Biology subjects

Knoll, A.

Publications and source records attributed to Knoll, A..

5 recordsLinked to original sources

bioRxiv2022

Mouse population genetics phenocopies heterogeneity of human Chd8 haploinsufficiency

Preclinical models of neurodevelopmental disorders typically use single inbred strains which fail to capture human genetic and symptom heterogeneity that is common clinically. We tested if systematically modeling human genetic diversity in mouse genetic reference panels would recapitulate population and individual differences in responses to a syndromic mutation in the high-confidence autism risk gene, CHD8. Trait disruptions mimicked those seen in human populations, including high penetrance of macrocephaly and disrupted behavior, but with robust strain and sex differences. For every trait, some strains exhibited a range of large effect size disruptions, sometimes in opposite directions, and remarkably others expressed resilience. Thus, systematically introducing genetic diversity into mouse models of neurodevelopmental disorders provides a better framework for discovering individual differences in symptom etiologies and improved treatments. One-Sentence SummaryAutism trait heterogeneity due to a syndromic gene mutation is recapitulated in mice by incorporating genetic diversity.

neuroscience↗

bioRxiv2021

The BCM rule allows a spinal cord model to learn rhythmic movements

Animal locomotion is hypothesized to be controlled by a central pattern generator in the spinal cord. Experiments and models show that rhythm generating neurons and genetically determined network properties could sustain oscillatory output activity suitable for locomotion. However, current CPG models do not explain how a spinal cord circuitry, which has the same basic genetic plan across species, can adapt to control the different biomechanical properties and locomotion patterns existing in these species. Here we demonstrate that rhythmic and alternating movements in pendulum models can be learned by a monolayer spinal cord circuitry model using the BCM learning rule, which has been previously proposed to explain learning in the visual cortex. These results provide an alternative theory to CPG models, because rhythm generating neurons and genetically defined connectivity are not required in our model. Author summaryThe central pattern generator is the leading hypothesis of locomotor control in animals. There, rhythm generating neurons and genetically defined neural connectivity would form a circuit generating activity patterns suitable for locomotion. We provide a new hypothesis of locomotor control, where rhythmic patterns are learned by a Hebbian learning rule from a mechanical system that has an intrinsic tendency to oscillate.

neuroscience↗

bioRxiv2021

Diversified physiological sensory input connectivity questions the existence of distinct classes of spinal interneurons in the adult cat in vivo

The spinal cord is engaged in all forms of motor performance but its functions are far from understood. Because network connectivity defines function, we explored the connectivity for muscular, tendon and tactile sensory inputs among a wide population of spinal interneurons in the lower cervical segments. Using low noise intracellular whole cell recordings in the decerebrated, nonanesthetized cat in vivo, we could define mono-, di-, trisynaptic inputs as well as the weights of each input. Whereas each neuron had a highly specific input, and each indirect input could moreover be explained by inputs in other recorded neurons, we unexpectedly also found the input connectivity of the spinal interneuron population to form a continuum. Our data hence contrasts with the currently widespread notion of distinct classes of interneurons. We argue that this suggested diversified physiological connectivity, which likely requires a major component of circuitry learning, implies a more flexible functionality. 1. Graphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY 2. HighlightsO_LIIn vivo whole cell, intracellular recording of spinal interneurons. C_LIO_LIPatterns of input from Ia, Ib and cutaneous afferents is highly diversified. C_LIO_LILearning appears to be a defining factor of spinal interneuron connectivity. C_LI

neuroscience↗

bioRxiv2019

Biological data questions the support of the self inhibition required for pattern generation in the half center model.

Locomotion control in mammals has been hypothesized to be governed by a central pattern generator (CPG) located in the circuitry of the spinal cord. The most common model of the CPG is the half center model, where two pools of neurons generate alternating, oscillatory activity. In this model, the pools reciprocally inhibit each other ensuring alternating activity. There is experimental support for reciprocal inhibition. However another crucial part of the half center model is a self inhibitory mechanism which prevents the neurons of each individual pool from infinite firing. Self-inhibition is hence necessary to obtain alternating activity. But critical parts of the experimental bases for the proposed mechanisms for self-inhibition were obtained in vitro, in preparations of juvenile animals. The commonly used adaptation of spike firing does not appear to be present in adult animals in vivo. We therefore modeled several possible self inhibitory mechanisms for locomotor control. Based on currently published data, previously proposed hypotheses of the self inhibitory mechanism, necessary to support the CPG hypothesis, seems to be put into question by functional evaluation tests or by in vivo data. This opens for alternative explanations of how locomotion activity patterns in the adult mammal could be generated. Author summaryLocomotion control in animals is hypothesized to be controlled through an intrinsic central pattern generator in the spinal cord. This was proposed over a hundred years ago and has subsequently been formed into a consistent theory, through experimentation and computer modeling. However, critical data that support the neuronal circuitry mechanisms underpinning this theory has been obtained in experiments that greatly differ from intact animals. We propose, after trying to fill in this critical part, that new ideas are required to explain locomotion of intact animals.

neuroscience↗

bioRxiv2019

Neoproterozoic origin and multiple transitions to macroscopic growth in green seaweeds

The Neoproterozoic Era records the transition from a largely bacterial to a predominantly eukaryotic phototrophic world, creating the foundation for the complex benthic ecosystems that have sustained Metazoa from the Ediacaran Period onward. This study focusses on the evolutionary origins of green seaweeds, which play an important ecological role in the benthos of modern sunlit oceans and likely played a crucial part in the evolution of early animals by structuring benthic habitats and providing novel niches. By applying a phylogenomic approach, we resolve deep relationships of the core Chlorophyta (Ulvophyceae or green seaweeds, and freshwater or terrestrial Chlorophyceae and Trebouxiophyceae) and unveil a rapid radiation of Chlorophyceae and the principal lineages of the Ulvophyceae late in the Neoproterozoic Era. Our time-calibrated tree points to an origin and early diversification of green seaweeds in the late Tonian and Cryogenian periods, an interval marked by two global glaciations, with strong consequent changes in the amount of available marine benthic habitat. We hypothesize that the unicellular and simple multicellular ancestors of green seaweeds survived these extreme climate events in isolated refugia, and diversified following recolonization of benthic environments that became increasingly available as sea ice retreated. An increased supply of nutrients and biotic interactions such as grazing pressure has likely triggered the independent evolution of macroscopic growth via different strategies, including both true multicellularity, and multiple types of giant celled forms.\n\nSignificance StatementGreen seaweeds are important primary producers along coastlines worldwide, and likely played a key role in the evolution of animals. To understand their origin and diversification, we resolve key relationships among extant green algae using a phylotranscriptomic approach. We calibrate our tree using available fossil data, to reconstruct important evolutionary events such as transitions to benthic environments, and evolution of macroscopic growth. We estimate green seaweeds to have originated in the late Tonian/Cryogenian Period, followed by a marked Ordovician diversification of macroscopic forms. This ancient proliferation of green seaweeds likely modified shallow marine ecosystems, which set off an evolutionary arms race between ever larger seaweeds and grazers.

evolutionary biology↗