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Results for “molecular biology”

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bioRxiv2014

E. coli OxyS non-coding RNA does not trigger RNAi in C. elegans

The discovery of RNA interference (RNAi) in C. elegans has had a major impact on scientific research, led to the rapid development of RNAi tools and has inspired RNA-based therapeutics. Astonishingly, nematodes, planaria and many insects take up double-stranded RNA (dsRNA) from their environment to elicit RNAi; the biological function of this mechanism is unclear. Recently, the E. coli OxyS non-coding RNA was shown to regulate gene expression in C. elegans when E. coli is offered as food. This was surprising given that C. elegans is unlikely to encounter E. coli in nature. To directly test the hypothesis that the E. coli OxyS non-coding RNA triggers the C. elegans RNAi pathway, we sequenced small RNAs from C. elegans after feeding with bacteria. We clearly demonstrate that the OxyS non-coding RNA does not trigger an RNAi response in C. elegans. We conclude that the biology of environmental RNAi remains to be discovered.

Molecular Biology↗

bioRxiv2020

CUT&RUN reveals unique positioning of pre-initiated RNA polymerase II in the steady state of transcription

CUT&RUN is a powerful tool to study protein-DNA interactions in vivo. DNA fragments cleaved by the targeted micrococcal nuclease identify the footprints of DNA-binding proteins on the chromatin. We performed CUT&RUN on human lung carcinoma cell line A549 maintained in a multi-well cell culture plate to profile RNA polymerase II. Long (>270 bp) DNA fragments released by CUT&RUN corresponded to the bimodal peak around the transcription start sites, as previously seen with chromatin immunoprecipitation. However, we found that short (<120 bp) fragments identify a well-defined peak localised at the transcription start sites. This distinct DNA footprint of short fragments, which constituted only about 5% of the total reads, suggests the transient positioning of RNA polymerase II before promoter-proximal pausing, which has not been detected in the physiological settings by standard chromatin immunoprecipitation. We showed that the positioning of the large-size-class DNA footprints around the short-fragment peak was associated with the directionality of transcription, demonstrating the biological significance of distinct CUT&RUN footprints of RNA polymerase II.

molecular biology↗

bioRxiv2022

A CRISPR-dCas13 RNA-editing tool to study alternative splicing

Alternative splicing allows multiple transcripts to be generated from the same gene to diversify the protein repertoire and gain new functions despite a limited coding genome. It can impact a wide spectrum of biological processes, including disease. However, its significance has long been underestimated due to limitations in dissecting the precise role of each splicing isoform in a physiological context. Furthermore, identifying key regulatory elements to correct deleterious splicing isoforms has proven equally challenging, increasing the difficulty to tackle the role of alternative splicing in cell biology. In this work, we take advantage of dCasRx, a catalytically inactive RNA targeting CRISPR-dCas13 ortholog, to efficiently switch alternative splicing patterns of endogenous transcripts without affecting overall gene expression levels in a cost-effective manner. Additionally, we demonstrate a new application for the dCasRx splice-editing system to identify key regulatory RNA elements of specific splicing events. With this approach, we are expanding the RNA toolkit to better understand the regulatory mechanisms underlying alternative splicing and its physiological impact in various biological processes, including pathological conditions.

molecular biology↗

bioRxiv2022

IDENTIFICATION AND QUANTIFICATION OF MATRISOME PROTEINS OF MOUSE KIDNEYS

Extracellular matrix (ECM) is essential for tissue homeostasis. Understanding the matrisome (ECM proteome) composition and mechanisms of ECM control in health and disease is crucial for discovering therapeutic agents and diagnostic tools for inflammatory, fibrotic and cancerous conditions. The challenging obstacle in the ECM analysis is the need to optimise matrisome enrichment methods for different organs, diseases, and species. Currently, there is no optimized protocol nor a publicly available matrisome database for mouse kidneys. This limits the power of murine models in renal diseases and development research. In this study, we comparatively explored the matrisome of healthy C57BL/6 mice using two matrisome extraction methods, including the Millipore Compartment Fractionation (Method-1) and the Sequential Extraction (Method-2) approaches. We examined the efficiency of these methods in matrisome profiling by LC-MS/MS, protein identification and label-free quantification using MaxQuant. As a result of the study, 113 matrisome proteins were identified, including 22 proteins that have not been previously listed in the Matrisome Database (MD). Method-2 allowed identification and quantification of all core and ECM-associated matrisome proteins detected by Method-1 and additionally revealed more core matrisome and ECM-associated proteins. By characterisation of the murine renal matrisome enhanced by our methodological insights, this study provides critically important information for biological and medical kidney research.

molecular biology↗

bioRxiv2022

Do Newly Born Orphan Proteins Resemble Never Born Proteins?A Study using Deep Learning Algorithms

Newly Born proteins, devoid of detectable homology to any other proteins, known as orphan proteins, occur in a single species or within a taxonomically restricted gene family. They are generated by expression of novel Open Reading Frames, and appear throughout evolution. We were curious if the three recently developed programs for predicting protein structures, viz., AlphaFold2, RoseTTAFold, and ESMFold, might be of value for comparison of such Newly Born proteins to random polypeptides with amino acid content similar to that of native proteins, which have been called Never Born proteins. The programs were used to compare the structures of two sets of Never Born proteins that had been expressed - Group 1, which had been shown experimentally to possess substantial secondary structure, and Group 3, which had been shown to be intrinsically disordered. Overall, the models generated were scored as being of low quality but revealed some general principles. Specifically, all four members of Group 1 were predicted to be compact by all three algorithms. The members of Group 3 were predicted to be very extended, as would be expected for intrinsically disordered proteins. The three programs were then used to predict the structures of three orphan proteins whose crystal structures had been solved, two of which display novel folds. Finally, they were used to predict the structures of seven orphan proteins with well-identified biological functions, whose 3D structures are not known. Two proteins, which were predicted to be disordered based on their sequences, are predicted by all three structure algorithms to be extended structures. The other five were predicted to be compact structures with two exceptions in the case of AlphaFold2. All three prediction algorithms make remarkably similar and high-quality predictions for one large protein, HCO_11565, from a nematode. It is conjectured that this is due to many homologs in the taxonomically restricted family of which it is a member and to the fact that the Dali server revealed several non-related proteins with similar folds. Overall, orphan and taxonomically restricted proteins are often predicted to have compact 3D structures, sometimes with a novel fold that is a consequence of their novel sequences, which are associated with the appearance of new biological functions.

molecular biology↗

bioRxiv2019

qDRIP: Quantitative differential RNA:DNA hybrid immunoprecipitation sequencing

R-loops are dynamic, co-transcriptional nucleic acid structures that facilitate physiological processes and cause DNA damage in certain contexts. Perturbations of transcription or R-loop resolution are expected to change their genomic distribution. Next-generation sequencing approaches to map RNA:DNA hybrids, a component of R-loops, have so far not allowed quantitative comparisons between such conditions. Here we describe quantitative differential RNA:DNA immunoprecipitation (qDRIP), a method combining synthetic RNA:DNA-hybrid internal standards with high-resolution, strand-specific sequencing. We show that qDRIP avoids biases inherent to read-count normalization by accurately profiling signal in regions unaffected by transcription inhibition in human cells, and by facilitating accurate differential peak calling between conditions. Finally, we use these quantitative comparisons to make the first estimates of the absolute count of RNA:DNA hybrids per cell and their half-lives genome-wide. Overall, qDRIP allows for accurate normalization in conditions where R-loops are perturbed and for quantitative measurements that provide previously unattainable biological insights.

molecular biology↗

bioRxiv2017

Watching the clock for 25 years in FlyClockbase: Variability in circadian clocks of Drosophila melanogaster as uncovered by biological model curation

Biological model curation provides new insights by integrating biological knowledge-fragments, assessing their uncertainty, and analyzing the reliability of potential interpretations. Here we integrate published results about circadian clocks in Drosophila melanogaster while exploring economies of scale in biological model curation. Clocks govern rhythms of gene-expression that impact fitness, health, cancer, memory, mental functions, and more. Human clock insights have been repeatedly pioneered in flies. Flies simplify investigating complex gene regulatory networks, which express proteins cyclically using environmentally entrained interlocking feedback loops that act as clocks. Simulations could simplify research further. We found that very few computational models test their quality directly against experimentally observed time series scattered in the literature. We designed FlyClockbase for integrating such scattered data to enable robust efficient access for biologists and modelers. To this end we have been defining data structures that simplify the construction and maintenance of Versioned Biological Information Resources (VBIRs) that prioritize simplicity, openness, and therefore maintainability. We aim to simplify the preservation of more raw data and relevant annotations from experiments in order to multiply the long-term value of wet-lab datasets for modelers interested in meta-analyses, parameter estimates, and hypothesis testing. Currently FlyClockbase contains over 400 wildtype time series of core circadian components systematically curated from 86 studies published between 1990 and 2015. Using FlyClockbase, we show that PERIOD protein amount peak time variance unexpectedly exceeds that of TIMELESS. We hypothesize that PERIODs exceedingly more complex phosphorylation rules are responsible. Variances of daily event times are easily confounded by errors. We improved result reliability by a human error analysis of our data handling; this revealed significance-degrading outliers, possibly violating a presumed absence of wildtype heterogeneity or lab evolution. Separate analyses revealed elevated stochasticity in PCR-based peak time variances; yet our reported core difference in peak time variances appears robust. Our study demonstrates how biological model curation enhances the understanding of circadian clocks. It also highlights diverse broader challenges that are likely to become recurrent themes if models in molecular systems biology aim to integrate all relevant knowledge. We developed a trans-disciplinary workflow, which demonstrates the importance of developing compilers for VBIRs with a more biology-friendly logic that is likely to greatly simplify biological model curation. Curation-limited grand challenges, including personalizing medicine, critically depend on such progress if they are indeed to integrate all relevant knowledge.\n\nGeneral Article SummaryCircadian clocks impact health and fitness by controlling daily rhythms of gene-expression through complex gene-regulatory networks. Deciphering how they work requires experimentally tracking changes in amounts of clock components. We designed FlyClockbase to simplify data-access for biologists and modelers, curating over 400 time series observed in wildtype fruit flies from 25 years of clock research. Substantial biological model curation was essential for identifying differences in peak time variance of the clock-proteins PERIOD and TIMELESS, which probably stem from differences in phosphorylation-network complexity.\n\nWe repeatedly encountered systemic limitations of contemporary data analysis strategies in our work on circadian clocks. Thus, we used it as an opportunity for composing a panoramic view of the broader challenges in biological model curation, which are likely to increase as biologists aim to integrate all existing expertise in order to address diverse grand challenges. We developed and tested a trans-disciplinary research workflow, which enables biologists and compiler-architects to define biology-friendly compilers for efficiently constructing and maintaining Versioned Biological Information Resources (VBIRs). We report insights gleaned from our practical clock research that are essential for defining a VBIRs infrastructure, which improves the efficiency of biological model curation to the point where it can be democratized.\n\nStatement of data availabilityStabilizing Versioned Variant of this file: QQv1r4_2017m07d14_Lion\n\nBefore final publication FlyClockbase will be at https://github.com/FlyClockbase For review purposes FlyClockbase QQv1r4 will be provided as a zip-archive in the uploaded Supplemental Material; it is also available upon request from L. Loewe.\n\nAbbreviationsTable 1: Molecular core clock components\n\nTable 2: Concepts for organizing FlyClockbase\n\nSupplemental MaterialAppendix: Supplemental Text and Tables (32 pages included in this file, QQv1v4)\n\nSupplemental Statistical Analysis (87 pages not included in this file, QQv1v4)\n\nR-Script zip file (>12K lines not included in this file, QQv1v4)\n\nFlyClockbase zip file (available upon request, QQv1v4)

genetics↗

bioRxiv2020

Cryo-EM structural studies of the agonist complexed human TRPV4 ion-channel reveals novel structural rearrangements resulting in an open-conformation

The human transient receptor potential vanilloid 4 (hTRPV4) ion channel plays a critical role in a variety of biological processes. Whilst the activation of hTRPV4 gating properties has been reported for a broad spectrum of stimuli, including synthetic 4-phorbols, the molecular basis of the activation is poorly understood. Here we report the novel cryo-EM structure of the hTRPV4 determined in the presence of the archetypical phorbol acid agonist, 4-PDD. Complementary mutagenesis experiments support the EM-identified binding site as well as allowing rationalization of disruptive mutants located outside of the 4-PDD binding site. This work represents the first structural information of hTRPV4 in a ligand-induced open conformation. Together, our data reveal the underlying molecular mechanisms resulting in the opening of the central pore and ion-channel activation and provide a structural template for designing inhibitors targeting the open-state conformation of hTRPV4.

molecular biology↗

bioRxiv2022

The DNA replication initiation protein DnaD is recruited to a specific strand of the Bacillus subtilis chromosome origin

Genome replication is a fundamental biological activity shared by all organisms. Chromosomal replication proceeds bidirectionally from origins, requiring the loading of two helicases, one for each replisome. The molecular mechanisms for helicase loading at bacterial chromosome origins (oriC) are unclear. Here we investigated the essential DNA replication initiation protein DnaD in the model organism Bacillus subtilis. A set of DnaD residues required for ssDNA binding was identified, and photo-crosslinking revealed that this ssDNA binding region interacts preferentially with one strand of oriC. Biochemical and genetic data support the model that DnaD recognizes a new single-stranded DNA (ssDNA) motif located in oriC (DnaD Recognition Element, "DRE"). Considered with cryo-electron microscopy (cryo-EM) imaging of full length DnaD, we propose that the location of the DRE within the oriC orchestrates strand-specific recruitment of helicase to achieve bidirectional DNA replication. These findings significantly advance our mechanistic understanding of bidirectional replication from a bacterial chromosome origin.

molecular biology↗

bioRxiv2026

BiHiTo: Biomolecular Hierarchy-inspired Tokenization

Three-dimensional atomic arrangements of biomolecules are key to demystifying biological functions. The rapid expansion of accessible structural data, driven by advances in AI for science, highlights the critical challenge of efficiently modeling large-scale biomolecular structures, which are high-dimensional systems shaped by biological assembly principles. To address this, we introduce BiHiTo, a multi-level Biomolecular Hierarchy-inspired Tokenizer that intrinsically mimics natural biological assembly hierarchies. Specifically, we design a multi-codebook quantizer that mirrors the natural hierarchy of biomolecular structure, enabling simultaneous capture of representations spanning atomic motifs to global conformational variations. This hierarchical alignment markedly improves the biological interpretability and reconstruction fidelity of biomolecular structure.Extensive experiments demonstrate that BiHiTo delivers state-of-the-art performance and robust generalization across molecular dynamics trajectories and macromolecular complexes, facilitating advances in structure generation and dynamic conformation exploration. In the reconstruction of the CASP14 and OOD test set FastFolding protein multi-conformation data, our method achieves a 17% and 51% reduction in RMSD compared to Bio2Token, respectively.

molecular biology↗

bioRxiv2016

miR-106b-responsive gene landscape identifies regulation of Kruppel-like factor family

MicroRNA dysregulation is a common feature of cancer and due to the promiscuity of microRNA binding this can result in a wide array of genes whose expression is altered. miR-106b is an oncomiR overexpressed in cholangiocarcinoma and its upregulation in this and other cancers often leads to repression of anti-tumorigenic targets. The goal of this study was to identify the miR-106b-regulated gene landscape in cholangiocarcinoma cells using a genome-wide, unbiased mRNA analysis. Through RNA-Seq we found 112 mRNAs significantly repressed by miR-106b. The majority of these genes contain the specific miR-106b seed-binding site. We have validated 11 genes from this set at the mRNA level and demonstrated regulation by miR-106b of five proteins. Combined analysis of our miR-106b-regulated mRNA data set plus published reports indicate that miR-106b binding is anchored by G:C pairing in and near the seed. Novel targets Kruppel-like factor 2 (KLF2) and KLF6 were verified both at the mRNA and at the protein level. Further investigation showed regulation of four other KLF family members by miR-106b. We have discovered coordinated repression of several members of the KLF family by miR-106b that may play a role in cholangiocarcinoma tumor biology.

molecular biology↗

bioRxiv2020

ELAVL1 Exclusively Couples mRNA Stability with the 3'UTRs of Interferon Stimulated Genes

Upon detection of a pathogen, the innate immune system triggers signaling events leading to the transcription of mRNAs that encode for pro-inflammatory and anti-microbial effectors. RNA-binding proteins (RBPs) interact with these functionally critical mRNAs and temporally regulate their fates at the post-transcriptional level. One such RBP is ELAVL1, which is known to bind to introns and 3UTRs. While significant progress has been made in understanding how ELAVL1 regulates mRNAs, how its target repertoire and binding affinity changes within an immunological context remains poorly understood. Here, we overlap four distinct high-throughput approaches to define its cell-type and context-dependent targets and determine its regulatory impact during immune activation. ELAVL1 overwhelmingly binds to intronic sites in a naive state, but during an innate immune response, ELAVL1 targets the 3UTR - binding both previously and newly expressed mRNAs. We find that ELAVL1 mediates the RNA stability of genes that regulate the pathways involved in pathogen sensing and cytokine production. Our findings reveal the importance of examining RBP regulatory impact under dynamic transcriptomic events to best understand their post-transcriptional regulatory roles within specific biological circuitries.

molecular biology↗

bioRxiv2020

Cancer-Associated Mutations Perturb the Structure and Interactions of the Intrinsically Disordered p53 Transactivation Domain

Intrinsically disordered proteins (IDPs) are key components of regulatory networks that control crucial aspects of cell decision making. The intrinsically disordered transactivation domain (TAD) of tumor suppressor p53 mediates its interactions with multiple regulatory pathways to control the p53 homeostasis during the cellular response to genotoxic stress. Many cancer-associated mutations have been discovered in p53-TAD, but their structural and functional consequences are poorly understood. Here, by combining atomistic simulations, NMR spectroscopy, and binding assays, we demonstrate that cancer-associated mutations can significantly perturb the balance of p53 interactions with key activation and degradation regulators. Importantly, mutations do not all directly disrupt the known interaction interfaces. Instead, some mutations likely modulate the disordered state of p53-TAD, which affects the interactions. Our work suggests that the disordered conformational ensemble of p53-TAD can serve as a central conduit in regulating the response to various cellular stimuli at the protein-protein interaction level. Understanding how the disordered state of IDPs may be modulated by regulatory signals and/or disease associated perturbations will be essential in the studies on the role of IDPs in biology and diseases.

molecular biology↗

bioRxiv2021

Efficient tagging and purification of endogenous proteins for structural studies by single particle cryo-EM

A major bottleneck in structural biology is producing biologically relevant samples at sufficient quantities. This is particularly true for large protein assemblies where conventional techniques of gene overexpression require substantial optimization, hampering structural studies and drug development efforts. Here we describe a method combining CRISPR/Cas gene editing and fluorescence cell sorting to rapidly tag and purify endogenous human proteins from cell lines, enabling structural analysis of native proteins that are properly folded and assembled. We applied this approach to study the human proteasome from HEK cells and rapidly determined structures of major proteasomal complexes. Structures of the PA28-20S complex reveal the native subunit stoichiometry of PA28 and a distinct functional state of the complex. The efficient strategy for tagging and extracting endogenous proteins described here will enable the structural study of many challenging targets and provide more biologically relevant samples for research and therapeutic development.

molecular biology↗

bioRxiv2023

Viral and bacterial ecogenomics in globally expanding red snow blooms

Chlamydomonas algal blooms give snowmelt a red color, reducing snow albedo and creating a runaway effect that accelerates snow melting. The occurrence of red snow is predicted to grow in polar and subpolar regions with increasing global temperatures. Here, a global metaanalysis of microbial abundances showed that red snow had higher microbial abundances than white snow. We hypothesize that the increased microbial densities affect virus-bacteria interactions in snow, with potential effects on snowmelt dynamics. A genomic analysis of viral and bacterial communities in red and white snow from the Whistler region of British Columbia, Canada, identified 792 putative viruses infecting bacteria. The most abundant putative snow viruses displayed low genomic similarity with known viruses. We recovered the complete circular genomes of nine putative viruses, two of which were classified as temperate. Genomes of putative snow viruses encoded genes involved in energy metabolisms, such as NAD+ synthesis and salvage pathways. In model phages, these genes facilitate increased viral particle production and lysis rates. Yet, the frequency of temperate phages was positively correlated with microbial abundance in the snow samples. These results suggest the increased significance of temperate virus-bacteria interactions as microbial densities increase during snowmelt. We propose that this virus-bacteria dynamic may facilitate the red snow algae growth stimulated by bacteria, representing a potential biological feedback on snowmelt rates.

molecular biology↗

bioRxiv2023

Tardigrade secretory proteins protect biological structures from desiccation

Tardigrades, microscopic animals that survive a broad range of environmental stresses, express a unique set of proteins termed tardigrade-specific intrinsically disordered proteins (TDPs). TDPs are often expressed at high levels in tardigrades upon desiccation, and appear to mediate stress adaptation. Here, we focused on the proteins belonging to the secretory family of tardigrade proteins termed secreted-abundant heat soluble ("SAHS") proteins, and investigated their ability to protect diverse biological structures. Recombinantly expressed SAHS proteins prevented desiccated liposomes from fusion, and enhanced desiccation tolerance of E. coli and Rhizobium tropici upon extracellular application. Molecular dynamics simulation and comparative structural analysis suggest a model by which SAHS proteins may undergo a structural transition upon desiccation, in which removal of water and solutes from a large internal cavity in SAHS proteins destabilizes the beta-sheet structure. These results highlight the potential application of SAHS proteins as stabilizing molecules for preservation of cells.

molecular biology↗

bioRxiv2024

Fine-tuning BERT models to extract transcriptional regulatory interactions of bacteria from biomedical literature

AbstractCuration of biomedical literature has been the traditional approach to extract relevant biological knowledge; however, this is time-consuming and demanding. Recently, Large language models (LLMs) based on pre-trained transformers have addressed biomedical relation extraction tasks outperforming classical machine learning approaches. Nevertheless, LLMs have not been used for the extraction of transcriptional regulatory interactions between transcription factors and regulated elements (genes or operons) of bacteria, a first step to reconstruct a transcriptional regulatory network (TRN). These networks are incomplete or missing for many bacteria. We compared six state-of-the-art BERT architectures (BERT, BioBERT, BioLinkBERT, BioMegatron, BioRoBERTa, LUKE) for extracting this type of regulatory interactions. We fine-tuned 72 models to classify sentences in four categories: activator, repressor, regulator, and no relation. A dataset of 1562 sentences manually curated from literature of Escherichia coli was utilized. The best model of LUKE architecture obtained a relevant performance in the evaluation dataset (Precision: 0.8601, Recall: 0.8788, F1-Score Macro: 0.8685, MCC: 0.8163). An examination of model predictions revealed that the model learned different ways to express the regulatory effect. The model was applied to reconstruct a TRN of Salmonella Typhimurium using 264 complete articles. We were able to accurately reconstruct 82% of the network. A network analysis confirmed that the transcription factor PhoP regulated many genes (uppermost degree), some of them responsible for antimicrobial resistance. Our work is a starting point to address the limitations of curating regulatory interactions, especially for the reconstruction of TRNs of bacteria or diseases of biological interest.

molecular biology↗

bioRxiv2024

TOMOMAN: a software package for large scale cryo-electron tomography data preprocessing, community data sharing, and collaborative computing

Cryo-electron tomography (cryo-ET) and subtomogram averaging (STA) are becoming the preferred methodologies for investigating subcellular and macromolecular structures in native or near-native environments. While cryo-ET is amenable to a wide range of biological problems, these problems often have data processing requirements that need to be individually optimized, precluding the notion of a one-size-fits-all processing pipeline. Cryo-ET data processing is also becoming progressively more complex due to an increasing number of packages for each processing step. Though each package has its own strengths and weaknesses, independent development and different data formats makes them difficult to interface with one another. TOMOMAN (TOMOgram MANager) is an extensible package for streamlining the interoperability of packages, enabling users to develop project-specific processing workflows. TOMOMAN does this by maintaining an internal metadata format and wrapping external packages to manage and perform preprocessing, from raw tilt-series data to reconstructed tomograms. TOMOMAN can also export this metadata between various STA packages. TOMOMAN also includes tools for archiving projects to data repositories; allowing subsequent users to download TOMOMAN projects and directly resume processing where it was previously left off. By tracking essential metadata, TOMOMAN streamlines data sharing, which improves reproducibility of published results, reduces computational costs by minimizing reprocessing, and enables distributed cryo-ET projects between multiple groups and institutions. TOMOMAN provides a way for users to test different software packages to develop processing workflows that meet the specific needs of their biological questions and to distribute their results with the broader scientific community.

molecular biology↗