A periplasmic cinched protein is required for siderophore secretion and virulence of Mycobacterium tuberculosis.

Iron is essential for growth of Mycobacterium tuberculosis, the causative agent of tuberculosis. To acquire iron from the host, M. tuberculosis uses the siderophores called mycobactins and carboxymycobactins. Here, we show that the rv0455c gene is essential for M. tuberculosis to grow in low-iron medium and that secretion of both mycobactins and carboxymycobactins is drastically reduced in the rv0455c deletion mutant. Both water-soluble and membrane-anchored Rv0455c are functional in siderophore secretion, supporting an intracellular role. Lack of Rv0455c results in siderophore toxicity, a phenotype observed for other siderophore secretion mutants, and severely impairs replication of M. tuberculosis in mice, demonstrating the importance of Rv0455c and siderophore secretion during disease. The crystal structure of a Rv0455c homolog reveals a novel protein fold consisting of a helical bundle with a 'cinch' formed by an essential intramolecular disulfide bond. These findings advance our understanding of the distinct M. tuberculosis siderophore secretion system.

Two interacting ATPases protect Mycobacterium tuberculosis from glycerol and nitric oxide toxicity.

The Mycobacterium tuberculosis H37Rv genome has been sequenced and annotated over 20 years ago, yet roughly half of the protein-coding genes still lack a predicted function. We characterized two genes of unknown function, rv3679 and rv3680, for which inconsistent findings regarding their importance for virulence in mice have been reported. We confirmed that a rv3679-80 deletion mutant (Δrv3679-80) was virulent in mice and discovered that Δrv3679-80 suffered from a glycerol-dependent recovery defect on agar plates following mouse infection. Glycerol also exacerbated killing of Δrv3679-80 by nitric oxide. Rv3679-Rv3680 have previously been shown to form a complex with ATPase activity and we demonstrate that the ability of M. tuberculosis to cope with elevated levels of glycerol and nitric oxide requires intact ATP-binding motifs in both Rv3679 and Rv3680. Inactivation of glycerol kinase or Rv2370c, a protein of unknown function, suppressed glycerol mediated toxicity in Δrv3679-80 Glycerol catabolism led to increased intracellular methylglyoxal pools and Δrv3679-80 was hypersusceptible to extracellular methylglyoxal suggesting that glycerol toxicity in Δrv3679-80 is caused by methylglyoxal. Rv3679 and Rv3680 interacted with Rv1509, and Rv3679 had numerous additional interactors including proteins of the type II fatty acid synthase (FASII) pathway and mycolic acid modifying enzymes linking Rv3679 to fatty acid or lipid synthesis. This work provides experimentally determined roles for Rv3679 and Rv3680 and stimulates future research on these and other proteins of unknown function.Importance A better understanding of the pathogenesis of tuberculosis requires a better understanding of gene function in M. tuberculosis This work provides the first functional insight into the Rv3679/Rv3680 ATPase complex. We demonstrate that M. tuberculosis requires this complex and specifically its ATPase activity to resist glycerol and nitric oxide toxicity. We provide evidence that the glycerol-derived metabolite methylglyoxal causes toxicity in the absence of Rv3679/Rv3680. We further show that glycerol-dependent toxicity is reversed when glycerol kinase (GlpK) is inactivated. Our work uncovered other genes of unknown function that interact with Rv3679 and/or Rv3680 genetically or physically, underscoring the importance of understanding uncharacterized genes.

Adaptive SPECT.

Adaptive imaging systems alter their data-acquisition configuration or protocol in response to the image information received. An adaptive pinhole single-photon emission computed tomography (SPECT) system might acquire an initial scout image to obtain preliminary information about the radiotracer distribution and then adjust the configuration or sizes of the pinholes, the magnifications, or the projection angles in order to improve performance. This paper briefly describes two small-animal SPECT systems that allow this flexibility and then presents a framework for evaluating adaptive systems in general, and adaptive SPECT systems in particular. The evaluation is in terms of the performance of linear observers on detection or estimation tasks. Expressions are derived for the ideal linear (Hotelling) observer and the ideal linear (Wiener) estimator with adaptive imaging. Detailed expressions for the performance figures of merit are given, and possible adaptation rules are discussed.

Estimating random signal parameters from noisy images with nuisance parameters: linear and scanning-linear methods.

In a pure estimation task, an object of interest is known to be present, and we wish to determine numerical values for parameters that describe the object. This paper compares the theoretical framework, implementation method, and performance of two estimation procedures. We examined the performance of these estimators for tasks such as estimating signal location, signal volume, signal amplitude, or any combination of these parameters. The signal is embedded in a random background to simulate the effect of nuisance parameters. First, we explore the classical Wiener estimator, which operates linearly on the data and minimizes the ensemble mean-squared error. The results of our performance tests indicate that the Wiener estimator can estimate amplitude and shape once a signal has been located, but is fundamentally unable to locate a signal regardless of the quality of the image. Given these new results on the fundamental limitations of Wiener estimation, we extend our methods to include more complex data processing. We introduce and evaluate a scanning-linear estimator that performs impressively for location estimation. The scanning action of the estimator refers to seeking a solution that maximizes a linear metric, thereby requiring a global-extremum search. The linear metric to be optimized can be derived as a special case of maximum a posteriori (MAP) estimation when the likelihood is Gaussian and a slowly varying covariance approximation is made.