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Results for “molecular biology”

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bioRxiv2022

Real-time TIRF imaging of exocytosis in 3T3-L1 adipocytes stably expressing mCherry fused to human adiponectin.

Adiponectin is a peptide hormone abundantly released from adipocytes, and reduced circulating levels are associated with obesity-related diseases, such as type 2 diabetes, insulin resistance and cardiovascular disease. Adiponectin is released by regulated exocytosis of secretory vesicles, but traditional molecular biology and imaging techniques lack the specificity and time resolution to adequately quantify exocytosis and trafficking of adiponectin-containing vesicles. Here we generated 3T3-L1 adipocytes that stably express mCherry-tagged human adiponectin, resulting in robust labelling of small adiponectin vesicles with a diameter of 200-300 nm, in live cells. Total internal reflection fluorescence (TIRF) microscopy was used to visualise and quantify exocytosis and adiponectin release in real-time, observed as rapid disappearance of the fluorescence of individual vesicles. Bulk adiponectin secretion measurements confirmed that the labelled adiponectin was secreted to the surrounding solution under these conditions, and expressed in the same vesicle population as endogenous adiponectin. In contrast to previous electrophysiological results, elevation of cytosolic Ca2+ alone was sufficient to induce exocytosis, although at a lower rate compared to elevated cytosolic cAMP. We conclude that the adiponectin-mCherry-labelled cells are useful for studying adiponectin exocytosis at the single vesicle level, and that an intracellular elevation of either cAMP or Ca2+ can trigger adiponectin vesicle release.

cell biology↗

bioRxiv2022

Heat induces multi-omic and phenotypic stress propagation in zebrafish embryos

Heat alters biology from molecular to ecological levels, but may also have unknown indirect effects. This includes the novel concept that animals exposed to abiotic stress can induce stress in naive receivers. Here, we provide a comprehensive picture of the molecular signatures of this process, by integrating multi-omic and phenotypic data. In individual zebrafish embryos, repeated heat peaks elicited both a molecular response and a burst of accelerated growth followed by a growth slow-down in concert with reduced responses to novel stimuli. Metabolomes of the media of heat treated vs. untreated embryos revealed candidate stress metabolites including sulphur-containing compounds and lipids. These stress metabolites elicited transcriptomic changes in naive receivers related to immune response, extracellular signalling, glycosaminoglycan/keratan sulphate, and lipid metabolism. Consequently, non heat-exposed receivers (exposed to stress metabolites only) experienced accelerated catch-up growth in concert with reduced swimming performance. The combination of heat and stress metabolites accelerated development the most, mediated by apelin signalling. Our results prove the concept of indirect heat-induced stress propagation towards naive receivers, inducing phenotypes comparable to those resulting from direct heat exposure, but utilising distinct molecular pathways. Group-exposing a non-laboratory zebrafish line, we independently confirm that the glycosaminoglycan biosynthesis-related gene chs1, and the mucus glycoprotein gene prg4a, functionally connected to the candidate stress metabolite classes sugars and phosphocholine, are differentially expressed in receivers. This hints at production of Schreckstoff-like cues in receivers, leading to further stress propagation within groups, which may have ecological and animal welfare implications for aquatic populations in a changing climate. Significance StatementAquatic animals utilise chemicals to mediate adaptive behaviours. For instance, predated fish release chemical cues that elicit antipredatory responses in naive receivers. But whether abiotic factors such as heat likewise alter chemical communication has received little focus. Here, we uncover a novel dimension of chemical communication -- heat-stressed donors can induce stress in naive receivers. We show that heat activates molecular stress responses, leading to the release of distinct stress metabolite classes into the environment. These stress metabolites alter the transcriptome of receivers, resulting in faster development and hypoactivity. Heat combined with stress metabolites had the largest effect, highlighting that abiotic stress, experienced both directly and indirectly, can alter chemical communication and affect embryonic development. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=83 SRC="FIGDIR/small/508176v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@1e44b4borg.highwire.dtl.DTLVardef@10b6878org.highwire.dtl.DTLVardef@1f7c3bforg.highwire.dtl.DTLVardef@15436bc_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIWe elucidate the mechanism for a novel dimension of the heat stress response -- chemical communication from heat-stressed donors that induces stress in naive receivers -- constituting a positive feedback loop C_LIO_LIRepeated heat stress induces a cellular and cortisol stress response and alters the phenotype of zebrafish embryos C_LIO_LIHeat-stressed embryos release stress metabolites enriched in lipids and sulphur-containing organo-oxygen compounds C_LIO_LIIn combination, heat and stress metabolites induced 47% distinct differentially expressed genes, with many related to organ development C_LIO_LIThese stress metabolites alter the transcriptome and induce both faster development and hypoactivity in naive receivers, a similar response to that of heat stress itself C_LI

molecular biology↗

bioRxiv2022

Integrated microRNA and proteome analysis of cancer datasets with MoPC

MicroRNAs (miRNAs) are small molecules that play an essential role in regulating gene expression by post-transcriptional gene silencing. Their study is crucial in revealing the fundamental processes underlying pathologies and, in particular, cancer. To date, most studies on miRNA regulation consider the effect of specific miRNAs on specific target mRNAs, providing wet-lab validation. However, few tools have been developed to explain the miRNA-mediated regulation at the protein level. In this paper, the MoPc computational tool is presented, that relies on the partial correlation between mRNAs and proteins conditioned on the miRNA expression to predict miRNA-target interactions in multi-omic datasets. MoPc returns the list of significant miRNA-target interactions and plot the significant correlations on the heatmap in which the miRNAs and targets are ordered by the chromosomal location. The software was applied on three TCGA/CPTAC datasets (breast, glioblastoma, and lung cancer), returning enriched results in three independent targets databases. Author summaryAccording to the central dogma of molecular biology, DNA is transcribed into RNA and subsequently translated into proteins. However, many molecules affect the amount of protein produced, including microRNAs (miRNAs). They can inhibit the translation or intervene by implementing the decay of target mRNAs. In literature, most works focus on describing the effect of miRNAs on mRNA targets, while only a few tools integrate protein expression profiles. MoPc predicts miRNA-targets interaction by considering the expression of mRNA, proteins, and miRNAs simultaneously. The method is based on the partial correlation measure between mRNAs and proteins conditioned by the expression of the miRNAs. The results on TCGA/CPTAC datasets prove the relevance of the MoPc method both from a computational and a biological point of view.

bioinformatics↗

bioRxiv2022

Meta-analysis of (single-cell method) benchmarks reveals the need for extensibility and interoperability

Computational methods represent the lifeblood of modern molecular biology. Benchmarking is important for all methods, but with a focus here on computational methods, benchmarking is critical to dissect important steps of analysis pipelines, formally assess performance across common situations as well as edge cases, and ultimately guide users on what tools to use. Benchmarking can also be important for community building and advancing methods in a principled way. We conducted a meta-analysis of recent single-cell benchmarks to summarize the scope, extensibility, neutrality, as well as technical features and whether best practices in open data and reproducible research were followed. The results highlight that while benchmarks often make code available and are in principle reproducible, they remain difficult to extend, for example, as new methods and new ways to assess methods emerge. In addition, embracing containerization and workflow systems would enhance reusability of intermediate benchmarking results, thus also driving wider adoption.

bioinformatics↗

bioRxiv2022

An approach towards identifying the site of interaction between the Streptomyces phage PhiC31 protein Gp3 and the coiled-coil domain of its serine integrase

Streptomyces phage OC31 encodes a serine integrase which recombines the host (attB) and phage (attP) attachment sites to form new attL and attR sites. For attL and attR to be recombined by the integrase, the presence of its cognate recombination directionality factor (RDF) is required. It is hypothesized that the RDF binds the coiled-coil domain of the integrase to accomplish this switch in recombination directionality. Yet, nothing is known about the site of interaction between the RDF and integrase. Here, we tried to identify the region on the coiled-coil domain of OC31 integrase to which its cognate RDF (gp3) might bind. Mutant integrases fused to their cognate RDF (gp3) were created and selected for inactivity in attL x attR recombination. It was not possible to characterize the mutants and identify the Int-RDF binding region, due to unforeseen errors that occurred during the construction of the mutant library, but we demonstrated that simple experimental approaches could be used to identify this region. Despite this, an integrase mutant (P398L D595N) fused to gp3 was characterized. This mutant was catalyzing a more unidirectional attL x attR recombination reaction with reduced attP x attB recombination compared to the wild-type integrase. This mutant was selected since it could be used within the field of molecular biology to construct inversion switches which are a key element by which cells can be computerized. By the time this work was uploaded on bioRxiv, there is now a publication that investigated the Int-RDF interaction interface and several residues at the base of the coiled-coil that affected both the interaction and recombinase activity were identified (Paul C M Fogg, Ellen Younger, Booshini D Fernando, Thanafez Khaleel, W Marshall Stark, Margaret C M Smith, Recombination directionality factor gp3 binds PhiC31 integrase via the zinc domain, potentially affecting the trajectory of the coiled-coil motif, Nucleic Acids Research, Volume 46, Issue 3, 16 February 2018, Pages 1308-1320, https://doi.org/10.1093/nar/gkx1233).

synthetic biology↗

bioRxiv2022

Low-cost and highly efficient: A method for high-quality nucleic acid isolation from cotton fibres

Gene expression analyses to study the development of cotton fibers require high-quality nucleic acid. The conventional methods of nucleic acid extraction results in sub-quality nucleic acids with low yields. Young fibers are rich in polyphenols and sugars that react with nucleic acid to form phenols and insoluble substances. Furthermore, mature fibers contain more than 95% cellulose, hindering the nucleic acid isolation. Cytoplasm collapse and cellulose deposition also result in a very low yield of nucleic acid. Three different methods of RNA isolation from different cotton tissues were compared in this study to determine the best and most efficient one. The integrity and quality of RNA were analyzed using UV spectrum, agarose gel electrophoresis, RIN values, PCR, and Northern blot hybridization. RNA of functional quality was observed when using the high ion and pH method, with an A260/A280 ratio up to 1.87 and an average yield of 0.68 mg g-1 from fiber cells. From leaves, we found an A260/A280 ratio of 2.02 and an average yield of 6.35 mg g-1, which is suitable for molecular biology experiments. The extraction buffer with a high ion density and pH value include Tris-HCl, LiCl, EDTA, SDS, sodium deoxycholate, Nonident P-40, mercaptoethanol, and PVP. The addition of sodium deoxycholate and Nonider-40 (NP-40) enhances the density of other salt compounds and elevates the pH value. The results depicted that the high ion and pH method is a simple and effective way to extract a copious amount of high-quality RNA from polysaccharide-rich tissues. This method is also suitable for the extraction of cotton genomic DNA with high purity. Genomic DNA extracted from cotton using this method showed an A260/A230 ratio up to 2.09 and a yield of 1.44 mg g-1. This method is useful for isolating DNA and RNA from cotton fibers and produces high yields and quality at a comparatively low cost.

genomics↗

bioRxiv2022

MicroED structure of a protoglobin reactive carbene intermediate

Microcrystal electron diffraction (MicroED) is an emerging technique which has shown great potential for describing new chemical and biological molecular structures. [1] Several important structures of small molecules, natural products and peptides have been determined using ab initio methods. [2] However, only a couple of novel protein structures have thus far been derived by MicroED. [3, 4] Taking advantage of recent technological advances including higher acceleration voltage and using a low-noise detector in counting mode, we have determined the first structure of an Aeropyrum pernix protoglobin (ApePgb) variant by MicroED using an AlphaFold2 model for phasing. The structure revealed that mutations introduced during directed evolution enhance carbene transfer activity by reorienting an alphahelix of ApePgb into a dynamic loop making the catalytic active site more readily accessible. After exposing the tiny crystals to substrate, we also trapped the reactive iron-carbenoid intermediate involved in this engineered ApePgbs new-to-nature activity, a challenging carbene transfer from a diazirine via a putative metallo-carbene. The bound structure discloses how an enlarged active site pocket stabilizes the carbene bound to the heme iron and, presumably, the transition state for formation of this key intermediate. This work demonstrates that improved MicroED technology and the advancement in protein structure prediction now enables investigation of structures that were previously beyond reach.

biochemistry↗

bioRxiv2022

A highly contiguous genome assembly reveals sources of genomic novelty in the symbiotic fungus Rhizophagus irregularis

The root systems of most plant species are aided by the soil foraging capacities of symbiotic Arbuscular Mycorrhizal (AM) fungi of the Glomeromycotina subphylum. Despite recent advances in our knowledge of the ecology and molecular biology of this mutualistic symbiosis, our understanding of the AM fungi genome biology is just emerging. Presented here are the most contiguous and highest-quality nuclear and mitochondrial genome assemblies of an arbuscular mycorrhizal fungus to date, achieved through Nanopore long-read DNA sequencing and Hi-C data. This haploid genome assembly of Rhizophagus irregularis, alongside short- and long-read RNA-Sequencing data, was used to produce a comprehensive annotation catalogue of gene models, repetitive elements, small RNA loci, and DNA cytosine methylome. A phylostratigraphic gene age inference framework revealed that the birth of genes associated with nutrient transporter activity and transmembrane ion transport systems predates the emergence of Glomeromycotina. While symbiotic nutrient cycling in AM fungi relies on genes that existed in ancestor lineages, a burst of Glomeromycotina-restricted genetic innovation is also detected. Analysis of the chromosomal distribution of genetic and epigenetic features highlights evolutionarily young genomic regions that produce abundant small RNAs, suggesting active RNA-based monitoring of genetic sequences surrounding recently evolved genes. This chromosome-scale view of the genome of an AM fungus genome reveals previously unexplored sources of genomic novelty in an organism evolving under an obligate symbiotic life cycle. HighlightsO_LIAssembly of 32 highly contiguous chromosomal scaffolds for R. irregularis, with 23 complete and gapless C_LIO_LIGene annotation based on short- and long-read RNA-Seq data from different developmental stages C_LIO_LIComplete annotation set including mitochondrial genes, DNA methylome, small RNAome, repetitive/transposable elements, functional annotation C_LIO_LIIdentification of a burst of lineage-restricted genetic innovation in the Glomeromycotina subphylum C_LI

genomics↗

bioRxiv2022

Cryo-electron microscopy of the f1 filamentous phage reveals a new paradigm in viral infection and assembly

Phages are viruses that infect bacteria and dominate every ecosystem on our planet. As well as impacting microbial ecology, physiology and evolution, phages are exploited as tools in molecular biology and biotechnology. This is particularly true for the Ff (f1, fd or M13) phages, which represent a widely distributed group of filamentous viruses. Over nearly five decades, Ff has seen an extraordinary range of applications, including in phage display and nanotechnology. However, the complete structure of the phage capsid and consequently the mechanisms of infection and assembly remain largely mysterious. Using cryo-electron microscopy and a highly efficient system for production of short Ff-derived nanorods, we have determined the first structure of a filamentous virus, including the filament tips. Structure combined with mutagenesis was employed to identify domains of the phage that are important in bacterial attack and for release of new phage progeny. These data allow new models to be proposed for the phage lifecycle and will undoubtedly enable the development of novel biotechnological applications.

microbiology↗

bioRxiv2022

Cell density-dependent death triggered by viral palindromic DNA sequences

Defense systems that recognize viruses have provided not only the tools of molecular biology but also important insights into other mechanisms that can induce immunity to these or other infectious agents including transmissible plasmids and chromosomal genetic elements. Several systems that trigger cell death upon viral infection have recently been recognized but the signals that activate these abortive infection systems remain largely unknown. Here we characterize one such system in Vibrio cholerae that we found was responsible for triggering cell-density dependent death (CDD) of bacterial cells in response to the presence of certain genetic elements. The key components of the CDD system include quorum-regulated components DdmABC and the host factor PriA. Our analysis indicates that the plasmid and phage signals that trigger CDD were palindromic DNA sequences that are predicted to form stem-loop hairpin structures from single-stranded DNA during stalled replication. Our results further suggest that other agents that generate damaged DNA can also trigger DdmABC/PriA activation and cell death probably through activation of a nuclease domain present in the DdmA protein. Thus, any infectious process that results in damaged DNA, particularly during DNA replication, can in theory trigger cell death through the DdmABC/PriA abortive infection system.

microbiology↗

bioRxiv2022

Processing and evaluating the quality of genome-wide nascent transcription profiling libraries

Precision genomic run-on assays (PRO-seq) quantify nascent RNA at single nucleotide resolution with strand specificity. Here we deconstruct a recently published genomic nascent RNA processing pipeline (PEPPRO) into its components and link the analyses to the underlying molecular biology. PRO-seq experiments are evolving and variations can be found throughout the literature. The analyses are presented as individual code chunks with comprehensive details so that users can modify the framework to accommodate different protocols. We present the framework to quantify the following quality control metrics: library complexity, nascent RNA purity, nuclear run-on efficiency, alignment rate, sequencing depth, and RNA degradation.

bioinformatics↗

bioRxiv2022

Preventing multiple resistance above all: new insights for managing fungal adaptation

Sustainable crop protection is crucial for food security, but is threatened by the adaptation of diverse, evolving pathogen population. Resistance can be managed by maximizing selection pressure diversity, by dose variation and the spatial and temporal combination of active ingredients. We explored the interplay between operational drivers for maximizing management strategy sustainability relative to the resistance status of fungal populations. We applied an experimental evolution approach to three artificial populations of an economically important wheat pathogen, Zymoseptoria tritici, differing in initial resistance status. We revealed that diversified selection pressure limited the selection of resistance in naive populations and those with low frequencies of single. Increasing the number of modes of action delayed resistance development most effectively -- ahead of increasing the number of fungicides, fungicide choice based on resistance risk and temporal variation in fungicide exposure -- but favored generalism in the evolved populations. However, the prior presence of multiple resistant resistant isolates and their subsequent selection in populations overrode the effects of diversity in management strategies, incidentally invalidating any universal ranking. Initial resistance composition must therefore be considered specifically in sustainable resistance management, to address real-world field situation. Abbreviated summaryExperimental evolution is a relevant tool for exploring the determinants of antifungal adaptation in fungi. Here, using the model species Z. tritici and two fungicidal modes of action associated with contrasting resistance risks, we have demonstrated that initial population composition, and in particular the presence of multiple resistance, represents the main determinant of adaptive trajectories. Originality-Significance StatementPesticides are part of microbe environment in agricultural systems and may select for resistance. This adaptation of pathogens is a burden for plant health. Using an original multicriteria assessment and experimental evolution, we revealed that multi-fungicide use, selecting for multiple resistance, trumped any other driver of selection, invalidating any universal ranking of management strategies, a dispute extensively illustrated in literature and still inconclusive, especially in agriculture. This outcome refocuses the debate on population diversity and evolution rather than on the intrinsic properties of strategies, as mostly acclaimed in literature. From a practical point of view, our results highlight the importance of considering local population composition when recommending spraying programs. This practice is currently not generalized in agriculture but may be timely to effectively delay resistance evolution and reduce pesticide load in agricultural systems, a growing social demand, since resistance monitoring at relatively fine spatial scales and at low frequency may become commonplace in a near future with the rise of new molecular biology technologies

evolutionary biology↗

bioRxiv2022

AFsample: Improving Multimer Prediction with AlphaFold using Aggressive Sampling

The AlphaFold neural network model has revolutionized structural molecular biology with unprecedented performance. We demonstrate that by stochastically perturbing the neural network by enabling dropout at inference combined with massive sampling, it is possible to improve the quality of the generated models. We generated around 6,000 models per target compared to 25 default for AF2-multimer, with v1 and v2 multimer network models, with and without templates, and increased the number of recycles within the network. The method was benchmarked in CASP15, and compared to AF2-multimer it improved the average DockQ from 0.41 to 0.55 using identical input and was ranked at the very top in the protein assembly category when compared to all other groups participating in CASP15. The simplicity of the method should facilitate the adaptation by the field, and the method should be useful for anyone interested in modelling multimeric structures, alternate conformations or flexible structures. AvailabilityAFsample is available online at http://wallnerlab.org/AFsample.

bioinformatics↗

bioRxiv2022

DNA origami 2.0

DNA origami is a technique that allows the creation of precise, modular, and programmable nanostructures using DNA. These nanostructures have found use in several fields like biophysics, molecular biology, nanoelectronics, and nanophotonic due to their programmable nature as well as ability to organize other nanomaterials with high accuracy. However, they are fragile and unstable when removed from their optimal aqueous conditions. In contrast, other commonly used bottom-up methods for creating inorganic nanoparticles do not have these issues, but it is difficult to control the shape or spatial organization of ligands on these nanoparticles. In this study, we present a simple, highly controlled method for templated growth of silica on top of DNA origami while preserving all the salient features of DNA origami. Using the polyplex micellization (PM) strategy, we create DNA nanostructures that can withstand salt-free, buffer-free, alcohol-water mixtures, enabling us to control the material growth conditions while maintaining the monodispersity and organization of nanoelements. We demonstrate the growth of silica shells of different thicknesses on brick and ring-shaped DNA origami structures using the standard Stober process. We also demonstrate the thermostability of the silica-coated nanostructures as well as accessibility of surface sites programmed into the DNA origami after the silica growth in the final inorganic nanostructure.

bioengineering↗

bioRxiv2023

Composition of nasopharyngeal microbiota in individuals with SARS-COV-2 infection across three COVID-19 waves in India

Multiple variants of the SARS-CoV-2 virus have been plaguing the world through successive waves of infection over the past three years. Studies by independent research groups across geographies have shown that the microbiome composition in COVID-19 patients (CP) differ from that of healthy individuals (CN). However, such observations were based on limited-sized sample-sets collected primarily from the early days of the pandemic. Here, we study the nasopharyngeal microbiota in COVID-19 patients, wherein the samples have been collected across the three COVID-19 waves witnessed in India, which were driven by different variants of concern. We also present the variations in microbiota of symptomatic vs asymptomatic COVID-19 patients. The nasopharyngeal swabs were collected from 589 subjects providing samples for diagnostics purposes at Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India. CP showed a marked shift in the microbial diversity and composition compared to CN, in a wave-dependent manner. Rickettsiaceae was the only family that was noted to be consistently depleted in CP samples across the waves. The genera Staphylococcus, Anhydrobacter, Thermus, and Aerococcus were observed to be highly abundant in the symptomatic CP patients when compared to the asymptomatic group. In general, we observed a decrease in the burden of opportunistic pathogens in the host microbiota during the later waves of infection. To our knowledge, this is the first longitudinal study which was designed to understand the relation between the evolving nature of the virus and the changes in the human nasopharyngeal microbiota. Such studies not only pave way for better understanding of the disease pathophysiology but also help gather preliminary evidence on whether interventions to the host microbiota can help in better protection or faster recovery.

microbiology↗

bioRxiv2023

The regulatory role of the CD2AP/TKS4 interaction in EMT and its potential as abiomarker for colon cancer

BackgroundColon cancer is a leading cause of death worldwide. Although several biomarkers have been developed, more sensitive and specific methods are needed for its early detection. TKS4 and CD2AP scaffold proteins have been already linked to dynamic actin assembly-related processes, such as colon cancer cell migration, although their co-instructive role during tumour-formation remains unknown. Therefore, this study was designed to validate TKS4-CD2AP interaction and study the interdependent effect of TKS4/CD2AP on oncogenic events. MethodsCD2AP was identified as a novel TKS4 interacting partner in six cell lines via co-immunoprecipitation-mass spectrometry. The interaction was validated via western blot, immunocytochemistry, DuoLink assay and peptide microarray. Gene silencing and overexpressing experiments were performed to uncover the cooperative effects of TKS4 and CD2AP in cell movement and in epithelial-mesenchymal transition (EMT). The expression levels of TKS4 and CD2AP mRNAs were quantified using a human colon cancer array, and the results were subjected to bioinformatic database analysis. ResultsThe molecular biology analysis revealed that one of the SH3-domain of CD2AP interacts with a proline-rich short linear motif in TKS4. Functional studies showed that TKS4 and CD2AP form a scaffold complex that regulates migration- and EMT-related pathways of colon cancer cells. The relative TKS4 and CD2AP expression level measurements pointed out that CD2AP/TKS4 ratio is a sensitive biomarker for the identification of tumorous colon tissue. ConclusionsThis is the first study demonstrating the TKS4-CD2AP protein-protein interaction in vitro and in vivo and their interdependent regulative effect on mesenchymal transition-like process in colon cancer. Furthermore, the results highlight that the relative expression levels of CD2AP and TKS4 might serve as a biomarker for the diagnosis of early-stage colon cancer.

cancer biology↗

bioRxiv2023

SHARE-Topic: Bayesian Inerpretable Modelling of Single-Cell Multi-Omic Data

Single-cell sequencing technologies are providing unprecedented insights into the molecular biology of individual cells. More recently, multi-omic technologies have emerged which can simultaneously measure gene expression and the epigenomic state of the same cell, holding the promise to unlock our understanding of the epigenetic mechanisms of gene regulation. However, the sparsity and noisy nature of the data pose fundamental statistical challenges which hinder our ability to extract biological knowledge from these complex data sets. Here we propose SHARE-Topic, a Bayesian generative model of multi-omic single cell data which addresses these challenges from the point of view of topic models. SHARE-Topic identifies common patterns of co-variation between different omic layers, providing interpretable explanations for the complexity of the data. Tested on joint ATAC and expression data, SHARE-Topic was able to provide low dimensional representations that recapitulate known biology, and to define in a principled way associations between genes and distal regulators in individual cells. We illustrate SHARE-Topic in a case study of B-cell lymphoma, studying the usage of alternative promoters in the regulation of the FOXP1 transcription factors.

bioinformatics↗

bioRxiv2023

Unraveling codon usage of Escherichia coli using machine learning

Machine learning is used to investigate the codon usage of protein-encoding genes, which is one of the fundamental questions of molecular biology. The presentation, parameter learning, and decoding of the conditional random field (CRF) model are implemented and then utilized to analyze the codon usage of the genes of Escherichia coli and its phages. Most genes of E. coli use codons conforming to the weights of the model determined by all E. coli genes. Phages use the codons like their host E. coli. Finally, the study evaluates the codon usage of several example genes in the context of the model. These results help to understand the codon usage in E. coli.

systems biology↗