Unclassified Caudoviricetes strain:Acinetobacter baumannii
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ABSTRACT:
PROVIDER: PRJNA912627 | ENA |
REPOSITORIES: ENA
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Project description:Acinetobacter phage Aclw_9
| PRJNA912625 | ENA
Project description:Acinetobacter phage Acba_4
| PRJNA912609 | ENA
Project description:The bacterial pathogen, Acinetobacter baumannii, is a leading cause of drug-resistant infections. Here, we investigated the potential of developing nanobodies that specifically recognize A. baumannii over other Gram-negative bacteria. Through generation and panning of a synthetic nanobody library, we identified several potential lead candidates. We demonstrate how incorporation of next generation sequencing analysis can aid in selection of lead candidates for further characterization. Using monoclonal phage display, we validated the binding of several lead nanobodies to A. baumannii. Subsequent purification and biochemical characterization revealed one particularly robust nanobody that broadly and specifically bound A. baumannii compared to other common drug resistant pathogens. These findings support the potentially for nanobodies to selectively target A. baumannii and the identification of lead candidates for possible future diagnostic and therapeutic development.
2023-06-21 | GSE202972 | GEO
Project description:Transcriptomic comparison of a multidrug resistant Acinetobacter baumannii strain and a susceptible reference strain.
2009-11-20 | E-MEXP-2254 | biostudies-arrayexpress
Project description:In recent years, the Gram-negative bacterium Acinetobacter baumannii has garnered considerable attention for its unprecedented capacity to rapidly develop resistance to antibacterial therapeutics. This is coupled with the seemingly epidemic emergence of new hyper-virulent strains. Although strain-specific differences for A. baumannii isolates have been well described, these studies have primarily focused on proteinaceous factors. At present, only limited publications have investigated the presence and role of small regulatory RNA (sRNA) transcripts. Herein, we perform such an analysis, describing the RNA-seq-based identification of 78 A. baumannii sRNAs in the AB5075 background. Together with six previously identified elements, we include each of these in a new genome annotation file, which will serve as a tool to investigate regulatory events in this organism. Our work reveals that the sRNAs display high expression, accounting for >50 % of the 20 most strongly expressed genes. Through conservation analysis we identified six classes of similar sRNAs, with one found to be particularly abundant and homologous to regulatory, C4 antisense RNAs found in bacteriophages. These elements appear to be processed from larger transcripts in an analogous manner to the phage C4 molecule and are putatively controlled by two further sRNAs that are strongly antisense to them. Collectively, this study offers a detailed view of the sRNA content of A. baumannii, exposing sequence and structural conservation amongst these elements, and provides novel insight into the potential evolution, and role, of these understudied regulatory molecules. This study is based on the annotation of novel sRNAs on basis of an Acinetobacter baumannii RNA sequencing dataset. Each sample was generated by pooling three independent biological replicate RNA preps
2016-03-30 | E-GEOD-75708 | biostudies-arrayexpress
Project description:In this study the transcriptomes of Acinetobacter baumannii strains ATCC 17978 and 17978hm were compared. Strain 17978hm is a hns knockout derivative of strain ATCC 17978. Strain 17978hm displays a hyper-motile phenotype on semi-solid Mueller-Hinton (MH) media (0.25% agar). ATCC 17978 and 17978hm from an 37C overnight culture were transferred to the centre of the semi-solid MH plate and incubated at 37C for 8 hours. Only 17978hm cells displayed a motile phenotype and covered the complete surface of the plate. These motile 17978hm cells and the non-motile wild-type ATCC 17978 cells were harvested and RNA was isolated. The comparative transcriptome analysis was performed using the FairPlay labeling kit and a custom made Agilent MicroArray with probes designed to coding regions of the ATCC 17978 genome. The data was analyzed using Agilent GeneSpring GX9 and the significance analysis of microarray MS Excel add-on.
2013-08-05 | GSE40681 | GEO