 strain. A quantitative model developed and validated with a part of the data. While the model may be used for predicting the activity of any designed AMPs, in this work, we perform an in silico screening for the entire database of naturally occurring AMPs, to provide a rational guidance in this urgently needed drug development.

SUBMITTER: Majumder A

PROVIDER: S-EPMC6774513 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Computational screening of antimicrobial peptides for Acinetobacter baumannii.

Majumder Ayan A Biswal Malay Ranjan MR Prakash Meher K MK

PloS one 20191002 10

Acinetobacter baumannii, has been developing resistance to even the last line of drugs. Antimicrobial peptides (AMPs) to which bacteria do not develop resistance easily may be the last hope. A few independent experimental studies have designed and studied the activity of AMPs on A. baumannii, however the number of such studies are still limited. With the goal of developing a rational approach to the screening of AMPs against A. baumannii, we carefully curated the drug activity data from 75 catio ...[more]

PMID: 31577808

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Project description:Multidrug-Resistant (MDR) and Extensively Drug Resistant (XDR) Acinetobacter baumannii (Ab) represent a serious cause of healthcare-associated infections worldwide. Currently, the available treatment options are very restricted and colistin-based therapies are last-line treatments of these infections, even though colistin resistant (COLR) Ab have rarely been isolated yet. In bacteria, small non-coding RNAs (sRNAs) have been implicated in regulatory pathways of different biological functions, however, no knowledge exists about the sRNA role on the biological adaptation in COLR Ab. Our study investigated two Italian XDR isogenic colistin-susceptible/resistant (COLS/R) Ab strain-pairs to discover new sRNA signatures. Comparative sRNA transcriptome (sRNAome) analyses were carried out by Illumina RNA-seq using both a Tru-Seq and a Short Insert library, whilst Ab ATCC 17978 and ACICU Reference Genome assembly, mapping, annotation and statistically significant differential expression (q-value ≤ 0.01) of the raw reads were performed by the Rockhopper tool. A computational filtering, sorting only similarly statistically significant differentially expressed (DE) sRNAs mapping on the same gene in both COLR Ab isolates was conducted. COLR vs. COLS sRNAome, analyzed integrating the DE sRNAs obtained from the two different libraries, revealed some statistically significant DE sRNAs in COLR Ab. In detail, we found: (i) two different under-expressed cis-acting sRNAs (AbsRNA1 and AbsRNA2) mapping in antisense orientation the 16S rRNA gene A1S_r01, (ii) one under-expressed cis-acting sRNA (AbsRNA3) targeting the A1S_2505 gene (hypothetical protein), (iii) one under-expressed microRNA-size small RNA fragment (AbsRNA4) and its pre-microAbsRNA4 targeting the A1S_0501 gene (hypothetical protein), (iv) as well as an over-expressed microRNA-size small RNA fragment (AbsRNA5) and its pre-microAbsRNA5 targeting the A1S_3097 gene (signal peptide). Custom TaqMan® probe-based real-time qPCRs validated the expression pattern of the selected sRNA candidates shown by RNA-seq. Furthermore, analysis on sRNA ΔA1S_r01, ΔA1S_2505 as well as the over-expressed A1S_3097 mutants revealed no effects on colistin resistance. Our study, for the first time, found the sRNAome signatures of clinical COLR Ab with a computational prediction of their targets related to protein synthesis, host-microbe interaction and other different biological functions, including biofilm production, cell-cycle control, virulence, and antibiotic-resistance.

Dataset Information

Computational screening of antimicrobial peptides for Acinetobacter baumannii.

Publications

Computational screening of antimicrobial peptides for Acinetobacter baumannii.

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