Proteogenomic analysis of Mycobacterium tuberculosis by high resolution mass spectrometry

The genome sequencing of H37Rv strain of Mycobacterium tuberculosis was completed in 1998 followed by the whole genome sequencing of a clinical isolate, CDC1551 in 2002. Since then, the genomic sequences of a number of other strains have become available making it one of the better studied pathogenic bacterial species at the genomic level. However, annotation of its genome remains challenging because of high GC content and dissimilarity to other model prokaryotes. To this end, we carried out an in-depth proteogenomic analysis of the M. tuberculosis H37Rv strain using Fourier transform mass spectrometry with high resolution at both MS and tandem MS levels. In all, we identified 3176 proteins from Mycobacterium tuberculosis representing ~80% of its total predicted gene count. In addition to protein database search, we carried out a genome database search, which led to identification of ~250 novel peptides. Based on these novel genome search-specific peptides, we discovered 41 novel protein coding genes in the H37Rv genome. Using peptide evidence and alternative gene prediction tools, we also corrected 79 gene models. Finally, mass spectrometric data from N terminus-derived peptides confirmed 727 existing annotations for translational start sites while correcting those for 33 proteins. We report creation of a high confidence set of protein coding regions in Mycobacterium tuberculosis genome obtained by high resolution tandem mass-spectrometry at both precursor and fragment detection steps for the first time. This proteogenomic approach should be generally applicable to other organisms whose genomes have already been sequenced for obtaining a more accurate catalogue of protein-coding genes.     

Evidence of the formation of direct covalent adducts of primaquine, 2-tert-butylprimaquine (NP-96) and monohydroxy metabolite of NP-96 with glutathione and N-acetylcysteine

2-tert-Butylprimaquine (NP-96) is a novel quinoline anti-malarial compound with superior therapeutic profile than primaquine (PQ). Moreover, it is the first 8-aminoquinoline that is established to be devoid of methemoglobin toxicity. The purpose of the present study was to investigate covalent adduct formation tendency of PQ, NP-96 and their phase I metabolites with glutathione (GSH) and N-acetylcysteine (NAc). For the same, the two compounds were incubated in human and rat liver microsomes in the presence of trapping agents and NADPH. In a control set, NADPH was excluded, while a blank was also studied that was devoid of both NADPH and microsomes. The components in the reaction mixtures were initially separated on a C-18 column (250 mm×4.6mm, 5 μm) using a mobile phase composed of acetonitrile and 10 mM ammonium acetate in a gradient mode. The samples were then subjected to LC-MS(n) and LC-HR-MS analyses, and data were collected in full scan MS, data dependent MS/MS, targeted MS/MS, neutral loss scan (NLS) and accurate mass (MS/TOF) modes. In a significant finding, both PQ and NP-96 themselves showed potential to bind covalently with GSH and NAc, as adducts were observed even in the control and blank incubations. Intense peaks corresponding to covalent adduct of mono-hydroxy metabolite of NP-96 with GSH and NAc were also detected in NADPH supplemented reaction solution.     

Biometry based ageing of nestling Indian Spotted Owlets ( Athene brama brama)

Biometric analysis helps in sex differentiation, understanding development and for studies of avian biology such as foraging ecology, evolutionary ecology, and survivorship. We suggest that biometry can also be a reliable, practical and inexpensive tool to determine the age of nestlings in the field by non-invasive methods. As an example we studied the biometry of wing, culmen, talon, tarsus and body mass of nestling southern Indian Spotted Owlets (Athene brama brama). Based on the growth pattern analysis using logistic growth model, discriminant analysis and CHAID (Chi-squared Automatic Interaction Detection) based decision tree, we show that biometry of nestling Spotted Owlets is an easy, reliable and inexpensive method to determine nestling age and to assess growth rate and relative nutritional status. These biometric parameters also allow us to predict their ability to initiate first flight from the nest site. This method is described here for the first time and we postulate that such charts can be devised for other avian species as well, so as to assist conservation biologists and bird rescuers.     

Cell physiology rather than enzyme kinetics can determine the efficiency of cytochrome P450-catalyzed C–H-oxyfunctionalization

Cell physiology is a critical factor determining the efficiency of reactions performed by microbial biocatalysts. In order to develop an efficient biotransformation procedure for the hydroxylation of (S)-limonene to (S)-perillyl alcohol by recombinant Pseudomonas putida cells harboring the cytochrome P450 monooxygenase CYP153A6, physiological parameters were optimized. The previously reported synthesis of (S)-perillyl alcohol by P. putida GPo12 was based on complex and sensitive octane feeding strategies (van Beilen et al. in Appl Environ Microbiol 71:1737-1744, 2005), indicating the pivotal role of cell physiology. In contrast to previous findings, the screening of different carbon sources showed that glycerol and citrate are suitable alternatives to octane allowing high specific limonene hydroxylation activities. The use of P. putida KT2440 as an alternative host strain and citrate as the carbon source improved practical handling and allowed a 7.5-fold increase of the specific activity (to 22.6 U g (CDW) (-1) ). In two-liquid-phase biotransformations, 4.3 g of (S)-perillyl alcohol L (tot) (-1) were produced in 24 h, representing a sixfold improvement in productivity compared to previously reported results. It is concluded that, for selective cytochrome P450-based hydrocarbon oxyfunctionalizations by means of living microbial cells, the relationship between cell physiology and the target biotransformation is crucial, and that understanding the relationship should guide biocatalyst and bioprocess design.     

Cypermethrin exposure leads to regulation of proteins expression involved in neoplastic transformation in mouse skin

Cypermethrin, a synthetic pyrethroid insecticide is shown to exert carcinogenic effects in rodents; however, its underlying mechanism remains elusive. Here, we showed the effect of cypermethrin on protein expression involved in neoplastic transformation in mouse skin. Comparative protein expression profiles between untreated control and cypermethrin-treated mouse skin were explored using 2-DE. A total of 27 spots that were statistically significant (p<0.05) and differentially expressed in response to cypermethrin exposure were identified by MALDI-TOF/TOF and LC-MS/MS. Among them, six up-regulated proteins (carbonic anhydrase 3 (Ca 3), Hsp-27, S100A6, galectin-7, S100A9, S100A11) and one down-regulated protein (superoxide dismutase [Cu-Zn] (Sod 1)) are associated with cancer-related key processes. These selected dysregulated proteins were further validated in 2-DE gels of mouse skin treated with known tumorigens (benzo-[a]-pyrene, 12-O-tetradecanoyl-phorbol-13-acetate and mezerein), respectively. Comparative studies showed that Ca 3, S100A6, S100A9, S100A11 and Sod 1 are specific for stages of development and progression of tumors whereas Hsp-27 and galectin-7 are specific for tumor promotion stage by cypermethrin in mouse skin. Furthermore, these chosen proteins confirmed by Western blotting and immunofluorescence staining were consistent with changes in 2-DE check. This proteomic investigation for the first time provides key proteins that will contribute in understanding the mechanism behind cypermethrin-induced neoplastic transformation.     

Effects of transmitters and amyloid-beta peptide on calcium signals in rat cortical astrocytes: Fura-2AM measurements and stochastic model simulations

Background

To better understand the complex molecular level interactions seen in the pathogenesis of Alzheimer''s disease, the results of the wet-lab and clinical studies can be complemented by mathematical models. Astrocytes are known to become reactive in Alzheimer''s disease and their ionic equilibrium can be disturbed by interaction of the released and accumulated transmitters, such as serotonin, and peptides, including amyloid- peptides (A). We have here studied the effects of small amounts of A25–35 fragments on the transmitter-induced calcium signals in astrocytes by Fura-2AM fluorescence measurements and running simulations of the detected calcium signals.

Methodology/Principal Findings

Intracellular calcium signals were measured in cultured rat cortical astrocytes following additions of serotonin and glutamate, or either of these transmitters together with A25–35. A25–35 increased the number of astrocytes responding to glutamate and exceedingly increased the magnitude of the serotonin-induced calcium signals. In addition to A25–35-induced effects, the contribution of intracellular calcium stores to calcium signaling was tested. When using higher stimulus frequency, the subsequent calcium peaks after the initial peak were of lower amplitude. This may indicate inadequate filling of the intracellular calcium stores between the stimuli. In order to reproduce the experimental findings, a stochastic computational model was introduced. The model takes into account the major mechanisms known to be involved in calcium signaling in astrocytes. Model simulations confirm the principal experimental findings and show the variability typical for experimental measurements.

Conclusions/Significance

Nanomolar A25–35 alone does not cause persistent change in the basal level of calcium in astrocytes. However, even small amounts of A25–35, together with transmitters, can have substantial synergistic effects on intracellular calcium signals. Computational modeling further helps in understanding the mechanisms associated with intracellular calcium oscillations. Modeling the mechanisms is important, as astrocytes have an essential role in regulating the neuronal microenvironment of the central nervous system.     

From molecular signal activation to locomotion: an integrated, multiscale analysis of cell motility on defined matrices

The adhesion, mechanics, and motility of eukaryotic cells are highly sensitive to the ligand density and stiffness of the extracellular matrix (ECM). This relationship bears profound implications for stem cell engineering, tumor invasion and metastasis. Yet, our quantitative understanding of how ECM biophysical properties, mechanotransductive signals, and assembly of contractile and adhesive structures collude to control these cell behaviors remains extremely limited. Here we present a novel multiscale model of cell migration on ECMs of defined biophysical properties that integrates local activation of biochemical signals with adhesion and force generation at the cell-ECM interface. We capture the mechanosensitivity of individual cellular components by dynamically coupling ECM properties to the activation of Rho and Rac GTPases in specific portions of the cell with actomyosin contractility, cell-ECM adhesion bond formation and rupture, and process extension and retraction. We show that our framework is capable of recreating key experimentally-observed features of the relationship between cell migration and ECM biophysical properties. In particular, our model predicts for the first time recently reported transitions from filopodial to "stick-slip" to gliding motility on ECMs of increasing stiffness, previously observed dependences of migration speed on ECM stiffness and ligand density, and high-resolution measurements of mechanosensitive protrusion dynamics during cell motility we newly obtained for this study. It also relates the biphasic dependence of cell migration speed on ECM stiffness to the tendency of the cell to polarize. By enabling the investigation of experimentally-inaccessible microscale relationships between mechanotransductive signaling, adhesion, and motility, our model offers new insight into how these factors interact with one another to produce complex migration patterns across a variety of ECM conditions.