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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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At least 271 records · Page 15Linked to original sources

bioRxiv2015

An integrated homeostatic reinforcement learning theory of motivation explains the transition to cocaine addiction

Drugs of abuse implicate both reward learning and homeostatic regulation mechanisms of the brain. Theories of addiction, thus, have mostly depicted this phenomenon as pathology in either habit-based learning system or homeostatic mechanisms. Showing the limits of those accounts, we hypothesize that compulsive drug seeking arises from drugs hijacking a system that integrates homeostatic regulation mechanism with goal-directed action/behavior. Building upon a recently developed homeostatic reinforcement learning theory, we present a computational theory proposing that cocaine reinforces goal-directed drug-seeking due to its rapid homeostatic corrective effect, whereas its chronic use induces slow and long-lasting changes in homeostatic setpoint. Our theory accounts for key behavioral and neurobiological features of addiction, most notably, escalation of cocaine use, drug-primed craving and relapse, and individual differences underlying susceptibility to addiction. The theory also generates unique predictions about the mechanisms of cocaine-intake regulation and about cocaine-primed craving and relapse that are confirmed by new experiments.\n\nSignificanceChronic use of addictive drugs renders increased motivation in planning to obtain and consume the drugs, despite their adverse social, occupational, and health consequences. It is as if addicts gradually develop a strong need for the drug and use their cognitive abilities and the knowledge of their environment in order to fulfil that need. In this paper, we build a mathematical model of this conception of addiction and show through quantitative simulations that such a model actually behaves in the same way that human addicts or laboratory animals that are exposed to cocaine behave. For example, the model shows gradually increasing motivation for drugs, relapse after long periods of abstinence, and individual differences in susceptibility to addiction.

Neuroscience↗

bioRxiv2015

Recovery of dynamics and function in spiking neural networks by closed-loop control

There is a growing interest in developing novel brain stimulation methods to control disease-related aberrant neural activity and to address basic neuroscience questions. Conventional methods for manipulating brain activity rely on open-loop approaches that usually lead to excessive stimulation and, crucially, do not restore the original computations performed by the network. Thus, they are often accompanied by undesired side-effects. Here, we introduce delayed feedback control (DFC), a conceptually simple but effective method, to control pathological oscillations in spiking neural networks. Using mathematical analysis and numerical simulations we show that DFC can restore a wide range of aberrant network dynamics either by suppressing or enhancing synchronous irregular activity. Importantly, DFC besides steering the system back to a healthy state, it also recovers the computations performed by the underlying network. Finally, using our theory we isolate the role of single neuron and synapse properties in determining the stability of the closed-loop system.

Neuroscience↗

bioRxiv2015

COGNITIVE DOMAINS FUNCTION COMPLEMENTATION BY NTNG GENE PARALOGS

Gene duplication was proposed by S.Ohno (1) as a key mechanism of a novel gene function evolution. A pair of gene paralogs, NTNG1 and NTNG2, sharing identical gene and protein structures and encoding similar proteins, forms a functional complement subfunctionalising (SF) within cognitive domains and forming cognitive endophenotypes, as detected by Intellectual Quotient (IQ) tests (2). Both NTNG paralogs are associated with autism spectrum disorder (ASD), bipolar disorder (BD) and schizophrenia (SCZ), with unique nonoverlapping segregation among the other 15 cognitive disorders (CD), emphasizing an evolutionary gain-dependent link between advanced cognitive functions and concomitant neurocognitive pathologies. Complementary expression and human brain transcriptome composition of the paralogs explains the observed phenomena of their functional complementarity. The lowest identity among NTNGs is found in a middle of encoded by them proteins designated as uknown (Ukd) domain. NTNG1 contains anthropoid-specific constrained regions, and both genes contain non-coding conserved sequences underwent accelerated evolution in human. NTNG paralogs SF perturbates \"structure drives function\" concept at protein and gene levels. The paralogs function diversification forms a so-called \"Cognitive Complement (CC)\", a product of gene duplication and subsequent cognitive subfunction bifurcation among the NTNG gene duplicates.

Genomics↗

bioRxiv2016

Mergeomics: integration of diverse genomics resources to identify pathogenic perturbations to biological systems

Mergeomics is a computational pipeline (http://mergeomics.research.idre.ucla.edu/Download/Package/) that integrates multidimensional omics-disease associations, functional genomics, canonical pathways and gene-gene interaction networks to generate mechanistic hypotheses. It first identifies biological pathways and tissue-specific gene subnetworks that are perturbed by disease-associated molecular entities. The disease-associated subnetworks are then projected onto tissue-specific gene-gene interaction networks to identify local hubs as potential key drivers of pathological perturbations. The pipeline is modular and can be applied across species and platform boundaries, and uniquely conducts pathway/network level meta-analysis of multiple genomic studies of various data types. Application of Mergeomics to cholesterol datasets revealed novel regulators of cholesterol metabolism.

Systems Biology↗

bioRxiv2016

Evidence for a probabilistic, brain-distributed, recursive mechanism for decision-making

Decision formation recruits many brain regions, but the procedure they jointly execute is unknown. Here we characterize its essential composition, using as a framework a novel recursive Bayesian algorithm that makes decisions based on spike-trains with the statistics of those in sensory cortex (MT). Using it to simulate the random-dot-motion task, we demonstrate it quantitatively replicates the choice behaviour of monkeys, whilst predicting losses of otherwise usable information from MT. Its architecture maps to the recurrent cortico-basal-ganglia-thalamo-cortical loops, whose components are all implicated in decision-making. We show that the dynamics of its mapped computations match those of neural activity in the sensorimotor cortex and striatum during decisions, and forecast those of basal ganglia output and thalamus. This also predicts which aspects of neural dynamics are and are not part of inference. Our single-equation algorithm is probabilistic, distributed, recursive, and parallel. Its success at capturing anatomy, behaviour, and electrophysiology suggests that the mechanism implemented by the brain has these same characteristics.\n\nAuthor SummaryDecision-making is central to cognition. Abnormally-formed decisions characterize disorders like over-eating, Parkinsons and Huntingtons diseases, OCD, addiction, and compulsive gambling. Yet, a unified account of decisionmaking has, hitherto, remained elusive. Here we show the essential composition of the brains decision mechanism by matching experimental data from monkeys making decisions, to the knowable function of a novel statistical inference algorithm. Our algorithm maps onto the large-scale architecture of decision circuits in the primate brain, replicating the monkeys choice behaviour and the dynamics of the neural activity that accompany it. Validated in this way, our algorithm establishes a basic framework for understanding the mechanistic ingredients of decisionmaking in the brain, and thereby, a basic platform for understanding how pathologies arise from abnormal function.

Neuroscience↗

bioRxiv2016

A Novel Multi-network Approach Reveals Tissue-specific Cellular Modulators of Fibrosis in Systemic Sclerosis, Pulmonary Fibrosis and Pulmonary Arterial Hypertension

We have used integrative genomics to determine if a common molecular mechanism underlies different clinical manifestations in systemic sclerosis (SSc), and the related conditions pulmonary fibrosis (PF) and pulmonary arterial hypertension (PAH). We identified a common pathogenic gene expression signature - an immune-fibrotic axis-indicative of pro-fibrotic macrophages in multiple affected tissues (skin, lung, esophagus and PBMCs) of SSc, PF, and PAH. We used this disease-associated signature to query tissue-specific functional genomic networks. This allowed us to identify common and tissue-specific pathology of SSc and related conditions. We rigorously contrasted the lung- and skin-specific gene-gene interaction networks to identify a distinct lung resident macrophage signature associated with lipid stimulation and alternative activation. In keeping with our network results, we find distinct macrophages alternative activation transcriptional programs in SSc-PF lung and in the skin of patients with an \"inflammatory\" SSc gene expression signature. Our results suggest that the innate immune system is central to SSc disease processes, but that subtle distinctions exist between tissues. Our approach provides a framework for examining molecular signatures of disease in fibrosis and autoimmune diseases and for leveraging publicly available data to understand common and tissue-specific disease processes in complex human diseases.

Systems Biology↗

bioRxiv2016

Bacterial sequences detected in 99 out of 99 serum samples from Ebola patients

Evolution and clinical manifestations of Ebola virus (EBOV) infection overlap with the pathologic processes that occur in sepsis1. Some viruses certainly compromise the immune system, leading to a breach in the integrity of the mucosal epithelial barrier, thus allowing bacterial translocation2, 3. Guided by these facts, we wondered if bacteria could be involved in the pathogenesis of some of the septic shock-like symptoms typical of EBOV infected patients, something that could have a dramatic impact on the design of new treatment approaches. We decided to search for bacteria in available EBOV patient sequence datasets. Given that EBOV is an RNA virus and that, hence, some NGS sequencing experiments carried out to sequence the EBOV genomes were RNA-Seq experiments, we thought that, if there were any bacteria in patient serum, at least some bacterial RNA might probably be detected in the sequenced material from Ebola patients. Thus, we searched for bacteria in a RNA-Seq public dataset from 99 Ebola samples from the last outbreak4, and surprisingly, in spite of the certainly suboptimal experimental conditions for bacterial RNA sequencing, we found bacteria in all of the 99 samples

Bioinformatics↗

bioRxiv2016

Osteosarcoma with apparent Ewing sarcoma gene rearrangement

Poorly differentiated round cell sarcomas present diagnostic challenges due to their variable morphology and lack of specific immunophenotypic markers. We present a case of a 15-year-old female with a tibial tumor that exhibited features of Ewing-like sarcoma, including apparent rearrangement of the EWSR1 gene. Hybridization capture-based next-generation DNA sequencing showed evidence of complex genomic rearrangements, absence of known pathogenic Ewing-like chromosome translocations, and deletions RB1, PTCH1, and ATRX, supporting the diagnosis of osteosarcoma. This illustrates the potential of clinical genomic profiling to improve diagnosis and enable specifically targeted therapies for cancers with complex pathologies.

Molecular Biology↗

bioRxiv2016

Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap

Recent large-scale studies have identified multiple genetic risk factors for mental illness and indicate a complex, polygenic, and pleiotropic genetic architecture for neuropsychiatric disease. However, little is known about how genetic variants yield brain dysfunction or pathology. We use transcriptomic profiling as an unbiased, quantitative readout of molecular phenotypes across 5 major psychiatric disorders, including autism (ASD), schizophrenia (SCZ), bipolar disorder (BD), depression (MDD), and alcoholism (AAD), compared with carefully matched controls. We identify a clear pattern of shared and distinct gene-expression perturbations across these conditions, identifying neuronal gene co-expression modules downregulated across ASD, SCZ, and BD, and astrocyte related modules most prominently upregulated in ASD and SCZ. Remarkably, the degree of sharing of transcriptional dysregulation was strongly related to polygenic (SNP-based) overlap across disorders, indicating a significant genetic component. These findings provide a systems-level view of the neurobiological architecture of major neuropsychiatric illness and demonstrate pathways of molecular convergence and specificity.\n\nOne Sentence SummaryAutism, schizophrenia, and bipolar disorder share global gene expression patterns, characterized by astrocyte activation and disrupted synaptic processes.

Genomics↗

bioRxiv2016

The architecture of the human RNA-binding protein regulatory network

RNA-binding proteins (RBPs) are key players of post-transcriptional regulation of gene expression. These proteins influence both cellular physiology and pathology by regulating processes ranging from splicing and polyadenylation to mRNA localization, stability, and translation. To fine-tune the outcome of their regulatory action, RBPs rely on an intricate web of competitive and cooperative interactions. Several studies have described individual interactions of RBPs with RBP mRNAs, suggestive of a RBP-RBP regulatory structure. Here we present the first systematic investigation of this structure, based on a network including almost fifty thousand experimentally determined interactions between RBPs and bound RBP mRNAs.\n\nOur analysis identified two features defining the structure of the RBP-RBP regulatory network. What we call \"RBP clusters\" are groups of densely interconnected RBPs which co-regulate their targets, suggesting a tight control of cooperative and competitive behaviors. \"RBP chains\", instead, are hierarchical structures driven by evolutionarily ancient RBPs, which connect the RBP clusters and could in this way provide the flexibility to coordinate the tuning of a broad set of biological processes.\n\nThe combination of these two features suggests that RBP chains may use the modulation of their RBP targets to coordinately control the different cell programs controlled by the RBP clusters. Under this island-hopping model, the regulatory signal flowing through the chains hops from one RBP cluster to another, implementing elaborate regulatory plans to impact cellular phenotypes. This work thus establishes RBP-RBP interactions as a backbone driving post-transcriptional regulation of gene expression to allow the fine-grained control of RBPs and their targets.

Systems Biology↗

bioRxiv2016

A missense mutation in TUBD1 is associated with high juvenile mortality in Braunvieh and Fleckvieh cattle

BackgroundHaplotypes with reduced or missing homozygosity may harbor deleterious alleles that compromise juvenile survival. A scan for homozygous haplotype deficiency revealed a short segment on bovine chromosome 19 (Braunvieh haplotype 2, BH2) that was associated with high juvenile mortality in Braunvieh cattle. However, the molecular genetic underpinnings and the pathophysiology of BH2 remain to be elucidated.\n\nResultsThe frequency of BH2 was 6.5 % in 8,446 Braunvieh animals from the national bovine genome databases. Both perinatal and juvenile mortality of BH2 homozygous calves were higher than the average in Braunvieh cattle resulting in a depletion of BH2 homozygous adult animals (P=9.3x10-12). The analysis of whole-genome sequence data from 54 Braunvieh animals uncovered a missense mutation in TUBD1 (rs383232842, p.H210R) that was compatible with recessive inheritance of BH2. The availability of sequence data of 236 animals from diverse bovine populations revealed that the missense mutation also segregated at a low frequency (1.7 %) in the Fleckvieh breed. A validation study in 37,314 Fleckvieh animals confirmed high juvenile mortality of homozygous calves (P=2.2x10-15). Our findings show that the putative disease allele is located on an ancestral haplotype that segregates in Braunvieh and Fleckvieh cattle. To unravel the pathophysiology of BH2, six homozygous animals were examined at the animal clinic. Clinical and pathological findings revealed that homozygous calves suffered from chronic airway disease possibly resulting from defective cilia in the respiratory tract.\n\nConclusionsA missense mutation in TUBD1 is associated with high perinatal and juvenile mortality in Braunvieh and Fleckvieh cattle. The mutation is located on a common haplotype likely originating from an ancient ancestor of Braunvieh and Fleckvieh cattle. Our findings demonstrate for the first time that deleterious alleles may segregate across closed cattle breeds without recent admixture. Homozygous calves suffer from chronic airway disease resulting in poor growth performance and high juvenile mortality. The respiratory manifestations resemble key features of diseases resulting from impaired function of airway cilia.

Genomics↗

bioRxiv2016

Cerebrospinal Fluid and Interstitial Fluid Motion via the Glymphatic Pathway Modelled by Optimal Mass Transport

It was recently shown that the brain-wide cerebrospinal fluid (CSF) and interstitial fluid exchange system designated the glymphatic pathway plays a key role in removing waste products from the brain, similarly to the lymphatic system in other body organs1,2. It is therefore important to study the flow patterns of glymphatic transport through the live brain in order to better understand its functionality in normal and pathological states. Unlike blood, the CSF does not flow rapidly through a network of dedicated vessels, but rather through peri-vascular channels and brain parenchyma in a slower time-domain, and thus conventional fMRI or other blood-flow sensitive MRI sequences do not provide much useful information about the desired flow patterns. We have accordingly analyzed a series of MRI images, taken at different times, of the brain of a live rat, which was injected with a paramagnetic tracer into the CSF via the lumbar intrathecal space of the spine. Our goal is twofold: (a) find glymphatic (tracer) flow directions in the live rodent brain; and (b) provide a model of a (healthy) brain that will allow the prediction of tracer concentrations given initial conditions. We model the liquid flow through the brain by the diffusion equation. We then use the Optimal Mass Transfer (OMT) approach3 to model the glymphatic flow vector field, and estimate the diffusion tensors by analyzing the (changes in the) flow. Simulations show that the resulting model successfully reproduces the dominant features of the experimental data.

Neuroscience↗

bioRxiv2016

An atypical role for the myeloid receptor Mincle in CNS injury

Mincle is a C-type lectin known to play a role in innate immune responses to sterile inflammation, but its contribution to pathologies following an ischemic or traumatic injury is not well understood. In the current study we demonstrate a key role for Mincle in ischemic (i.e. transient middle cerebral artery occlusion) but not traumatic central nervous system injury; absence of Mincle also did not significantly alter the extent of tissue damage or functional outcome in peripheral models of ischemic tissue injury. In the stroke model mice lacking Mincle displayed significantly improved functional outcome from focal cerebral ischemia. The functional improvements in Mincle KO animals were accompanied by reduced infiltration of neutrophils and lower levels of proinflammatory cytokines in recruited peripheral blood cells. Bone marrow chimera experiments revealed that presence of Mincle in the central nervous system, but not peripheral immune cells, was the critical regulator of a poor outcome following transient focal cerebral ischemia, however we exclude a direct role for Mincle in microglia or neural activation. We demonstrate that Mincle lacks widespread expression in the brain, but is specifically associated with macrophages resident in the perivascular niche. These findings implicate Mincle in the initiation, extent and severity of local responses to ischemic injury in the brain, but not peripheral tissues. Mincle signalling therefore offers a novel therapeutic target in the quest to limit damage after stroke.\n\nSources of supportAustralian National Health & Medical Research Council [1057846, 1060538 and Fellowship to NAR], SpinalCure Australia (Career Development Fellowship to MJR), the Australian Research Council, the State Government of Victoria, the Australian Government and The University of Queensland.

Cell Biology↗

bioRxiv2016

Recognizing the Continuous Nature of Expression Heterogeneity and Clinical Outcomes in Clear Cell Renal Cell Carcinoma

PURPOSEEvaluation of 12 ccRCC publicly-available ccRCC gene expression datasets showed that previously proposed discrete molecular subtypes are unstable. To reflect the continuous nature of gene expression observed, we developed a quantitative score (Continuous Linear Enhanced Assessment of Renal cell carcinoma, or CLEAR) using expression analysis founded on pathologic parameters.\n\nMATERIALS AND METHODS265 ccRCC gene expression profiles were used to develop the CLEAR score, representing a genetic correlate of the continuum of morphological tumor grade. A signature derivation method based on correlation of CLEAR score with gene expression ranking was used to derive an 18-transcript signature. External validation was conducted in multiple public expression datasets.\n\nResultsAs a measure of intertumoral gene expression heterogeneity, the CLEAR score demonstrated both superior prognostic estimates (94% vs 83% adequacy index in TCGA dataset) and inverse correlation with anti-angiogenic tyrosine-kinase inhibition (65% vs 55% adequacy index) in comparison to previously proposed discrete subtyping classifications. Inverse correlation with high-dose interleukin-2 outcomes was also observed for the CLEAR score (p=0.05). Multiple somatic mutations (VHL, PBRM1, SETD2, KDM5C, TP53, BAP1, PTEN, MTOR) were associated with the CLEAR score. Application of the CLEAR score to independent expression profiling of intratumoral ccRCC regions demonstrated its ability to reflect intratumoral expression heterogeneity and further analysis showed average intertumoral heterogeneity exceeded intratumoral heterogeneity.\n\nConclusionsThe CLEAR score, a gene expression signature developed on histopathology, outperformed discrete subtype-classification in prognostic estimates and correlated better with treatment outcomes. Recognizing cancer as a continuum has important implications for laboratory and clinical research.

Cancer Biology↗

bioRxiv2016

Lactobacillus plantarum is a pathobiont for adult Drosophila.

The microbiome of Drosophila promotes intestinal stem cell division through evolutionarily conserved biochemical pathways. As such, axenic flies have lower rates of gut stem cell division than age-matched wild type counterparts. Additionally, flies with a full consortium of symbiotic bacteria are shorter lived than those maintained in the absence of a microbiome. However, we do not know if stem cell division is essential for symbiont-dependent regulation of adult fly lifespan. To determine if individual symbionts cause aging-dependent death in Drosophila, we examined the impacts of common symbionts on host longevity. In this study, we found that mono-association of adult Drosophila with Lactobacillus plantarum, a widely reported fly symbiont, and member of the probiotic Lactobacillus genus, curtails adult longevity relative to germ-free counterparts. However, the effects of plantarum on lifespan were independent of intestinal aging. Instead, we found that association with plantarum causes an extensive intestinal pathology within the host, characterized by loss of intestinal stem cells, impaired epithelial renewal, and a gradual erosion of epithelial integrity. Our study uncovers an unknown aspect of Lactobacillus plantarum-Drosophila interactions, and establishes a simple model to characterize symbiont-dependent disruption of intestinal homeostasis.

Microbiology↗

bioRxiv2016

Amyloid β-peptides interfere with mitochondrial preprotein import competence by a co-aggregation process

A{beta} peptides play a central role in the etiology of Alzheimer disease (AD) by exerting cellular toxicity correlated with aggregate formation. Experimental evidences showed an intraneuronal accumulation of A{beta} peptides and an interference with mitochondrial functions. Nevertheless, the relevance of intracellular A{beta} peptides in the pathophysiology of AD remained controversial. Here, we found that the two major species of A{beta} peptides, in particular A{beta}42, exhibited a strong inhibitory effect on the preprotein import reactions essential for mitochondrial biogenesis. However, A{beta} peptides interacted only weakly with mitochondria and did not affect the inner membrane potential or the structure of the preprotein translocase complexes. A{beta} peptides significantly decreased the import competence of mitochondrial precursor proteins through a extra-mitochondrial co-aggregation mechanism. Co-aggregation and import inhibition were significantly stronger in case of the longer peptide A{beta}42, correlating with its importance in AD pathology. Our results demonstrate that a direct interference of aggregation-prone A{beta} peptides with mitochondrial protein biogenesis represents a crucial aspect of the pathobiochemical mechanisms contributing to cellular damage in AD.

Cell Biology↗

bioRxiv2016

MetaGxData: Breast and Ovarian Clinically Annotated Transcriptomics Datasets

A wealth of transcriptomic and clinical data on solid tumours are under-utilized due to unharmonized data storage and format. We have developed the MetaGxData package compendium, which includes manually-curated and standardized clinical, pathological, survival, and treatment metadata across breast, ovarian, and pancreatic cancer data. MetaGxData is the largest compendium of curated transcriptomic data for these cancer types to date, spanning 86 datasets and encompassing 15,249 samples. Open access to standardized metadata across cancer types promotes use of their transcriptomic and clinical data in a variety of cross-tumour analyses, including identification of common biomarkers, establishing common patterns of co-expression networks, and assessing the validity of prognostic signatures. Here, we demonstrate that MetaGxData is a flexible framework that facilitates meta-analyses by using it to identify common prognostic genes in ovarian and breast cancer. Furthermore, we use the data compendium to create the first gene signature that is prognostic in a meta-analysis across 3 cancers. These findings demonstrate the potential of MetaGxData to serve as an important resource in oncology research and provide a foundation for future development of cancer-specific compendia.

Bioinformatics↗

bioRxiv2016

Shared effect modeling reveals that a fraction of autoimmune disease associations are consistent with eQTLs in three immune cell types

The majority of autoimmune disease risk effects identified by genome-wide association studies (GWAS) localize to open chromatin with gene regulatory activity. GWAS loci are also enriched for expression quantitative trait loci (eQTLs), suggesting that most disease risk variants exert their pathological effects by altering gene expression1,2. However, because causal variants are difficult to identify and cis-eQTLs occur frequently, it remains challenging to translate this bulk observation into specific instances of a disease risk variant driving changes to gene regulation. Here, we use a novel joint likelihood framework with higher resolution than previous methods to identify loci where disease risk and an eQTL are driven by a single, shared genetic effect as opposed to distinct effects in close proximity. We find that approximately 25% of autoimmune disease loci harbor an eQTL driven by the same genetic ...

Genetics↗