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Results for “Molecular Biology”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2020

Grandmother's chemical legacy of pesticide exposure: bi-generational effects and acclimation in a model invertebrate

Man-made chemicals are a significant contributor to the ongoing deterioration of ecosystems. Currently, risk assessment of these chemicals is based on observations in a single generation of animals, despite potential adverse intergenerational effects. Here, we investigate the effect of the fungicide prochloraz across three generations of Daphnia magna. We studied both the effects of continuous exposure over all generations and the effects of first-generation (F0) exposure on two subsequent, non-exposed, generations. Effects at different levels of biological organization were monitored. Acclimation to prochloraz was found after continuous exposure. Following F0-exposure, non-exposed F1-offspring showed no significant effects. However, in the F2 animals, several parameters differed significantly from controls. A direct association between grandmaternal effects and toxic mode of action of prochloraz was found, showing that chemicals can be harmful not only to the exposed generation, but also to subsequent generations and that effects may even skip a generation.

molecular biology↗

bioRxiv2023

Latent transcriptional programs reveal histology-encoded tumor features spanning tissue origins

Precision medicine in cancer treatment depends on deciphering tumor phenotypes to reveal the underlying biological processes. Molecular profiles, including transcriptomics, provide an information-rich tumor view, but their high-dimensional features and assay costs can be prohibitive for clinical translation at scale. Recent studies have suggested jointly leveraging histology and genomics as a strategy for developing practical clinical biomarkers. Here, we use machine learning techniques to identify de novo latent transcriptional processes in squamous cell carcinomas (SCCs) and to accurately predict their activity levels directly from tumor histology images. In contrast to analyses focusing on pre-specified, individual genes or sample groups, our latent space analysis reveals sets of genes associated with both histologically detectable features and clinically relevant processes, including immune response, collagen remodeling, and fibrosis. The results demonstrate an approach for discovering clinically interpretable histological features that indicate complex, potentially treatment-informing biological processes.

cancer biology↗

bioRxiv2025

Multiplexed single-cell transcriptomics reveals diverse phenotypic outcomes for pathogenic SHP2 variants

The protein tyrosine phosphatase SHP2, encoded by PTPN11, is an important regulator of Ras/MAPK signaling that acts downstream of receptor tyrosine kinases and other transmembrane receptors. Germline PTPN11 mutations cause developmental disorders such as Noonan Syndrome, whereas somatic mutations drive various cancers. While many pathogenic mutations enhance SHP2 catalytic activity, others are inactivating or affect protein interactions, confounding our understanding of SHP2-driven disease. Here, we combine single-cell transcriptional profiling of cells expressing clinically diverse SHP2 variants with protein biochemistry, structural analysis, and cell biology to explain how pathogenic mutations dysregulate signaling. Our analyses reveal that loss of catalytic activity does not phenocopy SHP2 knock-out at the gene expression level, that some mechanistically distinct mutations have convergent phenotypic effects, and that different mutations at the same hotspot residue can yield divergent cell states. These findings provide a framework for understanding the connection between SHP2 structural perturbations, cellular outcomes, and human diseases.

molecular biology↗

bioRxiv2019

Nuclear gene transformation in a dinoflagellate

The lack of a robust gene transformation tool that allows functional testing of the vast number of nuclear genes in dinoflagellates has greatly hampered our understanding of fundamental biology in this ecologically important and evolutionarily unique lineage. Here we report the development of a dinoflagellate expression vector, an electroporation protocol, and successful expression of introduced genes in the dinoflagellate Oxyrrhis marina. This protocol, involving the use of Lonzas Nucleofector and a codon optimized antibiotic resistance gene, has been successfully used to produce consistent results in several independent experiments. It is anticipated that this protocol will be adaptable for other dinoflagellates and will allow characterization of many novel dinoflagellate genes.

molecular biology↗

bioRxiv2025

Dual Probe Ligation In Situ Hybridization with Rolling-Circle Amplification for High-Plex Spatial Transcriptomics

New biological insights are increasingly dependent upon a deeper understanding of tissue architectures. Critical to such studies are spatial transcriptomics technologies, especially those amenable to analysis of the most widely available human tissue type, formalin-fixed and paraffin-embedded (FFPE) clinical specimens. Here we build on our previous oligonucleotide probe ligation-based approach to accurately analyze FFPE mRNA, which suffers from variable levels of degradation. Ligation In Situ Hybridization followed by rolling circle amplification (LISH-LocknRoll or LISH-LnR), provides a streamlined method to detect the spatial location of specific mRNA isoforms within FFPE tissue architectures. Iterative fluorescent probe hybridization and imaging enables highly multiplexed spatial transcriptomic studies, as demonstrated herein for fixed specimens from inclusion body myositis patients and pediatric rhabdomyosarcoma patients. We additionally demonstrate a system of molecular rheostats that can be used to fine tune the performance of the LISH-LnR assay. Combined with LISH-seq and LISH-QC, the LISH-LnR methodology provides a powerful approach to spatial transcriptomics.

molecular biology↗

bioRxiv2020

Bright and tunable far-red chemigenetic indicators

Functional imaging using fluorescent indicators has revolutionized biology but additional sensor scaffolds are needed to access properties such as bright, far-red emission. We introduce a new platform for chemigenetic fluorescent indicators, utilizing the self-labeling HaloTag protein conjugated to environmentally sensitive synthetic fluorophores. This approach affords bright, far-red calcium and voltage sensors with highly tunable photophysical and chemical properties, which can reliably detect single action potentials in neurons.

molecular biology↗

bioRxiv2023

The diversity of splicing modifiers acting on A-1 bulged 5'-splice sites reveals rules to guide rational design

Non-physiological alternative splicing patterns are associated with numerous human diseases. Among the strategies developed to treat these diseases, small molecule splicing modifiers are emerging as a new class of RNA therapeutics. The SMN2 splicing modifier SMN-C5 was used as a prototype to understand their mode of action and discover the concept of 5-splice site bulge repair. However, different small molecules harbouring a similar activity were also identified. In this study, we combined NMR spectroscopy and computational approaches to determine the binding modes of other SMN2 and HTT splicing modifiers at the interface between U1 snRNP and an A-1 bulged 5-splice site. Our results show that the other splicing modifiers interact with the intermolecular RNA helix epitope containing an unpaired adenine within a G-2A-1G+1U+2 motif, which is essential for their biological activity. We also determined structural models of risdiplam, SMN-CX, and branaplam bound to RNA, and solved the solution structure of the most divergent SMN2 splicing modifier, SMN-CY, in complex with the RNA helix. These findings not only deepen our understanding of the chemical diversity of splicing modifiers that target A-1 bulged 5-splice sites, but also identify common pharmacophores required for modulating 5-splice site selection with small molecules.

molecular biology↗

bioRxiv2024

An Atlas of Cellular Archetypes

We sought to discover universal organizing principles behind phenotypic variation within cell types. Pareto optimality describes how trade-offs between optimal solutions account for variation, predicting that the boundary points of a data distribution reflect specialized functions. We hypothesized that Pareto optimality dominates transcriptomic variation across all cell types. We used the Tabula Sapiens atlas of single-cell RNA sequencing across cell types and tissues in the human body to test this hypothesis and discovered that most cell types adhere to this theory. This enabled us to use this principled method to characterize the functions performed by each cell type. These phenotypes are derived from an unbiased approach and do not incorporate ideas from existing biological models or theories, and yet in many cases they recapitulate our understanding of the functions of major cell types. Ultimately, we conclude that multi-objective optimization broadly shapes the observed phenotypic variation within cell types. This finding enables us to write explicit representations of the low-dimensional manifolds on which transcriptomes of single cells reside. This can inform the design of the next generation of virtual cell language models, which aim to statistically learn low-dimensional transcriptomic manifolds.

molecular biology↗

bioRxiv2024

Cell surface ribonucleoproteins cluster with heparan sulfate to regulate growth factor signaling

Receptor-ligand interactions govern a wide array of biological pathways, facilitating a cells ability to interrogate and integrate information from the extracellular space. Here, using an unbiased genome-wide knockout screen, we identify heparan sulfate proteoglycans (HSPGs) as a major component in the organizational mechanism of cell surface glycoRNA and cell surface RNA binding proteins (csRBPs). Cleavage of mature heparan sulfate chains, knockout of N- and 6-O-sulfotransferases, overexpression of endo-6-O-sulfatases, or the addition of exogenous heparan sulfate chains with high 2-O sulfation result in marked loss in glycoRNA-csRBP clustering in U2OS cells. Functionally, we provide evidence that signal transduction by HS-dependent growth factors such as VEGF-A165 is regulated by cell surface RNAs, and in vitro VEGF-A165, selectively interacts with glycoRNAs. Our findings uncover a new molecular mechanism of controlling signal transduction of specific growth factors across the plasma membrane by the regulated assembly of glycoRNAs, csRBPs, and heparan sulfate clusters.

molecular biology↗

bioRxiv2026

Fine-tuning m6A and METTL3 levels have profound impact on cellular proliferation and protein synthesis

The RNA modification m6A is the most abundant internal RNA modification in eukaryotic mRNAs and long non-coding RNAs and has been implicated in diverse and important biological processes. Notably, m6A has been associated with both pro and anti-tumorigenic roles depending on cellular and biological context. In basal-like triple negative breast cancer (TNBC), heterozygous loss of the m6A methyltransferase METTL3 and increased levels of the m6A demethylase FTO are associated with poor prognosis and an increased risk of metastasis. Here, using CRISPR generated METTL3 heterozygous knockout TNBC cell lines (MDA-MB-468) and Nanopore direct RNA sequencing, we characterise transcriptome-wide changes in m6A modification patterns following partial loss of METTL3. We reveal that partial loss of global m6A is associated with preferential changes in the methylation status of transcripts involved in translational control, leading to an increase in translational output and proliferative capacity. In contrast, strong pharmacologic inhibition of METTL3 suppresses translation and proliferation. Our findings highlight how m6A levels differentially regulate gene expression in a dose dependent manner and provides a deeper molecular understanding of the RNA modification m6A and its role in fine-tuning translation and affecting both tumorigenesis and cancer progression.

molecular biology↗

bioRxiv2024

A metabolic atlas of mouse aging

Humans are living longer, but this is accompanied by an increased incidence of age-related chronic diseases. Many of these diseases are influenced by age-associated metabolic dysregulation, but how metabolism changes in multiple organs during aging in males and females is not known. Answering this could reveal new mechanisms of aging and age-targeted therapeutics. In this study, we describe how metabolism changes in 12 organs in male and female mice at 5 different ages. Organs show distinct patterns of metabolic aging that are affected by sex differently. Hydroxyproline shows the most consistent change across the dataset, decreasing with age in 11 out of 12 organs investigated. We also developed a metabolic aging clock that predicts biological age and identified alpha-ketoglutarate, previously shown to extend lifespan in mice, as a key predictor of age. Our results reveal fundamental insights into the aging process and identify new therapeutic targets to maintain organ health.

molecular biology↗

bioRxiv2024

MuMu: a sample multiplexing protocol for droplet-based simultaneous single nuclei RNA- and ATAC-seq systems

Sample multiplexing is a common approach to reduce experimental cost and technical batch effect. Here, we present a protocol that for the first time allows the pooling of single nuclei from multiple biological samples prior to performing simultaneous single nuclei RNA-seq and ATAC-seq, which we term Multiplexed Multiome (MuMu). We describe steps for assembling the custom Tn5 transposome, performing the transposition reaction, nuclei pooling, sequencing library preparation, and sequencing data pre-processing. This protocol will greatly reduce the cost of sn-Multiome. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=163 HEIGHT=200 SRC="FIGDIR/small/625728v2_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@19d7962org.highwire.dtl.DTLVardef@18c1c04org.highwire.dtl.DTLVardef@18355a9org.highwire.dtl.DTLVardef@16cdb6f_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2025

Spatio-temporal protein interaction analysis using bimolecular fluorescence complementation in C. elegans

Dynamic protein-protein interactions (PPIs) shape all aspects of cellular biology. Thus, significant efforts have been made to develop assays testing binary PPIs. The transparency of C. elegans makes it a great model organism for fluorescence-based PPI detection in vivo. However, to date, there is currently a lack of quantitative PPI assays that also provide information on the subcellular location of protein interactions in C. elegans. Here, we have made several modifications to the original bimolecular fluorescence complementation (BiFC) assay used in C. elegans to make it more quantitative and spatio-temporally controlled. First, transgenes are expressed at single copy, reducing the variability associated with multi-copy expression. Second, we have added bicistronic reference fluorescent proteins to each transgene, allowing for the normalization and quantification of the PPI. Finally, we have incorporated the auxin-inducible degradation system, allowing for small-molecule inducible control of the PPI signal. We demonstrate the utility of our modified BiFC assay by testing several model PPIs. Thus, we anticipate that our updated BiFC approach will expand the available tools for studying PPIs in C. elegans, but similar logic could be applied to other model organisms amenable to transgenesis and in vivo fluorescent imaging. Article SummaryProtein-protein interactions (PPIs) play a central role in all facets of cellular biology. Here, we developed an improved assay to study PPIs in C. elegans, based on bimolecular fluorescence complementation (BiFC), where two halves of split-YFP can be reconstituted in an interaction-dependent manner. Our modifications include making the readout of the assay less variable and more quantitative, while also enabling signal to accumulate in an inducible manner. We envision that our updated BiFC approach will serve as a useful tool for C. elegans researchers interested in characterizing PPIs of interest in vivo.

molecular biology↗

bioRxiv2019

Unveiling the dimer/monomer propensities of Smad MH1-DNA complexes

R-Smads are effectors of the transforming growth factor {beta} (TGF{beta}) superfamily and along with Smad4 form trimers to interact with other transcription factors and with DNA. The 5GC-DNA complexes determined here by X-ray crystallography for Smad5 and Smad8 proteins corroborate that all MH1 domains bind SBE and 5GC sites similarly, although Smad2/3/4 MH1 domains bind DNA as monomers whereas Smad1/5/8 form helix-swapped dimers. To examine the relevance of the dimerization phenomenon and to exclude a possible crystallography-induced dimeric state, we studied these MH1 domains in solution. The results show that Smad5/8 domains populate dimers and monomers in equilibrium, whereas their Smad2/3/4 counterparts adopt monomeric conformations. We also found that swapping the loop1 sequence between Smad5 and Smad3 results in the Smad5 chimera-DNA complex crystallizing as a monomer, revealing that the loop1 sequence determines the monomer/dimer propensity of Smad MH1-domains. We propose that the distinct MH1-dimerization status of TGF{beta} and BMP activated Smads influences the interaction with specific loci genome-wide by distinct R-Smad and Smad4 complexes. SignificanceTGF{beta}- and BMP-activated R-Smads were believed to have different preferences with respect to the recognition of DNA motifs and to respond to specific activation inputs. However, recent results indicate that several types of R-Smads can be activated by similar receptors and that all Smads might recognize various DNA motifs. These results pose new questions as to why different types of R-Smads have been conserved for more than 500 million years if they could have a redundant function. They also raise questions as to how different Smad complexes recognize specific clusters of DNA motifs genome-wide. Here, using structural biology approaches, we elucidate some of the rules that help define the dimers of Smad-DNA complexes and propose how dimers and monomers could influence the composition of Smad complexes, as well as the recognition of specific cis-regulatory elements genome-wide. HighlightsR-Smads and Smad4 interact with 5GC and GTCT sites using a conserved binding mode. Functional differences of TGF{beta}- and BMP-activated R-Smads are not exclusively related to DNA specificity. Dimer/monomer propensities are detected in solution and in the absence of DNA. Loop1 sequence determines the propensity of R-Smads to form monomers or dimers in complexes with DNA. Author ContributionsL.R., Z.K., and T.G. designed and performed most experiments and coordinated collaborations with other authors. L.R. and E.A. cloned, expressed and purified all proteins, L.R., R.F., C.T., N.M., and J.C performed EMSA experiments. L.R., E.A., T.G., T.C., P.M.M., and M.J.M. performed the SAXS and NMR measurements and analyzed the data. P.M.M. analyzed the clustering of DNA motifs in ChIP-Seq data. Z.K. B.B. and R.P. screened crystallization conditions, collected X-ray data and determined the structures. Z.K., R.F. R.P., T.G., J.A.M., and M.J.M. analyzed the structures. All authors contributed ideas to the project. M.J.M. and R.P. supervised the project. M.J.M. wrote the manuscript with contributions from all other authors. The authors declare no conflict of interest. Data DepositionNMR assignments and chemical shifts have been deposited in the Biological Magnetic Resonance Data Bank, BMRB entry 27548, and the Small-angle scattering data and models have been deposited in SASBDB, entries SASDE32 (Smad5) and SASDE42 (Smad8). Densities and coordinates have been deposited in the Protein Data Bank, entries 6FZS (Smad5), 6FZT (Smad8), 6TBZ (Smad5_3 chimera), 6TCE (Smad5_gly mutant). This article contains supporting information.

molecular biology↗

bioRxiv2026

A high-throughput compound screen identifies multiple druggable targets in Plasmodium falciparum transmission stages

Most antimalarials are ineffective against the sexual transmission stages, known as gametocytes, of the malaria parasite Plasmodium falciparum. Their low sensitivity to drugs is attributed to limited compound uptake and a poorly understood form of cellular quiescence. Our current understanding of druggable transmission-blocking processes is therefore limited. Based on genetically engineered parasites that facilitate the mass production of synchronous mature gametocytes, we developed a high throughput drug screening platform that allowed us to test more than 50,000 compounds for gametocytocidal effects in one day. By screening a diversity-oriented library, we identified over 40 molecules that kill mature gametocytes in the low nanomolar range. Using resistance selection coupled to whole genome sequencing and drug-target interaction modelling, we followed up on three chemically tractable compounds that are also highly active against asexual parasites and prevent gametocyte transmission to mosquitoes. We show that the compound ONX-0914, a specific inhibitor of the {beta}5i/LMP7 subunit of human immunoproteasomes, targets the parasite proteasomal {beta}5 subunit. In contrast, the compounds CR-1-31-B and brusatol interfere with translation by targeting eukaryotic initiation factor 4A (eIF4A) and the peptidyl transferase center (PTC) of the 80S ribosome, respectively. Interestingly, parasite resistance to brusatol, a broad-spectrum antitumor drug, is linked to the differential modification of specific rRNA bases near the ribosomal A-site, mediated by altered base specificity of a rRNA methyltransferase. In summary, we successfully combined high-throughput compound screening with drug target deconvolution to reveal the targets and mode-of-action for three potent gametocytocidal molecules and discover the mechanism of resistance to the anti-tumorigenic drug brusatol. In addition to critically advancing our understanding of mature gametocyte biology and druggable processes in P. falciparum transmission stages, our observations made with brusatol-resistant parasites may become relevant for anti-cancer drug research.

molecular biology↗

bioRxiv2020

Exploiting prior knowledge about biological macromolecules in cryo-EM structure determination

Three-dimensional reconstruction of the electron scattering potential of biological macromolecules from electron cryo-microscopy (cryo-EM) projection images is an ill-posed problem. The most popular cryo-EM software solutions to date rely on a regularisation approach that is based on the prior assumption that the scattering potential varies smoothly over three-dimensional space. Although this approach has been hugely successful in recent years, the amount of prior knowledge it exploits compares unfavourably to the knowledge about biological structures that has been accumulated over decades of research in structural biology. Here, we present a regularisation framework for cryo-EM structure determination that exploits prior knowledge about biological structures through a convolutional neural network that is trained on known macromolecular structures. We insert this neural network into the iterative cryo-EM structure determination process through an approach that is inspired by Regularisation by Denoising. We show that the new regularisation approach yields better reconstructions than the current state-of-the-art for simulated data and discuss options to extend this work for application to experimental cryo-EM data.

molecular biology↗

bioRxiv2024

More than half of annotated human miRNAs are never expressed at levels sufficient for biological function

MicroRNAs (miRNAs) are widely studied for their role in post-transcriptional gene regulation, often using exogenous overexpression systems to reveal their functions. However, such approaches may not accurately reflect endogenous miRNA activity due to the substantially higher expression levels achieved experimentally. To address this, we sought to determine the minimal endogenous expression threshold required for a miRNA to exert biologically significant effects. By comparing these experimentally determined expression thresholds with small RNA sequencing datasets comprising hundreds of cell lines and tens of thousands of tissue samples, we found that more than half of all annotated miRNAs are never expressed at levels sufficient to be biologically relevant. This calls into question the conclusions of thousands of studies reporting functions for these lowly expressed miRNAs, whose results are likely attributable to artificial overexpression rather than physiological activity. Our study highlights the need for more rigorous evaluation of miRNA functionality in their native context, and provides further support to arguments that the size of the functional human "microRNAome" is far smaller than some estimates of miRNA numbers based upon small RNA sequencing data.

molecular biology↗

bioRxiv2025

FlexRibbon: Joint Sequence and Structure Pretraining for Protein Modeling

AO_SCPLOWBSTRACTC_SCPLOWProtein foundation models have advanced rapidly, with most approaches falling into two dominant paradigms. Sequence-based language models (e.g., ESM-2) capture sequence semantics at scale, and a number of recent works incorporate structural signals into sequence encoders. MSA-based predictors (e.g., AlphaFold 2/3) achieve accurate folding by exploiting evolutionary couplings, but their reliance on homologous sequences makes them less reliable in highly mutated or alignment-sparse regimes. We present FlexRibbon{ddagger}, a pretrained protein model that jointly learns from amino acid sequences and three-dimensional structures. Our pretraining strategy combines masked language modeling with diffusion-based denoising, enabling bidirectional sequence-structure learning without requiring MSAs. Trained on both experimentally resolved structures and AlphaFold 2 predictions, FlexRibbon captures global folds as well as flexible conformations critical for biological function. Evaluated across diverse tasks spanning interface design, intermolecular interaction prediction, and protein function prediction, FlexRibbon establishes new state-of-the-art performance on 12 different tasks, with particularly strong gains in mutation-rich settings where MSA-based methods often struggle.

molecular biology↗