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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2018

Spectral and topological analysis of the cortical representation of the head position: does hypnotizability matter?

The aim of the study was to assess the EEG correlates of head positions, which have never been studied in humans, in participants with different psychophysiological characteristics, as encoded by their hypnotizability scores. This choice is motivated by earlier studies suggesting different processing of the vestibular/neck proprioceptive information in subjects with high (highs) and low (lows) hypnotizability scores maintaining their head rotated toward one side (RH). We analysed EEG signals recorded in 20 highs and 19 lows in basal conditions (head forward) and during RH, using spectral analysis, which captures changes localized to specific recording sites, and Topological Data Analysis (TDA), which instead describes large-scale differences in processing and representing sensorimotor information. Spectral analysis revealed significant differences related to the head position for alpha1, beta2, beta3, gamma bands, but not to hypnotizability. TDA instead revealed global hypnotizability-related differences in the strengths of the correlations among recording sites during RH. Significant changes were observed in lows on the left parieto-occipital side and in highs in right fronto-parietal region. Significant differences between the two groups were found in the occipital region, where changes were larger in lows than in highs. The study reports findings of the EEG correlates of the head posture for the first time, indicates that hypnotizability modulates its representation/processing on large-scale and that spectral and topological data analysis provide complementary results.

neuroscience↗

bioRxiv2018

Reactive SINDy: Discovering governing reactions from concentration data

The inner workings of a biological cell or a chemical reaction can be rationalized by the network of reactions, whose structure reveals the most important functional mechanisms. For complex systems, these reaction networks are not known a priori and cannot be efficiently computed with ab initio methods, therefore an important approach goal is to estimate effective reaction networks from observations, such as time series of the main species. Reaction networks estimated with standard machine learning techniques such as least-squares regression may fit the observations, but will typically contain spurious reactions. Here we extend the sparse identification of nonlinear dynamics (SINDy) method to vector-valued ansatz functions, each describing a particular reaction process. The resulting sparse tensor regression method \"reactive SINDy\" is able to estimate a parsimonious reaction network. We illustrate that a gene regulation network can be correctly estimated from observed time series.

biochemistry↗

bioRxiv2018

Word stress representations are language specific: evidence from event-related brain potentials

Understanding speech at the basic levels entails the simultaneous and independent processing of phonemic and prosodic features. While it is well-established that phoneme perception relies on language-specific long-term traces, it is unclear if the processing of prosodic features similarly involves language-specific representations. In the present study, we investigated the processing of a specific prosodic feature, word stress, using the method of event-related brain potentials (ERPs) employing a cross-linguistic approach. Hungarian participants heard disyllabic pseudowords stressed either on the first (legal stress) or on the second (illegal stress) syllable, pronounced either by a Hungarian or a German speaker. Results obtained using a data-driven ERP analysis methodology showed that all pseudowords in the deviant position elicited an Early Differentiating Negativity (EDN) and a Mismatch Negativity (MMN) component, except for the Hungarian pseudowords stressed on the first syllable. This suggests that Hungarian listeners did not process the native legal stress pattern as deviant, but the same stress pattern with a non-native accent was processed as deviant. This implies that the processing of word stress was based on language-specific long-term memory traces.

neuroscience↗

bioRxiv2018

Combining transcriptomic and fitness data reveals adaptive and additive plastic responses of gene expression to multiple stressors in Tribolium castaneum.

Gene expression is known to be highly responsive to the environment and to vary between species or populations under divergent selection. Yet, its contribution to the process of adaption is still controversial despite growing evidence that differences in gene regulation contribute to adaptive divergence. While most studies so far investigated evolved plasticity in already diverged populations, phenotypic selection acting on gene expression at the onset of adaptation to an environmental change has not been characterized. Here, we combined fitness and whole-transcriptome data in a large-scale experiment with Tribolium castaneum to investigate gene expression and fitness responses to drought, heat and their combination. Fitness was reduced by both stressors and their combined effects were nearly additive. Accordingly, expression data showed that both stressors were acting independently and did not interfere physiologically. With expression and fitness within the same individuals, we estimated selection on single gene expression levels. We found that variation in fitness can be attributed to gene expression variation. Selection intensities on expression levels differed between conditions and were opposite between control and stress conditions, showing evidence of evolutionary trade-offs. Plastic expression changes were mostly adaptive when affected by heat stress, and partially non-adaptive when affected by drought.

evolutionary biology↗

bioRxiv2018

Differential immune gene expression associated with contemporary range expansion of two invasive rodents in Senegal

BackgroundBiological invasions are major anthropogenic changes associated with threats to biodiversity and health. What determines the successful establishment of introduced populations still remains unsolved. Here we explore the appealing assertion that invasion success relies on immune phenotypic traits that would be advantageous in recently invaded sites. ResultsWe compared gene expression profiles between anciently and recently established populations of two major invading species, the house mouse Mus musculus domesticus and the black rat Rattus rattus, in Senegal. Transcriptome analyses revealed respectively 364 and 83 differentially expressed genes along the mouse and rat invasion routes. Among them, 20.0% and 10.6% were annotated with functions related to immunity. All immune-related genes detected along the mouse invasion route were over-expressed in recently invaded sites. Genes of the complement activation pathway were over-represented. Results were less straightforward when considering the black rat as no particular immunological process was over-represented. ConclusionsWe revealed changes in transcriptome profiles along invasion routes. Patterns differed between both invasive species. These changes potentially be driven by increased infection risks in recently invaded sites for the house mouse and stochastic events associated with colonization history for the black rat. These results provide a first step in identifying the immune ecoevolutionary processes potentially involved in invasion success.

ecology↗

bioRxiv2018

Increased Epstein-Barr virus C-promoter activity with CTCF-binding site deletion is associated with elevated EBNA2 recruitment.

The regulation of transcription from Epstein-Barr virus promoters is known to involve the association of the host CCCTC-binding factor (CTCF) protein. This control involves direct binding of CTCF across the EBV genome and the formation of three-dimensional loops between virus promoters and enhancers. We sought to address how the deletion of a CTCF binding site upstream of the C-promoter (Cp) affected viral transcription in infected lymphoblastoid cell lines (LCLs) and how binding of the EBV trans-activating protein EBNA2 was changed across this promoter. Transcript level from Cp was up-regulated with CTCF binding site deletion, and transcription from other promoters (Wp and Qp) was decreased, while transcript levels were largely unchanged by independent mutation of a Cp-RBPJ{kappa} binding site. In turn, expression of EBNA2 protein was also increased, likely driven by increases in polycistronic EBNA2-encoding transcripts. Finally, Cp up-regulation was associated with an 8-fold increase in EBNA2 enrichment across Cp, concomitant with increased association of the associated cellular factor RBPJ{kappa}, probably due to a more accessible three-dimensional chromatin conformation upstream of Cp. Overall, the data presented here confirm that binding of CTCF directly upstream of Cp is important for the regulation of transcription from this and other EBV promoters.

microbiology↗

bioRxiv2018

The Flexiscope: a Low Cost, Flexible, Convertible, and Modular Microscope with Automated Scanning and Micromanipulation.

With technologies rapidly evolving, many research institutions are now opting to invest in costly, high-quality, specialised microscopes which are shared by many researchers. As a consequence, the user may not have the ability to adapt a microscope to their specific needs and limitations in experimental design are introduced. A flexible work-horse microscopy system is a valuable tool in any laboratory to meet the diverse needs of a research team and promote innovation in experimental design. We have developed the Flexiscope; a multi-functional, adaptable, efficient and high-performance microscopy/electrophysiology system for everyday applications in a neurobiology laboratory. The core optical components are relatively constant in the three configurations described here; an upright configuration, an inverted configuration and an upright/electrophysiology configuration. We have provided a comprehensive description of the Flexiscope. We show that this method is capable of oblique infrared illumination imaging, multi-channel fluorescent imaging, and automated 3D scanning of larger specimens. Image quality is conserved across the three configurations of the microscope, and conversion between configurations is possible quickly and easily, while the motion control system can be repurposed to allow sub-micron computer-controlled micromanipulation. The Flexiscope provides similar performance and usability to commercially available systems. However, as it can be easily reconfigured for multiple roles, it can remove the need to purchase multiple microscopes, giving significant cost savings. The modular re-configurable nature allows the user to customise the system to their specific needs and adapt/upgrade the system as challenges arise, without requiring specialised technical skills.

neuroscience↗

bioRxiv2018

High Temporal Sub-millisecond Time Resolution Stimulation Increases Performances of Retina Prosthetic Vision

Vision loss has an enormous impact on affected individuals, and increasing social and economics costs for the whole of society. Important approaches have been introduced, aimed at restoring visual functionality in the case of vision degradation and loss. Currently the most promising technology is represented by retinal implants, with companies producing devices approved for commercialization. The first clinical studies encouragingly reported perception elicited by both devices. Some patients retrieve autonomy, but only a few could reach satisfactory perception levels, allowing more complex tasks such as reading. Fundamental limitations however still exist in both spatial and temporal resolution, and these limitations call for improvements of the technology and of the stimulation strategies used therein. This study focuses on the importance of temporal resolution for retinal stimulation, and how it can be used to improve restored perception for implanted patients. We show a quantification of the improvement of discrimination performance when stimulating with high frame rates compared to conventional 30-60Hz frame rates. Such effect is evaluated using data collected from implanted patients, and deriving from it a realistic phosphene model. This study allowed to accurately replicate the perceptual effects of the studied technologies, and to evaluate the hypotheses regarding performance improvements using higher temporal resolutions for stimulation strategies in visual restoration devices.

neuroscience↗

bioRxiv2018

High-resolution structural genomics reveals new therapeutic vulnerabilities in glioblastoma

We investigated the role of 3D genome architecture in instructing functional properties of glioblastoma stem cells (GSCs) by generating the highest-resolution 3D genome maps to-date for this cancer. Integration of DNA contact maps with chromatin and transcriptional profiles identified specific mechanisms of gene regulation, including individual physical interactions between regulatory regions and their target genes. Residing in structurally conserved regions in GSCs was CD276, a gene known to play a role in immuno-modulation. We show that, unexpectedly, CD276 is part of a stemness network in GSCs and can be targeted with an antibody-drug conjugate to curb self-renewal, a key stemness property. Our results demonstrate that integrated structural genomics datasets can be employed to rationally identify therapeutic vulnerabilities in self-renewing cells.\n\nSIGNIFICANCEIn adult GBM, GSCs act as therapy-resistant reservoirs to nucleate tumor recurrence. New therapeutic approaches that target these cell populations hold the potential of significantly improving patient care and overall prognosis for this always-lethal cancer. Our work describes new links between 3D genome architecture and stemness properties in GSCs. In particular, through integration of multiple genomics and structural genomics datasets, we found an unexpected connection between immune-related genes and self-renewal programs in GBM. Among these, we show that targeting CD276 with knockdown strategies or specific antibody-drug conjugates achieve suppression of self-renewal. Strategies to target CD276+ cells are currently in clinical trials for solid tumors. Our results indicate that CD276-targeting agents could be deployed in GBM to specifically target GSC populations.\n\nHIGHLIGHTSO_LIWe generated high (sub-5 kb) resolution Hi-C maps for stem-like cells from GBM patients.\nC_LIO_LIIntegration of Hi-C and genomics datasets dissects mechanisms of gene regulation.\nC_LIO_LI3D genomes poise immune-related genes, including CD276, for expression.\nC_LIO_LITargeting CD276 curbs self-renewal properties of GBM cells.\nC_LI

cancer biology↗

bioRxiv2018

Resting-State Brain Fluctuation and Functional Connectivity Dissociate Moral Injury from Posttraumatic Stress Disorder

Moral injury is closely associated with posttraumatic stress disorder (PTSD) and is characterized by disturbances in social and moral cognition. Little is known about the neural underpinnings of moral injury, and whether the neural correlates are different between moral injury and PTSD.\n\nA sample of 26 US military veterans (2 females; 28~55 years old) were investigated to determine how moral injury experiences and PTSD symptoms are differentially related to spontaneous fluctuations indexed by low frequency fluctuation (ALFF) as well as functional connectivity during resting-state functional magnetic resonance imaging (fMRI) scanning.\n\nALFF in the left inferior parietal lobule (L IPL) was positively associated with moral injury sub-scores of transgressions, negatively associated with sub-scores of betrayals, and not related with PTSD symptoms. Moreover, functional connectivity between the L IPL and bilateral precuneus was positively related with PTSD symptoms and negatively related with moral injury total scores.\n\nOur results provide the first evidence that moral injury and PTSD have dissociable neural underpinnings, and behaviorally distinct sub-components of moral injury are different in neural responses. The findings increase our knowledge of the neural distinctions between moral injury and PTSD and may contribute to developing nosology and interventions for military veterans afflicted with moral injury.

neuroscience↗

bioRxiv2018

Indirect effects on fitness between individuals that have never met via an extended phenotype

Interactions between organisms are ubiquitous and have important consequences for phenotypes and fitness. Individuals can even influence those they never meet, if they have extended phenotypes which mean the environments others experience are altered. North American red squirrels (Tamiasciurus hudsonicus) guard food hoards, an extended phenotype that typically outlives the individual and is almost always inherited by non relatives. Hoarding by previous owners can therefore influence subsequent owners. We found that red squirrels bred earlier and had higher lifetime fitness if the previous owner was a male. This was driven by hoarding behaviour, as males and mid-aged squirrels had the largest hoards, and these effects persisted across owners, such that if the previous owner was male or died in mid-age subsequent occupants had larger hoards. Individuals can, therefore, influence each others resource dependent traits and fitness without meeting via extended phenotypes, and so the past can influence contemporary population dynamics.

ecology↗

bioRxiv2018

Alpha-band oscillations reflect external spatial coding for tactile stimuli in sighted, but not in congenitally blind humans

We investigated the function of oscillatory alpha-band activity in the neural coding of spatial information during tactile processing. Sighted humans concurrently encode tactile location in skin-based and, after integration with posture, external spatial reference frames, whereas congenitally blind humans preferably use skin-based coding. Accordingly, lateralization of alpha-band activity in parietal regions during attentional orienting in expectance of tactile stimulation reflected external spatial coding in sighted, but skin-based coding in blind humans. Here, we asked whether alpha-band activity plays a similar role in spatial coding for tactile processing, that is, after the stimulus has been received. Sighted and congenitally blind participants were cued to attend to one hand in order to detect rare tactile deviant stimuli at this hand while ignoring tactile deviants at the other hand and tactile standard stimuli at both hands. The reference frames encoded by oscillatory activity during tactile processing were probed by adopting either an uncrossed or crossed hand posture. In sighted participants, attended relative to unattended standard stimuli suppressed the power in the alpha-band over ipsilateral centro-parietal and occipital cortex. Hand crossing attenuated this attentional modulation predominantly over ipsilateral posterior-parietal cortex. In contrast, although contralateral alpha-activity was enhanced for attended versus unattended stimuli in blind participants, no crossing effects were evident in the oscillatory activity of this group. These findings suggest that oscillatory alpha-band activity plays a pivotal role in the neural coding of external spatial information for touch.

neuroscience↗

bioRxiv2018

Variational Infinite Heterogeneous Mixture Model for Semi-supervised Clustering of Heart Enhancers

MotivationPMammalian genomes can contain thousands of enhancers but only a subset are actively driving gene expression in a given cellular context. Integrated genomic datasets can be harnessed to predict active enhancers. One challenge in integration of large genomic datasets is the increasing heterogeneity: continuous, binary and discrete features may all be relevant. Coupled with the typically small numbers of training examples, semi-supervised approaches for heterogeneous data are needed; however, current enhancer prediction methods are not designed to handle heterogeneous data in the semi-supervised paradigm.\n\nResultsWe implemented a Dirichlet Process Heterogeneous Mixture model that infers Gaussian, Bernoulli and Poisson distributions over features. We derived a novel variational inference algorithm to handle semi-supervised learning tasks where certain observations are forced to cluster together. We applied this model to enhancer candidates in mouse heart tissues based on heterogeneous features. We constrained a small number of known active enhancers to appear in the same cluster, and 47 additional regions clustered with them. Many of these are located near heart-specific genes. The model also predicted 1176 active promoters, suggesting that it can discover new enhancers and promoters.\n\nAvailabilityWe created the dphmix Python package: https://pypi.org/project/dphmix/\n\nContactalan.moses@utoronto.ca

bioinformatics↗

bioRxiv2018

A Framework for Intelligence and Cortical Function Based on Grid Cells in the Neocortex

How the neocortex works is a mystery. In this paper we propose a novel framework for understanding its function. Grid cells are neurons in the entorhinal cortex that represent the location of an animal in its environment. Recent evidence suggests that grid cell-like neurons may also be present in the neocortex. We propose that grid cells exist throughout the neocortex, in every region and in every cortical column. They define a location-based framework for how the neocortex functions. Whereas grid cells in the entorhinal cortex represent the location of one thing, the body relative to its environment, we propose that cortical grid cells simultaneously represent the location of many things. Cortical columns in somatosensory cortex track the location of tactile features relative to the object being touched and cortical columns in visual cortex track the location of visual features relative to the object being viewed. We propose that mechanisms in the entorhinal cortex and hippocampus that evolved for learning the structure of environments are now used by the neocortex to learn the structure of objects. Having a representation of location in each cortical column suggests mechanisms for how the neocortex represents object compositionality and object behaviors. It leads to the hypothesis that every part of the neocortex learns complete models of objects and that there are many models of each object distributed throughout the neocortex. The similarity of circuitry observed in all cortical regions is strong evidence that even high-level cognitive tasks are learned and represented in a location-based framework.

neuroscience↗

bioRxiv2018

Comparative Modeling of Transcranial Magnetic and Electric Stimulation in Mouse, Monkey, and Human

Transcranial magnetic stimulation (TMS) and transcranial electric stimulation (TES) are increasingly popular methods to noninvasively affect brain activity. However, their mechanism of action and dose-response characteristics remain under active investigation. Translational studies in animals play a pivotal role in these efforts due to a larger neuroscientific toolset enabled by invasive recordings. In order to translate knowledge gained in animal studies to humans, it is crucial to generate comparable stimulation conditions with respect to the induced electric field in the brain. Here, we conduct a finite element method (FEM) modeling study of TMS and TES electric fields in a mouse, capuchin monkey, and human model. We systematically evaluate the induced electric fields and analyze their relationship to head and brain anatomy. We find that with increasing head size, TMS-induced electric field strength first increases and then decreases according to a two-term exponential function. TES-induced electric field strength strongly decreases from smaller to larger specimen with up to 100x fold differences across species. Our results can serve as a basis to compare and match stimulation parameters across studies in animals and humans.\n\nHIGHLIGHTSO_LITranslational research in brain stimulation should account for large differences in induced electric fields in different organisms\nC_LIO_LIWe simulate TMS and TES electric fields using anatomically realistic finite element models in three species: mouse, monkey, and human\nC_LIO_LITMS with a 70 mm figure-8 coil creates an approximately 2-times weaker electric field in a mouse brain than in monkey and human brains, where electric field strength is comparable\nC_LIO_LITwo-electrode TES creates an approximately 100-times stronger electric field in a mouse brain and 3.5-times stronger electric field in a monkey brain than in a human brain\nC_LI

neuroscience↗

bioRxiv2018

Supply and consumption of glucose 6-phosphate in the chloroplast stroma

Fructose 6-phosphate is an intermediate in the Calvin-Benson cycle and can be acted on by phosphoglucoisomerase to make glucose 6-phosphate (G6P) for starch synthesis. A high concentration of G6P is favorable for starch synthesis but can also stimulate G6P dehydrogenase initiating the glucose-6-phosphate shunt an alternative pathway around the Calvin-Benson cycle. A low concentration of glucose 6-phosphate will limit this futile cycle. In order to understand the biochemical regulation of plastidic glucose 6-phosphate supply and consumption, we characterized biochemical parameters of two key enzymes, phosphoglucoisomerase (PGI) and G6P dehydrogenase (G6PDH). We have found that the plastidic PGI in has a higher Km for G6P compared to that for fructose 6-phosphate. The Km of G6PDH isoform 1 is increased under reducing conditions. The other two isoforms exhibit less redox regulation; isoform 2 is the most inhibited by NADPH. Our results support the conclusion that PGI restricts stromal G6P synthesis limiting futile cycling via G6PDH. It also acts like a one-way valve, allowing carbon to leave the Calvin-Benson cycle but not reenter. We found flexible redox regulation of G6PDH that could regulate the glucose-6-phosphate shunt.\n\nHighlightGlucose 6-phosphate stimulates glucose-6-phosphate dehydrogenase. This enzyme is less active during the day but retains significant activity that is very sensitive to the concentration of glucose 6-phopshate.

biochemistry↗

bioRxiv2018

Removing Confounding Factors Associated Weights in Deep Neural Networks Improves the Prediction Accuracy for Healthcare Applications

The proliferation of healthcare data has brought the opportunities of applying data-driven approaches, such as machine learning methods, to assist diagnosis. Recently, many deep learning methods have been shown with impressive successes in predicting disease status with raw input data. However, the \"black-box\" nature of deep learning and the high-reliability requirement of biomedical applications have created new challenges regarding the existence of confounding factors. In this paper, with a brief argument that inappropriate handling of confounding factors will lead to models sub-optimal performance in real-world applications, we present an efficient method that can remove the influences of confounding factors such as age or gender to improve the across-cohort prediction accuracy of neural networks. One distinct advantage of our method is that it only requires minimal changes of the baseline models architecture so that it can be plugged into most of the existing neu-ral networks. We conduct experiments across CT-scan, MRA, and EEG brain wave with convolutional neural networks and LSTM to verify the efficiency of our method.

bioinformatics↗

bioRxiv2018

The geometry of habitat fragmentation: effects of distribution patterns on short-term species persistence

Land-use changes cause habitat loss and fragmentation and are thus important drivers of anthropogenic biodiversity change. However, there is an ongoing debate about how fragmentation per se affects biodiversity in a given amount of habitat. We illustrate why it is important to distinguish two different aspects of fragmentation to resolve this debate: (i) geometric fragmentation effects, which exclusively arise from the spatial distributions of species and habitat fragments, and (ii) demographic fragmentation effects due to reduced fragment size, increased isolation, or edge effects. While most empirical studies are primarily interested in quantifying demographic fragmentation effects, geometric effects are typically invoked only as post-hoc explanations of biodiversity responses to fragmentation per se. Here, we present an approach to quantify geometric fragmentation effects on species persistence probability. We illustrate this approach using spatial simulations where we systematically varied the initial abundances and distribution patterns (i.e. random, aggregated, and regular) of species as well as habitat amount and fragmentation per se. As expected, we found no geometric fragmentation effects when species were randomly distributed. However, when species were aggregated, we found positive effects of fragmentation per se on persistence probability for a large range of scenarios. For regular species distributions, we found weakly negative geometric effects. These findings are independent of the ecological mechanisms which generate non-random species distributions. Our study helps to reconcile seemingly contradictory results of previous fragmentation studies. Since intraspecific aggregation is a ubiquitous pattern in nature, our findings imply widespread positive geometric fragmentation effects. This expectation is supported by many studies that find positive effects of fragmentation per se on species occurrences and diversity after controlling for habitat amount. We outline how to disentangle geometric and demographic effects of fragmentation, which is critical for predicting the response of biodiversity to landscape change.

ecology↗