RNA profiles reveal signatures of future health and disease in pregnancy.

Maternal morbidity and mortality continue to rise, and pre-eclampsia is a major driver of this burden1. Yet the ability to assess underlying pathophysiology before clinical presentation to enable identification of pregnancies at risk remains elusive. Here we demonstrate the ability of plasma cell-free RNA (cfRNA) to reveal patterns of normal pregnancy progression and determine the risk of developing pre-eclampsia months before clinical presentation. Our results centre on comprehensive transcriptome data from eight independent prospectively collected cohorts comprising 1,840 racially diverse pregnancies and retrospective analysis of 2,539 banked plasma samples. The pre-eclampsia data include 524 samples (72 cases and 452 non-cases) from two diverse independent cohorts collected 14.5 weeks (s.d., 4.5 weeks) before delivery. We show that cfRNA signatures from a single blood draw can track pregnancy progression at the placental, maternal and fetal levels and can robustly predict pre-eclampsia, with a sensitivity of 75% and a positive predictive value of 32.3% (s.d., 3%), which is superior to the state-of-the-art method2. cfRNA signatures of normal pregnancy progression and pre-eclampsia are independent of clinical factors, such as maternal age, body mass index and race, which cumulatively account for less than 1% of model variance. Further, the cfRNA signature for pre-eclampsia contains gene features linked to biological processes implicated in the underlying pathophysiology of pre-eclampsia.

Impact of early preeclampsia prediction on medication adherence and behavior change: a survey of pregnant and recently-delivered individuals.

BACKGROUND: Behavior change and medication adherence represent potential barriers to optimal prevention of pregnancy complications including preeclampsia. We sought to evaluate baseline sentiments on pregnancy care and medication amenability, and how these measures would be impacted by early predictive testing for preeclampsia. METHODS: We developed a digital survey to query participants' baseline sentiments on pregnancy care, knowledge about pregnancy complications, and views on a hypothetical test to predict preeclampsia. The survey was administered online to pregnant and recently-delivered individuals in the United States. Survey data were analyzed using pooled two-sample proportion z-tests with adjustment for multiple comparisons. RESULTS: One thousand and twenty-two people completed the survey. 84% reported they were satisfied with their pregnancy care. Self-assessed knowledge about preeclampsia was high, with 75% of respondents reporting they have a "good understanding" of preeclampsia, but measured knowledge was low, with only 10% able to identify five common signs/symptoms of preeclampsia. Notably, 40% of participants with prior preeclampsia believed they were at average or below-average risk for recurrence. 91% of participants desired early pregnancy predictive testing for preeclampsia. If found to be at high risk for preeclampsia, 88% reported they would be more motivated to follow their provider's medication recommendations and 94% reported they would desire home blood pressure monitoring. Increased motivation to follow clinicians' medication and monitoring recommendations was observed across the full spectrum of medication amenability. Individuals who are more medication-hesitant still reported high rates of motivation to change behavior and adhere to medication recommendations if predictive testing showed a high risk of preeclampsia. Importantly, a high proportion of medication-hesitant individuals reported that if a predictive test demonstrated they were at high risk of preeclampsia, they would feel more motivated to take medications (83.0%) and aspirin (75.9%) if recommended. CONCLUSION: While satisfaction with care is high, participants desire more information about their pregnancy health, would value predictive testing for preeclampsia, and report they would act on this information. Improved detection of at-risk individuals through objective testing combined with increased adherence to their recommended care plan may be an important step to remedy the growing gap in prevention.

Pathway size matters: the influence of pathway granularity on over-representation (enrichment analysis) statistics.

BACKGROUND: Enrichment or over-representation analysis is a common method used in bioinformatics studies of transcriptomics, metabolomics, and microbiome datasets. The key idea behind enrichment analysis is: given a set of significantly expressed genes (or metabolites), use that set to infer a smaller set of perturbed biological pathways or processes, in which those genes (or metabolites) play a role. Enrichment computations rely on collections of defined biological pathways and/or processes, which are usually drawn from pathway databases. Although practitioners of enrichment analysis take great care to employ statistical corrections (e.g., for multiple testing), they appear unaware that enrichment results are quite sensitive to the pathway definitions that the calculation uses. RESULTS: We show that alternative pathway definitions can alter enrichment p-values by up to nine orders of magnitude, whereas statistical corrections typically alter enrichment p-values by only two orders of magnitude. We present multiple examples where the smaller pathway definitions used in the EcoCyc database produces stronger enrichment p-values than the much larger pathway definitions used in the KEGG database; we demonstrate that to attain a given enrichment p-value, KEGG-based enrichment analyses require 1.3-2.0 times as many significantly expressed genes as does EcoCyc-based enrichment analyses. The large pathways in KEGG are problematic for another reason: they blur together multiple (as many as 21) biological processes. When such a KEGG pathway receives a high enrichment p-value, which of its component processes is perturbed is unclear, and thus the biological conclusions drawn from enrichment of large pathways are also in question. CONCLUSIONS: The choice of pathway database used in enrichment analyses can have a much stronger effect on the enrichment results than the statistical corrections used in these analyses.

Identification and Characterization of Pleiotropic High-Persistence Mutations in the Beta Subunit of the Bacterial RNA Polymerase.

Mutations conferring resistance to bactericidal antibiotics reduce the average susceptibility of mutant populations. It is unknown, however, how those mutations affect the survival of individual bacteria. Since surviving bacteria can be a reservoir for recurring infections, it is important to know how survival rates may be affected by resistance mutations and by the choice of antibiotics. Here, we present evidence that (i) Escherichia coli mutants with 100 to 1,000 times increased frequency of survival in ciprofloxacin, an archetypal fluoroquinolone antibiotic, can be readily obtained in a stepwise selection; (ii) the high survival frequency is conferred by mutations in the switch region of the beta subunit of the RNA polymerase; (iii) the switch-region mutations are (p)ppGpp mimics, partially analogous to rpoB stringent mutations; (iv) the stringent and switch region rpoB mutations frequently occur in clinical isolates of E. coli, Acinetobacter baumannii, Mycobacterium tuberculosis, and Staphylococcus aureus, and at least one of them, RpoB S488L, which is a common rifampicin resistance mutations, dramatically increases the survival of a clinical methicillin-resistant S. aureus (MRSA) strain in ampicillin; and (v) the RpoB-associated high-survival phenotype can be reversed by subinhibitory concentrations of chloramphenicol.

Thymineless Death Lives On: New Insights into a Classic Phenomenon.

The primary mechanisms by which bacteria lose viability when deprived of thymine have been elusive for over half a century. Early research focused on stalled replication forks and the deleterious effects of uracil incorporation into DNA from thymidine-deficient nucleotide pools. The initiation of the replication cycle and origin-proximal DNA degradation during thymine starvation have now been quantified via whole-genome microarrays and other approaches. These advances have fostered innovative models and informative experiments in bacteria since this topic was last reviewed. Given that thymineless death is similar in mammalian cells and that certain antibacterial and chemotherapeutic drugs elicit thymine deficiency, a mechanistic understanding of this phenomenon might have valuable biomedical applications.

De Novo Characterization of Genes That Contribute to High-Level Ciprofloxacin Resistance in Escherichia coli.

Sensitization of resistant bacteria to existing antibiotics depends on the identification of candidate targets whose activities contribute to resistance. Using a transposon insertion library in an Escherichia coli mutant that was 2,000 times less susceptible to ciprofloxacin than its parent and the relative fitness scores, we identified 19 genes that contributed to the acquired ciprofloxacin resistance and mapped the shortest genetic path that increased the antibiotic susceptibility of the resistant bacteria back to a near wild-type level.

An evolutionarily biased distribution of miRNA sites toward regulatory genes with high promoter-driven intrinsic transcriptional noise.

BACKGROUND: miRNAs are a major class of regulators of gene expression in metazoans. By targeting cognate mRNAs, miRNAs are involved in regulating most, if not all, biological processes in different cell and tissue types. To better understand how this regulatory potential is allocated among different target gene sets, we carried out a detailed and systematic analysis of miRNA target sites distribution in the mouse genome. RESULTS: We used predicted conserved and non-conserved sites for 779 miRNAs in 3' UTR of 18440 genes downloaded from TargetScan website. Our analysis reveals that 3' UTRs of genes encoding regulatory proteins harbor significantly greater number of miRNA sites than those of non-regulatory, housekeeping and structural, genes. Analysis of miRNA sites for orthologous 3'UTR's in 10 other species indicates that the regulatory genes were maintaining or accruing miRNA sites while non-regulatory genes gradually shed them in the course of evolution. Furthermore, we observed that 3' UTR of genes with higher gene expression variability driven by their promoter sequence content are targeted by many more distinct miRNAs compared to genes with low transcriptional noise. CONCLUSIONS: Based on our results we envision a model, which we dubbed "selective inclusion", whereby non-regulatory genes with low transcription noise and stable expression profile lost their sites, while regulatory genes which endure higher transcription noise retained and gained new sites. This adaptation is consistent with the requirements that regulatory genes need to be tightly controlled in order to have precise and optimum protein level to properly function.

The association of DNA damage response and nucleotide level modulation with the antibacterial mechanism of the anti-folate drug trimethoprim.

BACKGROUND: Trimethoprim is a widely prescribed antibiotic for a variety of bacterial infections. It belongs to a class of anti-metabolites - antifolates - which includes drugs used against malarial parasites and in cancer therapy. However, spread of bacterial resistance to the drug has severely hampered its clinical use and has necessitated further investigations into its mechanism of action and treatment regimen. Trimethoprim selectively starves bacterial cells for tetrahydrofolate, a vital cofactor necessary for the synthesis of several metabolites. The outcome (bacteriostatic or bactericidal) of such starvation, however, depends on the availability of folate-dependent metabolites in the growth medium. To characterize this dependency, we investigated in detail the regulatory and structural components of Escherichia coli cellular response to trimethoprim in controlled growth and supplementation conditions. RESULTS: We surveyed transcriptional responses to trimethoprim treatment during bacteriostatic and bactericidal conditions and analyzed associated gene sets/pathways. Concurrent starvation of all folate dependent metabolites caused growth arrest, and this was accompanied by induction of general stress and stringent responses. Three gene sets were significantly associated with the bactericidal effect of TMP in different media including LB: genes of the SOS regulon, genes of the pyrimidine nucleotide biosynthetic pathway and members of the multiple antibiotic resistance (mar) regulon controlled by the MarR repressor. However, the SOS response was identified as the only universal transcriptional signature associated with the loss of viability by direct thymine starvation or by folate stress. We also used genome-wide gene knock-out screen to uncover means of sensitization of bacteria to the drug. We observed that among a number of candidate genes and pathways, the effect of knock-outs in the deoxyribose nucleotide salvage pathway, encoded by the deoCABD operon and under the control of the DeoR repressor, was most informative. CONCLUSION: Transcriptional induction of DNA damage response is an essential feature of the bactericidal effect of trimethoprim. Either the observation of the transcriptional response or DNA damage itself, or both, is made possible by thymine starvation when other folate-dependent metabolites are not limited. The effect of DNA damage by the drug takes place prior to its bactericidal effect, at the beginning of the lag stage of the treatment. Mutations in the deoxyribose nucleotide salvage pathway can affect duration of the lag as well as the rate of killing. This information can be used to postulate certain mechanistic differences between direct thymine starvation in thymidylate synthase deficient mutants and thymine starvation by anti-folate inhibitors.

Thymineless death is associated with loss of essential genetic information from the replication origin.

Thymine starvation results in a terminal cellular condition known as thymineless death (TLD), which is the basis of action for several common antibiotics and anticancer drugs. We characterized the onset and progression of TLD in Escherichia coli and found that DNA damage is the only salient property that distinguishes cells irreversibly senesced under thymine starvation from cells reversibly arrested by the nucleotide limitation. The damage is manifested as the relative loss of genetic material spreading outward from the replication origin: the extent of TLD correlates with the progression of damage. The reduced lethality in mutants deficient in the RecFOR/JQ repair pathway also correlates with the extent of damage, which explains most of the observed variance in cell killing. We propose that such spatially localized and persistent DNA damage is the consequence of transcription-dependent initiation of replication in the thymine-starved cells and may be the underlying cause of TLD.

A Bayesian approach to joint modeling of protein-DNA binding, gene expression and sequence data.

The genome-wide DNA-protein-binding data, DNA sequence data and gene expression data represent complementary means to deciphering global and local transcriptional regulatory circuits. Combining these different types of data can not only improve the statistical power, but also provide a more comprehensive picture of gene regulation. In this paper, we propose a novel statistical model to augment protein-DNA-binding data with gene expression and DNA sequence data when available. We specify a hierarchical Bayes model and use Markov chain Monte Carlo simulations to draw inferences. Both simulation studies and an analysis of an experimental data set show that the proposed joint modeling method can significantly improve the specificity and sensitivity of identifying target genes as compared with conventional approaches relying on a single data source.

In vivo and in vitro patterns of the activity of simocyclinone D8, an angucyclinone antibiotic from Streptomyces antibioticus.

Simocyclinone D8 (SD8) exhibits antibiotic activity against gram-positive bacteria but not against gram-negative bacteria. The molecular basis of the cytotoxicity of SD8 is not fully understood, although SD8 has been shown to inhibit the supercoiling activity of Escherichia coli gyrase. To understand the mechanism of SD8, we have employed biochemical assays to directly measure the sensitivities of E. coli and Staphylococcus aureus type II topoisomerases to SD8 and microarray analysis to monitor the cellular responses to SD8 treatment. SD8 is a potent inhibitor of either E. coli or S. aureus gyrase. In contrast, SD8 exhibits only a moderate inhibitory effect on S. aureus topoisomerase IV, and E. coli topoisomerase IV is virtually insensitive to SD8. The antimicrobial effect of SD8 against E. coli has become evident in the absence of the AcrB multidrug efflux pump. As expected, SD8 treatment exhibits the signature responses to the loss of supercoiling activity in E. coli: upregulation of gyrase genes and downregulation of the topoisomerase I gene. Unlike quinolone treatment, however, SD8 treatment does not induce the SOS response. These results suggest that DNA gyrase is the target of SD8 in both gram-positive and gram-negative bacteria and that the lack of the antibacterial effect against gram-negative bacteria is due, in part, to the activity of the AcrB efflux pump.

Improved detection of differentially expressed genes through incorporation of gene locations.

In determining differential expression in cDNA microarray experiments, the expression level of an individual gene is usually assumed to be independent of the expression levels of other genes, but many recent studies have shown that a gene's expression level tends to be similar to that of its neighbors on a chromosome, and differentially expressed (DE) genes are likely to form clusters of similar transcriptional activity along the chromosome. When modeled as a one-dimensional spatial series, the expression level of genes on the same chromosome frequently exhibit significant spatial correlation, reflecting spatial patterns in transcription. By modeling these spatial correlations, we can obtain improved estimates of transcript levels. Here, we demonstrate the existence of spatial correlations in transcriptional activity in the Escherichia coli (E. coli) chromosome across more than 50 experimental conditions. Based on this finding, we propose a hierarchical Bayesian model that borrows information from neighboring genes to improve the estimation of the expression level of a given gene and hence the detection of DE genes. Furthermore, we extend the model to account for the circular structure of E. coli chromosome and the intergenetic distance between gene neighbors. The simulation studies and analysis of real data examples in E. coli and yeast Saccharomyces cerevisiae show that the proposed method outperforms the commonly used significant analysis of microarray (SAM) t-statistic in detecting DE genes.

RecA can stimulate the relaxation activity of topoisomerase I: Molecular basis of topoisomerase-mediated genome-wide transcriptional responses in Escherichia coli.

The superhelicity of the chromosome, which is controlled by DNA topoisomerases, modulates global gene expression. Investigations of transcriptional responses to the modulation of gyrase function have identified two types of topoisomerase-mediated transcriptional responses: (i) steady-state changes elicited by a mutation in gyrase, such as the D82G mutation in GyrA, and (ii) dynamic changes elicited by the inhibition of gyrase. We hypothesize that the steady-state effects are due to the changes in biochemical properties of gyrase, whereas the dynamic effects are due to an imbalance between supercoiling and relaxation activities, which appears to be influenced by the RecA activity. Herein, we present biochemical evidence for hypothesized mechanisms. GyrA D82G gyrase exhibits a reduced supercoiling activity. The RecA protein can influence the balance between supercoiling and relaxation activities either by interfering with the activity of DNA gyrase or by facilitating the relaxation reaction. RecA has no effect on the supercoiling activity of gyrase but stimulates the relaxation activity of topoisomerase I. This stimulation is specific and requires formation of an active RecA filament. These results suggest that the functional interaction between RecA and topoisomerase I is responsible for RecA-mediated modulation of the relaxation-dependent transcriptional activity of the Escherichia coli chromosome.

Analysis of pleiotropic transcriptional profiles: a case study of DNA gyrase inhibition.

Genetic and environmental perturbations often result in complex transcriptional responses involving multiple genes and regulons. In order to understand the nature of a response, one has to account for the contribution of the downstream effects to the formation of a response. Such analysis can be carried out within a statistical framework in which the individual effects are independently collected and then combined within a linear model. Here, we modeled the contribution of DNA replication, supercoiling, and repair to the transcriptional response of inhibition of the Escherichia coli gyrase. By representing the gyrase inhibition as a true pleiotropic phenomenon, we were able to demonstrate that: (1) DNA replication is required for the formation of spatial transcriptional domains; (2) the transcriptional response to the gyrase inhibition is coordinated between at least two modules involved in DNA maintenance, relaxation and damage response; (3) the genes whose transcriptional response to the gyrase inhibition does not depend on the main relaxation activity of the cell can be classified on the basis of a GC excess in their upstream and coding sequences; and (4) relaxation by topoisomerase I dominates the transcriptional response, followed by the effects of replication and RecA. We functionally tested the effect of the interaction between relaxation and repair activities, and found support for the model derived from the microarray data. We conclude that modeling compound transcriptional profiles as a combination of downstream transcriptional effects allows for a more realistic, accurate, and meaningful representation of the transcriptional activity of a genome.

Analysis of mutational patterns in quinolone resistance-determining regions of GyrA and ParC of clinical isolates.

Fluoroquinolone (FQ)-resistant bacteria pose a major global health threat. Unanalysed genomic data from thousands of sequenced microbes likely contain important hints regarding the evolution of FQ resistance, yet this information lies fallow. Here we analysed the co-occurrence patterns of quinolone resistance mutations in genes encoding the FQ drug targets DNA gyrase (gyrase) and topoisomerase IV (topo-IV) from 36,402 bacterial genomes, representing 10 Gram-positive and 10 Gram-negative species. For 19 species, the likeliest routes toward resistance mutations in both targets were determined, and for 5 species those mutations necessary and sufficient to predict FQ resistance were also determined. Target mutation hierarchy was fixed in all examined Gram-negative species, with gyrase being the primary and topo-IV the secondary quinolone target, as well as in six of nine Gram-positive species, with topo-IV being the primary and gyrase the secondary target. By contrast, in three Gram-positive species (Staphylococcus haemolyticus, Streptococcus pneumoniae and Streptococcus suis), under some conditions gyrase became the primary and topo-IV the secondary target. The path through individual resistance mutations varied by species. Both linear and branched paths were identified in Gram-positive and Gram-negative organisms alike. Finally, FQ resistance could be predicted based solely on target gene quinolone resistance mutations for Acinetobacter baumannii, Escherichia coli and Staphylococcus aureus, but not Klebsiella pneumoniae or Pseudomonas aeruginosa. These findings have important implications both for sequence-based diagnostics and for understanding the emergence of FQ resistance.

Gene expression patterns of sulfur starvation in Synechocystis sp. PCC 6803.

BACKGROUND: The unicellular cyanobacterium Synechocystis sp. PCC 6803 is a model microbe for studying biochemistry, genetics and molecular biology of photobiological processes. Importance of this bacterium in basic and applied research calls for a systematic, genome-wide description of its transcriptional regulatory capacity. Characteristic transcriptional responses to changes in the growth environment are expected to provide a scaffold for describing the Synechocystis transcriptional regulatory network as well as efficient means for functional annotation of genes in the genome. RESULTS: We designed, validated and used Synechocystis genome-wide oligonucleotide (70-mer) microarray (representing 96.7% of all chromosomal ORFs annotated at the time of the beginning of this project) to study transcriptional activity of the cyanobacterial genome in response to sulfur (S) starvation. The microarray data were verified by quantitative RT-PCR. We made five main observations: 1) Transcriptional changes upon sulfate starvation were relatively moderate, but significant and consistent with growth kinetics; 2) S acquisition genes encoding for a high-affinity sulfate transporter were significantly induced, while decreased transcription of genes for phycobilisome, photosystems I and II, cytochrome b6/f, and ATP synthase indicated reduced light-harvesting and photosynthetic activity; 3) S starvation elicited transcriptional responses associated with general growth arrest and stress; 4) A large number of genes regulated by S availability encode hypothetical proteins or proteins of unknown function; 5) Hydrogenase structural and maturation accessory genes were not identified as differentially expressed, even though increased hydrogen evolution was observed. CONCLUSION: The expression profiles recorded by using this oligonucleotide-based microarray platform revealed that during transition from the condition of plentiful S to S starvation, Synechocystis undergoes coordinated transcriptional changes, including changes in gene expression whose products are involved in sensing nutrient limitations and tuning bacterial metabolism. The transcriptional profile of the nutrient starvation was dominated by a decrease in abundances of many transcripts. However, these changes were unlikely due to the across-the-board, non-specific shut down of transcription in a condition of growth arrest. Down-regulation of transcripts encoding proteins whose function depends on a cellular S status indicated that the observed repression has a specific regulatory component. The repression of certain S-related genes was paralleled by activation of genes involved in internal and external S scavenging.

Limited functional conservation of a global regulator among related bacterial genera: Lrp in Escherichia, Proteus and Vibrio.

BACKGROUND: Bacterial genome sequences are being determined rapidly, but few species are physiologically well characterized. Predicting regulation from genome sequences usually involves extrapolation from better-studied bacteria, using the hypothesis that a conserved regulator, conserved target gene, and predicted regulator-binding site in the target promoter imply conserved regulation between the two species. However many compared organisms are ecologically and physiologically diverse, and the limits of extrapolation have not been well tested. In E. coli K-12 the leucine-responsive regulatory protein (Lrp) affects expression of approximately 400 genes. Proteus mirabilis and Vibrio cholerae have highly-conserved lrp orthologs (98% and 92% identity to E. coli lrp). The functional equivalence of Lrp from these related species was assessed. RESULTS: Heterologous Lrp regulated gltB, livK and lrp transcriptional fusions in an E. coli background in the same general way as the native Lrp, though with significant differences in extent. Microarray analysis of these strains revealed that the heterologous Lrp proteins significantly influence only about half of the genes affected by native Lrp. In P. mirabilis, heterologous Lrp restored swarming, though with some pattern differences. P. mirabilis produced substantially more Lrp than E. coli or V. cholerae under some conditions. Lrp regulation of target gene orthologs differed among the three native hosts. Strikingly, while Lrp negatively regulates its own gene in E. coli, and was shown to do so even more strongly in P. mirabilis, Lrp appears to activate its own gene in V. cholerae. CONCLUSION: The overall similarity of regulatory effects of the Lrp orthologs supports the use of extrapolation between related strains for general purposes. However this study also revealed intrinsic differences even between orthologous regulators sharing >90% overall identity, and 100% identity for the DNA-binding helix-turn-helix motif, as well as differences in the amounts of those regulators. These results suggest that predicting regulation of specific target genes based on genome sequence comparisons alone should be done on a conservative basis.

Life after transcription--revisiting the fate of messenger RNA.

Recently, several groups have used high-density DNA microarrays to study mRNA turnover. These new data suggest that decay contributes significantly to determining mRNA levels, and they should prompt us to refocus our attention on the regulatory potential of mRNA decay.

Operon information improves gene expression estimation for cDNA microarrays.

BACKGROUND: In prokaryotic genomes, genes are organized in operons, and the genes within an operon tend to have similar levels of expression. Because of co-transcription of genes within an operon, borrowing information from other genes within the same operon can improve the estimation of relative transcript levels; the estimation of relative levels of transcript abundances is one of the most challenging tasks in experimental genomics due to the high noise level in microarray data. Therefore, techniques that can improve such estimations, and moreover are based on sound biological premises, are expected to benefit the field of microarray data analysis RESULTS: In this paper, we propose a hierarchical Bayesian model, which relies on borrowing information from other genes within the same operon, to improve the estimation of gene expression levels and, hence, the detection of differentially expressed genes. The simulation studies and the analysis of experiential data demonstrated that the proposed method outperformed other techniques that are routinely used to estimate transcript levels and detect differentially expressed genes, including the sample mean and SAM t statistics. The improvement became more significant as the noise level in microarray data increases. CONCLUSION: By borrowing information about transcriptional activity of genes within classified operons, we improved the estimation of gene expression levels and the detection of differentially expressed genes.

Persisters: a distinct physiological state of E. coli.

BACKGROUND: Bacterial populations contain persisters, phenotypic variants that constitute approximately 1% of cells in stationary phase and biofilm cultures. Multidrug tolerance of persisters is largely responsible for the inability of antibiotics to completely eradicate infections. Recent progress in understanding persisters is encouraging, but the main obstacle in understanding their nature was our inability to isolate these elusive cells from a wild-type population since their discovery in 1944. RESULTS: We hypothesized that persisters are dormant cells with a low level of translation, and used this to physically sort dim E. coli cells which do not contain sufficient amounts of unstable GFP expressed from a promoter whose activity depends on the growth rate. The dim cells were tolerant to antibiotics and exhibited a gene expression profile distinctly different from those observed for cells in exponential or stationary phases. Genes coding for toxin-antitoxin module proteins were expressed in persisters and are likely contributors to this condition. CONCLUSION: We report a method for persister isolation and conclude that these cells represent a distinct state of bacterial physiology.