Gravitational waves in Einstein-{\ae}ther and generalized TeVeS theory after GW170817

In this work, we discuss the polarization contents of Einstein-\ae ther theory and the generalized tensor-vector-scalar (TeVeS) theory, as both theories have a normalized timelike vector field. We derive the linearized equations of motion around the flat spacetime background using the gauge-invariant variables to easily separate physical degrees of freedom. We find the plane wave solutions are then found, and identify the polarizations by examining the geodesic deviation equations. We find that there are five polarizations in Einstein-\ae ther theory and six polarizations in the generalized TeVeS theory. In particular, the transverse breathing mode is mixed with the pure longitudinal mode. We also discuss the experimental tests of the extra polarizations in Einstein-\ae ther theory using pulsar timing arrays combined with the gravitational-wave speed bound derived from the observations on GW 170817 and GRB 170817A. It turns out that it might be difficult to use pulsar timing arrays to distinguish different polarizations in Einstein-\ae ther theory. The same speed bound also forces one of the propagating modes in the generalized TeVeS theory to travel much faster than the speed of light. Since the strong coupling problem does not exist in some parameter subspaces, the generalized TeVeS theory is excluded in these parameter subspaces.Comment: 33 pages, 7 figure

Unraveling acetogen gas fermentation using quantitative systems biology

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Understanding the role of interactions between host and Mycobacterium tuberculosis under hypoxic condition: an in silico approach

Mycobacterium tuberculosis infection in humans is often associated with extended period of latency. To adapt to the hostile hypoxic environment inside a macrophage, M. tuberculosis cells undergo several physiological and metabolic changes. Previous studies have mostly focused on inspecting individual facets of this complex process. In order to gain deeper insights into the infection process and to understand the coordination among different regulatory/ metabolic pathways in the pathogen, the current in silico study investigates three aspects, namely, (i) host-pathogen interactions (HPIs) between human and M. tuberculosis proteins, (ii) gene regulatory network pertaining to adaptation of M. tuberculosis to hypoxia and (iii) alterations in M. tuberculosis metabolism under hypoxic condition. Subsequently, cross-talks between these components have been probed to evaluate possible gene-regulatory events as well as HPIs which are likely to drive metabolic changes during pathogen's adaptation to the intra-host hypoxic environment.The newly identified HPIs suggest the pathogen's ability to subvert host mediated reactive oxygen intermediates/ reactive nitrogen intermediates (ROI/ RNI) stress as well as their potential role in modulating host cell cycle and cytoskeleton structure. The results also indicate a significantly pronounced effect of HPIs on hypoxic metabolism of M. tuberculosis. Findings from the current study underscore the necessity of investigating the infection process from a systems-level perspective incorporating different facets of intra-cellular survival of the pathogen.The comprehensive host-pathogen interaction network, a Boolean model of M. tuberculosis H37Rv (Mtb) hypoxic gene-regulation, as well as a genome scale metabolic model of Mtb, built for this study are expected to be useful resources for future studies on tuberculosis infection

multiTFA:A python package for multi-variate thermodynamics-based flux analysis

MOTIVATION: We achieve a significant improvement in thermodynamic-based flux analysis (TFA) by introducing multivariate treatment of thermodynamic variables and leveraging component contribution, the state-of-the-art implementation of the group contribution methodology. Overall, the method greatly reduces the uncertainty of thermodynamic variables. RESULTS: We present multiTFA, a Python implementation of our framework. We evaluated our application using the core Escherichia coli model and achieved a median reduction of 6.8 kJ/mol in reaction Gibbs free energy ranges, while three out of 12 reactions in glycolysis changed from reversible to irreversible. AVAILABILITY AND IMPLEMENTATION: Our framework along with documentation is available on https://github.com/biosustain/multitfa. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online

Additional file 14: of Understanding the role of interactions between host and Mycobacterium tuberculosis under hypoxic condition: an in silico approach

Significantly enriched GO biological process terms in the set of M. tuberculosis H37Rv proteins, which were observed to be ‘active’/ switched ON in the ‘hypoxic’ stable state. This stable state was obtained through simulation of Boolean model corresponding to the gene regulatory network collated in the present study. (XLSX 10 kb

Additional file 1: of Understanding the role of interactions between host and Mycobacterium tuberculosis under hypoxic condition: an in silico approach

Details of the method used for prediction of host-pathogen interactions (HPIs) between human and M. tuberculosis H37Rv (Mtb) proteins. (DOCX 96 kb

Additional file 5: of Understanding the role of interactions between host and Mycobacterium tuberculosis under hypoxic condition: an in silico approach

List of genes involved in hypoxic response regulation of M. tuberculosis H37Rv. (XLSX 14 kb

Additional file 15: of Understanding the role of interactions between host and Mycobacterium tuberculosis under hypoxic condition: an in silico approach

Details of the methodology adopted for identifying the shortest-paths among (A) the HPI-network, (B) the M. tuberculosis H37Rv hypoxic- gene regulatory network, and (C) the hypoxic-metabolism network of M. tuberculosis H37Rv. (DOCX 19 kb

Additional file 12: of Understanding the role of interactions between host and Mycobacterium tuberculosis under hypoxic condition: an in silico approach

List of metabolic reactions in M. tuberculosis H37Rv which were significantly perturbed (over 2-fold) during hypoxia as compared to aerobic condition (results obtained through FBA simulations) (.xlsx format). (XLSX 14 kb

Additional file 3: of Understanding the role of interactions between host and Mycobacterium tuberculosis under hypoxic condition: an in silico approach

Perturbations in (A) M. tuberculosis H37Rv (Mtb) and (B) human gene expression at different time-points post infection. The mean of expression values of a gene from different experimental datasets (collected from literature) has been considered. Expression values exhibiting at least 2-fold differential expression are indicated. (XLSX 2703 kb