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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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Pathogenic DDX3X mutations impair RNA metabolism and neurogenesis during fetal cortical development

De novo germline mutations in the RNA helicase DDX3X account for 1-3% of unexplained intellectual disability (ID) cases in females, and are associated with autism, brain malformations, and epilepsy. Yet, the developmental and molecular mechanisms by which DDX3X mutations impair brain function are unknown. Here we use human and mouse genetics, and cell biological and biochemical approaches to elucidate mechanisms by which pathogenic DDX3X variants disrupt brain development. We report the largest clinical cohort to date with DDX3X mutations (n=78), demonstrating a striking correlation between recurrent dominant missense mutations, polymicrogyria, and the most severe clinical outcomes. We show that Ddx3x controls cortical development by regulating neuronal generation and migration. Severe DDX3X missense mutations profoundly disrupt RNA helicase activity and induce ectopic RNA-protein granules and aberrant translation in neural progenitors and neurons. Together, our study demonstrates novel mechanisms underlying DDX3X syndrome, and highlights roles for RNA-protein aggregates in the pathogenesis of neurodevelopmental disease.

genetics

Proteomic Analysis of Rat Serum Revealed the Effects of Chronic Sleep Deprivation on Metabolic, Cardiovascular and Nervous System

Sleep is an essential and fundamental physiological process that plays crucial roles in the balance of psychological and physical health. Sleep disorder may lead to adverse health outcomes. The effects of sleep deprivation were extensively studied, but its mechanism is still not fully understood. The present study aimed to identify the alterations of serum proteins associated with chronic sleep deprivation, and to seek for potential biomarkers of sleep disorder mediated diseases. A label-free quantitative proteomics technology was used to survey the global changes of serum proteins between normal rats and chronic sleep deprivation rats. A total of 309 proteins were detected in the serum samples and among them, 117 proteins showed more than 1.8-folds abundance alterations between the two groups. Functional enrichment and network analyses of the differential proteins revealed a close relationship between chronic sleep deprivation and several biological processes including energy metabolism, cardiovascular function and nervous function. And four proteins including pyruvate kinase M1, clusterin, kininogen1 and profilin-1were identified as potential biomarkers for chronic sleep deprivation. The four candidates were validated via parallel reaction monitoring (PRM) based targeted proteomics. In addition, protein expression alteration of the four proteins was confirmed in myocardium and brain of rat model. In summary, the comprehensive proteomic study revealed the biological impacts of chronic sleep deprivation and discovered several potential biomarkers. This study provides further insight into the pathological and molecular mechanisms underlying sleep disorders at protein level.

bioinformatics

Lipid interactions enhance activation and potentiation of cystic fibrosis transmembrane conductance regulator (CFTR)

The recent cryo-electron microscopy structures of phosphorylated, ATP-bound CFTR in detergent micelles failed to reveal an open anion conduction pathway as expected on the basis of previous functional studies in biological membranes. We tested the hypothesis that interaction of CFTR with lipids is important for opening of its channel. Interestingly, molecular dynamics studies revealed that phospholipids associate with regions of CFTR proposed to contribute to its channel activity. More directly, we found that CFTR purified together with associated lipids using the amphipol: A8-35, exhibited higher rates of catalytic activity, channel activation and potentiation using ivacaftor, than did CFTR purified in detergent. Catalytic activity in CFTR detergent micelles was partially rescued by addition of phospholipids plus cholesterol, arguing that these lipids contribute directly to its modulation. In summary, these studies highlight the importance of lipids in regulated CFTR channel activation and potentiation.

biophysics

Human 5′ UTR design and variant effect prediction from a massively parallel translation assay

Predicting the impact of cis-regulatory sequence on gene expression is a foundational challenge for biology. We combine polysome profiling of hundreds of thousands of randomized 5' UTRs with deep learning to build a predictive model that relates human 5' UTR sequence to translation. Together with a genetic algorithm, we use the model to engineer new 5' UTRs that accurately target specified levels of ribosome loading, providing the ability to tune sequences for optimal protein expression. We show that the same approach can be extended to chemically modified RNA, an important feature for applications in mRNA therapeutics and synthetic biology. We test 35,000 truncated human 5' UTRs and 3,577 naturally-occurring variants and show that the model accurately predicts ribosome loading of these sequences. Finally, we provide evidence of 47 SNVs associated with human diseases that cause a significant change in ribosome loading and thus a plausible molecular basis for disease.

synthetic biology

Accurate estimation of molecular counts in droplet-based single-cell RNA-seq experiments

Single-cell RNA-seq protocols provide powerful means for examining the gamut of cell types and transcriptional states that comprise complex biological tissues. Recently-developed approaches based on droplet microfluidics, such as inDrop or Drop-seq, use massively multiplexed barcoding to enable simultaneous measurements of transcriptomes for thousands of individual cells. The increasing complexity of such data also creates challenges for subsequent computational processing and troubleshooting of these experiments, with few software options currently available. Here we describe a flexible pipeline for processing droplet-based transcriptome data that implements barcode corrections, classification of cell quality, and diagnostic information about the droplet libraries. We introduce advanced methods for correcting composition bias and sequencing errors affecting cellular and molecular barcodes to provide more accurate estimates of molecular counts in individual cells.

genomics

A prior-based approach for hypothesis comparison and its utility to discern among temporal scenarios of divergence

One of the major problems in evolutionary biology is to elucidate the relationships between historical events and the tempo and mode of lineage divergence. The development of relaxed molecular clock models and the increasing availability of DNA sequences resulted in more accurate estimations of taxa divergence times. However, finding the link between competing historical events and divergence is still challenging. Here we investigate assigning constrained-age priors to nodes of interest in a time-calibrated phylogeny as a means of hypothesis comparison. These priors are equivalent to historic scenarios for lineage origin. The hypothesis that best explains the data can be selected by comparing the likelihood values of the competing hypotheses, modelled with different priors. A simulation approach was taken to evaluate the performance of the prior-based method and to compare it with an unconstrained approach. We explored the effect of DNA sequence length and the temporal placement and span of competing hypotheses (i.e. historic scenarios) on selection of the correct hypothesis and the strength of the inference. Competing hypotheses were compared applying a posterior simulation analogue of the Akaike Information Criterion and Bayes factors (obtained after calculation of the marginal likelihood with three estimators: Harmonic Mean, Stepping Stone and Path Sampling). We illustrate the potential application of the prior-based method on an empirical data set to compare competing geological hypotheses explaining the biogeographic patterns in Pleurodeles newts. The correct hypothesis was selected on average 89% times. The best performance was observed with DNA sequence length of 3500-10000 bp. The prior-based method is most reliable when the hypotheses compared are not temporally too close. The strongest inferences were obtained when using the Stepping Stone and Path Sampling estimators. The prior-based approach proved effective in discriminating between competing hypotheses when used on empirical data. The unconstrained analyses performed well but it probably requires additional computational effort. Researchers applying this approach should rely only on inferences with moderate to strong support. The prior-based approach could be applied on biogeographical and phylogeographical studies where robust methods for historical inferences are still lacking.

evolutionary biology

A molecular framework for functional versatility of HECATE transcription factors

During the plant life cycle, diverse signalling inputs are continuously integrated and engage specific genetic programs depending on the cellular or developmental context. Consistent with an important role in this process, HECATE (HEC) bHLH transcription factors display diverse functions, from photomorphogenesis to the control of shoot meristem dynamics and gynoecium patterning. However, the molecular mechanisms underlying their functional versatility and the deployment of specific HEC sub-programs still remain elusive.\n\nTo address this issue, we systematically identified proteins with the capacity to interact with HEC1, the best characterized member of the family, and integrated this information with our data set of direct HEC1 target genes. The resulting core genetic modules were consistent with specific developmental functions of HEC1, including its described activities in light signalling, gynoecium development and auxin homeostasis. Importantly, we found that in addition, HEC genes play a role in the modulation of flowering time and uncovered that their role in gynoecium development may involve the direct transcriptional regulation of NGATHA1 (NGA1) and NGA2 genes. NGA factors were previously shown to contribute to fruit development, but our data now show that they also modulate stem cell homeostasis in the SAM.\n\nTaken together, our results suggest a molecular network underlying the functional versatility of HEC transcription factors. Our analyses have not only allowed us to identify relevant target genes controlling shoot stem cell activity and a so far undescribed biological function of HEC1, but also provide a rich resource for the mechanistic elucidation of further context dependent HEC activities.\n\nSignificance statementAlthough many transcription factors display diverse regulatory functions during plant development, our understanding of the underlying mechanisms remains poor. Here, by reconstructing the regulatory modules orchestrated by the bHLH transcription factor HECATE1 (HEC1), we defined its regulatory signatures and delineated a regulatory network that provides a molecular basis for its functional versatility. In addition, we uncovered a function for HEC genes in modulating flowering time and further identified downstream signalling components balancing shoot stem cell activity.

plant biology

Integrated analysis of single-cell embryo data yields a unified transcriptome signature for the human preimplantation epiblast

Single-cell profiling techniques create opportunities to delineate cell fate progression in mammalian development. Recent studies provide transcriptome data from human preimplantation embryos, in total comprising nearly 2000 individual cells. Interpretation of these data is confounded by biological factors such as variable embryo staging and cell-type ambiguity, as well as technical challenges in the collective analysis of datasets produced with different sample preparation and sequencing protocols. Here we address these issues to assemble a complete gene expression time course spanning human preimplantation embryogenesis. We identify key transcriptional features over developmental time and elucidate lineage-specific regulatory networks. We resolve post hoc cell-type assignment in the blastocyst, and define robust transcriptional prototypes that capture epiblast and primitive endoderm lineages. Examination of human pluripotent stem cell transcriptomes in this framework identifies culture conditions that sustain a naive state pertaining to the inner cell mass. Our approach thus clarifies understanding both of lineage segregation in the early human embryo and of in vitro stem cell identity, and provides an analytical resource for comparative molecular embryology.

developmental biology

The genetics of resistance to Morinda fruit toxin during the postembryonic stages in Drosophila sechellia

Many phytophagous insect species are ecologic specialists that have adapted to utilize a single host plant. Drosophila sechellia is a specialist that utilizes the ripe fruit of Morinda citrifolia, which is toxic to its sibling species, D. simulans. Here we apply multiplexed shotgun genotyping and QTL analysis to examine the genetic basis of resistance to M. citrifolia fruit toxin in interspecific hybrids. We find that at least four dominant and four recessive loci interact additively to confer resistance to the M. citrifolia fruit toxin. These QTL include a dominant locus of large effect on the third chromosome (QTL-IIIsima) that was not detected in previous analyses. The small-effect loci that we identify overlap with regions that were identified in selection experiments with D. simulans on octanoic acid and in QTL analyses of adult resistance to octanoic acid. Our high-resolution analysis sheds new light upon the complexity of M. citrifolia resistance, and suggests that partial resistance to lower levels of M. citrifolia toxin could be passed through introgression from D. sechellia to D. simulans in nature. The identification of a locus of major effect, QTL-IIIsima, is an important step towards identifying the molecular basis of host plant specialization by D. sechellia.

Evolutionary Biology

Coalescent times and patterns of genetic diversity in species with facultative sex: effects of gene conversion, population structure and heterogeneity

Many diploid organisms undergo facultative sexual reproduction. However, little is currently known concerning the distribution of neutral genetic variation amongst facultative sexuals except in very simple cases. Under-standing this distribution is important when making inferences about rates of sexual reproduction, effective population size and demographic history. Here, we extend coalescent theory in diploids with facultative sex to consider gene conversion, selfing, population subdivision, and temporal and spatial heterogeneity in rates of sex. In addition to analytical results for two-sample coalescent times, we outline a coalescent algorithm that accommodates the complexities arising from partial sex; this algorithm can be used to generate multi-sample coalescent distributions. A key result is that when sex is rare, gene conversion becomes a significant force in reducing diversity within individuals, which can remove genomic signatures of infrequent sex (the Meselson Effect) or entirely reverse the predictions. Our models offer improved methods for assessing the null model (I.e. neutrality) of patterns of molecular variation in facultative sexuals.

Evolutionary Biology

Molecular Basis For The Specific And Multivariate Recognitions Of RNA Substrates By Human hnRNPA2/B1

Human hnRNPA2/B1 is an RNA-binding protein that plays important roles in a variety of biological processes, from mRNA maturation, trafficking and translation to regulation of gene expression mediated by long non-coding RNAs and microRNAs. hnRNPA2/B1 contains two RNA recognition motifs (RRM) that provide sequence-specific recognition of widespread RNA substrates including recently reported m6A-containing motifs. Here we determined the first crystal structures of tandem RRM domains of hnRNPA2/B1 in complex with various RNA substrates. Our structures reveal that hnRNPA2/B1 can bind two RNA elements in an antiparallel fashion with a sequence preference for AGG and UAG by RRM1 and RRM2, respectively, suggesting an RNA matchmaker mechanism during the hnRNPA2/B1 function. However, our combined studies did not observe specific binding of m6A by either the RRM domains or the full-length hnRNPA2/B1, implying that the \"reader\" function of hnRNPA2/B1 may adopt an unknown mechanism that remains to be characterized.

biochemistry

Enhanced Waddington Landscape Model with Cell-CellCommunication Can Explain Molecular Mechanisms ofSelf-Organization

The molecular mechanisms of self-organization that orchestrate embryonic cells to create astonishing patterns have been among major questions of developmental biology. It is recently shown that embryonic stem cells (ESCs), when cultured on particular micropatterns, can self-organize and mimic early steps of pre-implantation embryogenesis. A systems-biology model to address this observation from a dynamical systems perspective is essential. Here, we propose a multicellular mathematical model for pattern formation during in vitro gastrulation of human ESCs. This model enhances the basic principles of Waddington epigenetic landscape with cell-cell communication, in order to enable pattern and tissue formation. To prevent overfitting of the model, there is a minimal number of parameters in the model, which are sufficient to address different experimental observations such as the formation of three germ layers and trophectoderm, responses to altered culture conditions and micropattern diameters, and unexpected spotted forms of the germ layers under certain conditions. This model provides a basis for in-silico modeling of self-organization.

systems biology

Does alpha-tocopherol flip-flop help to protect membranes against oxidation?

Alpha-tocopherols (-toc) are crucial in protecting biological membranes against oxidation by free radicals. We investigate the behavior of -toc molecules in lipid bilayers containing oxidized lipids by molecular dynamics (MD) simulations. To verify the approach, the location and orientation of -toc are first shown to be in agreement with previous experimental results. The simulations further show that -toc molecules stay inside the lipid bilayer with their hydroxyl groups in contact with the bilayer surface. Interestingly, interbilayer -toc flip-flop was observed in both oxidized and non-oxidized bilayers with significantly higher frequency in aldehyde lipid bilayer. Free energy calculations were performed and estimates of the flip-flop rates across the bilayers were determined. As the main finding, our results show that the presence of oxidized lipids leads to a significant decrease of free energy barriers and that the flip-flop rates depend on the type of oxidized lipid present. Our results suggest that -toc molecules could potentially act as high efficacy scavengers of free radicals to protect membranes from oxidative attack and help stabilize them under oxidative stress.

biophysics

Vaccinomics strategy for developing a unique multi-epitope monovalent vaccine against Marburg marburgvirus

Marburg virus causes severe hemorrhagic fever in both humans and non-human primates with high degree of infectivity and lethality. To date no approved treatment is available for Marburg virus infection. A study was employed to design a novel chimeric vaccine against Marburg virus by adopting reverse vaccinology approach. Envelope glycoprotein and matrix protein VP40 were identified as most antigenic viral proteins which generated a plethora of antigenic epitopes. Results showed that vaccine construct V1 was superior in terms of various physicochemical properties and structural stability. Molecular docking analysis of the refined vaccine with different MHCs and human immune TLR8 receptor demonstrated higher binding affinity. Moreover, complexed structure of the modeled vaccine and TLR8 indicated minimal deformability at molecular level. Translational potency and microbial expression of the modeled vaccine within E. coli strain K12 by pET28a(+) vector were also biologically significant. However, further in vitro and in vivo investigation could be implemented for the acceptance and validation of the designed vaccine against Marburg virus.

bioinformatics

Cooperative induction of ordered peptide and fatty acid aggregates

Interactions between biological membranes and disease-associated amyloids are well documented and their prevalence suggests that an inherent affinity exists between these two distinct molecular assemblies. Within the framework of our research project on amyloids and the origins of life, we hypothesized here that such interactions could increase both the sequence and structure space of peptide amyloids in a heterogeneous system and that if cooperative in nature, the interaction could be advantageous to the propagation of these entities in a prebiotic context. Thus, we have investigated the interplay between vesicle-forming fatty acids and amyloidogenic peptides, the respective precursors of lipids and proteins. Individually they are able to form ordered structures under a limited range of conditions with the bilayer of fatty acid vesicles and the cross-{beta} core of amyloids both being repetitive structures that could in principle support a cooperative interaction. Here we report that an 8-residue basic peptide that can form an amphipathic {beta}-strand, that is soluble at neutral pH and that can form amyloids above its pI at pH 11, is also able to cooperatively form novel co-aggregates of diverse structure with and in the context of simple fatty acids at neutral pH. Below the critical vesicle concentration (CVC) the mixtures of fatty acid and peptide yield a flocculent precipitate with an underlying {beta}-structure. Above the CVC, the mixtures yield ribbon or tube-like structures that bear some of the hallmarks of amyloids yet have associated with them a significant amount of fatty acids, likely in a bilayer structure. In the context of the origin of cellular life these results expand the phase space of both peptides and fatty acids while providing a simple yet robust physical connection between two distinct biological entities relevant for life.

biophysics

Phylogeny Recapitulates Learning: Self-Optimization of Genetic Code

Learning algorithms have been proposed as a non-selective mechanism capable of creating complex adaptive systems in life. Evolutionary learning however has not been demonstrated to be a plausible cause for the origin of a specific molecular system. Here we show that genetic codes as optimal as the Standard Genetic Code (SGC) emerge readily by following a molecular analog of the Hebbs rule (\"neurons fire together, wire together\"). Specifically, error-minimizing genetic codes are obtained by maximizing the number of physio-chemically similar amino acids assigned to evolutionarily similar codons. Formulating genetic code as a Traveling Salesman Problem (TSP) with amino acids as \"cities\" and codons as \"tour positions\" and implemented with a Hopfield neural network, the unsupervised learning algorithm efficiently finds an abundance of genetic codes that are more error-minimizing than SGC. Drawing evidence from molecular phylogenies of contemporary tRNAs and aminoacyl-tRNA synthetases, we show that co-diversification between gene sequences and gene functions, which cumulatively captures functional differences with sequence differences and creates a genomic \"memory\" of the living environment, provides the biological basis for the Hebbian learning algorithm. Like the Hebbs rule, the locally acting phylogenetic learning rule, which may simply be stated as increasing phylogenetic divergence for increasing functional difference, could lead to complex and robust life systems. Natural selection, while essential for maintaining gene function, is not necessary to act at system levels. For molecular systems that are self-organizing through phylogenetic learning, the TSP model and its Hopfield network solution offer a promising framework for simulating emerging behavior, forecasting evolutionary trajectories, and designing optimal synthetic systems.

evolutionary biology

BrainImageR: Spatiotemporal gene set analysis referencing the human brain

RATIONALENeurological molecular analyses such as transcriptomics, epigenetics, and genome-wide association studies must be assessed in the context of the human brain in order to generate biologically meaningful inferences. It is often difficult to access primary human brain tissue; therefore, approximations are made using in vitro modeling or by identifying disease-associated genes from DNA extracted from blood. Gene sets from these studies are then compared to the post-mortem human brain to provide an assessment of the brain region and the developmental time point that a gene set is most closely associated with. However, most analyses of postmortem datasets are achieved by building new computational tools each time in-house, which can cause discrepancies from study to study, indicating that the field is in need of a user-friendly suite of tools to examine spatiotemporal expression with respect to the postmortem brain. Such a tool will be of use to the molecular interrogation of neurological and psychiatric disorders, with direct advantages for the disease-modeling and human genetics communities.\n\nRESULTSWe have developed brainImageR, an R package that calculates both the spatial and temporal association of a dataset with post-mortem gene expression data from the Allen Brain Atlas. BrainImageR performs a robust analysis of gene set enrichment to identify enriched anatomical regions, provides a global high-resolution visualization of these enrichments across the human brain, and predicts when in developmental time the sample is most closely matched to, a task that has become increasingly important in the field of in vitro neuronal modeling. These functionalities of brainImageR enable a quick and efficient characterization of a given dataset across normal human brain development.\n\nAVAILABILITY AND IMPLEMENTATIONBrainImageR is released under the Creative Commons CC BY-SA 4.0 license and the source code can be downloaded through github at https://github.com/saralinker/brainImageR.\n\nCONTACTgage@salk.edu

bioinformatics

The molecular mechanism of N-acetylglucosamine side-chain attachment to the Lancefield group A Carbohydrate in Streptococcus pyogenes

In many Lactobacillales species (i.e. lactic acid bacteria), peptidoglycan is decorated by polyrhamnose polysaccharides that are critical for cell envelope integrity and cell shape and also represent key antigenic determinants. Despite the biological importance of these polysaccharides, their biosynthetic pathways have received limited attention. The important human pathogen, Streptococcus pyogenes, synthesizes a key antigenic surface polymer--the Lancefield group A carbohydrate (GAC). GAC is covalently attached to peptidoglycan and consists of a polyrhamnose polymer, with N-acetylglucosamine (GlcNAc) side chains, which is an essential virulence determinant. The molecular details of the mechanism of polyrhamnose modification with GlcNAc are currently unknown. In this report, using molecular genetics, analytical chemistry and mass spectrometry analysis, we demonstrated that GAC biosynthesis requires two distinct undecaprenol-linked GlcNAc-lipid intermediates: GlcNAc-pyrophosphorylundecaprenol (GlcNAc-P-P-Und) produced by the GlcNAc-phosphate transferase GacO and GlcNAc-phosphate-undecaprenol (GlcNAc-P-Und) produced by the glycosyltransferase GacI. Further investigations revealed that the GAC polyrhamnose backbone is assembled on GlcNAc-P-P-Und. Our results also suggested that a GT-C glycosyltranferase, GacL, transfers GlcNAc from GlcNAc-P-Und to polyrhamnose. Moreover, GacJ, a small membrane-associated protein, formed a complex with GacI and significantly stimulated its catalytic activity. Of note, we observed that GacI homologs perform a similar function in Streptococcus agalactiae and Enterococcus faecalis. In conclusion, the elucidation of GAC biosynthesis in S. pyogenes reported here enhances our understanding of how other Gram-positive bacteria produce essential components of their cell wall.

microbiology