Metabolic investigation of host/pathogen interaction using MS2-infected Escherichia coli

<p>Abstract</p> <p>Background</p> <p>RNA viruses are responsible for a variety of illnesses among people, including but not limited to the common cold, the flu, HIV, and ebola. Developing new drugs and new strategies for treating diseases caused by these viruses can be an expensive and time-consuming process. Mathematical modeling may be used to elucidate host-pathogen interactions and highlight potential targets for drug development, as well providing the basis for optimizing patient treatment strategies. The purpose of this work was to determine whether a genome-scale modeling approach could be used to understand how metabolism is impacted by the host-pathogen interaction during a viral infection. <it>Escherichia coli</it>/MS2 was used as the host-pathogen model system as MS2 is easy to work with, harmless to humans, but shares many features with eukaryotic viruses. In addition, the genome-scale metabolic model of <it>E. coli </it>is the most comprehensive model at this time.</p> <p>Results</p> <p>Employing a metabolic modeling strategy known as "flux balance analysis" coupled with experimental studies, we were able to predict how viral infection would alter bacterial metabolism. Based on our simulations, we predicted that cell growth and biosynthesis of the cell wall would be halted. Furthermore, we predicted a substantial increase in metabolic activity of the pentose phosphate pathway as a means to enhance viral biosynthesis, while a break down in the citric acid cycle was predicted. Also, no changes were predicted in the glycolytic pathway.</p> <p>Conclusions</p> <p>Through our approach, we have developed a technique of modeling virus-infected host metabolism and have investigated the metabolic effects of viral infection. These studies may provide insight into how to design better drugs. They also illustrate the potential of extending such metabolic analysis to higher order organisms, including humans.</p

The Tarantula Massive Binary Monitoring: I. Observational campaign and OB-type spectroscopic binaries

© ESO, 2017.Context. Massive binaries play a crucial role in the Universe. Knowing the distributions of their orbital parameters is important for a wide range of topics from stellar feedback to binary evolution channels and from the distribution of supernova types to gravitational wave progenitors, yet no direct measurements exist outside the Milky Way. Aims. The Tarantula Massive Binary Monitoring project was designed to help fill this gap by obtaining multi-epoch radial velocity (RV) monitoring of 102 massive binaries in the 30 Doradus region. Methods. In this paper we analyze 32 FLAMES/GIRAFFE observations of 93 O- and 7 B-type binaries. We performed a Fourier analysis and obtained orbital solutions for 82 systems: 51 single-lined (SB1) and 31 double-lined (SB2) spectroscopic binaries. Results. Overall, the binary fraction and orbital properties across the 30 Doradus region are found to be similar to existing Galactic samples. This indicates that within these domains environmental effects are of second order in shaping the properties of massive binary systems. A small difference is found in the distribution of orbital periods, which is slightly flatter (in log space) in 30 Doradus than in the Galaxy, although this may be compatible within error estimates and differences in the fitting methodology. Also, orbital periods in 30 Doradus can be as short as 1.1 d, somewhat shorter than seen in Galactic samples. Equal mass binaries (q> 0.95) in 30 Doradus are all found outside NGC 2070, the central association that surrounds R136a, the very young and massive cluster at 30 Doradus's core. Most of the differences, albeit small, are compatible with expectations from binary evolution. One outstanding exception, however, is the fact that earlier spectral types (O2-O7) tend to have shorter orbital periods than later spectral types (O9.2-O9.7). Conclusions. Our results point to a relative universality of the incidence rate of massive binaries and their orbital properties in the metallicity range from solar (Z) to about half solar. This provides the first direct constraints on massive binary properties in massive star-forming galaxies at the Universe's peak of star formation at redshifts z ~ 1 to 2 which are estimated to have Z 0.5 Z

Microbial Maintenance: A Critical Review on Its Quantification

Microbial maintenance is an important concept in microbiology. Its quantification, however, is a subject of continuous debate, which seems to be caused by (1) its definition, which includes nongrowth components other than maintenance; (2) the existence of partly overlapping concepts; (3) the evolution of variables as constants; and (4) the neglect of cell death in microbial dynamics. The two historically most important parameters describing maintenance, the specific maintenance rate and the maintenance coefficient, are based on partly different nongrowth components. There is thus no constant relation between these parameters and previous equations on this subject are wrong. In addition, the partial overlap between these parameters does not allow the use of a simple combination of these parameters. This also applies for combinations of a threshold concentration with one of the other estimates of maintenance. Maintenance estimates should ideally explicitly describe each nongrowth component. A conceptual model is introduced that describes their relative importance and reconciles the various concepts and definitions. The sensitivity of maintenance on underlying components was analyzed and indicated that overall maintenance depends nonlinearly on relative death rates, relative growth rates, growth yield, and endogenous metabolism. This quantitative sensitivity analysis explains the felt need to develop growth-dependent adaptations of existing maintenance parameters, and indicates the importance of distinguishing the various nongrowth components. Future experiments should verify the sensitivity of maintenance components under cellular and environmental conditions

Pyrroloquinoline quinone, a chemotactic attractant for Escherichia coli.

Escherichia coli is attracted by pyrroloquinoline quinone (PQQ), and chemotaxis toward glucose is enhanced by the presence of PQQ. A ptsI mutant showed no chemotactic response to either glucose or PQQ alone but did show a chemotactic response to a mixture of glucose and PQQ. A strain lacking the methylated chemotaxis receptor protein Tar showed no response to PQQ

Enzymatic synthesis of L-amino acids

Leuchtenberger W. Enzymatic synthesis of L-amino acids. In: Neijssel OM, van der Meer R .R, Luyben KCAM, Nederlandse Biotechnologische Vereniging, eds. Proc. 4th European Congress on Biotechnology 1987. Vol 4. Amsterdam: Elsevier; 1987: 701-711