139 research outputs found
MultiMetEval: comparative and multi-objective analysis of genome-scale metabolic models
Comparative metabolic modelling is emerging as a novel field, supported by the development of reliable and standardized approaches for constructing genome-scale metabolic models in high throughput. New software solutions are needed to allow efficient comparative analysis of multiple models in the context of multiple cellular objectives. Here, we present the user-friendly software framework Multi-Metabolic Evaluator (MultiMetEval), built upon SurreyFBA, which allows the user to compose collections of metabolic models that together can be subjected to flux balance analysis. Additionally, MultiMetEval implements functionalities for multi-objective analysis by calculating the Pareto front between two cellular objectives. Using a previously generated dataset of 38 actinobacterial genome-scale metabolic models, we show how these approaches can lead to exciting novel insights. Firstly, after incorporating several pathways for the biosynthesis of natural products into each of these models, comparative flux balance analysis predicted that species like Streptomyces that harbour the highest diversity of secondary metabolite biosynthetic gene clusters in their genomes do not necessarily have the metabolic network topology most suitable for compound overproduction. Secondly, multi-objective analysis of biomass production and natural product biosynthesis in these actinobacteria shows that the well-studied occurrence of discrete metabolic switches during the change of cellular objectives is inherent to their metabolic network architecture. Comparative and multi-objective modelling can lead to insights that could not be obtained by normal flux balance analyses. MultiMetEval provides a powerful platform that makes these analyses straightforward for biologists. Sources and binaries of MultiMetEval are freely available from https://github.com/PiotrZakrzewski/MetEvβal/downloads
Large tunable valley splitting in edge-free graphene quantum dots on boron nitride
Coherent manipulation of binary degrees of freedom is at the heart of modern
quantum technologies. Graphene offers two binary degrees: the electron spin and
the valley. Efficient spin control has been demonstrated in many solid state
systems, while exploitation of the valley has only recently been started, yet
without control on the single electron level. Here, we show that van-der Waals
stacking of graphene onto hexagonal boron nitride offers a natural platform for
valley control. We use a graphene quantum dot induced by the tip of a scanning
tunneling microscope and demonstrate valley splitting that is tunable from -5
to +10 meV (including valley inversion) by sub-10-nm displacements of the
quantum dot position. This boosts the range of controlled valley splitting by
about one order of magnitude. The tunable inversion of spin and valley states
should enable coherent superposition of these degrees of freedom as a first
step towards graphene-based qubits
Probing the Role of Protein Surface Charge in the Activation of PrfA, the Central Regulator of Listeria monocytogenes Pathogenesis
Listeria monocytogenes is a food-borne intracellular bacterial pathogen capable of causing serious human disease. L. monocytogenes survival within mammalian cells depends upon the synthesis of a number of secreted virulence factors whose expression is regulated by the transcriptional activator PrfA. PrfA becomes activated following bacterial entry into host cells where it induces the expression of gene products required for bacterial spread to adjacent cells. Activation of PrfA appears to occur via the binding of a small molecule cofactor whose identity remains unknown. Electrostatic modeling of the predicted PrfA cofactor binding pocket revealed a highly positively charged region with two lysine residues, K64 and K122, located at the edge of the pocket and another (K130) located deep within the interior. Mutational analysis of these residues indicated that K64 and K122 contribute to intracellular activation of PrfA, whereas a K130 substitution abolished protein activity. The requirement of K64 and K122 for intracellular PrfA activation could be bypassed via the introduction of the prfA G145S mutation that constitutively activates PrfA in the absence of cofactor binding. Our data indicate that the positive charge of the PrfA binding pocket contributes to intracellular activation of PrfA, presumably by facilitating binding of an anionic cofactor
Constitutive Activation of PrfA Tilts the Balance of Listeria monocytogenes Fitness Towards Life within the Host versus Environmental Survival
PrfA is a key regulator of Listeria monocytogenes pathogenesis and induces the expression of multiple virulence factors within the infected host. PrfA is post-translationally regulated such that the protein becomes activated upon bacterial entry into the cell cytosol. The signal that triggers PrfA activation remains unknown, however mutations have been identified (prfA* mutations) that lock the protein into a high activity state. In this report we examine the consequences of constitutive PrfA activation on L. monocytogenes fitness both in vitro and in vivo. Whereas prfA* mutants were hyper-virulent during animal infection, the mutants were compromised for fitness in broth culture and under conditions of stress. Broth culture prfA*-associated fitness defects were alleviated when glycerol was provided as the principal carbon source; under these conditions prfA* mutants exhibited a competitive advantage over wild type strains. Glycerol and other three carbon sugars have been reported to serve as primary carbon sources for L. monocytogenes during cytosolic growth, thus prfA* mutants are metabolically-primed for replication within eukaryotic cells. These results indicate the critical need for environment-appropriate regulation of PrfA activity to enable L. monocytogenes to optimize bacterial fitness inside and outside of host cells
Thermal Properties of Graphene, Carbon Nanotubes and Nanostructured Carbon Materials
Recent years witnessed a rapid growth of interest of scientific and
engineering communities to thermal properties of materials. Carbon allotropes
and derivatives occupy a unique place in terms of their ability to conduct
heat. The room-temperature thermal conductivity of carbon materials span an
extraordinary large range - of over five orders of magnitude - from the lowest
in amorphous carbons to the highest in graphene and carbon nanotubes. I review
thermal and thermoelectric properties of carbon materials focusing on recent
results for graphene, carbon nanotubes and nanostructured carbon materials with
different degrees of disorder. A special attention is given to the unusual size
dependence of heat conduction in two-dimensional crystals and, specifically, in
graphene. I also describe prospects of applications of graphene and carbon
materials for thermal management of electronics.Comment: Review Paper; 37 manuscript pages; 4 figures and 2 boxe
Impact of PET acquisition durations on image quality and lesion detectability in whole-body 68Ga-PSMA PET-MRI
Integration of CT urography improves diagnostic confidence of 68Ga-PSMA-11 PET/CT in prostate cancer patients
Intracellular Vesicles as Reproduction Elements in Cell Wall-Deficient L-Form Bacteria
Cell wall-deficient bacteria, or L-forms, represent an extreme example of bacterial plasticity. Stable L-forms can multiply and propagate indefinitely in the absence of a cell wall. Data presented here are consistent with the model that intracellular vesicles in Listeria monocytogenes L-form cells represent the actual viable reproductive elements. First, small intracellular vesicles are formed along the mother cell cytoplasmic membrane, originating from local phospholipid accumulation. During growth, daughter vesicles incorporate a small volume of the cellular cytoplasm, and accumulate within volume-expanding mother cells. Confocal Raman microspectroscopy demonstrated the presence of nucleic acids and proteins in all intracellular vesicles, but only a fraction of which reveals metabolic activity. Following collapse of the mother cell and release of the daughter vesicles, they can establish their own membrane potential required for respiratory and metabolic processes. Premature depolarization of the surrounding membrane promotes activation of daughter cell metabolism prior to release. Based on genome resequencing of L-forms and comparison to the parental strain, we found no evidence for predisposing mutations that might be required for L-form transition. Further investigations revealed that propagation by intracellular budding not only occurs in Listeria species, but also in L-form cells generated from different Enterococcus species. From a more general viewpoint, this type of multiplication mechanism seems reminiscent of the physicochemical self-reproducing properties of abiotic lipid vesicles used to study the primordial reproduction pathways of putative prokaryotic precursor cells
Animal model integration to AutDB, a genetic database for autism
<p>Abstract</p> <p>Background</p> <p>In the post-genomic era, multi-faceted research on complex disorders such as autism has generated diverse types of molecular information related to its pathogenesis. The rapid accumulation of putative candidate genes/loci for Autism Spectrum Disorders (ASD) and ASD-related animal models poses a major challenge for systematic analysis of their content. We previously created the Autism Database (AutDB) to provide a publicly available web portal for ongoing collection, manual annotation, and visualization of genes linked to ASD. Here, we describe the design, development, and integration of a new module within AutDB for ongoing collection and comprehensive cataloguing of ASD-related animal models.</p> <p>Description</p> <p>As with the original AutDB, all data is extracted from published, peer-reviewed scientific literature. Animal models are annotated with a new standardized vocabulary of phenotypic terms developed by our researchers which is designed to reflect the diverse clinical manifestations of ASD. The new Animal Model module is seamlessly integrated to AutDB for dissemination of diverse information related to ASD. Animal model entries within the new module are linked to corresponding candidate genes in the original "Human Gene" module of the resource, thereby allowing for cross-modal navigation between gene models and human gene studies. Although the current release of the Animal Model module is restricted to mouse models, it was designed with an expandable framework which can easily incorporate additional species and non-genetic etiological models of autism in the future.</p> <p>Conclusions</p> <p>Importantly, this modular ASD database provides a platform from which data mining, bioinformatics, and/or computational biology strategies may be adopted to develop predictive disease models that may offer further insights into the molecular underpinnings of this disorder. It also serves as a general model for disease-driven databases curating phenotypic characteristics of corresponding animal models.</p
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