Joanna Bacon

Quantification of global transcription patterns in prokaryotes using spotted microarrays

We describe an analysis, applicable to any spotted microarray dataset produced using genomic DNA as a reference, that quantifies prokaryotic levels of mRNA on a genome-wide scale. Applying this to Mycobacterium tuberculosis, we validate the technique, show a correlation between level of expression and biological importance, define the complement of invariant genes and analyze absolute levels of expression by functional class to develop ways of understanding an organisms biology without comparison to another growth condition.

Non-Replicating Mycobacterium tuberculosis Elicits a Reduced Infectivity Profile with Corresponding Modifications to the Cell Wall and Extracellular Matrix

A key feature of Mycobacterium tuberculosis is its ability to become dormant in the host. Little is known of the mechanisms by which these bacilli are able to persist in this state. Therefore, the focus of this study was to emulate environmental conditions encountered by M. tuberculosis in the granuloma, and determine the effect of such conditions on the physiology and infectivity of the organism. Non-replicating persistent (NRP) M. tuberculosis was established by the gradual depletion of nutrients in an oxygen-replete and controlled environment. In contrast to rapidly dividing bacilli, NRP bacteria exhibited a distinct phenotype by accumulating an extracellular matrix rich in free mycolate and lipoglycans, with increased arabinosylation. Microarray studies demonstrated a substantial down-regulation of genes involved in energy metabolism in NRP bacteria. Despite this reduction in metabolic activity, cells were still able to infect guinea pigs, but with a delay in the development of disease when compared to exponential phase bacilli. Using these approaches to investigate the interplay between the changing environment of the host and altered physiology of NRP bacteria, this study sheds new light on the conditions that are pertinent to M. tuberculosis dormancy and how this organism could be establishing latent disease.

Enhanced heterogeneity of rpoB in Mycobacterium tuberculosis found at low pH

OBJECTIVES The aim of this study was to gain an insight into the molecular mechanisms of the evolution of rifampicin resistance in response to controlled changes in the environment. METHODS We determined the proportion of rpoB mutants in the chemostat culture and characterized the sequence of mutations found in the rifampicin resistance-determining region of rpoB in a steady-state chemostat at pH 7.0 and 6.2. RESULTS The overall proportion of rpoB mutants of strain H37Rv remained constant for 37 days at pH 7.0, ranging between 3.6 x 10(-8) and 8.9 x 10(-8); however, the spectrum of mutations varied. The most commonly detected mutation, serine to leucine mutation at codon 531 (S531L), increased from 40% to 89%, while other mutations (S531W, H526Y, H526D, H526R, S522L and D516V) decreased over the 37 day sampling period. Changing the pH from 7.0 to 6.2 did not significantly alter the overall proportion of mutants, but resulted in a decrease in the percentage of strains harbouring S531L (from 89% to 50%) accompanied by an increase in the range of different mutations from 4 to 12. CONCLUSIONS The data confirm that the fitness of strains with the S531L mutation is greater than that of strains containing other mutations. We also conclude that at low pH the environment is permissive for a wider spectrum of mutations, which may provide opportunities for a successful mutant to survive.

Mycobacterium tuberculosis Is Resistant to Isoniazid at a Slow Growth Rate by Single Nucleotide Polymorphisms in katG Codon Ser315

An important aim for improving TB treatment is to shorten the period of antibiotic therapy without increasing relapse rates or encouraging the development of antibiotic-resistant strains. In any M. tuberculosis population there is a proportion of bacteria that are drug-tolerant; this might be because of pre-existing populations of slow growing/non replicating bacteria that are protected from antibiotic action due to the expression of a phenotype that limits drug activity. We addressed this question by observing populations of either slow growing (constant 69.3h mean generation time) or fast growing bacilli (constant 23.1h mean generation time) in their response to the effects of isoniazid exposure, using controlled and defined growth in chemostats. Phenotypic differences were detected between the populations at the two growth rates including expression of efflux mechanisms and the involvement of antisense RNA/small RNA in the regulation of a drug-tolerant phenotype, which has not been explored previously for M. tuberculosis. Genotypic analyses showed that slow growing bacilli develop resistance to isoniazid through mutations specifically in katG codon Ser315 which are present in approximately 50–90% of all isoniazid-resistant clinical isolates. The fast growing bacilli persisted as a mixed population with katG mutations distributed throughout the gene. Mutations in katG codon Ser315 appear to have a fitness cost in vitro and particularly in fast growing cultures. Our results suggest a requirement for functional katG-encoded catalase-peroxide in the slow growers but not the fast-growing bacteria, which may explain why katG codon Ser315 mutations are favoured in the slow growing cultures.

Transcriptional Responses of Mycobacterium tuberculosis Exposed to Adverse Conditions In Vitro

Mycobacterium tuberculosis encounters a range of stimuli in the host. Understanding the environmental cues that initiate the transcriptional response of M. tuberculosis, which enable the bacterium to replicate and/or survive in the host, will provide markers that are specific to different stages of disease, further refining the search for improved treatments and vaccines. Studying M. tuberculosis gene expression in vivo is technically challenging and more amenable in vitro experiments are being used to aid interpretation and to dissect the signals that are responsible for controlling subsets of genes. Key parameters that affect the growth of a pathogen in the host include nutrient status, environmental pH, oxygen availability, and host defences. Studying gene expression, pathogenicity, and physiology of M. tuberculosis that has been exposed to these relevant host conditions in vitro will further increase our understanding of the virulence factors that M. tuberculosis requires to establish disease. Complementary information obtained by metabolic flux analysis, proteomics, and regulatory networks analysis will enable a clearer picture of how transcriptional responses translate to changes in the metabolome and physiology of the organism.

An integrated machine learning approach for predicting DosR-regulated genes in Mycobacterium tuberculosis

BackgroundDosR is an important regulator of the response to stress such as limited oxygen availability in Mycobacterium tuberculosis. Time course gene expression data enable us to dissect this response on the gene regulatory level. The mRNA expression profile of a regulator, however, is not necessarily a direct reflection of its activity. Knowing the transcription factor activity (TFA) can be exploited to predict novel target genes regulated by the same transcription factor. Various approaches have been proposed to reconstruct TFAs from gene expression data. Most of them capture only a first-order approximation to the complex transcriptional processes by assuming linear gene responses and linear dynamics in TFA, or ignore the temporal information in data from such systems.ResultsIn this paper, we approach the problem of inferring dynamic hidden TFAs using Gaussian processes (GP). We are able to model dynamic TFAs and to account for both linear and nonlinear gene responses. To test the validity of the proposed approach, we reconstruct the hidden TFA of p53, a tumour suppressor activated by DNA damage, using published time course gene expression data. Our reconstructed TFA is closer to the experimentally determined profile of p53 concentration than that from the original study. We then apply the model to time course gene expression data obtained from chemostat cultures of M. tuberculosis under reduced oxygen availability. After estimation of the TFA of DosR based on a number of known target genes using the GP model, we predict novel DosR-regulated genes: the parameters of the model are interpreted as relevance parameters indicating an existing functional relationship between TFA and gene expression. We further improve the prediction by integrating promoter sequence information in a logistic regression model. Apart from the documented DosR-regulated genes, our prediction yields ten novel genes under direct control of DosR.ConclusionsChemostat cultures are an ideal experimental system for controlling noise and variability when monitoring the response of bacterial organisms such as M. tuberculosis to finely controlled changes in culture conditions and available metabolites. Nonlinear hidden TFA dynamics of regulators can be reconstructed remarkably well with Gaussian processes from such data. Moreover, estimated parameters of the GP can be used to assess whether a gene is controlled by the reconstructed TFA or not. It is straightforward to combine these parameters with further information, such as the presence of binding motifs, to increase prediction accuracy.

Continuous Culture of Mycobacteria

Batch cultures have predominately been used for the study of physiology and gene expression in mycobacteria. This chapter describes the assembly of chemostats and the methodology that is being used for growing Mycobacterium tuberculosis in continuous culture, which provides the greatest control over experimental conditions. It is difficult to determine the underlying genetic changes that enable M. tuberculosis to adapt to the host environment, but in vitro experiments aid the interpretation of gene expression profiles of the bacillus in vivo. Selecting relevant host conditions for study presents a major challenge. Oxygen availability has been identified as an important environmental stimulus and is a simple parameter to adjust and monitor. Described here are continuous culture methods to determine the response of M. tuberculosis to low oxygen environments.

A Bayesian Change point model for differential gene expression patterns of the DosR regulon of Mycobacterium tuberculosis

BackgroundLow oxygen availability has been shown previously to stimulate M. tuberculosis to establish non-replicative persistence in vitro. The two component sensor/regulator dosRS is a major mediator in the transcriptional response of M. tuberculosis to hypoxia and controls a regulon of approximately 50 genes that are induced under this condition.The aim of this study was to determine whether the induction of the entire DosR regulon is triggered as a synchronous event or if induction can unfold as a cascade of events as the differential expression of subsets of genes is stimulated by different oxygen availabilities.ResultsA novel aspect of our work is the use of chemostat cultures of M. tuberculosis which allowed us to control environmental conditions very tightly. We exposed M. tuberculosis to a sudden drop in oxygen availability in chemostat culture and studied the transcriptional response of the organism during the transition from a high oxygen level (10% dissolved oxygen tension or DOT) to a low oxygen level (0.2% DOT) using DNA microarrays. We developed a Bayesian change point analysis method that enabled us to detect subtle shifts in the timing of gene induction. It results in probabilities of a change in gene expression at certain time points. A computational analysis of potential binding sites upstream of the DosR-controlled genes shows how the transcriptional responses of these genes are influenced by the affinity of these binding sites to DosR. Our study also indicates that a subgroup of DosR-controlled genes is regulated indirectly.ConclusionThe majority of the dosR-dependent genes were up-regulated at 0.2% DOT, which confirms previous findings that these genes are triggered by hypoxic environments. However, our change point analysis also highlights genes which were up-regulated earlier at levels of about 8% DOT indicating that they respond to small fluctuations in oxygen availability. Our analysis shows that there are pairs of divergent genes where one gene in the pair is up-regulated before the other, presumably for a flexible response to a constantly changing environment in the host.

In vitro gene expression dissected: chemostat surgery for Mycobacterium tuberculosis

A unique approach, combining defined and reproducible in vitro models with DNA microarrays, has been developed to study environmental modulation of mycobacterial gene expression. The gene expression profiles of samples of Mycobacterium tuberculosis, from independent chemostat cultures grown under defined and reproducible conditions, were found to be highly correlated. This approach is now being used to study the effect of relevant stimuli, such as limited oxygen availability, on mycobacterial gene expression. A modification of the chemostat culture system, enabling largevolume controlled batch culture, has been developed to study starvation survival. Cultures of M. tuberculosis have been maintained under nutrient-starved conditions for extended periods, with 106 – 107 bacilli surviving in a culturable state after 100 days. The design of the culture system has made it possible to control the environment and collect multiple time-course samples to study patterns of gene expression. These studies demonstrate that it is possible to perform long-term studies and obtain reproducible expression data using controlled and defined in vitro models.

A Flow Cytometry Method for Rapidly Assessing Mycobacterium tuberculosis Responses to Antibiotics with Different Modes of Action

ABSTRACT Current methods for assessing the drug susceptibility of Mycobacterium tuberculosis are lengthy and do not capture information about viable organisms that are not immediately culturable under standard laboratory conditions as a result of antibiotic exposure. We have developed a rapid dual-fluorescence flow cytometry method using markers for cell viability and death. We show that the fluorescent marker calcein violet with an acetoxy-methyl ester group (CV-AM) can differentiate between populations of M. tuberculosis growing at different rates, while Sytox green (SG) can differentiate between live and dead mycobacteria. M. tuberculosis was exposed to isoniazid or rifampin at different concentrations over time and either dual stained with CV-AM and SG and analyzed by flow cytometry or plated to determine the viability of the cells. Although similar trends in the loss of viability were observed when the results of flow cytometry and the plate counting methods were compared, there was a lack of correlation between these two approaches, as the flow cytometry analysis potentially captured information about cell populations that were unable to grow under standard conditions. The flow cytometry approach had an additional advantage in that it could provide insights into the mode of action of the drug: antibiotics targeting the cell wall gave a flow cytometry profile distinct from those inhibiting intracellular processes. This rapid drug susceptibility testing method could identify more effective antimycobacterials, provide information about their potential mode of action, and accelerate their progress to the clinic.