Antonio L. C. Gomes

The Mycobacterium tuberculosis regulatory network and hypoxia

We have taken the first steps towards a complete reconstruction of the Mycobacterium tuberculosis regulatory network based on ChIP-Seq and combined this reconstruction with system-wide profiling of messenger RNAs, proteins, metabolites and lipids during hypoxia and re-aeration. Adaptations to hypoxia are thought to have a prominent role in M. tuberculosis pathogenesis. Using ChIP-Seq combined with expression data from the induction of the same factors, we have reconstructed a draft regulatory network based on 50 transcription factors. This network model revealed a direct interconnection between the hypoxic response, lipid catabolism, lipid anabolism and the production of cell wall lipids. As a validation of this model, in response to oxygen availability we observe substantial alterations in lipid content and changes in gene expression and metabolites in corresponding metabolic pathways. The regulatory network reveals transcription factors underlying these changes, allows us to computationally predict expression changes, and indicates that Rv0081 is a regulatory hub.

Principles for designing synthetic microbial communities

Advances in synthetic biology to build microbes with defined and controllable properties are enabling new approaches to design and program multispecies communities. This emerging field of synthetic ecology will be important for many areas of biotechnology, bioenergy and bioremediation. This endeavor draws upon knowledge from synthetic biology, systems biology, microbial ecology and evolution. Fully realizing the potential of this discipline requires the development of new strategies to control the intercellular interactions, spatiotemporal coordination, robustness, stability and biocontainment of synthetic microbial communities. Here, we review recent experimental, analytical and computational advances to study and build multi-species microbial communities with defined functions and behavior for various applications. We also highlight outstanding challenges and future directions to advance this field.

ChIP-Seq and the complexity of bacterial transcriptional regulation.

Transcription factors (TFs) play a central role in regulating gene expression in all bacteria. Yet, until recently, studies of TF binding were limited to a small number of factors at a few genomic locations. Chromatin immunoprecipitation followed by sequencing enables mapping of binding sites for TFs in a global and high-throughput fashion. The NIAID funded TB systems biology project http://www.broadinstitute.org/annotation/tbsysbio/home.html aims to map the binding sites for every transcription factor in the genome of Mycobacterium tuberculosis (MTB), the causative agent of human TB. ChIP-Seq data already released through TBDB.org have provided new insight into the mechanisms of TB pathogenesis. But in addition, data from MTB are beginning to challenge many simplifying assumptions associated with gene regulation in all bacteria. In this chapter, we review the global aspects of TF binding in MTB and discuss the implications of these data for our understanding of bacterial gene regulation. We begin by reviewing the canonical model of bacterial transcriptional regulation using the lac operon as the standard paradigm. We then review the use of ChIP-Seq to map the binding sites of DNA-binding proteins and the application of this method to mapping TF binding sites in MTB. Finally, we discuss two aspects of the binding discovered by ChIP-Seq that were unexpected given the canonical model: the substantial binding outside the proximal promoter region and the large number of weak binding sites.

Role of intragenic binding of cAMP responsive protein (CRP) in regulation of the succinate dehydrogenase genes Rv0249c-Rv0247c in TB complex mycobacteria

Bacterial pathogens adapt to changing environments within their hosts, and the signaling molecule adenosine 3′, 5′-cyclic monophosphate (cAMP) facilitates this process. In this study, we characterized in vivo DNA binding and gene regulation by the cAMP-responsive protein CRP in M. bovis BCG as a model for tuberculosis (TB)-complex bacteria. Chromatin immunoprecipitation followed by deep-sequencing (ChIP-seq) showed that CRP associates with ∼900 DNA binding regions, most of which occur within genes. The most highly enriched binding region was upstream of a putative copper transporter gene (ctpB), and crp-deleted bacteria showed increased sensitivity to copper toxicity. Detailed mutational analysis of four CRP binding sites upstream of the virulence-associated Rv0249c-Rv0247c succinate dehydrogenase genes demonstrated that CRP directly regulates Rv0249c-Rv0247c expression from two promoters, one of which requires sequences intragenic to Rv0250c for maximum expression. The high percentage of intragenic CRP binding sites and our demonstration that these intragenic DNA sequences significantly contribute to biologically relevant gene expression greatly expand the genome space that must be considered for gene regulatory analyses in mycobacteria. These findings also have practical implications for an important bacterial pathogen in which identification of mutations that affect expression of drug target-related genes is widely used for rapid drug resistance screening.

Characterization of a cAMP responsive transcription factor, Cmr (Rv1675c), in TB complex mycobacteria reveals overlap with the DosR (DevR) dormancy regulon

Mycobacterium tuberculosis (Mtb) Cmr (Rv1675c) is a CRP/FNR family transcription factor known to be responsive to cAMP levels and during macrophage infections. However, Cmrs DNA binding properties, cellular targets and overall role in tuberculosis (TB) complex bacteria have not been characterized. In this study, we used experimental and computational approaches to characterize Cmrs DNA binding properties and identify a putative regulon. Cmr binds a 16-bp palindromic site that includes four highly conserved nucleotides that are required for DNA binding. A total of 368 binding sites, distributed in clusters among ∼200 binding regions throughout the Mycobacterium bovis BCG genome, were identified using ChIP-seq. One of the most enriched Cmr binding sites was located upstream of the cmr promoter, and we demonstrated that expression of cmr is autoregulated. cAMP affected Cmr binding at a subset of DNA loci in vivo and in vitro, including multiple sites adjacent to members of the DosR (DevR) dormancy regulon. Our findings of cooperative binding of Cmr to these DNA regions and the regulation by Cmr of the DosR-regulated virulence gene Rv2623 demonstrate the complexity of Cmr-mediated gene regulation and suggest a role for Cmr in the biology of persistent TB infection.

Decoding ChIP-seq with a double-binding signal refines binding peaks to single-nucleotides and predicts cooperative interaction

The comprehension of protein and DNA binding in vivo is essential to understand gene regulation. Chromatin immunoprecipitation followed by sequencing (ChIP-seq) provides a global map of the regulatory binding network. Most ChIP-seq analysis tools focus on identifying binding regions from coverage enrichment. However, less work has been performed to infer the physical and regulatory details inside the enriched regions. This research extends a previous blind-deconvolution approach to develop a post-peak-calling algorithm that improves binding site resolution and predicts cooperative interactions. At the core of our new method is a physically motivated model that characterizes the binding signal as an extreme value distribution. This model suggests a mathematical framework to study physical properties of DNA shearing from the ChIP-seq coverage. The model explains the ChIP-seq coverage with two signals: The first considers DNA fragments with only a single binding event, whereas the second considers fragments with two binding events (a double-binding signal). The model incorporates motif discovery and is able to detect multiple sites in an enriched region with single-nucleotide resolution, high sensitivity, and high specificity. Our method improves peak caller sensitivity, from less than 45% up to 94%, at a false positive rate < 11% for a set of 47 experimentally validated prokaryotic sites. It also improves resolution of highly enriched regions of large-scale eukaryotic data sets. The double-binding signal provides a novel application in ChIP-seq analysis: the identification of cooperative interaction. Predictions of known cooperative binding sites show a 0.85 area under an ROC curve.

Native atomic burials, supplemented by physically motivated hydrogen bond constraints, contain sufficient information to determine the tertiary structure of small globular proteins

We investigate the possibility that atomic burials, as measured by their distances from the structural geometrical center, contain sufficient information to determine the tertiary structure of globular proteins. We report Monte Carlo simulated annealing results of all‐atom hard‐sphere models in continuous space for four small proteins: the all‐β WW‐domain 1E0L, the α/β protein‐G 1IGD, the all‐α engrailed homeo‐domain 1ENH, and the α + β engineered monomeric form of the Cro protein 1ORC. We used as energy function the sum over all atoms, labeled by i, of |Ri − R  i* |, where Ri is the atomic distance from the center of coordinates, or central distance, and R  i* is the “ideal” central distance obtained from the native structure. Hydrogen bonds were taken into consideration by the assignment of two ideal distances for backbone atoms forming hydrogen bonds in the native structure depending on the formation of a geometrically defined bond, independently of bond partner. Lowest energy final conformations turned out to be very similar to the native structure for the four proteins under investigation and a strong correlation was observed between energy and distance root mean square deviation (DRMS) from the native in the case of all‐β 1E0L and α/β 1IGD. For all α 1ENH and α + β 1ORC the overall correlation between energy and DRMS among final conformations was not as high because some trajectories resulted in high DRMS but low energy final conformations in which α‐helices adopted a non‐native mutual orientation. Comparison between central distances and actual accessible surface areas corroborated the implicit assumption of correlation between these two quantities. The Z‐score obtained with this native‐centric potential in the discrimination of native 1ORC from a set of random compact structures confirmed that it contains a much smaller amount of native information when compared to a traditional contact Go potential but indicated that simple sequence‐dependent burial potentials still need some improvement in order to attain a similar discriminability. Taken together, our results suggest that central distances, in conjunction to physically motivated hydrogen bond constraints, contain sufficient information to determine the native conformation of these small proteins and that a solution to the folding problem for globular proteins could arise from sufficiently accurate burial predictions from sequence followed by minimization of a burial‐dependent energy function. Proteins 2008.

Resource competition may lead to effective treatment of antibiotic resistant infections.

Drug resistance is a common problem in the fight against infectious diseases. Recent studies have shown conditions (which we call antiR) that select against resistant strains. However, no specific drug administration strategies based on this property exist yet. Here, we mathematically compare growth of resistant versus sensitive strains under different treatments (no drugs, antibiotic, and antiR), and show how a precisely timed combination of treatments may help defeat resistant strains. Our analysis is based on a previously developed model of infection and immunity in which a costly plasmid confers antibiotic resistance. As expected, antibiotic treatment increases the frequency of the resistant strain, while the plasmid cost causes a reduction of resistance in the absence of antibiotic selection. Our analysis suggests that this reduction occurs under competition for limited resources. Based on this model, we estimate treatment schedules that would lead to a complete elimination of both sensitive and resistant strains. In particular, we derive an analytical expression for the rate of resistance loss, and hence for the time necessary to turn a resistant infection into sensitive (tclear). This time depends on the experimentally measurable rates of pathogen division, growth and plasmid loss. Finally, we estimated tclear for a specific case, using available empirical data, and found that resistance may be lost up to 15 times faster under antiR treatment when compared to a no treatment regime. This strategy may be particularly suitable to treat chronic infection. Finally, our analysis suggests that accounting explicitly for a resistance-decaying rate may drastically change predicted outcomes in host-population models.

Description of atomic burials in compact globular proteins by Fermi-Dirac probability distributions

We perform a statistical analysis of atomic distributions as a function of the distance R from the molecular geometrical center in a nonredundant set of compact globular proteins. The number of atoms increases quadratically for small R, indicating a constant average density inside the core, reaches a maximum at a size‐dependent distance Rmax, and falls rapidly for larger R. The empirical curves turn out to be consistent with the volume increase of spherical concentric solid shells and a Fermi‐Dirac distribution in which the distance R plays the role of an effective atomic energy ϵ(R) = R. The effective chemical potential μ governing the distribution increases with the number of residues, reflecting the size of the protein globule, while the temperature parameter β decreases. Interestingly, βμ is not as strongly dependent on protein size and appears to be tuned to maintain approximately half of the atoms in the high density interior and the other half in the exterior region of rapidly decreasing density. A normalized size‐independent distribution was obtained for the atomic probability as a function of the reduced distance, r = R/Rg, where Rg is the radius of gyration. The global normalized Fermi distribution, F(r), can be reasonably decomposed in Fermi‐like subdistributions for different atomic types τ, Fτ(r), with ΣτFτ(r) = F(r), which depend on two additional parameters μτ and hτ. The chemical potential μτ affects a scaling prefactor and depends on the overall frequency of the corresponding atomic type, while the maximum position of the subdistribution is determined by hτ, which appears in a type‐dependent atomic effective energy, ετ(r) = hτr, and is strongly correlated to available hydrophobicity scales. Better adjustments are obtained when the effective energy is not assumed to be necessarily linear, or ετ*(r) = hτ*rα,, in which case a correlation with hydrophobicity scales is found for the product ατhτ*. These results indicate that compact globular proteins are consistent with a thermodynamic system governed by hydrophobic‐like energy functions, with reduced distances from the geometrical center, reflecting atomic burials, and provide a conceptual framework for the eventual prediction from sequence of a few parameters from which whole atomic probability distributions and potentials of mean force can be reconstructed. Proteins 2007.

Comprehensive Definition of the SigH Regulon of Mycobacterium tuberculosis Reveals Transcriptional Control of Diverse Stress Responses

Expression of SigH, one of 12 Mycobacterium tuberculosis alternative sigma factors, is induced by heat, oxidative and nitric oxide stresses. SigH activation has been shown to increase expression of several genes, including genes involved in maintaining redox equilibrium and in protein degradation. However, few of these are known to be directly regulated by SigH. The goal of this project is to comprehensively define the Mycobacterium tuberculosis genes and operons that are directly controlled by SigH in order to gain insight into the role of SigH in regulating M. tuberculosis physiology. We used ChIP-Seq to identify in vivo SigH binding sites throughout the M. tuberculosis genome, followed by quantification of SigH-dependent expression of genes linked to these sites and identification of SigH-regulated promoters. We identified 69 SigH binding sites, which are located both in intergenic regions and within annotated coding sequences in the annotated M. tuberculosis genome. 41 binding sites were linked to genes that showed greater expression following heat stress in a SigH-dependent manner. We identified several genes not previously known to be regulated by SigH, including genes involved in DNA repair, cysteine biosynthesis, translation, and genes of unknown function. Experimental and computational analysis of SigH-regulated promoter sequences within these binding sites identified strong consensus -35 and -10 promoter sequences, but with tolerance for non-consensus bases at specific positions. This comprehensive identification and validation of SigH-regulated genes demonstrates an extended SigH regulon that controls an unexpectedly broad range of stress response functions.