bluuebunny/crossref_metadata_2025 huggingface dataset:
SOMDE: A scalable method for identifying spatially variable genes with self-organizing map
Authors: Hao Minsheng , Hua Kui , Zhang Xuegong
Published: December 2020

Recent developments of spatial transcriptomic sequencing technologies provide powerful tools for understanding cells in the physical context of tissue micro-environments. A fundamental task in spatial gene expression analysis is to identify genes with spatially variable expression patterns, or spatially variable genes (SVgenes). Several computational methods have been developed for this task. Their high computational complexity limited their scalability to the latest and future large-scale spatial expression data.

We present SOMDE, an efficient method for identifying SVgenes in large-scale spatial expression data. SOMDE uses self-organizing map (SOM) to cluster neighboring cells into nodes, and then uses a Gaussian Process to fit the node-level spatial gene expression to identify SVgenes. Experiments show that SOMDE is about 5-50 times faster than existing methods with comparable results. The adjustable resolution of SOMDE makes it the only method that can give results in ∼5 minutes in large datasets of more than 20,000 sequencing sites. SOMDE is available as a python package on PyPI athttps://pypi.org/project/somdefree for academic use.
Long-lasting impact of starvation experience on fly activity and place preference
Authors: Mahishi Deepthi , Triphan Tilman , Hesse Ricarda , Huetteroth Wolf
Published: December 2020

Animal behaviours are demonstrably governed by sensory stimulation, previous experience and internal states like hunger. With increasing hunger, priorities shift towards foraging and feeding. During foraging, flies are known to employ efficient path integration strategies. However, general long-term activity patterns for both hungry and satiated flies in conditions of foraging remain to be better understood. Similarly, little is known about how chronic contact chemosensory stimulation affects locomotion. To address these questions, we have developed a novel, simplistic fly activity tracking setup – the Panopticon. Using a 3D-printed Petri dish inset, our assay allows recording of walking behaviour, of several flies in parallel, with all arena surfaces covered by a uniform substrate layer. We tested two constellations of providing food: i) in single patches, and ii) omnipresent within the substrate layer. Fly tracking is done with FIJI, further assessment, analysis and presentation is done with a custom-built MATLAB analysis framework. We find that starvation history leads to a long-lasting reduction in locomotion, as well as a delayed place preference for food patches not driven by immediate hunger motivation.
Epilepsy kinase CDKL5 is a DNA damage sensor which controls transcriptional activity at DNA breaks
Authors: Khanam Taran , Muñoz Ivan , Weiland Florian , Carroll Thomas , Borsos Barbara N , Pantazi Vasiliki , Slean Meghan , Novak Miroslav , Toth Rachel , Appleton Paul , Pankotai Tibor , Zhou Houjiang , Rouse John
Published: December 2020

Mutation of theCDKL5kinase gene leads to the seizure-prone neurodevelopmental condition CDD (CDKL5 deficiency disorder) and is the most common genetic cause of childhood epilepsy. However, the phospho-targets and roles of CDKL5 are poorly understood, especially in the nucleus. We reveal CDKL5 as a sensor of DNA damage in actively transcribed regions of the nucleus, which phosphorylates transcriptional regulators such as Elongin A (ELOA) on a specific consensus motif. Recruitment of CDKL5 and ELOA to DNA damage sites, and subsequent ELOA phosphorylation, requires both active transcription and synthesis of poly–ADP ribose to which CDKL5 can bind. Critically, CDKL5 is essential for transcriptional control at DNA breaks. Therefore, CDKL5 is a DNA damage-sensing regulator of transcription, with implications for CDKL5-related human diseases.

One sentence summary

CDKL5 is a DNA damage-sensing kinase that modulates transcriptional activity near DNA breaks.
EVALUATING METHODS AND PROTOCOLS OF FERRITIN-BASED MAGNETOGENETICS
Authors: Hernández-Morales Miriam , Han Victor , Kramer Richard H , Liu Chunlei
Published: December 2020

FeRIC (Ferritin iron Redistribution to Ion Channels) is a magnetogenetic technique that uses radio frequency (RF) alternating magnetic fields to activate the transient receptor potential channels, TRPV1 and TRPV4, coupled to cellular ferritins. In cells expressing ferritin-tagged TRPV, RF stimulation increases the cytosolic Ca2+levels via a biochemical pathway. The interaction between RF and ferritin increases the free cytosolic iron levels that in turn, trigger chemical reactions producing reactive oxygen species and oxidized lipids that activate the ferritin-tagged TRPV. In this pathway, it is expected that experimental factors that disturb the ferritin expression, the ferritin iron load, the TRPV functional expression, or the cellular redox state will impact the efficiency of RF in activating ferritin-tagged TRPV. Here, we examined several experimental factors that either enhance or abolish the RF control of ferritin-tagged TRPV. The findings may help optimize and establish reproducible magnetogenetic protocols.
Linkage disequilibrium between rare mutations
Authors: Good Benjamin H.
Published: December 2020

The statistical associations between mutations, collectively known as linkage disequilibrium (LD), encode important information about the evolutionary forces acting within a population. Yet in contrast to single-site analogues like the site frequency spectrum, our theoretical understanding of linkage disequilibrium remains limited. In particular, little is currently known about how mutations with different ages and fitness costs contribute to expected patterns of LD, even in simple settings where recombination and genetic drift are the major evolutionary forces. Here, we introduce a forward-time framework for predicting linkage disequilibrium between pairs of neutral and deleterious mutations as a function of their present-day frequencies. We show that the dynamics of linkage disequilibrium become much simpler in the limit that mutations are rare, where they admit a simple heuristic picture based on the trajectories of the underlying lineages. We use this approach to derive analytical expressions for a family of frequency-weighted LD statistics as a function of the recombination rate, the frequency scale, and the additive and epistatic fitness costs of the mutations. We find that the frequency scale can have a dramatic impact on the shapes of the resulting LD curves, reflecting the broad range of time scales over which these correlations arise. We also show that the differences between neutral and deleterious LD are not purely driven by differences in their mutation frequencies, and can instead display qualitative features that are reminiscent of epistasis. We conclude by discussing the implications of these results for recent LD measurements in bacteria. This forward-time approach may provide a useful framework for predicting linkage disequilibrium across a range of evolutionary scenarios.
Building Models of Functional Interactions Among Brain Domains that Encode Varying Information Complexity: A Schizophrenia Case Study
Authors: Batta Ishaan , Abrol Anees , Fu Zening , Preda Adrian , van Erp Theo G.M. , Calhoun Vince D.
Published: December 2020

Revealing associations among various structural and functional patterns of the brain can yield highly informative results about the healthy and disordered brain. Studies using neuroimaging data have more recently begun to utilize the information within as well as across various functional and anatomical domains (i.e., groups of brain networks). However, most whole-brain approaches assume similar complexity of interactions throughout the brain. Here we investigate the hypothesis that interactions between brain networks capture varying amounts of complexity, and that we can better capture this information by varying the complexity of the model subspace structure based on available training data. To do this, we employ a Bayesian optimization-based framework known as the Tree Parzen Estimator (TPE) to identify, exploit and analyze patterns of variation in the information encoded by temporal information extracted from functional magnetic resonance imaging (fMRI) subdomains of the brain. Using a repeated cross-validation procedure on a schizophrenia classification task, we demonstrate evidence that interactions between specific functional subdomains are better characterized by more sophisticated model architectures compared to less complicated ones required by the others for optimally contributing towards classification and understanding the brain’s functional interactions. We show that functional subdomains known to be involved in schizophrenia require more complex architectures to optimally unravel discriminatory information about the disorder. Our study points to the need for adaptive, hierarchical learning frameworks that cater differently to the features from different subdomains, not only for a better prediction but also for enabling the identification of features predicting the outcome of interest.
Activity-based urinary biomarkers of response and resistance to checkpoint blockade immunotherapy
Authors: Mac Quoc D. , Xu Congmin , Bowen James R. , Sivakumar Anirudh , Phuengkham Hathaichanok , Su Fang-Yi , Stentz Samuel Z. , Sim Hyoungjun , Harris Adrian M. , Li Tonia T. , Qiu Peng , Kwong Gabriel A.
Published: December 2020

Immune checkpoint blockade (ICB) therapy has transformed cancer treatment, yet most patients do not derive clinical benefit and responders can acquire resistance to therapy. Noninvasive biomarkers are needed to indicate early on-treatment response and resistance mechanisms. Here we developedImmuNeSensors for monItorinG cHeckpoint blockadeTherapy (INSIGHT), which comprises a library of mass-barcoded peptide substrates conjugated to αPD1 antibodies, as therapeutic sensors. Following systemic administration, INSIGHT carries out the dual role of reinvigorating T cell function and profiling T cell and tumor proteases by the release of cleaved peptides into urine for noninvasive detection by mass spectrometry. We show that an αPD1 therapeutic sensor for Granzyme B discriminates early treatment responses before tumor volumes significantly diverge from isotype controls in murine models of colorectal cancer. To differentiate mechanisms of resistance by multivariate analysis, we design a mass-barcoded, 14-plex INSIGHT library to profile proteases differentially expressed by tumors harboring B2m or Jak1 loss-of-function mutations. We find that binary classifiers trained on urine samples indicate response to αPD-1 therapy as early as the start of the second dose, and discriminate B2m from Jak1 resistance with high sensitivity and specificity (AUROCs > 0.9). Our data supports the use of activity-based biomarkers for early on-treatment response assessment and classification of refractory tumors based on resistance mechanisms.
Enhancing Task fMRI Preprocessing via Individualized Model-Based Filtering of Intrinsic Activity Dynamics
Authors: Singh Matthew F. , Wang Anxu , Cole Michael , Ching ShiNung , Braver Todd S.
Published: December 2020

Brain responses recorded during fMRI are thought to reflect both rapid, stimulus-evoked activity and the propagation of spontaneous activity through brain networks. In the current work we describe a method to improve the estimation of task-evoked brain activity by first “filtering-out” the intrinsic propagation of pre-event activity from the BOLD signal. We do so using Mesoscale Individualized NeuroDynamic (MINDy; [1]) models built from individualized resting-state data (MINDy-based Filtering). After filtering, time-series are analyzed using conventional techniques. Results demonstrate that this simple operation significantly improves the statistical power and temporal precision of estimated group-level effects. Moreover, use of MINDy-based filtering increased the similarity of neural activation profiles and prediction of individual differences in behavior across tasks measuring the same construct (cognitive control).Thus, by subtracting the propagation of previous activity, we obtain better estimates of task-related neural activity.
Tuning electrical stimulation of the cervical vagus nerve for abdominal signaling while reducing cardiovascular side effects
Authors: Horn Charles C. , Forssell Mats , Sciullo Michael , Harms Jonathan E. , Fulton Stephanie , Mou Chenchen , Sun Fan , Simpson Tyler W. , Xiao Gutian , Fisher Lee E. , Bettinger Christopher , Fedder Gary K.
Published: December 2020

Electrical vagus nerve stimulation (VNS) has the potential to treat a wide variety of diseases by modulating afferent and efferent communication to the heart, lungs, esophagus, stomach, and intestines. Although distal vagal nerve branches, close to end organs, could provide a selective therapeutic approach, these locations are often surgically inaccessible. In contrast, the cervical vagus nerve has been targeted for decades using surgically implantable cuff electrodes to treat epileptic seizures and depression; however, to date, clinical implementation of VNS has relied on an electrode with contacts that fully wrap around the nerve, producing non-selective activation of the entire nerve. Here we demonstrate selective cervical VNS using cuff electrodes with multiple contacts around the nerve circumference to target different functional pathways. These flexible probes were adjusted to the diameter of the nerve using an adhesive hydrogel wrap to create a robust electrode interface. Our approach was verified in a rat model by demonstrating that cervical VNS produces neural activity in the abdominal vagus nerve while limiting effects on the cardiovascular system (i.e., changes in heart rate or blood pressure). This study demonstrates the potential for selective cervical VNS as a therapeutic approach for modulating distal nerve branches while reducing off target effects. This methodology could potentially be refined to treat gastrointestinal, metabolic, inflammatory, cardiovascular, and respiratory diseases amenable to vagal neuromodulatory control.
LLAMA: a robust and scalable machine learning pipeline for analysis of cell surface projections in large scale 4D microscopy data
Authors: Lefevre James G. , Koh Yvette W. H. , Wall Adam A. , Condon Nicholas D. , Stow Jennifer L. , Hamilton Nicholas A.
Published: December 2020

abstract

We present LLAMA, a pipeline for systematic analysis of terabyte scale 4D microscopy datasets. Analysis of individual biological structures in imaging at this scale requires efficient and robust methods which do not require human micromanagement or editing of outputs. To meet this challenge, we use a machine learning method for semantic segmentation, followed by a robust and configurable object separation and tracking algorithm, and the generation of detailed object level statistics. Advanced visualisation is a key element of LLAMA: we provide a specialised software tool which supports quality control and optimisation as well as visualisation of outputs. LLAMA was used in a quantitative analysis of macrophage surface membrane projections (filopodia, ruffles, tent-pole ruffles) examining the differential effects of two interventions: lipopolysaccharide (LPS) and macrophage colony stimulating factor (CSF-1). Distinct patterns of increased activity were identified. In addition, a continuity of behaviour was found between tent pole ruffling and wave-like ruffling, further defining the role of filopodia in ruffling.
LJA: Assembling Long and Accurate Reads Using Multiplex de Bruijn Graphs
Authors: Bankevich Anton , Bzikadze Andrey , Kolmogorov Mikhail , Antipov Dmitry , Pevzner Pavel A.
Published: December 2020

Although most existing genome assemblers are based on the de Bruijn graphs, it remains unclear how to construct these graphs for large genomes and largek-mer sizes. This algorithmic challenge has become particularly important with the emergence of long high-fidelity (HiFi) reads that were recently utilized to generate a semi-manual telomere-to-telomere assembly of the human genome and to get a glimpse into biomedically important regions that evaded all previous attempts to sequence them. To enable automated assemblies of long and accurate reads, we developed a fast LJA algorithm that reduces the error rate in these reads by three orders of magnitude (making them nearly error-free) and constructs the de Bruijn graph for large genomes and largek-mer sizes. Since the de Bruijn graph constructed for a fixedk-mer size is typically either too tangled or too fragmented, LJA uses a new concept of a multiplex de Bruijn graph with varyingk-mer sizes. We demonstrate that LJA improves on the state-of-the-art assemblers with respect to both accuracy and contiguity and enables automated telomere-to-telomere assemblies of entire human chromosomes.
Three-dimensional spatial transcriptomics uncovers cell type dynamics in the rheumatoid arthritis synovium
Authors: Vickovic Sanja , Schapiro Denis , Carlberg Konstantin , Lötstedt Britta , Larsson Ludvig , Korotkova Marina , Hensvold Aase H , Catrina Anca I , Sorger Peter K , Malmström Vivianne , Regev Aviv , Ståhl Patrik L
Published: December 2020

The inflamed rheumatic joint is a highly heterogeneous and complex tissue with dynamic recruitment and expansion of multiple cell types that interact in multifaceted ways within a localized area. Rheumatoid arthritis synovium has primarily been studied either by immunostaining or by molecular profiling after tissue homogenization. Here, we use Spatial Transcriptomics to study local cellular interactions at the site of chronic synovial inflammation. We report comprehensive spatial RNA-seq data coupled to quantitative and cell type-specific chemokine-driven dynamics at and around organized structures of infiltrating leukocyte cells in the synovium.
Canonical neural networks perform active inference
Authors: Isomura Takuya , Shimazaki Hideaki , Friston Karl
Published: December 2020

This work considers a class of canonical neural networks comprising rate coding models, wherein neural activity and plasticity minimise a common cost function—and plasticity is modulated with a certain delay. We show that such neural networks implicitly perform active inference and learning to minimise the risk associated with future outcomes. Mathematical analyses demonstrate that this biological optimisation can be cast as maximisation of model evidence, or equivalently minimisation of variational free energy, under the well-known form of a partially observed Markov decision process model. This equivalence indicates that the delayed modulation of Hebbian plasticity—accompanied with adaptation of firing thresholds—is a sufficient neuronal substrate to attain Bayes optimal control. We corroborated this proposition using numerical analyses of maze tasks. This theory offers a universal characterisation of canonical neural networks in terms of Bayesian belief updating and provides insight into the neuronal mechanisms underlying planning and adaptive behavioural control.
Non-cell autonomous inhibition of the Hedgehog response due to impaired cholesterol synthesis requires Ptch1/2 function
Authors: Jägers Carina , Roelink Henk
Published: December 2020

Congenital birth defects due to mutations of enzymes involved cholesterol synthesis, like Smith-Lemli-Opitz syndrome (SLOS) and Lathosterolosis are characterized by an accumulation of cholesterol precursors. The phenotype of both SLOS and Lathosterolosis have similarities to syndromes associated with abnormal Sonic hedgehog (Shh) signaling, consistent with the observation that cholesterol precursors and their derivative can inhibit Shh signaling. Two types of multipass membrane proteins play central roles in Shh signal transduction, the putative Resistance, Nodulation and Division (RND) antiporters Patched (Ptch)1 and −2, and the G-protein coupled receptor Smoothened (Smo). Sterols have been suggested as cargo for Ptch1/2, while Smo activity can affected both positively and negatively by steroidal molecules. We demonstrate that embryonic stem cells with mutations in the7-dehydroxycholesterol reductase(7Dhcr) orsterol-C5-desaturase(Sc5d) gene reduce the Hh response in adjacent wildtype cells when grown in mosaic organoids. This non-cell autonomous inhibitory activity of the mutant cells requires the presence of both Ptch1 and Ptch2. These observations support a model in which late cholesterol precursors that accumulate in cells lacking 7Dhcr are the cargo for Ptch1 and Ptch2 efflux activity and mediate the non-cell autonomous inhibition of Smo.
Stimulus-dependent representational drift in primary visual cortex
Authors: Marks Tyler D. , Goard Michael J.
Published: December 2020

To produce consistent sensory perception, neurons must maintain stable representations of sensory input. However, neurons in many regions exhibit progressive drift across days. Longitudinal studies have found stable responses to artificial stimuli across sessions in primary sensory areas, but it is unclear whether this stability extends to naturalistic stimuli. We performed chronic 2-photon imaging of mouse V1 populations to directly compare the representational stability of artificial versus naturalistic visual stimuli over weeks. Responses to gratings were highly stable across sessions. However, neural responses to naturalistic movies exhibited progressive representational drift across sessions. Differential drift was present across cortical layers, in inhibitory interneurons, and could not be explained by differential response strength or higher order stimulus statistics. However, representational drift was accompanied by similar differential changes in local population correlation structure. These results suggest representational stability in V1 is stimulus-dependent and related to differences in preexisting circuit architecture of co-tuned neurons.
The Role of Human Platelet-Rich Plasma to Enhance the Differentiation from Adipose derived Mesenchymal Stem Cells into Cardiomyocyte: An Experimental Study
Authors: Suryawan I Gde Rurus , Andrianto  , Anggaraeni Arifta Devi , Agita Arisya , Nugraha Ricardo Adrian
Published: December 2020

Background

Adipose derived mesenchymal stem cells (AMSCs) offer great potential to differentiate into cardiomyocyte. However, the optimal method to maximize the proliferation and differentiation is challenging. Platelet rich plasma (PRP) which contains high levels of diverse growth factors that can stimulate stem cell proliferation and differentiation in the context of cardiac tissue regeneration

Objective

To analyze the effect of PRP administration on the AMSCs differentiation into cardiomyocyte and compare to the group without PRP administration.

Methods

This study is a true experimental randomized post-test design study. AMSCs were isolated from adipose tissues and cultured until 4 passages. The samples were divided into 3 groups, i.e. negative control (α-MEM), positive control (differentiation medium), and treatment group (PRP). The assessment of GATA-4 marker expression was conducted using flowcytometry on the fifth day and cTnT was conducted using immunocytochemistry on the tenth day to determine the differentiation to cardiomyocyte. Data analysis was conducted using T-test and One-Way ANOVA on normally distributed data determined through Shapiro Wilk test.

Results

Flowcytometry on GATA-4 expression revealed significant improvement on PRP group compared to negative and positive controls (67.04 ± 4.49 vs 58.15 ± 1.23 p < 0.05; 67.04 ± 4.49 vs 52.96 ± 2.02 p < 0.05). This was supported by the results of immunocytochemistry on troponin expression which revealed significant improvement on PRP group compared to negative and positive controls (38.13 ± 5.2 vs 10.73 ± 2.39 p < 0.05; 38.13 ± 5.2 vs 26.00 ± 0.4 p < 0.05). This was concordant to the hypothesis which stated that there was an effect of PRP administration on AMSCs differentiation into cardiomyocyte.

Conclusion

PRP administration on AMSCs culture significantly improve the differentiation to cardiomyocyte measured by GATA-4 and cTnT expressions.
Plasma neutralizing antibodies in an infant with interclade HIV-1 superinfection preferentially neutralize superinfecting HIV-1 strains
Authors: Mishra Nitesh , Sharma Shaifali , Dobhal Ayushman , Kumar Sanjeev , Chawla Himanshi , Singh Swarandeep , Singh Ravinder , Das Bimal Kumar , Lodha Rakesh , Kabra Sushil Kumar , Luthra Kalpana
Published: December 2020

HIV-1 superinfection is defined as infection by an unrelated second strain of HIV-1 after seroconversion due to primary infecting strain and has been associated with development of breadth in the neutralizing antibody (nAb) response, altered disease progression and efficacy of antiretrovirals; though conflicting observations have also been reported. Superinfection has been reported in HIV-1 infected adults. Recently we observed that multivariant infection in infants was associated with early induction of plasma broadly neutralizing antibodies (bnAbs) targeting diverse autologous viruses, however, there is paucity of information on infants with HIV-1 superinfection. Furthermore, the mechanisms by which superinfection in an infant, after priming by an initial infection, potentiate the evolution of a bnAb response have not been evaluated. Herein, we performed a longitudinal analysis and observed evolution of nAb responses in an antiretroviral naïve perinatally HIV-1 infected infant, with interclade superinfection (clade C followed by a unique A1C recombinant). The nAb responses broadened rapidly after superinfection targeted an undefined glycan-dependent epitope on the superinfecting variant, while no enrichment of nAb response against the primary infecting strain occurred. Defining virological features in infants with sequential infection with highly divergent circulating viruses that improve nAb responses will contribute information that could be leveraged for optimization of multicomponent candidate vaccines.

Importance

HIV-1 infected infants develop bnAbs rapidly suggesting factors governing bnAb induction in infants are distinct from adults. HIV-1 superinfection is more common in adults whereas the stringent genetic bottleneck for transmission in infants often leads to infection by a single transmitted/founder HIV-1 strain. Longitudinal studies in infants with HIV-1 superinfection can provide key information on the viral factors that induce a bnAb response towards development of a polyvalent vaccine. Herein, we show that in infant who was sequentially infected with two HIV-1 strains from different clades, antibody responses were primarily generated against the superinfecting, second strain of HIV-1.

These antibody responses were dependent on glycans, and targeted an undefined epitope in the C3V4 region of HIV-1 Env. A better understanding of how neutralizing antibody responses develop during natural HIV-1 superinfection in infants will provide information relevant to HIV Env vaccine development and evaluation.
Role of two metacaspases in development and pathogenicity of the Rice Blast fungus,Magnaporthe oryzae
Authors: Fernandez Jessie , Lopez Victor , Kinch Lisa , Pfeifer Mariel A. , Gray Hillery , Garcia Nalleli , Grishin Nick V. , Khang Chang-Hyun , Orth Kim
Published: December 2020

Rice blast disease caused byMagnaporthe oryzaeis a devastating disease of cultivated rice worldwide. Infections by this fungus lead to a significant reduction in rice yields and threats to food security. To gain better insight into growth and cell death inM. oryzaeduring infection, we characterized two predictedM. oryzaemetacaspase proteins, MoMca1 and MoMca2. These proteins appear to be functionally redundant and are able to complement the yeast Yca1 homologue. Biochemical analysis revealed thatM. oryzaemetacaspases exhibited Ca2+dependent caspase activityin vitro. Deletion of bothMoMca1andMoMca2inM. oryzaeresulted in reduced sporulation, delay in conidial germination and attenuation of disease severity. In addition, the double ΔMomca1mca2mutant strain showed increased radial growth in the presence of oxidative stress. Interestingly, the ΔMomca1mca2strain showed an increase accumulation of insoluble aggregates compared to the wild-type strain during vegetative growth. Our findings suggest that MoMca1 and MoMca2 promote the clearance of insoluble aggregates inM. oryzae, demonstrating the important role these metacaspases have in fungal protein homeostasis. Furthermore, these metacaspase proteins may play additional roles, like in regulating stress responses, that would help maintain the fitness of fungal cells required for host infection.

IMPORTANCE

Magnaporthe oryzaecauses rice blast disease that threatens global food security by resulting in the severe loss of rice production every year. A tightly regulated life cycle allowsM. oryzaeto disarm the host plant immune system during its biotrophic stage before triggering plant cell death in its necrotrophic stage. The waysM. oryzaenavigates its complex life cycle remains unclear. This work characterizes two metacaspase proteins with peptidase activity inM. oryzaethat are shown to be involved in the regulation of fungal growth and development prior to infection by potentially helping maintain fungal fitness. This study provides new insight into the role of metacaspase proteins in filamentous fungi by illustrating the delays inM. oryzaemorphogenesis in the absence of these proteins. Understanding the mechanisms by whichM. oryzaemorphology and development promote its devastating pathogenicity may lead to the emergence of proper methods for disease control.
Effective connectivity extracts clinically relevant prognostic information from resting state activity in stroke
Authors: Adhikari Mohit H , Griffis Joseph , Siegel Joshua S. , de Schotten Michel Thiebaut , Deco Gustavo , Instabato Andrea , Gilson Mathieu , Corbetta Maurizio
Published: December 2020

Recent resting-state fMRI studies in stroke patients have identified two robust biomarkers of acute brain dysfunction: a reduction of inter-hemispheric functional connectivity (FC) between homotopic regions of the same network, and an abnormal increase of ipsilesional FC between task-negative and task-positive resting-state networks (RSNs). Whole-brain computational modeling studies, at the individual subject level, using undirected effective connectivity (EC) derived from empirically measured FC, have shown a reduction of measures of integration and segregation in stroke as compared to healthy brains. Here we employ a novel method, first, to infer whole-brain directional EC from zero-lagged and lagged FC, then, to compare it to empirically measured FC for predicting stroke vs. healthy status, and patient performance (zero, one, multiple deficits) across neuropsychological tests. We also investigated the accuracy of FC vs. model EC in predicting the long-term outcome from acute measures.

Both FC and EC predicted healthy from stroke individuals significantly better than the chance-level, however, EC accuracy was significantly higher than that of FC at 1-2 weeks, three months, and one year post-stroke. The predictive FC links mainly included those reported in previous studies (within-network inter-hemispheric, and between task-positive and -negative networks intra-hemispherically). Predictive EC links included additional between-network links. EC was a better predictor than FC of the number of behavioral domains in which patients suffered deficits, both at two weeks and one-year post onset of stroke. Interestingly, patient deficits at one-year time point were better predicted by EC values at two weeks rather than at one-year time point. Our results thus demonstrate that the second-order statistics of fMRI resting-state activity at an early stage of stroke, derived from a whole-brain EC, estimated in a model fitted to reproduce the propagation of BOLD activity, has pertinent information for clinical prognosis.
Therapeutic effects of Chlorzoxazone, a BKCa channel agonist, in a mouse model of Fragile X syndrome
Authors: Lemaire-Mayo Valerie , Piquemal Marion , Crusio Wim E. , Louette Eric , Pietropaolo Susanna
Published: December 2020

Fragile X syndrome (FXS) is an X-linked developmental disorder characterized by several behavioral abnormalities, including hyperactivity, sensory hyper-responsiveness and cognitive deficits, as well as autistic symptoms, e.g., reduced social interaction. These behavioural alterations are recapitulated by the major animal model of FXS, i.e., the Fmr1-KO mouse, which has been extensively employed to identify therapeutic targets for FXS, though effective pharmacological treatments are still lacking. Here we focused on the therapeutic role of large-conductance Calcium-dependent potassium (BKCa) channels, playing a crucial role in neuronal excitability and neurotransmitter release. Reduced expression/functionality of these channels has been described in FXS patients and mice, so that molecules activating these channels have been proposed as promising treatments for this syndrome. Here we performed an extensive characterization of the therapeutic impact of a novel BKCa agonist on FXS-like symptoms in the Fmr1-KO mouse model, employing a drug repurposing setting. We evaluated the acute and chronic effects of chlorzoxazone, i.e., a classical drug used for non-developmental muscular pathologies, on the locomotor, social, cognitive and sensory-motor alterations of Fmr1-KO mice and compared them with other pharmacological treatments recently proposed for FXS that instead do not target BKCa channels. Our results clearly demonstrate for the first time the marked efficacy of chlorzoxazone in treating all the behavioral abnormalities of FXS mice, thus encouraging the preferential use of this molecule over others for clinical applications in the field of FXS, and potentially of other neurodevelopmental disorders.
Plant sedimentary ancient DNA from Far East Russia covering the last 28 ka reveals different assembly rules in cold and warm climates
Authors: Huang Sichao , Stoof-Leichsenring Kathleen R. , Liu Sisi , Courtin Jeremy , Andreev Andrej A. , Pestryakova Luidmila. A. , Herzschuh Ulrike
Published: December 2020

Woody plants are expanding into the Arctic under a warming climate. The related impact on plant diversity is not well understood because we have only limited knowledge about plant assembly rules and because of a lack of time-series of plant diversity. Here, we applied sedimentary ancient DNA metabarcoding using the plant-specificgandhprimers of thetrnLgene to a sediment record from Lake Ilirney (central Chukotka Far Eastern Russia) covering the last 28 thousand years. Our results show that forb-dominated steppe-tundra and Saliceae-rich dwarf-shrub tundra communities dominated during the cold climate before 14 ka, while deciduous erect-shrub tundra was abundant during the warm period between 14 and 0 ka.Larixinvasion during the late Holocene substantially lagged behind the period of densest vegetation and likely warmest period between 10 and 6 ka. Overall, we discovered the highest richness during 28–23 ka and a second richness peak during 13–10 ka: both periods are characterised by low shrub abundance. The richest communities during the cold pre-14 ka period were phylogenetically clustered, which probably originates from environmental filtering along with niche differentiation under limited resources. In contrast, the richest post-14 ka community was phylogenetically overdispersed, likely originating from an erratic recruitment process in the course of warming. Despite differences in timescale, some of our evidence can be relevant to arctic plant diversity changes. By analogy to the past, we expect a lagged response of tree invasion. In the long-term, ongoing expansion of deciduous shrubs will eventually result in a phylogenetically more diverse community but will also cause reduced plant taxonomic richness; however, richness may overshoot in the short-term.
Feasibility and application of polygenic score analysis to the morphology of human induced pluripotent stem cells
Authors: Coleman Jonathan R. I.
Published: December 2020

Genome-wide association studies have identified thousands of significant associations between genetic variants and complex traits. Inferring biological insights from these associations has been challenging. One approach attempted has been to examine the effects of individual variants in cellular models. Here, I demonstrate the feasibility of examining the aggregate effect of many variants on cellular phenotypes. I examine the effects of polygenic scores for cross-psychiatric disorder risk, schizophrenia, body mass index and height on cellular morphology, using 1.5 million induced pluripotent stem cells (iPSC) from 60 European-ancestry donors from the Human iPSC Initiative dataset. I show that measuring multiple cells per donor provides sufficient power for polygenic score analyses, and that cross-psychiatric disorder risk is associated with cell area (p = 0.004). Combined with emerging methods of high-throughput iPSC phenotyping, cellular polygenic scoring is a promising method for understanding potential biological effects of the polygenic component of complex traits.
Duplex formation between the template and the nascent strand in the transcription-regulating sequences determines the site of template switching in SARS – CoV-2
Authors: D’souza Aaron R. , Buckingham Amanda , Salasc Fanny , Ingemarsdotter Carin , Iaconis Gennaro , Jarvis Isobel , Groom Harriet C. T. , Kenyon Julia , Lever Andrew M. L.
Published: December 2020

Recently published transcriptomic data of the SARS-CoV-2 coronavirus show that there is a large variation in the frequency and steady state levels of subgenomic mRNA sequences. This variation is derived from discontinuous subgenomic RNA synthesis where the polymerase switches template from a 3’ proximal genome body sequence to a 5’ untranslated leader sequence. This leads to a fusion between the common 5’ leader sequence and a 3’ proximal body sequence in the RNA product. This process revolves around a common core sequence (CS) that is present at both the template sites that make up the fusion junction. Base-pairing between the leader CS and the nascent complementary minus strand body CS, and flanking regions (together called the transcription regulating sequence, TRS) is vital for this template switching event. However, various factors can influence the site of template switching within the same TRS duplex. Here, we model the duplexes formed between the leader and complementary body TRS regions, hypothesising the role of the stability of the TRS duplex in determining the major sites of template switching for the most abundant mRNAs. We indicate that the stability of secondary structures and the speed of transcription play key roles in determining the probability of template switching in the production of subgenomic RNAs.
Evolutionarily ancient role of cholecystokinin-type neuropeptide signalling as an inhibitory regulator of feeding-related processes revealed in an echinoderm
Authors: Tinoco Ana B. , Barreiro-Iglesias Antón , Yañez-Guerra Luis Alfonso , Delroisse Jérôme , Zhang Ya , Gunner Elizabeth F. , Zampronio Cleidiane , Jones Alexandra M. , Egertová Michaela , Elphick Maurice R.
Published: December 2020

Cholecystokinin (CCK) / sulfakinin (SK)-type neuropeptides regulate feeding and digestion in chordates and protostomes (e.g. insects). Here we characterised CCK/SK-type signalling for the first time in a non-chordate deuterostome - the starfishAsterias rubens(phylum Echinodermata). In this species, two neuropeptides (ArCCK1, ArCCK2) derived from the precursor protein ArCCKP act as ligands for a CCK/SK-type receptor (ArCCKR) and are expressed in the nervous system, digestive system, tube feet and body wall. Furthermore, ArCCK1 and ArCCK2 cause dose-dependent contraction of cardiac stomach, tube foot and body wall apical muscle preparationsin vitroand injection of these neuropeptidesin vivotriggers cardiac stomach retraction and inhibition of the onset of feeding inA. rubens. Thus, an evolutionarily ancient role of CCK/SK-type neuropeptides as inhibitory regulators of feeding-related processes in the Bilateria has been conserved in the unusual and unique context of the extra-oral feeding behaviour and pentaradial body plan of an echinoderm.
A viral histone-like protein exploits antagonism between linker histones and HMGB proteins to obstruct the cell cycle
Authors: Lynch Kelsey L. , Bat-Erdene Mongoljin , Dillon Melanie R. , Lewis Hannah C. , Avgousti Daphne C.
Published: December 2020

Virus infection necessarily requires redirecting cellular resources towards viral progeny production. Adenovirus encodes the histone-like protein VII that causes catastrophic global reorganization of host chromatin to promote virus infection. Protein VII recruits the family of high mobility group box (HMGB) proteins to chromatin along with the histone chaperone SET. As a consequence of this recruitment, we find that protein VII causes chromatin-depletion of several linker histone H1 isoforms. The relationship between linker histone H1 and the functionally opposite HMGB proteins is critical for higher order chromatin structure. However, the physiological consequences of perturbing this relationship are largely unknown. Here, we employ complementary systems inSaccharomyces cerevisiaeand human cells to demonstrate that adenovirus protein VII disrupts the H1-HMGB balance to obstruct the cell cycle. We find that protein VII causes an accumulation of G2/M cells both in yeast and human systems, underscoring the high conservation of this chromatin vulnerability. In contrast, adenovirus E1A and E1B proteins are well-established to override cell cycle regulation and promote transformation of human cells. Strikingly, we find that protein VII obstructs the cell cycle even in the presence of E1A and E1B, suggesting that protein VII-directed cell cycle disruption ensures host resources are directed towards viral proliferation during infection. Together, our results demonstrate that protein VII targets H1-HMGB1 antagonism to obstruct cell cycle progression, revealing an unexpected chromatin vulnerability exploited for viral benefit.
The Personalized Proteome: Comparing Proteogenomics and Open Variant Search Approaches for Single Amino Acid Variant Detection
Authors: Salz Renee , Bouwmeester Robbin , Gabriels Ralf , Degroeve Sven , Martens Lennart , Volders Pieter-Jan , ’t Hoen Peter A.C.
Published: December 2020

Discovery of variant peptides such as single amino acid variant (SAAV) in shotgun proteomics data is essential for personalized proteomics. Both the resolution of shotgun proteomics methods and the search engines have improved dramatically, allowing for confident identification of SAAV peptides. However, it is not yet known if these methods are truly successful in accurately identifying SAAV peptides without prior genomic information in the search database. We studied this in unprecedented detail by exploiting publicly available long-read RNA seq and shotgun proteomics data from the gold standard reference cell line NA12878. Searching spectra from this cell line with the state-of-the-art open modification search engineionbotagainst carefully curated search databases resulted in 96.7% false positive SAAVs and an 85% lower true positive rate than searching with peptide search databases that incorporate prior genetic information. While adding genetic variants to the search database remains indispensable for correct peptide identification, inclusion of long-read RNA sequences in the search database contributes only 0.3% new peptide identifications. These findings reveal the differences in SAAV detection that result from various approaches, providing guidance to researchers studying SAAV peptides and developers of peptide spectrum identification tools.
A Synthetic Transcription Platform for Programmable Gene Expression in Mammalian Cells
Authors: Chen William C.W. , Gaidukov Leonid , Lai Yong , Wu Ming-Ru , Cao Jicong , Gutbrod Michael J. , Choi Gigi C.G. , Utomo Rachel P. , Chen Ying-Chou , Wroblewska Liliana , Kellis Manolis , Zhang Lin , Weiss Ron , Lu Timothy K.
Published: December 2020

Precise, scalable, and sustainable control of genetic and cellular activities in mammalian cells is key to developing precision therapeutics and smart biomanufacturing. We created a highly tunable, modular, versatile CRISPR-based synthetic transcription system for the programmable control of gene expression and cellular phenotypes in mammalian cells. Genetic circuits consisting of well-characterized libraries of guide RNAs, binding motifs of synthetic operators, transcriptional activators, and additional genetic regulatory elements expressed mammalian genes in a highly predictable and tunable manner. We demonstrated the programmable control of reporter genes episomally and chromosomally, with up to 25-fold more activity than seen with the EF1α promoter, in multiple cell types. We used these circuits to program the secretion of human monoclonal antibodies and to control T-cell effector function marked by interferon-γ production. Antibody titers and interferon-γ concentrations significantly correlated with synthetic promoter strengths, providing a platform for programming gene expression and cellular function in diverse applications.
Developmental effects on pattern visual evoked potentials characterized by principal component analysis
Authors: Gentile Carlyn Patterson , Joshi Nabin R. , Ciuffreda Kenneth J. , Arbogast Kristy B. , Master Christina , Aguirre Geoffrey K.
Published: December 2020

Purpose

Peak amplitude and peak latency in the pattern reversal visual evoked potential (prVEP) vary with maturation. We considered that principal component analysis (PCA) may be used to describe age-related variation over the entire prVEP time course and provide a means of modeling and removing variation due to developmental age.

Methods

prVEP was recorded from 155 healthy subjects ages 11-19 years at two timepoints. We created a model of the prVEP by identifying principal components (PCs) that explained >95% of the variance in a “training” dataset of 40 subjects. We examined the ability of the PCs to explain variance in an age- and sex-matched “validation” dataset (n=40) and calculated the intra-subject reliability of the PC coefficients between the two timepoints. We explored the effect of subject age and sex upon the PC coefficients.

Results

Seven PCs accounted for 96.0% of the variability of the training dataset and 90.5% of the variability in the validation dataset with good within-subject reliability across timepoints (R>0.7 for all PCs). The PCA model revealed narrowing and amplitude reduction of the P100 peak with maturation, and a broader and smaller P100 peak in males compared to females.

Conclusions

PCA is a generalizable, reliable, and unbiased method of analyzing prVEP. The PCA model revealed changes across maturation and biological sex not fully described by standard peak analysis.

Translational relevance

We describe a novel application of PCA to characterize developmental changes of prVEP in youth that can be used to compare healthy and pathologic pediatric cohorts.