Human electromagnetic and haemodynamic networks systematically converge in unimodal cortex and diverge in transmodal cortex

Whole-brain neural communication is typically estimated from statistical associations among electromagnetic or haemodynamic time-series. The relationship between functional network architectures recovered from these 2 types of neural activity remains unknown. Here, we map electromagnetic networks (measured using magnetoencephalography (MEG)) to haemodynamic networks (measured using functional magnetic resonance imaging (fMRI)). We find that the relationship between the 2 modalities is regionally heterogeneous and systematically follows the cortical hierarchy, with close correspondence in unimodal cortex and poor correspondence in transmodal cortex. Comparison with the BigBrain histological atlas reveals that electromagnetic–haemodynamic coupling is driven by laminar differentiation and neuron density, suggesting that the mapping between the 2 modalities can be explained by cytoarchitectural variation. Importantly, haemodynamic connectivity cannot be explained by electromagnetic activity in a single frequency band, but rather arises from the mixing of multiple neurophysiological rhythms. Correspondence between the two is largely driven by MEG functional connectivity at the beta (15 to 29 Hz) frequency band. Collectively, these findings demonstrate highly organized but only partly overlapping patterns of connectivity in MEG and fMRI functional networks, opening fundamentally new avenues for studying the relationship between cortical microarchitecture and multimodal connectivity patterns.

What is the relationship between functional network architectures inferred from electromagnetic and haemodynamic data? This study shows that superposition of electromagnetic networks at canonical frequency bands manifests as highly structured patterns of haemodynamic functional connectivity in the human brain, reflecting systematic variation in cytoarchitecture.     

Phage endolysins are adapted to specific hosts and are evolutionarily dynamic

Endolysins are produced by (bacterio)phages to rapidly degrade the bacterial cell wall and release new viral particles. Despite sharing a common function, endolysins present in phages that infect a specific bacterial species can be highly diverse and vary in types, number, and organization of their catalytic and cell wall binding domains. While much is now known about the biochemistry of phage endolysins, far less is known about the implication of their diversity on phage–host adaptation and evolution. Using CRISPR-Cas9 genome editing, we could genetically exchange a subset of different endolysin genes into distinct lactococcal phage genomes. Regardless of the type and biochemical properties of these endolysins, fitness costs associated to their genetic exchange were marginal if both recipient and donor phages were infecting the same bacterial strain, but gradually increased when taking place between phage that infect different strains or bacterial species. From an evolutionary perspective, we observed that endolysins could be naturally exchanged by homologous recombination between phages coinfecting a same bacterial strain. Furthermore, phage endolysins could adapt to their new phage/host environment by acquiring adaptative mutations. These observations highlight the remarkable ability of phage lytic systems to recombine and adapt and, therefore, explain their large diversity and mosaicism. It also indicates that evolution should be considered to act on functional modules rather than on bacteriophages themselves. Furthermore, the extensive degree of evolvability observed for phage endolysins offers new perspectives for their engineering as antimicrobial agents.

Endolysins are produced by bacteriophages to degrade the host cell wall and release new particles, but the implications of their diversity on phage-host adaptation and evolution is unknown. This study uses CRISPR-Cas9 genome editing to reveal novel insights into bacteriophage endolysin diversity and phage-bacteria interactions as well as into endolysin adaptation towards a new bacterial host.     

Molecular Epidemiology of Carbapenem Non-Susceptible Acinetobacter baumannii in France

Carbapenem-resistant Acinetobacter baumannii have emerged globally. The objective of this study was to investigate the epidemiology, clonal diversity and resistance mechanisms of imipenem non-susceptible A. baumannii isolates in France. Between December 2010 and August 2011, 132 notifications were collected, including 37 outbreaks corresponding to 242 cases (2 to 55 per cluster). Multilocus sequence typing, pulsed-field gel electrophoresis (PFGE) and characterisation of carbapenemase-encoding genes were performed on 110 non-repetitive isolates. Gene bla _OXA-23 was the most frequently detected (82%), followed by bla _OXA-24 (11%) and bla _OXA-58 (7%). Eleven sequence types (ST) were distinguished, among which sequence types ST1, ST2 (64%), ST20, ST25, ST85 and ST107. Isolates from epidemiological clusters had the same ST and resistance genes, indicating probable transmission within centres. In contrast, PFGE types of isolates differed among centres, arguing against transmission among centers. This study provides the first epidemiological snapshot of the population of A. baumannii with reduced susceptibility to carbapenems from France, and further underlines the predominance of international clones.     

Retinol (Vitamin A) Increases α-Synuclein, β-Amyloid Peptide,Tau Phosphorylation and RAGE Content in Human SH-SY5Y Neuronal Cell Line

Retinoids (vitamin A and derivatives) are recognized as essential factors for central nervous system (CNS) development. Retinol (vitamin A) also was postulated to be a major antioxidant component of diet as it modulates reactive species (RS) production and oxidative stress in biological systems. Oxidative stress plays a major role either in pathogenesis or development of neurodegenerative diseases, or even in both. Here we investigate the role of retinol supplementation to human neuron-derived SH-SY5Y cells over RS production and biochemical markers associated to neurodegenerative diseases expressed at neuronal level in Parkinson’s disease and Alzheimer’s disease: α-synuclein, β-amyloid peptide, tau phosphorylation and RAGE. Retinol treatment (24 h) impaired cell viability and increased intracellular RS production at the highest concentrations (7 up to 20 µM). Antioxidant co-treatment (Trolox 100 µM) rescued cell viability and inhibited RS production. Furthermore, retinol (10 µM) increased the levels of α-synuclein, tau phosphorylation at Ser396, β-amyloid peptide and RAGE. Co-treatment with antioxidant Trolox inhibited the increased in RAGE, but not the effect of retinol on α-synuclein, tau phosphorylation and β-amyloid peptide accumulation. These data indicate that increased availability of retinol to neurons at levels above the cellular physiological concentrations may induce deleterious effects through diverse mechanisms, which include oxidative stress but also include RS-independent modulation of proteins associated to progression of neuronal cell death during the course of neurodegenerative diseases.     

Lethal mutagenesis and evolutionary epidemiology

The lethal mutagenesis hypothesis states that within-host populations of pathogens can be driven to extinction when the load of deleterious mutations is artificially increased with a mutagen, and becomes too high for the population to be maintained. Although chemical mutagens have been shown to lead to important reductions in viral titres for a wide variety of RNA viruses, the theoretical underpinnings of this process are still not clearly established. A few recent models sought to describe lethal mutagenesis but they often relied on restrictive assumptions. We extend this earlier work in two novel directions. First, we derive the dynamics of the genetic load in a multivariate Gaussian fitness landscape akin to classical quantitative genetics models. This fitness landscape yields a continuous distribution of mutation effects on fitness, ranging from deleterious to beneficial (i.e. compensatory) mutations. We also include an additional class of lethal mutations. Second, we couple this evolutionary model with an epidemiological model accounting for the within-host dynamics of the pathogen. We derive the epidemiological and evolutionary equilibrium of the system. At this equilibrium, the density of the pathogen is expected to decrease linearly with the genomic mutation rate U. We also provide a simple expression for the critical mutation rate leading to extinction. Stochastic simulations show that these predictions are accurate for a broad range of parameter values. As they depend on a small set of measurable epidemiological and evolutionary parameters, we used available information on several viruses to make quantitative and testable predictions on critical mutation rates. In the light of this model, we discuss the feasibility of lethal mutagenesis as an efficient therapeutic strategy.     

Transferability,development of simple sequence repeat (SSR) markers and application to the analysis of genetic diversity and population structure of the African fan palm (Borassus aethiopum Mart.) in Benin

Biological pathways play an important role in the occurrence, development and recovery of complex diseases, such as cancers, which are multifactorial complex diseases that are generally caused by mutation of multiple genes or dysregulation of pathways. We propose a path-specific effect statistic (PSE) to detect the differential specific paths under two conditions (e.g. case VS. control groups, exposure Vs. nonexposure groups). In observational studies, the path-specific effect can be obtained by separately calculating the average causal effect of each directed edge through adjusting for the parent nodes of nodes in the specific path and multiplying them under each condition. Theoretical proofs and a series of simulations are conducted to validate the path-specific effect statistic. Applications are also performed to evaluate its practical performances. A series of simulation studies show that the Type I error rates of PSE with Permutation tests are more stable at the nominal level 0.05 and can accurately detect the differential specific paths when comparing with other methods. Specifically, the power reveals an increasing trends with the enlargement of path-specific effects and its effect differences under two conditions. Besides, the power of PSE is robust to the variation of parent or child node of the nodes on specific paths. Application to real data of Glioblastoma Multiforme (GBM), we successfully identified 14 positive specific pathways in mTOR pathway contributing to survival time of patients with GBM. All codes for automatic searching specific paths linking two continuous variables and adjusting set as well as PSE statistic can be found in supplementary materials.  The proposed PSE statistic can accurately detect the differential specific pathways contributing to complex disease and thus potentially provides new insights and ways to unlock the black box of disease mechanisms.