Sublethal concentrations of antibiotics cause shift to anaerobic metabolism in Listeria monocytogenes and induce phenotypes linked to antibiotic tolerance
ABSTRACT: The human pathogenic bacterium Listeria monocytogenes was exposed to antibiotics both during clinical treatment and as a saprophyte. As one of the keys to successful treatment is continued antibiotic sensitivity, the purpose of this study was to determine if exposure to sublethal antibiotic concentrations would affect the bacterial physiology and potentially induce tolerance to antibiotics. Transcriptomic analyses demonstrated that each of four antibiotics caused a compound-specific gene expression pattern related to (the) mode-of-action of the particular antibiotic. All four antibiotics caused the same changes in expression of several metabolic genes indicating a shift from aerobic to anaerobic metabolism driven by the induction of lmo1634 and the repression of alsA and lmo1992. This shift in metabolism could be a survival strategy in response to antibiotics and is further supported by the observation that a Δlmo1634 mutant was more sensitive to bactericidal antibiotics. The monocin locus encoding a cryptic prophage was induced by co-trimoxazole and repressed by ampicillin and gentamicin. This expression pattern correlated with the observed antibiotic-dependent biofilm formation, indicating a role of monocin in antibiotic-induced biofilm formation and a ΔlmaDCBA mutant confirmed this correlation. Thus, sublethal concentrations of antibiotics caused metabolic and physiological changes indicating that the organism is preparing to withstand lethal concentrations of antibiotics. Investigation of mRNA and sRNA expression profiles of L. monocytogenes EGD cells exposed to sublethal concentrations of four different antibiotics i.e. ampicillin, tetracycline, gentamicin and co-trimoxazole for 3h.
Project description:The human pathogenic bacterium Listeria monocytogenes was exposed to antibiotics both during clinical treatment and as a saprophyte. As one of the keys to successful treatment is continued antibiotic sensitivity, the purpose of this study was to determine if exposure to sublethal antibiotic concentrations would affect the bacterial physiology and potentially induce tolerance to antibiotics. Transcriptomic analyses demonstrated that each of four antibiotics caused a compound-specific gene expression pattern related to (the) mode-of-action of the particular antibiotic. All four antibiotics caused the same changes in expression of several metabolic genes indicating a shift from aerobic to anaerobic metabolism driven by the induction of lmo1634 and the repression of alsA and lmo1992. This shift in metabolism could be a survival strategy in response to antibiotics and is further supported by the observation that a Δlmo1634 mutant was more sensitive to bactericidal antibiotics. The monocin locus encoding a cryptic prophage was induced by co-trimoxazole and repressed by ampicillin and gentamicin. This expression pattern correlated with the observed antibiotic-dependent biofilm formation, indicating a role of monocin in antibiotic-induced biofilm formation and a ΔlmaDCBA mutant confirmed this correlation. Thus, sublethal concentrations of antibiotics caused metabolic and physiological changes indicating that the organism is preparing to withstand lethal concentrations of antibiotics. Overall design: Investigation of mRNA and sRNA expression profiles of L. monocytogenes EGD cells exposed to sublethal concentrations of four different antibiotics i.e. ampicillin, tetracycline, gentamicin and co-trimoxazole for 3h.
Project description:We report the application of a high-throughput technique, RNA-seq, to study the transcriptomic response of P. putida DOT-T1E in the presence of antibiotics with different mechanisms of action with the aim to study in more detail the defense mechanisms that bacteria use to resist against toxic compounds. We find that P. putida DOT-T1E responde in a different way against each antimicrobial compound, what clearly shows that bacteria defense in different ways depending on the targets that compounds uses to attack. Our work is the first global transcriptomic analysis done in P. putida DOT-T1E in the presence of a considerable range of antibiotics. P. putida DOT-T1E mRNA profiles in the presence of control condition (LB) and 8 different antibiotics (ampicillin, chloramphenicol, kanamycin, ciprofloxacin, tetracycline, spectinomycin, gentamicin and rifampicin)
Project description:We studied the effects of three classes of antibiotics (amoxicillin, chlortetracycline and enrofloxacin ) on P. multocida transcriptome using custom oligonucleotide microarrays from Nimblegen systems. All the 2015 genes of Pm70 were spotted on the array and hybridizations were carried out with RNA isolated from three independent cultures of Pm70 grown in the presence or absence of sub-minimum inhibitory (sub-MIC) doses of antibiotics. Differentially expressed genes were identified by ANOVA and Dunnett’s test. Biological modeling of the differentially expressed genes (DE) was carried out based on Clusters of Orthologous (COG) groups and network analysis in Pathway Studio. Keywords: Response to sub-MIC antibiotics The experimental design included three biological replicate cultures of P. multocida grown in the absence or presence of sub-MIC antibiotics. Effects of antibiotics on the transcriptome with each antibiotic were determined by comparing the growth in the presence of antibiotic (treatment) to growth in the absence of antibiotic (control).
Project description:Treatment of bacteria with antibiotics at or close to the inhibitory concentration leads to specific transcriptional responses often affecting target genes and targets pathways. A dataset of transcriptional profiles (compendium) induced by antibiotics with known mode-of-action (MoA) can be used to gain information on the putative MoA of novel substances with unknown MoAs. We used a Pasteurella multocida microarray to generate a compendium of transcriptional profiles and to obtain information on the putative MoA of a novel antibiotic compound. We also show a strong impact of the bacteriostatic antibiotics on P. multocida virulence gene transcription. Keywords: antibiotica treatment, time course Midlog-grown cultures of P. multocida were treated for 10 or 30 min with 8 different antibiotics and one novel compound (thiazin) at minimal inhibitory concentrations (MICs) and were harvested. Control bacteria were not-treated and harvested at approximately the same optical density an OD578 of ~ 0.5. Total RNA was extracted from these samples and labelled with biotin. P. multocida whole genome transcriptional profiling was performed by hybridization on the custom-made Affymetrix microarray according to the manufacturer’s instructions. The experiments were done in triplicates.
Project description:Non-typeable Haemophilus influenzae (NTHi) is a common acute otitis media pathogen, with an incidence that is increased by previous antibiotic treatment. NTHi is also an emerging causative agent of other chronic infections in humans, some linked to morbidity, and all of which impose substantial treatment costs. In this study we explore the possibility that antibiotic exposure may stimulate biofilm formation by NTHi bacteria. We discovered that sub-inhibitory concentrations of beta-lactam antibiotic (i.e., amounts that partially inhibit bacterial growth) stimulated the biofilm-forming ability of NTHi strains, an effect that was strain and antibiotic dependent. When exposed to sub-inhibitory concentrations of beta-lactam antibiotics NTHi strains produced tightly packed biofilms with decreased numbers of culturable bacteria but increased biomass. The ratio of protein per unit weight of biofilm decreased as a result of antibiotic exposure. Antibiotic-stimulated biofilms had altered ultrastructure, and genes involved in glycogen production and transporter function were up regulated in response to antibiotic exposure. Down-regulated genes were linked to multiple metabolic processes but not those involved in stress response. Antibiotic-stimulated biofilm bacteria were more resistant to a lethal dose (10µg/mL) of cefuroxime. Our results suggest that beta-lactam antibiotic exposure may act as a signaling molecule that promotes transformation into the biofilm phenotype. Loss of viable bacteria, increase in biofilm biomass and decreased protein production coupled with a concomitant up-regulation of genes involved with glycogen production might result in a biofilm of sessile, metabolically inactive bacteria sustained by stored glycogen. These biofilms may protect surviving bacteria from subsequent antibiotic challenges, and act as a reservoir of viable bacteria once antibiotic exposure has ended. 12 samples
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
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:We purified Atoh1-GFP positive hair cells from organotypic cultures of P1 cochlea 3 hours after 0.5mM gentamicin treatment and performed RNA sequencing to profile the early transcriptional response of hair cells to aminoglycoside antibiotics. Levels of mRNA in gentamicin-treated hair cells (three replicates) were compared to untreated hair cells (three replicates). GFP negative, non-hair cells populations from treated organs were compared to those from untreated organs (three replicates for each condition).
Project description:Deeper understanding of antibiotic-induced physiological responses is critical to identifying means for enhancing our current antibiotic arsenal. Bactericidal antibiotics with diverse targets have been hypothesized to kill bacteria, in part, by inducing production of damaging reactive species. This notion has been supported by many groups, but recently challenged. Here we robustly test the hypothesis using biochemical, enzymatic and biophysical assays along with genetic and phenotypic experiments. We first used a novel intracellular hydrogen peroxide (H2O2) sensor, together with a chemically diverse panel of fluorescent dyes sensitive to an array of reactive species, to demonstrate that antibiotics broadly induce redox stress. Subsequent gene expression analyses reveal that complex antibiotic-induced oxidative stress responses are distinct from canonical responses generated by supra-physiological levels of H2O2. We next developed a method to dynamically quantify cellular respiration and found that bactericidal antibiotics elevate oxygen consumption, indicating significant alterations to bacterial redox physiology. We further show that catalase or DNA mismatch repair enzyme overexpression, as well as antioxidant pre-treatment limit antibiotic lethality, indicating that reactive oxygen species causatively contribute to antibiotic killing. Critically, the killing efficacy of antibiotics was diminished under strict anaerobic conditions, but could be enhanced by exposure to molecular oxygen or addition of alternative electron acceptors, suggesting that environmental factors play a role in killing cells physiologically primed for death. This work provides direct evidence that bactericidal antibiotics, downstream of their target-specific interactions, induce complex redox alterations that contribute to cellular damage and death, thus supporting an evolving, expanded model of antibiotic lethality. Here, we used microarrays to analyze oxidative stress responses to bactericidal antibiotic treatment in wildtype and mutant E coli WT or mutant E coli cells were grown to OD ~0.3. Untreated cells were harvested at time 0 as controls. Treated cells given the appropriate chemical perturbation and harvested 1 hour post-treatment. All experiments were performed in technical triplicate.
Project description:The multidrug resistance-encoding plasmids belonging to the IncA/C incompatibility group have recently emerged among Escherichia coli and Salmonella enterica in the United States. These plasmids have a unique genetic structure compared to other enterobacterial plasmid types, a broad host range, and propensity to acquire large numbers of antimicrobial resistance genes via their accessory regions. Using E. coli strain DH5α harboring the prototype IncA/C plasmid pAR060302, we sought to define the baseline transcriptome of IncA/C plasmids under laboratory growth and in the face of selective pressure. The effects of ampicillin, florfenicol or streptomycin exposure were compared to cells left untreated at logarithmic phase using Illumina sequencing (RNA-Seq). Under growth in Luria-Bertani broth lacking antibiotics, much of the backbone of pAR060302 was transcriptionally inactive, including its putative transfer regions. A few plasmid backbone genes of interest were highly transcribed, including genes of a putative toxin-antitoxin system and an H-NS-like transcriptional regulator. In contrast, numerous genes within the accessory regions of pAR060302 were highly transcribed, including the resistance genes floR, blaCMY-2, aadA, and aacA. Antibiotic treatment with ampicillin or streptomycin resulted in no genes being differentially expressed compared to controls lacking antibiotics, suggesting that many of the resistance-associated genes are not differentially expressed due to exposure to these antibiotics. In contrast, florfenicol treatment resulted in the up-regulation of floR and numerous chromosomally encoded genes. Overall, the transcriptome mapping of pAR060302 suggests that it mitigates the fitness costs of carrying resistance-associated genes through global regulation with its transcriptional regulators. Bacterial strains and growth conditions. E. coli strain DH5α harboring pAR060302 was grown in 10 mL DifcoTM Luria-Bertani (LB) broth aliquots at 37º C with shaking until an OD600 of 0.5. A total of 8 cultures were independently grown representing two biological replicates per condition tested. Six of the cultures were amended, 2 cultures per antibiotic, with ampicillin (50 µg/mL final concentration), florfenicol (30 µg/mL final concentration), or streptomycin (50 µg/mL final concentration) and allowed to incubate at 37º C with shaking for an additional 30 min. Two cultures were not amended with any antibiotic. Cells were pelleted and RNA was purified using a commercially available RNA extraction kit (Qiagen). RNA preparations were then subjected to a DNase treatment to eliminate DNA contamination from the sample (Qiagen). A treatment was also included to deplete ribosomal RNA using a commercially available kit (MicrobExpress, Ambion). The two biological replicates for each growth condition were pooled for sequencing. Ilumina sequencing for transcriptome mapping. cDNA libraries were generated with an insert size of 100 bp and sequenced with 76-base cycles of single-end reads using a Genome Analyzer II (Illumina) platform according to manufacturer’s protocols at the Biomedical Genomics Center (University of Minnesota, Minneapolis, Minnesota, USA). Approximately 160,000 plasmid-mapped reads each were obtained for the ampicillin and streptomycin treated samples, and 260,000 plasmid-mapped reads each for the control and florfenicol treatment samples. Genome-mapped read counts were as follows: control, ~6.4 million reads, florfenicol treatment, ~5.7 million reads, ampicillin treatment, ~1.7 million reads, and streptomycin treatment, ~5.2 million reads. We only used those reads uniquely mapped on plasmid or chromosomal DNA for global normalization and further analysis. RNAseq data analysis. cDNA reads were trimmed so that the quality at each base position was above 30 (~15-20 bp) and then mapped either to the E. coli K-12 MG1655 published genome sequence (Genbank accession no. NC_000913) or to the pAR060302 published sequence (Genbank accession no. NC_092692) using BOWTIE. The E. coli strain DH5α has an incomplete annotation and for this reason the E. coli K-12 annotation was used, representing an estimation of differentially expressed genes due to exposure of antimicrobials. The reads mapped per kilobase of gene per million (RPKM) reads was calculated using either the E. coli chromosome or the pAR060302 annotation and was used for global normalization. The per kilobase cDNA length normalized the effect of different length of cDNAs such that the sequence reads have a equal chance to map on the long cDNA regions and the short cDNA regions. After RPKM normalization, each sample is comparable to each other. An R package, DEGseq, was used to identify differentially expressed genes between the control and each antibiotic treatment condition. A cutoff of q-value < 0.05 and a fold change of > 3 were used to measure statistical significance.
Project description:Background: Penicillins inhibit cell wall synthesis; therefore, H. pylori must be dividing for these antibiotics to be effective. Identifying growth responses to varying medium pH may allow design of more effective treatment regimens. Aim: To determine the effect of acidity on bacterial growth and the bactericidal efficacy of ampicillin. Methods: H. pylori were incubated in dialysis chambers suspended in 1.5L of media at various pHs with 5mM urea, with or without ampicillin, for 4, 8 or 16 hours, thus mimicking unbuffered gastric juice. Changes in gene expression, viability and survival were determined. The bacterial load of H. pylori infected gerbils was determined with and without profound acid inhibition. Results: At pH 3.0, but not at pH 4.5 or 7.4, there was decreased expression of ~400 genes, including many cell envelope biosynthesis, cell division genes and penicillin-binding proteins. In the presence of ampicillin, viability and survival declined at pH 4.5 and 7.4 but not at pH 3.0. Profound acid inhibition of H. pylori infected gerbils increased the antral bacterial load >3 fold, showing that elevation of intragastric pH stimulated growth. Conclusions: Ampicillin is bactericidal at pH 4.5 and 7.4, but not at pH 3.0, due to decreased expression of cell envelope and division genes at pH 3.0. Therefore, at pH 3.0, the pH at the gastric surface, the bacteria are non-dividing and persist with ampicillin treatment. A more effective inhibitor of acid secretion that maintains gastric pH near neutrality for 24 hours/day should enhance the efficacy of triple therapy and of amoxicillin, even allowing dual therapy for H. pylori eradication. There were a total of three biological replicates, each containing one control (incubated at pH 7.4) and one acidic (pH 3.0) sample, whose RNA were extracted on different dates. Microarray studies performed on these six samples were done in triplicate. One of the triplicates for two of the biological control triplicates were removed from the data set due to poor hybridization