Structural Basis of RNA Recognition by Mycobacterium tuberculosis MazF Homologues

The MazEF toxin-antitoxin (TA) system consists of the antitoxin MazE and the toxin MazF. MazF is a sequence-specific endoribonuclease that upon activation causes cellular growth arrest and increass the level of persisters. Moreover, MazF-induced cells are in a quasi-dormant state that cells remain metabolically active while stop dividing. The quasi-dormancy is similar to the nonreplicating state of M. tuberculosis during latent tuberculosis, thus suggesting the role of mazEF in M. tuberculosis dormancy and persistence. M. tuberculosis has nine mazEF TA modules, each with different RNA cleavage specificities and implicated in selective gene expression during stress conditions. To date only the Bacillus subtilis MazF-RNA complex structure has been determined. As M. tuberculosis MazF homologues recognize distinct RNA sequences, their molecular mechanisms of substrate specificity remain unclear. By taking advantage of X-ray crystallography, we have determined structures of two M. tuberculosis MazF-RNA complexes, MazF-mt1 (Rv2801c) and MazF-mt3 (Rv1991c) in complex with an uncleavable RNA substrate. These structures have provided the molecular basis of sequence-specific RNA recognition and cleavage by MazF toxins.

Both MazF-mt1-RNA and MazF-mt3-RNA complexes showed similar structural organization with one molecule of RNA bound to a MazF-mt1 or MazF-mt3 dimer and occupying the same pocket within the MazF dimer interface. Similar to B. subtilis MazF-RNA complex, MazF-mt1 and MazF-mt3 displayed a conserved active site architecture, where two highly conserved residues, Arg and Thr, form hydrogen bonds with the scissile phosphate group in the cleavage site of the bound RNA. The MazF-mt1-RNA complex also showed specific interactions with its three-base RNA recognition element. Compared with the B. subtilis MazF-RNA complex, our structures showed that residues involved in sequence-specific recognition of target RNA vary between the MazF homologues, therefore explaining the molecular basis for their different RNA recognition sequences. In addition, local conformational changes of the loops in the RNA binding site of MazF-mt1 appear to play a role in MazF targeting different RNA lengths and sequences. In contrast, the MazF-mt3-RNA complex is in a non-optimal RNA binding state with a symmetry-related MazF-mt3 molecule found to make interactions with the bound RNA in the crystal. The crystal-packing interactions were further examined by isothermal titration calorimetry (ITC) studies on selected MazF-mt3 mutants. Our attempts to utilize a MazF-mt3 mutant bearing mutations involved in crystal contacts all crystallized with few nucleotides, which are still found to interact with a symmetry mate. However, these different crystal forms revealed the conformational flexibility of loops in the RNA binding interface of MazF-mt3, suggesting their role in RNA binding and recognition, which will require further studies on additional MazF-mt3-RNA complex interactions.

In conclusion, the structures of the MazF-mt1-RNA and MazF-mt3-RNA complexes provide the first structural information on any M. tuberculosis MazF homologues. Supplemented with structure-guided mutational studies on MazF toxicity in vivo, this study has addressed the structural basis of different RNA cleavage specificities among MazF homologues. Our work will guide future studies on the function of other M. tuberculosis MazF and MazE-MazF homologues, and will help delineate their physiological roles in M. tuberculosis stress responses and pathogenesis.

Pairing QuantiFERON gold in-tube with opt-out HIV testing in a tuberculosis contact investigation in the Southeastern United States.

Knowing one's HIV status is particularly important in the setting of recent tuberculosis (TB) exposure. Blood tests for assessment of tuberculosis infection, such as the QuantiFERON Gold in-tube test (QFT; Cellestis Limited, Carnegie, Victoria, Australia), offer the possibility of simultaneous screening for TB and HIV with a single blood draw. We performed a cross-sectional analysis of all contacts to a highly infectious TB case in a large meatpacking factory. Twenty-two percent were foreign-born and 73% were black. Contacts were tested with both tuberculin skin testing (TST) and QFT. HIV testing was offered on an opt-out basis. Persons with TST >or=10 mm, positive QFT, and/or positive HIV test were offered latent TB treatment. Three hundred twenty-six contacts were screened: TST results were available for 266 people and an additional 24 reported a prior positive TST for a total of 290 persons with any TST result (89.0%). Adequate QFT specimens were obtained for 312 (95.7%) of persons. Thirty-two persons had QFT results but did not return for TST reading. Twenty-two percent met the criteria for latent TB infection. Eighty-eight percent accepted HIV testing. Two (0.7%) were HIV seropositive; both individuals were already aware of their HIV status, but one had stopped care a year previously. None of the HIV-seropositive persons had latent TB, but all were offered latent TB treatment per standard guidelines. This demonstrates that opt-out HIV testing combined with QFT in a large TB contact investigation was feasible and useful. HIV testing was also widely accepted. Pairing QFT with opt-out HIV testing should be strongly considered when possible.

Equity trading volume and volatility: Latent information arrivals and common long-run dependencies

This article examines the behavior of equity trading volume and volatility for the individual firms composing the Standard & Poor's 100 composite index. Using multivariate spectral methods, we find that fractionally integrated processes best describe the long-run temporal dependencies in both series. Consistent with a stylized mixture-of-distributions hypothesis model in which the aggregate "news"-arrival process possesses long-memory characteristics, the long-run hyperbolic decay rates appear to be common across each volume-volatility pair.

Latent Stick-Breaking Processes.

We develop a model for stochastic processes with random marginal distributions. Our model relies on a stick-breaking construction for the marginal distribution of the process, and introduces dependence across locations by using a latent Gaussian copula model as the mechanism for selecting the atoms. The resulting latent stick-breaking process (LaSBP) induces a random partition of the index space, with points closer in space having a higher probability of being in the same cluster. We develop an efficient and straightforward Markov chain Monte Carlo (MCMC) algorithm for computation and discuss applications in financial econometrics and ecology. This article has supplementary material online.

Latent factor analysis to discover pathway-associated putative segmental aneuploidies in human cancers.

Tumor microenvironmental stresses, such as hypoxia and lactic acidosis, play important roles in tumor progression. Although gene signatures reflecting the influence of these stresses are powerful approaches to link expression with phenotypes, they do not fully reflect the complexity of human cancers. Here, we describe the use of latent factor models to further dissect the stress gene signatures in a breast cancer expression dataset. The genes in these latent factors are coordinately expressed in tumors and depict distinct, interacting components of the biological processes. The genes in several latent factors are highly enriched in chromosomal locations. When these factors are analyzed in independent datasets with gene expression and array CGH data, the expression values of these factors are highly correlated with copy number alterations (CNAs) of the corresponding BAC clones in both the cell lines and tumors. Therefore, variation in the expression of these pathway-associated factors is at least partially caused by variation in gene dosage and CNAs among breast cancers. We have also found the expression of two latent factors without any chromosomal enrichment is highly associated with 12q CNA, likely an instance of "trans"-variations in which CNA leads to the variations in gene expression outside of the CNA region. In addition, we have found that factor 26 (1q CNA) is negatively correlated with HIF-1alpha protein and hypoxia pathways in breast tumors and cell lines. This agrees with, and for the first time links, known good prognosis associated with both a low hypoxia signature and the presence of CNA in this region. Taken together, these results suggest the possibility that tumor segmental aneuploidy makes significant contributions to variation in the lactic acidosis/hypoxia gene signatures in human cancers and demonstrate that latent factor analysis is a powerful means to uncover such a linkage.

Early versus delayed fixed dose combination abacavir/lamivudine/zidovudine in patients with HIV and tuberculosis in Tanzania.

Fixed dose combination abacavir/lamivudine/zidovudine (ABC/3TC/ZDV) among HIV-1 and tuberculosis (TB)-coinfected patients was evaluated and outcomes between early vs. delayed initiation were compared. In a randomized, pilot study conducted in the Kilimanjaro Region of Tanzania, HIV-infected inpatients with smear-positive TB and total lymphocyte count <1200/mm(3) were randomized to initiate ABC/3TC/ZDV either 2 (early) or 8 (delayed) weeks after commencing antituberculosis therapy and were followed for 104 weeks. Of 94 patients screened, 70 enrolled (41% female, median CD4 count 103 cells/mm(3)), and 33 in each group completed 104 weeks. Two deaths and 12 serious adverse events (SAEs) were observed in the early arm vs. one death, one clinical failure, and seven SAEs in the delayed arm (p = 0.6012 for time to first grade 3/4 event, SAE, or death). CD4 cell increases were +331 and +328 cells/mm(3), respectively. TB-immune reconstitution inflammatory syndromes (TB-IRIS) were not observed in any subject. Using intent-to-treat (ITT), missing = failure analyses, 74% (26/35) vs. 89% (31/35) randomized to early vs. delayed therapy had HIV RNA levels <400 copies/ml at 104 weeks (p = 0.2182) and 66% (23/35) vs. 74% (26/35), respectively, had HIV RNA levels <50 copies/ml (p = 0.6026). In an analysis in which switches from ABC/3TC/ZDV = failure, those receiving early therapy were less likely to be suppressed to <400 copies/ml [60% (21/35) vs. 86% (30/35), p = 0.030]. TB-IRIS was not observed among the 70 coinfected subjects beginning antiretroviral treatment. ABC/3TC/ZDV was well tolerated and resulted in steady immunologic improvement. Rates of virologic suppression were similar between early and delayed treatment strategies with triple nucleoside regimens when substitutions were allowed.

Bayesian Analysis of Latent Threshold Dynamic Models

We discuss a general approach to dynamic sparsity modeling in multivariate time series analysis. Time-varying parameters are linked to latent processes that are thresholded to induce zero values adaptively, providing natural mechanisms for dynamic variable inclusion/selection. We discuss Bayesian model specification, analysis and prediction in dynamic regressions, time-varying vector autoregressions, and multivariate volatility models using latent thresholding. Application to a topical macroeconomic time series problem illustrates some of the benefits of the approach in terms of statistical and economic interpretations as well as improved predictions. Supplementary materials for this article are available online. © 2013 Copyright Taylor and Francis Group, LLC.

Cross-Domain Multitask Learning with Latent Probit Models

Learning multiple tasks across heterogeneous domains is a challenging problem since the feature space may not be the same for different tasks. We assume the data in multiple tasks are generated from a latent common domain via sparse domain transforms and propose a latent probit model (LPM) to jointly learn the domain transforms, and the shared probit classifier in the common domain. To learn meaningful task relatedness and avoid over-fitting in classification, we introduce sparsity in the domain transforms matrices, as well as in the common classifier. We derive theoretical bounds for the estimation error of the classifier in terms of the sparsity of domain transforms. An expectation-maximization algorithm is derived for learning the LPM. The effectiveness of the approach is demonstrated on several real datasets.

Whole genome sequencing identifies circulating Beijing-lineage Mycobacterium tuberculosis strains in Guatemala and an associated urban outbreak.

Limited data are available regarding the molecular epidemiology of Mycobacterium tuberculosis (Mtb) strains circulating in Guatemala. Beijing-lineage Mtb strains have gained prevalence worldwide and are associated with increased virulence and drug resistance, but there have been only a few cases reported in Central America. Here we report the first whole genome sequencing of Central American Beijing-lineage strains of Mtb. We find that multiple Beijing-lineage strains, derived from independent founding events, are currently circulating in Guatemala, but overall still represent a relatively small proportion of disease burden. Finally, we identify a specific Beijing-lineage outbreak centered on a poor neighborhood in Guatemala City.