Effect of Hydrogen Peroxide on Immersion Challenge of Rainbow Trout Fry with Flavobacterium psychrophilum

An experimental model for immersion challenge of rainbow trout fry (Oncorhynchus mykiss) with Flavobacterium psychrophilum, the causative agent of rainbow trout fry syndrome and bacterial cold water disease was established in the present study. Although injection-based infection models are reliable and produce high levels of mortality attempts to establish a reproducible immersion model have been less successful. Various concentrations of hydrogen peroxide (H₂O₂) were evaluated before being used as a pre-treatment stressor prior to immersion exposure to F. psychrophilum. H₂O₂ accelerated the onset of mortality and increased mortality approximately two-fold; from 9.1% to 19.2% and from 14.7% to 30.3% in two separate experiments. Clinical signs observed in the infected fish corresponded to symptoms characteristically seen during natural outbreaks. These findings indicate that pre-treatment with H₂O₂ can increase the level of mortality in rainbow trout fry after exposure to F. psychrophilum

Structural and functional analysis of cellular networks with CellNetAnalyzer

BACKGROUND: Mathematical modelling of cellular networks is an integral part of Systems Biology and requires appropriate software tools. An important class of methods in Systems Biology deals with structural or topological (parameter-free) analysis of cellular networks. So far, software tools providing such methods for both mass-flow (metabolic) as well as signal-flow (signalling and regulatory) networks are lacking. RESULTS: Herein we introduce CellNetAnalyzer, a toolbox for MATLAB facilitating, in an interactive and visual manner, a comprehensive structural analysis of metabolic, signalling and regulatory networks. The particular strengths of CellNetAnalyzer are methods for functional network analysis, i.e. for characterising functional states, for detecting functional dependencies, for identifying intervention strategies, or for giving qualitative predictions on the effects of perturbations. CellNetAnalyzer extends its predecessor FluxAnalyzer (originally developed for metabolic network and pathway analysis) by a new modelling framework for examining signal-flow networks. Two of the novel methods implemented in CellNetAnalyzer are discussed in more detail regarding algorithmic issues and applications: the computation and analysis (i) of shortest positive and shortest negative paths and circuits in interaction graphs and (ii) of minimal intervention sets in logical networks. CONCLUSION: CellNetAnalyzer provides a single suite to perform structural and qualitative analysis of both mass-flow- and signal-flow-based cellular networks in a user-friendly environment. It provides a large toolbox with various, partially unique, functions and algorithms for functional network analysis.CellNetAnalyzer is freely available for academic use

Potentiating antibacterial activity by predictably enhancing endogenous microbial ROS production

The ever-increasing incidence of antibiotic-resistant infections combined with a weak pipeline of new antibiotics has created a global public health crisis1. Accordingly, novel strategies for enhancing our antibiotic arsenal are needed. As antibiotics kill bacteria in part by inducing reactive oxygen species (ROS)2–4, we reasoned that targeting microbial ROS production might potentiate antibiotic activity. Here we show that ROS production can be predictably enhanced in Escherichia coli, increasing the bacteria’s susceptibility to oxidative attack. We developed an ensemble, genome-scale metabolic modeling approach capable of predicting ROS production in E. coli. The metabolic network was systematically perturbed and its flux distribution analyzed to identify targets predicted to increase ROS production. In silico–predicted targets were experimentally validated and shown to confer increased susceptibility to oxidants. Validated targets also increased susceptibility to killing by antibiotics. This work establishes a systems-based method to tune ROS production in bacteria and demonstrates that increased microbial ROS production can potentiate killing by oxidants and antibiotics

Evidence for a Grooming Claw in a North American Adapiform Primate: Implications for Anthropoid Origins

Among fossil primates, the Eocene adapiforms have been suggested as the closest relatives of living anthropoids (monkeys, apes, and humans). Central to this argument is the form of the second pedal digit. Extant strepsirrhines and tarsiers possess a grooming claw on this digit, while most anthropoids have a nail. While controversial, the possible presence of a nail in certain European adapiforms has been considered evidence for anthropoid affinities. Skeletons preserved well enough to test this idea have been lacking for North American adapiforms. Here, we document and quantitatively analyze, for the first time, a dentally associated skeleton of Notharctus tenebrosus from the early Eocene of Wyoming that preserves the complete bones of digit II in semi-articulation. Utilizing twelve shape variables, we compare the distal phalanges of Notharctus tenebrosus to those of extant primates that bear nails (n = 21), tegulae (n = 4), and grooming claws (n = 10), and those of non-primates that bear claws (n = 7). Quantitative analyses demonstrate that Notharctus tenebrosus possessed a grooming claw with a surprisingly well-developed apical tuft on its second pedal digit. The presence of a wide apical tuft on the pedal digit II of Notharctus tenebrosus may reflect intermediate morphology between a typical grooming claw and a nail, which is consistent with the recent hypothesis that loss of a grooming claw occurred in a clade containing adapiforms (e.g. Darwinius masillae) and anthropoids. However, a cladistic analysis including newly documented morphologies and thorough representation of characters acknowledged to have states constituting strepsirrhine, haplorhine, and anthropoid synapomorphies groups Notharctus tenebrosus and Darwinius masillae with extant strepsirrhines rather than haplorhines suggesting that the form of pedal digit II reflects substantial homoplasy during the course of early primate evolution

Genetic Co-Occurrence Network across Sequenced Microbes

The phenotype of any organism on earth is, in large part, the consequence of interplay between numerous gene products encoded in the genome, and such interplay between gene products affects the evolutionary fate of the genome itself through the resulting phenotype. In this regard, contemporary genomes can be used as molecular records that reveal associations of various genes working in their natural lifestyles. By analyzing thousands of orthologs across ~600 bacterial species, we constructed a map of gene-gene co-occurrence across much of the sequenced biome. If genes preferentially co-occur in the same organisms, they were called herein correlogs; in the opposite case, called anti-correlogs. To quantify correlogy and anti-correlogy, we alleviated the contribution of indirect correlations between genes by adapting ideas developed for reverse engineering of transcriptional regulatory networks. Resultant correlogous associations are highly enriched for physically interacting proteins and for co-expressed transcripts, clearly differentiating a subgroup of functionally-obligatory protein interactions from conditional or transient interactions. Other biochemical and phylogenetic properties were also found to be reflected in correlogous and anti-correlogous relationships. Additionally, our study elucidates the global organization of the gene association map, in which various modules of correlogous genes are strikingly interconnected by anti-correlogous crosstalk between the modules. We then demonstrate the effectiveness of such associations along different domains of life and environmental microbial communities. These phylogenetic profiling approaches infer functional coupling of genes regardless of mechanistic details, and may be useful to guide exogenous gene import in synthetic biology.Comment: Supporting information is available at PLoS Computational Biolog

Insertion of an Esterase Gene into a Specific Locust Pathogen (Metarhizium acridum) Enables It to Infect Caterpillars

An enduring theme in pathogenic microbiology is poor understanding of the mechanisms of host specificity. Metarhizium is a cosmopolitan genus of invertebrate pathogens that contains generalist species with broad host ranges such as M. robertsii (formerly known as M. anisopliae var. anisopliae) as well as specialists such as the acridid-specific grasshopper pathogen M. acridum. During growth on caterpillar (Manduca sexta) cuticle, M. robertsii up-regulates a gene (Mest1) that is absent in M. acridum and most other fungi. Disrupting M. robertsii Mest1 reduced virulence and overexpression increased virulence to caterpillars (Galleria mellonella and M. sexta), while virulence to grasshoppers (Melanoplus femurrubrum) was unaffected. When Mest1 was transferred to M. acridum under control of its native M. robertsii promoter, the transformants killed and colonized caterpillars in a similar fashion to M. robertsii. MEST1 localized exclusively to lipid droplets in M. robertsii conidia and infection structures was up-regulated during nutrient deprivation and had esterase activity against lipids with short chain fatty acids. The mobilization of stored lipids was delayed in the Mest1 disruptant mutant. Overall, our results suggest that expression of Mest1 allows rapid hydrolysis of stored lipids, and promotes germination and infection structure formation by M. robertsii during nutrient deprivation and invasion, while Mest1 expression in M. acridum broadens its host range by bypassing the regulatory signals found on natural hosts that trigger the mobilization of endogenous nutrient reserves. This study suggests that speciation in an insect pathogen could potentially be driven by host shifts resulting from changes in a single gene

Information Routing Driven by Background Chatter in a Signaling Network

Living systems are capable of processing multiple sources of information simultaneously. This is true even at the cellular level, where not only coexisting signals stimulate the cell, but also the presence of fluctuating conditions is significant. When information is received by a cell signaling network via one specific input, the existence of other stimuli can provide a background activity –or chatter– that may affect signal transmission through the network and, therefore, the response of the cell. Here we study the modulation of information processing by chatter in the signaling network of a human cell, specifically, in a Boolean model of the signal transduction network of a fibroblast. We observe that the level of external chatter shapes the response of the system to information carrying signals in a nontrivial manner, modulates the activity levels of the network outputs, and effectively determines the paths of information flow. Our results show that the interactions and node dynamics, far from being random, confer versatility to the signaling network and allow transitions between different information-processing scenarios

Contrasted Effects of Diversity and Immigration on Ecological Insurance in Marine Bacterioplankton Communities

The ecological insurance hypothesis predicts a positive effect of species richness on ecosystem functioning in a variable environment. This effect stems from temporal and spatial complementarity among species within metacommunities coupled with optimal levels of dispersal. Despite its importance in the context of global change by human activities, empirical evidence for ecological insurance remains scarce and controversial. Here we use natural aquatic bacterial communities to explore some of the predictions of the spatial and temporal aspects of the ecological insurance hypothesis. Addressing ecological insurance with bacterioplankton is of strong relevance given their central role in fundamental ecosystem processes. Our experimental set up consisted of water and bacterioplankton communities from two contrasting coastal lagoons. In order to mimic environmental fluctuations, the bacterioplankton community from one lagoon was successively transferred between tanks containing water from each of the two lagoons. We manipulated initial bacterial diversity for experimental communities and immigration during the experiment. We found that the abundance and production of bacterioplankton communities was higher and more stable (lower temporal variance) for treatments with high initial bacterial diversity. Immigration was only marginally beneficial to bacterial communities, probably because microbial communities operate at different time scales compared to the frequency of perturbation selected in this study, and of their intrinsic high physiologic plasticity. Such local “physiological insurance” may have a strong significance for the maintenance of bacterial abundance and production in the face of environmental perturbations

Epigenetics and airways disease

Epigenetics is the term used to describe heritable changes in gene expression that are not coded in the DNA sequence itself but by post-translational modifications in DNA and histone proteins. These modifications include histone acetylation, methylation, ubiquitination, sumoylation and phosphorylation. Epigenetic regulation is not only critical for generating diversity of cell types during mammalian development, but it is also important for maintaining the stability and integrity of the expression profiles of different cell types. Until recently, the study of human disease has focused on genetic mechanisms rather than on non-coding events. However, it is becoming increasingly clear that disruption of epigenetic processes can lead to several major pathologies, including cancer, syndromes involving chromosomal instabilities, and mental retardation. Furthermore, the expression and activity of enzymes that regulate these epigenetic modifications have been reported to be abnormal in the airways of patients with respiratory disease. The development of new diagnostic tools might reveal other diseases that are caused by epigenetic alterations. These changes, despite being heritable and stably maintained, are also potentially reversible and there is scope for the development of 'epigenetic therapies' for disease

A framework for evolutionary systems biology

<p>Abstract</p> <p>Background</p> <p>Many difficult problems in evolutionary genomics are related to mutations that have weak effects on fitness, as the consequences of mutations with large effects are often simple to predict. Current systems biology has accumulated much data on mutations with large effects and can predict the properties of knockout mutants in some systems. However experimental methods are too insensitive to observe small effects.</p> <p>Results</p> <p>Here I propose a novel framework that brings together evolutionary theory and current systems biology approaches in order to quantify small effects of mutations and their epistatic interactions <it>in silico</it>. Central to this approach is the definition of fitness correlates that can be computed in some current systems biology models employing the rigorous algorithms that are at the core of much work in computational systems biology. The framework exploits synergies between the realism of such models and the need to understand real systems in evolutionary theory. This framework can address many longstanding topics in evolutionary biology by defining various 'levels' of the adaptive landscape. Addressed topics include the distribution of mutational effects on fitness, as well as the nature of advantageous mutations, epistasis and robustness. Combining corresponding parameter estimates with population genetics models raises the possibility of testing evolutionary hypotheses at a new level of realism.</p> <p>Conclusion</p> <p>EvoSysBio is expected to lead to a more detailed understanding of the fundamental principles of life by combining knowledge about well-known biological systems from several disciplines. This will benefit both evolutionary theory and current systems biology. Understanding robustness by analysing distributions of mutational effects and epistasis is pivotal for drug design, cancer research, responsible genetic engineering in synthetic biology and many other practical applications.</p