bluuebunny/crossref_metadata_2025 huggingface dataset:
Predicting plant disease epidemics from functionally represented weather series
Authors: Shah D. A. , Paul P. A. , De Wolf E. D. , Madden L. V.
Published: May 2019

Epidemics are often triggered by specific weather patterns favouring the pathogen on susceptible hosts. For plant diseases, models predicting epidemics have therefore often emphasized the identification of early season weather patterns that are correlated with a disease outcome at some later point. Toward that end, window-pane analysis is an exhaustive search algorithm traditionally used in plant pathology for mining correlations in a weather series with respect to a disease endpoint. Here we show, with reference to Fusarium head blight (FHB) of wheat, that a functional approach is a more principled analytical method for understanding the relationship between disease epidemics and environmental conditions over an extended time series. We used scalar-on-function regression to model a binary outcome (FHB epidemic or non-epidemic) relative to weather time series spanning 140 days relative to flowering (when FHB infection primarily occurs). The functional models overall fit the data better than previously described standard logistic regression (lr) models. Periods much earlier than heretofore realized were associated with FHB epidemics. The findings were used to create novel weather summary variables which, when incorporated into lr models, yielded a new set of models that performed as well as existing lr models for real-time predictions of disease risk.

This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’. This issue is linked with the subsequent theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’.
A case of cutaneous toxigenic Corynebacterium ulcerans likely acquired from a domestic dog
Authors: Othieno Richard , Mark Kate , Etherson Michelle , Foster Geoffrey , Murray Steven , Kalima Pota , Fry Norman K. , Cameron Claire , Strachan Jenni
Published: May 2019

Introduction.

Corynebacterium ulcerans

can produce diphtheria toxin and although still rare, is now the predominant cause of toxigenic diphtheria infection in the UK, making this organism of great clinical and public health importance. Here we describe a cutaneous case, likely secondary to domestic animal contact.

Case presentation. A 60-year-old female presented with a slow-healing finger-burn wound. A skin swab cultured Corynebacterium ulcerans, which was confirmed to be toxin producing. She resided with her partner and two dogs, one of which had a chronic skin lesion. Her most recent diphtheria vaccine was in 2009. Four close contacts were identified, two of whom were healthcare professionals, and nose and throat swabs were obtained. The patient was treated with clarithromycin (14 day course), diphtheria vaccine and excluded from work until completion of antibiotics and negative clearance swabs. Contacts were given erythromycin (7 day course), vaccinated and healthcare worker contacts excluded from work until swab negative. A veterinary practitioner swabbed the throats and a skin lesion of their dogs. One contact (partner of patient) and all dog swabs were positive. Partial allelic profiles from MLST supported an epidemiological link. The dogs were treated with antibiotics and antimicrobial skin wash. Repeat swabs for the index case, contact and both dogs were negative following treatment.

Conclusion. This was a rare case of cutaneous diphtheria secondary to

Corynebacterium ulcerans

with domestic animals the most likely source, although human-to-human contact could not be excluded, with important human and animal public health implications.
Tmod2 is a regulator of cocaine responses through control of striatal and cortical excitability, and drug-induced plasticity
Authors: Mitra Arojit , Deats Sean P. , Dickson Price E. , Zhu Jiuhe , Gardin Justin , Nieman Brian J. , Henkelman R. Mark , Tsai Nien-Pei , Chesler Elissa J. , Zhang Zhong-Wei , Kumar Vivek
Published: May 2019

Drugs of abuse induce neuroadaptations, including synaptic plasticity, that are critical for transition to addiction, and genes and pathways that regulate these neuroadaptations are potential therapeutic targets. Tropomodulin 2 (Tmod2) is an actin-regulating gene that plays an important role in synapse maturation and dendritic arborization and has been implicated in substance-abuse and intellectual disability in humans. Here we mine the KOMP2 data and find that Tmod2 knockout mice show emotionality phenotypes that are predictive of addiction vulnerability. Detailed addiction phenotyping showed that Tmod2 deletion does not affect the acute locomotor response to cocaine administration. However, sensitized locomotor responses are highly attenuated in these knockouts, indicating perturbed drug-induced plasticity. In addition, Tmod2 mutant animals do not self-administer cocaine indicating lack of hedonic responses to cocaine. Whole brain MR imaging shows differences in brain volume across multiple regions although transcriptomic experiments did not reveal perturbations in gene co-expression networks. Detailed electrophysiological characterization of Tmod2 KO neurons, showed increased spontaneous firing rate of early postnatal and adult cortical and striatal neurons. Cocaine-induced synaptic plasticity that is critical for sensitization is either missing or reciprocal in Tmod2 KO nucleus accumbens shell medium spiny neurons, providing a mechanistic explanation of the cocaine response phenotypes. Combined, these data provide compelling evidence that Tmod2 is a major regulator of plasticity in the mesolimbic system and regulates the reinforcing and addictive properties of cocaine.

Significance statement

We identify, characterize, and establish tropomodulin 2 (Tmod2), an actin-regulating gene exclusively expressed in neurons, as an important regulator of addiction-related phenotypes. We show that Tmod2, knockout mice (Tmod2 KO) exhibit phenotypes that are predictive of addiction. In detailed addiction phenotyping, we find the Tmod2 regulates cocaine sensitization and self-administration. We explore anatomical, transcriptional, electrophysiological mechanisms of this regulation. Combined these studies provide compelling evidence that Tmod2 is critical for synaptic plasticity necessary for transition to addiction.
Reply to “A discriminative learning approach to differential expression analysis for single-cell RNA-seq”
Authors: Becht Etienne , Zhao Edward , Amezquita Robert , Gottardo Raphael
Published: May 2019

Multivariate logistic regression (mLR) has been recently proposed by Ntranos et al. to perform gene differential expression analyses of single-cell RNA-sequencing (scRNAseq) data. Herein we reproduce and extend some of their findings. We notably show that while mLR performs better in simulated datasets, these simulations do not recapitulate important features of experimental datasets. Indeed, our results suggest that MAST followed by Sidak aggregation of the p-values perform better than mLR on experimental datasets. Overall, we highlight that most of the new results obtained by Ntranos et al is likely due to the quantification of scRNAseq data at the transcript or transcript compatibility classes level, rather than the use of mLR.
Lights, Camera, Path Splitter: A New Approach for Truly Simultaneous Dual Optical Mapping of the Heart with a Single Camera
Authors: Jaimes Rafael , McCullough Damon , Siegel Bryan , Swift Luther , Hiebert James , McInerney Daniel , Posnack Nikki Gillum
Published: May 2019

Background

Optical mapping of transmembrane voltage and intracellular calcium is a powerful tool for investigating cardiac physiology and pathophysiology. However, simultaneous dual mapping of two fluorescent probes remains technically challenging. We introduce a novel, easy-to-use approach that requires a path splitter, single camera and excitation light to simultaneously acquire voltage and calcium signals from whole heart preparations, which can be applied to other physiological models – including neurons and isolated cardiomyocytes.

Results

Complementary probes were selected that could be excited with a single wavelength light source. Langendorff-perfused hearts (rat, swine) were stained and imaged using a sCMOS camera outfitted with an optical path splitter to simultaneously acquire two emission fields at high spatial and temporal resolution. Voltage (RH237) and calcium (Rhod2) signals were acquired concurrently on a single sensor, resulting in two 384×256 images at 814 frames per second. At this frame rate, the signal-to-noise ratio was 47 (RH237) and 85 (Rhod2). Imaging experiments were performed on small rodent hearts, as well as larger pig hearts with sufficient optical signals. In separate experiments, each dye was used independently to assess crosstalk and demonstrate signal specificity. Additionally, the effect of ryanodine on myocardial calcium transients was validated – with no measurable effect on the amplitude of optical action potentials. To demonstrate spatial resolution, ventricular tachycardia was induced –resulting in the novel finding that spatially discordant calcium alternans can be present in different regions of the heart, even when electrical alternans remain concordant. The described system excels in providing a wide field of view and high spatiotemporal resolution for a variety of cardiac preparations.

Conclusions

We report the first multiparametric mapping system that simultaneously acquires calcium and voltage signals from cardiac preparations, using a path splitter, single camera and excitation light. This approach eliminates the need for multiple cameras, excitation light patterning or frame interleaving. These features can aid in the adoption of dual mapping technology by the broader cardiovascular research community, and decrease the barrier of entry into panoramic heart imaging, as it reduces the number of required cameras.
Ribosomal DNA methylation as stable biomarkers for detection of cancer in plasma
Authors: Zhang Xianglin , Fang Huan , Zhang Wei , Zhong Bixi , Li Yanda , Wang Xiaowo
Published: May 2019

Background

Recently, liquid biopsy for cancer detection has pursued great progress. However, there are still a lack of high quality markers. It is a challenge to detect cancer stably and accurately in plasma cell free DNA (cfDNA), when the ratio of cancer signal is low. Repetitive genes or elements may improve the robustness of signals. In this study, we focused on ribosomal DNA which repeats hundreds of times in human diploid genome and investigated performances for cancer detection in plasma.

Results

We collected bisulfite sequencing samples including normal tissues and 4 cancer types and found that intergenic spacer (IGS) of rDNA has high methylation levels and low variation in normal tissues and plasma. Strikingly, IGS of rDNA shows significant hypo-methylation in tumors compared with normal tissues. Further, we collected plasma bisulfite sequencing data from 224 healthy subjects and cancer patients. Means of AUC in testing set were 0.96 (liver cancer), 0.94 (lung cancer and), 0.92 (colon cancer) with classifiers using only 10 CpG sites. Due to the feature of high copy number, when liver cancer plasma WGBS was down-sampled to 10 million raw reads (0.25× whole genome coverage), the prediction performance decreased only a bit (mean AUC=0.93). Finally, methylation of rDNA could also be used for monitor cancer progression and treatment.

Conclusion

Taken together, we provided the high-resolution map of rDNA methylation in tumors and supported that methylation of rDNA was a competitive and robust marker for detecting cancer and monitoring cancer progression in plasma.
Controlling and co-ordinating chitinase secretion in aSerratia marcescenspopulation
Authors: de Assis Alcoforado Costa Marília , Owen Richard A. , Tammsalu Triin , Buchanan Grant , Palmer Tracy , Sargent Frank
Published: May 2019

Serratia marcescensis a γ-Proteobacterium and an opportunistic animal and insect pathogen. The bacterium exhibits a complex extracellular protein ‘secretome’ comprising numerous enzymes, toxins and effector molecules. One component of the secretome is the ‘chitinolytic machinery’, which is a set of at least four chitinases that allow the use of insoluble extracellular chitin as sole carbon and nitrogen source. Secretion of the chitinases across the outer membrane is governed by thechiWXYZoperon encoding a holin/endopeptidase pair. Expression of thechiWXYZoperon is co-ordinated with the chitinase genes and is also bimodal, since normally only 1% of the population expresses the chitinolytic machinery. In this work, the role of the ChiR protein in chitinase production has been explored. Using live cell imaging and flow cytometry, ChiR was shown to govern the co-ordinated regulation ofchiWXYZwith bothchiAandchiC. Moreover, overexpression ofchiRalone was able to increase the proportion of the cell population expressing chitinase genes to >60%. In addition, quantitative label-free proteomic analysis of cells overexpressingchiRestablished that ChiR regulates the entire chitinolytic machinery. The proteomic experiments also revealed a surprising link between the regulation of the chitinolytic machinery and the production of proteins involved in the metabolism of nitrogen compounds such as nitrate and nitrite. The research demonstrates for the first time that ChiR plays a critical role in controlling bimodal gene expression inS. marcescens, and provides new evidence of a clear link between chitin breakdown and nitrogen metabolism.

IMPORTANCE

The opportunistic pathogenSerratia marcescenssecretes chitinases through the action of thechiWXYZoperon, which encodes a holin/endopeptidase pair. Expression ofchiWXYZis normally bimodal, with only 1% of the population transcribing these genes. In this work, it is demonstrated that overexpression ofchiRinduces exquisitely co-ordinated holin/endopeptidase and chitinase gene expression in the majority of the population of cells, establishing that ChiR is a key player in biomodal gene expression. This work also reveals for the first time that co-operating pathways are induced by ChiR, including enzymes involved in ammonia, nitrite and nitrate metabolism. This work expands knowledge of basic bacterial physiology and could have applications in the biomedical and biotechnological research fields.
CRISPR-Cas9 mutated pregnane x receptor (pxr) retains pregnenolone-induced expression of cytochrome p450 family 3, subfamily A, polypeptide 65 (cyp3a65) in zebrafish (Danio rerio) larvae
Authors: Salanga Matthew C. , Brun Nadja R. , Francolini Rene , Stegeman John J. , Goldstone Jared V.
Published: May 2019

Pregnane x receptor (PXR) is a nuclear receptor that regulates transcriptional responses to drug or xenobiotic exposure in many vertebrate species. One key response is the induction of cytochrome P450 3A (CYP3A) transcription. PXR is a promiscuous receptor activated by a wide range of ligands that can differ across species, making functional studies on its role in the chemical defensome, most relevant when approached in a species-specific manner. Genetic knockout studies in mammals have shown a requirement for PXR in ligand-dependent activation of CYP3A expression or reporter gene activity. Transient knockdown in zebrafish revealed a similar requirement, however it is not known what the effect of a genetic knockout would be in the zebrafish model. Here, we report on generation of two zebrafish lines each carrying a genetic deletion in the pxr coding region, predicted to result in loss of a functional gene product. To our surprise zebrafish larvae, homozygous for either of the pxr mutant alleles, retain their ability to induce cyp3a65 mRNA expression following exposure to the established zebrafish Pxr ligand, pregnenolone (PN). Thus, zebrafish carrying pxr alleles with sizable deletions in either the DNA binding or the ligand binding domains do not yield a loss-of-function phenotype, suggesting that a compensatory mechanism is responsible for cyp3a65 induction. Two alternative possibilities are that Pxr is not required for the effect or that truncated yet functional mutant Pxr is sufficient for the effect.
Community driven dynamics of oscillatory network responses to threat
Authors: Muthuraman M , Chirumamilla VC , Koirala N , Anwar AR , Tüscher O , Vogt J , Horstmann P , Meyer B , Bonano GA , Gonzalez-Escamilla G , Groppa S
Published: May 2019

Physiological responses to threat stimuli involve neural synchronized oscillations in cerebral networks with distinct organization properties. Community architecture within these networks and its dynamic adaptation could play a critical role in achieving optimal physiological responses.

Here we applied dynamic network analyses to address the early phases of threat processing at the millisecond level, describing multi-frequency (theta and alpha) integration and basic reorganization properties (flexibility and clustering) that drive physiological responses. We quantified cortical and subcortical network interactions and captured illustrative reconfigurations using community allegiance as essential fingerprints of large-scale adaptation.

A theta band driven community reorganization of key anatomical regions forming the threat network (TN) along with transitions of nodes from the dorsal attention (DAN) and salience (SN) circuits predict the optimal physiological response to threat. We show that increase flexibility of the community network architecture drives the physiological responses during instructed threat processing. Nodal switches modulate the directionality of information flows in the involved circuits.

These results provide a captivating perspective of flexible network responses to threat and shed new light on basic physiological principles relevant for the development of stress- and threat-related mental disorders.
Brain-predicted age difference score is related to specific cognitive functions: A multi-site replication analysis
Authors: Boyle R. , Jollans L. , Rueda-Delgado L.M. , Rizzo R. , Yener G.G. , McMorrow J.P. , Knight S.P. , Carey D. , Robertson I.H. , Emek-Savaş D.D. , Stern Y. , Kenny R.A. , Whelan R.
Published: May 2019

Brain-predicted age difference scores are calculated by subtracting chronological age from ‘brain’ age, which is estimated using neuroimaging data. Positive scores reflect accelerated ageing and are associated with increased mortality risk and poorer physical function. To date, however, the relationship between brain-predicted age difference scores and specific cognitive functions has not been systematically examined using appropriate statistical methods. First, applying machine learning to 1,359 T1-weighted MRI scans, we predicted the relationship between chronological age and voxel-wise grey matter data. This model was then applied to MRI data from three independent datasets, significantly predicting chronological age in each dataset: Dokuz Eylül University (n=175), the Cognitive Reserve/Reference Ability Neural Network study (n=380), and The Irish Longitudinal Study on Ageing (n=487). Each independent dataset had rich neuropsychological data. Brain-predicted age difference scores were significantly negatively correlated with performance on measures of general cognitive status (two datasets); processing speed, visual attention, and cognitive flexibility (three datasets); visual attention and cognitive flexibility (two datasets); and semantic verbal fluency (two datasets). As such, there is firm evidence of correlations between increased brain-predicted age differences and reduced cognitive function in some domains that are implicated in cognitive ageing.
Locally-adapted Mimulus ecotypes differentially impact rhizosphere bacterial and archaeal communities in an environment-dependent manner
Authors: Bowsher Alan W. , Kearns Patrick J. , Popovic Damian , Lowry David B. , Shade Ashley
Published: May 2019

Plant root-microbe interactions influence plant productivity, health, and resistance to stress. Although there is evidence that plant species and even genotypes can alter soil microbial community structure, environmental conditions can potentially outweigh plant genetic effects. Here, we used a reciprocal transplant experiment to understand the contributions of the environment and the host plant to rhizosphere microbiome composition in locally-adapted ecotypes of Mimulus guttatus (syn. Erythranthe guttata (Fisch. ex DC.) G.L. Nesom). Two genotypes of a coastal ecotype and two genotypes of an inland ecotype were planted at coastal and inland sites. After three months, we collected rhizosphere and bulk soil and assessed microbial communities by 16S rRNA gene sequencing. We found that local environment (coastal versus inland site) strongly influenced rhizosphere communities, at least in part due to distinct local microbial species pools. Host identity played a smaller role: at each site, the ecotypes exhibited remarkably similar composition of microbial communities at the class level, indicating that divergent M. guttatus ecotypes recruit phylogenetically similar rhizosphere communities, even in environments to which they are maladapted. Nevertheless, the two ecotypes significantly differed in community composition at the inland site due to an exclusive set of rare taxa associated with each ecotype. Although our results indicate that locally-adapted M. guttatus ecotypes are genetically diverged in factors shaping rhizosphere communities, environmental factors can trump genetic factors in shaping the M. guttatus microbiome. Overall, our findings demonstrate that wild plants strongly impact root-associated microbial communities, but hierarchical drivers interact to shape microbial community assembly outcomes.
gapsplit: Efficient random sampling for non-convex constraint-based models
Authors: Keaty Thomas C. , Jensen Paul A.
Published: May 2019

Gapsplit generates random samples from convex and non-convex constraint-based models. Gapsplit targets under-sampled regions of the solution space for uniform coverage.

Availability and Implementation

Python and Matlab source code are freely available at http://jensenlab.net/tools.

Contact

pjens@illinois.edu
Making the most of Clumping and Thresholding for polygenic scores
Authors: Privé Florian , Vilhjálmsson Bjarni J. , Aschard Hugues , Blum Michael G.B.
Published: May 2019

Polygenic prediction has the potential to contribute to precision medicine. Clumping and Thresh-olding (C+T) is a widely used method to derive polygenic scores. When using C+T, it is common to test several p-value thresholds to maximize predictive ability of the derived polygenic scores. Along with this p-value threshold, we propose to tune three other hyper-parameters for C+T. We implement an efficient way to derive thousands of different C+T polygenic scores corresponding to a grid over four hyper-parameters. For example, it takes a few hours to derive 123,200 different C+T scores for 300K individuals and 1M variants on a single node with 16 cores.

We find that optimizing over these four hyper-parameters improves the predictive performance of C+T in both simulations and real data applications as compared to tuning only the p-value threshold. A particularly large increase can be noted when predicting depression status, from an AUC of 0.557 (95% CI: [0.544-0.569]) when tuning only the p-value threshold in C+T to an AUC of 0.592 (95% CI: [0.580-0.604]) when tuning all four hyper-parameters we propose for C+T.

We further propose Stacked Clumping and Thresholding (SCT), a polygenic score that results from stacking all derived C+T scores. Instead of choosing one set of hyper-parameters that maximizes prediction in some training set, SCT learns an optimal linear combination of all C+T scores by using an efficient penalized regression. We apply SCT to 8 different case-control diseases in the UK biobank data and find that SCT substantially improves prediction accuracy with an average AUC increase of 0.035 over standard C+T.
Strong Purifying Selection Contributes to Genome Streamlining in Epipelagic Marinimicrobia
Authors: Martinez-Gutierrez Carolina Alejandra , Aylward Frank O.
Published: May 2019

Marine microorganisms inhabiting nutrient-depleted waters play critical roles in global biogeochemical cycles due to their abundance and broad distribution. Many of these microbes share similar genomic features including small genome size, low % G+C content, short intergenic regions, and low nitrogen content in encoded amino acids, but the evolutionary drivers of these characteristics are unclear. Here we compared the strength of purifying selection across the Marinimicrobia, a candidate phylum which encompasses a broad range of phylogenetic groups with disparate genomic features, by estimating the ratio of non-synonymous and synonymous substitutions (dN/dS) in conserved marker genes. Our analysis shows significantly lower dN/dS values in epipelagic Marinimicrobia that exhibit features consistent with genome streamlining when compared to their mesopelagic counterparts. We found a significant positive correlation between median dN/dS values and genomic traits associated to streamlined organisms, including % G+C content, genome size, and intergenic region length. Our findings are consistent with genome streamlining theory, which postulates that small, compact genomes with low G+C contents are adaptive and the product of strong purifying selection. Our results are also in agreement with previous findings that genome streamlining is common in epipelagic waters, suggesting that genomes inhabiting this region of the ocean have been shaped by strong selection together with prevalent nutritional constraints characteristic of this environment.
Cochlear activity in silent cue-target intervals shows a theta-rhythmic pattern and is correlated to attentional alpha modulations
Authors: Albrecht Köhler Moritz Herbert , Demarchi Gianpaolo , Weisz Nathan
Published: May 2019

A long-standing debate concerns where in the processing hierarchy of the central nervous system (CNS) selective attention takes effect. In the auditory system cochlear processes can be influenced via direct and mediated (by the inferior colliculus) projections from the auditory cortex to the superior olivary complex (SOC). Studies illustrating attentional modulations of cochlear responses have so far been limited to sound-evoked responses. The aim of the present study is to investigate intermodal (audiovisual) selective attention in humans simultaneously at the cortical and cochlear level during a stimulus-free cue-target period. We found that cochlear activity in the silent cue-target periods was modulated by a theta-rhythmic pattern (∼6 Hz). While this pattern was present independently of attentional focus, cochlear theta activity was clearly enhanced when attending to the upcoming auditory input. On a cortical level, classical posterior alpha and beta power enhancements were found during auditory selective attention. Interestingly, participants with a stronger release of inhibition in auditory brain regions show a stronger attentional modulation of cochlear theta activity. These results hint at a putative theta-rhythmic sampling of auditory input at the cochlear level. Furthermore, our results point to an interindividual variable engagement of efferent pathways in an attentional context that are linked to processes within and beyond processes in auditory cortical regions.
Reward-predictive representations generalize across tasks in reinforcement learning
Authors: Lehnert Lucas , Littman Michael L. , Frank Michael J.
Published: May 2019

In computer science, reinforcement learning is a powerful framework with which artificial agents can learn to maximize their performance for any given Markov decision process (MDP). Advances over the last decade, in combination with deep neural networks, have enjoyed performance advantages over humans in many difficult task settings. However, such frameworks perform far less favorably when evaluated in their ability to generalize or transfer representations across different tasks. Existing algorithms that facilitate transfer typically are limited to cases in which the transition function or the optimal policy is portable to new contexts, but achieving “deep transfer” characteristic of human behavior has been elusive. Such transfer typically requires discovery of abstractions that permit analogical reuse of previously learned representations to superficially distinct tasks. Here, we demonstrate that abstractions that minimize error in predictions of reward outcomes generalize across tasks with different transition and reward functions. Such reward-predictive representations compress the state space of a task into a lower dimensional representation by combining states that are equivalent in terms of both the transition and reward functions. Because only state equivalences are considered, the resulting state representation is not tied to the transition and reward functions themselves and thus generalizes across tasks with different reward and transition functions. These results contrast with those using abstractions that myopically maximize reward in any given MDP and motivate further experiments in humans and animals to investigate if neural and cognitive systems involved in state representation perform abstractions that facilitate such equivalence relations.

Author summary

Humans are capable of transferring abstract knowledge from one task to another. For example, in a right-hand-drive country, a driver has to use the right arm to operate the shifter. A driver who learned how to drive in a right-hand-drive country can adapt to operating a left-hand-drive car and use the other arm for shifting instead of re-learning how to drive. Despite the fact that both tasks require different coordination of motor skills, both tasks are the same in an abstract sense: In both tasks, a car is operated and there is the same progression from 1st to 2nd gear and so on. We study distinct algorithms by which a reinforcement learning agent can discover state representations that encode knowledge about a particular task, and evaluate how well they can generalize. Through a sequence of simulation results, we show that state abstractions that minimize errors in prediction about future reward outcomes generalize across tasks, even those that superficially differ in both the goals (rewards) and the transitions from one state to the next. This work motivates biological studies to determine if distinct circuits are adapted to maximize reward vs. to discover useful state representations.
Mechanisms of convergent egg-provisioning in poison frogs
Authors: Fischer Eva K. , Roland Alexandre B. , Moskowitz Nora A. , Vidoudez Charles , Ranaivorazo Ndimbintsoa , Tapia Elicio E. , Trauger Sunia A. , Vences Miguel , Coloma Luis A. , O’Connell Lauren A.
Published: May 2019

Parental provisioning of offspring with physiological products occurs in many animals. Within amphibians, maternal provisioning has evolved multiple times, including in South American dendrobatid and Malagasy mantellid poison frogs. In some of these species, mothers feed unfertilized eggs to their developing tadpoles for several months until tadpoles complete metamorphosis. We conducted field studies in Ecuador and Madagascar to ask whether convergence at the behavioral level provides similar benefits to offspring and whether nursing behavior relies on shared neural mechanisms across frogs and vertebrates more broadly. At an ecological level, we found that nursing allows poison frog mothers to provide chemical defenses to their tadpoles in both species. At the level of brain regions, nursing behavior was associated with increased neural activity in the lateral septum and preoptic area in both species, demonstrating recruitment of shared brain regions in the convergent evolution of maternal care within frogs and across vertebrates. In contrast at a molecular level, only mantellids showed increased oxytocin neuron activity akin to that in nursing mammals. Taken together, our findings demonstrate that convergently evolved maternal provisioning behavior provides similar benefits to offspring and relies on similar brain regions. However, the molecular mechanisms underlying the convergence in nursing behavior may be different, suggesting evolutionary versatility in the mechanisms promoting maternal behavior.
Not a one-way road – severity, progression and prevention of firework fears in dogs
Authors: Riemer Stefanie
Published: May 2019

Noise fears represent a highly prevalent welfare problem in dogs. An online survey was performed to explore severity and progression of firework fears in dogs, and relationships with demographics, health, behaviour problems, and owners’ training efforts to prevent or alleviate firework fears. 1225 responses were analysed. Fifty-two percent of dogs were at least partially affected by firework fears, and the great majority developed a fear of fireworks in the first year of life, with a decreasing frequency of new occurrences up until seven years, and only few newly affected dogs beyond this age. While almost three quarters of fearful dogs had recovered by the next morning, recovery took up to one day in 10%, up to one week in 12%, and several weeks or even months in >3%. Univariate analyses indicated a significant effect of breed group, age, sex, neuter status, origin and age at acquisition on severity of firework fears in dogs. However, binomial models including multiple predictors of presence/ absence of firework fears identified only age, breed group (mixed breeds being most affected), health problems, and an interaction between health problems and age as significant predictors. This discrepancy might be explained by collinearities of predictors and underlying differences between mixed-breed dogs and purebreds, such as mixed breeds being acquired from shelters more often, being adopted at higher ages, and being neutered more often. Firework fears are highly correlated with fears of gunshots and thunder, and to a low extent with fears of other noises, but not with any other behavioural problems. Both improvement and deterioration of firework fears were frequently reported. While an early age of onset and breed differences point to a strong genetic contribution to firework fears, training puppies or non-fearful adults to associate the noise with positive stimuli is highly effective in preventing later development of firework fears.
Evaluation and Optimization of Chemically-Cleavable Linkers for Quantitative Mapping of Small Molecule-Protein Interactomes
Authors: Rabalski Adam J. , Bogdan Andrew R. , Baranczak Aleksandra
Published: May 2019

Numerous reagents have been developed to enable chemical proteomic analysis of small molecule-protein interactomes. However, the performance of these reagents has not been systematically evaluated and compared. Herein, we report our efforts to conduct a parallel assessment of two widely-used chemically-cleavable linkers equipped with dialkoxydiphenylsilane (DADPS linker) and azobenzene (AZO linker) moieties. Profiling a cellular cysteinome using iodoacetamide alkyne probe demonstrated a significant discrepancy between the experimental results obtained through the application of each of the reagents. To better understand the source of observed discrepancy, a mass tolerant database search strategy using MSFragger software was performed. This resulted in identifying a previously unreported artifactual modification on the residual mass of the azobenzene linker. Furthermore, we conducted a comparative analysis of enrichment modes using both cleavable linkers. This effort determined that enrichment of proteolytic digests yielded a far greater number of identified cysteine residues than the enrichment conducted prior to protein digest. Inspired by recent studies where multiplexed quantitative labeling strategies were applied to cleavable biotin linkers, we combined this further optimized protocol using the DADPS cleavable linker with tandem mass tag (TMT) labeling to profile the FDA-approved covalent EGFR kinase inhibitor dacomitinib against the cysteinome of an epidermoid cancer cell line. Our analysis resulted in the detection and quantification of over 10,000 unique cysteine residues, a nearly 3-fold increase over previous studies that used cleavable biotin linkers for enrichment. Critically, cysteine residues corresponding to proteins directly as well as indirectly modulated by dacomitinib treatment were identified. Overall, our study suggests that the dialkoxydiphenylsilane linker could be broadly applied wherever chemically cleavable linkers are required for chemical proteomic characterization of cellular proteomes.
Scribble and Discs-large direct adherens junction positioning and supermolecular assembly to establish apical-basal polarity
Authors: Bonello Teresa T. , Peifer Mark
Published: May 2019

Apical-basal polarity is a fundamental property of animal tissues. TheDrosophilaembryo provides an outstanding model for defining mechanisms that initiate and maintain polarity. Polarity is initiated during cellularization, when cell-cell adherens junctions are positioned at the future boundary of apical and basolateral domains. Polarity maintenance then involves complementary and antagonistic interplay between apical and basal polarity complexes. The Scribble/Dlg module is well-known for promoting basolateral identity during polarity maintenance. Here we report a surprising role for the Scribble/Dlg module in polarity initiation, placing it at the top of the network that positions adherens junctions. Scribble and Dlg are enriched in nascent adherens junctions and are essential for adherens junction positioning and supermolecular assembly. They also play a role in basal junction assembly. We test hypotheses for the underlying mechanisms. Our data suggest that the Scribble/Dlg module plays multiple roles in polarity initiation, via Par-1-dependent and independent mechanisms. Different domains of Scribble contribute to these distinct roles. Together these data reveal novel roles for Scribble/Dlg as master scaffolds regulating the assembly of distinct junctional complexes at different times and places.
Allosteric regulation of glycogen phosphorylase solution phase structural dynamics at high spatial resolution
Authors: Kish Monika , Smith Victoria , Subramanian Sivaraman , Vollmer Frank , Lethbridge Natasha , Cole Lindsay , Bond Nicholas. J. , Phillips Jonathan J.
Published: May 2019

Glycogen phosphorylase (GlyP) was the first allosteric enzyme to be described. Yet, the precise dynamic changes in solution phase structure and stability that underpin functional regulation have remained elusive. We have developed a new fully-automated and highly flexible implementation of hydrogen/deuterium-exchange mass spectrometry, operating in the millisecond regime. This enabled measurements of the solution phase local structural dynamics involved in allosteric regulation of GlyP. Here, we quantify GlyP structural dynamics in solution, describing correlated changes in structure in the activated (pSer14) and inhibited (glucose-6-phosphate bound) forms of the enzyme. The sensitivity of these measurements discerned that the 250s’ loop is natively disordered in the apo T-state, adopting a more ordered conformation in the active state. The quantitative change in stability of the 280s loop is identified, providing the first direct evidence of the entropic switch that sterically regulates substrate access to the active site.

Significance Statement

We have developed a new fully-automated and highly flexible implementation of hydrogen/deuterium-exchange mass spectrometry, operating in the millisecond regime. Measurements of glycogen phosphorylase quantify the solution phase stability of local structure at near-amino acid structural resolution and with no appreciable lower limit of stability. This uncovered the highly-resolved local alterations in stability which provides direct evidence of the entropic mechanism by which access to the active site is gated by the 280s loop.

Footnotes

Author contributions: M.K., V.S., S.S., N.L., F.V., N.B., L.C. and J.J.P. designed research; M.K., V.S., S.S., L.C. and J.J.P. performed research; M.K., V.S., S.S., L.C. and J.J.P. analyzed data; and M.K. and J.J.P. wrote the manuscript.
Molecular Determinants of μ-Conotoxin KIIIA Interaction with the Human Voltage-Gated Sodium Channel NaV1.7
Authors: Kimball Ian H. , Nguyen Phuong T. , Olivera Baldomero M. , Sack Jon T. , Yarov-Yarovoy Vladimir
Published: May 2019

The voltage-gated sodium (NaV) channel subtype NaV1.7 plays a critical role in pain signaling, making it an important drug target. Here we studied the molecular interactions between μ-conotoxin KIIIA (KIIIA) and the human NaV1.7 channel (hNaV1.7). We developed a structural model of hNaV1.7 using Rosetta computational modeling and performed in silico docking of KIIIA using RosettaDock to predict residues forming specific pairwise contacts between KIIIA and hNaV1.7. We experimentally validated these contacts using mutant cycle analysis. Comparison between our KIIIA-hNaV1.7 model and the cryo-EM structure of KIIIA-hNaV1.2 revealed key similarities and differences between NaVchannel subtypes with potential implications for the molecular mechanism of toxin block. The accuracy of our integrative approach, combining structural data with computational modeling, experimental validation, and molecular dynamics simulations, suggests that Rosetta structural predictions will be useful for rational design of novel biologics targeting specific NaVchannels.
USP1 deubiquitinates protein kinase Akt to inhibit PI3K-Akt-FoxO signaling
Authors: Goldbraikh Dana , Neufeld Danielle , Mutlak-Eid Yara , Lasry Inbal , Parnis Anna , Cohen Shenhav
Published: May 2019

PI3K-Akt-FoxO-mTOR signaling is the central pathway controlling growth and metabolism in all cells. Activation of this pathway requires ubiquitination of Akt prior to its activation by phosphorylation. Here, we found that the deubiquitinating (DUB) enzyme USP1 removes K63-linked polyubiquitin chains on Akt to sustain PI3K-Akt-FoxO signaling low during prolonged starvation. DUB screening platform identified USP1 as a direct DUB for Akt, and USP1 depletion in atrophying muscle increased Akt ubiquitination, PI3K-Akt-FoxO signaling, and glucose uptake during fasting. Co-immunoprecipitation and mass spectrometry identified Disabled-2 (Dab2) and the tuberous sclerosis complex TSC1/TSC2 as USP1 bound proteins. During starvation, Dab2 was essential for Akt recruitment to USP1/UAF1 complex, and for PI3K-Akt-FoxO inhibition. Additionally, to maintain its own protein levels high, USP1 limits TSC1 levels to sustain mTOR-mediated basal protein synthesis rates. This USP1-mediated suppression of PI3K-Akt-FoxO signaling probably contributes to insulin resistance in catabolic diseases and perhaps to malignancies seen with USP1 mutations.
TNAP limits TGF-β-dependent cardiac and skeletal muscle fibrosis by inactivating SMAD2/3 transcription factors
Authors: Arnò Benedetta , Galli Francesco , Roostalu Urmas , Aldeiri Bashar , Miyake Tetsuaki , Albertini Alessandra , Bragg Laricia , Prehar Sukhpal , McDermott John C. , Cartwright Elizabeth J. , Cossu Giulio
Published: May 2019

Fibrosis is associated with almost all forms of chronic cardiac and skeletal muscle diseases. The accumulation of extracellular matrix impairs the contractility of muscle cells contributing to organ failure. Transforming growth factor beta (TGF-β) plays a pivotal role in fibrosis, activating pro-fibrotic gene programs via phosphorylation of SMAD2/3 transcription factors. However, the mechanisms that control de-phosphorylation of SMAD2/3 have remained poorly characterized. Here we show that tissue non-specific alkaline phosphatase (TNAP) is highly upregulated in hypertrophic hearts and in dystrophic skeletal muscles, and the abrogation of TGF-β signalling in TNAP positive cells reduces vascular and interstitial fibrosis. We show that TNAP co-localizes and interacts with SMAD2. TNAP inhibitor MLS-0038949 increases SMAD2/3 phosphorylation, while TNAP overexpression reduces SMAD2/3 phosphorylation and the expression of downstream fibrotic genes. Overall our data demonstrate that TNAP negatively regulates TGF-β signalling and likely represents a mechanism to limit fibrosis.

Summary statement

This paper shows that tissue non-specific alkaline phosphatase negatively regulates TGF-β signalling and may represent a mechanism to limit fibrosis through SMAD dephosphorylation.
Stochastic semi-supervised learning to prioritise genes from high-throughput genomic screens
Authors: Vitsios Dimitrios , Petrovski Slavé
Published: May 2019

Access to large-scale genomics datasets has increased the utility of hypothesis-free genome-wide analyses that result in candidate lists of genes. Often these analyses highlight several gene signals that might contribute to pathogenesis but are insufficiently powered to reach experiment-wide significance. This often triggers a process of laborious evaluation of highly-ranked genes through manual inspection of various public knowledge resources to triage those considered sufficiently interesting for deeper investigation. Here, we introduce a novel multi-dimensional, multi-step machine learning framework to objectively and more holistically assess biological relevance of genes to disease studies, by relying on a plethora of gene-associated annotations. We developed mantis-ml to serve as an automated machine learning (AutoML) framework, following a stochastic semi-supervised learning approach to rank known and novel disease-associated genes through iterative training and prediction sessions of random balanced datasets across the protein-coding exome (n=18,626 genes). We applied this framework on a range of disease-specific areas and as a generic disease likelihood estimator, achieving an average Area Under Curve (AUC) prediction performance of 0.85. Critically, to demonstrate applied utility on exome-wide association studies, we overlapped mantis-ml disease-specific predictions with data from published cohort-level association studies. We retrieved statistically significant enrichment of high mantis-ml predictions among the top-ranked genes from hypothesis-free cohort-level statistics (p<0.05), suggesting the capture of true prioritisation signals. We believe that mantis-ml is a novel easy-to-use tool to support objectively triaging gene discovery and overall enhancing our understanding of complex genotype-phenotype associations.
Chemical-state-dependent free energy profile from single-molecule trajectories of biomolecular motor: Application to processive chitinase
Authors: Okazaki Kei-ichi , Nakamura Akihiko , Iino Ryota
Published: May 2019

The mechanism of biomolecular motors has been elucidated using single-molecule experiments for visualizing motor motion. However, it remains elusive that how changes in the chemical state during the catalytic cycle of motors lead to unidirectional motions. In this study, we use singlemolecule trajectories to estimate an underlying diffusion model with chemical-state-dependent free energy profile. To consider nonequilibrium trajectories driven by the chemical energy consumed by biomolecular motors, we develop a novel framework based on a hidden Markov model, wherein switching among multiple energy profiles occurs reflecting the chemical state changes in motors. The method is tested using simulation trajectories and applied to singlemolecule trajectories of processive chitinase, a linear motor that is driven by the hydrolysis energy of a single chitin chain. The chemical-state-dependent free energy profile underlying the burnt- bridge Brownian ratchet mechanism of processive chitinase is determined. The novel framework allows us to connect the chemical state changes to the unidirectional motion of biomolecular motors.