Biology subjects

Bernard, C.

Publications and source records attributed to Bernard, C..

At least 55 records · Page 3Linked to original sources

bioRxiv2022

A note on discretising Keyfitz entropy

Keyfitz entropy is a widely used metric to quantify the shape of survivorship of populations, from plants, to animals, and microbes. Keyfitz entropy values < 1 correspond to life histories with an increasing mortality rate with age (i.e., actuarial senescence), whereas values > 1 correspond to species with a decreasing mortality rate with age (negative senescence), and a Keyfitz entropy of exactly 1 corresponds to a constant mortality rate with age. Keyfitz entropy was originally defined using a continuous-time model, and has since been discretised to facilitate its calculation from discrete-time demographic data. In this short note, we show that the previously used discretisation of the continuous-time metric does not preserve the relationship with increasing, decreasing, or constant mortality rates. To resolve this discrepancy, we propose a new discrete-time formula for Keyfitz entropy for age-classified life histories. We show that this new method of discretisation preserves the relationship with increasing, decreasing, or constant mortality rates. We analyse the relationship between the original and the new discretisation, and we find that the existing metric tends to underestimate Keyfitz entropy for both short-lived species and long-lived species, thereby introducing a consistent bias. To conclude, to avoid biases when classifying life histories as (non-)senescent, we suggest researchers use either the new metric proposed here, or one of the many previously suggested survivorship shape metrics applicable to discrete-time demographic data such as Gini coefficient or Hayleys median.

ecology↗

bioRxiv2022

Multiscale cosimulation design template implemented for a neuroscience application

Integration of information across heterogeneous sources creates added scientific value. It is, however, a challenge to progress, often a barrier, to interoperate data, tools and models across spatial and temporal scales. Here we present a design template for coupling simulators operating at different scales and enabling co-simulation. We illustrate its functioning along a neuroscience example, in which individual regions of interest are simulated on the cellular level to address mechanistic questions, while the remaining network is efficiently simulated on the population level. A workflow is illustrated for the use case of The Virtual Brain and NEST, in which the cellular-level hippocampus of the mouse is embedded into a full brain network involving micro and macro electrode recordings. This new tool allows integrating knowledge across scales in the same simulation framework and validate them against multiscale experiments, thereby largely widening the explanatory power of computational models.

neuroscience↗

bioRxiv2022

Deficit in observational learning in experimental epilepsy

Individuals use the observation of a conspecific to learn new behaviors and skills in many species. Whether observational learning is affected in epilepsy is not known. Using the pilocarpine rat model of epilepsy, we assessed learning by observation in a spatial task. The task involves a naive animal observing a demonstrator animal seeking a reward at a specific spatial location. After five observational sessions, the observer is allowed to explore the rewarded space and look for the reward. Although control observer rats succeed in finding the reward when allowed to explore the rewarded space, epileptic animals fail. However, epileptic animals are able to successfully learn the location of the reward through their own experience after several trial sessions. Thus, epileptic animals show a clear deficit in learning by observation. This result may be clinically relevant, in particular in children who strongly rely on observational learning.

animal behavior and cognition↗

bioRxiv2022

MOSAIC: A Unified Trait Database to Complement Structured Population Models

O_LIThe ecological sciences have joined the big data revolution. However, despite exponential growth in data availability, broader interoperability amongst datasets is still needed to unlock the potential of open access. The interface of demography and functional traits is well-positioned to benefit from said interoperability. Trait-based ecological approaches have been criticised because of their inability to predict fitness components, the core of demography; likewise, demographic approaches are data-hungry, and so using traits as ecological shortcuts to understanding and forecasting population viability could offer great value. C_LIO_LIHere, we introduce MOSAIC, an open-access trait database that unlocks the demographic potential stored in the COMADRE, COMPADRE, and PADRINO open-access databases. MOSAIC data have been digitised and curated through a combination of existing datasets and additional taxonomic and/or trait records sourced from primary literature. In its first release, MOSAIC (v. 1.0.0) includes 14 trait fields for 300 animal and plant species: biomass, height, growth determination, regeneration, sexual dimorphism, mating system, hermaphrodism, sequential hermaphrodism, dispersal capacity, type of dispersal, mode of dispersal, dispersal classes, volancy, and aquatic habitat dependency. MOSAIC also includes species-level phylogenies for 1,359 species and population-specific climate data where locations are recorded. C_LIO_LIUsing MOSAIC, we highlight a taxonomic mismatch of widely used trait databases with existing structured population models. Despite millions of trait records available in open-access databases, taxonomic overlap between open-access demographic and trait databases is <5%. We identify where traits of interest to ecologists can benefit from database integration and start to quantify traits that are poorly quantified (e.g., growth determination, modularity). C_LIO_LIThe MOSAIC database evidences the importance of improving interoperability in open-access efforts in ecology as well as the need for complementary digitisation to fill targeted taxonomic gaps. In addition, MOSAIC highlights emerging challenges associated with the disparity between locations where different trait records are sourced. C_LI

ecology↗

bioRxiv2022

Cystic fibrosis patient-derived bronchial organoids unveil druggable pathways against Mycobacterium abscessus infection.

Mycobacterium abscessus (Mabs) drives life-shortening mortality in cystic fibrosis (CF) patients, primarily because of its resistance to chemotherapeutic agents. To date, our knowledge on the host and bacterial determinants driving Mabs pathology in CF patient lung remains rudimentary. Here, we used human airway organoids (AOs) microinjected with smooth (S) or rough (R-)Mabs to evaluate bacteria fitness, host responses to infection, and new treatment efficacy. We show that S Mabs formed biofilm, R Mabs formed cord serpentines and displayed a higher virulence. While Mabs infection triggers enhanced oxidative stress, pharmacological activation of antioxidant pathways resulted in better control of Mabs growth. Genetic and pharmacological inhibition of the CFTR is associated with better growth and higher virulence of S and R Mabs. Finally, pharmacological activation of antioxidant pathways inhibited Mabs growth and improved efficacy in combination with cefoxitin, a first line antibiotic. In conclusion, we have established AOs as a suitable human system to decipher mechanisms of CF-driven respiratory infection by Mabs and propose antioxidants as a potential host-directed strategy to improve Mabs infection control.

cell biology↗

bioRxiv2021

Input-specific control of interneuron numbers in nascent striatal networks

The assembly of functional neuronal circuits requires appropriate numbers of distinct classes of neurons, but the mechanisms through which their relative proportions are established remain poorly defined. Investigating the mouse striatum, here we found that the two most prominent subtypes of striatal interneurons, parvalbumin-expressing (PV+) GABAergic and cholinergic (ChAT+) interneurons, undergo extensive programmed cell death between the first and second postnatal weeks. Remarkably, the survival of PV+ and ChAT+ interneurons is regulated by distinct mechanisms mediated by their specific afferent connectivity. While long-range cortical inputs control PV+ interneuron survival, ChAT+ interneuron survival is regulated by local input from the medium spiny neurons. Our results identify input-specific circuit mechanisms that operate during the period of programmed cell death to establish the final number of interneurons in nascent striatal networks.

neuroscience↗

bioRxiv2021

Cortical wiring by synapse-specific control of local protein synthesis

Neurons use local protein synthesis as a mechanism to support their morphological complexity, which requires independent control across multiple subcellular compartments including individual synapses. However, to what extent local translation is differentially regulated at the level of specific synaptic connections remains largely unknown. Here, we identify a signaling pathway that regulates the local synthesis of proteins required for the formation of excitatory synapses on parvalbumin-expressing (PV+) interneurons in the mouse cerebral cortex. This process involves the regulation of the mTORC1 inhibitor Tsc2 by the receptor tyrosine kinase ErbB4, which enables the local control of mRNA translation in a cell type-specific and synapse-specific manner. Ribosome-associated mRNA profiling reveals a molecular program of synaptic proteins that regulates the formation of excitatory inputs on PV+ interneurons downstream of ErbB4 signaling. Our work demonstrates that local protein translation is regulated at the level of specific connections to control synapse formation in the nervous system.

neuroscience↗

bioRxiv2021

RRNPP_detector: a tool to detect RRNPP quorum sensing systems in chromosomes, plasmids and phages of gram-positive bacteria

Gram-positive bacteria (e.g. Firmicutes) and their mobile genetic elements (plasmids, bacteriophages) encode peptide-based quorum sensing systems (QSSs) that regulate behavioral transitions in a density-dependent manner. In their simplest form, termed "RRNPP", these QSSs are composed of two adjacent genes: a communication propeptide and its cognate intracellular receptor. Despite the prime importance of RRNPP QSSs in the regulation of key biological pathways such as virulence, sporulation or biofilm formation in bacteria, conjugation in plasmids or lysogeny in temperate bacteriophages, no tools exist to predict their presence in target genomes/mobilomes. Here, we introduce RRNPP_detector, a software to predict RRNPP QSSs in chromosomes, plasmids and bacteriophages of gram-positive bacteria, available at https://github.com/TeamAIRE/RRNPP_detector. RRNPP_detector does not rely on homology searches but on a signature of multiple criteria, which are common between distinct families of experimentally-validated RRNPP QSSs. Because this signature is generic while specific to the canonical mechanism of RRNPP quorum sensing, it enables the discovery of novel RRNPP QSSs and thus of novel "languages" of biocommunication. Applying RRNPP_detector against complete genomes of viruses and Firmicutes available on the NCBI, we report a potential 7.5-fold expansion of RRNPP QSS diversity, alternative secretion-modes for certain candidate QSS propeptides, bilingual bacteriophages and plasmids, as well as predicted chromosomal and plasmidic Biosynthetic-Gene-Clusters regulated by QSSs.

bioinformatics↗

bioRxiv2021

Large-scale identification of viral quorum sensing systems reveal convergent evolution of density-dependent sporulation-hijacking in bacteriophages

Communication between viruses supported by quorum sensing systems (QSSs) were found to optimize the fitness of temperate bacteriophages of Bacilli by guiding the transition from the host-destructive lytic cycle to the host-protective lysogenic cycle in a density-dependent manner. All known phage-encoded QSSs consist of a communication propeptide and a cognate intracellular receptor that regulates the expression of adjacent target genes upon recognition of the matured peptide, a signature known as RRNPP and found in chromosomes, plasmids and phages of Firmicutes bacteria. Recently, we have introduced the RRNPP_detector software to detect novel genetic systems matching the RRNPP signature, which unearthed many novel phage-encoded candidate QSSs. Here, by looking at the adjacent genes likely regulated by these viral candidate QSSs, we identified an unsuspected clustering of viral QSSs with viral genes whose bacterial homologs are key regulators of the last-resort bacterial sporulation initiation pathway (rap, spo0E or abrB). Consistently, we found evidence in published data that certain of these QSSs encoded by prophages (phage genomes inserted within a bacterial genome) dynamically manipulate the timing of sporulation in the host. Because these viral QSSs are genetically diverse and are found associated with different sporulation regulators, this suggests a convergent evolution in bacteriophages of density-dependent sporulation-hijacking mechanisms. SIGNIFICANCECommunication between viruses supported by quorum sensing systems (QSSs) is a brand new research area that has transformed our views of viral adaptation and virus-host co-evolution. The viral QSSs discovered so far were found to guide the lysis-lysogeny decision in temperate bacteriophages as a function of phage density. Here, we identified that quorum sensing-mediated communication between phages can not only guide the regulation of viral processes but also the manipulation of the bacterial sporulation pathway. Our finding introduces the new view that not only bacteria decide when it is time to sporulate, some bacteriophages are also key stakeholders in this dynamical decision-making process. Considering that spores are the transmissive form of many pathogens, these new insights have important applied implications.

bioinformatics↗

bioRxiv2021

OTX2 homeoprotein functions in adult choroid plexus

Choroid plexus secretes cerebrospinal fluid important for brain development and homeostasis. The OTX2 homeoprotein is critical for choroid plexus development and remains highly expressed in adult choroid plexus. Through RNA sequencing analyses of constitutive and conditional knockdown adult mouse models, we reveal putative roles for OTX2 in choroid plexus function, including cell signaling and adhesion, and show that it regulates the expression of factors secreted into cerebrospinal fluid, notably transthyretin. We show that Otx2 expression impacts choroid plexus immune and stress responses, and also affects splicing which leads to changes in mRNA isoforms of proteins implicated in oxidative stress response and DNA repair. Through mass spectrometry analysis of OTX2 protein partners in the choroid plexus, and in known non-cell autonomous target regions such as visual cortex and ventricular-subventricular zone, we identified putative targets involved in cell adhesion, chromatin structure and RNA processing. Thus, OTX2 retains important roles in choroid plexus function and brain homeostasis throughout life.

neuroscience↗

bioRxiv2021

Disordered information processing dynamics in experimental epilepsy

Neurological disorders share common high-level alterations, such as cognitive deficits, anxiety, and depression. This raises the possibility of fundamental alterations in the way information conveyed by neural firing is maintained and dispatched in the diseased brain. Using experimental epilepsy as a model of neurological disorder we tested the hypothesis of altered information processing, analyzing how neurons in the hippocampus and the entorhinal cortex store and exchange information during slow and theta oscillations. We equate the storage and sharing of information to low level, or primitive, information processing at the algorithmic level, the theoretical intermediate level between structure and function. We find that these low-level processes are organized into substates during brain states marked by theta and slow oscillations. Their internal composition and organization through time are disrupted in epilepsy, loosing brain state-specificity, and shifting towards a regime of disorder in a brain region dependent manner. We propose that the alteration of information processing at an algorithmic level may be a mechanism behind the emergent and widespread co-morbidities associated with epilepsy, and perhaps other disorders.

neuroscience↗

bioRxiv2020

Neuronal cascades shape whole-brain functional dynamics at rest

At rest, mammalian brains display remarkable spatiotemporal complexity, evolving through recurrent brain states on a slow timescale of the order of tens of seconds. While the phenomenology of the resting state dynamics is valuable in distinguishing healthy and pathological brains, little is known about its underlying mechanisms. Here, we identify neuronal cascades as a potential mechanism. Using full-brain network modeling, we show that neuronal populations, coupled via a detailed structural connectome, give rise to large-scale cascades of firing rate fluctuations evolving at the same time scale of resting-state networks. The ignition and subsequent propagation of cascades depend upon the brain state and connectivity of each region. The largest cascades produce bursts of Blood-Oxygen-Level-Dependent (BOLD) co-fluctuations at pairs of regions across the brain, which shape the simulated resting-state network dynamics.We experimentally confirm these theoretical predictions. We demonstrate the existence and stability of intermittent epochs of functional connectivity comprising BOLD co-activation bursts in mice and human fMRI. We then provide evidence for the existence and leading role of the neuronal cascades in humans with simultaneous EEG/fMRI recordings. These results show that neuronal cascades are a major determinant of spontaneous fluctuations in brain dynamics at rest. 1 Significance StatementFunctional connectivity and its dynamics are widely used as a proxy of brain function and dysfunction. Their neuronal underpinnings remain unclear. Using connectome-based modeling, we link the fast microscopic neuronal scale to the slow emergent whole-brain dynamics. We show that cascades of neuronal activations spontaneously propagate in resting state-like conditions. The largest neuronal cascades result in the co-fluctuation of Blood-Oxygen-Level-Dependent signals at pairs of brain regions, which in turn translate to stable brain states. Thus, we provide a theoretical framework for the emergence and the dynamics of resting-state networks. We verify these predictions in empirical mouse fMRI and human EEG/fMRI datasets measured in resting states conditions. Our work sheds light on the multiscale mechanisms of brain function.

neuroscience↗

bioRxiv2020

MG53 is not a critical regulator of insulin signaling pathway in skeletal muscle

In type 2 diabetes (T2D), both muscle and liver are severely resistant to insulin action. Muscle insulin resistance accounts for more than 80% of the impairment in total body glucose disposal in T2D patients and is often characterized by an impaired insulin signaling. Mitsugumin 53 (MG53), a muscle-specific TRIM family protein initially identified as a key regulator of cell membrane repair machinery has been suggested to be a critical regulator of muscle insulin signaling pathway by acting as ubiquitin E3 ligase targeting both the insulin receptor and insulin receptor substrate 1 (IRS1). Here, we show using in vitro and in vivo approaches that MG53 is not a critical regulator of insulin signaling and glucose homeostasis. First, MG53 expression is not consistently regulated in skeletal muscle from various preclinical models of insulin resistance. Second, MG53 gene knock-down in muscle cells does not lead to impaired insulin response as measured by Akt phosphorylation on Serine 473 and glucose uptake. Third, recombinant human MG53 does not alter insulin response in both differentiated C2C12 and human skeletal muscle cells. Fourth, ectopic expression of MG53 in HEK293 cells lacking endogenous MG53 expression fails to alter insulin response as measured by Akt phosphorylation. Finally, both male and female mg53 -/- mice were not resistant to high fat induced obesity and glucose intolerance compared to wild-type mice. Taken together, these results strongly suggest that MG53 is not a critical regulator of insulin signaling pathway in skeletal muscle.

cell biology↗

bioRxiv2020

Characterization of cyanobacteria isolated from thermal muds of Balaruc-Les-Bains (France) and description of a new genus and species Pseudochroococcuscouteii

Cyanobacteria are able to synthesize a high diversity of natural compounds that account for their success in the colonization of a variety of ecological niches. Many of them have beneficial properties. The mud from the thermal baths of Balaruc-Les-Bains, one of the oldest thermal baths in France, has long been recognized as a healing treatment for arthro-rheumatic diseases. To characterize the cyanobacteria living in these muds and the metabolites they potentially produce, several strains were isolated from the water column and biofilms of the retention basin and analyzed using a polyphasic approach. Morphological, ultrastructural and molecular (16S rRNA gene and 16S-23S ITS region sequencing) methods were employed to identify nine cyanobacterial strains belonging to the orders Chroococcales, Synechococcales, Oscillatoriales and Nostocales. The combination of morphological and genetic characteristics supported the description of a new genus and species with the type species as Pseudo-chroococcus couteii. The high taxonomic diversity in the muds of the thermal baths of Balaruc-Les-Bains along with literature reports of the potential for bioactive metabolite synthesis of these taxa allowed us to hypothesize that some of the metabolites produced by these strains could contribute to the therapeutic properties of the muds from Thermes de Balaruc-Les-Bains.

microbiology↗

bioRxiv2020

Time scale separation of information processing between sensory and associative regions

A hierarchy of local timescales with a back (sensory)-to-front (prefrontal) gradient reflects brain region specialization. However, cognitive processes emerge from the coordinated activity across regions, and the corresponding timescales should refer to the interactions rather than to regional activity. Using edgewise connectivity on magnetoencephalography signals, we demonstrate a reverse front-to-back gradient when non-local interactions are prominent. Thus, the timescales are dynamic and reconfigure between back-to-front and front-to-back patterns.

neuroscience↗

bioRxiv2020

A unified physiological framework of transitions between seizures, status epilepticus and depolarization block at the single neuron level

The majority of seizures recorded in humans and experimental animal models can be described by a generic phenomenological mathematical model, The Epileptor. In this model, seizure-like events (SLEs) are driven by a slow variable and occur via saddle node (SN) and homoclinic bifurcations at seizure onset and offset, respectively. Here we investigated SLEs at the single cell level using a biophysically relevant neuron model including a slow/fast system of four equations. The two equations for the slow subsystem describe ion concentration variations and the two equations of the fast subsystem delineate the electrophysiological activities of the neuron. Using extracellular K+ as a slow variable, we report that SLEs with SN/homoclinic bifurcations can readily occur at the single cell level when extracellular K+ reaches a critical value. In patients and experimental models, seizures can also evolve into sustained ictal activity (SIA) and, depolarization block (DB), activities which are also parts of the dynamic repertoire of the Epileptor. Increasing extracellular concentration of K+ in the model to values found during experimental status epilepticus and DB, we show that SIA and DB can also occur at the single cell level. Thus, seizures, SIA and DB, which have been first identified as network events, can exist in a unified framework of a biophysical model at the single neuron level and exhibit similar dynamics as observed in the Epileptor. Author SummaryEpilepsy is a neurological disorder characterized by the occurrence of seizures. Seizures have been characterized in patients in experimental models at both macroscopic and microscopic scales using electrophysiological recordings. Experimental works allowed the establishment of a detailed taxonomy of seizures, which can be described by mathematical models. We can distinguish two main types of models. Phenomenological (generic) models have few parameters and variables and permit detailed dynamical studies often capturing a majority of activities observed in experimental conditions. But they also have abstract parameters, making biological interpretation difficult. Biophysical models, on the other hand, use a large number of variables and parameters due to the complexity of the biological systems they represent. Because of the multiplicity of solutions, it is difficult to extract general dynamical rules. In the present work, we integrate both approaches and reduce a detailed biophysical model to sufficiently low-dimensional equations, and thus maintaining the advantages of a generic model. We propose, at the single cell level, a unified framework of different pathological activities that are seizures, depolarization block, and sustained ictal activity.

neuroscience↗

bioRxiv2020

Spatio-temporal heterogeneity in hippocampal metabolism in control and epilepsy conditions.

The hippocampuss dorsal and ventral parts are involved in different operative circuits, which functions vary in time during the night and day cycle. These functions are altered in epilepsy. Since energy production is tailored to function, we hypothesized that energy production would be space- and time-dependent in the hippocampus and that such organizing principle would be modified in epilepsy. Using metabolic imaging and metabolite sensing ex vivo, we show that the ventral hippocampus favors aerobic glycolysis over oxidative phosphorylation as compared to the dorsal part in the morning in control mice. In the afternoon, aerobic glycolysis is decreased, and oxidative phosphorylation increased. In the dorsal hippocampus, the metabolic activity varies less between these two times but is weaker than in the ventral. Thus, the energy metabolism is different along the dorsoventral axis and changes as a function of time in control mice. In an experimental model of epilepsy, we find a large alteration of such spatio-temporal organization. In addition to a general hypometabolic state, the dorsoventral difference disappears in the morning, when seizure probability is low. In the afternoon, when seizure probability is high, the aerobic glycolysis is enhanced in both parts, the increase being stronger in the ventral area. We suggest that energy metabolism is tailored to the functions performed by brain networks, which vary over time. In pathological conditions, the alterations of these general rules may contribute to network dysfunctions. SIGNIFICANCE STATEMENTThe dorsal part of the hippocampus is involved in spatial learning and memory processes, while the ventral is implicated in motivational and emotional behavior. These functions change during the night and day cycle, and they are altered in epilepsy. Here we show that energy production (glycolysis versus oxidative phosphorylation) varies along the dorsoventral axis in a circadian manner ex vivo in control mice. These rules are altered in experimental epilepsy. Thus, energy production may be tailored to the function performed by hippocampal subdivisions and to the time of the day. Alterations in epilepsy may contribute to seizure generation and cognitive deficits.

neuroscience↗

bioRxiv2020

OTX2 non-cell autonomous activity regulates inner retinal function

OTX2 is a homeoprotein transcription factor expressed in photoreceptors and bipolar cells in the retina. OTX2, like many other homeoproteins, transfers between cells and exerts non-cell autonomous effects such as promoting survival of retinal ganglion cells that do not express the protein. Here we used a genetic approach to target extracellular OTX2 in the retina by conditional expression of a secreted single chain anti-OTX2 antibody. Compared to control mice, the expression of this antibody by Parvalbumin-expressing neurons in the retina is followed by a reduction in visual acuity in one-month-old mice with no alteration of the retinal structure or cell type number or aspect. A- and b-waves measured by electroretinogram were also indistinguishable from control mice, suggesting no functional deficit of photoreceptors and bipolar cells. Mice expressing the OTX2-neutralizing antibody did show a significant doubling in the flicker amplitude, consistent with a change in inner retinal function. Our results show that interfering in vivo with OTX2 non-cell autonomous activity in the postnatal retina leads to an alteration in inner retinal cell functions and causes a deficit in visual acuity. Significance statementOTX2 is a homeoprotein transcription factor expressed in retinal photoreceptors and bipolar cells. Although the Otx2 locus is silent in the inner retina, the protein is detected in cells of the ganglion cell layer consistent with the ability of this class of proteins to transfer between cells. We expressed a secreted single chain antibody (scFv) against OTX2 in the retina to neutralize extracellular OTX2. Antibody expression leads to reduced visual acuity with no change in retinal structure, or photoreceptor or bipolar physiology; however, activity in the inner retina was altered. Thus, interfering with OTX2 non-cell autonomous activity in postnatal retina alters inner retinal function and causes vision loss, highlighting the physiological value of homeoprotein direct non-cell autonomous signaling.

neuroscience↗