Large-scale chemical-genetics yields new M. tuberculosis inhibitor classes.

New antibiotics are needed to combat rising levels of resistance, with new Mycobacterium tuberculosis (Mtb) drugs having the highest priority. However, conventional whole-cell and biochemical antibiotic screens have failed. Here we develop a strategy termed PROSPECT (primary screening of strains to prioritize expanded chemistry and targets), in which we screen compounds against pools of strains depleted of essential bacterial targets. We engineered strains that target 474 essential Mtb genes and screened pools of 100-150 strains against activity-enriched and unbiased compound libraries, probing more than 8.5 million chemical-genetic interactions. Primary screens identified over tenfold more hits than screening wild-type Mtb alone, with chemical-genetic interactions providing immediate, direct target insights. We identified over 40 compounds that target DNA gyrase, the cell wall, tryptophan, folate biosynthesis and RNA polymerase, as well as inhibitors that target EfpA. Chemical optimization yielded EfpA inhibitors with potent wild-type activity, thus demonstrating the ability of PROSPECT to yield inhibitors against targets that would have eluded conventional drug discovery.

Hypoxia Sensing and Persistence Genes Are Expressed during the Intragranulomatous Survival of Mycobacterium tuberculosis.

Although it is accepted that the environment within the granuloma profoundly affects Mycobacterium tuberculosis (Mtb) and infection outcome, our ability to understand Mtb gene expression in these niches has been limited. We determined intragranulomatous gene expression in human-like lung lesions derived from nonhuman primates with both active tuberculosis (ATB) and latent TB infection (LTBI). We employed a non-laser-based approach to microdissect individual lung lesions and interrogate the global transcriptome of Mtb within granulomas. Mtb genes expressed in classical granulomas with central, caseous necrosis, as well as within the caseum itself, were identified and compared with other Mtb lesions in animals with ATB (n = 7) or LTBI (n = 7). Results were validated using both an oligonucleotide approach and RT-PCR on macaque samples and by using human TB samples. We detected approximately 2,900 and 1,850 statistically significant genes in ATB and LTBI lesions, respectively (linear models for microarray analysis, Bonferroni corrected, P < 0.05). Of these genes, the expression of approximately 1,300 (ATB) and 900 (LTBI) was positively induced. We identified the induction of key regulons and compared our results to genes previously determined to be required for Mtb growth. Our results indicate pathways that Mtb uses to ensure its survival in a highly stressful environment in vivo. A large number of genes is commonly expressed in granulomas with ATB and LTBI. In addition, the enhanced expression of the dormancy survival regulon was a key feature of lesions in animals with LTBI, stressing its importance in the persistence of Mtb during the chronic phase of infection.

Early innate immunity determines outcome of Mycobacterium tuberculosis pulmonary infection in rabbits.

BACKGROUND: Pulmonary infection of humans by Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB), results in active disease in 5-10% of individuals, while asymptomatic latent Mtb infection (LTBI) is established in the remainder. The host immune responses that determine this differential outcome following Mtb infection are not fully understood. Using a rabbit model of pulmonary TB, we have shown that infection with the Mtb clinical isolate HN878 (a hyper-virulent W-Beijing lineage strain) leads to progressive cavitary disease similar to what is seen in humans with active TB. In contrast, infection with Mtb CDC1551 (a hyper-immunogenic clinical isolate) is efficiently controlled in rabbit lungs, with establishment of LTBI, which can be reactivated upon treatment with immune-suppressive drugs. We hypothesize that the initial interaction of Mtb with the cells of the host response in the lungs determine later outcome of infection. RESULTS: To test this hypothesis, we used our rabbit model of pulmonary TB and infected the animals with Mtb HN878 or CDC1551. At 3 hours, with similar lung bacillary loads, HN878 infection caused greater accumulation of mononuclear and polymorphonuclear leukocytes (PMN) in the lungs, compared to animals infected with CDC1551. Using whole-genome microarray gene expression analysis, we delineated the early transcriptional changes in the lungs of HN878- or CDC1551-infected rabbits at this time and compared them to the differential response at 4 weeks of Mtb-infection. Our gene network and pathway analysis showed that the most significantly differentially expressed genes involved in the host response to HN878, compared to CDC1551, at 3 hours of infection, were components of the inflammatory response and STAT1 activation, recruitment and activation of macrophages, PMN, and fMLP (N-formyl-Methionyl-Leucyl-Phenylalanine)-stimulation. At 4 weeks, the CDC1551 bacillary load was significantly lower and the granulomatous response reduced compared to HN878 infection. Moreover, although inflammation was dampened in both Mtb infections at 4 weeks, the majority of the differentially expressed gene networks were similar to those seen at 3 hours. CONCLUSIONS: We propose that differential regulation of the inflammation-associated innate immune response and related gene expression changes seen at 3 hours determine the long term outcome of Mtb infection in rabbit lungs.

Molecular immunologic correlates of spontaneous latency in a rabbit model of pulmonary tuberculosis.

BACKGROUND: Infection of humans with Mycobacterium tuberculosis (Mtb) results in latent tuberculosis infection (LTBI) in 90-95% of immune competent individuals, with no symptoms of active disease. The World Health Organization estimates that 1.5 billion people have LTBI, which can reactivate in the setting of waning host immunity, posing a threat to global TB control. Various animal models have been used to study the pathogenesis of TB. However, besides nonhuman primates, rabbits are the only animal model that fully recapitulates the pathological features of human TB, including progressive disease with necrosis and cavitation or establishment of spontaneous latency. RESULTS: We defined the molecular immunological correlates of LTBI establishment in a rabbit model of pulmonary infection with Mtb CDC1551. After aerosol infection, exponential bacterial growth was noted in the lungs for 4 weeks, followed by a significant decline by 12 weeks, resulting in the absence of cultivable bacilli by 24 weeks. We used rabbit whole genome microarrays to profile the lung transcriptome during the course of infection. At 2 weeks post-infection, gene networks involved in natural killer (NK) and dendritic cell (DC) activation and macrophage antimicrobial activities were highly upregulated. This was followed by upregulation of gene networks involved in macrophage and T cell activation and autophagy, peaking at 4 to 8 weeks. Concomitantly, host Th1, but not Th2 or inflammatory, immune response genes were significantly upregulated. Thus, the expression kinetics of genes involved in cross-talk between innate and adaptive immunity over the first 8 weeks post-infection were consistent with early efficient control of infection in the lungs. Interestingly, expression of many genes of the host innate and adaptive immune response pathways was downregulated at 12 weeks, suggesting that immune activation did not persist once bacilli began to clear from the infected lungs. CONCLUSIONS: Our results suggest that early activation of host innate immunity prior to efficient activation of T cell-mediated adaptive immunity but not inflammation is essential for establishment of LTBI in Mtb CDC1551-infected rabbits. We also show that T cell activation and the host adaptive immune response networks are dampened once bacterial growth is controlled, ultimately resulting in spontaneous LTBI.

CMRF: analyzing differential gene regulation in two group perturbation experiments.

BACKGROUND: Microarray experiments often measure expressions of genes taken from sample tissues in the presence of external perturbations such as medication, radiation, or disease. The external perturbation can change the expressions of some genes directly or indirectly through gene interaction network. In this paper, we focus on an important class of such microarray experiments that inherently have two groups of tissue samples. When such different groups exist, the changes in expressions for some of the genes after the perturbation can be different between the two groups. It is not only important to identify the genes that respond differently across the two groups, but also to mine the reason behind this differential response. In this paper, we aim to identify the cause of this differential behavior of genes, whether because of the perturbation or due to interactions with other genes. RESULTS: We propose a new probabilistic Bayesian method CMRF based on Markov Random Field to identify such genes. CMRF leverages the information about gene interactions as the prior of the model. We compare the accuracy of CMRF with SSEM and Student's t test and our old method SMRF on semi-synthetic dataset generated from microarray data. CMRF obtains high accuracy and outperforms all the other three methods. We also conduct a statistical significance test using a parametric noise based experiment to evaluate the accuracy of our method. In this experiment, CMRF generates significant regions of confidence for various parameter settings. CONCLUSIONS: In this paper, we solved the problem of finding primarily differentially regulated genes in the presence of external perturbations when the data is sampled from two groups. The probabilistic Bayesian method CMRF based on Markov Random Field incorporates dependency structure of the gene networks as the prior to the model. Experimental results on synthetic and real datasets demonstrated the superiority of CMRF compared to other simple techniques.

Inferring progression models for CGH data.

MOTIVATION: One of the mutational processes that has been monitored genome-wide is the occurrence of regional DNA copy number alterations (CNAs), which may lead to deletion or over-expression of tumor suppressors or oncogenes, respectively. Understanding the relationship between CNAs and different cancer types is a fundamental problem in cancer studies. RESULTS: This article develops an efficient method that can accurately model the progression of the cancer markers and reconstruct evolutionary relationship between multiple types of cancers using comparative genomic hybridization (CGH) data. Such modeling can lead to better understanding of the commonalities and differences between multiple cancer types and potential therapies. We have developed an automatic method to infer a graph model for the markers of multiple cancers from a large population of CGH data. Our method identifies highly related markers across different cancer types. It then builds a directed acyclic graph that shows the evolutionary history of these markers based on how common each marker is in different cancer types. We demonstrated the use of this model in determining the importance of markers in cancer evolution. We have also developed a new method to measure the evolutionary distance between different cancers based on their markers. This method employs the graph model we developed for the individual markers to measure the distance between pairs of cancers. We used this measure to create an evolutionary tree for multiple cancers. Our experiments on Progenetix database show that our markers are largely consistent to the reported hot-spot imbalances and most frequent imbalances. The results show that our distance measure can accurately reconstruct the evolutionary relationship between multiple cancer types.

Hybridization-based capture of pathogen mRNA enables paired host-pathogen transcriptional analysis.

Dual transcriptional profiling of host and bacteria during infection is challenging due to the low abundance of bacterial mRNA. We report Pathogen Hybrid Capture (PatH-Cap), a method to enrich for bacterial mRNA and deplete bacterial rRNA simultaneously from dual RNA-seq libraries using transcriptome-specific probes. By addressing both the differential RNA content of the host relative to the infecting bacterium and the overwhelming abundance of uninformative structural RNAs (rRNA, tRNA) of both species in a single step, this approach enables analysis of very low-input RNA samples. By sequencing libraries before (pre-PatH-Cap) and after (post-PatH-Cap) enrichment, we achieve dual transcriptional profiling of host and bacteria, respectively, from the same sample. Importantly, enrichment preserves relative transcript abundance and increases the number of unique bacterial transcripts per gene in post-PatH-Cap libraries compared to pre-PatH-Cap libraries at the same sequencing depth, thereby decreasing the sequencing depth required to fully capture the transcriptional profile of the infecting bacteria. We demonstrate that PatH-Cap enables the study of low-input samples including single eukaryotic cells infected by 1-3 Pseudomonas aeruginosa bacteria and paired host-pathogen temporal gene expression analysis of Mycobacterium tuberculosis infecting macrophages. PatH-Cap can be applied to the study of a range of pathogens and microbial species, and more generally, to lowly-abundant species in mixed populations.

Mucosal infection rewires TNFɑ signaling dynamics to skew susceptibility to recurrence.

A mucosal infectious disease episode can render the host either more or less susceptible to recurrent infection, but the specific mechanisms that tip the balance remain unclear. We investigated this question in a mouse model of recurrent urinary tract infection and found that a prior bladder infection resulted in an earlier onset of tumor necrosis factor-alpha (TNFɑ)-mediated bladder inflammation upon subsequent bacterial challenge, relative to age-matched naive mice. However, the duration of TNFɑ signaling activation differed according to whether the first infection was chronic (Sensitized) or self-limiting (Resolved). TNFɑ depletion studies revealed that transient early-phase TNFɑ signaling in Resolved mice promoted clearance of bladder-colonizing bacteria via rapid recruitment of neutrophils and subsequent exfoliation of infected bladder cells. In contrast, sustained TNFɑ signaling in Sensitized mice prolonged damaging inflammation, worsening infection. This work reveals how TNFɑ signaling dynamics can be rewired by a prior infection to shape diverse susceptibilities to future mucosal infections.

Simultaneous detection of genotype and phenotype enables rapid and accurate antibiotic susceptibility determination.

Multidrug resistant organisms are a serious threat to human health1,2. Fast, accurate antibiotic susceptibility testing (AST) is a critical need in addressing escalating antibiotic resistance, since delays in identifying multidrug resistant organisms increase mortality3,4 and use of broad-spectrum antibiotics, further selecting for resistant organisms. Yet current growth-based AST assays, such as broth microdilution5, require several days before informing key clinical decisions. Rapid AST would transform the care of patients with infection while ensuring that our antibiotic arsenal is deployed as efficiently as possible. Growth-based assays are fundamentally constrained in speed by doubling time of the pathogen, and genotypic assays are limited by the ever-growing diversity and complexity of bacterial antibiotic resistance mechanisms. Here we describe a rapid assay for combined genotypic and phenotypic AST through RNA detection, GoPhAST-R, that classifies strains with 94-99% accuracy by coupling machine learning analysis of early antibiotic-induced transcriptional changes with simultaneous detection of key genetic resistance determinants to increase accuracy of resistance detection, facilitate molecular epidemiology and enable early detection of emerging resistance mechanisms. This two-pronged approach provides phenotypic AST 24-36 h faster than standard workflows, with <4 h assay time on a pilot instrument for hybridization-based multiplexed RNA detection implemented directly from positive blood cultures.

Comparative study of an osazone based ligand and its palladium(II) complex with human serum albumin: A spectroscopic, thermodynamic and molecular docking approach.

An osazone based ligand, hexane-3,4-dione-bis(2'-phenylhydrazone) (LH2), was synthesized by 1:2M Schiff base condensation of 3,4-hexanedione and phenylhydrazine in dehydrated methanol. Its palladium(II) complex (1) has also been synthesized. LH2 and 1 have thoroughly been characterized by several spectroscopic and analytical means. DFT optimized structure of 1 shows that it is a monomeric Pd(II) complex having 'N2Cl2' coordination chromophore. Our BVS analysis also satisfactorily reproduces the oxidation number of the palladium center. 1 shows irreversible Pd(II)/Pd(I) reduction in its CV in methanol. 1 is three-fold more emissive than LH2. This enhanced emission has also been supported by time correlated single photon counting (TCSPC) measurements at room temperature. Human serum albumin (HSA) binding aspects of both LH2 and 1 have been investigated through various biophysical techniques. The binding constants as determined from Benesi-Hilderbrand plot using the absorbance spectral analyses were found respectively to be 1.18×105 and 4.38×104M-1 for LH2 and 1. The experimental findings confirm that both are good HSA binders. The thermodynamic parameters (∆G°, ∆H° and ∆S°) have also been evaluated by isothermal titration calorimetric (ITC) experiments. These parameters indicate that the binding processes are spontaneous both for LH2 and 1. Molecular docking analyses reveal that both LH2 and 1 reside in domain-I of HSA.

Biophysical studies on the interaction of a novel oxime based palladium(II) complex with DNA and RNA.

A novel oxime based palladium(II) complex (1) has been synthesized out of the reaction of a Schiff base ligand, 1-phenyl-1-(pyridin-2-yl-hydrazono)-propan-2-one oxime (LH2) with Na2[PdCl4] in THF. Red and diamagnetic 1 has thoroughly been characterized by several analytical and spectroscopic means like CHN, ESI-MS, FAB-MS, FT-IR, 1H NMR, 13C NMR, UV-Vis and molar electrical conductivity measurements. Geometry optimizations at the level of DFT reveals that the Pd(II) centre in 1 is nested in a square-planar 'N3Cl' coordination environment. Semi-empirical BVS mode of analysis was also undertaken to reproduce the oxidation state of the palladium centre. 1 shows quasi-reversible Pd(II)/Pd(III) and Pd(III)/Pd(IV) redox couples in its CV in acetonitrile. The photophysical studies reveal that 1 is two-fold less emissive than its tethering ligand. Several biophysical studies have been undertaken to demonstrate the binding aspects of DNA and RNA with 1. Ethidium bromide displacement study concludes that 1 is partially intercalated to the CT DNA. Thermodynamic parameters of binding have also been determined from temperature dependent fluorescence spectroscopy employing the van't Hoff plot. The binding constants as determined from McGhee-von Hippel equation (Scatchard plot) indicate that 1 is a good binder of both DNA and RNA. However, the magnitude of the binding constant as determined for RNA interaction with 1 is found to be higher than that for DNA interaction.

Spectroscopic and molecular docking studies on the interaction of human serum albumin with copper(II) complexes.

Two osazone based ligands, butane-2,3-dione bis(2'-pyridylhydrazone) (BDBPH) and hexane-3,4-dione bis(2'-pyridylhydrazone) (HDBPH), were synthesized out of the 2:1M Schiff base condensation of 2-hydrazino pyridine respectively with 2,3-butanedione and 3,4-hexanedione. The X-ray crystal structures of both the ligands have been determined. The copper(II) complex of HDBPH has also been synthesized and structurally characterized. HDBPH and its copper(II) complex have thoroughly been characterized through various spectroscopic and analytical techniques. The X-ray crystal structure of the copper complex of HDBPH shows that it is a monomeric Cu(II) complex having 'N4O2' co-ordination chromophore. Interaction of human serum albumin (HSA) with these ligands and their monomeric copper(II) complexes have been studied by various spectroscopic means. The experimental findings show that the ligands as well as their copper complexes are good HSA binders. Molecular docking investigations have also been done to unravel the mode of binding of the species with HSA.

Synthesis, structure, DFT calculations, electrochemistry, fluorescence, DNA binding and molecular docking aspects of a novel oxime based ligand and its palladium(II) complex.

A novel oxime based ligand, phenyl-(pyridine-2-yl-hydrazono)-acetaldehyde oxime (LH), and its palladium(II) complex (1) have been synthesised and spectroscopically characterised. The ligand crystallizes in the monoclinic space group (P21/c). The X-ray crystal structure of the ligand shows that it forms a hydrogen bonded helical network. The ligand has been characterised by C, H and N microanalyses, (1)H and (13)C NMR, ESI-MS, FT-IR and UV-Vis spectral measurements. Geometry optimizations at the level of DFT show that the Pd(II) centre is nested in a square-planar 'N3Cl' coordination chromophore. The diamagnetic palladium complex has been characterised by C, H and N microanalyses, FAB-MS, FT-IR, UV-Vis spectra and molar electrical conductivity measurements. The observed electronic spectrum of 1 correlates with our theoretical findings as evaluated through TD-DFT. 1 displays quasi-reversible Pd(II)/Pd(III) and Pd(III)/Pd(IV) redox couples in its CV in acetonitrile. 1 is nine-fold more emissive with respect to the binding ligand. Biophysical studies have been carried out to show the DNA binding aspects of both the ligand and complex. The binding constants for the ligand and complex were found to be 3.93×10(4) and 1.38×10(3)M(-1) respectively. To have an insight into the mode of binding of LH and 1 with CT DNA a hydrodynamic study was also undertaken. The mode of binding has also been substantiated through molecular docking. A promising groove binding efficacy has been revealed for the ligand.

Deficiency of the novel exopolyphosphatase Rv1026/PPX2 leads to metabolic downshift and altered cell wall permeability in Mycobacterium tuberculosis.

UNLABELLED: Mycobacterium tuberculosis can persist for decades in the human host. Stringent response pathways involving inorganic polyphosphate [poly(P)], which is synthesized and hydrolyzed by polyphosphate kinase (PPK) and exopolyphosphatase (PPX), respectively, are believed to play a key regulatory role in bacterial persistence. We show here that M. tuberculosis poly(P) accumulation is temporally linked to bacillary growth restriction. We also identify M. tuberculosis Rv1026 as a novel exopolyphosphatase with hydrolytic activity against long-chain poly(P). Using a tetracycline-inducible expression system to knock down expression of Rv1026 (ppx2), we found that M. tuberculosis poly(P) accumulation leads to slowed growth and reduced susceptibility to isoniazid, increased resistance to heat and acid pH, and enhanced intracellular survival during macrophage infection. By transmission electron microscopy, the ppx2 knockdown strain exhibited increased cell wall thickness, which was associated with reduced cell wall permeability to hydrophilic drugs rather than induction of drug efflux pumps or altered biofilm formation relative to the empty vector control. Transcriptomic and metabolomic analysis revealed a metabolic downshift of the ppx2 knockdown characterized by reduced transcription and translation and a downshift of glycerol-3-phosphate levels. In summary, poly(P) plays an important role in M. tuberculosis growth restriction and metabolic downshift and contributes to antibiotic tolerance through altered cell wall permeability. IMPORTANCE: The stringent response, involving the regulatory molecules inorganic polyphosphate [poly(P)] and (p)ppGpp, is believed to mediate Mycobacterium tuberculosis persistence. In this study, we identified a novel enzyme (Rv1026, PPX2) responsible for hydrolyzing long-chain poly(P). A genetically engineered M. tuberculosis strain deficient in the ppx2 gene showed increased poly(P) levels, which were associated with early bacterial growth arrest and reduced susceptibility to the first-line drug isoniazid, as well as increased bacterial survival during exposure to stress conditions and within macrophages. Relative to the control strain, the mutant showed increased thickness of the cell wall and reduced drug permeability. Global gene expression and metabolite analysis revealed reduced expression of the transcriptional and translational machinery and a shift in carbon source utilization. In summary, regulation of the poly(P) balance is critical for persister formation in M. tuberculosis.

Synthesis, structure, spectral characterization, electrochemistry and evaluation of antibacterial potentiality of a novel oxime-based palladium(II) compound.

The title monomeric Pd(II) compound, [Pd(L)(Cl)], was synthesized in moderate yield out of the reaction of equimolar proportion of Na2[PdCl4] and 3-[(5-bromo-2-hydroxy-benzylidene)-hydrazono]-butan-2-one oxime (LH) in tetrahydrofuran milieu. LH is a 1:1 Schiff-base condensate of 2,3-butanedionemonoxime monohydrazone and 5-bromosalicylaldehyde. [Pd(L)(Cl)] has been characterized by C, H and N microanalyses, (1)H and (13)C NMR, FAB-MS, FT-IR, Raman spectra, UV-Vis spectra and molar electrical conductivity measurements. [Pd(L)(Cl)] is diamagnetic. Structural elucidation reveals that the palladium center in [Pd(L)(Cl)] is nested in 'N2OCl' coordination environment. The geometry around Pd in [Pd(L)(Cl)] is distorted square-planar. The redox behavior of [Pd(L)(Cl)] in DMF shows a reduction couple, Pd(II)/Pd(I) at -0.836 V versus Ag/AgCl. The in vitro antimicrobial activity of [Pd(L)(Cl)] was screened against both Gram-positive and Gram-negative human pathogenic bacteria. This bioactivity was substantiated with SEM study. [Pd(L)(Cl)] exhibits satisfactory bactericidal as well as bacteriostatic activity.

Lesion-Specific Immune Response in Granulomas of Patients with Pulmonary Tuberculosis: A Pilot Study.

The formation and maintenance of granulomas is central to the host response to Mycobacterium tuberculosis (Mtb) infection. It is widely accepted that the lungs of patients with tuberculosis (TB) usually contain multiple infection foci, and that the granulomas evolve and differentiate independently, resulting in considerable heterogeneity. Although gene expression profiles of human blood cells have been proposed as biomarkers of Mtb infection and/or active disease, the immune profiles of discrete lesion types has not been studied extensively. Using histology, immunopathology and genome-wide transcriptome analysis, we explored the immunological profile of human lung TB granulomas. We show that although the different granulomas share core similarities in their immunological/inflammatory characteristics, they also exhibit significant divergence. Despite similar numbers of CD68+ macrophages in the different lesions, the extent of immune reactivity, as determined by the density of CD3+ T cells in the macrophage rich areas, and the extent of fibrosis, shows considerable variation. Both quantitative and qualitative differences among significantly differentially expressed genes (SDEG) were noted in each of the lesion types studied. Further, network/pathway analysis of SDEG revealed differential regulation of inflammatory response, immune cell trafficking, and cell mediated immune response in the different lesions. Our data highlight the formidable challenges facing ongoing efforts to identify peripheral blood biomarkers due to the diversity of lesion types and complexity of local immune responses in the lung.

Systems biology-based identification of Mycobacterium tuberculosis persistence genes in mouse lungs.

UNLABELLED: Identifying Mycobacterium tuberculosis persistence genes is important for developing novel drugs to shorten the duration of tuberculosis (TB) treatment. We developed computational algorithms that predict M. tuberculosis genes required for long-term survival in mouse lungs. As the input, we used high-throughput M. tuberculosis mutant library screen data, mycobacterial global transcriptional profiles in mice and macrophages, and functional interaction networks. We selected 57 unique, genetically defined mutants (18 previously tested and 39 untested) to assess the predictive power of this approach in the murine model of TB infection. We observed a 6-fold enrichment in the predicted set of M. tuberculosis genes required for persistence in mouse lungs relative to randomly selected mutant pools. Our results also allowed us to reclassify several genes as required for M. tuberculosis persistence in vivo. Finally, the new results implicated additional high-priority candidate genes for testing. Experimental validation of computational predictions demonstrates the power of this systems biology approach for elucidating M. tuberculosis persistence genes. IMPORTANCE: Mycobacterium tuberculosis, the causative agent of tuberculosis (TB), has a genetic repertoire that permits it to persist in the face of host immune responses. Identification of such persistence genes could reveal novel drug targets and elucidate mechanisms by which the organism eludes the immune system and resists drugs. Genetic screens have identified a total of 31 persistence genes, but to date only 15% of the ~4,000 M. tuberculosis genes have been tested experimentally. In this paper, as an alternative to brute force experimental screens, we describe computational methods that predict new persistence genes by combining known examples with growing databases of biological networks. Experimental testing demonstrated that these predictions are highly accurate, validating the computational approach and providing new information about M. tuberculosis persistence in host tissues. Using the new experimental results as additional input highlights additional genes for testing. Our approach can be extended to other data types and target organisms to characterize host-pathogen interactions relevant to this and other infectious diseases.

Metabolomic analysis reveals extended metabolic consequences of marginal vitamin B-6 deficiency in healthy human subjects.

Marginal deficiency of vitamin B-6 is common among segments of the population worldwide. Because pyridoxal 5'-phosphate (PLP) serves as a coenzyme in the metabolism of amino acids, carbohydrates, organic acids, and neurotransmitters, as well as in aspects of one-carbon metabolism, vitamin B-6 deficiency could have many effects. Healthy men and women (age: 20-40 y; n = 23) were fed a 2-day controlled, nutritionally adequate diet followed by a 28-day low-vitamin B-6 diet (<0.5 mg/d) to induce marginal deficiency, as reflected by a decline of plasma PLP from 52.6±14.1 (mean ± SD) to 21.5±4.6 nmol/L (P<0.0001) and increased cystathionine from 131±65 to 199±56 nmol/L (P<0.001). Fasting plasma samples obtained before and after vitamin B6 restriction were analyzed by (1)H-NMR with and without filtration and by targeted quantitative analysis by mass spectrometry (MS). Multilevel partial least squares-discriminant analysis and S-plots of NMR spectra showed that NMR is effective in classifying samples according to vitamin B-6 status and identified discriminating features. NMR spectral features of selected metabolites indicated that vitamin B-6 restriction significantly increased the ratios of glutamine/glutamate and 2-oxoglutarate/glutamate (P<0.001) and tended to increase concentrations of acetate, pyruvate, and trimethylamine-N-oxide (adjusted P<0.05). Tandem MS showed significantly greater plasma proline after vitamin B-6 restriction (adjusted P<0.05), but there were no effects on the profile of 14 other amino acids and 45 acylcarnitines. These findings demonstrate that marginal vitamin B-6 deficiency has widespread metabolic perturbations and illustrate the utility of metabolomics in evaluating complex effects of altered vitamin B-6 intake.

SSLPred: predicting synthetic sickness lethality.

Two genes in an organism have a Synthetic Sickness Lethality (SSL) interaction, if their joint deletion leads to a lower than expected fitness. Synthetic Gene Array (SGA) is a technique that helps in identifying SSL values for pairs of genes in a given set of genes. SSL interactions are useful to discover the co-expressed gene groups in the regulatory and signaling networks. Also, they are used to unravel the pair of pathways (subset of physically interacting genes) that substitute the functions of each other. Generating an SGA entry is costly as it requires producing and monitoring a double mutant (a progeny with two mutated genes). Generating a comprehensive SGA can be very expensive as the number of gene pairs is quadratic in the number of genes of the corresponding organism. In this paper, we develop a new method SSLPred to predict the SSL interactions in an organism. Our method is built on the concept of Between Pathway Models (BPM), where majority of the SSL pairs span across the two functionally complementing pathways. We develop a regression based approach that learns the mapping between the gene expressions of single deletion mutant to the corresponding SGA entries. We compare our method to the one by Hescott et al. for predicting the GI (Genetic Interaction) score of Saccharomyces cerevisiae (S. cerevisiae) on four benchmark datasets. On different experimental setups, on average SSLPred performs significantly better compared to the other method.

GBA manager: an online tool for querying low-complexity regions in proteins.

Abstract We developed GBA Manager, an online software that facilitates the Graph-Based Algorithm (GBA) we proposed in our earlier work. GBA identifies the low-complexity regions (LCR) of protein sequences. GBA exploits a similarity matrix, such as BLOSUM62, to compute the complexity of the subsequences of the input protein sequence. It uses a graph-based algorithm to accurately compute the regions that have low complexities. GBA Manager is a user friendly web-service that enables online querying of protein sequences using GBA. In addition to querying capabilities of the existing GBA algorithm, GBA Manager computes the p-values of the LCR identified. The p-value gives an estimate of the possibility that the region appears by chance. GBA Manager presents the output in three different understandable formats. GBA Manager is freely accessible at http://bioinformatics.cise.ufl.edu/GBA/GBA.htm .