bluuebunny/crossref_metadata_2025 huggingface dataset:
Targeting MOG to skin macrophages prevents EAE in macaques through TGFβ-induced peripheral tolerance
Authors: Fovet Claire-Maëlle , Stimmer Lev , Contreras Vanessa , Horellou Philippe , Hubert Audrey , Sediki Nabila , Chapon Catherine , Tricot Sabine , Leroy Carole , Flament Julien , Massonneau Julie , Tchitchek Nicolas , ’t Hart Bert A. , Zurawski Sandra , Klucar Peter , Deiva Kumaran , Zurawski Gerard , Oh SangKon , Le Grand Roger , Serguera Ché
Published: March 2019

To study the effect of vaccination on tolerization to the myelin antigen MOG we used a macaque model of experimental autoimmune encephalitis (EAE) in which immunization with recombinant human myelin oligodendrocyte glycoprotein (rhMOG) elicits brain inflammation and demyelination mediated by MOG-specific autoreactive CD4+ T lymphocytes and anti-MOG IgG. For antigen targeting to tolerizing antigen presenting cells, we used a recombinant antibody directed to the Dendritic Cells (DC)-Asialoglycoprotein receptor (DC-ASGPR). The intradermal administration of an anti-DC-ASGPR-MOG fusion protein, but not a control anti-DC-ASGPR-PSA (prostate specific antigen) protein, protected monkeys committed to develop EAE. Although effective treatment did not modify anti-MOG IgG production, it prevented the CD4+ T lymphocyte activation and pro-inflammatory cytokine production. Moreover, animals treated with anti-DC-ASGPR-MOG experienced a rise of MOG-specific CD4+CD25+FOXP3+CD39+ regulatory T cells as well as a TGFβ1, TGFβ2 and IL-8 upsurge after rhMOG re-immunization. Our results indicate that the pathogenicity of autoantibodies directed to MOG is mitigated in the presence of MOG-specific regulatory lymphocytes. This vaccination scheme appears suitable to treat relapsing autoimmune diseases with identified autoantigens such as that harboring anti-MOG or anti-AQP4 autoantibodies.
SPiQE: an automated analytical tool for detecting and characterising fasciculations in amyotrophic lateral sclerosis
Authors: Bashford J , Wickham A , Iniesta R , Drakakis E , Boutelle M , Mills K , Shaw C
Published: March 2019

OBJECTIVES

Fasciculations are a clinical hallmark of amyotrophic lateral sclerosis (ALS). Compared to concentric needle EMG, high-density surface EMG (HDSEMG) is non-invasive and records fasciculation potentials (FPs) from greater muscle volumes over longer durations. To detect and characterise FPs from vast data sets generated by serial HDSEMG, we developed an automated analytical tool.

METHODS

Six ALS patients and two control patients (one with benign fasciculation syndrome and one with multifocal motor neuropathy) underwent 30-minute HDSEMG from biceps and gastrocnemius monthly. In MATLAB we developed a novel, innovative method to identify FPs amidst fluctuating noise levels. One hundred repeats of 5-fold cross validation estimated the model’s predictive ability.

RESULTS

By applying this method, we identified 5,318 FPs from 80 minutes of recordings with a sensitivity of 83.6% (+/-0.2 SEM), specificity of 91.6% (+/-0.1 SEM) and classification accuracy of 87.9% (+/-0.1 SEM). An amplitude exclusion threshold (100μV) removed excessively noisy data without compromising sensitivity. The resulting automated FP counts were not significantly different to the manual counts (p=0.394).

CONCLUSION

We have devised and internally validated an automated method to accurately identify FPs from HDSEMG, a technique we have named Surface Potential Quantification Engine (SPiQE).

SIGNIFICANCE

Longitudinal quantification of fasciculations in ALS could provide unique insight into motor neuron health.

Highlights

SPiQE combines serial high-density surface EMG with an innovative signal-processing methodology

SPiQE identifies fasciculations in ALS patients with high sensitivity and specificity

The optimal noise-responsive model achieves an average classification accuracy of 88%
The optimal discovery procedure for significance analysis of general gene expression studies
Authors: Bass Andrew J. , Storey John D.
Published: March 2019

Analysis of biological data often involves the simultaneous testing of thousands of genes. This requires two key steps: the ranking of genes and the selection of important genes based on a significance threshold. One such testing procedure, called the "optimal discovery procedure" (ODP), leverages information across different tests to provide an optimal ranking of genes. This approach can lead to substantial improvements in statistical power compared to other methods. However, current applications of the ODP have only been established for simple study designs using microarray technology. Here we extend this work to the analysis of complex study designs and RNA sequencing studies. We then apply our extended framework to a static RNA sequencing study, a longitudinal and an independent sampling time-series study, and an independent sampling dose-response study. We find that our method shows improved performance compared to other testing procedures, finding more differentially expressed genes and increasing power for enrichment analysis. Thus the extended ODP enables a superior significance analysis of genomic studies. The algorithm is implemented in our freely available R package called edge.
Direct control of shell regeneration by the mantle tissue in the pearl oysterPinctada fucatavia accelerating CaCO3 nucleation
Authors: Huang Jingliang , Liu Yangjia , Jiang Taifeng , Dong Wentao , Zheng Guilian , Xie Liping , Zhang Rongqing
Published: March 2019

Molluscan bivalves rapidly repair the damaged shells to prevent further injury. However, it remains unclear how this process is precisely controlled. In this study, we applied scanning electronic microscopy, transmission electronic microscopy and histochemical analysis to examine the detailed shell regeneration process of the pearl oysterPinctada fucata. It was found that the shell damage caused the mantle tissue to retract, which resulted in dislocation of the mantle zones to their correspondingly secreted shell layers. However, the secretory repertoires of the different mantle zones remained unchanged. As a result, the dislocation of the mantle tissue dramatically affected the shell morphology, and the unusual presence of the submarginal zone on the nacreous layers caused de novo precipitation of prismatic layers on the nacreous layers. Real-time PCR revealed that the expression of the shell matrix proteins (SMPs) were significantly upregulated, which was confirmed by the thermal gravimetric analysis (TGA) of the newly formed shell. The increased matrix secretion accelerated CaCO3nucleation thus promoting shell deposition. Taken together, our study revealed the close relationship between the physiological activities of the mantle tissue and the morphological change of the regenerated shells.
Temporal variation of fatty acid composition and pesticides in honeybeesApis melliferaand beebread
Authors: Gooley Zuyi C. , Gooley Aaron C.
Published: March 2019

A twelve-month study was conducted on changes in fatty acid composition and pesticide residues in honeybees and beebread. In honeybees, saturated fatty acid and monounsaturated fatty acid gradually increased as summer began then decreased when spring started, and polyunsaturated fatty acid had an opposite seasonal trend. Similar fluctuation was observed in the beebread collected from the same hive as those honeybees through summer to fall, especially in the essential fatty acids omega-6 and omega-3. Honeybees’ lipid metabolism can be disrupted after being exposed to a sub-lethal level of pesticide. Although three out of sixteen analyzed pesticides were detected in beebread samples summer through fall in our study, we were not able to find any negative affect of those pesticides on the honeybees’ fatty acid composition. Temporary field-realistic pesticide exposure may weaken honeybees but are unlikely to show any reflection in their fat bodies if the colony was otherwise healthy.
A distinct pool of Nav1.5 channels at the lateral membrane of murine ventricular cardiomyocytes
Authors: Rougier Jean-Sébastien , Essers Maria C. , Gillet Ludovic , Guichard Sabrina , Sonntag Stephan , Shmerling Doron , Abriel Hugues
Published: March 2019

Background

In cardiac ventricular muscle cells, the presence of voltage-gated sodium channels Nav1.5 at the lateral membrane depends in part on the interaction between the dystrophin-syntrophin complex and the Nav1.5 C-terminal PDZ-domain-binding sequence Ser-Ile-Val (SIV motif). α1-Syntrophin, a PDZ-domain adaptor protein, mediates the interaction between Nav1.5 and dystrophin at the lateral membrane of cardiac cells. Using the cell-attached patch-clamp approach on cardiomyocytes expressing Nav1.5 in which the SIV motif is deleted (ΔSIV), sodium current (INa) recordings from the lateral membrane revealed an SIV-motif-independent INa. Since immunostainings have suggested that Nav1.5 is expressed in transverse (T-) tubules, this remaining INa might be conducted by channels in the T-tubules. Of note, a recent study using heterologous expression systems showed that α1-syntrophin also interacts with the Nav1.5 N-terminus, which may explain the SIV-motif independent INa at the lateral membrane of cardiomyocytes.

Aim

To address the role of α1-syntrophin in regulating the INa at the lateral membrane of cardiac cells.

Methods and results

Patch-clamp experiments in cell-attached configuration were performed on the lateral membranes of wild-type, α1-syntrophin knock-down, and ΔSIV ventricular mouse cardiomyocytes. Compared to wild-type, a reduction of the lateral INa was observed in myocytes from α1-syntrophin knockdown hearts. However, similar to ΔSIV myocytes, a remaining INa was still recorded. In addition, cell-attached INa recordings from lateral membrane did not differ significantly between non-detubulated and detubulated ΔSIV cardiomyocytes. Lastly, we obtained evidence suggesting that cell-attached patch-clamp experiments on the lateral membrane cannot record currents conducted by channels in T-tubules such as calcium channels.

Conclusion

Altogether, these results suggest the presence of a sub-pool of sodium channels at the lateral membrane of cardiomyocytes that is independent of α1-syntrophin and the PDZ-binding motif of Na 1.5, located in membrane domains outside of T-tubules. The question of a T-tubular pool of Nav1.5 channels however remains open.
SF3B1ness score: screeningSF3B1mutation status from over 60,000 transcriptomes based on a machine learning approach
Authors: Shiraishi Yuichi , Chiba Kenichi , Okada Ai
Published: March 2019

In precision oncology, genomic evidence is used to determine the optimal treatment for each patient. However, identification of somatic mutations from genome sequencing data is often technically difficult and functional significance of somatic mutations is inconclusive in many cases. In this paper, to seek for an alternative approach, we tackle the problem of predicting functional mutations from transcriptome sequencing data. Focusing onSF3B1, a key splicing factor gene, we develop SF3B1ness score for classifying functional mutation status using a combination of Naive Bayes classifier and zero-inflated beta-binomial modeling (R package is available at (https://github.com/friend1WS/SF3B1ness). Using 8,992 TCGA exome and RNA sequencing data for evaluation, we show that the classifier based on SF3B1ness score is able to (1) attain very high precision (>93%) and sensitivity (>95%), (2) rescue several somatic mutations not identified by exome sequence analysis especially due to low variant allele frequencies, and (3) successfully measure functional importance for somatic mutation whose significance has been unknown. Furthermore, to demonstrate that the SF3B1ness score is highly robust and can be extensible to the cohorts outside training data, we performed a functionalSF3B1mutation screening on 51,577 additional transcriptome sequencing data. We have detected 135 samples with putativeSF3B1functional mutations including those that are rarely registered in the somatic mutation database (e.g., G664C, L747W, and R775G). Moreover, we could identify two cases withSF3B1mutations from normal tissues, implying that SF3B1ness score can be used for detecting clonal hematopoiesis.
Thermal preference influences depth use but not biomass of predatory fishes in response to lake morphometry
Authors: Bartley Timothy J. , Guzzo Matthew M. , Cazelles Kevin , Verville Alex , McMeans Bailey C. , McCann Kevin S.
Published: March 2019

Top predators’ responses to environmental conditions shape food web architecture and influence ecosystem structure and stability. Yet the impacts of fundamental properties like ecosystem size and morphometry on top predators’ behaviour are poorly understood. We examined how lake morphometry impacts the behaviour (inferred by depth use) of three key fish top predators—the cold-adapted lake trout, the cool-adapted walleye, and the warm-adapted smallmouth bass— which can each strongly impact local food web structure. We used catch-per-unit-effort data from nearly 500 boreal lakes of Ontario, Canada to evaluate the role of thermal preference in dictating mean depth of capture and biomass index in response to lake morphometry. We found evidence that thermal preferences influence how species’ depth use and biomass changed with lake size, proportion of littoral area, and maximum lake depth, although we found no relationship with lake shape. However, found no strong evidence that lake morphology influences these species’ biomasses, despite theory that predicts such a relationship. Our results suggest that some aspects of lake morphometry can alter habitat accessibility and productivity in ways that influence the behaviour and biomass of these top predator species depending on their thermal preferences. Our results have implications for how lake food webs expand and contract with lake morphometry and other key abiotic factors. We argue that several key abiotic factors likely drive top predator depth use in ways that may shape local food web structure and play an important role in determining the ultimate fate of ecosystems with environmental change.
Cytokinin functions as an asymmetric and anti-gravitropic signal in lateral roots
Authors: Waidmann Sascha , Rosquete Michel Ruiz , Schöller Maria , Lindner Heike , LaRue Therese , Sarkel Elizabeth , Petřík Ivan , Dünser Kai , Martopawiro Shanice , Sasidharan Rashmi , Novak Ondrej , Wabnik Krzysztof , Dinneny José R. , Kleine-Vehn Jürgen
Published: March 2019

Directional organ growth allows the plant root system to strategically cover its surroundings. Intercellular auxin transport is aligned with the gravity vector in the primary root tips, facilitating downward organ bending at the lower root flank. Here we show that cytokinin signaling functions as a lateral root specific anti-gravitropic component, promoting the radial distribution of the root system. We performed a genome-wide association study and revealed that signal peptide processing of Cytokinin Oxidase 2 (CKX2) affects its enzymatic activity and, thereby, determines the degradation of cytokinins in naturalArabidopsis thalianaaccessions. Cytokinin signaling interferes with growth at the upper lateral root flank and thereby prevents downward bending. Our interdisciplinary approach revealed that two phytohormonal cues at opposite organ flanks counterbalance each other’s negative impact on growth, suppressing organ growth towards gravity and allow for radial expansion of the root system.
Corticotropin-Releasing Hormone Signaling in the Oval Bed Nucleus of the Stria Terminalis Mediates Chronic Stress-Induced Negative Valence Behaviors Associated with Anxiety
Authors: Hu Pu , Maita Isabella , Kwok Christopher , Gu Edward , Gergues Mark , Liu Ji , Pang Zhiping , Swaab Dick F. , Lucassen Paul J. , Roepke Troy A. , Samuels Benjamin A.
Published: March 2019

The bed nucleus of stria terminalis (BNST) is a forebrain region highly sensitive to stress that expresses corticotropin-releasing hormone (CRH) neuropeptide at high levels and regulates negative valence behaviors associated with anxiety. However, how chronic stress modulates CRH signaling and neuronal activity in BNST remains unknown. We subjected C57BL6/J mice to a 6-week chronic variable mild stress (CVMS) paradigm and investigated the effects on behavior, BNST cellular neurophysiology, and BNST CRH signaling. We also utilized pharmacological infusions and optogenetics to decipher and mimic the effects of CVMS on BNST cellular neurophysiology and behavior. CVMS elevated plasma corticosterone levels, induced negative valence behaviors associated with anxiety, diminished M-currents (voltage-gated K+currents that stabilize membrane potential and regulate neuronal excitability), and increased mEPSC amplitude in ovBNST. Additionally, the number of c-fos+, CRH+, and CRH activator pituitary adenylate cyclase-activating polypeptide (PACAP)+cells were increased while CRH inhibitor striatal-enriched protein tyrosine phosphatase (STEP)+cells were decreased in ovBNST. These expression data were confirmed with qPCR. CVMS also activated PKA in BNST and the electrophysiological and behavioral effects of CVMS were reversed by ovBNST infusion of the PKA-selective antagonist H89. Moreover, optogenetic activation of ovBNST directly induced negative valence behaviors associated with anxiety, mimicking the effects of CVMS. CVMS mediates effects on negative valence behaviors associated with anxiety by activating CRH signaling components and cellular excitability in ovBNST Our findings decipher an important CRH-associated stress molecular signature in BNST and advance our understanding of the neural circuitry underlying stress-induced disorders.
Analytic Model of fMRI BOLD Signals for Separable Metrics of Neural and Metabolic Activity
Authors: Schaper Charles D.
Published: March 2019

The applications of fMRI (functional magnetic resonance imaging) are broad covering diagnostic and clinical extents of brain function, which involves the analysis of BOLD (blood oxygen level-dependent) contrast signals. The BOLD signals are sourced from both neural and metabolic functions, and thus to enable a detailed examination of fMRI studies, methods are sought to separate the neural and metabolic functions, such that the neural component, which is often the metric of interest, can be independently examined, especially in relation to neural connectivity. In this work, a modeling approach is developed that separates the neural and metabolic functions from the overall BOLD signal. The newly developed model is initially developed within a linear framework and demonstrates excellent comparison in data fit at 97.4% to the three Gamma function, which has been widely used to characterize fMRI BOLD experimental data. The neural component of the model formulation is comprised of a proper transfer function of two poles and two zeros, and characterizes the salient features of the BOLD signal, including the initial dip, peak, undershoot, and stabilization period. The linear model is extended to characterize nonlinear fMRI BOLD signal responses through the integration of saturation functions to both the leading and trailing edges of the signal. The nonlinear model representation not only explains the muted response in amplitude and oscillations, but also explains nuanced oscillations during the hold and settling phases of fMRI BOLD responses as exemplified in comparison to published data of sensorimotor responses. Further, the newly developed decomposition is derived within a framework for modeling neurovascular coupling environments, and thus lends credibility to the modeling framework. In developing the decomposition of the neural and metabolic transfer functions, it is a conclusion that the BOLD signal correlates very well with the fast dynamics associated with neural response to external stimuli.

Graphical Abstract

The normalized impulse response of the BOLD signal and the corresponding neural activity according to the newly developed model. There is a correspondence of the critical points for the oscillatory response of the neural function and metabolic reactivity, including the initial dip, peak and subsequent undershoot. Thus, the BOLD signal is a correlated representation of the underlying neural response.
Genome-wide association study and low-cost genomic predictions for growth and fillet yield in Nile tilapia (Oreochromis niloticus)
Authors: Yoshida Grazyella M. , Lhorente Jean P. , Correa Katharina , Soto Jose , Salas Diego , Yáñez José M.
Published: March 2019

Fillet yield (FY) and harvest weight (HW) are economically important traits in Nile tilapia production. Genetic improvement of these traits, especially for FY, are lacking, due to the absence of efficient methods to measure the traits without sacrificing fish and the use of information from relatives to selection. However, genomic information could be used by genomic selection to improve traits that are difficult to measure directly in selection candidates, as in the case of FY. The objectives of this study were: (i) to perform genome-wide association studies (GWAS) to dissect the genetic architecture of FY and HW, (ii) to evaluate the accuracy of genotype imputation and (iii) to assess the accuracy of genomic selection using true and imputed low-density (LD) single nucleotide polymorphism (SNP) panels to determine a cost-effective strategy for practical implementation of genomic information in tilapia breeding programs. The data set consisted of 5,866 phenotyped animals and 1,238 genotyped animals (108 parents and 1,130 offspring) using a 50K SNP panel. The GWAS were performed using all genotyped and phenotyped animals. The genotyped imputation was performed from LD panels (LD0.5K, LD1K and LD3K) to high-density panel (HD), using information from parents and 20% of offspring in the reference set and the remaining 80% in the validation set. In addition, we tested the accuracy of genomic selection using true and imputed genotypes comparing the accuracy obtained from pedigree-based best linear unbiased prediction (PBLUP) and genomic predictions. The results from GWAS supports evidence of the polygenic nature of FY and HW. The accuracy of imputation ranged from 0.90 to 0.98 for LD0.5K and LD3K, respectively. The accuracy of genomic prediction outperformed the estimated breeding value from PBLUP. The use of imputation for genomic selection resulted in an increased relative accuracy independent of the trait and LD panel analyzed. The present results suggest that genotype imputation could be a cost-effective strategy for genomic selection in tilapia breeding programs.
Large-scale chemical-genetics of the human gut bacteriumBacteroides thetaiotaomicron
Authors: Liu Hualan , Price Morgan N. , Carlson Hans K. , Chen Yan , Ray Jayashree , Shiver Anthony L. , Petzold Christopher J. , Huang Kerwyn Casey , Arkin Adam P. , Deutschbauer Adam M.
Published: March 2019

The genomic catalogue of the human microbiota has expanded dramatically in recent years, and insights derived from human microbiota genomics has vast potential to generate treatments for human diseases. However, predictably harnessing the microbiota for beneficial outcomes is currently limited by our lack of understanding of the physiology of the constituent bacteria. For instance, the functions of most of their genes are not known. Here, we systematically measure mutant phenotypes for genes from the gut commensalBacteroides thetaiotaomicron. Using a barcoded transposon mutant library, we measured the fitness of 4,055B. thetaiotaomicrongenes across 492 experiments, including growth on 45 carbon substrates and in the presence of 57 stress-inducing compounds. Our data is in strong agreement with previous studies, and more importantly also uncovers the biological roles of poorly annotated genes. We identified 497 genes with a specific phenotype in only one or a handful of conditions, thus enabling informed predictions of gene function for a subset of these genes. For example, we identified a glycoside hydrolase important for growth on type I rhamnogalacturonan, a DUF4861 protein for glycosaminoglycan utilization, a DUF1080 protein for disaccharide utilization, and a tripartite multidrug resistance system specifically important for bile salt tolerance. Our approach can be applied to other members of the human microbiota to experimentally characterize their genes.
Retaining pluripotency and exogenous mRNA introduction in planarian stem cell culture
Authors: Lei Kai , Zhang Wenya , Chen Jiajia , McKinney Sean A. , Ross Eric J. , Lee Heng-Chi , Alvarado Alejandro Sánchez
Published: March 2019

Planarians possess naturally occurring pluripotent adult somatic stem cells (neoblasts) required for homeostasis and whole-body regeneration. However, no reliable neoblast culture methods are currently available, hindering mechanistic studies of pluripotency and the development of transgenic tools. We report the first robust methods for neoblast culture and delivery of exogenous mRNAs. We identify optimal culture media for maintaining neoblasts in vitro, and show via transplantation that cultured stem cells retain pluripotency for two days. We developed a new procedure that significantly improves neoblast yield and purity by modifying standard flow cytometry methods. These methods enable the introduction and expression of exogenous mRNAs in neoblasts, overcoming a key hurdle impeding the application of transgenics in planarians. The advances in cell culture reported here create new opportunities for mechanistic studies of planarian adult stem cell pluripotency, and provide a systematic framework to develop cell culture techniques in other emerging research organisms.
A practical computerized decision support system for predicting the severity of Alzheimer’s disease of an individual
Authors: Bucholc Magda , Ding Xuemei , Wang Haiying , Glass David H. , Wang Hui , Prasad Girijesh , Maguire Liam P. , Bjourson Anthony J. , McClean Paula L. , Todd Stephen , Finn David P. , Wong-Lin KongFatt ,   for the Alzheimer’s Disease Neuroimaging Initiative
Published: March 2019

Computerized clinical decision support systems can help to provide objective, standardized, and timely dementia diagnosis. However, current computerized systems are mainly based on the group analysis, discrete classification of disease stages, or expensive and not readily accessible biomarkers, while current clinical practice relies relatively heavily on cognitive and functional assessments (CFA). In this study, we developed a computational framework using a suite of machine learning tools for identifying key markers in predicting the severity of Alzheimer’s disease (AD) from a large set of biological and clinical measures. Six machine learning approaches, namely Kernel Ridge Regression (KRR), Support Vector Regression (SVR), and k-Nearest Neighbor (kNNreg) for regression and Support Vector Machine (SVM), Random Forest (RF), and k-Nearest Neighbor (kNNclass) for classification, were used for the development of predictive models. We demonstrated high predictive power of CFA. Predictive performance of models incorporating CFA was shown to be consistently higher accuracy than those based solely on biomarker modalities. We found that KRR and SVM were the best performing regression and classification methods respectively. The optimal SVM performance was observed for a set of four CFA test scores (FAQ, ADAS13, MoCA, MMSE) with multi-class classification accuracy of 83.0%, 95%CI = (72.1%, 93.8%) while the best performance of the KRR model was reported with combined CFA and MRI neuroimaging data, i.e.,R2= 0.874, 95%CI = (0.827, 0.922). Given the high predictive power of CFA and their widespread use in clinical practice, we then designed a data-driven and self-adaptive computerized clinical decision support system (CDSS) prototype for evaluating the severity of AD of an individual on a continuous spectrum. The system implemented an automated computational approach for data pre-processing, modelling, and validation and used exclusively the scores of selected cognitive measures as data entries. Taken together, we have developed an objective and practical CDSS to aid AD diagnosis.
MTH1 inhibitor TH588 induces mitosis-dependent accumulation of genomic 8-oxodG and disturbs mitotic progression
Authors: Rudd Sean G , Gad Helge , Amaral Nuno , Hagenkort Anna , Groth Petra , Ström Cecilia E , Mortusewicz Oliver , Berglund Ulrika Warpman , Helleday Thomas
Published: March 2019

Reactive oxygen species (ROS) oxidise nucleotide triphosphate pools (e.g., 8-oxodGTP), which may kill cells if incorporated into DNA. Whether cancers avoid poisoning from oxidised nucleotides by preventing incorporation via the oxidised purine diphosphatase MTH1 remains under debate. Also, little is known about DNA polymerases incorporating oxidised nucleotides in cells or how oxidised nucleotides in DNA become toxic. We show replacement of one of the main DNA replicases in human cells, DNA polymerase delta (Pol δ), to an error-prone variant allows increased 8-oxodG accumulation into DNA following treatment with the MTH1 inhibitor (MTH1i) TH588. The resulting elevated genomic 8-oxodG correlates with increased cytotoxicity of TH588. Interestingly, no substantial perturbation of replication fork progression is observed, but rather mitotic progression is impaired and mitotic DNA synthesis triggered. Reducing mitotic arrest by reversin treatment prevents accumulation of genomic 8-oxodG and reduces cytotoxicity of TH588, in line with the notion that mitotic arrest is required for ROS build-up and oxidation of the nucleotide pool. Furthermore, we demonstrate delayed mitosis and increased mitotic cell death following TH588 treatment in cells expressing the error-prone Pol δ variant, which is not observed following treatments with anti-mitotic agents, thus linking incorporation of oxidised nucleotides and disturbed mitotic progression.
Investigation of the validity of two Bayesian ancestral state reconstruction models for estimatingSalmonellatransmission during outbreaks
Authors: Bloomfield Samuel J. , Vaughan Timothy G. , Benschop Jackie , Marshall Jonathan C. , Hayman David T. S. , Biggs Patrick J. , Carter Philip E. , French Nigel P.
Published: March 2019

Ancestral state reconstruction models use genetic data to characterize a group of organisms’ common ancestor. These models have been applied to salmonellosis outbreaks to estimate the number of transmissions between different animal species that share similar geographical locations, with animal host as the state. However, as far as we are aware, no studies have validated these models for outbreak analysis. In this study, salmonellosis outbreaks were simulated using a stochastic Susceptible-Infected-Recovered model, and the host population and transmission parameters of these simulated outbreaks were estimated using Bayesian ancestral state reconstruction models (discrete trait analysis (DTA) and structured coalescent (SC)). These models were unable to accurately estimate the number of transmissions between the host populations or the amount of time spent in each host population. The DTA model was inaccurate because it assumed the number of isolates sampled from each host population was proportional to the number of individuals infected within each host population. The SC model was inaccurate possibly because it assumed that each host population’s effective population size was constant over the course of the simulated outbreaks. This study highlights the need for phylodynamic models that can take into consideration factors that influence the characteristics and behavior of outbreaks, e.g. changing effective population sizes, variation in infectious periods, intra-population transmissions, and disproportionate sampling of infected individuals.
Extent, heritability, and functional relevance of single cell expression variability in highly homogeneous populations of human cells
Authors: Osorio Daniel , Yu Xue , Zhong Yan , Li Guanxun , Yu Peng , Serpedin Erchin , Huang Jianhua , Cai James J.
Published: March 2019

Because of recent technological developments, single-cell assays such as single-cell RNA sequencing (scRNA-seq) have become much more widely available and have achieved unprecedented resolution in revealing cell heterogeneity. The extent of intrinsic cell-to-cell variability in gene expression, orsingle cell expression variability(scEV), has thus been increasingly appreciated. However, it remains unclear whether this variability is functionally important and, if so, what its implications are for multi-cellular organisms. We therefore analyzed multiple scRNA-seq data sets from lymphoblastoid cell lines (LCLs), lung airway epithelial cells (LAECs), and dermal fibroblasts (DFs). For each of the three cell types, we estimated scEV in homogeneous populations of cells; we identified 465, 466, and 291 highly variable genes (HVGs), respectively. These HVGs were enriched with specific functions precisely relevant to the cell types, from which the scRNA-seq data used to identify HVGs were generated—e.g., HVGs identified in lymphoblastoid cells were enriched in cytokine signaling pathways, LAECs collagen formation, and DFs keratinization. HVGs were deeply embedded in gene regulatory networks specific to corresponding cell types. We also found that scEV is a heritable trait, partially determined by cell donors’ genetic makeups. Furthermore, across genes, especially immune genes, levels of scEV and between-individual variability in gene expression were positively correlated, suggesting a potential link between the two variabilities measured at different organizational levels. Taken together, our results support the “variation is function” hypothesis, which postulates that scEV is required for higher-level system function. Thus, we argue that quantifying and characterizing scEV in relevant cell types may deepen our understating of normal as well as pathological cellular processes.
The structure of species discrimination signals across a primate radiation
Authors: Winters Sandra , Allen William L. , Higham James P.
Published: March 2019

Discriminating between conspecifics and heterospecifics potentially challenging for closely related sympatric species. The guenons, a recent primate radiation, exhibit high degrees of sympatry and form multi-species groups in which hybridization is possible but rare in most populations. Guenons have species-specific colorful face patterns hypothesized to function in species discrimination. Here, we apply a novel machine learning approach to identify the face regions most essential for correct species classification across fifteen guenon species. We then demonstrate the validity of these computational results using experiments with live guenons, showing that facial traits identified as critical for accurate classification do indeed influence selective attention toward con- and heterospecific faces. Our results suggest variability among guenon species in reliance on single-trait-based versus holistic facial characteristics when discriminating between species, and differences in behavioral responses to faces can be linked to whether discrimination is based on a single trait or whole-face pattern. Our study supports the hypothesis that guenon face patterns function to promote species discrimination and provides novel insights into the relationship between species interactions and phenotypic diversity.
Anodal transcranial direct current stimulation reduces collinear lateral inhibition in normal peripheral vision
Authors: Raveendran Rajkumar Nallour , Tsang Katelyn , Tiwana Dilraj , Thompson Benjamin
Published: March 2019

Collinear flanking stimuli can reduce the detectability of a Gabor target presented in peripheral vision. This phenomenon is called collinear lateral inhibition and it may contribute to crowding in peripheral vision. Perceptual learning can reduce collinear lateral inhibition in peripheral vision, however intensive training is required. Our aim was to assess whether modulation of collinear lateral inhibition can be achieved within a short time-frame using a single 20-minute session of primary visual cortex anodal transcranial direct current stimulation (a-tDCS). Thirteen observers with normal vision performed a 2AFC contrast detection task with collinear flankers positioned at a distance of 2λ from the target (lateral inhibition) or 6λ (control condition). The stimuli were presented 6° to the left of a central cross and fixation was monitored with an infra-red eye tracker. Participants each completed two randomly sequenced, single-masked stimulation sessions; real anodal tDCS and sham tDCS. For the 2λ separation condition, a-tDCS induced a significant reduction in detection threshold (reduced lateral inhibition). Sham stimulation had no effect. No effects of a-tDCS were observed for the 6λ separation condition. This result lays the foundation for future work investigating whether a-tDCS may be useful as a visual rehabilitation tool for individuals with central vision loss who are reliant on peripheral vision.
Disrupting butterfly microbiomes does not affect host survival and development
Authors: Phalnikar Kruttika , Kunte Krushnamegh , Agashe Deepa
Published: March 2019

Associations with gut microbes play a crucial role in the physiology, immune function, development, and behavior of many insects. However, butterflies may be an exception to this pattern since butterfly microbiomes do not show the host-specific and developmental shifts that are expected to evolve under strong host-microbial associations. Here, we present the first experimental test of this hypothesis by disrupting gut microbial communities of two butterfly species, Danaus chrysippus and Ariadne merione. Larvae of both the species fed on host plant leaves that were either chemically sterilized or treated with antibiotics had significantly reduced bacterial loads and disrupted gut bacterial communities substantially. However, neither host species treated this way suffered a significant fitness cost. We did not find significant variation in survival, growth and development between test larvae and control larvae. This suggested that butterflies do not rely on their gut bacteria for digestion, detoxification, resource accumulation and metamorphosis. Thus, our results provide empirical support for the growing realization that dependence on gut bacteria for growth and survival is not a universal phenomenon across insects.
Selective labelling of arginine residues engaged in binding sulfatedglycosaminoglycans
Authors: Bui Thao P. , Li Yong , Nunes Quentin M. , Wilkinson Mark C. , Fernig David G.
Published: March 2019

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The activities of hundreds of proteins in the extracellular space are regulated by binding to the glycosaminoglycan heparan sulfate (HS). These interactions are driven by ionic bonds between sulfate and carboxylate groups on the polysaccharide and the side chains of basic residues in the protein. Here we develop a method to selectively label the guanidino side chains of arginine residues in proteins that engage the anionic groups in the sugar. The protein is bound to heparin (a common experimental proxy for HS) on an affinity column. Arginine side chains that are exposed to solvent, and thus involved in binding, are protected by reaction with the dicarbonyl phenylgyoxal (PGO). Elution of the bound proteins then exposes arginine side chains that had directly engaged with anionic groups on the polysaccharide. These are reacted with hydroxyl-phenylglyoxal (HPG). PGO was found to generate three products: a 1:1 product, the 1:1 water condensed product and a 2:1 PGO:arginine product. These three reaction products and that of HPG had distinct masses. Scripts were written to analyse the mass spectra and so identify HPG labelled arginine residues. Proof of principle was acquired on model peptides. The method was then applied to the identification of heparin binding arginine residues in fibroblast growth factors (FGF) 1 and 2. The data demonstrate that four out of eleven arginine residues on FGF2 and five out of six arginine residues of FGF1 engage heparin. Our approach provides a rapid and reliable means to identify arginines involved in functional complexes such as those of proteins with heparin
PHi-C: deciphering Hi-C data into polymer dynamics
Authors: Shinkai Soya , Nakagawa Masaki , Sugawara Takeshi , Togashi Yuichi , Ochiai Hiroshi , Nakato Ryuichiro , Taniguchi Yuichi , Onami Shuichi
Published: March 2019

Computational modelling methods for Hi-C data have revealed averaged and static features of the 3D genome in cell nuclei. Here, we describe a 4D simulation method, PHi-C (Polymer dynamics deciphered from Hi-C data), that depicts dynamic 3D genome features through polymer modelling. This method allows for demonstrations of dynamic characteristics of genomic loci and chromosomes, as observed in live-cell imaging experiments, and provides physical insights into Hi-C data.
COALIA: a computational model of human EEG for consciousness research
Authors: Bensaid Siouar , Modolo Julien , Merlet Isabelle , Wendling Fabrice , Benquet Pascal
Published: March 2019

Understanding the origin of the main physiological processes involved in consciousness is a major challenge of contemporary neuroscience, with crucial implications for the study of Disorders of Consciousness (DOC). The difficulties in achieving this task include the considerable quantity of experimental data in this field, along with the non-intuitive, nonlinear nature of neuronal dynamics. One possibility of integrating the main results from the experimental literature into a cohesive framework, while accounting for nonlinear brain dynamics, is the use of physiologically-inspired computational models. In this study, we present a physiologically-grounded computational model, attempting to account for the main micro-circuits identified in the human cortex, while including the specificities of each neuronal type. More specifically, the model accounts for thalamo-cortical (vertical) regulation of cortico-cortical (horizontal) connectivity, which is a central mechanism for brain information integration and processing. The distinct neuronal assemblies communicate through feedforward and feedback excitatory and inhibitory synaptic connections implemented in a template brain accounting for long-range connectome. The EEG generated by this physiologically-based simulated brain is validated through comparison with brain rhythms recorded in humans in two states of consciousness (wakefulness, sleep). Using the model, it is possible to reproduce the local disynaptic disinhibition of basket cells (fast GABAergic inhibition) and glutamatergic pyramidal neurons through long-range activation of VIP interneurons that induced inhibition of SST interneurons. The model (COALIA) predicts that the strength and dynamics of the thalamic output on the cortex control the local and long-range cortical processing of information. Furthermore, the model reproduces and explains clinical results regarding the complexity of transcranial magnetic stimulation TMS-evoked EEG responses in DOC patients and healthy volunteers, through a modulation of thalamo-cortical connectivity that governs the level of cortico-cortical communication. This new model provides a quantitative framework to accelerate the study of the physiological mechanisms involved in the emergence, maintenance and disruption (sleep, anesthesia, DOC) of consciousness.
Chestnut extract but not sodium salicylate decrease the severity of diarrhea and enterotoxigenic Escherichia coli F4 shedding in artificially infected piglets
Authors: Girard M. , Hu D. , Pradervand N. , Neuenschwander S. , Bee G.
Published: March 2019

The development of alternatives to antibiotics is crucial to limiting the incidence of antimicrobial resistance, especially in prophylactic and metaphylactic use to control post-weaning diarrhea (PWD). Feed additives, including bioactive compounds, could be a promising alternative. This study aimed to test two bioactive compounds, sodium salicylate (SA) and a chestnut extract (CE) containing hydrolysable tannins, on the occurrence of PWD. At weaning, 72 piglets were assigned to four treatments that combined two factors: CE supplementation (with 2% of CE (CE+) or without (CE-)) and SA supplementation (with 35 mg/kg BW of SA (SA+) or without (SA-)). Then, 4 days after weaning, all piglets were infected with a suspension at 108 CFU/ml of enterotoxigenic Escherichia coli (ETEC F4ac). Each piglet had free access to an electrolyte solution containing, or not, SA. This SA supplementation was administered for 5 days (i.e., from the day of infection (day 0) to 4 days post-infection (day 4). During the 2 weeks post-infection, supplementation with SA had no effect (P > 0.05) on growth performances nor on fecal scores. A significant SA × time interaction (P < 0.01) for fecal scores and the percentage of diarrhea indicated that piglets with SA did not recover faster and did have a second episode of diarrhea. In contrast to SA treatment, inclusion of CE increased (P < 0.05) growth performances and feed intake. In the first week post-infection, CE decreased (P < 0.001) the overall fecal scores, the percentage of piglets with diarrhea, the days in diarrhea, and ETEC shedding in the feces. There was a SA×CE interaction (P < 0.05) for ETEC shedding, suggesting a negative effect of combining SA with CE. This study highlighted that, in contrast to SA, CE could represent a promising alternative to antibiotics immediately after weaning for improving growth performance and reducing PWD.
Infection with a small intestinal helminth Heligmosomoides polygyrus bakeri consistently alters microbial communities throughout the small and large intestine
Authors: Rapin Alexis , Chuat Audrey , Lebon Luc , Zaiss Mario M. , Marsland Benjamin , Harris Nicola L.
Published: March 2019

Increasing evidence suggests that intestinal helminth infection can alter intestinal microbial communities with important impacts on the mammalian host. However, all of the studies to date utilize different techniques to study the microbiome and access different sites of the intestine with little consistency noted between studies. In the present study, we set out to perform a comprehensive analysis of the impact of intestinal helminth infection on the mammalian intestinal bacterial microbiome. For this purpose, we investigated the impact of experimental infection using the natural murine small intestinal helminth,Heligmosomoides polygyrus bakeri(Hpb) and examined possible alterations in both the mucous and luminal bacterial communities along the entire small and large intestine. We also explored the impact of common experimental variables, including the parasite batch and pre-infection microbiome, on the outcome of helminth-bacterial interactions. This work provides evidence that helminth infection reproducibly alters intestinal microbial communities – with an impact of infection noted along the entire length of the intestine. Although the exact nature of helminth-induced alterations to the intestinal microbiome differed depending on the parasite batch and microbiome community structure present prior to infection, changes extended well beyond the introduction of new bacterial species by the infecting larvae. Moreover, striking similarities between different experiments were noted, including the consistent outgrowth of a bacterium belonging to the Peptostreptococcaceae family throughout the intestine.

Author Summary

Increasing evidence indicates a role for interactions between intestinal helminths and the microbiome in regulating mammalian health, and a greater understanding of helminth-microbiota interactions may open the path for the development of novel immunomodulatory therapies. However, such studies are hampered by the inconsistent nature of the data reported so far. Such inconsistancies likely result from variations in the experimental and technological methodologies employed to investigate helminth-microbiota interactions and well has natural variation in the starting microbiome composition and/or worm genetics. We conducted a thorough study in which the reproducibility of helminth-induced alterations of microbial communities was determined and impact of common experimental variables – such as the starting microbiome and parasite batch - was determined. Our work reveals the robust ability of small intestinal helminth infection to alter microbial communities along the entire length of the intestine and additionally identifies a single bacterium that is strongly associated with infection across multiple experiments.