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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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.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

Testing the unitary theory of language lateralisation using functional transcranial Doppler sonography study in adults

Cerebral lateralisation for language can vary from task to task, but it is unclear if this reflects error of measurement or independent lateralisation of different language systems. We used functional transcranial Doppler sonography to assess language lateralisation in 37 adults (7 left-handers) on six tasks, each given on two occasions. Tasks taxed different aspects of language function. A preregistered structural equation analysis was used to compare models of means and covariances. For most people, a single lateralised factor explained most of the covariance between tasks. A minority, however, showed dissociation of asymmetry, giving a second factor. This was mostly derived from a receptive task, which was highly reliable but not lateralised. The results suggest that variation in strength of language lateralisation reflects true individual differences and not just error of measurement. Inclusion of several tasks in a laterality battery makes it easier to detect cases of atypical asymmetry.

neuroscience↗

bioRxiv2018

Selene: a PyTorch-based deep learning library for sequence-level data

To enable the application of deep learning in biology, we present Selene (https://selene.flatironinstitute.org/), a PyTorch-based deep learning library for fast and easy development, training, and application of deep learning model architectures for any biological sequences. We demonstrate how Selene allows researchers to easily train a published architecture on new data, develop and evaluate a new architecture, and use a trained model to answer biological questions of interest.

bioinformatics↗

bioRxiv2018

DIAlign provides precise retention time alignment across distant runs in DIA and targeted proteomics

SWATH-MS has been widely used for proteomics analysis given its high-throughput and reproducibility but ensuring consistent quantification of analytes across large-scale studies of heterogeneous samples such as human-plasma remains challenging. Heterogeneity in large-scale studies can be caused by large time intervals between data-acquisition, acquisition by different operators or instruments, intermittent repair or replacement of parts, such as the liquid chromatography column, all of which affect retention time (RT) reproducibility and successively performance of SWATH-MS data analysis. Here, we present a novel algorithm for retention time alignment of SWATH-MS data based on direct alignment of raw MS2 chromatograms using a hybrid dynamic programming approach. The algorithm does not impose a chronological order of elution and allows for alignment of elution-order swapped peaks. Furthermore, allowing RT-mapping in a certain window around coarse global fit makes it robust against noise. On a manually validated dataset, this strategy outperforms the current state-of-the-art approaches. In addition, on a real-world clinical data, our approach outperforms global alignment methods by mapping 98% of peaks compared to 67% cumulatively and DIAlignR can reduce alignment error up to 30-fold for extremely distant runs. The robustness of technical parameters used in this pairwise alignment strategy has also been demonstrated. The source code is released under the BSD license at https://github.com/Roestlab/DIAlignR.\n\nAbbreviations\n\nData AvailabilityRaw chromatograms and features extracted by OpenSWATH are available on PeptideAtlas.\n\nServername: ftp.peptideatlas.org\n\nUsername: PASS01280\n\nPassword: KQ2592b

bioinformatics↗

bioRxiv2018

Multi-dimensional spectral gap optimization of order parameters (SGOOP) through conditional probability factorization

Spectral gap optimization of order parameters (SGOOP) (Tiwary and Berne, Proc. Natl. Acad. Sci. 113 2839 (2016)) is a method for constructing the reaction coordinate (RC) in molecular systems, especially when they are plagued with hard to sample rare events, given a larger dictionary of order parameters or basis functions, and limited static and dynamic information about the system. In its original formulation, SGOOP is designed to construct a 1-dimensional RC. Here we extend its scope by introducing a simple but powerful extension based on the notion of conditional probability factorization where known features are washed out to learn additional and possibly hidden features of the energy landscape. We show how SGOOP can be used to proceed in a sequential and bottom-up manner to (i) systematically probe the need for extending the dimensionality of the RC, and (ii) if such a need is identified, learn additional coordinates of the RC in a computationally efficient manner. We formulate the method and demonstrate its usefulness through three illustrative examples, including the challenging and important problem of calculating the kinetics of benzene unbinding from the protein T4L99A lysozyme, where we obtain excellent agreement in terms of dissociation pathway and kinetics with other sampling methods and experiments. In this last case, starting from a larger dictionary of fairly generic and arbitrarily chosen 11 order parameters, we demonstrate how to automatically learn a 2-dimensional RC, which we then use in the infrequent metadynamics protocol to obtain 16 independent unbinding trajectories. We believe our method will be a big step in increasing the usefulness of SGOOP in performing intuition-free sampling of complex systems. Finally, we believe that the usefulness of our protocol is amplified by its applicability to not just SGOOP but also other generic methods for constructing the RC.

biophysics↗

bioRxiv2018

Whole genome sequencing enables definitive diagnosis of Cystic Fibrosis and Primary Ciliary Dyskinesia

Understanding the genomic basis of inherited respiratory disorders can assist in the clinical management of individuals with these rare disorders. We apply whole genome sequencing for the discovery of disease-causing variants in the non-coding regions of known disease genes for two individuals with inherited respiratory disorders. We describe analysis strategies to pinpoint candidate non-coding variants within the non-coding genome and demonstrate aberrant RNA splicing as a result of deep intronic variants in DNAH11 and CFTR. These findings confirm clinical diagnoses of primary ciliary dyskinesia and cystic fibrosis, respectively.

genomics↗

bioRxiv2018

Impaired development of neocortical circuits contributes to the neurological alterations in DYRK1A haploinsufficiency syndrome

Autism spectrum disorders are early onset neurodevelopmental disorders characterized by deficits in social communication and restricted repetitive behaviors, yet they are quite heterogeneous in terms of their genetic basis and phenotypic manifestations. Recently, de novo pathogenic mutations in DYRK1A, a chromosome 21 gene associated to neuropathological traits of Down syndrome, have been identified in patients presenting a recognizable syndrome included in the autism spectrum. These mutations produce DYRK1A kinases with partial or complete absence of the catalytic domain, or they represent missense mutations located within this domain. Here, we undertook an extensive biochemical characterization of the DYRK1A missense mutations reported to date and show that most of them, but not all, result in enzymatically dead DYRK1A proteins. We also show that haploinsufficient Dyrk1a+/- mutant mice mirror the neurological traits associated with the human pathology, such as defective social interactions, stereotypic behaviors and epileptic activity. These mutant mice present altered proportions of excitatory and inhibitory neocortical neurons and synapses. Moreover, we provide evidence that alterations in the production of cortical excitatory neurons are contributing to these defects. Indeed, by the end of the neurogenic period, the expression of developmental regulated genes involved in neuron differentiation and/or activity is altered. Therefore, our data indicate that altered neocortical neurogenesis could critically affect the formation of cortical circuits, thereby contributing to the neuropathological changes in DYRK1A haploinsufficiency syndrome.

neuroscience↗

bioRxiv2018

A family of transcription factors that limit lifespan: ETS factors have conserved roles in longevity

Increasing average population age, and the accompanying burden of ill health, is one of the public health crises of our time. Understanding the basic biology of the ageing process may help ameliorate the pathologies that characterise old age. Ageing can be modulated, often through changes in gene expression where regulation of transcription plays a pivotal role. Activities of Forkhead transcription factors (TFs) are known to extend lifespan, but detailed knowledge of the broader transcriptional networks that promote longevity is lacking. This study focuses on the E twenty-six (ETS) family of TFs. This family of TFs is large, conserved across metazoa, and known to play roles in development and cancer, but the role of its members in ageing has not been studied extensively. In Drosophila, an ETS transcriptional repressor, Aop, and an ETS transcriptional activator, Pnt, are known to genetically interact with Foxo and activating Aop is sufficient to extend lifespan. Here, it is shown that Aop and Foxo effect a related gene-expression programme. Additionally, Aop can modulate Foxos transcriptional output to moderate or synergise with Foxo activity depending on promoter context, both in vitro and in vivo. In vivo genome-wide mRNA expression analysis in response to Aop, Pnt or Foxo indicated, and further experiments confirmed, that combinatorial activities of the three TFs dictate metabolic status, and that direct reduction of Pnt activity is sufficient to promote longevity. The role of ETS factors in longevity was not limited to Pnt and Aop. Knockdown of Ets21c or Eip74EF in distinct cell types also extended lifespan, revealing that lifespan is limited by transcription from the ETS binding site in multiple cellular contexts. Reducing the activity of the C. elegans ETS TF Lin-1 also extended lifespan, a finding that corroborates established evidence of roles of this TF family in ageing. Altogether, these results reveal the ETS family of TFs as pervasive and evolutionarily conserved brokers of longevity.

genetics↗

bioRxiv2018

Interactions between N-terminal modules in MPS1 enable spindle checkpoint silencing

AO_SCPCAPBSTRACTC_SCPCAPFaithful chromosome segregation relies on the ability of the spindle assembly checkpoint (SAC) to delay anaphase onset until all chromosomes are attached to the mitotic spindle via their kinetochores. MPS1 kinase is recruited to unattached kinetochores to initiate SAC signaling, and is removed from kinetochores once stable microtubule attachments have been formed to allow normal mitotic progression. Here we show that a helical fragment within the kinetochore-targeting NTE module of MPS1 is required for interactions with kinetochores, and also forms intramolecular interactions with its adjacent TPR domain. Bypassing this NTE-TPR interaction results in high MPS1 levels at kinetochores due to loss of regulatory input into MPS1 localization, ineffecient MPS1 delocalization from kinetochores upon microtubule attachment, and SAC silencing defects. These results show that SAC responsiveness to attachments relies on regulated intramolecular interactions in MPS1 and highlight the sensitivity of mitosis to perturbations in the dynamics of the MSP1-NDC80-C interactions.

cell biology↗

bioRxiv2018

Individual variability in behavior and functional networks predicts vulnerability using a predator scent model of PTSD

Only a minority of individuals who experience traumatic event(s) subsequently develop post-traumatic stress disorder (PTSD). However, whether differences in vulnerability to PTSD result from predisposition or a consequence of trauma exposure remains unclear. A major challenge in differentiating these possibilities is that clinical studies focus on individuals already exposed to traumatic experiences, and do not take into account pre-trauma conditions. Here using the predator scent model of PTSD in rats and a longitudinal design, we measured pre-trauma brain-wide neural circuit functional connectivity (FC), behavioral and corticosterone responses to trauma exposure, and post-trauma anxiety. Individual differences in freezing responses to predator scent exposure correlated with differences in pre-trauma FC in a set of neural circuits, especially in olfactory and stress-related systems, indicating that pre-existing function in these circuits could predispose animals to differential fearful responses to threats. Counterintuitively, rats with the lowest freezing showed more avoidance of the predator scent, a prolonged corticosterone response, and higher anxiety long after exposure. This study provides a comprehensive framework of pre-existing circuit function that determines threat response strategy, which might be directly related to the development of PTSD-like behaviors.

neuroscience↗

bioRxiv2018

Modular modeling improves the predictions of genetic variant effects on splicing

Predicting the effects of genetic variants on splicing is highly relevant for human genetics. We describe the framework MMSplice (modular modeling of splicing) with which we built the winning model of the CAGI 2018 exon skipping prediction challenge. The MMSplice modules are neural networks scoring exon, intron, and splice sites, trained on distinct large-scale genomics datasets. These modules are combined to predict effects of variants on exon skipping, alternative donor and acceptor sites, splicing efficiency, and pathogenicity, with matched or higher performance than state-of-the-art. Our models, available in the repository Kipoi, apply to variants including indels directly from VCF files.

genomics↗

bioRxiv2018

Altered orbitofrontal sulcogyral patterns in gambling disorder: a multicenter study

Gambling disorder is a serious psychiatric condition characterized by decision-making and reward processing impairments that are associated with dysfunctional brain activity in the orbitofrontal cortex (OFC). However, it remains unclear whether OFC functional abnormalities in gambling disorder are accompanied by structural abnormalities. We addressed this question by examining the organization of sulci and gyri in the OFC. This organization is in place very early and stable across life, such that OFC sulcogyral patterns (classified into Type I, II and III) can be regarded as potential pre-morbid markers of pathological conditions. We gathered structural brain data from nine existing studies, reaching a total of 165 individuals with gambling disorder and 159 healthy controls. Our results, supported by both frequentist and Bayesian statistics, show that the distribution of OFC sulcogyral patterns is skewed in individuals with gambling disorder, with an increased prevalence of Type II pattern compared with healthy controls. Examination of gambling severity did not reveal any significant relationship between OFC sulcogyral patterns and disease severity. Altogether, our results provide evidence for a skewed distribution of OFC sulcogyral patterns in gambling disorder, and suggest that pattern Type II might represent a pre-morbid structural brain marker of the disease. It will be important to investigate more closely the functional implications of these structural abnormalities in future work.

neuroscience↗

bioRxiv2018

Association of the types of alcoholic beverages and blood lipids in a local population in Jharkhand, India

Although light-to-moderate alcohol consumption is considered beneficial, alcohol in binge doses or high cumulative lifetime consumption leads to cardiovascular diseases, metabolic syndrome and structural damage to various organs. Alcohol is known to alter blood lipid concentrations; however, the association of the types of alcohol on the lipid profile has not been investigated extensively. A cross-sectional study involving male participants (n = 86) aged 20 to 60 from the Ranchi and Dhanbad zone of Jharkhand, India, was carried out to investigate the effects of cumulative lifetime consumption of Haria, a local rice-based fermented alcohol, Indian made foreign liquor (IMFL), and a combination of the two on the blood lipid profiles. Demographic characteristics, dietary intake and medical history were obtained from the participants by questionnaire, and lipid levels were determined by analysis of blood samples. The effect of Haria alone on the blood lipids was also investigated on the local female population (n = 31). After adjusting for demographic and dietary factors, IMFL and combination of IMFL and Haria consumption was associated with increased serum total cholesterol, triglyceride, and low density lipoprotein (LDL) cholesterol levels (P < 0.05) and decreased high density lipoprotein (HDL) cholesterol levels (P < 0.05). None of the blood lipids changed significantly in Haria consumers in both male and female groups. This study suggests that Haria, a popular alcoholic beverage of West Bengal and east-central India, is a relatively safe local alcoholic beverage and does not alter the lipid profile in consumers.

biochemistry↗

bioRxiv2018

Non-linear changes in modelled terrestrial ecosystems subjected to perturbations

When perturbed ecosystems undergo rapid and non-linear changes, this can result in regime shifts to an entirely different ecological state. The need to understand the extent, nature, magnitude and reversibility of these changes is urgent given the profound effects that humans are having on the natural world. It remains very challenging to empirically document non-linear changes and regime shifts within complex, real ecological communities, or even to demonstrate such shifts in simplified experimental systems. General ecosystem models, which simulate the dynamics of entire ecological communities based on a mechanistic representation of ecological processes, provide an alternative and novel way to project ecosystem changes across all scales and trophic levels and to forecast impact thresholds beyond which dramatic or irreversible changes may occur. We model non-linear changes in four terrestrial biomes subjected to human removal of plant biomass, such as occurs through agricultural land-use change. We find that irreversible and non-linear responses are predicted to be common where removal of vegetation exceeds 80% (a level that occurs across nearly 10% of the terrestrial surface), especially for organisms at higher trophic levels and in less productive ecosystems such as drylands. Very large, irreversible changes to the entire ecosystem structure are expected at levels of vegetation removal akin to those in the most intensively used real-world ecosystems. Our results suggest that the projected 21st century rapid increases in agricultural land conversion to feed an expanding human population, may lead to widespread trophic cascades and in some cases irreversible changes to the structure of ecological communities.

ecology↗

bioRxiv2018

Genomic knockout of alms1 in zebrafish recapitulates Alstrom syndrome and provides insight into metabolic phenotypes

SCIENTIFIC ABSTRACTAlstrom syndrome is an autosomal recessive obesity ciliopathy caused by loss-of-function mutations in the ALMS1 gene. In addition to multi-organ dysfunction, such as cardiomyopathy, retinal degeneration, and renal dysfunction, the disorder is characterized by high rates of obesity, insulin resistance and early onset type 2 diabetes mellitus (T2DM). To investigate mechanisms linking disease phenotypes we generated a loss-of-function deletion of alms1 in the zebrafish using CRISPR/Cas9. We demonstrate conserved phenotypic effects including cardiac defects, retinal degeneration, and metabolic deficits that included propensity for obesity and fatty livers in addition to hyperinsulinemia and glucose response defects. Gene expression changes in {beta}-cells isolated from alms1-/- mutants revealed changes consistent with insulin hyper-secretion and glucose sensing failure, which were also identified in cultured murine {beta}-cells lacking Alms1. These data present a zebrafish model to assess etiology and new secretory pathway defects underlying Alstrom syndrome-associated metabolic phenotypes. Given the hyperinsulinemia and reduced glucose sensitivity in these animals we also propose the alms1 loss-of-function mutant as a monogenic model for studying T2DM phenotypes.\n\nAUTHOR SUMMARYThese data comprise a thorough characterization of a zebrafish model of Alstrom syndrome, a human obesity syndrome caused by loss-of-function deletions in a single gene, ALMS1. The high rates of obesity and insulin resistance found in these patients suggest this disorder as a single-gene model for Type 2 Diabetes Mellitus (T2DM), a disorder caused by a variety of environmental and genetic factors in the general population. We identify a propensity for obesity, excess lipid storage, loss of {beta}-cells in islets, and hyperinsulinemia in larval and adult stages of zebrafish alms1 mutants. We isolated {beta}-cells from the alms1 mutants and compared the gene expression profiles from RNASeq datasets to identify molecular pathways that may contribute to the loss of {beta}-cells and hyperinsulinemia. The increase in genes implicated in generalized pancreatic secretion, insulin secretion, and glucose transport suggest potential {beta}-cell exhaustion as a source of {beta}-cell loss and excess larval insulin. We propose this mutant as a new genetic tool for understanding the metabolic failures found in Type 2 Diabetes Mellitus.

genetics↗

bioRxiv2018

Single cell variations in expression of codominant alleles A and B on RBC of AB blood group individuals

One of the key questions in biology is whether all cells of a "cell type" have more or less the same phenotype, especially with relation to non-imprinted autosomal loci. Recent studies point to differential allelic expression of autosomal genes being a prevalent phenomenon responsible to confer phenotypic variability at individual cell level. However, most studies have been carried out in actively transcribing cells. Here we display cellular mosaicism arising from differential allelic expression for the cell surface glycoprotein in the enucleated RBCs. We studied the expression of the A and B histo-blood group antigens encoded by the co-dominant alleles in individual RBCs using immunofluorescence. We assessed the relative levels of the co-dominant alleles IA and IB in 2512 RBC from 24 individuals with AB blood group using Cy3- and FITC- tagged antibodies. Quantification of individual fluorescence intensities from each cell and test of their normal distribution revealed that contrary to the general belief that all RBC in AB individuals express both antigens in comparable amounts, they segregated into 4 groups: showing normal distribution for both antigens, either antigen, and neither antigen; the deviation from normal distribution could not be correlated to maternal/paternal origin, thus appear to be stochastic. Surprisingly, very few people showed any correlation between the amounts of these two antigens on RBC. In fact, the ratio of antigen A to B in the entire set of samples spanned over 5 orders of magnitude. This variability in amount of the antigens A and/or B, combined with a lack of correlation between the amounts of these two antigens resulted in unique staining patterns for RBC, generating widespread mosaicism in the RBC population of AB blood group individuals.

genetics↗

bioRxiv2018

Chronic, Low-Level Oral Exposure to Marine Toxin, Domoic Acid, Alters Whole Brain Morphometry in Nonhuman Primates

Domoic acid (DA) is an excitatory neurotoxin produced by marine algae and responsible for Amnesiac Shellfish Poisoning in humans. Current regulatory limits (~0.075-0.1 mg/kg/day) protect against acute toxicity, but recent studies suggest that the chronic consumption of DA below the regulatory limit may produce subtle neurotoxicity in adults, including decrements in memory. As DA-algal blooms are increasing in both severity and frequency, we sought to better understand the effects of chronic DA exposure on reproductive and neurobehavioral endpoints in a preclinical nonhuman primate model. To this end, we initiated a long-term study using adult, female Macaca fascicularis monkeys exposed to daily, oral doses of 0.075 or 0.15 mg/kg of DA for a range of 321-381, and 346-554 days, respectively. This time period included a pre-pregnancy, pregnancy, and postpartum period. Throughout these times, trained data collectors observed intentional tremors in some exposed animals during biweekly clinical examinations. The present study explores the basis of this neurobehavioral finding with in vivo imaging techniques, including diffusion tensor magnetic resonance imaging and spectroscopy. Diffusion tensor analyses revealed that, while DA exposed macaques did not significantly differ from controls, increases in DA-related tremors were negatively correlated with fractional anisotropy, a measure of structural integrity, in the internal capsule, fornix, pons, and corpus callosum. Brain concentrations of lactate, a neurochemical closely linked with astrocytes, were also weakly, but positively associated with tremors. These findings are the first documented results suggesting that chronic oral exposure to DA at concentrations near the current human regulatory limit are related to structural and chemical changes in the adult primate brain.

pharmacology and toxicology↗

bioRxiv2018

Anemia Diagnosis on a Simple Paper-based Assay

In developing countries, the maternal and neonatal mortality rate is often affected by prenatal period anemia, a preventable and ubiquitous impairment attributed due to low hemoglobin (Hgb) concentration. We report the development of a simple, frugal (~ 0.02 $ per test), rapid and high fidelity paper-based colorimetric microfluidic device for point-of-care (POC) detection of anemia. We validate our findings with 32 blood samples collected from different patients covering a wide spectrum of anemia and subsequently, compare with standard pathological results measured using a hematology analyzer. POC based Hgb estimates are correlated with the pathological gold standard estimates of Hgb levels (r = 0.909), and the POC test method yielded similar sensitivity and specificity for detecting mild anemia (n = 8) (<11 g/dl) (sensitivity: 87.5%, specificity: 100 %) and for severe anemia (n = 3) (<7 g/dl) (sensitivity: 100 %, specificity: 100 %). The estimated Hgb levels are, within 1.5 g/dl from the pathological estimate, for 91 % of the blood samples. Results demonstrate the elevated efficacy and viability of this POC colorimetric diagnostic test, in comparison to the state-of-the-art complex and expensive diagnostic tests for anemia detection.

bioengineering↗

bioRxiv2018

Cellular determinants of metabolite concentration ranges

Cellular functions are shaped by reaction networks whose dynamics are determined by the concentrations of underlying components. However, cellular mechanisms ensuring that a components concentration resides in a given range remain elusive. We present network properties which suffice to identify components whose concentration ranges can be efficiently computed in mass-action metabolic networks. We show that the derived ranges are in excellent agreement with simulations from a detailed kinetic metabolic model of Escherichia coli. We demonstrate that the approach can be used with genome-scale metabolic models to arrive at predictions concordant with measurements from Escherichia coli under different growth scenarios. By application to 14 genome-scale metabolic models from diverse species, our approach specifies the cellular determinants of concentration ranges that can be effectively employed to make predictions for a variety of biotechnological and medical applications.\n\nAuthor SummaryWe present a computational approach for inferring concentration ranges from genome-scale metabolic models. The approach specifies a determinant and molecular mechanism underling facile control of concentration ranges for components in large-scale cellular networks. Most importantly, the predictions about concentration ranges do not require knowledge of kinetic parameters (which are difficult to specify at a genome scale), provided measurements of concentrations in a reference state. The approach assumes that reaction rates follow the mass action law used in the derivations of other types of kinetics. We apply the approach with large-scale kinetic and stoichiometric metabolic models of organisms from different kingdoms of life to show that we can identify a proportion of metabolites to which our approach is applicable. By challenging the predictions of concentration ranges in the genome-scale metabolic network of E. coli with real-world data sets, we further demonstrate the prediction power and limitations of the approach.

bioinformatics↗