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bioRxiv2026

An M-learner approach for heterogeneous mediation analysis with high-dimensional omics mediators

Causal mediation analysis is widely used to identify biological pathways linking exposures to outcomes, but most methods assume homogeneous mediation effects across individuals. In high-dimensional omics settings, this assumption can mask important heterogeneity driven by demographic, genetic, or environmental factors. We propose the M-high-learner, a flexible framework for detecting heterogeneous mediation effects with high-dimensional mediators. The method identifies mediators with subgroup-specific indirect effects while distinguishing them from null or homogeneous signals and controlling the type I error rate. It is computationally efficient, scalable, and yields interpretable sub-types. Simulation studies show that the proposed approach achieves high power while maintaining accurate error control. Applications to the Framingham Heart Study and the Multi-Ethnic Study of Atherosclerosis reveal that the mediation role of gene expression in sexs effect on high-density lipoprotein varies across subgroups defined by body mass index and age. Our framework provides a practical tool for uncovering heterogeneous biological mechanisms in high-dimensional genomic studies. Author SummaryBiological processes linking risk factors to disease often differ across individuals, but many existing methods assume these processes are the same for everyone. This can hide important differences between groups. We developed a powerful method to identify when these pathways vary across subgroups using large-scale molecular data. Our approach detects differences in how intermediate biological factors contribute to outcomes in populations defined by characteristics such as age and body mass index. Applying our method to population studies, we found that some biological pathways operate differently across groups, suggesting that key mechanisms may be missed when differences are ignored. Our work provides a tool to better understand how disease-related processes vary across individuals, which may support more targeted and personalized approaches to health research.

bioinformatics↗

bioRxiv2017

Drosophila beta-Tubulin 97EF is upregulated at low temperature and stabilizes microtubules

Summary statementEctotherms thrive within an often remarkable temperature range. At low temperature, betaTub97EF, a beta-tubulin paralog stabilizing microtubules, is upregulated in a tissue-specific manner in the fly Drosophila melanogaster.\n\nAbstractCells in ectotherms function normally within an often wide temperature range. As temperature dependence is not uniform across all the distinct biological processes, acclimation presumably requires complex regulation. The molecular mechanisms coping with the disruptive effects of temperature variation are still poorly understood. Interestingly, one of five different beta-tubulin paralogs, betaTub97EF, was among the genes up-regulated at low temperature in cultured Drosophila cells. As microtubules are known to be cold-sensitive, we analyzed whether betaTub97EF protects microtubules at low temperatures. During development at the optimal temperature (25{degrees}C), betaTub97EF was expressed in a tissue-specific pattern primarily in the gut. There, as well as in hemocytes, expression was increased at low temperature (14{degrees}C). While betaTub97EF mutants were viable and fertile at 25{degrees}C, their sensitivity within the well-tolerated range was slightly enhanced during embryogenesis specifically at low temperatures. Changing beta-tubulin isoform ratios in hemocytes demonstrated that beta-Tubulin 97EF has a pronounced microtubule stabilizing effect. Moreover, betaTub97EF is required for normal microtubule stability in the gut. These results suggest that betaTub97EF up-regulation at low temperature contributes to acclimation by stabilizing microtubules.

developmental biology↗

bioRxiv2017

Monomerization of Far-Red Fluorescent Proteins

Anthozoa class red fluorescent proteins (RFPs) are frequently used as biological markers, with far-red emitting variants ({lambda}em ~ 600 - 900 nm) sought for whole animal imaging because biological tissues are permeable to light in this range. A barrier to the use of naturally occurring RFP variants as molecular markers is that all are tetrameric, which is not ideal for cell biological applications. Efforts to engineer monomeric RFPs have usually produced dimmer and blue-shifted variants, as the chromophore is sensitive to small structural perturbations. In fact, despite much effort, only four native RFPs have been successfully monomerized, leaving the vast majority of RFP biodiversity untapped in biomarker development. Here we report the generation of monomeric variants of HcRed and mCardinal, both far-red dimers, and describe a comprehensive methodology for the rapid monomerization of novel red-shifted oligomeric RFPs. Among the resultant variants, is mKelly1 (emission maximum: {lambda}em = 656 nm), which along with the recently reported mGarnet2 (1), forms a new class of bright, monomeric, far-red FPs.

biochemistry↗

bioRxiv2018

A meta-analysis of Planarian: an animal model useful to understand the effect of magnetic field

The planarians research since the first description until nowadays has a broad spectrum of topics. The present paper deals on a meta-analysis which identified as a problem the lack of consolidate information and data analysis about the use of planarian as animal model, and specifically the use of magnetic field in regeneration experiments. To conduct the meta-analysis 1255 papers published since 1955 to 2017 were analysed, identifying the Stem cell biology and regeneration as the most published topic, with 276 papers, followed by molecular and cellular analyses (238), genetics (175), inter and transdisciplinary research (107), ecotoxicological evaluations (102), animal model (67), ecological and biological studies (56), magnetic field (57), developmental biology (32) and RNA regulation (31).Other statistics and metrics indicators were taken in to account like total of papers and distribution per year, distribution of paper by journals and selection of main journals according to the number of published papers, most cited papers, authors and countries and distribution of papers by countries. Finally, were analysed those papers with Planarians research using magnetic field, all of them published during the last three years. It was an evidence that this topic is becoming a trending with rising interest, being the most reported species to study the magnetic field effects Dugesia spp. and Girardia sp.\n\nSummary statementThis work presents a meta-analysis which allows consolidating information and a better understanding of trends in Planarian researches, emphasizing in the use of magnetic field.

cell biology↗

bioRxiv2017

A role for the Tgf-β/Bmp co-receptor Endoglin in the molecular oscillator that regulates the hair follicle cycle

The hair follicle is a biological oscillator that alternates growth, regression and rest phases driven by the sequential activation of the proliferation/differentiation programs of resident stem cell populations. The activation of hair follicle stem cell niches and subsequent entry into the growing phase is mainly regulated by Wnt/{beta}-catenin signalling, while regression and resting phases are mainly regulated by Tgf-{beta}/Bmp/Smad activity. A major question still unresolved is the nature of the molecular switch that dictates the coordinated transition between both signalling pathways. Here we have focused on the role of Endoglin (Eng), a key coreceptor for members of the Tgf-{beta}/Bmp family of growth factors.\n\nUsing an Eng haploinsufficient mouse model we report that Eng is required to maintain a correct follicle cycling pattern and for an adequate stimulation of hair follicle stem cell niches. We further report that {beta}-catenin binds to the Eng promoter depending on Bmp signalling. Moreover, we show that {beta}-catenin interacts with Smad4 in a Bmp/Eng dependent context and both proteins act synergistically to activate Eng promoter transcription. These observations point to the existence of a growth/rest switching mechanism in the hair follicle that is based on an Eng-dependent feedback crosstalk between Wnt/{beta}-catenin and Bmp/Smad signals.

cell biology↗

bioRxiv2018

Disrupted structure and aberrant function of CHIP mediates the loss of motor and cognitive function in preclinical models of cerebellar CHIPopathy

CHIP (carboxyl terminus of heat shock 70-interacting protein) has long been recognized as an active member of the cellular protein quality control system given the ability of CHIP to function as both a co-chaperone and ubiquitin ligase. Mutations in CHIP are the driver of spinocerebellar autosomal recessive 16 (SCAR16), or cerebellar CHIPopathy, as we initially discovered this disease was caused by a loss of CHIP ubiquitin ligase function. The initial mutation describing SCAR16 was a missense mutation in the ubiquitin ligase domain of CHIP (p.T246M). Using multiple biophysical and cellular approaches, we demonstrate that T246M mutation results in structural disorganization and misfolding of the CHIP U-box domain, promoting oligomerization, and increased proteasome-dependent turnover. CHIP-T246M has no ligase activity, but maintains interactions with chaperones and alters the co-chaperone function of CHIP. To establish preclinical models of SCAR16, we engineered T246M at the endogenous locus in both mice and rats. Animals homozygous for T246M had both cognitive and motor cerebellar dysfunction distinct from those observed in the CHIP null animal model, as well as deficits in learning and memory, reflective of the cognitive deficits reported in SCAR16 patients. We conclude that the T246M mutation is not equivalent to the total loss of CHIP, supporting the concept that disease-causing CHIP mutations have different biophysical and functional repercussions on CHIP function that may directly correlate to the spectrum of clinical phenotypes observed in SCAR16 patients. Our findings both further expand our basic understanding of CHIP biology and provide meaningful mechanistic insight underlying the molecular drivers of SCAR16 disease pathology, which may be used to inform the development of novel therapeutics for this devastating disease.

animal behavior and cognition↗

bioRxiv2018

Biparental inheritance of chloroplasts is controlled by lipid biosynthesis

In most eukaryotes, organellar genomes are transmitted preferentially by the mother, but molecular mechanisms and evolutionary forces underlying this fundamental biological principle are far from understood. It is believed that biparental inheritance promotes competition between the cytoplasmic organelles and allows the spread of so-called selfish cytoplasmic elements. Those can be, for example, fast replicating or aggressive chloroplasts (plastids) that are incompatible with the hybrid nuclear genome and therefore maladaptive.\n\nHere we show that the ability of plastids to compete against each other is a metabolic phenotype determined by extremely rapidly evolving genes in the plastid genome of the evening primrose Oenothera. Repeats in the regulatory region of accD (the plastid-encoded subunit of the acetyl-CoA carboxylase, which catalyzes the first and rate limiting step of lipid biosynthesis), as well as in ycf2 (a giant reading frame of still unknown function), are responsible for the differences in competitive behavior of plastid genotypes. Polymorphisms in these genes influence lipid synthesis and most likely profiles of the plastid envelope membrane. These in turn determine plastid division and/or turn-over rates and hence competitiveness. This work uncovers cytoplasmic drive loci controlling the outcome of biparental chloroplast transmission. Here, they define the mode of chloroplast inheritance, since plastid competitiveness can result in uniparental inheritance (through elimination of the \"weak\" plastid) or biparental inheritance (when two similarly \"strong\" plastids are transmitted).\n\nSignificance statementPlastids and mitochondria are usually uniparentally inherited, typically maternally. When the DNA-containing organelles are transmitted to the progeny by both parents, evolutionary theory predicts that the maternal and paternal organelles will compete in the hybrid. As their genomes do not undergo sexual recombination, one organelle will \"try\" to outcompete the other, thus favoring the evolution and spread of aggressive cytoplasms. The investigations described here in the evening primrose, a model species for biparental plastid transmission, have discovered that chloroplast competition is a metabolic phenotype. It is conferred by rapidly evolving genes that are encoded on the chloroplast genome and control lipid biosynthesis. Due to their high mutation rate these loci can evolve and become fixed in a population very quickly.

genetics↗

bioRxiv2018

Genome structure and evolution of Antirrhnum majus L.

Snapdragon (Antirrhinum majus L.), a member of Plantaginaceae, is an important model for plant genetics and molecular studies on plant growth and development, transposon biology and self-incompatibility. Here we report a high-quality genome assembly of A. majus cultivated JI7 (A. majus cv.JI7) of a 510 Mb with 37,714 annotated protein-coding genes. The scaffolds covering 97.12% of the assembled genome were anchored on 8 chromosomes. Comparative and evolutionary analyses revealed that Plantaginaceae and Solanaceae diverged from their most recent ancestor around 62 million years ago (MYA). We also revealed the genetic architectures associated with complex traits such as flower asymmetry and self-incompatibility including a unique TCP duplication around 46-49 MYA and a near complete{psi} S-locus of ca.2 Mb. The genome sequence obtained in this study not only provides the first genome sequenced from Plantaginaceae but also bring the popular plant model system of Antirrhinum into a genomic age.

genomics↗

bioRxiv2017

From word models to executable models of signaling networks using automated assembly

Word models (natural language descriptions of molecular mechanisms) are a common currency in spoken and written communication in biomedicine but are of limited use in predicting the behavior of complex biological networks. We present an approach to building computational models directly from natural language using automated assembly. Molecular mechanisms described in simple English are read by natural language processing algorithms, converted into an intermediate representation and assembled into executable or network models. We have implemented this approach in the Integrated Network and Dynamical Reasoning Assembler (INDRA), which draws on existing natural language processing systems as well as pathway information in Pathway Commons and other online resources. We demonstrate the use of INDRA and natural language to model three biological processes of increasing scope: (i) p53 dynamics in response to DNA damage; (ii) adaptive drug resistance in BRAF-V600E mutant melanomas; and (iii) the RAS signaling pathway. The use of natural language for modeling makes routine tasks more efficient for modeling practitioners and increases the accessibility and transparency of models for the broader biology community.\n\nStandfirst textINDRA uses natural language processing systems to read descriptions of molecular mechanisms and assembles them into executable models.\n\nHighlightsO_LIINDRA decouples the curation of knowledge as word models from model implementation\nC_LIO_LIINDRA is connected to multiple natural language processing systems and can draw on information from curated databases\nC_LIO_LIINDRA can assemble dynamical models in rule-based and reaction network formalisms, as well as Boolean networks and visualization formats\nC_LIO_LIWe used INDRA to build models of p53 dynamics, resistance to targeted inhibitors of BRAF in melanoma, and the Ras signaling pathway from natural language\nC_LI

systems biology↗

bioRxiv2018

The RhoGAP SPV-1 regulates calcium signaling to control the contractility of the C. elegans spermatheca during embryo transits.

Contractility of the non-muscle and smooth muscle cells that comprise biological tubing is regulated by the Rho-ROCK and calcium signaling pathways. Although many molecular details about these signaling pathways are known, less is known about how they are coordinated spatiotemporally in biological tubes. The spermatheca of the C. elegans reproductive system enables study of the signaling pathways regulating actomyosin contractility in live adult animals. The RhoGAP SPV-1 was previously identified as a negative regulator of RHO-1/Rho and spermathecal contractility. Here, we uncover a role for SPV-1 as a key regulator of calcium signaling. spv-1 mutants expressing the calcium indicator GCaMP in the spermatheca exhibit premature calcium release, elevated calcium levels, and disrupted spatial regulation of calcium signaling during spermathecal contraction. Although RHO-1 is required for spermathecal contractility, RHO-1 does not play a significant role in regulating calcium. In contrast, activation of CDC-42 recapitulates many aspects of spv-1 mutant calcium signaling. Depletion of cdc-42 by RNAi does not suppress the premature or elevated calcium signal seen in spv-1 mutants, suggesting other targets remain to be identified. Our results suggest SPV-1 works through both the Rho-ROCK and calcium signaling pathways to coordinate cellular contractility.\n\nHighlight SummaryThrough in vivo imaging of the calcium sensor GCaMP, we show that the RhoGAP SPV-1 is a key regulator of calcium signaling in the C. elegans spermatheca. Our data suggests SPV-1 acts at least partially through the small GTPase CDC-42 to modulate calcium signaling, while also acting on RHO-1 to modulate Rho-ROCK signaling. This places SPV-1 as a central regulator of cellular contractility.

cell biology↗

bioRxiv2017

Molecular characterization of breast and lung tumors by integration of multiple data types with sparse-factor analysis

Effective cancer treatment is crucially dependent on the identification of the biological processes that drive a tumor. However, multiple processes may be active simultaneously in a tumor. Clustering is inherently unsuitable to this task as it assigns a tumor to a single cluster. In addition, the wide availability of multiple data types per tumor provides the opportunity to profile the processes driving a tumor more comprehensively.\n\nHere we introduce Functional Sparse-Factor Analysis (funcSFA) to address these challenges. FuncSFA integrates multiple data types to define a lower dimensional space capturing the relevant variation. A tailor-made module associates biological processes with these factors. FuncSFA is inspired by iCluster, which we improve in several key aspects. First, we increase the convergence efficiency significantly, allowing the analysis of multiple molecular datasets that have not been pre-matched to contain only concordant features. Second, FuncSFA does not assign tumors to discrete clusters, but identifies the dominant driver processes active in each tumor. This is achieved by a regression of the factors on the RNA expression data followed by a functional enrichment analysis and manual curation step.\n\nWe apply FuncSFA to the TCGA breast and lung datasets. We identify EMT and Immune processes common to both cancer types. In the breast cancer dataset we recover the known intrinsic subtypes and identify additional processes. These include immune infiltration and EMT, and processes driven by copy number gains on the 8q chromosome arm. In lung cancer we recover the major types (adenocarcinoma and squamous cell carcinoma) and processes active in both of these types. These include EMT, two immune processes, and the activity of the NFE2L2 transcription factor.\n\nIn summary, FuncSFA is a robust method to perform discovery of key driver processes in a collection of tumors through unsupervised integration of multiple molecular data types and functional annotation.\n\nAuthor SummaryIn order to select effective cancer treatment, we need to determine which biological processes are active in a tumor. To this end, tumors have been quantified by high dimensional molecular measurements such as RNA sequencing and DNA copy number profiling. In order to support decision making, these measurements need to be condensed into interpretable summaries. Such summaries can be made interpretable by connecting them to biological processes.\n\nBiological process activity is continuous and multiple biological processes are taking place in a single tumor. Therefore, the biological processes associated with a tumor are misrepresented by clustering, which tries to put every tumor in a single cluster. In the method introduced in this paper (funcSFA), molecular measurements are summarized into a small number factors. A factor is a continuous value per tumor that aims to represent the activity of a biological process.\n\nWhen applied to breast and lung cancer, funcSFA identifies factors covering well known biology of these tumor types. FuncSFA also finds novel factors covering biology whose importance is not yet widely recognized in these tumor types. Some of the factors suggest treatment opportunities that can be further investigated in cell lines and mice.

bioinformatics↗

bioRxiv2018

A data mining paradigm for identifying key factors in biological processes using gene expression data

A large volume of biological data is being generated for studying mechanisms of various biological processes. These precious data enable large-scale computational analyses to gain biological insights. However, it remains a challenge to mine the data efficiently for knowledge discovery. The heterogeneity of these data makes it difficult to consistently integrate them, slowing down the process of biological discovery. We introduce a data processing paradigm to identify key factors in biological processes via systematic collection of gene expression datasets, primary analysis of data, and evaluation of consistent signals. To demonstrate its effectiveness, our paradigm was applied to epidermal development and identified many genes that play a potential role in this process. Besides the known epidermal development genes, a substantial proportion of the identified genes are still not supported by gain- or loss-of-function studies, yielding many novel genes for future studies. Among them, we selected a top gene for loss-of-function experimental validation and confirmed its function in epidermal differentiation, proving the ability of this paradigm to identify new factors in biological processes. In addition, this paradigm revealed many key genes in cold-induced thermogenesis using data from cold-challenged tissues, demonstrating its generalizability. This paradigm can lead to fruitful results for studying molecular mechanisms in an era of explosive accumulation of publicly available biological data.

bioinformatics↗

bioRxiv2016

NaviCom: A web application to create interactive molecular network portraits using multi-level omics data

Human diseases such as cancer are routinely characterized by high-throughput molecular technologies, and multi-level omics data are accumulated in public databases at increasing rate. Retrieval and visualization of these data in the context of molecular network maps can provide insights into the pattern of molecular functions encompassed by an omics profile. In order to make this task easy, we developed NaviCom, a Python package and web platform for visualization of multi-level omics data on top of biological network maps. NaviCom is bridging the gap between cBioPortal, the most used resource of large-scale cancer omics data and NaviCell, a data visualization web service that contains several molecular network map collections. NaviCom proposes several standardized modes of data display on top of molecular network maps, allowing to address specific biological questions. We illustrate how users can easily create interactive network-based cancer molecular portraits via NaviCom web interface using the maps of Atlas of Cancer Signaling Network (ACSN) and other maps. Analysis of these molecular portraits can help in formulating a scientific hypothesis on the molecular mechanisms deregulated in the studied disease.

systems biology↗

bioRxiv2018

FUN-LOV: Fungal LOV domains for optogenetic control of gene expression and flocculation in yeast

Optogenetic switches permit accurate control of gene expression upon light stimulation. These synthetic switches have become a powerful tool for gene regulation, allowing modulation of customized phenotypes, overcoming the obstacles of chemical inducers and replacing their use by an inexpensive resource: light. In this work, we implemented FUN-LOV; an optogenetic switch based on the photon-regulated interaction of WC-1 and VVD, two LOV (Light Oxygen Voltage) blue-light photoreceptors from the fungus Neurospora crassa. When tested in yeast, FUN-LOV yields light-controlled gene expression with exquisite temporal resolution, and a broad dynamic range of over 1300-fold, as measured by a luciferase reporter. We also tested the FUN-LOV switch for heterologous protein expression in Saccharomyces cerevisiae, where Western blot analysis confirmed strong induction upon light stimulation, surpassing by 2.5 times the levels achieved with a classic GAL4/galactose chemical inducible system. Additionally, we utilized FUN-LOV to control the ability of yeast cells to flocculate. Light-controlled expression of the flocculin encoding gene FLO1, by the FUN-LOV switch, yielded Flocculation in Light (FIL), whereas the light-controlled expression of the co-repressor TUP1 provided Flocculation in Darkness (FID). Overall, the results revealed the potential of the FUN-LOV optogenetic switch to control two biotechnologically relevant phenotypes such as heterologous protein expression and flocculation, paving the road for the engineering of new yeast strains for industrial applications. Importantly, FUN-LOV s ability to accurately manipulate gene expression, with a high-temporal dynamic range, can be exploited in the analysis of diverse biological processes in various organisms.\n\nImportanceOptogenetic switches are molecular devices which allow the control of different cellular processes by light, such as gene expression, providing a versatile alternative to chemical inducers. Herein, we report a novel optogenetic switch (FUN-LOV) based on the LOV-domain interaction of two blue-light photoreceptors (WC-1 and VVD) from the fungus N. crassa. In yeast cells, FUN-LOV allowed tight regulation of gene expression, with low background in darkness and a highly dynamic and potent control by light. We used FUN-LOV to optogenetically manipulate, in yeast, two biotechnologically relevant phenotypes: heterologous protein expression and flocculation, resulting in strains with potential industrial applications. Importantly, FUN-LOV can be implemented in diverse biological platforms to orthogonally control a multitude of cellular processes.

microbiology↗

bioRxiv2018

A Single Adaptive Mutation in Sodium Taurocholate Cotransporting Polypeptide Induced by Hepadnaviruses Determines Virus Species-specificity

Hepatitis B virus (HBV) and its hepadnavirus relatives infect a wide range of vertebrates from fish to human. Hepadnaviruses and their hosts have a long history of acquiring adaptive mutations. However, there are no reports providing direct molecular evidence for such a coevolutionary \"arms race\" between hepadnaviruses and their hosts. Here, we present evidence suggesting the adaptive evolution of the sodium taurocholate cotransporting polypeptide (NTCP), an HBV receptor, has been influenced by virus infection. Evolutionary analysis of the NTCP-encoding genes from 20 mammals showed that most NTCP residues are highly conserved among species, exhibiting evolution under negative selection (dN/dS < 1); this observation implies that the evolution of NTCP is restricted by maintaining its original protein function. However, 0.7 % of NTCP amino acid (aa) residues exhibit rapid evolution under positive selection (dN/dS > 1). Notably, a substitution at aa 158, a positively selected residue, converting the human NTCP to a monkey-type sequence abrogated the capacity to support HBV infection; conversely, a substitution at this residue converting the monkey Ntcp to the human sequence was sufficient to confer HBV susceptibility. Together, these observations suggested that positive selection at aa 158 was induced by virus infection. Moreover, the aa 158 sequence determined attachment of the HBV envelope protein to host cell, demonstrating the mechanism whereby HBV infection would create positive selection at this residue in NTCP. In summary, we provide the first evidence in agreement with the function of hepadnavirus as a driver for inducing an adaptive mutation in host receptor.\n\nImportanceHepatitis B virus (HBV) and its hepadnavirus relatives infect a wide range of vertebrates, with a long infectious history (hundreds of millions of years). Such a long history generally allows adaptive mutations in hosts to escape from infection, while simultaneously allowing adaptive mutations in viruses to overcome host barriers. However, there is no published molecular evidence for such a coevolutionary \"arms race\" between hepadnaviruses and hosts. In the present study, we performed coevolutionary phylogenetic analysis between hepadnaviruses and the sodium taurocholate cotransporting polypeptide (NTCP), an HBV receptor, combined with virological experimental assays for investigating the biological significance of NTCP sequence variation. Our data provide the first molecular evidences supporting that HBV-related hepadnaviruses drive adaptive evolution in the NTCP sequence, including a mechanistic explanation of how NTCP mutations determine host viral susceptibility. Our novel insights enhance our understanding of how hepadnaviruses evolved with their hosts, permitting the acquisition of strong species-specificity.

evolutionary biology↗

bioRxiv2015

Olfactory receptors are sensitive to molecular volume of odorants

To study olfaction, first we should know which physical or chemical properties of odorant molecules determine the response of olfactory receptor neurons, and then we should study the effect of those properties on the combinatorial encoding in olfactory system.\n\nIn this work we show that the response of an olfactory receptor neuron in Drosophila depends on molecular volume of an odorant; The molecular volume determines the upper limits of the neural response, while the actual neural response may depend on other properties of the molecules. Each olfactory receptor prefers a particular volume, with some degree of flexibility. These two parameters predict the volume and flexibility of the binding-pocket of the olfactory receptors, which are the targets of structural biology studies.\n\nAt the end we argue that the molecular volume can affects the quality of perceived smell of an odorant via the combinatorial encoding, molecular volume may mask other underlying relations between properties of molecules and neural responses and we suggest a way to improve the selection of odorants in further experimental studies.

Neuroscience↗

bioRxiv2017

A systematic approach for dissecting the molecular mechanisms of transcriptional regulation in bacteria

Gene regulation is one of the most ubiquitous processes in biology. But while the catalog of bacterial genomes continues to expand rapidly, we remain ignorant about how almost all of the genes in these genomes are regulated. At present, characterizing the molecular mechanisms by which individual regulatory sequences operate requires focused efforts using low-throughput methods. Here we show how a combination of massively parallel reporter assays, mass spectrometry, and information-theoretic modeling can be used to dissect bacterial promoters in a systematic and scalable way. We demonstrate this method on both well-studied and previously uncharacterized promoters in the enteric bacterium Escherichia coli. In all cases we recover nucleotide-resolution models of promoter mechanism. For some promoters, including previously unannotated ones, the approach allowed us to further extract quantitative biophysical models describing input-output relationships. This method opens up the possibility of exhaustively dissecting the mechanisms of promoter function in E. coli and a wide range of other bacteria.

biophysics↗

bioRxiv2017

Multi-generational silencing dynamics control cell aging

Cellular aging plays an important role in many diseases, such as cancers, metabolic syndromes and neurodegenerative disorders. There has been steady progress in identifying aging-related factors such as reactive oxygen species and genomic instability, yet an emerging challenge is to reconcile the contributions of these factors with the fact that genetically identical cells can age at significantly different rates. Such complexity requires single-cell analyses designed to unravel the interplay of aging dynamics and cell-to-cell variability. Here we use novel microfluidic technologies to track the replicative aging of single yeast cells and reveal that the temporal patterns of heterochromatin silencing loss regulate cellular lifespan. We found that cells show sporadic waves of silencing loss in the heterochromatic ribosomal DNA (rDNA) during the early phases of aging, followed by sustained loss of silencing preceding cell death. Isogenic cells have different lengths of the early intermittent silencing phase that largely determine their final lifespans. Combining computational modeling and experimental approaches, we found that the intermittent silencing dynamics is important for longevity and is dependent on the conserved Sir2 deacetylase, whereas either sustained silencing or sustained loss of silencing shortens lifespan. These findings reveal, for the first time, that the temporal patterns of a key molecular process can directly influence cellular aging and thus could provide guidance for the design of temporally controlled strategies to extend lifespan.\n\nSignificanceAging is an inevitable consequence of living, and with it comes increased morbidity and mortality. Novel approaches to mitigating age-related chronic diseases demand a better understanding of the biology of aging. Studies in model organisms have identified many conserved molecular factors that influence aging. The emerging challenge is to understand how these factors interact and change dynamically to drive aging. Using multidisciplinary technologies, we have revealed a sirtuin-dependent intermittent pattern of chromatin silencing during yeast aging that is crucial for longevity. Our findings highlight the important role of silencing dynamics in aging, which deserves careful consideration when designing schemes to delay or reverse aging by modulating sirtuins and silencing.

systems biology↗