Prediction of transcriptional regulatory interactions in bacteria : a comparative genomics approach

Exponential growth of genomic data in the last two decades has made manual analyses impractical for all but trial studies. As genomic analyses have become more sophisticated, and move toward comparisons across large datasets, computational approaches have become essential. One of the most important biological questions is to understand the mechanisms underlying gene regulation. Genetic regulation is commonly investigated and modelled through the use of transcriptional regulatory network (TRN) structures. These model the regulatory interactions between two key components: transcription factors (TFs) and the target genes (TGs) they regulate. Transcriptional regulatory networks have proven to be invaluable scientific tools in Bioinformatics. When used in conjunction with comparative genomics, they have provided substantial insights into the evolution of regulatory interactions. Current approaches to regulatory network inference, however, omit two additional key entities: promoters and transcription factor binding sites (TFBSs). In this study, we attempted to explore the relationships among these regulatory components in bacteria. Our primary goal was to identify relationships that can assist in reducing the high false positive rates associated with transcription factor binding site predictions and thereupon enhance the reliability of the inferred transcription regulatory networks. In our preliminary exploration of relationships between the key regulatory components in Escherichia coli transcription, we discovered a number of potentially useful features. The combination of location score and sequence dissimilarity scores increased de novo binding site prediction accuracy by 13.6%. Another important observation made was with regards to the relationship between transcription factors grouped by their regulatory role and corresponding promoter strength. Our study of E.coli ��70 promoters, found support at the 0.1 significance level for our hypothesis | that weak promoters are preferentially associated with activator binding sites to enhance gene expression, whilst strong promoters have more repressor binding sites to repress or inhibit gene transcription. Although the observations were specific to �70, they nevertheless strongly encourage additional investigations when more experimentally confirmed data are available. In our preliminary exploration of relationships between the key regulatory components in E.coli transcription, we discovered a number of potentially useful features { some of which proved successful in reducing the number of false positives when applied to re-evaluate binding site predictions. Of chief interest was the relationship observed between promoter strength and TFs with respect to their regulatory role. Based on the common assumption, where promoter homology positively correlates with transcription rate, we hypothesised that weak promoters would have more transcription factors that enhance gene expression, whilst strong promoters would have more repressor binding sites. The t-tests assessed for E.coli �70 promoters returned a p-value of 0.072, which at 0.1 significance level suggested support for our (alternative) hypothesis; albeit this trend may only be present for promoters where corresponding TFBSs are either all repressors or all activators. Nevertheless, such suggestive results strongly encourage additional investigations when more experimentally confirmed data will become available. Much of the remainder of the thesis concerns a machine learning study of binding site prediction, using the SVM and kernel methods, principally the spectrum kernel. Spectrum kernels have been successfully applied in previous studies of protein classification [91, 92], as well as the related problem of promoter predictions [59], and we have here successfully applied the technique to refining TFBS predictions. The advantages provided by the SVM classifier were best seen in `moderately'-conserved transcription factor binding sites as represented by our E.coli CRP case study. Inclusion of additional position feature attributes further increased accuracy by 9.1% but more notable was the considerable decrease in false positive rate from 0.8 to 0.5 while retaining 0.9 sensitivity. Improved prediction of transcription factor binding sites is in turn extremely valuable in improving inference of regulatory relationships, a problem notoriously prone to false positive predictions. Here, the number of false regulatory interactions inferred using the conventional two-component model was substantially reduced when we integrated de novo transcription factor binding site predictions as an additional criterion for acceptance in a case study of inference in the Fur regulon. This initial work was extended to a comparative study of the iron regulatory system across 20 Yersinia strains. This work revealed interesting, strain-specific difierences, especially between pathogenic and non-pathogenic strains. Such difierences were made clear through interactive visualisations using the TRNDifi software developed as part of this work, and would have remained undetected using conventional methods. This approach led to the nomination of the Yfe iron-uptake system as a candidate for further wet-lab experimentation due to its potential active functionality in non-pathogens and its known participation in full virulence of the bubonic plague strain. Building on this work, we introduced novel structures we have labelled as `regulatory trees', inspired by the phylogenetic tree concept. Instead of using gene or protein sequence similarity, the regulatory trees were constructed based on the number of similar regulatory interactions. While the common phylogentic trees convey information regarding changes in gene repertoire, which we might regard being analogous to `hardware', the regulatory tree informs us of the changes in regulatory circuitry, in some respects analogous to `software'. In this context, we explored the `pan-regulatory network' for the Fur system, the entire set of regulatory interactions found for the Fur transcription factor across a group of genomes. In the pan-regulatory network, emphasis is placed on how the regulatory network for each target genome is inferred from multiple sources instead of a single source, as is the common approach. The benefit of using multiple reference networks, is a more comprehensive survey of the relationships, and increased confidence in the regulatory interactions predicted. In the present study, we distinguish between relationships found across the full set of genomes as the `core-regulatory-set', and interactions found only in a subset of genomes explored as the `sub-regulatory-set'. We found nine Fur target gene clusters present across the four genomes studied, this core set potentially identifying basic regulatory processes essential for survival. Species level difierences are seen at the sub-regulatory-set level; for example the known virulence factors, YbtA and PchR were found in Y.pestis and P.aerguinosa respectively, but were not present in both E.coli and B.subtilis. Such factors and the iron-uptake systems they regulate, are ideal candidates for wet-lab investigation to determine whether or not they are pathogenic specific. In this study, we employed a broad range of approaches to address our goals and assessed these methods using the Fur regulon as our initial case study. We identified a set of promising feature attributes; demonstrated their success in increasing transcription factor binding site prediction specificity while retaining sensitivity, and showed the importance of binding site predictions in enhancing the reliability of regulatory interaction inferences. Most importantly, these outcomes led to the introduction of a range of visualisations and techniques, which are applicable across the entire bacterial spectrum and can be utilised in studies beyond the understanding of transcriptional regulatory networks.

Systems Biology Approaches to Probe Gene Regulation in Bacteria

Mechanisms that allow pathogens to colonize the host are not the product of isolated genes, but instead emerge from the concerted operation of regulatory networks. Therefore, identifying components and the systemic behavior of networks is necessary to a better understanding of gene regulation and pathogenesis. To this end, I have developed systems biology approaches to study transcriptional and post-transcriptional gene regulation in bacteria, with an emphasis in the human pathogen Mycobacterium tuberculosis (Mtb). First, I developed a network response method to identify parts of the Mtb global transcriptional regulatory network utilized by the pathogen to counteract phagosomal stresses and survive within resting macrophages. As a result, the method unveiled transcriptional regulators and associated regulons utilized by Mtb to establish a successful infection of macrophages throughout the first 14 days of infection. Additionally, this network-based analysis identified the production of Fe-S proteins coupled to lipid metabolism through the alkane hydroxylase complex as a possible strategy employed by Mtb to survive in the host. Second, I developed a network inference method to infer the small non-coding RNA (sRNA) regulatory network in Mtb. The method identifies sRNA-mRNA interactions by integrating a priori knowledge of possible binding sites with structure-driven identification of binding sites. The reconstructed network was useful to predict functional roles for the multitude of sRNAs recently discovered in the pathogen, being that several sRNAs were postulated to be involved in virulence-related processes. Finally, I applied a combined experimental and computational approach to study post-transcriptional repression mediated by small non-coding RNAs in bacteria. Specifically, a probabilistic ranking methodology termed rank-conciliation was developed to infer sRNA-mRNA interactions based on multiple types of data. The method was shown to improve target prediction in Escherichia coli, and therefore is useful to prioritize candidate targets for experimental validation.

Analysis of the hierarchical structure of the B. subtilis transcriptional regulatory network

The transcriptional regulation of gene expression is orchestrated by complex networks of interacting genes. Increasing evidence indicates that these `transcriptional regulatory networks' (TRNs) in bacteria have an inherently hierarchical architecture, although the design principles and the specific advantages offered by this type of organization have not yet been fully elucidated. In this study, we focussed on the hierarchical structure of the TRN of the gram-positive bacterium Bacillus subtilis and performed a comparative analysis with the TRN of the gram-negative bacterium Escherichia coli. Using a graph-theoretic approach, we organized the transcription factors (TFs) and sigma-factors in the TRNs of B. subtilis and E. coli into three hierarchical levels (Top, Middle and Bottom) and studied several structural and functional properties across them. In addition to many similarities, we found also specific differences, explaining the majority of them with variations in the distribution of s-factors across the hierarchical levels in the two organisms. We then investigated the control of target metabolic genes by transcriptional regulators to characterize the differential regulation of three distinct metabolic subsystems (catabolism, anabolism and central energy metabolism). These results suggest that the hierarchical architecture that we observed in B. subtilis represents an effective organization of its TRN to achieve flexibility in response to a wide range of diverse stimuli.

Characterization of the 5' upstream regulatory region of the human myostatin gene: regulation of myostatin gene transcription by dexamethasone in vitro

We cloned and characterized a 3.3-kb fragment containing the 5'-regulatory region of the human myostatin gene. The promoter sequence contains putative muscle growth response elements for glucocorticoid, androgen, thyroid hormone, myogenic differentiation factor 1, myocyte enhancer factor 2, peroxisome proliferator-activated receptor, and nuclear factor-kappaB. To identify sites important for myostatin's gene transcription and regulation, eight deletion constructs were placed in C(2)C(12) and L6 skeletal muscle cells. Transcriptional activity of the constructs was found to be significantly higher in myotubes compared with that of myoblasts. To investigate whether glucocorticoids regulate myostatin gene expression, we incubated both cell lines with dexamethasone. On both occasions, dexamethasone dose dependently increased both the promoter's transcriptional activity and the endogenous myostatin expression. The effects of dexamethasone were blocked when the cells were coincubated with the glucocorticoid receptor antagonist RU-486. These findings suggest that glucocorticoids upregulate myostatin expression by inducing gene transcription, possibly through a glucocorticoid receptor-mediated pathway. We speculate that glucocorticoid-associated muscle atrophy might be due in part to the upregulation of myostatin expression.

Toward functional genomics in bacteria: Analysis of gene expression in Escherichia coli from a bacterial artificial chromosome library of Bacillus cereus

As the study of microbes moves into the era of functional genomics, there is an increasing need for molecular tools for analysis of a wide diversity of microorganisms. Currently, biological study of many prokaryotes of agricultural, medical, and fundamental scientific interest is limited by the lack of adequate genetic tools. We report the application of the bacterial artificial chromosome (BAC) vector to prokaryotic biology as a powerful approach to address this need. We constructed a BAC library in Escherichia coli from genomic DNA of the Gram-positive bacterium Bacillus cereus. This library provides 5.75-fold coverage of the B. cereus genome, with an average insert size of 98 kb. To determine the extent of heterologous expression of B. cereus genes in the library, we screened it for expression of several B. cereus activities in the E. coli host. Clones expressing 6 of 10 activities tested were identified in the library, namely, ampicillin resistance, zwittermicin A resistance, esculin hydrolysis, hemolysis, orange pigment production, and lecithinase activity. We analyzed selected BAC clones genetically to identify rapidly specific B. cereus loci. These results suggest that BAC libraries will provide a powerful approach for studying gene expression from diverse prokaryotes.

Targeted Gene Repression Technologies for Regenerative Medicine, Genomics, and Gene Therapy

Gene regulation is a complex and tightly controlled process that defines cell function in physiological and abnormal states. Programmable gene repression technologies enable loss-of-function studies for dissecting gene regulation mechanisms and represent an exciting avenue for gene therapy. Established and recently developed methods now exist to modulate gene sequence, epigenetic marks, transcriptional activity, and post-transcriptional processes, providing unprecedented genetic control over cell phenotype. Our objective was to apply and develop targeted repression technologies for regenerative medicine, genomics, and gene therapy applications. We used RNA interference to control cell cycle regulation in myogenic differentiation and enhance the proliferative capacity of tissue engineered cartilage constructs. These studies demonstrate how modulation of a single gene can be used to guide cell differentiation for regenerative medicine strategies. RNA-guided gene regulation with the CRISPR/Cas9 system has rapidly expanded the targeted repression repertoire from silencing single protein-coding genes to modulation of genes, promoters, and other distal regulatory elements. In order to facilitate its adaptation for basic research and translational applications, we demonstrated the high degree of specificity for gene targeting, gene silencing, and chromatin modification possible with Cas9 repressors. The specificity and effectiveness of RNA-guided transcriptional repressors for silencing endogenous genes are promising characteristics for mechanistic studies of gene regulation and cell phenotype. Furthermore, our results support the use of Cas9-based repressors as a platform for novel gene therapy strategies. We developed an in vivo AAV-based gene repression system for silencing endogenous genes in a mouse model. Together, these studies demonstrate the utility of gene repression tools for guiding cell phenotype and the potential of the RNA-guided CRISPR/Cas9 platform for applications such as causal studies of gene regulatory mechanisms and gene therapy.

Quantifying Eukaryotic Gene Regulation in Hormone Response and Disease.

Quantifying the function of mammalian enhancers at the genome or population scale has been longstanding challenge in the field of gene regulation. Studies of individual enhancers have provided anecdotal evidence on which many foundational assumptions in the field are based. Genome-scale studies have revealed that the number of sites bound by a given transcription factor far outnumber the genes that the factor regulates. In this dissertation we describe a new method, chromatin immune-enriched reporter assays (ChIP-reporters), and use that approach to comprehensively test the enhancer activity of genomic loci bound by the glucocorticoid receptor (GR). Integrative genomics analyses of our ChIP-reporter data revealed an unexpected mechanism of glucocorticoid (GC)-induced gene regulation. In that mechanism, only the minority of GR bound sites acts as GC-inducible enhancers. Many non-GC-inducible GR binding sites interact with GC-induced sites via chromatin looping. These interactions can increase the activity of GC-induced enhancers. Finally, we describe a method that enables the detection and characterization of the functional effects of non-coding genetic variation on enhancer activity at the population scale. Taken together, these studies yield both mechanistic and genetic evidence that provides context that informs the understanding of the effects of multiple enhancer variants on gene expression.

Pseudomonas Aeruginosa AmpR Transcriptional Regulatory Network

In Enterobacteriaceae, the transcriptional regulator AmpR, a member of the LysR family, regulates the expression of a chromosomal β-lactamase AmpC. The regulatory repertoire of AmpR is broader in Pseudomonas aeruginosa, an opportunistic pathogen responsible for numerous acute and chronic infections including cystic fibrosis. Previous studies showed that in addition to regulating ampC, P. aeruginosa AmpR regulates the sigma factor AlgT/U and production of some quorum sensing (QS)-regulated virulence factors. In order to better understand the ampR regulon, the transcriptional profiles generated using DNA microarrays and RNA-Seq of the prototypic P. aeruginosa PAO1 strain with its isogenic ampR deletion mutant, PAO∆ampR were analyzed. Transcriptome analysis demonstrates that the AmpR regulon is much more extensive than previously thought influencing the differential expression of over 500 genes. In addition to regulating resistance to β-lactam antibiotics via AmpC, AmpR also regulates non-β-lactam antibiotic resistance by modulating the MexEF-OprN efflux pump. Virulence mechanisms including biofilm formation, QS-regulated acute virulence, and diverse physiological processes such as oxidative stress response, heat-shock response and iron uptake are AmpR-regulated. Real-time PCR and phenotypic assays confirmed the transcriptome data. Further, Caenorhabditis elegans model demonstrates that a functional AmpR is required for full pathogenicity of P. aeruginosa. AmpR, a member of the core genome, also regulates genes in the regions of genome plasticity that are acquired by horizontal gene transfer. The extensive AmpR regulon included other transcriptional regulators and sigma factors, accounting for the extensive AmpR regulon. Gene expression studies demonstrate AmpR-dependent expression of the QS master regulator LasR that controls expression of many virulence factors. Using a chromosomally tagged AmpR, ChIP-Seq studies show direct AmpR binding to the lasR promoter. The data demonstrates that AmpR functions as a global regulator in P. aeruginosa and is a positive regulator of acute virulence while negatively regulating chronic infection phenotypes. In summary, my dissertation sheds light on the complex regulatory circuit in P. aeruginosa to provide a better understanding of the bacterial response to antibiotics and how the organism coordinately regulates a myriad of virulence factors.

Neuronal K-Cl Cotransporter : Transcriptional Mechanisms of KCC2 Gene Regulation

K-Cl cotransporter 2 (KCC2) maintains a low intracellular Cl concentration required for fast hyperpolarizing responses of neurons to classical inhibitory neurotransmitters γ-aminobutyric acid (GABA) and glycine. Decreased Cl extrusion observed in genetically modified KCC2-deficient mice leads to depolarizing GABA responses, impaired brain inhibition, and as a consequence to epileptic seizures. Identification of mechanisms regulating activity of the SLC12A5 gene, which encodes the KCC2 cotransporter, in normal and pathological conditions is, thus, of extreme importance. Multiple reports have previously elucidated in details a spatio-temporal pattern of KCC2 expression. Among the characteristic features are an exclusive neuronal specificity, a dramatic upregulation during embryonic and early postnatal development, and a significant downregulation by neuronal trauma. Numerous studies confirmed these expressional features, however transcriptional mechanisms predetermining the SLC12A5 gene behaviour are still unknown. The aim of the presented thesis is to recognize such transcriptional mechanisms and, on their basis, to create a transcriptional model that would explain the established SLC12A5 gene behaviour. Up to recently, only one KCC2 transcript has been thought to exist. A particular novelty of the presented work is the identification of two SLC12A5 gene promoters (SLC12A5-1a and SLC12A5-1b) that produce at least two KCC2 isoforms (KCC2a and KCC2b) differing by their N-terminal parts. Even though a functional 86Rb+ assay reveals no significant difference between transport activities of the isoforms, consensus sites for several protein kinases, found in KCC2a but not in KCC2b, imply a distinct kinetic regulation. As a logical continuation, the current work presents a detailed analysis of the KCC2a and KCC2b expression patterns. This analysis shows an exclusively neuron-specific pattern and similar expression levels for both isoforms during embryonic and neonatal development in rodents. During subsequent postnatal development, the KCC2b expression dramatically increases, while KCC2a expression, depending on central nervous system (CNS) area, either remains at the same level or moderately decreases. In an attempt to explain both the neuronal specificity and the distinct expressional kinetics of the KCC2a and KCC2b isoforms during postnatal development, the corresponding SLC12A5-1a and SLC12A5-1b promoters have been subjected to a comprehensive bioinformatical analysis. Binding sites of several transcription factors (TFs), conserved in the mammalian SLC12A5 gene orthologs, have been identified that might shed light on the observed behaviour of the SLC12A5 gene. Possible roles of these TFs in the regulating of the SLC12A5 gene expression have been elucidated in subsequent experiments and are discussed in the current thesis.

Information processing in the transcriptional regulatory network of yeast: Functional robustness

Background: Gene networks are considered to represent various aspects of molecular biological systems meaningfully because they naturally provide a systems perspective of molecular interactions. In this respect, the functional understanding of the transcriptional regulatory network is considered as key to elucidate the functional organization of an organism.

Regulatory network of lipopolysaccharide O-antigen biosynthesis in Yersinia enterocolitica includes cell envelope-dependent signals

Lipopolysaccharide (LPS) is a glycolipid present in the outer membrane of all Gram-negative bacteria, and it is one of the signature molecules recognized by the receptors of the innate immune system. In addition to its lipid A portion (the endotoxin), its O-chain polysaccharide (the O-antigen) plays a critical role in the bacterium-host interplay and, in a number of bacterial pathogens, it is a virulence factor. We present evidence that, in Yersinia enterocolitica serotype O:8, a complex signalling network regulates O-antigen expression in response to temperature. Northern blotting and reporter fusion analyses indicated that temperature regulates the O-antigen expression at the transcriptional level. Promoter cloning showed that the O-antigen gene cluster contains two transcriptional units under the control of promoters P(wb1) and P(wb2). The activity of both promoters is under temperature regulation and is repressed in bacteria grown at 37 degrees C. We demonstrate that the RosA/RosB efflux pump/potassium antiporter system and Wzz, the O-antigen chain length determinant, are indirectly involved in the regulation mainly affecting the activity of promoter P(wb2). The rosAB transcription, under the control of P(ros), is activated at 37 degrees C, and P(wb2) is repressed through the signals generated by the RosAB system activation, i.e. decreased [K+] and increased [H+]. The wzz transcription is under the control of P(wb2), and we show that, at 37 degrees C, overexpression of Wzz downregulates slightly the P(wb1) and P(wb2) activities and more strongly the P(ros) activity, with the net result that more O-antigen is produced. Finally, we demonstrate that overexpression of Wzz causes membrane stress that activates the CpxAR two-component signal transduction system.

Isoform specificity for oestrogen receptor and thyroid hormone receptor genes and their interactions on the NR2D gene promoter

Oestrogens are critical for the display of lordosis behaviour and, in recent years, have also been shown to be involved in synaptic plasticity. In the brain, the regulation of ionotropic glutamate receptors has consequences for excitatory neurotransmission. Oestrogen regulation of the N-methyl-d-aspartate receptor subunit 2D (NR2D) has generated considerable interest as a possible molecular mechanism by which synaptic plasticity can be modulated. Since more than one isoform of the oestrogen receptor (ER) exists in mammals, it is possible that oestrogen regulation via the ERalpha and ERbeta isoforms on the NR2D oestrogen response element (ERE) is not equivalent. In the kidney fibroblast (CV1) cell line, we show that in response to 17beta-oestradiol, only ERalpha, not ERbeta, could upregulate transcription from the ERE which is in the 3' untranslated region of the NR2D gene. When this ERE is in the 5' position, neither ERalpha nor ERbeta showed transactivation capacity. Thyroid hormone receptor (TR) modulation of ER mediated induction has been shown for other ER target genes, such as the preproenkephalin and oxytocin receptor genes. Since the various TR isoforms exhibit distinct roles, we hypothesized that TR modulation of ER induction may also be isoform specific. This is indeed the case. The TRalpha1 isoform stimulated ERalpha mediated induction from the 3'-ERE whereas the TRbeta1 isoform inhibited this induction. This study shows that isoforms of both the ER and TR have different transactivation properties. Such flexible regulation and crosstalk by nuclear receptor isoforms leads to different transcriptional outcomes and the combinatorial logic may aid neuroendocrine integration.

Symmetry in biology: from genetic code to stochastic gene regulation

Mathematical models, as instruments for understanding the workings of nature, are a traditional tool of physics, but they also play an ever increasing role in biology - in the description of fundamental processes as well as that of complex systems. In this review, the authors discuss two examples of the application of group theoretical methods, which constitute the mathematical discipline for a quantitative description of the idea of symmetry, to genetics. The first one appears, in the form of a pseudo-orthogonal (Lorentz like) symmetry, in the stochastic modelling of what may be regarded as the simplest possible example of a genetic network and, hopefully, a building block for more complicated ones: a single self-interacting or externally regulated gene with only two possible states: ` on` and ` off`. The second is the algebraic approach to the evolution of the genetic code, according to which the current code results from a dynamical symmetry breaking process, starting out from an initial state of complete symmetry and ending in the presently observed final state of low symmetry. In both cases, symmetry plays a decisive role: in the first, it is a characteristic feature of the dynamics of the gene switch and its decay to equilibrium, whereas in the second, it provides the guidelines for the evolution of the coding rules.

Aspects of gene regulation in the diploid and tetraploid Odontophrynus americanus (Amphibia, Anura, Leptodactylidae)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Capsule gene regulation in Bacillus anthracis and implications for virulence

The poly-D-glutamic acid capsule of Bacillus anthracis is considered essential for lethal anthrax disease. Yet investigations of capsule function have been limited primarily to attenuated B. anthracis strains lacking certain genetic elements. In work presented in this thesis, I constructed and characterized a genetically complete (pXO1 + pXO2+) B. anthracis strain (UT500) and isogenic mutants deleted for two previously identified capsule gene regulators, atxA and acpA, and a newly-identified regulator, acpB. Results of transcriptional analysis and microscopy revealed that atxA controls expression of the first gene of the capsule biosynthesis operon, capB, via positive transcriptional regulation of acpA and acpB. acpA and acpB appear to be partial functional homologs. Deletion of either gene alone has little effect on capsule synthesis. However, a mutant deleted for both acpA and acpB is noncapsulated. Thus, in contrast to previously published models, my results suggest that atxA is the master regulator of cap gene expression in a genetically complete strain. A detailed transcriptional analysis of capB and the regulatory genes was performed to establish the effects of the regulators and CO2/bicarbonate on specific mRNAs of target genes. CO2/bicarbonate is a well-established signal for B. anthracis capsule synthesis in culture. Taqman RT-PCR results indicated that growth in the presence of elevated CO2 greatly increased expression of acpA, acpB and capB but not atxA. 5′ end mapping of capB and acpA revealed atxA-regulated and atxA-independent transcriptional start sites for both genes. All atxA-regulated start sites were also CO2-regulated. A single atxA-independent start site was identified 5 ′ of acpB. However, RT-PCR analysis indicated that capD and acpB are co-transcribed. Thus, it is likely that atxA-mediated control of acpB expression occurs via transcriptional activation of the atxA-regulated start sites of capB. Finally, I examined the contribution of the B. anthracis capsule to virulence. The virulence of the parent strain, mutants deleted for the capsule biosynthesis genes ( capBCAD), and mutants missing the capsule regulator genes was compared using a mouse model for inhalation anthrax. The data indicate that in this model, capsule is essential for virulence. Mice survived infection with the noncapsulated capBCAD and acpA acpB mutants. These mutants initiated germination in the lung, but did not disseminate to the spleen. The acpA mutant had an LD50 value similar to the parent strain and was able to disseminate and cause lethal infection. Unexpectedly, the acpB mutant had a higher LD 50 and a reduced ability to disseminate. During in vitro culture, the acpB single mutant produces capsule and toxin similar to the parent strain. It is likely that acpB regulates the expression of downstream genes that contribute to the virulence of B. anthracis. ^