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Results for “Molecular Biology”

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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2015

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↗

bioRxiv2017

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↗

bioRxiv2018

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↗

bioRxiv2018

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↗

bioRxiv2018

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↗

bioRxiv2018

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↗

bioRxiv2018

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↗

bioRxiv2017

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↗

bioRxiv2017

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↗

bioRxiv2017

Genomic regression of claw keratin, taste receptor and light-associated genes inform biology and evolutionary origins of snakes

Regressive evolution of anatomical traits corresponds with the regression of genomic loci underlying such characters. As such, studying patterns of gene loss can be instrumental in addressing questions of gene function, resolving conflicting results from anatomical studies, and understanding the evolutionary history of clades. The origin of snakes coincided with the regression of a number of anatomical traits, including limbs, taste buds and the visual system. By studying the genomes of snakes, I was able to test three hypotheses associated with the regression of these features. The first concerns two keratins that are putatively specific to claws. Both genes that encode these keratins were pseudogenized/deleted in snake genomes, providing additional evidence of claw- specificity. The second hypothesis is whether snakes lack taste buds, an issue complicated by unequivocal, conflicting results in the literature. I found evidence that different snakes have lost one or more taste receptors, but all snakes examined retained at least some capacity for taste. The final hypothesis I addressed is that the earliest snakes were adapted to a dim light niche. I found evidence of deleted and pseudogenized genes with light- associated functions in snakes, demonstrating a pattern of gene loss similar to other historically nocturnal clades. Together these data also provide some bearing on the ecological origins of snakes, including molecular dating estimates that suggest dim light adaptation preceded the loss of limbs.

evolutionary biology↗

bioRxiv2017

The systematic conservation planning for intraspecific genetic diversity.

Intraspecific diversity informs the demographic and evolutionary histories of populations, and should be a main conservation target. Although approaches exist for identifying relevant biological conservation units, attempts to identify priority conservation areas for intraspecific diversity are scarce, especially within a multi-specific framework. We used neutral molecular data on six European freshwater fish species (Squalius cephalus, Phoxinus phoxinus, Barbatula barbatula, Gobio occitaniae, Leuciscus burdigalensis and Parachondrostoma toxostoma) sampled at the riverscape scale (i.e. the Garonne-Dordogne River basin, France) to determine hot- and cold-spots of genetic diversity, and to identify priority conservation areas using a systematic conservation planning approach. We demonstrate that systematic conservation planning is efficient for identifying priority areas representing a predefined part of the total genetic diversity of a whole landscape. With the exception of private allelic richness, classical genetic diversity indices (allelic richness, genetic uniqueness) were poor predictors for identifying priority areas. Moreover, we identified weak surrogacies among conservation solutions found for each species, implying that conservation solutions are highly species-specific. Nonetheless, we showed that priority areas identified using intraspecific genetic data from multiple species provide more effective conservation solutions than areas identified for single species or on the basis of traditional taxonomic criteria.

evolutionary biology↗

bioRxiv2018

Sequence variation of rare outer membrane protein β-barrel domains in clinical strains provides insights into the evolution of Treponema pallidum subsp. pallidum, the syphilis spirochete.

In recent years, considerable progress has been made in topologically and functionally characterizing integral outer membrane proteins (OMPs) of Treponema pallidum subspecies pallidum (TPA), the syphilis spirochete, and identifying its surface-exposed {beta}-barrel domains. Extracellular loops in OMPs of Gram-negative bacteria are known to be highly variable. We examined the sequence diversity of {beta}-barrel-encoding regions of tprC, tprD, and bamA, in 31 specimens from Cali, Colombia; San Francisco, California; and the Czech Republic and compared them to allelic variants in the 41 reference genomes in the NCBI database. To establish a phylogenetic framework, we used tp0548 genotyping and tp0558 sequences to assign strains to the Nichols or SS14 clades. We found that (i) {beta}-barrels in clinical strains could be grouped according to allelic variants in TPA reference genomes; (ii) for all three OMP loci, clinical strains within the Nichols or SS14 clades often harbored {beta}-barrel variants that differed from the Nichols and SS14 reference strains; and (iii) OMP variable regions often reside in predicted extracellular loops containing B-cell epitopes. Based upon structural models, non-conservative amino acid substitutions in predicted transmembrane {beta}-strands of TprC and TprD2 could give rise to functional differences in their porin channels. OMP profiles of some clinical strains were mosaics of different reference strains and did not correlate with results from enhanced molecular typing. Our observations suggest that human host selection pressures drive TPA OMP diversity and that genetic exchange contributes to the evolutionary biology of TPA. They also set the stage for topology-based analysis of antibody responses against OMPs and help frame strategies for syphilis vaccine development.\n\nIMPORTANCEDespite recent progress characterizing outer membrane proteins (OMPs) of Treponema pallidum (TPA), little is known about how their surface-exposed, {beta}-barrel-forming domains vary among strains circulating within high-risk populations. In this study, sequences for the {beta}-barrel-encoding regions of three OMP loci, tprC, tprD, and bamA, in TPA from a large number of patient specimens from geographically disparate sites were examined. Structural models predict that sequence variation within {beta}-barrel domains occurred predominantly within predicted extracellular loops. Amino acid substitutions in predicted transmembrane strands that could potentially affect porin channel function also were noted. Our findings suggest that selection pressures exerted by human populations drive TPA OMP diversity and that recombination at OMP loci contributes to the evolutionary biology of syphilis spirochetes. These results also set the stage for topology-based analysis of antibody responses that promote clearance of TPA and frame strategies for vaccine development based upon conserved OMP extracellular loops.

microbiology↗

bioRxiv2018

Vertical and horizontal integration of multi-omics data with miodin

SummaryStudies on multiple modalities of omics data such as transcriptomics, genomics and proteomics are growing in popularity, since they allow us to investigate complex mechanisms across molecular layers. Integration of multi-omics data remains challenging and requires combination of several software tools to process data and generate biological insights. This paper presents miodin, a software package for streamlined data analysis and integration of omics data across experiments on the same samples, or across studies on the same variables.\n\nAvailability and implementationThe miodin package is implemented in R and is freely available for use and extension under the GPL-3 license. Package source, reference documentation and user manual are available at https://gitlab.com/algoromics/miodin.\n\nContactbenjamin.ulfenborg@his.se

bioinformatics↗

bioRxiv2015

Phylodynamics of H5N1 Highly Pathogenic Avian Influenza in Europe, 2005–2010: Potential for Molecular Surveillance of New Outbreaks

Previous Bayesian phylogeographic studies of H5N1 highly pathogenic avian influenza viruses (HPAIVs) explored the origin and spread of the epidemic from China into Russia, indicating that HPAIV circulated in Russia prior to its detection there in 2005. In this study, we extend this research to explore the evolution and spread of HPAIV within Europe during the 2005-2010 epidemic, using all available sequences of the HA and NA gene regions that were collected in Europe and Russia during the outbreak. We use discrete-trait phylodynamic models within a Bayesian statistical framework to explore the evolution of HPAIV. Our results indicate that the genetic diversity and effective population size of HPAIV peaked between mid-2005 and early 2006, followed by drastic decline in 2007, which coincides with the end of the epidemic in Europe. Our results also suggest that domestic birds were the most likely source of the spread of the virus from Russia into Europe. Additionally, estimates of viral dispersal routes indicate that Russia, Romania, and Germany were key epicenters of these outbreaks. Our study quantifies the dynamics of a major European HPAIV pandemic and substantiates the ability of phylodynamic models to improve molecular surveillance of novel AIVs.

Evolutionary Biology↗

bioRxiv2017

The Evolutionary Dynamics Of The Odorant Receptor Gene Family In Corbiculate Bees

Insects rely on chemical information to locate food, choose mates, and detect potential predators. It has been hypothesized that adaptive changes in the olfactory system facilitated the diversification of numerous insect lineages. For instance, evolutionary changes of Odorant Receptor (OR) genes often occur in parallel with modifications in life history strategies. Corbiculate bees display a diverse array of behaviors that are controlled through olfaction, including varying degrees of social organization, and manifold associations with floral resources. Here we investigated the molecular mechanisms driving the evolution of the OR gene family in corbiculate bees in comparison to other chemosensory gene families. Our results indicate that the genomic organization of the OR gene family has remained highly conserved for approximately 80 million years, despite exhibiting major changes in repertoire size among bee lineages. Moreover, the evolution of OR genes appears to be driven mostly by lineage-specific gene duplications in few genomic regions that harbor large numbers of OR genes. A selection analysis revealed that OR genes evolve under positive selection, with the strongest signals detected in recently duplicated copies. Our results indicate that chromosomal translocations had a minimal impact on OR evolution, and instead local molecular mechanisms appear to be main drivers of OR repertoire size. Our results provide empirical support to the longstanding hypothesis that positive selection shaped the diversification of the OR gene family. Together, our results shed new light on the molecular mechanisms underlying the evolution of olfaction in insects.

evolutionary biology↗

bioRxiv2017

Developmental switching in Physarum polycephalum: Petri net analysis of single cell trajectories of gene expression indicates responsiveness and genetic plasticity of the Waddington quasipotential landscape

The developmental switch to sporulation in Physarum polycephalum is a phytochrome-mediated far-red light-induced cell fate decision that synchronously encompasses the entire multinucleate plasmodial cell and is associated with extensive reprogramming of the transcriptome. By repeatedly taking samples of single cells after delivery of a light stimulus pulse, we analysed differential gene expression in two mutant strains and in a heterokaryon of the two strains all of which display a different propensity for making the cell fate decision. Multidimensional scaling of the gene expression data revealed individually different single cell trajectories eventually leading to sporulation. Characterization of the trajectories as walks through states of gene expression discretized by hierarchical clustering allowed the reconstruction of Petri nets that model and predict the observed behavior. Structural analyses of the Petri nets indicated stimulus- and genotype-dependence of both, single cell trajectories and of the quasipotential landscape through which these trajectories are taken. The Petri net-based approach to the analysis and decomposition of complex cellular responses and of complex mutant phenotypes may provide a scaffold for the data-driven reconstruction of causal molecular mechanisms that shape the topology of the quasipotential landscape.

systems biology↗

bioRxiv2017

Theoretical foundation of the RelTime method for estimating divergence times from variable evolutionary rates

RelTime estimates divergence times by relaxing the assumption of a strict molecular clock in a phylogeny. It showed excellent performance in estimating divergence times for both simulated and empirical molecular sequence datasets in which evolutionary rates varied extensively throughout the tree. RelTime is computationally efficient and scales well with increasing size of datasets. Until now, however, RelTime has not had a formal mathematical foundation. Here, we show that the basis of the RelTime approach is a relative rate framework (RRF) that combines comparisons of evolutionary rates in sister lineages with the principle of minimum rate change between an evolutionary lineage and its descendants. We present analytical solutions for estimating relative lineage rates and divergence times under RRF. We also discuss the relationship of RRF with other approaches, including the Bayesian framework. We conclude that RelTime will be also useful for phylogenies with branch lengths derived not only from molecular data, but also morphological and biochemical traits.

evolutionary biology↗

bioRxiv2017

A minimal model of protein allocation during phototrophic growth

Photoautotrophic growth depends upon an optimal allocation of finite cellular resources to diverse intracellular processes. Commitment of a certain mass fraction of the proteome to a specific cellular function, typically reduces the proteome available for other cellular functions. Here, we develop a minimal semi-quantitative kinetic model of cyanobacterial phototrophic growth to describe such trade-offs of cellular protein allocation. The model is based on coarse-grained descriptions of key cellular processes, in particular carbon uptake, metabolism, photosynthesis, and protein translation. The model is parametrized using literature data and experimentally obtained growth curves. Of particular interest are the resulting cyanobacterial growth laws as fundamental characteristics of cellular growth. We show that the model gives rise to similar growth laws as observed for heterotrophic organisms, with several important differences due to the distinction between light energy and carbon uptake. We discuss recent experimental data supporting the model results and show that minimal growth models have implications for our understanding of the limits of phototrophic growth and bridge a gap between molecular physiology and ecology.

systems biology↗