Project description:Tan2012 - Antibiotic Treatment, Inoculum Effect The efficacy of many antibiotics decreases with increasing bacterial density, a phenomenon called the ‘inoculum effect’ (IE). This study reveals that, for ribosome-targeting antibiotics, IE is due to bistable inhibition of bacterial growth, which reduces the efficacy of certain treatment frequencies. This model is described in the article: The inoculum effect and band-pass bacterial response to periodic antibiotic treatment. Tan C, Phillip Smith R, Srimani JK, Riccione KA, Prasada S, Kuehn M, You L. Mol Syst Biol. 2012 Oct 9; 8:617 Abstract: The inoculum effect (IE) refers to the decreasing efficacy of an antibiotic with increasing bacterial density. It represents a unique strategy of antibiotic tolerance and it can complicate design of effective antibiotic treatment of bacterial infections. To gain insight into this phenomenon, we have analyzed responses of a lab strain of Escherichia coli to antibiotics that target the ribosome. We show that the IE can be explained by bistable inhibition of bacterial growth. A critical requirement for this bistability is sufficiently fast degradation of ribosomes, which can result from antibiotic-induced heat-shock response. Furthermore, antibiotics that elicit the IE can lead to 'band-pass' response of bacterial growth to periodic antibiotic treatment: the treatment efficacy drastically diminishes at intermediate frequencies of treatment. Our proposed mechanism for the IE may be generally applicable to other bacterial species treated with antibiotics targeting the ribosomes. This model is hosted on BioModels Database and identified by: MODEL1208300000 . To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models . To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Treatment failures of antibiotic therapy are of major concern and can be caused by a misalignment of the antibiotic susceptibility determined in vitro with the behaviour of the pathogen in the patient. The aim of this study was to investigate the transcriptomic response of the uropathogenic strain E. coli CFT073 to antibiotic treatment in blood stream infection (BSI) models in order to understand and avoid antibiotic therapy failures in urosepsis treatments. Blood stream infection models were established by growing E. coli CFT073 in pooled human serum with and without ciprofloxacin and compared to Iso-sensitest medium. The antibiotic challenge was introduced at mid-logarithmic phase of growth of the organism to depict a clinical scenario . Global gene expression profiling of these conditions was examined using commercial DNA microarrays. The organism’s metabolic genes appeared to be regulated differently in each medium, this indicated that the bacterial growth regulation were different between the models. Bacterial growth in human serum mainly involved regulations of amino acid synthesis/utilisation such as glycine, arginine, thiamine, regulations of fimbrial proteins and bacteriophage genes. When comparing the responses to antibiotic challenge, bacteria grown in the respective medium displayed specific responses to the antibiotic challenge which were not seen in the other media. The common functions of genes that responded to the ciprofloxacin challenge were SOS response, DNA repair, DNA replication, fimbrial genes and bacteriophage initiation. A subset of the bacteriophage genes showed similar responses between the three models. From genes that were differentially regulated, responses observed in the serum model appeared to have the highest fold changes. In this study we established new models to investigate blood stream infections. They have been used to identify previously unknown differences in the molecular response to antibiotic treatment by the uropathogenic E. coli CFT073 depending on the media. These unique responses will help to unravel the complexity of bloodstream infection and can help to improve the antibiotic therapy that is used.

Project description:Treatment failures of antibiotic therapy are of major concern and can be caused by a misalignment of the antibiotic susceptibility determined in vitro with the behaviour of the pathogen in the patient. The aim of this study was to investigate the transcriptomic response of the uropathogenic strain E. coli CFT073 to antibiotic treatment in blood stream infection (BSI) models in order to understand and avoid antibiotic therapy failures in urosepsis treatments. Blood stream infection models were established by growing E. coli CFT073 in pooled human blood with and without ciprofloxacin. The antibiotic challenge was introduced at mid-logarithmic phase of growth of the organism to depict a clinical scenario. The responses were quantified by comparing to the responses at a given time point without the challenge. Global gene expression profiling of these conditions was examined using commercial DNA microarrays. The organism’s metabolic genes appeared to be regulated differently in each medium, this indicated that the bacterial growth regulation were different between the models. Bacterial growth in human serum mainly involved regulations of amino acid synthesis/utilisation such as glycine, arginine, thiamine, regulations of fimbrial proteins and bacteriophage genes. When comparing the responses to antibiotic challenge, bacteria grown in the respective medium displayed specific responses to the antibiotic challenge which were not seen in the other media. The common functions of genes that responded to the ciprofloxacin challenge were SOS response, DNA repair, DNA replication, fimbrial genes and bacteriophage initiation. A subset of the bacteriophage genes showed similar responses between the three models. From genes that were differentially regulated, responses observed in the serum model appeared to have the highest fold changes. In this study we established new models to investigate blood stream infections. They have been used to identify previously unknown differences in the molecular response to antibiotic treatment by the uropathogenic E. coli CFT073 depending on the media. These unique responses will help to unravel the complexity of bloodstream infection and can help to improve the antibiotic therapy that is used.

Project description:Treatment failures of antibiotic therapy are of major concern and can be caused by a misalignment of the antibiotic susceptibility determined in vitro with the behaviour of the pathogen in the patient. The aim of this study was to investigate the transcriptomic response of the uropathogenic strain E. coli CFT073 to antibiotic treatment in blood stream infection (BSI) models in order to understand and avoid antibiotic therapy failures in urosepsis treatments. Blood stream infection models were established by growing E. coli CFT073 in pooled human blood with and without ciprofloxacin. The antibiotic challenge was introduced at mid-logarithmic phase of growth of the organism to depict a clinical scenario. The responses were quantified by comparing to the responses at a given time point without the challenge. Global gene expression profiling of these conditions was examined using commercial DNA microarrays. The organismâ??s metabolic genes appeared to be regulated differently in each medium, this indicated that the bacterial growth regulation were different between the models. Bacterial growth in human serum mainly involved regulations of amino acid synthesis/utilisation such as glycine, arginine, thiamine, regulations of fimbrial proteins and bacteriophage genes. When comparing the responses to antibiotic challenge, bacteria grown in the respective medium displayed specific responses to the antibiotic challenge which were not seen in the other media. The common functions of genes that responded to the ciprofloxacin challenge were SOS response, DNA repair, DNA replication, fimbrial genes and bacteriophage initiation. A subset of the bacteriophage genes showed similar responses between the three models. From genes that were differentially regulated, responses observed in the serum model appeared to have the highest fold changes. In this study we established new models to investigate blood stream infections. They have been used to identify previously unknown differences in the molecular response to antibiotic treatment by the uropathogenic E. coli CFT073 depending on the media. These unique responses will help to unravel the complexity of bloodstream infection and can help to improve the antibiotic therapy that is used. A 10 array study using total RNA recovered from bacteria that were grown in human whole blood, with and without ciprofloxacin challenge. Arrays were performed in 5 biological replicates from each condition.

Project description:Treatment failures of antibiotic therapy are of major concern and can be caused by a misalignment of the antibiotic susceptibility determined in vitro with the behaviour of the pathogen in the patient. The aim of this study was to investigate the transcriptomic response of the uropathogenic strain E. coli CFT073 to antibiotic treatment in blood stream infection (BSI) models in order to understand and avoid antibiotic therapy failures in urosepsis treatments. Blood stream infection models were established by growing E. coli CFT073 in pooled human serum with and without ciprofloxacin and compared to Iso-sensitest medium. The antibiotic challenge was introduced at mid-logarithmic phase of growth of the organism to depict a clinical scenario . Global gene expression profiling of these conditions was examined using commercial DNA microarrays. The organismâs metabolic genes appeared to be regulated differently in each medium, this indicated that the bacterial growth regulation were different between the models. Bacterial growth in human serum mainly involved regulations of amino acid synthesis/utilisation such as glycine, arginine, thiamine, regulations of fimbrial proteins and bacteriophage genes. When comparing the responses to antibiotic challenge, bacteria grown in the respective medium displayed specific responses to the antibiotic challenge which were not seen in the other media. The common functions of genes that responded to the ciprofloxacin challenge were SOS response, DNA repair, DNA replication, fimbrial genes and bacteriophage initiation. A subset of the bacteriophage genes showed similar responses between the three models. From genes that were differentially regulated, responses observed in the serum model appeared to have the highest fold changes. In this study we established new models to investigate blood stream infections. They have been used to identify previously unknown differences in the molecular response to antibiotic treatment by the uropathogenic E. coli CFT073 depending on the media. These unique responses will help to unravel the complexity of bloodstream infection and can help to improve the antibiotic therapy that is used. A 20 array study using total RNA recovered from bacteria from bacteria that were either grown in human serum or Iso-Sensitest (IST) broth, with and without ciprofloxacin challenge. Arrays were performed in 5 biological replicates from each condition.Upon QC checks, certain biological repeats were excluded due to poor hybridisation results.

Project description:Kaiser2014 - Salmonella persistence after ciprofloxacin treatment The model describes the bacterial tolerance to antibiotics. Using a mouse model for Salmonella diarrhea, the authors have found that bacterial persistence occurs in the presence of the antibiotic ciprofloxacin because Salmonella can exist in two different states. One, the fast-growing population that spreads in the host's tissues and the other, slow-growing "persister" population that hide out inside dendritic cells of the host's immune system and cannot be attacked by the antibiotics. However, this can be killed by adding agents that directly stimulate the host's immune defense. This model is described in the article: Cecum lymph node dendritic cells harbor slow-growing bacteria phenotypically tolerant to antibiotic treatment. Kaiser P, Regoes RR, Dolowschiak T, Wotzka SY, Lengefeld J, Slack E, Grant AJ, Ackermann M, Hardt WD. PLoS Biol. 2014 Feb 18;12(2):e1001793. Abstract: In vivo, antibiotics are often much less efficient than ex vivo and relapses can occur. The reasons for poor in vivo activity are still not completely understood. We have studied the fluoroquinolone antibiotic ciprofloxacin in an animal model for complicated Salmonellosis. High-dose ciprofloxacin treatment efficiently reduced pathogen loads in feces and most organs. However, the cecum draining lymph node (cLN), the gut tissue, and the spleen retained surviving bacteria. In cLN, approximately 10%-20% of the bacteria remained viable. These phenotypically tolerant bacteria lodged mostly within CD103⁺CX₃CR1⁻CD11c⁺ dendritic cells, remained genetically susceptible to ciprofloxacin, were sufficient to reinitiate infection after the end of the therapy, and displayed an extremely slow growth rate, as shown by mathematical analysis of infections with mixed inocula and segregative plasmid experiments. The slow growth was sufficient to explain recalcitrance to antibiotics treatment. Therefore, slow-growing antibiotic-tolerant bacteria lodged within dendritic cells can explain poor in vivo antibiotic activity and relapse. Administration of LPS or CpG, known elicitors of innate immune defense, reduced the loads of tolerant bacteria. Thus, manipulating innate immunity may augment the in vivo activity of antibiotics. This model is hosted on BioModels Database and identified by: MODEL1312170001. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

			Action	DRS
	SRR30782618_1.fastq.gz	Fastqsanger.gz
	SRR30782618_2.fastq.gz	Fastqsanger.gz
	SRR30782619_1.fastq.gz	Fastqsanger.gz
	SRR30782619_2.fastq.gz	Fastqsanger.gz
	SRR30782620_1.fastq.gz	Fastqsanger.gz

Dataset Information

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets