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bioRxiv2020

Kinetics of self-assembly of inclusions due to lipid membrane thickness interactions

Self-assembly of proteins on lipid membranes underlies many important processes in cell biology, such as, exo- and endo-cytosis, assembly of viruses, etc. An attractive force that can cause self-assembly is mediated by membrane thickness interactions between proteins. The free energy profile associated with this attractive force is a result of the overlap of thickness deformation fields around the proteins. The thickness deformation field around proteins of various shapes can be calculated from the solution of a boundary value problem and is relatively well understood. Yet, the time scales over which self-assembly occurs has not been explored. In this paper we compute this time scale as a function of the initial distance between two inclusions by viewing their coalescence as a first passage time problem. The first passage time is computed using both Langevin dynamics and a partial differential equation, and both methods are found to be in excellent agreement. Inclusions of three different shapes are studied and it is found that for two inclusions separated by about hundred nanometers the time to coalescence is hundreds of milliseconds irrespective of shape. Our Langevin dynamics simulation of self-assembly required an efficient computation of the interaction energy of inclusions which was accomplished using a finite difference technique. The interaction energy profiles obtained using this numerical technique were in excellent agreement with those from a previously proposed semi-analytical method based on Fourier-Bessel series. The computational strategies described in this paper could potentially lead to efficient methods to explore the kinetics of self-assembly of proteins on lipid membranes. Author summarySelf-assembly of proteins on lipid membranes occurs during exo- and endo-cytosis and also when viruses exit an infected cell. The forces mediating self-assembly of inclusions on membranes have therefore been of long standing interest. However, the kinetics of self-assembly has received much less attention. As a first step in discerning the kinetics, we examine the time to coalescence of two inclusions on a membrane as a function of the distance separating them. We use both Langevin dynamics simulations and a partial differential equation to compute this time scale. We predict that the time to coalescence is on the scale of hundreds of milliseconds for two inclusions separated by about hundred nanometers. The deformation moduli of the lipid membrane and the membrane tension can affect this time scale.

biophysics↗

bioRxiv2019

Tetraploidy in rodent cardiac stem cells confers enhanced biological properties

Ploidy for cardiomyocytes is well described but remains obscure in cardiac interstitial cells (CICs). Ploidy of c-kit+CICs were assessed using a combination of confocal, karyotypic, and flow cytometric assessments coupled with molecular and bioinformatic analyses. Fundamental differences were found between cultured rodent (rat, mouse) c-kit+CICs possessing mononuclear tetraploid (4n) content versus large mammal (human, swine) with mononuclear diploid (2n) content. In-situ analysis, confirmed with fresh isolates, revealed diploid content in c-kit+CICs from human and a mixture of diploid and tetraploid nuclei in mouse. Molecular assessment of the p53 signaling pathway provides a plausible explanation for escape from replicative senescence in rodent but not human ckit+CICs. Single cell transcriptional profiling reveals distinctions between diploid versus tetraploid populations in mouse ckit+CICs, alluding to functional divergences. Collectively, these data reveal fundamental species-specific biological differences in c-kit+CICs that could account for challenges in extrapolation of myocardial preclinical studies from rodent to large animal models.

cell biology↗

bioRxiv2020

Ribosomal proteins could explain the phylogeny of Bacillus species

Protein translation is a highly conserved process in biology. As participants of translation, ribosomal proteins in the large and small subunits of the ribosomes are likely to be highly conserved; thus, could they be endowed with sufficient sequence diversity to chronicle the evolutionary history of different species in the same or different genus? Using different Bacillus species as a model system, this study sought to examine if ribosomal proteins could reproduce the maximum likelihood phylogeny described by 16S rRNA of the investigated Bacillus species. Bacillus species investigated were Bacillus amyloliquefaciens, Bacillus cereus, Bacillus licheniformis, Bacillus megaterium, Bacilluspumilus, Bacillus subtilis, and Bacillus thuringiensis. Results revealed that ribosomal proteins could be categorized into four different groups depending on their extent in reproducing the 16S rRNA phylogeny of the different Bacillus species. The first group comprises ribosomal protein that could reproduce all the phylogenetic positions of the Bacillus species accurately. These ribosomal proteins were ribosomal protein L6, L7/12, L9, L13, L24, L32, S3, S9, S12, S15, S16, S17, and S18. Ribosomal proteins that hold partial phylogenetic significance constitutes the second group where the ribosomal proteins could reproduce the major branches of the 16S rRNA phylogenetic tree but differ in the placement of one or two Bacillus species. In general, this group of ribosomal proteins had difficulty differentiating B. licheniformis and B. pumilus at the sequence level. Members of this group of ribosomal protein include ribosomal protein L22, L29, L30, L31 Type B, L33, L35, S1, S4, S5, S6, S7, S8, S11, S13, S19, and S20. The third group of ribosomal proteins were those which were highly conserved at the sequence level, and which could not differentiate the different Bacillus species. These ribosomal proteins were ribosomal protein L5, L36, S2, S10, and S21. Finally, there were also ribosomal proteins that randomly placed the different Bacillus species into phylogenetic positions not in sync with those depicted by the 16S rRNA phylogenetic tree. These ribosomal proteins were ribosomal protein L7Ae, L17, L20, L23, L27, L28, L31, L34 and S14 Type Z. Overall, members of all four groups of ribosomal proteins came from both the large and small ribosome subunits which meant that evolutionary forces exerted selective pressure on both subunits but at differing extents. Collectively, specific ribosomal proteins could reproduce the phylogeny of different Bacillus species as described by the gold standard phylogenetic marker, 16S rRNA, which highlighted that co-evolutionary processes could be at work in shaping the evolution of ribosomal proteins and rRNA in close contact with each other in the ribosome. Subject areasecology, biochemistry, biotechnology, microbiology, cell biology Significance of the work16S rRNA is the gold standard phylogenetic marker used to inform the evolutionary relationships between different species across the three domains of life. Given that 16S rRNA is nestled in the ribosomes together with a consortium of ribosomal proteins each with unique structural and enzymatic functions, could ribosomal proteins be used similarly as phylogenetic markers for informing species divergence and relationships? Specifically, as part of the highly conserved ribosome important to protein translation, do ribosomal proteins possess sufficient sequence diversity to help chronicle the evolutionary relationships between different species? By reconstructing the maximum likelihood phylogenetic tree of different Bacillus species, this study revealed that ribosomal proteins fall into four categories concerning their utility for informing phylogeny between different species of the same genus. Specifically, there existed ribosomal proteins able to accurately reproduce the phylogenetic tree described by 16S rRNA. On the other hand, there were ribosomal proteins that hold only partial phylogenetic significance where they could reproduce the major branches of the reference phylogenetic tree but differ in the placement of one or two species along the tree. Besides the above two categories, they were also ribosomal proteins whose sequence diversity was not sufficient to help differentiate between different Bacillus species. Finally, another class of ribosomal proteins did not chronicle the evolutionary trajectories of the different species resulting in phylogenetic tree with random placement of the different species. Overall, evolutionary forces likely exerted different selection forces on different ribosome subunits as well as individual ribosomal protein that resulted in the differentiation of their utility as phylogenetic markers of different species of the same genus. Co-evolution between ribosomal proteins as well as between ribosomal proteins and rRNA might underpin part of the evolutionary history chronicled by individual ribosomal proteins, thereby, endowing them with phylogenetic significance. HighlightsO_LIRibosomal proteins were found to be useful in describing the phylogeny of different Bacillus species compared to the gold standard phylogenetic marker, 16S rRNA. C_LIO_LIBy examining the maximum likelihood phylogenetic tree reconstructed, ribosomal proteins could be categorized into four groups with differing phylogenetic significance. C_LIO_LIThe first group comprises ribosomal proteins able to accurately reproduce all the phylogenetic positions of different Bacillus species relative to 16S rRNA phylogenetic tree. This group include ribosomal protein L6, L7/12, L9, L13, L24, L32, S3, S9, S12, S15, S16, S17, and S18. C_LIO_LIThe second group refers to ribosomal proteins able to reproduce the major branches of the 16S rRNA phylogenetic tree but lacks in the correct placement of one or two Bacillus species. These ribosomal proteins were L22, L29, L30, L31 Type B, L33, L35, SI, S4, S5, S6, S7, S8, Sll, S13, S19, and S20. C_LIO_LIThe third group of ribosomal proteins are ones with highly conserved sequence unable to differentiate between different Bacillus species. It comprised ribosomal proteins L5, L36, S2, S10, and S21. C_LIO_LIThe final group of ribosomal proteins did not chronicle the evolutionary forces acting on the different Bacillus species and generated phylogenetic trees with random placement of the different Bacillus species. These ribosomal proteins were L7Ae, L17, L20, L23, L27, L28, L31, L34 and S14 Type Z. C_LI

evolutionary biology↗

bioRxiv2014

Preparation of Synaptosomes from Postmortem Human Prefrontal Cortex

Synaptosomes are a popular type of isolated synaptic fraction intensively used in neuroscience and cell biology. They are prepared by layering on density gradients and thought to consist largely of axonal endings with attached postsynaptic structures (Morgan, 1976), in contrast to synaptoneurosomes (Hollingsworth et al, 1985) which are prepared by filtration and are thought to consist largely of pinched-off dendritic spines with attached presynaptic structures. Although most studies of synaptosomes have utilized rodent or primate tissue, a score of studies have employed human samples derived from surgical specimens or postmortem brain. We recently described the isolation of synaptosomes from human postmortem prefrontal cortex to study the expression of synaptic microRNAs and other small RNAs in depression, schizophrenia and bipolar disorder (Smalheiser et al, 2014). This protocol alluded to methods and modifications that are scattered among several publications, and did not explain the reasons for the procedures chosen. Because our protocol differs from other published human synaptosome protocols in a variety of respects, we present here a detailed description of synaptosome preparation that should facilitate the use of this standardized synaptic fraction by other workers.

Neuroscience↗

bioRxiv2015

Cancer Classification by Correntropy-Based Sparse Compact Incremental Learning Machine

Cancer prediction is of great importance and significance and it is crucial to provide researchers and scientists with novel, accurate and robust computational tools for this issue. Recent technologies such as Microarray and Next Generation Sequencing have paved the way for computational methods and techniques to play critical roles in this regard. Many important problems in cell biology require the dense nonlinear interactions between functional modules to be considered. The importance of computer simulation in understanding cellular processes is now widely accepted, and a variety of simulation algorithms useful for studying certain subsystems have been designed. In this article, a Sparse Compact Incremental Learning Machine (SCILM) is proposed for cancer classification problem on microarray gene expression data which take advantage of Correntropy cost that makes it robust against diverse noises and outliers. Moreover, since SCILM uses l1-norm of the weights, it has sparseness which can be applied for gene selection purposes as well. Finally, due to compact structure, the proposed method is capable of performing classification tasks in all of the cases with only one neuron in its hidden layer. The experimental analysis is performed on 26 well known microarray datasets regarding diverse kinds of cancers and the results show that the proposed method not only achieved significantly high accuracy but also because of its sparseness, final connectivity weights determined the value and effectivity of each gene regarding the corresponding cancer.

Bioinformatics↗

bioRxiv2016

SourceData - a semantic platform for curating and searching figures

Here we present SourceData (http://sourcedata.embo.org), a platform that allows researchers and publishers to share scientific figures and, when available, the underlying source data in a way that is machine-readable and findable. SourceData is unique in its focus on the core of scientific evidence--data presented in figures--and its capability to make papers searchable based on their data content and hence directly couple data to improved discoverability. SourceData aims at establishing a selfreinforcing data ecosystem that bridges the conventional visual and narrative description of research findings with a machine-readable representation of data and hypotheses.\n\nIn molecular and cell biology, most of the data that result from hypothesis-driven research are exclusively available in the form of figures or tables in published papers. In spite of their importance for the understanding of biological processes and human di ...

Bioinformatics↗

bioRxiv2016

A scored human protein-protein interaction network to catalyze genomic interpretation

Human protein-protein interaction networks are critical to understanding cell biology and interpreting genetic and genomic data, but are challenging to produce in individual large-scale experiments. We describe a general computational framework that through data integration and quality control provides a scored human protein-protein interaction network (InWeb_IM). Juxtaposed with five comparable resources, InWeb_IM has 2.8 times more interactions (~585K) and a superior functional signal showing that the added interactions reflect real cellular biology. InWeb_IM is a versatile resource for accurate and cost-efficient functional interpretation of massive genomic datasets illustrated by annotating candidate genes from >4,700 cancer genomes and genes involved in neuropsychiatric diseases.

Genomics↗

bioRxiv2016

Laurdan and di-4-ANEPPDHQ probe different properties of the membrane

Lipid packing is a crucial feature of cellular membranes. Quantitative analysis of membrane lipid packing can be achieved using polarity sensitive probes whose emission spectrum depends on the lipid packing. However, detailed insight into the exact mechanism that causes the spectral shift is essential to interpret the data correctly. Here, we analysed frequently used polarity sensitive probes, Laurdan and di-4-ANEPPDHQ, to test whether the underlying physical mechanisms of their spectral shift is the same, thus whether they report on the same physico-chemical properties of the cell membrane. Their steady-state spectra as well as time-resolved emission spectra in solvents and model membranes showed that they probe different properties of the lipid membrane. Our findings are important for the application of these dyes in cell biology.

Biophysics↗

bioRxiv2016

Co-operation, competition and crowding: a discrete framework linking Allee kinetics, nonlinear diffusion, shocks and sharp-fronted travelling waves

AO_SCPLOWBSTRACTC_SCPLOWInvasion processes are ubiquitous throughout cell biology and ecology. During invasion, individuals can become isolated from the bulk population and behave differently. We present a discrete, exclusion-based description of the birth, death and movement of individuals. The model distinguishes between individuals that are part of, or are isolated from, the bulk population by imposing different rates of birth, death and movement. This enables the simulation of various co-operative or competitive mechanisms, where there is either a positive or negative benefit associated with being part of the bulk population, respectively. The mean-field approximation of the discrete process gives rise to 22 different classes of partial differential equation, which can include Allee kinetics and nonlinear diffusion. Here we examine the ability of each class of partial differential equation to support travelling wave solutions and interpret the long time behaviour in terms of the individual-level parameters. For the first time we show that the strong Allee effect and nonlinear diffusion can result in shock-fronted travelling waves. We also demonstrate how differences in group and individual motility rates can influence the persistence of a population and provide conditions for the successful invasion of a population.

Biophysics↗

bioRxiv2016

Deciphering the genic basis of environmental adaptations by simultaneous forward and reverse genetics in Saccharomyces cerevisiae

The budding yeast Saccharomyces cerevisiae is the best studied eukaryote in molecular and cell biology, but its utility for understanding the genetic basis of natural phenotypic variation is limited by the inefficiency of association mapping owing to strong and complex population structure. To facilitate association mapping, we analyzed 190 high-quality genomes of diverse strains, including 85 newly sequenced ones, to uncover yeasts population structure that varies substantially among genomic regions. We identified 181 yeast genes that are absent from the reference genome and demonstrated their expression and role in important functions such as drug resistance. We then simultaneously measured the growth rates of over 4500 lab strains each deficient of a nonessential gene and 81 natural strains across multiple environments using unique DNA barcode present in each strain. We combined the genome-wide reverse genetic information with genome-wide association analysis to determine potential genomic regions of importance to environmental adaptations, and for a subset experimentally validated their role by reciprocal hemizygosity tests. The resources provided permit efficient and reliable association mapping in yeast and significantly enhances its value as a model for understanding the genetic mechanisms of phenotypic polymorphism and evolution.

genomics↗

bioRxiv2016

Physical models of spatial genome organization

Remodeling of nuclear organization occurs during normal cell development, differentiation and cancer. One of the biggest gaps of knowledge remains how to link the information on chromatin and chromosome structural organization with genes activity. In this paper we introduce some physical ideas and a general computational method demonstrating how genome 3D architecture and its remodeling can be quantitatively modeled. We study a hypothetical scenario of alterations of chromosome territories positioning in the course of cell proliferation. On this basis we obtain quantitative information about chromosomal contacts in the nucleus. We predict changes of radial distributions of contacts between chromosomal megabase domains during proliferation. The proposed modeling approach may be helpful in integrating experimental data on nuclear reorganization associated with normal development and with various diseases. This predictive modeling may find applications in genome research of normal and cancer cells, stem cell biology, biology of aging, etc.

cancer biology↗

bioRxiv2016

Quantitative Analysis of Dopamine Neuron Subtypes Generated from Mouse Embryonic Stem Cells

Dopamine (DA) neuron subtypes modulate specific physiological functions and are involved in distinct neurological disorders. Embryonic stem cell (ESC) derived DA neurons have the potential to aid in the study of disease mechanisms, drug discovery, and possibly cell replacement therapies. DA neurons can be generated from ESCs in vitro, but the subtypes of ESC-derived DA neurons have not been investigated in detail despite the diversity of DA neurons observed in vivo. Due to cell culture heterogeneity, sampling methods applied to ESC-derived cultures can be ambiguous and potentially biased. Therefore, we developed a quantification method to capture the depth of DA neuron production in vitro by estimating the error associated with systematic random sampling. Using this method, we quantified calbindin+ and calretinin+ subtypes of DA neurons generated from mouse ESCs. We found a higher production of the calbindin+ subtype (11-27%) compared to the calretinin+ subtype (2-13%) of DA neuron; in addition, DA neurons expressing neither subtype marker were also generated. We then examined whether exogenous sonic hedgehog (SHH) and fibroblast growth factor 8 (FGF8) affected subtype generation. Our results demonstrate that exogenous SHH and FGF8 did not alter DA neuron subtype generation in vitro. These findings suggest that a deeper understanding DA neuron derivation inclusive of mechanisms that govern the in vitro subtype specification of ESC-derived DA neurons is required.\n\nNoteAll research was planned and conducted while members were at Brown University\n\nResearch fundingNIH/NCRR/NIGMS RI Hospital COBRE Center for Stem Cell Biology (8P20GM103468-04) (MZ) Brown Institute for Brain Science Pilot Grant (4-63662) (MZ/DHK)

neuroscience↗

bioRxiv2017

A new and accurate continuum description of moving fronts

Processes that involve moving fronts of populations are prevalent in ecology and cell biology. A common approach to describe these processes is a lattice-based random walk model, which can include mechanisms such as crowding, birth, death, movement and agent-agent adhesion. However, these models are generally analytically intractable and it is computationally expensive to perform sufficiently many realisations of the model to obtain an estimate of average behaviour that is not dominated by random fluctuations. To avoid these issues, both mean-field and corrected mean-field continuum descriptions of random walk models have been proposed. However, both continuum descriptions are inaccurate outside of limited parameter regimes, and corrected mean-field descriptions cannot be employed to describe moving fronts. Here we present an alternative description in terms of the dynamics of groups of contiguous occupied lattice sites and contiguous vacant lattice sites. Our description provides an accurate prediction of the average random walk behaviour in all parameter regimes. Critically, our description accurately predicts the persistence or extinction of the population in situations where previous continuum descriptions predict the opposite outcome. Furthermore, unlike traditional mean-field models, our approach provides information about the spatial clustering within the population and, subsequently, the moving front.

biophysics↗

bioRxiv2017

The Co-regulation Data Harvester for Tetrahymenathermophila: automated high-throughput geneannotation and functional inference in a microbialeukaryote

Identifying co-regulated genes can provide a useful approach for defining pathway-specific machinery in an organism. To be efficient, this approach relies on thorough genome annotation, which is not available for most organisms with sequenced genomes. Studies in Tetrahymena thermophila, the most experimentally accessible ciliate, have generated a rich transcriptomic database covering many well-defined physiological states. Genes that are involved in the same pathway show significant co-regulation, and screens based on gene co-regulation have identified novel factors in specific pathways, for example in membrane trafficking. However, a limitation has been the relatively sparse annotation of the Tetrahymena genome, making it impractical to approach genome-wide analyses. We have therefore developed an efficient approach to analyze both co-regulation and gene annotation, called the Co-regulation Data Harvester (CDH). The CDH automates identification of co-regulated genes by accessing the Tetrahymena transcriptome database, determines their orthologs in other organisms via reciprocal BLAST searches, and collates the annotations of those orthologs' functions. Inferences drawn from the CDH reproduce and expand upon experimental findings in Tetrahymena. The CDH, which is freely available, represents a powerful new tool for analyzing cell biological pathways in Tetrahymena. Moreover, to the extent that genes and pathways are conserved between organisms, the inferences obtained via the CDH should be relevant, and can be explored, in many other systems.

bioinformatics↗

bioRxiv2017

Sub-minute phosphoregulation of cell-cycle systems during Plasmodium gamete formation revealed by a high-resolution time course

Malaria parasites are protists of the genus Plasmodium, whose transmission to mosquitoes is initiated by the production of gametes. Male gametogenesis is an extremely rapid process that is tightly controlled to produce eight flagellated microgametes from a single haploid gametocyte within 10 minutes after ingestion by a mosquito. Regulation of the cell cycle is poorly understood in divergent eukaryotes like Plasmodium, where the highly synchronous response of gametocytes to defined chemical and physical stimuli from the mosquito has proved to be a powerful model to identify specific phosphorylation events critical for cell-cycle progression. To reveal the wider network of phosphorylation signalling in a systematic and unbiased manner, we have measured a high-resolution time course of the phosphoproteome of P. berghei gametocytes during the first minute of gametogenesis. The data show an extremely broad response in which distinct cell-cycle events such as initiation of DNA replication and mitosis are rapidly induced and simultaneously regulated. We identify several protein kinases and phosphatases that are likely central in the gametogenesis signalling pathway and validate our analysis by investigating the phosphoproteomes of mutants in two of them, CDPK4 and SRPK1. We show these protein kinases to have distinct influences over the phosphorylation of similar downstream targets that are consistent with their distinct cellular functions, which is revealed by a detailed phenotypic analysis of an SRPK1 mutant. Together, the results show that key cell-cycle systems in Plasmodium undergo simultaneous and rapid phosphoregulation. We demonstrate how a highly resolved time-course of dynamic phosphorylation events can generate deep insights into the unusual cell biology of a divergent eukaryote, which serves as a model for an important group of human pathogens.

microbiology↗

bioRxiv2017

Multiple Poliovirus-Induced Organelles Suggested By Comparison Of Spatiotemporal Dynamics Of Membranous Structures And Phosphoinositides

Poliovirus (PV) infection induces membranes with elevated levels of phosphatidylinositol-4-phosphate (PI4P) and invaginated, tubular structures that appear as vesicular clusters in cross section. Here, we characterize PV mutants, termed EG and GG, which exhibit aberrant proteolytic processing of the P3 precursor that can delay the onset of genome replication and/or impair virus assembly. For WT PV, changes to the PI4P pool were observed as early as 30 min post-infection. PI4P remodeling occurred even in the presence of guanidine hydrochloride, a replication inhibitor. Vesicular clusters were not apparent until 3 h post-infection, a time too slow for these structures to be responsible for genome replication. Delays in the onset of genome replication observed for EG and GG PVs were explained completely by the reduced kinetics of virus-induced remodeling of PI4P pools, consistent with PI4P serving as a marker of the genome-replication organelle. Infectious virus produced by GG PV is known to be reduced nearly 5 logs. We show that GG PV was unable to make virus-induced vesicular clusters. Instead, GG PV-infected cells accumulated elongated tubules. Our results are consistent with the existence of distinct organelles for genome-replication and virus assembly. We suggest that the pace of formation and spatiotemporal dynamics of PV induced organelles may be set by the rate of P3 precursor processing to form 3AB and/or 3CD proteins.\n\nAUTHOR SUMMARYAll positive-strand RNA viruses replicate their genomes in association with host cell membranes. PV does not just remodel existing membranes, but induces membranes with unique structure and lipid composition. There has been some suggestion that the functions of the PV induced structures observed during infection may not be those that perform genome-replication. This study uses kinetic analysis of virus-induced membrane formation and PI4P induction by two PV mutants to provide evidence for the existence of a virus-induced genome-replication organelle distinct from a second organelle, the absence of which impairs virus assembly. In addition, our studies suggest that formation of both organelles may require participation of viral proteins, 3AB and/or 3CD. Therefore, this study provides a new perspective on the cell biology of PV infection and should inspire a fresh look at picornavirus-induced organelles, their functions and the role of P3 proteins in their formation.

molecular biology↗

bioRxiv2017

An Aphrodisiac Produced By Vibrio fischeri Stimulates Mating In The Closest Living Relatives Of Animals

We serendipitously discovered that the marine bacterium Vibrio fischeri induces sexual reproduction in one of the closest living relatives of animals, the choanoflagellate Salpingoeca rosetta. Although bacteria influence everything from nutrition and metabolism to cell biology and development in eukaryotes, bacterial regulation of eukaryotic mating was unexpected. Here we show that a single V. fischeri protein, the previously uncharacterized EroS, fully recapitulates the aphrodisiac activity of live V. fischeri. EroS is a chondroitin lyase; although its substrate, chondroitin sulfate, was previously thought to be an animal synapomorphy, we demonstrate that S. rosetta produces chondroitin sulfate and thus extend the ancestry of this important glycosaminoglycan to the premetazoan era. Finally, we show that V. fischeri, purified EroS, and other bacterial chondroitin lyases induce S. rosetta mating at environmentally-relevant concentrations suggesting that bacterially-produced aphrodisiacs likely regulate choanoflagellate mating in nature.

microbiology↗

bioRxiv2017

miRNAtools: advanced training using the miRNA web of knowledge

miRNAs are small non-coding RNAs, that act as negative regulators of the genomic output. Their intrinsic importance within cell biology and human disease is well known. Their mechanism of action based on the base pairing binding to their cognate targets, have helped the development of many computer applications for the prediction of miRNA target recognition. More recently, many other computer applications have appeared with the objective of studying miRNA roles in many contexts, trying to dissect and predict their functions in a specific biological process. Learning about miRNA function needs a practical training in the use of specific computer and web-based applications that are complementary to the wet-lab studies. In the last seven years we have been involved in the organization of advanced training courses about the in silico functional analysis of miRNAs and non-coding RNAs, for students ranging from the postgraduate to the post-doctoral level. In order to guide the learning process about miRNAs, we have created miRNAtools (http://mirnatools.eu), a web repository of miRNA tools and tutorials. This page is a compilation of tools to analyze miRNAs and their regulatory action that intends to collect and organize the information that is dispersed in the web. The miRNAtools webpage is completed by a collection of tutorials that can be used by students and tutors engaged in advanced training courses. The tutorials follow the rationale of the analysis of the function of selected miRNAs, starting from their nomenclature and genomic localization and finishing by assessing their involvement in specific cellular functions.\n\nDESCRIPTION OF THE AUTHORFrancisco J. Enguita is assistant professor at the Faculty of Medicine, University of Lisbon and senior investigator at the Instituto de Medicina Molecular within the same University.\n\nKEY POINTSO_LI- We have designed a web-page, mIRNAtools3 (http://mirnatools.eu) specifically devoted for advanced teaching purposes within the miRNA field.\nC_LIO_LI- The webpage constitutes also a repository of web-tools for the analysis of miRNA function in several contexts.\nC_LIO_LI- The webpage contains tutorials that cover many aspects related with miRNAs including nomenclature, target prediction and validation, and functional analysis.\nC_LI

bioinformatics↗