title: Scale Bar of Aging Trajectories for Screening Personal Rejuvenation Treatments

abstract: Although aging is an increasingly severe healthy, economic, and social global problem, it is far from well-modeling aging due to the aging processs complexity. To promote the aging modeling, here we did the quantitative measurement based on aging blood transcriptome. Specifically, the aging blood transcriptome landscape was constructed through ensemble modeling in a cohort of 505 people, and 1138 age-related genes were identified. To assess the aging rate in the linear dimension of aging, we constructed a simplified linear aging clock, which distinguished fast-aging and slow-aging populations and showed the differences in the composition of immune cells. Meanwhile, the non-linear dimension of aging revealed the transcriptome fluctuations with a crest around the age of 40 and showed that this crest came earlier and was more vigorous in the fast-aging population. Moreover, the aging clock was applied to evaluate the rejuvenation effect of molecules in vitro, such as Nicotinamide Mononucleotide (NMN) and Metformin. In sum, this study developed a de novo aging clock to evaluate agedependent precise medicine by revealing its fluctuation nature based on comprehensively mining the aging blood transcriptome, promoting the development of personal aging monitoring and anti-aging therapies.

category: bioengineering


title: Evolutionary PTEN Gene Divergence Underpins the Remodeling of Plant Vacuolar Compartments

abstract: Membrane fusion and fission are fundamental processes in sustaining cellular compartmentalization. Fission of a lipid bilayer requires a furrow formation that brings membranes in close proximity prior to a contiguous membrane cleavage. Although plant ancestors abandoned cleavage furrow-mediated cytokinesis more than 500 million years ago, here we show that plants still employ this mechanical principle to divide embryonic vacuoles. The evolutionary divergence in PHOSPHATASE AND TENSIN HOMOLOG DELETED ON CHROMOSOME TEN (PTEN) enzymes was required to coordinate this process, as Arabidopsis loss-of-function pten2a pten2b mutants contain hyper compartmentalized embryonic vacuoles. In contrast, PTEN2 overexpression hinders lytic and secretion cellular pathways downstream of TGN in xylem cells. These processes are critical for the formation of secondary cell walls in xylem cells and depend on a poorly characterized and evolutionarily novel N-terminal domain in PTEN2s. The PTEN2 subfamily appeared with the emergence of the Phragmoplastophyta clade, when vacuolar compartments enlarged and cleavage furrow-mediated cytokinesis became extinct. Together, our work suggests that the evolutionary innovation of the PTEN family is conserved across terrestrial plants and central to vacuolar remodelling.

category: plant biology


title: Royal knifefish generate powerful suction feeding through large neurocranial elevation and high muscle power output

abstract:
Suction feeding in ray-finned fishes involves powerful buccal cavity expansion to accelerate water and food into the mouth. Previous XROMM studies in largemouth bass (Micropterus salmoides), bluegill sunfish (Lepomis macrochirus), and channel catfish (Ictalurus punctatus) have shown that more than 90% of suction power in high performance strikes comes from the axial musculature. Thus, the shape of the axial muscles and skeleton may impact suction feeding mechanics. Royal knifefish (Chitala blanci) have an unusual postcranial morphology, with a ventrally flexed vertebral column and relatively large mass of epaxial muscle. Based on their body shape, we hypothesized that royal knifefish would generate high power strikes by utilizing large neurocranial elevation, vertebral column extension, and epaxial shortening. As predicted, C. blanci generated high suction expansion power compared to the other three species studied to date (up to 160 W), which was achieved by increasing both the rate of volume change and the intraoral subambient pressure. The large epaxial muscle (25% of body mass) shortened at high velocities to produce large neurocranial elevation and vertebral extension (up to 41 deg, combined), as well as high muscle mass-specific power (up to 800 W kg-1). For the highest power strikes, axial muscles generated 95% of the power, and 64% of the axial muscle mass consisted of the epaxial muscles. The epaxial-dominated suction expansion of royal knifefish supports our hypothesis that postcranial morphology may be a strong predictor of suction feeding biomechanics.

SUMMARY STATEMENTRoyal knifefish rely on their distinct postcranial morphology--with a curved vertebral column and large dorsal body muscles--to produce large neurocranial elevation and powerful suction feeding.

category: zoology


title: Royal knifefish generate powerful suction feeding through large neurocranial elevation and high epaxial muscle power


title: Structural changes after early life adversity in rodents: a systematic review with meta-analysis

abstract: Early life adversity (ELA) is a well-documented risk factor for psychiatric illnesses in humans. This risk may, in part, be conferred by structural changes induced by ELA, lasting into adulthood. We here review the evidence for such lasting structural changes in rodent models for ELA involving altered maternal care during the first two postnatal weeks. In total, we extracted data from 64 studies reporting on 260 comparisons in adult rats or mice which experienced ELA or control treatment. Most of the observations concerned structural changes in the hippocampus of adult male rats earlier exposed to maternal separation. A 3-level meta-analysis revealed that ELA reduced hippocampal volume and the number of dendritic branches as well as dendritic length of principal hippocampal cells. No differences were observed across the hippocampal subfields. In terms of adult neurogenesis in the dentate subgranular zone, both staining for BrdU and the early neuronal marker DCX were significantly reduced, while the general proliferation marker Ki67 remained unchanged. The neuronal growth factor BDNF did not show significant changes, although the unexplained heterogeneity was moderate. Generally, the effect of ELA compared to control on structural markers was not affected by additional stressors experienced in life. Overall, the data available support the notion that ELA, at least in the hippocampus of male rats, lastingly reduces volume, hampers dendritic growth and suppresses adult neurogenesis.

category: neuroscience


title: Long dsRNA mediated RNA interference (dsRNAi) is antiviral in interferon competent mammalian cells

abstract: In invertebrate cells, RNA interference (RNAi) acts as a powerful defense against virus infection by cleaving virally produced long dsRNA into siRNA by Dicer and loaded into RISC which can then destroy/disrupt complementary viral mRNA sequences. Comparatively in mammalian cells, the type I interferon (IFN) pathway is the cornerstone of the innate antiviral response. Although the cellular machinery for RNAi functions in mammalian cells, its role in the antiviral response remains controversial. Here we show that IFN competent mammalian cells engage in dsRNA-mediated RNAi. We found that pre-soaking mammalian cells with concentrations of sequence-specific dsRNA too low to induce IFN production could significantly inhibit viral replication, including SARS-CoV-2. This phenomenon was dependent on dsRNA length, was comparable in effect to transfected siRNAs, and could knockdown multiple sequences at once. Additionally, Dicer-knockout cell lines were incapable of this inhibition, confirming use of RNAi. This represents the first evidence that soaking with gene-specific dsRNA can generate viral knockdown in mammalian cells. Furthermore, demonstrating RNAi below the threshold of IFN induction has uses as a novel therapeutic platform.

category: immunology


title: Acclimation of phenology relieves leaf longevity constraints in deciduous forests

abstract: Leaf phenology is key for regulating total growing season mass and energy fluxes. Long-term temporal trends towards earlier leaf unfolding are observed across Northern Hemisphere forests. Phenological dates also vary between years, whereby end-of-season (EOS) dates correlate positively with start-of-season (SOS) dates and negatively with growing season total net CO2 assimilation (Anet). These associations have been interpreted as the effect of a constrained leaf longevity or of premature carbon (C) sink saturation - with far-reaching consequences for long-term phenology projections under climate change and rising CO2. Here, we use multi-decadal ground and remote-sensing observations to show that the relationships between Anet and EOS are opposite at the interannual and the decadal time scales. A decadal trend towards later EOS persists in parallel with a trend towards increasing Anet - in spite of the negative Anet-EOS relationship at the interannual scale. This indicates that acclimation of phenology has enabled plants to transcend a constrained leaf longevity or premature C sink saturation over the course of several decades, leading to a more effective use of available light and a sustained extension of the vegetation CO2 uptake season over time.

category: ecology


title: Structural insights into the galanin receptors signaling

abstract:
Galanin is a biologically active neuropeptide, and functions through three distinct G protein-coupled receptors (GPCRs), namely GALR1, GALR2 and GLAR3. GALR signaling plays important roles in regulating various physiological processes such as energy metabolism, neuropathic pain, epileptic activity, and sleep homeostasis. GALR1 and GALR3 signal through the Gi/o pathway, whereas GALR2 signals mainly through the Gq/11 pathway. However, the molecular basis for galanin recognition and G protein selectivity of GALRs remains poorly understood. Here, we report the cryoelectron microscopy structures of the GALR1-Go and the GALR2-Gq complexes bound to the endogenous ligand galanin or spexin. The galanin peptide mainly adopts an alpha helical structure, which binds at the extracellular vestibule of the receptors, nearly parallel to the membrane plane without penetrating deeply into the receptor core. Structural analysis combined with functional studies reveals important structural determinants for the G protein selectivity of GALRs as well as other class A GPCRs. In addition, we show that the zinc ion is a negative allosteric regulator of GALR1 but not GALR2. Our studies provide insight into the mechanisms of G protein selectivity of GPCRs and highlight potential novel function of the neuromodulator zinc ion as a modulator of GPCR signaling in the central nervous system.

Significance StatementGalanin exerts various physiological functions through galanin receptors, including antinociceptive activity, depression and sleep. Here, we reveal a distinct binding site and binding pose of galanin peptide in galanin receptors from that of the published structures of peptide-bound GPCRs. Moreover, our work show that the neuromodulator zinc ion negatively modulates galanin signaling in the central nervous system, and further advances our understanding of mechanisms of G protein selectivity of GPCRs. These unique features of galanin receptors can be exploited for rational design of subtype selective ligands for treatments of neurological disorders.


title: Metastability, fractal scaling, and synergistic information processing: what phase relationships reveal about intrinsic brain activity

abstract:
Dynamic functional connectivity (dFC) in resting-state fMRI holds promise to deliver candidate biomarkers for clinical applications. However, the reliability and interpretability of dFC metrics remain contested. Despite a myriad of methodologies and resulting measures, few studies have combined metrics derived from different conceptualizations of brain functioning within the same analysis - perhaps missing an opportunity for improved interpretability. Using a complexity-science approach, we assessed the reliability and interrelationships of a battery of phase-based dFC metrics including tools originated from dynamical systems, stochastic processes, and information dynamics approaches. Our analysis revealed novel relationships between these metrics, which allowed us to build a predictive model for integrated information using metrics from dynamical systems and information theory. Furthermore, global metastability - a metric reflecting simultaneous tendencies for coupling and decoupling - was found to be the most representative and stable metric in brain parcellations that included cerebellar regions. Additionally, spatiotemporal patterns of phase-locking were found to change in a slow, non-random, continuous manner over time. Taken together, our findings show that the majority of characteristics of resting-state fMRI dynamics reflect an interrelated dynamical- and informational-complexity profile, which is unique to each acquisition. This finding challenges the interpretation of results from cross-sectional designs for brain neuromarker discovery, suggesting that individual life-trajectories may be more informative than sample means.

HighlightsO_LISpatiotemporal patterns of phase-locking tend to be time-invariant
C_LIO_LIGlobal metastability is representative and stable in a cohort of heathy young adults
C_LIO_LIdFC characteristics are in general unique to any fMRI acquisition
C_LIO_LIDynamical- and informational-complexity are interrelated
C_LIO_LIComplexity science contributes to a coherent description of brain dynamics
C_LI


title: Robust, long-term video EEG monitoring in a porcine model of post-traumatic epilepsy.

abstract:
To date, post-traumatic epilepsy (PTE) research in large animal models has been limited. Recent advances in neocortical microscopy have made possible new insights into neocortical PTE. However, it is very difficult to engender convincing neocortical PTE in rodents. Thus, large animal models that develop neocortical PTE may provide useful insights that also can be more comparable to human patients. Because gyrencephalic species have prolonged latent periods, long-term video EEG recording is required. Here, we report a fully subcutaneous EEG implant with synchronized video in freely ambulatory swine for up to 14 months during epileptogenesis following bilateral cortical impact injuries or sham surgery The advantages of this system include the availability of a commercially available system that is simple to install, a low failure rate after surgery for EEG implantation, radiotelemetry that enables continuous monitoring of freely ambulating animals, excellent synchronization to video to EEG, and a robust signal to noise ratio. The disadvantages of this system in this species and age are the accretion of skull bone which entirely embedded a subset of skull screws and EEG electrodes, and the inability to rearrange the EEG electrode array. These disadvantages may be overcome by splicing a subdural electrode strip to the electrode leads so that skull growth is less likely to interfere with long-term signal capture and by placing two implants for a more extensive montage. This commercially available system in this bilateral cortical impact swine model may be useful to a wide range of investigators studying epileptogenesis in PTE.

SignificancePost-traumatic epilepsy (PTE) is a cause of significant morbidity after traumatic brain injury (TBI) and is often drug-resistant. Robust, informative animal models would greatly facilitate PTE research. Ideally, this biofidelic model of PTE would utilize a species that approximates human brain anatomy, brain size, glial populations, and inflammatory pathways. An ideal model would also incorporate feasible methods for long-term video EEG recording required to quantify seizure activity. Here, we describe the first model of PTE in swine and describe a method for robust long-term video EEG monitoring for up to 14 months post-TBI. The relatively easy "out-of-the-box" radiotelemetry system and surgical techniques described here will be adaptable by a wide array of investigators studying the pathogenesis and treatment of PTE.


title: Region Selective Cortical Control Of The Thalamic Reticular Nucleus

abstract: Corticothalamic pathways, responsible for the top-down control of the thalamus display a classical, canonical organization in that every cortical region sends dual, layer 6 (L6) and layer 5 (L5) output to the thalamus. Here we demonstrate a qualitative, region-specific difference in the organization of corticothalamic pathways. We show that L5 pyramidal cells of the frontal, but not other cortical regions establish monosynaptic connection with the inhibitory thalamic reticular nucleus (TRN). The frontal L5-TRN pathway paralleled the L6-TRN projection but displayed distinct morphological and physiological features. The exact spike output of the L5 contacted TRN cells correlated with the level of cortical synchrony. Optogenetic perturbation of the L5-TRN connection disrupted the tight link between cortical and TRN activity. L5-driven TRN cells innervated all thalamic nuclei involved in the control of frontal cortical activity. Our data show that frontal cortical functions require a highly specialized cortical control over intrathalamic inhibitory processes.


title: Plausible pathway for a host-parasite molecular replication network to increase its complexity through Darwinian evolution

abstract: How the complexity of primitive self-replication molecules develops through Darwinian evolution remains a mystery with regards to the origin of life. Theoretical studies have proposed that coevolution with parasitic replicators increases network complexity by inducing inter-dependent replication. However, the feasibility of such complexification with biologically relevant molecules is still unknown owing to the lack of an experimental model. Here, we investigated the plausible complexification pathway of host-parasite replicators using both an experimental host-parasite RNA replication system and a theoretical model based on the experimental system. We first analyzed the parameter space that allows for sustainable replication in various replication networks ranging from a single molecule to three-member networks using computer simulation. The analysis shows that the most plausible complexification pathway from a single host replicator is the addition of a parasitic replicator, followed by the addition of a new host replicator that is resistant to the parasite. We also provide evidence that the pathway actually occurred in our previous evolutionary experiment. These results provide both a theoretical basis and experimental evidence that a single replicator spontaneously develops into multi-replicator networks through coevolution with parasitic replicators, which might be the first complexification step toward to the emergence of life.

category: evolutionary biology


title: Probabilistic quotient's work and pharmacokinetics' contribution: countering size effect in metabolic time series measurements

abstract:
Metabolomic time course analyses of biofluids are highly relevant for clinical diagnostics. However, many sampling methods suffer from unknown sample sizes commonly known as size effects. This prevents absolute quantification of biomarkers. Recently, several mathematical post acquisition normalization methods have been developed to overcome these problems either by exploiting already known pharmacokinetic information or by statistical means.

Here we present an improved normalization method, MIX, that combines the advantages of both approaches. It couples two normalization terms, one based on a pharmacokinetic model (PKM) and the other representing a popular statistical approach, probabilistic quotient normalization (PQN), in a single model.

To test the performance of MIX, we generated synthetic data closely resembling real finger sweat metabolome measurements. We show that MIX normalization successfully tackles key weaknesses of the individual strategies: it (i) reduces the risk of overfitting with PKM, and (ii) contrary to PQN, it allows to compute sample volumes. Finally, we validate MIX by using real finger sweat as well as blood plasma metabolome data and demonstrate that MIX allows to better and more robustly correct for size effects.

In conclusion, the MIX method improves the reliability and robustness of quantitative biomarker detection in finger sweat and other biofluids, paving the way for quantitative biomarker discovery and hypothesis generation from metabolomic time course data.

category: bioinformatics


title: Identifying interactions in omics data for clinical biomarker discovery

abstract: The identification of predictive biomarker signatures from omics data for clinical applications is an active area of research. Recent developments in assay technologies and machine learning (ML) methods have led to significant improvements in predictive performance. However, most high-performing ML suffer from complex architectures and lack interpretability. Here, we present the application of a novel symbolic-regression-based method, the QLattice, on a selection of clinical omics data sets. This approach identifies putative regulatory interactions between biomolecules and generates parsimonious high-performing models that can both predict and explain the outcome of a given omics experiment. Due to their simplicity and explicit functional form, the models can be easily interpreted and have the potential to facilitate the discovery of new biomarker signatures.


title: SNP calling for the Illumina Infinium Omni5-4 SNP BeadChip kit using the butterfly method

abstract: We introduce the "butterfly method" for SNP calling with the Illumina Infinium Omni5-4 BeadChip kit without the use of Illumina GenomeStudio software. The method is a within-sample method and does not use other samples nor population frequencies to call SNPs. The butterfly method is based on a three-component mixture of normal distributions, in which parameters are easily found using the open-source statistical software R. This makes the method transparent, straight-forward to change parameters according to the users needs, and easy to analyse the data within R after the SNPs have been called. We contribute with two open-source R packages that make SNP calling easy by helping with bookkeeping and by giving easy access to meta-information about the SNPs on the Illumina Infinium Omni5-4 BeadChip Kit (including chromosome, probe type, and SNP bases). We test our method on > 4 mio. SNPs and compare the results with those obtained with the GenTrain method used by Illumina GenomeStudio as well as SNPs obtained by PCR-free whole genome sequencing (WGS). We demonstrate two variants of our method: one where we account for potential probe type bias by estimating a separate model for each probe type (type I and type II) and another that uses a general model such that the models parameter estimates do not depend on the sample that is being analysed. We focused on varying the no-call rate and show how it changed the concordance with that of WGS. This is done by using a threshold on the a posteriori probability of belonging to a SNP cluster and by using the number of beads to adjust the stringency of the no-call mechanism. With the butterfly method, we achieve a SNP call rate of around 99% and a SNP concordance of around 99% with the WGS data. By lowering the a posteriori probability threshold for no-calls, we can get a higher call rate fraction than the GenomeStudio and by using a higher a posteriori probability threshold, we can achieve a higher concordance with the WGS data than the GenomeStudio.


title: An evolutionary algorithm for inverse RNA folding inspired by Levy flights

abstract: A Levy flight is a random walk with step sizes that follow a heavy-tailed probability distribution. This type of random walk, with many small steps and a few large ones, has inspired many applications in genetic programming and evolutionary algorithms in recent years, but is yet to be applied to RNA design. Here we study the inverse folding problem for RNA, viz. the discovery of sequences that fold into given target secondary structures. We implement a Levy mutation scheme in an updated version of aRNAque, an evolutionary inverse folding algorithm, and apply it to the design of RNAs with and without pseudoknots. We find that the Levy mutation scheme increases the diversity of designed RNA sequences and reduces the average number of evaluations of the evolutionary algorithm. The results show improved performance on both Pseudobase++ and the Eterna100 datasets, outperforming existing inverse folding tools. We propose that a Levy flight offers a better standard mutation scheme for optimizing RNA design.


title: Matrix viscoelasticity controls spatio-temporal tissue organization

abstract: The spatio-temporal patterning of multicellular tissues is driven by the collective dynamics of cell proliferation and active movement. These processes are mediated by the extracellular matrix environment via a combination of biomolecular and physical cues. Here we show that the passive viscoelastic properties of the matrix that encapsulate a proliferating ball of cells (e.g. a developing organoid) play a critical role in guiding tissue organization in space and time. By varying the viscoelasticity of well-defined model matrices, we show how a spheroidal tissue of breast epithelial cells breaks symmetry and forms finger-like protrusions that invade the matrix. A computational model allows us to recapitulate these observations and leads to a phase diagram that demarcates the regions of morphological stability and instability as a function of matrix viscoelasticity, tissue viscosity, cell motility and cell division rate. Experiments that use biomolecular manipulations to independently vary these parameters confirm our predictions. To further test our theory, we also study the self-organization of an in-vitro intestinal organoid and show that the morphological changes of this system also fits within our paradigm. Altogether, our studies demonstrate the role of stress relaxation mechanisms in determining the dynamics of tissue growth and the symmetry breaking instabilities associated with branching, a fundamental process in morphogenesis and oncogenesis, and suggest ways of controlling tissue form using the extracellular matrix.

category: biophysics


title: Increasing discovery rates in preclinical research through optimised statistical decision criteria

abstract: The success of scientific discovery in preclinical drug development is based on the different roles of exploration and confirmation. Exploration requires sensitivity while confirmation needs to be specific. Based on published empirical data, we simulated two preclinical research trajectories to examine their effectiveness to detect true effects while keeping animal numbers low. We compare a conventional p-value based approach with a method based on an a priori determined smallest effect size of interest (SESOI). Using a SESOI increases transition rates from exploration to confirmation and results in higher detection rates across the trajectory. Specificity in the SESOI trajectory increases if the prior probability of true effects is low. We conclude that employing a SESOI is superior to a p-value based approach. Based on our findings, we propose a reconsideration of planning and conducting preclinical experiments, especially when the prior probability of true hypotheses is low.

category: scientific communication and education


title: Balancing sensitivity and specificity in preclinical research


title: Re-routing metabolism by the mitochondrial pyruvate carrier inhibitor MSDC-0160 attenuates neurodegeneration in a rat model of Parkinson's disease

abstract:
BackgroundA growing body of evidence supports the idea that mitochondrial dysfunction might represent a key feature of Parkinsons disease (PD). Central regulators of energy production, mitochondria are also involved in several other essential functions such as cell death pathways and neuroinflammation which make them a potential therapeutic target for PD management. Interestingly, recent studies related to PD have reported a neuroprotective effect of targeting mitochondrial pyruvate carrier (MPC) by the insulin sensitizer MSDC-0160. As the sole point of entry of pyruvate into the mitochondrial matrix, MPC plays a crucial role in energetic metabolism which is impacted in PD. This study therefore aimed at providing insights into the mechanisms underlying the neuroprotective effect of MSDC-0160.

MethodsWe investigated behavioral, cellular and metabolic impact of chronic MSDC-0160 treatment in unilateral 6-OHDA PD rats. We evaluated mitochondrial related processes through the expression of pivotal mitochondrial enzymes in dorsal striatal biopsies and the level of metabolites in serum samples using nuclear magnetic resonance spectroscopy (NMR)-based metabolomics.

ResultsMSDC-0160 treatment in unilateral 6-OHDA rats improved motor behavior, decreased dopaminergic denervation and reduced mTOR activity and neuroinflammation. Concomitantly, MSDC-0160 administration strongly modified energy metabolism as revealed by increased ketogenesis, beta oxidation and glutamate oxidation to satisfy energy needs and maintain energy homeostasis.

ConclusionMSDC-0160 exerts its neuroprotective effect through reorganization of multiple pathways connected to energy metabolism.


title: Isolating perceptual biases caused by trial history during auditory categorization

abstract: Just as most experiences have their origin in our perceptions, our perceptions can also be fundamentally shaped by our experiences. However, isolating which events in the recent past can impact perceptual judgments remains a difficult question, partly because post-perceptual processes can also introduce strong history dependencies. Two mechanisms have been hypothesized to specifically modulate perception: 1) the repulsive influence caused by previous stimuli and generally labeled as aftereffects, and 2) the modulation caused by stimulus predictions based on learned temporal regularities of the sensory environment, a key assumption in the predictive coding framework. Here, we ask whether these two mechanisms do indeed bias perception by training rats in an auditory task featuring serial correlations along the sequence of stimuli. We develop a detailed behavioral model that isolates the repulsive aftereffect generated by previous stimuli and shows that this repulsion cannot be explained from an interaction between past and current stimuli, and that it is still present in catch trials lacking the current stimulus. Moreover, the model describes that the bias caused by the animals expectation, as they leverage the predictability of the stimulus sequence, is present in a foraging task without the sensory component but with the same serial correlations in the sequence of rewards. These results indicate that the aftereffect and the prediction biases observed during an auditory task can all be revealed in the absence of a sensory stimulus, putting into question their perceptual nature.


title: Predator-prey interactions in a warming world: the critical role of cold tolerance

abstract: Thermal tolerance mismatch within predator-prey systems may have pro-found effects on species population abundances and geographical distributions. To examine the generalized responses of a predator-prey system to climate change, we construct a biologically detailed stage-structured population dynamic model of interactions between ladybird beetles and aphids. We explore the models dynamics across the entire feasible parameter space of mean temperature and seasonality. Within this space, we explore different scenarios of predator and prey thermal tolerance mismatch to gain insight into how these thermal sensitivities affect the interacting species responses to climatic change. Our results indicate a predators cold tolerance has a larger effect on prey abundance than its heat tolerance. Mismatches between the predators and preys thermal tolerances also affect the species response to climate change. We identify three common patterns of species abundance across the feasible parameter space that relate to the type of thermal tolerance mismatches. Our study highlights the importance of understanding the complex interplay between climate change and species interactions.


title: Impact of ionizing radiation on the environmental microbiomes of Chernobyl wetlands

abstract: Radioactive contamination in the form of ionizing radiation can be a devastating pollutant because it has the potential to cause damage to DNA and other biomolecules. Anthropogenic sources of ionizing radiation include accidents in nuclear power plants, such as the one in Chernobyl 1986, which caused long-term radioactive pollution. Studies on animals within radioactive zones have provided us with a greater understanding of how wildlife can persevere despite chronic radiation exposure, however, we still know very little about the effects of radiation on the microbial communities in the environment. Here, we examined the impact of ionizing radiation and other environmental factors on the diversity and composition of environmental microbiomes in the wetlands of Chernobyl. We combined extensive field sampling along a gradient of radiation together with 16S rRNA high-throughput metabarcoding (Illumina NovaSeq). While radiation did not affect the alpha diversity of the microbiomes in sediment, soil, or water, it had a strong effect on the beta diversity, indicating that the microbial composition was affected by ionizing radiation. Specifically, we detected several microbial taxa that were more abundant in areas with high radiation levels within the Chernobyl Exclusion Zone, including bacteria and archaea known to be radioresistant. Overall, our results reveal the existence of rich and diverse microbiomes in Chernobyl wetlands, with multiple taxonomic groups that are able to thrive despite the radioactive contamination. Further field and laboratory-based approaches will help to forecast the functionality and re-naturalization dynamics of radiocontaminated environments.


title: Combinatorial selection of biomarkers to optimize gene signatures in diagnostics and single cell applications

abstract: Biomarker selection is a critical step in research and diagnostics: here we present the newly developed "combiroc" R package, for fast and reproducible identification of diagnostic and/or research biomarkers. The package introduces new features for automatic assessment of signal thresholds, as well as functions for identification of unlabeled samples. We also show how combiroc leverages better and unambiguous cell type assignment in single cell RNA sequencing experiments through the combinatorial selection of highly specific gene sub-signatures.


title: Symbolic Kinetic Models in Python (SKiMpy): Intuitive modeling of large-scale biological kinetic models

abstract:
MotivationLarge-scale kinetic models are an invaluable tool to understand the dynamic and adaptive responses of biological systems. The development and application of these models have been limited by the availability of computational tools to build and analyze large-scale models efficiently. The toolbox presented here provides the means to implement, parametrize and analyze large-scale kinetic models intuitively and efficiently.

ResultsWe present a Python package (SKiMpy) bridging this gap by implementing an efficient kinetic modeling toolbox for the semiautomatic generation and analysis of large-scale kinetic models for various biological domains such as signaling, gene expression, and metabolism. Furthermore, we demonstrate how this toolbox is used to parameterize kinetic models around a steady-state reference efficiently. Finally, we show how SKiMpy can imple-ment multispecies bioreactor simulations to assess biotechnological processes.

AvailabilityThe software is available as a Python 3 package on GitHub: https://github.com/EPFL-LCSB/SKiMpy, along with adequate documentation.

Contactvassily.hatzimanikatis@epfl.ch


title: Contractility-induced self-organization of smooth muscle cells: from multilayer cell sheets to dynamic three-dimensional clusters

abstract: Smooth muscle cells (SMCs) are mural cells that play a vital contractile function in many tissues. Abnormalities in SMC organization are associated with many diseases including atherosclerosis, asthma, and uterine fibroids. Various studies have reported that SMCs cultured on flat surfaces can spontaneously form three-dimensional clusters whose organization resembles that encountered in some of these pathological settings. Remarkably, how these structures form remains unknown. Here we combine in vitro experiments and physical modeling to show that three-dimensional clusters initiate when cellular contractile forces induce a hole in a flat SMC sheet, a process that can be modeled as the brittle fracture of a viscoelastic material. The subsequent evolution of the nascent cluster can be modeled as an active dewetting process with cluster shape evolution driven by a balance between cluster surface tension, arising from both cell contractility and adhesion, and cluster viscous dissipation. The description of the physical mechanisms governing the spontaneous emergence of these intriguing three-dimensional clusters offers insight into SMC-related disorders.


title: Improvements in estimating bioaccumulation metrics in the light of toxicokinetics models and Bayesian inference

abstract: The surveillance of chemical substances in the scope of Environmental Risk Assessment (ERA) is classically performed through bio-assays from which data are collected and then modelled. Some statistical analysis base on the fitting of toxicokinetic (TK) models to assess the bioaccumulative capacity of chemical substances via the estimation of bioaccumulation metrics as required by regulatory documents. Given that bio-assays are particularly expensive and time consuming, it is of crucial importance to deeply benefit from all information contained in the data. By revisiting the calculation of bioaccumulation metrics under a Bayesian framework, this paper presents improvements in the classification of the bioaccumulative capacity of chemical substances. A meta-analysis of a data-rich TK database was performed, considering the uncertainties around the bioaccumulation metrics. The subsequent results appeared sufficiently statistically robust to propose the replacement of the single median estimate to decide of the class to which assign a chemical substance. The main recommendation is to use the 75th percentile of the uncertainty interval of the bioaccumulation metrics, which revealed a better criterion to classify a chemical substance, and in the same way as the conventional method in 90% of cases.

category: pharmacology and toxicology


title: A systematic evaluation of yeast sample preparation protocols for spectral identifications, proteome coverage and post-isolation modifications

abstract: The importance of obtaining comprehensive and accurate information from cellular proteomics experiments asks for a systematic investigation of sample preparation protocols, particularly when working with unicellular organisms with strong cell walls, such as found in the model organism and cell factory S. cerevisiae. Sample preparation protocols may bias towards specific protein fractions or challenge the analysis of native protein modifications due to reagent-induced artefacts. Here, we performed a systematic comparison of sample preparation protocols using a matrix of different conditions commonly applied in whole cell lysate proteomics. The different protocols were evaluated for their overall fraction of identified spectra, proteome and amino acid sequence coverage, GO-term distribution and number of peptide modifications, by employing a combination of database and unrestricted modification search approaches. The best proteome and amino acid sequence coverage was achieved by using Urea combined with filter-aided or in-solution digestion protocols, where the overall outcomes were strongly influenced by the employed quenching procedure. Most importantly, the use of moderate incubation temperatures and times, circumvented excessive formation of modification artefacts. Extensive reagent-induced peptide modifications, however, were observed when using solvents such as acetone or additives such as formic acid. Moreover, several filter material-related modifications were observed when employing the filter-aided procedures. Ultimately, the best protocols enabled the identification of approximately 65-70% of all acquired fragmentation spectra, where additional de novo sequencing suggests that unidentified spectra were largely of too low spectral quality to provide confident spectrum matches. This study demonstrates the large impact of different sample preparation procedures on the proteomic analysis outcome, where the collected protocols and large sets of associated mass spectrometric raw data provide a resource to evaluate and design new protocols and guide the analysis of (native) peptide modifications in the model eukaryote yeast.

category: systems biology


title: A whole-brain 3D myeloarchitectonic atlas: mapping the Vogt-Vogt legacy to the cortical surface

abstract:
Building precise and detailed parcellations of anatomically and functionally distinct brain areas has been a major focus in Neuroscience. Pioneer anatomists parcellated the cortical manifold based on extensive histological studies of post-mortem brain, harnessing local variations in cortical cyto- and myeloarchitecture to define areal boundaries. Compared to the cytoarchitectonic field, where multiple neuroimaging studies have recently translated this old legacy data into useful analytical resources, myeloarchitectonics, which parcellate the cortex based on the organization of myelinated fibers, has received less attention. Here, we present the neocortical surface-based myeloarchitectonic atlas based on the histology-derived maps of the Vogt-Vogt school and its 2D translation by Nieuwenhuys. In addition to a myeloarchitectonic parcellation, our package includes intracortical laminar profiles of myelin content based on Vogt-Vogt-Hopf original publications. Histology-derived myelin density mapped on our atlas demonstrate close overlap with in vivo quantitative MRI markers for myelin and relates to cytoarchitectural features. Complementing the existing battery of approaches for digital cartography, the whole-brain myeloarchitectonic atlas offers an opportunity to validate imaging surrogate markers of myelin in both health and disease.

HighlightsO_LIOur myeloarchitectonic atlas builds on extensive meta-analyses-derived and ground-truth histological data.
C_LIO_LIOur atlas provides qualitative and quantitative 3D information on cortical myelin architecture.
C_LIO_LIMRI surrogate markers of myelin demonstrate close overlap with histological cortical parcellations, supporting biological validity of non-invasive metrics.
C_LIO_LIThis atlas can be seamlessly integrated into widely used neuroimaging analysis software to inform studies in health and disease.
C_LI


title: Cell-Type Specific Profiling of Histone Post-Translational Modifications in the Adult Mouse Striatum

abstract: Histone post-translational modifications (hPTMs) regulate gene expression via changes in chromatin accessibility and transcription factor recruitment. At a given locus, the coordinated enrichment of several distinct hPTMs regulate gene expression in response to external stimuli. However, neuronal hPTMs have been primarily characterized in bulk brain tissue and/or tissue pooled across subjects. This obscures both cell-type and individual variability, features essential to understand individual susceptibility to psychiatric disease. To address this limitation, we optimized a hybrid protocol, ICuRuS, to profile both activating and repressive hPTMs in neuronal subtypes from a single mouse. We report here profiling of striatal medium spiny neuron (MSN) subtypes, genetically defined by expression of Adenosine 2a Receptor (A2a) or Dopamine Receptor D1 (D1), which differentially regulate reward processing and pathophysiology. Using ICuRuS, we defined genome-wide, A2a- or D1-specific combinatorial hPTM profiles, and discovered regulatory epigenomic features at genes implicated in neurobiological function and disease.


title: Alveolar cell fate selection and lifelong maintenance of AT2 cells by FGF signaling

abstract:
The lungs gas exchange surface comprises thin alveolar type 1 (AT1) cells and cuboidal surfactant-secreting AT2 cells that are corrupted in some of the most common and deadly diseases including adenocarcinoma, emphysema, and SARS/Covid-19. These cells arise from an embryonic progenitor whose development into an AT1 or AT2 cell is thought to be dictated by differential mechanical forces. Here we show the critical determinant is FGF signaling. FGF Receptor 2 (Fgfr2) is expressed in mouse progenitors then restricts to nascent AT2 cells and remains on throughout life. Its ligands are expressed in surrounding mesenchyme and can, in the absence of differential mechanical cues, induce purified, uncommitted E16.5 progenitors to form alveolus-like structures with intermingled AT2 and AT1 cells. FGF signaling directly and cell autonomously specifies AT2 fate; progenitors lacking Fgfr2 in vitro and in vivo exclusively acquire AT1 fate. Fgfr2 loss in AT2 cells perinatally results in reprogramming to AT1 fate, whereas loss or inhibition later in life immediately triggers AT2 apoptosis followed by a compensatory regenerative response. We propose Fgfr2 signaling directly selects AT2 fate during development, induces a cell non-autonomous secondary signal for AT1 fate, and stays on throughout life to continuously maintain healthy AT2 cells.

One Sentence SummaryFGF signaling induces and distinguishes the two cell types of the lungs gas exchange surface, and the pathway remains on throughout life to maintain one that can be transformed into lung cancer or targeted in the deadly form of SARS/Covid-19.

category: developmental biology


title: The formal demography of kinship IV: Two-sex models

abstract:
BackgroundPrevious kinship models analyze female kin through female lines of descent, neglecting male kin and male lines of descent. Because males and females differ in mortality and fertility, including both sexes in kinship models is an important unsolved problem.

ObjectivesThe objectives are to develop a kinship model including female and male kin through all lines of descent, to explore approximations when full sex-specific rates are unavailable, and to apply the model to several populations as an example.

MethodsThe kin of a focal individual form an agexsex-classified population and are projected as Focal ages using matrix methods, providing expected age-sex structures for every type of kin at every age of Focal. Initial conditions are based on the distribution of ages at maternity and paternity.

ResultsThe equations for two-sex kinship dynamics are presented. As an example, the model is applied to populations with large (Senegal), medium (Haiti), and small (France) differences between female and male fertility. Results include numbers and sex ratios of kin as Focal ages. An approximation treating female and male rates as identical provides some insight into kin numbers, even when male and female rates are very different.

ContributionMany demographic and sociological parameters (e.g., aspects of health, bereavement, labor force participation) differ markedly between the sexes. This model permits analysis of such parameters in the context of kinship networks. The matrix formulation makes it possible to extend the two-sex analysis to include kin loss, multistate kin demography, and time varying rates.


title: Regulators of proteostasis are translationally repressed in fibroblasts from sporadic and LRRK2-G2019S Parkinson's patients

abstract: Parkinsons disease (PD) is characterized by heterogeneous motor and non-motor symptoms. The majority of PD cases are sporadic, whereas the leucine-rich repeat kinase 2 (LRRK2) G2019S mutation is the most common monogenic cause of familial PD and symptomatically indistinguishable from the sporadic form. Deficits in protein synthesis have been reported in PD. However, it is not known which proteins are affected or if there are synthesis differences between patients with sporadic and LRRK2 G2019S PD. Here we used non-canonical amino acid labeling and mass-spectrometry based proteomics to perform a quantitative comparison of nascent proteins in fibroblasts from sporadic and G2019S mutation PD patients compared to healthy individuals. We found that several proteins were under-represented among nascent proteins in cells from PD patients. Among these were regulators endo-lysosomal sorting, mRNA processing and translation itself. We further validated which of these proteins were dysregulated at the static proteome level using targeted proteomics. Key downregulated proteins included the autophagy regulator ATG9A and translational stability regulator YTHDF3. Notably, 68% of the identified proteins were downregulated in both sporadic and LRRK2-G2019S forms of PD. We identify translational repression of key regulators of proteostasis in patient fibroblasts that are common to both sporadic and LRRK2-G2019S PD.


title: Serological screening suggests single SARS-CoV-2 spillover events to cattle

abstract: Widespread human SARS-CoV-2 infections pose a constant risk for virus transmission to animals. Here, we serologically investigated 1000 cattle samples collected in late 2021 in Germany. Eleven sera tested antibody-positive, indicating that cattle may be occasionally infected by contact to SARS-CoV-2-positive keepers, but there is no indication of further spreading.

category: microbiology


title: A deep CNN framework for neural drive estimation from HD-EMG across contraction intensities and joint angles

abstract:
ObjectivePrevious studies have demonstrated promising results in estimating the neural drive to muscles, the net output of all motoneurons that innervate the muscle, using high-density electromyography (HD-EMG) for the purpose of interfacing with assistive technologies. Despite the high estimation accuracy, current methods based on neural networks need to be trained with specific motor unit action potential (MUAP) shapes updated for each condition (i.e., varying muscle contraction intensities or joint angles). This preliminary step dramatically limits the potential generalization of these algorithms across tasks. We propose a novel approach to estimate the neural drive using a deep convolutional neural network (CNN), which can identify the cumulative spike train (CST) through general features of MUAPs from a pool of motor units.

MethodsWe recorded HD-EMG signals from the gastrocnemius medialis muscle under three isometric contraction scenarios: 1) trapezoidal contraction tasks with different intensities, 2) contraction tasks with a trapezoidal or sinusoidal torque target, and 3) trapezoidal contraction tasks at different ankle angles. We applied a convolutive blind source separation (BSS) method to decompose HD-EMG signals to CST and segmented both signals into windows to train and validate the deep CNN. Then, we optimized the structure of the deep CNN and validated its generalizability across contraction tasks within each scenario.

ResultsWith the optimal configuration for the HD-EMG data window (overlap of 20 data points and window length of 40 data points), the deep CNN estimated the CST close to that from BSS, with a correlation coefficient higher than 0.96 and normalized root-mean-square-error lower than 7% with respect to the BSS (golden standard) within each scenario.

ConclusionThe proposed deep CNN framework can utilize data from different contraction tasks (e.g., different intensities), learn general features of MUAP variants, and estimate the neural drive for other contraction tasks.

SignificanceWith the proposed deep CNN, we could potentially build a neuraldrive-based human-machine interface that is generalizable to different contraction tasks without retraining.


title: Joint embedding of biological networks for cross-species functional alignment

abstract: Model organisms are widely used to better understand the molecular causes of human disease. While sequence similarity greatly aids this transfer, sequence similarity does not imply functional similarity, and thus, several current approaches incorporate protein-protein interactions (PPIs) to help map findings between species. Existing transfer methods either formulate the alignment problem as a matching problem which pits network features against known orthology, or more recently, as a joint embedding problem. Here, we propose a novel state-of-the-art joint embedding solution: Embeddings to Network Alignment (ETNA). More specifically, ETNA generates individual network embeddings based on network topological structures and then uses a Natural Language Processing-inspired cross-training approach to align the two embeddings using sequence orthologs. The final embedding preserves both within and between species gene functional relationships, and we demonstrate that it captures both pairwise and group functional relevance. In addition, ETNAs embeddings can be used to transfer genetic interactions across species and identify phenotypic alignments, laying the groundwork for potential opportunities for drug repurposing and translational studies.


title: Sequencing of individual barcoded cDNAs on Pacific Biosciences and Oxford Nanopore reveals platform-specific error patterns

abstract: Long-read transcriptomics requires understanding error sources inherent to technologies. Current approaches cannot compare methods for an individual RNA molecule. Here, we present a novel platform comparison method that combined barcoding strategies and long-read sequencing to sequence cDNA copies representing an individual RNA molecule on both Pacific Biosciences and Oxford Nanopore. We compared these long reads pairs in terms of sequence content and splicing structure. Although individual read pairs show high similarity, we found differences in (i) aligned length, (ii) TSS and (iii) polyA-site assignment, and (iv) exon-intron structures. Overall 25% of read pairs disagreed on either TSS, polyA-site, or a splice site. Intron-chain disagreement typically arises from alignment errors of microexons and complicated splice sites. Our single-molecule technology comparison revealed that inconsistencies are often caused by sequencing-error induced inaccurate ONT alignments, especially to downstream GTNNGT donor motifs. However, annotation-disagreeing upstream shifts in NAGNAG acceptors in ONT are often confirmed by PacBio and thus likely real. In both barcoded and non-barcoded ONT reads, we found that intron number and proximity of other GT/AGs better predict inconsistency with the annotation than read quality alone. We summarized these findings in an annotation-based algorithm for spliced alignment correction that improves subsequent transcript construction with ONT reads.


title: CView: A network based tool for enhanced alignment visualization

abstract: To date basic visualization of sequence alignments have largely focused on displaying per-site columns of nucleotide, or amino acid, residues along with associated frequency summarizations. The persistence of this tendency to the more recent tools designed for the viewing of mapped read data indicates that such a perspective not only provides a reliable visualization of per-site alterations, but also offers implicit reassurance to the end user in relation to data accessibility. However, the initial insight gained is limited, something that is especially true when viewing alignments consisting of many sequences representing differing factors, such as geographical location, date and subtype. A basic alignment viewer can have potential to increase initial insight through visual enhancement, whilst not delving into the realms of complex sequence analysis. Here we present CView, a visualizer that expands on the per-site representation of residues through the incorporation of a dynamic network that is based on the summarization of diversity present across different regions of the alignment. Within the network nodes are based on the clustering of sequence fragments spanning windows that are placed consecutively along the alignment. Edges are placed between nodes of neighbouring windows where they share sequence ids. Thus, if a single node is selected on the network, then the relationship that all sequences passing through that node have to other regions of diversity within the alignment can be instantly observed through the tracing of paths. In addition to augmenting visual insight, CView provides many export features including variant summarization, per-site residue and kmer frequency matrixes, consensus sequence generation, alignment dissection as well as general sequence clustering, each of which are useful across a range of research areas. The software has been designed to be user friendly, intuitive and interactive. It, along with source code, a quick start guide and test data, are available through the SourceForge project page: https://sourceforge.net/projects/cview/.


title: Integration of heterogeneous biological data in multiscale mechanistic model calibration: application to lung adenocarcinoma

abstract: Mechanistic models are built using knowledge as the primary information source, with well-established biological and physical laws determining the causal relationships within the model. Once the causal structure of the model is determined, parameters must be defined in order to accurately reproduce relevant data. Determining parameters and their values is particularly challenging in the case of models of pathophysiology, for which data for calibration is sparse. Multiple data sources might be required, and data may not be in a uniform or desirable format. We describe a calibration strategy to overcome the challenges of scarcity and heterogeneity of calibration data. Our strategy focuses on parameters where initial values cannot be easily derived from the literature and where final values are estimated via calibration with constraints set by relevant data. When combined with a covariance matrix adaptation evolution strategy (CMA-ES), this step-by-step approach can be applied to a wide range of biological models. We describe a stepwise, integrative and iterative approach to multiscale mechanistic model calibration, and provide an example of calibrating a pathophysiological lung adenocarcinoma model. Using the approach described here we illustrate the successful calibration of a complex knowledge-based mechanistic model using only the limited heterogeneous datasets publicly available in the literature.


title: Xeno-free induced pluripotent stem cell-derived neural progenitor cells for in vivo applications

abstract: Cell-based therapies are a promising treatment paradigm for neurodegenerative diseases and other brain injuries. Despite recent advances in stem cell technology, major concerns have been raised regarding the feasibility and safety of cell therapies for clinical applications. Here, we generate good manufacturing practice (GMP)-compatible neural progenitor cells (NPCs) from transgene- and xeno-free induced pluripotent stem cells (iPSCs) that can be smoothly adapted for clinical applications. The produced NPCs have a stable gene-expression over at least 15 passages and can be scaled for up to 1018 cells per initially seeded 106 cells. To ensure a pure NPC population for in vivo applications, we reduce risks of iPSC contamination using micro RNA-switch technology as a safety checkpoint. Using lentiviral transduction with a fluorescent and bioluminescent dual-reporter construct, combined with non-invasive in vivo bioluminescent imaging, we longitudinally tracked the grafted cells in healthy wild-type and genetically immunosuppressed mice as well as in a mouse model of ischemic stroke. Long term in-depth characterization revealed that transplanted cells have the capability to survive and spontaneously differentiate into functional and mature neurons throughout a time course of a month.


title: Modified viral-genetic mapping reveals local and global connectivity relationships of ventral tegmental area dopamine cells

abstract: Dopamine cells in the ventral tegmental area (VTADA) are critical for a variety of motivated behaviors. These cells receive synaptic inputs from over 100 anatomically-defined brain regions, which enables control from a distributed set of inputs across the brain. Extensive efforts have been made to map inputs to VTA cells based on neurochemical phenotype and output site. However, all of these studies have the same fundamental limitation that inputs local to the VTA cannot be properly assessed due to non-Cre-dependent uptake of EnvA-pseudotyped virus. Therefore, the quantitative contribution of local inputs to the VTA, including GABAergic, DAergic, and serotonergic, is not known. Here, we used a modified viral-genetic strategy that enables examination of both local as well as long-range inputs to VTADA cells. We found that nearly half of the total inputs to VTADA cells are located locally, revealing a substantial portion of inputs that have been missed by previous analyses. The majority of inhibition to VTADA cells arises from the substantia nigra pars reticulata, with large contributions from the VTA and the substantia nigra pars compacta. In addition to receiving inputs from VTAGABA neurons, DA neurons are connected with other DA neurons within the VTA as well as the nearby retrorubal field. Lastly, we show that VTADA neurons receive inputs from distributed serotonergic neurons throughout the midbrain and hindbrain, with the majority arising from the dorsal raphe. Our study highlights the importance of using the appropriate combination of viral-genetic reagents to unmask the complexity of connectivity relationships to defined cells in the brain.


title: Membrane Stretch Gates NMDA Receptors

abstract:
N-Methyl-D-aspartic (NMDA) receptors are excitatory glutamate-gated ion channels. Their activation is essential for the normal development, maintenance, and plasticity of excitatory synapses in the central nervous system. They function as glutamate-gated Ca2+-permeable channels, require glycine as co-agonist, and can be modulated by myriad of diffusible ligands and cellular cues, including mechanical stimuli. Previously, we found that in cultured astrocytes, shear stress initiates NMDA receptor-mediated Ca2+ entry in the absence of added agonists, suggesting that in addition to being mechanosensitive, NMDA receptors may be mechanically activated. Here, we used controlled expression of recombinant receptors and non-invasive on-cell single-channel current recordings to show that gentle membrane stretch can substitute for the neurotransmitter glutamate in gating NMDA receptor currents. Notably, stretch-activated currents preserved the hallmark features of the glutamate-gated currents, including glycine-requirement, large unitary conductance, high Ca2+ permeability, and voltage-dependent Mg2+ blockade. Further, we found that the stretch-gated current required the receptors intracellular domain, which may suggest a force-from-filament sensing mechanism. These results are consistent with the hypothesis that mechanical forces can gate NMDA receptor currents even in the absence of synaptic glutamate release, which has important implications for understanding mechanotransduction and the effect of mechanical forces on cells of the central nervous system.

HighlightsO_LIMembrane stretch gates NMDA receptor currents in the absence of the neurotransmitter glutamate.
C_LIO_LIStretch-gated currents maintain the characteristic features of glutamate-gated currents, including glycine requirement, Ca2+ permeability, and voltage-dependent Mg2+ block.
C_LIO_LIGating of NMDA receptor by membrane stretch requires the receptors intracellular domain.
C_LIO_LIMild stretch of neuronal membranes gate native NMDA receptor currents.
C_LI

SummaryMembrane stretch gates NMDA receptor currents in the absence of neurotransmitter. Stretch-gated currents have the biophysical hallmarks of the glutamate-gated currents including requirement for glycine, large Na+ conductance, high Ca2+ permeability, and voltage-dependent Mg2+ block.


title: A Multisite and Multimodal Comparative Study of Cerebellar Connectome Between Multiple Sclerosis and Neuromyelitis Optica Spectrum Disorders

abstract: The cerebellum has been increasingly recognized to play key roles in the pathology of multiple sclerosis (MS) and spectrum disorders (NMOSD), two main demyelinating diseases with similar clinical presentations. Despite accumulating evidence from neuroimaging research for cerebellar volumetric alterations in the diseases, however, there have been no network-based studies examining convergent and divergent alterations in cerebellar connectome between MS and NMOSD. This multisite and multimodal study examined common and specific alterations in within-cerebellar coordination and cerebello-cerebral communication between MS and NMOSD by retrospectively collecting structural and resting-state functional MRI data from 208 MS patients, 200 NMOSD patients and 228 healthy controls (HCs) in seven sites in China. Morphological brain networks were constructed by estimating interregional similarity in cortical thickness and functional brain networks were formed by calculating interregional temporal synchronization in functional signals. After identifying cerebellar modular architecture and based on prior cerebral cytoarchitectonic classification and functional partition, within-cerebellar and cerebello-cerebral morphological and functional connectivity were compared among the MS, NMOSD and HC groups. Five modules were identified within the cerebellum including Primary Motor A (PMA), Primary Motor B (PMB), Primary Non-Motor (PNM), Secondary Motor (SM) and Secondary Non-Motor (SNM) modules. Compared with the HCs, the MS and NMOSD patients exhibited both increases and decreases in within-cerebellar morphological connectivity that were mainly involved in the PMA, PMB and SNM. Particularly, the two patient groups showed a common altered pattern characterized by decreases between the PMA and SNM, both of which were more densely connected with the PMB. For cerebello-cerebral morphological connectivity, widespread reductions were found in both patient groups for the SM and SNM with almost all cerebral cytoarchitectonic classes and functional systems while increases were observed only in the NMOSD patients for the PMB with cerebral areas involving motor and sensory domains. With regard to cerebellar functional connectivity, fewer alterations were observed in the patients that were all characterized by reductions and were mainly involved in cerebello-cerebral interactions between cerebellar motor modules and cerebral association cortex and high-order networks, particularly in the NMOSD patients. Cerebellar connectivity-based classification achieved around 60% accuracies to distinguish the three groups to each other with morphological connectivity as predominant features for differentiating the patients from controls while functional connectivity for discriminating the two diseases. Altogether, this study characterizes common and specific circuit dysfunctions of the cerebellum between MS and NMOSD, which provide novel insights into shared and unique pathophysiologic mechanisms underlying the two diseases.


title: Region-specific CREB function regulates distinct forms of regret associated with resilience versus susceptibility to chronic stress

abstract: Regret describes recognizing that alternative actions could have led to better outcomes. This can transform into behavioral consequences, altering subsequent valuations, but remains unclear if regret derives from a generalized computation for mistake appraisal or instead is made up of dissociable action-specific processes. Using a novel neuroeconomic decision-making paradigm, we found mice were differentially sensitive to fundamentally distinct types of missed opportunities following exposure to chronic social defeat stress or manipulations of CREB, a key transcription factor implicated in chronic stress action. Bias to make compensatory decisions after rejecting high-value offers (regret type I) was unique to stress-susceptible mice. Bias following the converse operation, accepting low-value offers (regret type II), was enhanced in stress-resilient and absent in stress-susceptible mice. CREB function in either the medial prefrontal cortex or nucleus accumbens was required to suppress regret type I but differentially affected regret type II. We provide insight into how adaptive versus maladaptive stress-response traits may be related to fundamentally distinct forms of counterfactual thinking and could steer psychotherapy for mood disorders such as depression toward unveiling circuit-specific computations through a careful description of decision narrative.


title: T cell response following anti COVID-19 BNT162b2 vaccination is maintained against the SARS-CoV-2 Omicron B.1.1.529 variant of concern

abstract: The progression of the COVID-19 pandemic leads to the emergence of variants of concern (VOC), which may compromise the efficacy of the currently administered vaccines. Antigenic drift can potentially bring about a reduced protective T cell immunity and consequently to more severe disease manifestations. To assess this possibility, the T cell responses to the wild-type, Wuhan-1 SARS-CoV-2 ancestral spike protein and Omicron B.1.1.529 spike protein were compared. Accordingly, peripheral blood mononuclear cells (PBMC) were collected from 8 healthy volunteers 4-5 months following a third vaccination with BNT162b2, and stimulated with overlapping peptide libraries representing the spike of either the ancestral or Omicron SARS-CoV- 2 virus variants. Quantification of the specific T cells was carried out by a fluorescent ELISPOT assay, monitoring interferon-gamma (IFNg), interleukin-10 (IL-10) and interleukin-4 (IL-4) secreting cells. For all the examined individuals, comparable level of reactivity to both forms of spike protein were determined. In addition, a dominant Th1 response was observed, manifested mainly by IFNg secreting cells and only limited numbers of IL-10 and IL-4 secreting cells. The data demonstrates a stable T cell activity to the emerging Omicron variant in the tested individuals, therefore the protective immunity to the variant following BNT162b2 vaccination is not significantly affected.


title: Fat2 polarizes the WAVE complex in trans to align cell protrusions for collective migration

abstract: For a group of cells to migrate together, each cell must couple the polarity of its migratory machinery with that of the other cells in the cohort. Although collective cell migrations are common in animal development, little is known about how protrusions are coherently polarized among groups of migrating epithelial cells. We address this problem in the collective migration of the follicular epithelial cells in Drosophila melanogaster. In this epithelium, the cadherin Fat2 localizes to the trailing edge of each cell and promotes the formation of lamellipodia at the leading edge of the cell behind. We show that Fat2 performs this function by acting in trans to restrict WAVE complex activity to one long-lived region along each cells leading edge. Without Fat2, the WAVE complex distribution expands around the cell perimeter and fluctuates over time, resulting in reduced, unpolarized protrusive activity. We further show that Fat2s influence is very local, with sub-micron-scale puncta of Fat2 concentrating the WAVE complex in corresponding puncta just across the leading-trailing cell-cell interface. These findings demonstrate that a trans interaction between Fat2 and the WAVE complex creates stable regions of protrusive activity in each cell and aligns the cells protrusions across the epithelium for directionally persistent collective migration.


title: Olive mill wastewater extract as a potential mosquito larvicide

abstract: The larvicidal potential of olive mill waste water (OMWW) extract against mosquito larvae was evaluated. We exposed 2nd and 4th instar Culex laticinctus (Edwards) larvae to increasing OMWW concentrations. In addition, the effects of sublethal OMWW concentrations on larval development time and adult size were tested as well. The larvicidal activity of OMWW extract showed LC50 values of 10.08 and 50.07 parts per thousand (ppt) against the 2nd and 4th instars respectively. Larvae that developed in 1 ppt OMWW solution showed sex-specific responses. Males prolonged time to pupation, while females exhibited size reduction in comparison to controls. These results show that OMWW, which is known as agricultural byproduct waste, may be reused as a biopesticide.


title: Assessing the impact of roadkill on the persistence of wildlife populations: a case study on the giant anteater

abstract: Human activity is depleting biodiversity, and road networks are directly contributing to this trend due to roadkill. Nevertheless, few studies empirically estimated the impact of roadkill on wildlife populations. We integrated information on roadkill rates, population abundance, and animal movement to estimate the survival rates and the proportion of the population likely to be extirpated due to roadkill, using giant anteater (Myrmecophaga tridactyla) as model species. We then assessed the consequent implications of roadkill on population persistence using population viability analysis (PVA). The yearly survival rate of resident anteaters inhabiting road vicinity areas (0.78; CI:0.62-0.97) was considerably lower than for those living far from roads (0.95; CI:0.86-1.00). The real number of anteaters being road-killed is considerably higher than the one recorded in previous studies (by a factor of 2.4), with ca. 20% of the population inhabiting road vicinity areas being road-killed every year. According to PVA results, roadkill can greatly affect the persistence of the giant anteater populations by reducing the growth rate down to null or negative values. This study confirms that roads have significant impacts on local population persistence. Such impacts are likely to be common to other large mammals, calling for effective mitigation to reduce roadkill rates.


title: Mitochondrial diversity in the ribbed mussel, Geukensia demissa, relative to high marsh plant diversity at the southern edge of the distribution

abstract: Genomic diversity and relatedness among sample sites are often used to explore landscape-level processes of how and where organisms are limited in movement. In many cases, these patterns of diversity and relatedness can be useful for understanding larger ecological patterns. A prior study has suggested that larval input - inferred from landscape genomic data - of the ribbed mussel Geukensia demissa, a species with important roles in stabilizing salt marsh ecosystems, could be indicative of longer-term recruitment patterns of high marsh plant species. Here we use new observations of mitochondrial diversity in the same region but with more sites sampled to show that this prior study was wrong in suggesting that relationship. The same mitochondrial data are useful for monitoring cryptic patterns of climate response in these mussels relative to a subtropical congener.


title: Higher aboveground carbon stocks in mixed-species planted forests than monocultures - a meta-analysis

abstract: Natural forest is declining globally as the area of planted forest increases. Planted forests are often monocultures, despite results suggesting that higher species richness improves ecosystem functioning and stability. To test if this is generally the case, we performed a meta-analysis of available results. We assessed aboveground carbon stocks in mixed-species planted forests vs (a) the average of constituent species monocultures, (b) the best constituent species monoculture, and (c) commercial species monocultures. We investigated whether any advantage of mixtures over monocultures was positively related to species richness, as well as potential mechanisms driving differences in carbon stocks between mixtures and monocultures. The meta-analysis dataset included 79 comparisons from 21 sites. Carbon stocks in mixed planted forests were higher than the average of stocks in monocultures of their constituent species, containing on average 70% more carbon. Mixed planted forests also out-performed commercial monocultures, containing on average 77% more carbon. There was c.25% more carbon in mixed planted forests relative to the best performing monocultures, although this difference was not statistically significant. Overyielding was highest in four-species mixtures (richness range 2-6 species). More data providing better coverage of richness and age gradients (study sites aged 3.5-28 years) is needed to increase confidence in these results. None of the potential mechanisms we examined (nitrogen-fixer present vs absent; native vs non-native/mixed origin; tree diversity experiment vs forestry plantation) consistently explained variation in the diversity effects. This suggests that our findings are driven by a combination of small (statistically insignificant) effects from these sources or further unidentified mechanisms or some combination of the two. We conclude that increasing tree species richness in planted forests can increase carbon stocks while bringing other potential benefits associated with diversification. However, implementation will depend on the balance of these benefits relative to the operational challenges and costs of diversification.


title: Espalier: Efficient tree reconciliation and ARG reconstruction using maximum agreement forests

abstract: In the presence of recombination individuals may inherit different regions of their genome from different ancestors, resulting in a mosaic of phylogenetic histories across their genome. Ancestral recombination graphs (ARGs) can capture how phylogenetic relationships vary across the genome due to recombination, but reconstructing ARGs from genomic sequence data is notoriously difficult. Here we present a method for reconciling discordant phylogenetic trees and reconstructing ARGs using maximum agreement forests (MAFs). Given two discordant trees, a MAF identifies a set of topologically concordant subtrees present in both trees. We show how discordant trees can be reconciled through their MAF in a way that retains discordances strongly supported by sequence data while eliminating conflicts likely attributable to phylogenetic noise. We further show how MAFs and our reconciliation approach can be combined to select a path of local trees across the genome that maximizes the likelihood of the genomic sequence data, minimizes discordance between neighboring local trees, and identifies the recombination events necessary to explain remaining discordances to obtain a fully connected ARG. While heuristic, our ARG reconstruction approach is often as accurate as more exact methods while being much more computationally efficient. Moreover, important demographic parameters such as recombination rates can be accurately estimated from reconstructed ARGs. Finally, we apply our approach to plant infecting RNA viruses in the genus Potyvirus to demonstrate how true recombination events can be disentangled from phylogenetic noise using our ARG reconstruction methods.


title: Assessing the response to genomic selection by simulation

abstract: The goal of any plant breeding program is to maximize genetic gain for traits of interest. In classical quantitative genetics, the genetic gain can be obtained from what is known as "Breeders equation". In the past, only phenotypic data was used to compute the genetic gain. The advent of genomic prediction has opened the door to the utilization of dense markers for estimating genomic breeding values or GBV. The salient feature of genomic prediction is the possibility to carry out genomic selection with the assistance of the kinship matrix, hence, improving the prediction accuracy and accelerating the breeding cycle. However, estimates of GBV as such do not provide the full information on the number of entries to be selected as in the classical response to selection. In this paper, we use simulation, based on a fitted mixed model for genomic prediction in a multi-environmental framework, to answer two typical questions of a plant breeder: (1) How many entries need to be selected to have a defined probability of selecting the truly best entry from the population; (2) What is the probability of obtaining the truly best entries when some top-ranked entries are selected.

category: genetics


title: Machine learning guided signal enrichment for ultrasensitive plasma tumor burden monitoring

abstract: In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGE uses deep learning and a ctDNA-specific feature space to increase SNV signal to noise enrichment in WGS by 300X compared to our previous noise suppression platform MRDetect. MRD-EDGE also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1Gb to 200Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal to noise enrichment in MRD-EDGE enables de novo mutation calling in melanoma without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition.

category: genomics


title: Chronic social stress induces isolated deficits in reward anticipation on a neuroeconomic foraging task

abstract: Measuring reward anticipation distinct from other aspects of reward value, including costs required to obtain a reward or the intrinsic hedonic value of consuming the reward itself, can be difficult to disentangle. Here, we show that mice trained on a self-paced neuroeconomic foraging task convey reward anticipation via differentially invigorated travel times between uniquely flavored feeding sites separate from willingness to wait, consummatory behaviors, or place preferences measured within the same trial. Following exposure to chronic social defeat stress, we found that only stress-susceptible but not stress-resilient mice revealed deficits in this metric after consuming but not after rejecting a reward on the previous trial, indicating that blunted anticipation in these animals is state-dependent, or punctuated by recent reward receipt. After increasing economic pressure and task demands, locomotion was globally invigorated and, in turn, masked stress-related deficits in reward anticipation. These findings suggest that the ability to detect changes in specific aspects of motivational deficits associated with depression and other stress-related disorders depends on an interaction between the state of an individual and environmental circumstances.

category: animal behavior and cognition


title: Validity and reliability of Kinect v2 for quantifying upper body kinematics during seated reaching

abstract:
BackgroundKinematic analysis of the upper limbs is a good way to assess and monitor recovery in individuals with stroke, but remains little used in clinical routine due to its low feasibility. The aim of this study is to assess the validity and reliability of the Kinect v2 for the assessment of 17 kinematic variables commonly used in the analysis of upper limb reaching in stroke.

Methods26 healthy participants performed seated hand-reaching tasks while holding a dumbbell to induce a behaviour similar to that of a person with a stroke. 3D upper limb and trunk motion were simultaneously recorded with the Kinect v2 (Microsoft, USA) and with the VICON (OxfordMetrics, UK), the latter being the reference system. For each kinematic outcome, the validity of the Kinect was assessed with ICC, linear regression and Bland & Altman plots.

ResultsThe Kinect assesses trunk compensations, hand range of motion, movement time and mean velocity with a moderate to excellent reliability. In contrast, elbow and shoulder range of motion, time to peak velocity and path length ratio have a poor to moderate reliability, indicating that these variables should be interpreted with caution. Finally, instantaneous hand and elbow tracking are not precise enough to reliably assess Cartesian and angular kinematics over time, rendering variables such as the number of velocity peaks and the peak hand velocity unusable.

ConclusionsThanks to its ease of use and markerless properties, the Kinect can be used in clinical routine for semi-automated quantitative diagnostics guiding individualised rehabilitation of the upper limb. However, engineers and therapists must bear in mind the limitations of the Kinect for the instantaneous tracking of the hand and elbow.

category: bioengineering


title: Encoding sensing functions into material interface for a rationally engineered integrated electrochemical liquid biopsy

abstract: Limited healthcare capacity highlights the needs of integrated and simple sensing systems for personalized health monitoring. However, only a limited set of sensors can be employed for point-of-care applications, emphasizing the lack of a generalizable engineering strategy for sensor construction. Here, we report a de novo rational engineering strategy for the construction of an integrated electrochemical liquid biopsy (ELB) platform capable of direct profiling cancer exosomes from blood. Using a bottom-up approach for sensor design, a series of critical sensing functions is considered and encoded into the material interface by programming the electrode material with different chemical and structure features. We present that the rationally engineered electrochemical liquid biopsy platform is able to achieve one-step sensor fabrication, target isolation, non-fouling and high-sensitivity sensing, direct signal transduction and multiplexed detection. Integrating the multiplexed sensing with principal component analysis, we demonstrate the capability of the programmed sensing system on differentiating cancerous groups from healthy controls by analyzing clinical samples from lung cancer patients.


title: Resistor: an algorithm for predicting resistance mutations using Pareto optimization over multistate protein design and mutational signatures

abstract: Resistance to pharmacological treatments is a major public health challenge. Here we report RO_SCPLOWESISTORC_SCPLOW--a novel structure- and sequence-based algorithm for drug design providing prospective prediction of resistance mutations. RO_SCPLOWESISTORC_SCPLOW computes the Pareto frontier of four resistance-causing criteria: the change in binding affinity ({Delta}Ka) of the (1) drug and (2) endogenous ligand upon a proteins mutation; (3) the probability a mutation will occur based on empirically derived mutational signatures; and (4) the cardinality of mutations comprising a hotspot. To validate RO_SCPLOWESISTORC_SCPLOW, we applied it to kinase inhibitors targeting EGFR and BRAF in lung adenocarcinoma and melanoma. RO_SCPLOWESISTORC_SCPLOW correctly identified eight clinically significant EGFR resistance mutations, including the "gatekeeper" T790M mutation to erlotinib and gefitinib and five known resistance mutations to osimertinib. Furthermore, RO_SCPLOWESISTORC_SCPLOW predictions are consistent with sensitivity data on BRAF inhibitors from both retrospective and prospective experiments using the KinCon biosensor technology. RO_SCPLOWESISTORC_SCPLOW is available in the open-source protein design software OSPREY.


title: ScrepYard: an online resource for disulfide-stabilised tandem repeat peptides

abstract: Receptor avidity through multivalency is a highly sought-after property of ligands. While readily available in nature in the form of bivalent antibodies, this property remains challenging to engineer in synthetic molecules. The discovery of several bivalent venom peptides containing two homologous and independently folded domains (in a tandem repeat arrangement) has provided a unique opportunity to better understand the underpinning design of multivalency in multimeric biomolecules, as well as how naturally occurring multivalent ligands can be identified. In previous work we classified these molecules as a larger class termed secreted cysteine-rich repeat-proteins (SCREPs). Here, we present an online resource; ScrepYard, designed to assist researchers in identification of SCREP sequences of interest and to aid in characterizing this emerging class of biomolecules. Analysis of sequences within the ScrepYard reveals that two-domain tandem repeats constitute the most abundant SCREP domain architecture, while the interdomain "linker" regions connecting the ordered domains are found to be abundant in amino acids with short or polar sidechains and contain an unusually high abundance of proline residues. Finally, we demonstrate the utility of ScrepYard as a virtual screening tool for discovery of putatively multivalent peptides, by using it as a resource to identify a previously uncharacterised serine protease inhibitor and confirm its predicated activity using an enzyme assay.


title: Phenotypic deconvolution in heterogeneous cancer cell populations using drug screening data

abstract:
Tumor heterogeneity is an important driver of treatment failure in cancer since therapies often select for drug-tolerant or drug-resistant cellular subpopulations that drive tumor growth and recurrence. Profiling the drug-response heterogeneity of tumor samples using traditional genomic deconvolution methods has yielded limited results, due in part to the imperfect mapping between genomic variation and functional characteristics. Here, we leverage mechanistic population modeling to develop a statistical framework for profiling phenotypic heterogeneity from standard drug screen data on bulk tumor samples. This method, called PhenoPop, reliably identifies tumor subpopulations exhibiting differential drug responses, and estimates their drug-sensitivities and frequencies within the bulk. We apply PhenoPop to synthetically-generated cell populations, mixed cell-line experiments, and multiple myeloma patient samples, and demonstrate how it can be leveraged to perform individualized predictions of tumor growth under candidate therapies. This methodology can also be applied to deconvolve phenotypic responses to environmental stimuli in a variety of biological settings beyond cancer drug response.

Significance statementTumors are typically comprised of heterogeneous cell populations exhibiting diverse phenotypes. This heterogeneity, which is correlated with tumor aggressiveness and treatment-failure, confounds current drug screening efforts to identify effective candidate therapies for individual tumors. Here we present a method that enables the deconvolution of tumor samples into individual subcomponents exhibiting differential drug-response. This method relies on standard bulk drug-screen measurements and outputs the frequencies and drug-sensitivities of tumor subpopulations. Our method was validated in cell-line experiments and applied to characterize multiple myeloma patient samples. This method can be used for personalized predictions of tumor response to future treatments, and also applied more broadly to perform phenotypic deconvolution of heterogeneous populations in a variety of biological settings.

category: cancer biology


title: Specialization in somatostatin subnetworks in sensory and association cortex

abstract: Behavioral states profoundly affect cortical population activity dynamics and coding, yet the local circuits mediating these shifts are poorly understood, especially outside of sensory cortex. Somatostatin-expressing (SOM) inhibitory interneurons are highly sensitive to changes in brain state, and are well situated to modulate local population activity patterns. Here, we used two-photon calcium imaging to record the spike-related activity in populations of SOM and Non-SOM neurons in auditory cortex (AC) and posterior parietal cortex (PPC), to compare their functional interactions and activity modulation by behavioral state in sensory and association cortex. We have discovered both similarities and differences in the functional characteristics of SOM and Non-SOM populations across areas. In both regions, SOM neurons were more highly coordinated as populations than Non-SOM neurons. In PPC, SOM and Non-SOM neurons were positively modulated by increased arousal, while the effects of arousal in AC neurons were more diverse. Strikingly, the spatial structure of shared variability was different in AC and PPC: pairwise correlations in all cell types decayed rapidly with distance in AC but remained high over greater distances in PPC. Our results imply both generalization and specialization in the functional structure of excitatory and inhibitory subnetworks in sensory and association cortex.


title: Selective inhibition of goal-directed actions in the mesencephalic locomotor region

abstract: Dopamine enables purposive behavior and adjusts vigor as a function of the relative value of actions. In Parkinsons disease, dopamine neurons die and give rise to a series of motor and cognitive changes that interfere with the expression of volitional actions. Here we report a novel inhibitory input to dopamine neurons originated in the mesencephalic locomotor region that selectively blocks purposive behavior. GABAergic neurons of the pedunculopontine nucleus (PPN) synapse onto dopamine neurons of the substantia nigra and decrease dopamine release in the dorsal striatum. Activation of PPN neurons abolished exploratory locomotion and goal-directed actions while preserved other motor behaviors; furthermore, PPN caused a decrease in movement vigor and interrupted motor sequences presumably by modulating the immediate value of the learned action. Our results reveal an inhibitory mechanism in the midbrain that rapidly and reversibly adjusts the intrinsic value of ongoing actions.


title: ABLE: Automated Brain Lines Extraction Based on Laplacian Surface Collapse

abstract: The archetypical folded shape of the human cortex has been a long-standing topic for neuroscientific research. Nevertheless, the accurate neuroanatomical segmentation of sulci remains a challenge. Part of the problem is the uncertainty of where a sulcus transitions into a gyrus and vice versa. This problem can be avoided by focusing on sulcal fundi and gyral crowns which represent the topological opposites of cortical folding. We present Automated Brain Lines Extraction (ABLE), a method based on Laplacian surface collapse to segment sulcal fundi and gyral crown lines reliably. ABLE is built to work on standard FreeSurfer outputs, and eludes the delineation of anastomotic sulci while maintaining sulcal fundi lines that traverse the regions with the highest depth and curvature. First, it segments the cortex into gyral and sulcal surfaces; then, each surface is spatially filtered. A Laplacian-collapse-based algorithm is then applied to obtain a thinned representation of the surfaces. This surface is then used for careful detection of the endpoints of the lines. Finally, sulcal fundi and gyral crown lines are obtained by eroding the surfaces while preserving the connectivity between the endpoints. The method is validated by comparing ABLE with three other sulcal extraction methods using the Human Connectome Project (HCP) test-retest database to assess the reproducibility of the different tools. The results confirm ABLE as a reliable method to obtain sulcal lines with an accurate representation of the sulcal topology while ignoring anastomotic branches and the overestimation of the sulcal fundi lines. ABLE is publicly available via https://github.com/HGGM-LIM/ABLE.


title: Walking elicits global brain activity in Drosophila

abstract: Movement and behavioral state influence perception, and a stimulus can elicit opposite behavioral actions depending on whether the animal is moving toward or away from it. Here, we use fast wholebrain lightfield imaging in adult Drosophila melanogaster to analyze the relationship between movement and neuronal activity. Using pan-neuronal calcium imaging, we observe brainwide neuronal activity that tightly correlated with spontaneous bouts of movement. Imaging of specific sets of neurons across the brain reveals that both excitatory and inhibitory as well as different types of neuromodulatory neurons are active during walk inconsistent with a reduction of inhibition on neuronal activity. While most neuron types are activated at walk-onset, serotonergic neurons show more complex patterns of activity with neurons in several brain regions being inhibited during walk. Using available anatomical data, we map forward running and turning-induced activity onto different brain subregions and sometimes individual neurons. Moreover, we find that spontaneous walk and forced walk elicit highly similar wholebrain activity suggesting that a large part of the observed activity corresponds to walk itself rather than its initiation by higher brain centers. Based on our data, we conclude that movement and movement-related sensory feedback signals originating in the ventral nerve cord induce wide-spread activity in the brain allowing the integration of behavioral state into most or all brain processes.