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bioRxiv2018

Genome-Wide Association Studies of malaria susceptibility and resistance: progress, pitfalls and prospects

P. falciparum malaria is still among the leading causes of child mortality in sub-Saharan Africa; killing hundreds of thousands of children each year. Malaria has been recognized as one of the prominent evolutionary selective forces of human genome that led to the emergence of multiple host protective polymorphisms associated with minimizing the risk of developing severe malaria in endemic areas. A comprehensive understanding of the genetic bases of malaria resistance can shed light to the molecular mechanisms of host-parasite interactions that can potentially pave ways to the development of new therapeutics and vaccines. Genome-wide association studies (GWASs) have recently been implemented in malaria endemic areas and identified a number of novel association genetic variants. Despite this success, only few variants did replicate across the studies and the underlying biology is yet to be understood for the majority of the novel variants. Besides, there are several open questions around heritability, polygenic effects, epistatic interactions, genetic correlations and associated molecular pathways among others. In this review, we first assess the progress and pitfalls of malaria susceptibility GWASs. We then, provide an overview of the current progress in post-GWAS approaches and discuss how these approaches can potentially be implemented in malaria susceptibility GWASs to extract further functional information. We conclude by highlighting the importance of multi-step and multidimensional integrative studies for unravelling the genetic basis of malaria susceptibility and resistance at systems biology level.

genomics↗

bioRxiv2017

Molecular and functional variation in iPSC-derived sensory neurons

Induced pluripotent stem cells (iPSCs), and cells derived from them, have become key tools to model biological processes and disease mechanisms, particularly in cell types such as neurons that are difficult to access from living donors. Here, we present the first map of regulatory variants in an iPSC-derived cell type. To investigate genetic contributions to human sensory function, we performed 123 differentiations of iPSCs from 103 unique donors to a sensory neuronal fate, and measured gene expression, chromatin accessibility, and neuronal excitability. Compared with primary dorsal root ganglion, where sensory nerves collect near the spinal cord, gene expression was more variable across iPSC-derived neuronal cultures, particularly in genes related to differentiation and nervous system development. Single cell RNA-sequencing revealed that although the majority of cells are neuronal and express the expected marker genes, a substantial fraction have a fibroblast-like expression profile. By applying an allele-specific method we identify 3,778 quantitative trait loci influencing gene expression, 6,318 for chromatin accessibility, and 2,097 for RNA splicing at FDR 10%. A number of these overlap with common disease associations, and suggest candidate causal variants and target genes. These include known causal variants at SNCA for Parkinsons disease and TNFRSF1A for multiple sclerosis, as well as new candidates for migraine, Parkinsons disease, and schizophrenia.

genomics↗

bioRxiv2017

Genomic Locus Modulating Corneal Thickness in the Mouse Identifies POU6F2 as a Potential Risk of Developing Glaucoma

Purpose: Central corneal thickness (CCT) is one of the most heritable ocular traits and it is also a phenotypic risk factor for primary open angle glaucoma (POAG). The present study uses the BXD Recombinant Inbred (RI) strains to identify novel quantitative trait loci (QTLs) modulating CCT in the mouse with the potential of identifying a molecular link between CCT and risk of developing POAG.\n\nMethods: The BXD RI strain set was used to define mammalian genomic loci modulating CCT, with a total of 818 corneas measured from 61 BXD RI strains (between 60-100 days of age). The mice were anesthetized and the eyes were positioned in front of the lens of the Phoenix Micron IV Image-Guided OCT system or the Bioptigen OCT system. CCT data for each strain was averaged and used to identify quantitative trait loci (QTLs) modulating this phenotype using the bioinformatics tools on GeneNetwork (www.genenetwork.org). The candidate genes and genomic loci identified in the mouse were then directly compared with the summary data from a human primary open-angle glaucoma (POGA) genome wide association study (NEIGHBORHOOD) to determine if any genomic elements modulating mouse CCT are also risk factors for POAG.\n\nResults: This analysis revealed one significant QTL on Chr 13 and a suggestive QTL on Chr 7. The significant locus on Chr 13 (13 to 19 Mb) was examined further to define candidate genes modulating this eye phenotype. For the Chr 13 QTL in the mouse, only one gene in the region (Pou6f2) contained nonsynonymous SNPs. Of these five nonsynonymous SNPs in Pou6f2, two resulted in changes in the amino acid proline which could result in altered secondary structure affecting protein function. The 7 Mb region under the mouse Chr 13 peak distributes over 2 chromosomes in the human: Chr 1 and Chr 7. These genomic loci were examined in the NEIGHBORHOOD database to determine if they are potential risk factors for human glaucoma identified using meta-data from human GWAS. The top 50 hits all resided within one gene (POU6F2), with the highest significance level of p = 10-6 for SNP rs76319873. POU6F2 is found in retinal ganglion cells and in corneal limbal stem cells. To test the effect of POU6F2 on CCT we examined the corneas of a Pou6f2-null mice and the corneas were thinner than those of wild-type littermates. In addition, these POU6F2 RGCs die early in the DBA/2J model of glaucoma than most RGCs.\n\nConclusions: Using a mouse genetic reference panel, we identified a transcription factor, Pou6f2, that modulates CCT in the mouse. POU6F2 is also found in a subset of retinal ganglion cells and these RGCs are sensitive to injury.\n\nAuthors SummaryGlaucoma is a complex group of diseases with several known causal mutations and many known risk factors. One well-known risk factor for developing primary open angle glaucoma is the thickness of the central cornea. The present study leverages a unique blend of systems biology methods using BXD recombinant inbred mice and genome-wide association studies from humans to define a putative molecular link between a phenotypic risk factor (central corneal thickness) and glaucoma. We identified a transcription factor, POU6F2, that is found in the developing retinal ganglion cells and cornea. POU6F2 is also present in a subpopulation of retinal ganglion cells and in stem cells of the cornea. Functional studies reveal that POU6F2 is associated the central corneal thickness and with susceptibility of retinal ganglion cells to injury.

genetics↗

bioRxiv2018

A population-based human enCYCLOPedia for circadian medicine

The discovery that half of the mammalian protein-coding genome is clock-regulated has clear implications for medicine. Indeed, recent studies demonstrate time-of-day impact on therapeutic outcomes in human heart disease and cancer. Yet biological time is rarely given clinical consideration. A key barrier is the absence of information on the what and where of molecular rhythms in the human body. Here, we have applied CYCLOPS, an algorithm designed to reconstruct sample order in the absence of time-of-day information, to the GTEx collection of 632 human donors contributing 4,292 RNA-seq samples from 13 distinct human tissue types. We identify rhythms in expression across the body that persist at the population-level. This includes a set of ubiquitous cyclers comprised of well-established circadian clock factors but also many genes without prior circadian context. Among thousands of tissue-divergent rhythms, we discover a set of genes robustly oscillating in cardiovascular tissue, including key drug targets relevant to heart disease. These results also have implications for genetic studies where circadian variability may have masked genetic influence. It is our hope that the human enCYCLOPedia helps drive the translation of circadian biology into prospective clinical trials in cardiology and many other therapeutic areas.\n\nOne Sentence SummaryBioinformatic analyses on thousands of human tissue samples reveals an enCYCLOPedia of rhythmic gene expression across the body and identifies key translational opportunities for circadian medicine in cardiovascular disease.

bioinformatics↗

bioRxiv2017

Network analysis of mass spectrometry imaging data from colorectal cancer identifies key metabolites common to metastatic development.

A deeper understanding of inter-tumor and intra-tumor heterogeneity is a critical factor for the advancement of next generation strategies against cancer. The heterogeneous morphology exhibited by solid tumors is mirrored by their metabolic heterogeneity. Defining the basic biological mechanisms that underlie tumor cell variability will be fundamental to the development of personalized cancer treatments. Variability in the molecular signatures found in local regions of cancer tissues can be captured through an untargeted analysis of their metabolic constituents. Here we demonstrate that DESI mass spectrometry imaging (MSI) combined with network analysis can provide detailed insight into the metabolic heterogeneity of colorectal cancer (CRC). We show that network modules capture signatures which differentiate tumor metabolism in the core and in the surrounding region. Moreover, module preservation analysis of network modules between patients with and without metastatic recurrence explains the inter-subject metabolic differences associated with diverse clinical outcomes such as metastatic recurrence.\n\nSignificanceNetwork analysis of DESI-MSI data from CRC human tissue reveals clinically relevant co-expression ion patterns associated with metastatic susceptibility. This delineates a more complex picture of tumor heterogeneity than conventional hard segmentation algorithms. Using tissue sections from central regions and at a distance from the tumor center, ion co-expression patterns reveal common features among patients who developed metastases (up of > 5 years) not preserved in patients who did not develop metastases. This offers insight into the nature of the complex molecular interactions associated with cancer recurrence. Presently, predicting CRC relapse is challenging, and histopathologically like-for-like cancers frequently manifest widely varying metastatic tendencies. Thus, the methodology introduced here more robustly defines the risk of metastases based on tumor biochemical heterogeneity.\n\nAuthor contributionsP.I., Z.T., R.C.G.: designed the study, developed the workflow, analyzed the data, interpreted the results, wrote the paper; N.S. collected the MS, performed the H...E staining, wrote the paper; L.D.: interpreted the results, wrote the paper; A.M.: collected the MS; A.S.: histological assessment; L.P.: collected the tissue specimens and clinical metadata; A.D.: collected the MS; H.K.: performed the H...E staining; R.M.: collected the tissue specimens and clinical metadata. R.G.: histological assessment; J.K.N: designed the study, edited the paper.

cancer biology↗

bioRxiv2018

PathMe: Merging and exploring mechanistic pathway knowledge

BackgroundThe complexity of representing biological systems is compounded by an ever-expanding body of knowledge emerging from multi-omics experiments. A number of pathway databases have facilitated pathway-centric approaches that assist in the interpretation of molecular signatures yielded by these experiments. However, the lack of interoperability between pathway databases has hindered the ability to harmonize these resources and to exploit their consolidated knowledge. Such a unification of pathway knowledge is imperative in enhancing the comprehension and modeling of biological abstractions.\n\nResultsHere, we present PathMe, a Python package that transforms pathway knowledge from three major pathway databases into a unified abstraction using Biological Expression Language as the pivotal, integrative schema. PathMe is complemented by a novel web application (freely available at https://pathme.scai.fraunhofer.de/) which allows users to comprehensively explore pathway crosstalks and compare areas of consensus and discrepancies.\n\nConclusionsThis work has harmonized three major pathway databases and transformed them into a unified schema in order to gain a holistic picture of pathway knowledge. We demonstrate the utility of the PathMe framework in: i) integrating pathway landscapes at the database level, ii) comparing the degree of consensus at the pathway level, and iii) exploring pathway crosstalk and investigating consensus at the molecular level.

bioinformatics↗

bioRxiv2016

Length control of filamentous structures in cells by the limiting pool mechanism

How the size of organelles in cells is controlled despite a constant turnover of their constituent parts is a central problem in cell biology. A general mechanism has been proposed based on the idea that an organelle grows by self-assembly of molecular subunits that freely diffuse in the cytoplasm. Assembly continues until the available pool of subunits is depleted to the point when the stochastic addition and removal of subunits is balanced, leading to a structure of well-defined size. Here we focus on length control of multiple filamentous structures in cells, such as actin cables and flagella. Using queueing theory and computation we show that the limiting pool mechanism leads to three different phases of assembly, starting with a rapid growth phase when all filaments quickly accumulate a large number of available subunits. Then, the slower growing filamentous structures enter a disassembly phase as they gradually lose all of their subunits to the faster growing structures. Finally, when multiple, equivalent fast-growing filaments are present, their lengths undergo protracted diffusive dynamics due to the stochastic swapping of subunits between them. This eventually leads to a broad, power-law distribution of filament lengths in steady state. Our findings demonstrate that the limiting-pool mechanism is incapable of controlling lengths of multiple filamentous structures that are assembled from a common pool of subunits, and at best, can produce only one filament of a well-defined size. Overall, our theoretical results reveal physical limitations of the limiting-pool mechanism of organelle size control.\n\nSignificance StatementWhat determines the size of organelles in cells is a classic problem in cell biology. Recent experiments on mitotic spindles, and nucleolus have singled out the limiting-pool mechanism of size control. As these structures assemble, they deplete a finite pool of subunits present in the cell, thereby reducing the rate of subunit addition. Eventually the stochastic addition and removal of subunits are balanced and a well-defined size is achieved. We find that, while the limiting-pool mechanism does control the size of an individual structure, it fails when multiple structures are competing for the same pool of subunits. In that case we predict large size fluctuations and that the fastest growing structure takes up practically all the subunits from the pool.

Biophysics↗

bioRxiv2016

System-wide quantitative proteomics of the metabolic syndrome in mice: genotypic and dietary effects

Advances in mass spectrometry have made the quantitative measurement of proteins across multiple samples a reality, allowing for the study of complex biological systems such as the metabolic syndrome. Although deregulation of lipid metabolism and increased hepatic storage of triacylglycerides are known to play a part in the onset of the metabolic syndrome, its molecular basis and dependency on dietary and genotypic factors are poorly characterized. Here, we used a rich experimental design with two different mouse strains, dietary and metabolic perturbations to generate a compendium of quantitative proteome data, using three mass spectrometry strategies. The data recapitulates known properties of the metabolic system and indicate differential molecular adaptation of the two mouse strains to perturbations, contributing to a better understanding of the metabolic syndrome. We show that high-quality, high-throughput proteomic datasets provide an unbiased broad overview of complex systems upon perturbation.\n\nHIGHLIGHTSO_LIRich experimental design with two mouse strains, dietary and metabolic perturbations\nC_LIO_LIThree mass spectrometry proteomic data collection strategies in one data compendium\nC_LIO_LISWATH-MS data with systematic perturbation provide a broad unbiased view of the system\nC_LIO_LIThe data reveals differential adaptation of molecular systems in two mouse strains\nC_LI

Systems Biology↗

bioRxiv2018

Contingency in the convergent evolution of a regulatory network: Dosage compensation in Drosophila

The repeatability or predictability of evolution is a central question in evolutionary biology, and most often addressed in experimental evolution studies. Here, we infer how genetically heterogeneous natural systems acquire the same molecular changes, to address how genomic background affects adaptation in natural populations. In particular, we take advantage of independently formed neo-sex chromosomes in Drosophila species that have evolved dosage compensation by co-opting the dosage compensation (MSL) complex, to study the mutational paths that have led to the acquisition of 100s of novel binding sites for the MSL complex in different species. This complex recognizes a conserved 21-bp GA-rich sequence motif that is enriched on the X chromosome, and newly formed X chromosomes recruit the MSL complex by de novo acquisition of this binding motif. We identify recently formed sex chromosomes in the Drosophila repleta and robusta species groups by genome sequencing, and generate genomic occupancy maps of the MSL complex to infer the location of novel binding sites. We find that diverse mutational paths were utilized in each species to evolve 100s of de novo binding motifs along the neo-X, including expansions of microsatellites and transposable element insertions. However, the propensity to utilize a particular mutational path differs between independently formed X chromosomes, and appears to be contingent on genomic properties of that species, such as simple repeat or transposable element density. This establishes the \"genomic environment\" as an important determinant in predicting the outcome of evolutionary adaptations.

evolutionary biology↗

bioRxiv2018

Subcellular Time Series Modeling of Heterogeneous Cell Protrusion

In this paper, a new biological modeling approach is proposed for predicting complex heterogeneous subcellular behaviors. Cell protrusion which initiates cell migration has a significant amount of subcellular heterogeneity in micrometer length and minute time scales. It is driven by actin polymerization, e.g., pushing the plasma membrane forward, and then regulated by a multitude of actin regulators. While mathematical modeling is central to system-level understandings of cell protrusion, most of the modeling is based on the ensemble average of actin regulator dynamics at the cellular or population levels, preventing from capturing the heterogeneous cellular activities. With these in mind, a systematic modeling framework is proposed in this paper for predicting velocities of heterogeneous protrusion of migrating cells driven by multiple molecular mechanisms. The modeling framework is developed through the integration of the multiple AutoRegressive eXogenous (ARX) models employing probability density input variables. Unlike conventional ARX models, it provides an effective framework for modeling heterogeneous subcellular behaviors with complex nonlinearities and uncertainties of dynamic systems. To train and validate the proposed model, numerous subcellular time series are extracted from time-lapse movies of migrating PtK1 cells using spinning disk confocal microscope: The current edge velocities and fluorescent intensities of mDia1, actin at the leading edge are used as the input while the future cell edge velocities are selected as an output. It is demonstrated that the proposed approach is highly effective in predicting the future trends of heterogeneous cell protrusion. In particular, by capturing the various multiple activities from the dataset, it is expected that it would improve the understanding of the molecular mechanism underlying cellular and subcellular heterogeneity.

systems biology↗

bioRxiv2018

Periodically driven force protein translocation through a α-hemolysin biological nano-pore

We study the translocation of protein pulled under the action of time periodically external driving force through -hemolysin nano-pore using Langevin molecular dynamical simulation. We observe that time depended external pulling force could enhance to more efficient translocation process as compared to protein translocation driven by constant external pulling force. We characterized the time depended force driven translocation mechanism by studying the gain in translocation as a function of frequency. We also present Golestanian plot which shows the modulated evolutions of number of translocation peptides, and of the probability distribution function with frequency as a results of the transmission of force oscillation to translocation dynamics.

bioinformatics↗

bioRxiv2015

A cell-free framework for biological systems engineering

SUMMARYWhile complex dynamic biological networks control gene expression and metabolism in all living organisms, engineering comparable synthetic networks remains challenging1,2. Conducting extensive, quantitative and rapid characterization during the design and implementation process of synthetic networks is currently severely limited due to cumbersome molecular cloning and the difficulties associated with measuring parts, components and systems in cellular hosts. Engineering gene networks in a cell-free environment promises to be an efficient and effective approach to rapidly develop novel biological systems and understand their operating regimes3-5. However, it remains questionable whether complex synthetic networks behave similarly in cells and a cell-free environment, which is critical for in vitro approaches to be of significance to biological engineering. Here we show that synthetic dynamic networks can be readily implemented, characterized, and engineered in a cell-free framework and consequently transferred to cellular hosts. We implemented and characterized the \"repressilator\"6, a three-node negative feedback oscillator in vitro. We then used our cell-free framework to engineer novel three-node, four-node, and five-node negative feedback architectures going from the characterization of circuit components to the rapid analysis of complete networks. We validated our cell-free approach by transferring these novel three-node and five-node oscillators to Escherichia coli, resulting in robust and synchronized oscillations reflecting the in vitro observation. We demonstrate that comprehensive circuit engineering can be performed in a cell-free system and that the in vitro results have direct applicability in vivo. Cell-free synthetic biology thus has the potential to drastically speed up design-build-test cycles in biological engineering and enable the quantitative characterization of synthetic and natural networks.

Synthetic Biology↗

bioRxiv2017

Sex differences in gene regulation in the dorsal root ganglion after nerve injury

Pain is a subjective experience derived from complex interactions among biological, environmental, and psychosocial pathways. Sex differences in pain sensitivity and chronic pain prevalence are well established. However, the molecular causes underlying these sex dimorphisms are poorly understood particularly with regard to the role of the peripheral nervous system. Here we sought to identify shared and distinct gene networks functioning in the peripheral nervous systems that may contribute to sex differences of pain after nerve injury. We performed RNA-seq on dorsal root ganglia following chronic constriction injury of the sciatic nerve in male and female rats. Analysis from paired naive and injured tissues showed that 1456 genes were differentially expressed between sexes. Appreciating sex-related gene expression differences and similarities in neuropathic pain models may help to improve the translational relevance to clinical populations and efficacy of clinical trials of this major health issue.

neuroscience↗

bioRxiv2017

Effects of mutation and selection on plasticity of TDH3 promoter activity in Saccharomyces cerevisiae

Phenotypic plasticity is an evolvable property of biological systems that can arise from environment-specific regulation of gene expression. To better understand the evolutionary and molecular mechanisms that give rise to plasticity in gene expression, we quantified the effects of 235 single nucleotide mutations in the Saccharomyces cerevisiae TDH3 promoter (PTDH3) on the activity of this promoter in media containing glucose, galactose, or glycerol as a carbon source. We found that the distributions of mutational effects differed among environments because many mutations altered the plastic response exhibited by the wild type allele. Comparing the effects of these mutations to the effects of 30 PTDH3 polymorphisms on expression plasticity in the same environments provided evidence of natural selection acting to prevent the plastic response in PTDH3 activity between glucose and galactose from becoming larger. The largest changes in expression plasticity were observed between fermentable (glucose or galactose) and nonfermentable (glycerol) carbon sources and were caused by mutations located in the RAP1 and GCR1 transcription factor binding sites. Mutations altered expression plasticity most frequently between the two fermentable environments, however, with mutations causing significant changes in plasticity between glucose and galactose distributed throughout the promoter, suggesting they might affect chromatin structure. Taken together, these results provide insight into the molecular mechanisms underlying gene-by-environment interactions affecting gene expression as well as the evolutionary dynamics affecting natural variation in plasticity of gene expression.\n\nSignificance StatementFrom seasonal variation in the color of butterfly wings to trees bending toward the light, organisms often change in response to their environment. These changes, known as phenotypic plasticity, can result from differences in how genes are expressed among environments. Mutations causing environment-specific changes in gene expression provide raw material for phenotypic plasticity, but their frequency, effect size and direction of effects among environments are not well understood. This study shows that mutations in the promoter of a yeast metabolic gene often display environment-dependent effects on gene expression and that these environment-dependent effects have been shaped by selection in natural populations.

genetics↗

bioRxiv2017

The evolutionary history of the current global Ramularia collo-cygni epidemic

Ramularia Leaf Spot (RLS) has emerged as a threat for barley production in many regions of the world. Late appearance of unspecific symptoms caused that Ramularia collo-cygni could only by molecular diagnostics be detected as the causal agent of RLS. Although recent research has shed more light on the biology and genomics of the pathogen, the cause of the recent global spread remains unclear.\n\nTo address urgent questions, especially on the emergence to a major disease, life-cycle, transmission, and quick adaptation to control measures, we de-novo sequenced the genome of R. collo-cygni (urug2 isolate). Additionally, we sequenced fungal RNA from 6 different conditions, which allowed for an improved genome annotation. This resulted in a high quality draft assembly of about 32 Mb, with only 78 scaffolds with an N50 of 2.1 Mb. The overall annotation enabled the prediction of 12.346 high confidence genes. Genomic comparison revealed that R. collo-cygni has significantly diverged from related Dothidiomycetes, including gain and loss of putative effectors, however without obtaining species-specific genome features.\n\nTo evaluate the species-wide genetic diversity, we sequenced the genomes of 19 R. collo-cygni isolates from multiple geographic locations and diverse hosts and mapped sequences to our reference genome. Admixture analyses show that R. collo-cygni is world-wide genetically uniform and that samples do not show a strong clustering on either geographical location or host species. To date, the teleomorph of R. collo-cygni has not been observed. Analysis of linkage disequilibrium shows that in the world-wide sample set there are clear signals of recombination and thus sexual reproduction, however these signals largely disappear when excluding three outliers samples, suggesting that the main global expansion of R. collo-cygni comes from mixed or clonally propagating populations. We further analysed the historic population size (Ne) of R. collo-cygni using Bayesian simulations.\n\nWe discuss how our genomic data and population genetics analysis can help understand the current R. collo-cygni epidemic and provide different hypothesis that are supported by our data. We specifically highlight how recombination, clonal spreading and lack of host-specificity could further support global epidemics of this increasingly recognized plant disease and suggest specific approaches to combat this pathogen.

plant biology↗

bioRxiv2018

Elimination of PCR duplicates in RNA-seq and small RNA-seq using unique molecular identifiers

RNA-seq and small RNA-seq are powerful, quantitative tools to study gene regulation and function. Common high-throughput sequencing methods rely on polymerase chain reaction (PCR) to expand the starting material, but not every molecule amplifies equally, causing some to be overrepresented. Unique molecular identifiers (UMIs) can be used to distinguish undesirable PCR duplicates derived from a single molecule and identical but biologically meaningful reads from different molecules. We have incorporated UMIs into RNA-seq and small RNA-seq protocols and developed tools to analyze the resulting data. Our UMIs contain stretches of random nucleotides whose lengths sufficiently capture diverse molecule species in both RNA-seq and small RNA-seq libraries generated from mouse testis. Our approach yields high-quality data while allowing unique tagging of all molecules in high-depth libraries. Using simulated and real datasets, we demonstrate that our methods increase the reproducibility of RNA-seq and small RNA-seq data. Notably, we find that the amount of starting material and sequencing depth, but not the number of PCR cycles, determine PCR duplicate frequency. Finally, we show that computational removal of PCR duplicates based only on their mapping coordinates introduces substantial bias into data analysis.

genomics↗

bioRxiv2018

Ribo-tag translatomic profiling of Drosophila oenocyte reveals down-regulation of peroxisome and mitochondria biogenesis under aging and oxidative stress

BackgroundAging is accompanied with loss of tissue homeostasis and accumulation of cellular damages. As one of the important metabolic centers, aged liver shows altered lipid metabolism, impaired detoxification pathway, increased inflammation and oxidative stress response. However, the mechanisms for these age-related changes still remain unclear. In fruit flies, Drosophila melanogaster, liver-like functions are controlled by two distinct tissues, fat body and oenocytes. Although the role of fat body in aging regulation has been well studied, little is known about how oenocytes age and what are their roles in aging regulation. To address these questions, we used cell-type-specific ribosome profiling (RiboTag) to study the impacts of aging and oxidative stress on oenocyte translatome in Drosophila.\n\nResultsWe show that aging and oxidant paraquat significantly increased the levels of reactive oxygen species (ROS) in adult oenocytes of Drosophila, and aged oenocytes exhibited reduced sensitivity to paraquat treatment. Through RiboTag sequencing, we identified 3324 and 949 differentially expressed genes in oenocytes under aging and paraquat treatment, respectively. Aging and paraquat exhibit both shared and distinct regulations on oenocyte translatome. Among all age-regulated genes, mitochondrial, proteasome, peroxisome, fatty acid metabolism, and cytochrome P450 pathways were down-regulated, whereas DNA replication and glutathione metabolic pathways were up-regulated. Interestingly, most of the peroxisomal genes were down-regulated in aged oenocytes, including peroxisomal biogenesis factors and beta-oxidation genes. Further analysis of the oenocyte translatome showed that oenocytes highly expressed genes involving in liver-like processes (e.g., ketogenesis). Many age-related transcriptional changes in oenocytes are similar to aging liver, including up-regulation of Ras/MAPK signaling pathway and down-regulation of peroxisome and fatty acid metabolism.\n\nConclusionsOur oenocyte-specific translatome analysis identified many genes and pathways that are shared between Drosophila oenocytes and mammalian liver, highlighting the molecular and functional similarities between the two tissues. Many of these genes are altered in both aged oenocytes and aged liver, suggesting a conserved molecular mechanism underlying oenocyte and liver aging. Thus, our translatome analysis will contribute significantly to the understanding of oenocyte biology, and its role in lipid metabolism, stress response and aging regulation.

genomics↗

bioRxiv2018

Coarse-Grained Model of the SNARE Complex Shows that Quick Zippering Requires Partial Assembly

Neuronal transmitters are released from nerve terminals via the fusion of synaptic vesicles with the presynaptic membrane. Vesicles become attached to the membrane via the SNARE complex. The SNARE complex comprises the vesicle associate protein Synaptobrevin (Syb), the membrane associated protein syntaxin (Syx), and the cytosolic protein SNAP25, which together form a four-helical bundle. The full assembly of Syb onto the core SNARE bundle promotes vesicle fusion. We investigated SNARE assembly using a coarse-grained model of the SNARE complex. The model retains chemical specificity, and was calibrated using single molecule experiments and all-atom molecular dynamics simulations. Steered force-control simulations of SNARE unzippering by peeling off Syb were used to set up initial disassembled states of the SNARE complex. From these states, the assembly process was simulated. We found that if Syb is in helical form, then the SNARE complex assembles rapidly, on a sub-microsecond time-scale. We found that assembly times grow exponentially with separation distance between Syb and Syx C-termni. The formation of helical turns is likely to substantially decelerate the assembly, consistent with single molecule force experiments that show SNARE assembly duration on the time-scale of hundreds of ms. Since synaptic vesicle fusion occurs at a sub-millisecond time-scale, our results indicate that for biologically relevant rapid assembly the SNARE complex needs to be partially zippered and its constituent helices brought into proximity, possibly by means of molecular chaperones.

biophysics↗