SEARCH · bioRxiv Science

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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 595 records · Page 33Linked to original sources

bioRxiv2023

Evolutionary conservation of mechanical strain distributions in functional transitions of protein structures

One of the tenets of molecular biology is that dynamic transitions between three-dimensional structures determine the function of proteins. Therefore, it seems only natural that evolutionary analysis of proteins, presently based mainly on their primary sequence, needs to shift its focus towards their function as assessed by corresponding structural transitions. This can be facilitated by recent progress in cryogenic electron microscopy that provides atomic structures of multiple conformational states for proteins and protein assemblies isolated from evolutionarily related species. In this work, we study evolutionary conservation of multi-protein assembly function by using mechanical strain as a quantitative footprint of structural transitions. We adopt the formalism of finite strain analysis, developed in condensed matter physics, and apply it, as a case study, to a classical multi-protein assembly, the ATP synthase. Our Protein Strain Analysis (PSA) provides a precise characterization of rotation domains that agrees with the present biophysical knowledge. In addition, we obtain a strain distribution on the protein structure associated with functional transitions. By analyzing in detail, the strain patterns of the chains responsible for ATP synthesis across distinct species, we show that they are evolutionarily conserved for the same functional transition. Such conservation is not revealed by displacement or rotation patterns. Furthermore, within each functional transition, we can identify conserved strain patterns for ATP synthases isolated from different organisms. The observed strain conservation across evolutionary distant species indicates that strain should be essential in future structure-based evolutionary studies of protein function.

biophysics↗

bioRxiv2023

Pervasive, conserved secondary structure in highly charged protein regions

Understanding how protein sequences confer function remains a defining challenge in molecular biology. Two approaches have yielded enormous insight yet are often pursued separately: structure-based, where sequence-encoded structures mediate function, and disorder-based, where sequences dictate physicochemical and dynamical properties which determine function in the absence of stable structure. Here we study highly charged protein regions (>40% charged residues), which are routinely presumed to be disordered. Using recent advances in structure prediction and experimental structures, we show that roughly 40% of these regions form well-structured helices. Features often used to predict disorder--high charge density, low hydrophobicity, low sequence complexity, and evolutionarily varying length--are also compatible with solvated, variable-length helices. We show that a simple composition classifier predicts the existence of structure far better than well-established heuristics based on charge and hydropathy. We show that helical structure is more prevalent than previously appreciated in highly charged regions of diverse proteomes and characterize the conservation of highly charged regions. Our results underscore the importance of integrating, rather than choosing between, structure- and disorder-based approaches.

bioinformatics↗

bioRxiv2023

Population genomics-guided engineering of phenazine biosynthesis in Pseudomonas chlororaphis

The emergence of next-generation sequencing (NGS) technologies has made it possible to not only sequence entire genomes, but also identify metabolic engineering targets across the pangenome of a microbial population. This study leverages NGS data as well as existing molecular biology and bioinformatics tools to identify and validate genomic signatures for improving phenazine biosynthesis in Pseudomonas chlororaphis. We sequenced a diverse collection of 34 Pseudomonas isolates using short- and long-read sequencing techniques and assembled whole genomes using the NGS reads. In addition, we assayed three industrially relevant phenotypes (phenazine production, biofilm formation, and growth temperature) for these isolates in two different media conditions. We then provided the whole genomes and phenazine production data to a unitig-based microbial genome-wide association study (mGWAS) tool to identify novel genomic signatures responsible for phenazine production in P. chlororaphis. Post-processing of the mGWAS analysis results yielded 330 significant hits influencing the biosynthesis of one or more phenazine compounds. Based on a quantitative metric (called the phenotype score), we elucidated the most influential hits for phenazine production and experimentally validated them in vivo in the most optimal phenazine producing strain. Two genes significantly increased phenazine-1-carboxamide (PCN) production: a histidine transporter (ProY_1), and a putative carboxypeptidase (PS__04251). A putative MarR-family transcriptional regulator decreased PCN titer when overexpressed in a high PCN producing isolate. Overall, this work seeks to demonstrate the utility of a population genomics approach as an effective strategy in enabling identification of targets for metabolic engineering of bioproduction hosts.

systems biology↗

bioRxiv2023

LISTER: Semi-automatic metadata extraction from annotated experiment documentation in eLabFTW

The availability of scientific methods, code, and data is key for reproducing an experiment. Research data should be made available following the FAIR principle (findable, accessible, interoperable, and reusable). For that, the annotation of research data with metadata is central. However, existing research data management workflows often require that metadata should be created by the corresponding researchers, which takes effort and time. Here, we developed LISTER as a methodological and algorithmic solution to disentangle the creation of metadata from ontology alignment and extract metadata from annotated template-based experiment documentation using minimum effort. We focused on tailoring the integration between existing platforms by using eLabFTW as the electronic lab notebook and adopting the ISA (investigation, study, assay) model as the abstract data model framework; DSpace is used as a data cataloging platform. LISTER consists of three components: customized eLabFTW entries using specific hierarchies, templates, and tags; a container concept in eLabFTW, making metadata of a particular container content extractable along with its underlying, related containers; a Python-based app to enable easy-to-use, semi-automated metadata extraction from eLabFTW entries. LISTER outputs metadata as machine-readable .json and human-readable .csv formats, and MM descriptions in .docx format that could be used in a thesis or manuscript. The metadata can be used as a basis to create or extend ontologies, which, when applied to the published research data, will significantly enhance its value due to a more complete and holistic understanding of the data, but might also enable scientists to identify new connections and insights in their field. We applied LISTER to the fields of computational biophysical chemistry as well as protein biochemistry and molecular biology, and our concept should be extendable to other life science areas.

bioinformatics↗

bioRxiv2023

Dying cell-released exosomal CXCL1 promotes breast cancer metastasis by activating TAM/PD-L1 signaling

BackgroundEmerging evidence suggests that dying cell-released signals may induce cancer progression and metastasis by modulating the surrounding microenvironment. However, the underlying molecular mechanisms and targeting strategies are yet to be explored. MethodsApoptotic breast cancer cells induced by paclitaxel treatment were sorted and their released exosomes (exo-dead) were isolated from the cell supernatants. Chemokine array analysis was conducted to identify the crucial molecules in exo-dead. Zebrafish and mouse xenograft models were used to investigate the effect of exo-dead on breast cancer progression in vivo. Multiple molecular biological experiments were conducted to determine the underlying mechanisms of exo-dead in promoting breast cancer, as well as its intervention values. ResultsIt was demonstrated that exo-dead were phagocytized by macrophages and induced breast cancer metastasis by promoting the infiltration of immunosuppressive PD-L1+ TAMs. Chemokine array identified CXCL1 as a crucial component in exo-dead to activate TAM/PD-L1 signaling. Exosomal CXCL1 knockdown or macrophage depletion significantly inhibited exo-dead-induced breast cancer growth and metastasis. Mechanistic investigations revealed that CXCL1exo-dead enhanced TAM/PD-L1 signaling by transcriptionally activating EED-mediated PD-L1 promoter activity. More importantly, TPCA-1 (2-[(aminocarbonyl) amino]-5-(4-fluorophenyl)-3-thiophenecarboxamide) was screened as a promising inhibitor targeting exosomal CXCL1 signals to enhance paclitaxel chemosensitivity and limit breast cancer metastasis without noticeable toxicities. ConclusionsOur results highlight CXCL1exo-dead as a novel dying cell-released signal and provide TPCA-1 as a targeting candidate to improve breast cancer prognosis.

cancer biology↗

bioRxiv2023

A Golden Standard for Transcription Factor-Gene Regulatory Interactions in Escherichia coli K-12: How reliable are they based on the methods supporting them?

Post-genomic implementations have expanded the experimental strategies to identify elements involved in the regulation of transcription initiation. As new methodologies emerge, a natural step is to compare their results with those from established methodologies, such as the classic methods of molecular biology used to characterize transcription factor binding sites, promoters, or transcription units. In the case of Escherichia coli K-12, the best-studied microorganism, for the last 30 years we have continuously gathered such knowledge from original scientific publications, and have organized it in two databases, RegulonDB and EcoCyc. Furthermore, since RegulonDB version 11.0 (1), we offer comprehensive datasets of binding sites from chromatin immunoprecipitation combined with sequencing (ChIP-seq), ChIP combined with exonuclease digestion and next-generation sequencing (ChIP-exo), genomic SELEX screening (gSELEX), and DNA affinity purification sequencing (DAP-seq) HT technologies, as well as additional datasets for transcription start sites, transcription units and RNA sequencing (RNA-seq) expression profiles. Here, we present for the first time an analysis of the sources of knowledge supporting the collection of transcriptional regulatory interactions (RIs) of E. coli K-12. An RI is formed by the transcription factor, its positive or negative effect on a promoter, a gene or transcription unit. We improved the evidence codes so that the specific methods are described, and we classified them into seven independent groups. This is the basis for our updated computation of confidence levels, weak, strong, or confirmed, for the collection of RIs. We compare the confidence levels of the RI collection before and after adding HT evidence illustrating how knowledge will change as more HT data and methods appear in the future. Users can generate subsets filtering out the method they want to benchmark and avoid circularity, or keep for instance only the confirmed interactions. The comparison of different HT methods with the available datasets indicate that ChIP-seq recovers the highest fraction (>70%) of binding sites present in RegulonDB followed by gSELEX, DAP-seq and ChIP-exo. There is no other genomic database that offers this comprehensive high-quality anatomy of evidence supporting a corpus of transcriptional regulatory interactions.

genomics↗

bioRxiv2023

An N-acetyltransferase required for EsxA N-terminal protein acetylation and virulence in Mycobacterium marinum.

N-terminal protein acetylation is a ubiquitous post-translational modification that broadly impacts diverse cellular processes in higher organisms. Bacterial proteins are also N-terminally acetylated, but the mechanisms and consequences of this modification in bacteria are poorly understood. We previously quantified widespread N-terminal protein acetylation in pathogenic mycobacteria (C. R. Thompson, M. M. Champion, and P.A. Champion, J Proteome Res 17(9): 3246-3258, 2018, https://doi:10.1021/acs.jproteome.8b00373). The major virulence factor EsxA (ESAT-6, Early secreted antigen, 6kDa) was one of the first N-terminally acetylated proteins identified in bacteria. EsxA is conserved in mycobacterial pathogens, including Mycobacterium tuberculosis and Mycobacterium marinum, a non-tubercular mycobacterial species that causes tuberculosis-like disease in ectotherms. However, enzyme responsible for EsxA N-terminal acetylation has been elusive. Here, we used genetics, molecular biology, and mass-spectroscopy based proteomics to demonstrate that MMAR_1839 (renamed Emp1, ESX-1 modifying protein, 1) is the putative N-acetyl transferase (NAT) solely responsible for EsxA acetylation in Mycobacterium marinum. We demonstrated that ERD_3144, the orthologous gene in M. tuberculosis Erdman, is functionally equivalent to Emp1. We identified at least 22 additional proteins that require Emp1 for acetylation, demonstrating that this putative NAT is not dedicated to EsxA. Finally, we showed that loss of emp1 resulted in a significant reduction in the ability of M. marinum to cause macrophage cytolysis. Collectively, this study identified a NAT required for N-terminal acetylation in Mycobacterium and provided insight into the requirement of N-terminal acetylation of EsxA and other proteins in mycobacterial virulence in the macrophage. Significance StatementN-terminal acetylation is a protein modification that broadly impacts basic cellular function, protein turnover and disease in higher organisms. In bacteria, very little is understood how N-terminal acetylation impacts bacterial physiology and pathogenesis. Mycobacterial pathogens cause acute and chronic diseases in humans and in animals. [~]15% of mycobacterial proteins are N-terminally acetylated, but the enzymes responsible for this protein modification are largely unknown. We identified a conserved mycobacterial protein, MMAR_1839, that is required for the N-terminal acetylation of 23 mycobacterial proteins including EsxA, a protein essential for mycobacteria to cause disease. Loss of this enzyme from Mycobacterium marinum reduced macrophage killing, which is required for bacterial spread in the host. Defining the acetyltransferases responsible for the N-terminal protein acetylation of essential virulence factors could lead to new targets for therapeutics against mycobacterial pathogens.

microbiology↗

bioRxiv2023

An alphacoronavirus polymerase structure reveals conserved co-factor functions

Coronaviruses are a diverse subfamily of viruses containing pathogens of humans and animals. This subfamily of viruses replicates their RNA genomes using a core polymerase complex composed of viral non-structural proteins: nsp7, nsp8 and nsp12. Most of our understanding of coronavirus molecular biology comes from the betacoronaviruses like SARS-CoV and SARS-CoV-2, the latter of which is the causative agent of COVID-19. In contrast, members of the alphacoronavirus genus are relatively understudied despite their importance in human and animal health. Here we have used cryoelectron microscopy to determine the structure of the alphacoronavirus porcine epidemic diarrhea virus (PEDV) core polymerase complex bound to RNA. Our structure shows an unexpected nsp8 stoichiometry in comparison to other published coronavirus polymerase structures. Biochemical analysis shows that the N-terminal extension of one nsp8 is not required for in vitro RNA synthesis for alpha and betacoronaviruses as previously hypothesized. Our work shows the importance of studying diverse coronaviruses to reveal aspects of coronavirus replication while also identifying areas of conservation to be targeted by antiviral drugs. Significance StatementCoronaviruses are important human and animal pathogens with a history of crossing over from animal reservoirs into humans leading to epidemics or pandemics. Betacoronaviruses, such as SARS-CoV and SARS-CoV-2, have been the focus of research efforts in the field of coronaviruses, leaving other genera (alpha, gamma, and delta) understudied. To broaden our understanding, we studied an alphacoronavirus polymerase complex. We solved the first structure of a non-betacoronavirus replication complex, and in doing so identified previously unknown, and conserved, aspects of polymerase cofactor interactions. Our work displays the importance of studying coronaviruses from all genera and provides important insight into coronavirus replication that can be used for antiviral drug development.

biochemistry↗

bioRxiv2023

Mathematical Modeling of PCR with Variable Concentrations of DNA and Taq Polymerase

Polymerase Chain Reaction (PCR) is one of the important techniques in molecular biology for many diagnostics and research applications. In this current theoretical PCR optimization research, out of its seven recipe reagents, two of the important constituents e.g., DNA which might be very rare in forensic cases and polymerase enzyme due to its high cost were mathematically modeled and computationally simulated using MATLAB programming platform. Chemical equations of PCR stages were established using the law of mass action followed by differential equations derivations from each of the DNA amplification phases. Firstly, a mathematical model of Taq polymerase enzyme with its variable concentrations ranging from 0.05-0.35 IU/L was formulated which showed the best PCR product of 0.61 ng/L obtained with 0.2 IU/L of polymerase. Similarly, by fixing the optimal polymerase concentration obtained in the previous simulation, the prime-DNA variable concentrations ranging from 0.5-3.5 ng/L were further simulated which showed the best PCR product of 0.94 ng/L at 2.0 ng/L of DNA. PCR wet-lab experimentation and gel-electrophoresis visualization validated mathematically simulated optimized concentrations of the aforementioned two reagents which vary the PCR product considerably. Current findings indicate that mathematically optimized concentrations of Taq-polymerase and template-DNA may reduce the PCR cost, time and energy, but other factors of target-sequence specificity, purity/concentrations of the other reagents, working hygiene, technical intricacies, biosafety and biosecurity factors may also contribute the desired yield of the amplicon.

bioengineering↗

bioRxiv2023

Bacterial genome engineering using CRISPR RNA-guided transposases

CRISPR-associated transposons (CASTs) have the potential to transform the technology landscape for kilobase-scale genome engineering, by virtue of their ability to integrate large genetic payloads with high accuracy, easy programmability, and no requirement for homologous recombination machinery. These transposons encode efficient, CRISPR RNA-guided transposases that execute genomic insertions in E. coli at efficiencies approaching [~]100%, generate multiplexed edits when programmed with multiple guides, and function robustly in diverse Gram-negative bacterial species. Here we present a detailed protocol for engineering bacterial genomes using CAST systems, including guidelines on the available homologs and vectors, customization of guide RNAs and DNA payloads, selection of common delivery methods, and genotypic analysis of integration events. We further describe a computational crRNA design algorithm to avoid potential off-targets and CRISPR array cloning pipeline for DNA insertion multiplexing. Starting from available plasmid constructs, the isolation of clonal strains containing a novel genomic integration event-of-interest can be achieved in 1 week using standard molecular biology techniques.

bioengineering↗

bioRxiv2023

AG3D: A low-cost educational 3D printable toolkit for agarose gel electrophoresis

Access to desktop additive manufacturing is growing and the argument could be made for 3D printers to be standard laboratory equipment. The power of the printers lies in the democratisation of scientific equipment. Traditional agarose gel electrophoresis forms a cornerstone of molecular biology research, teaching and learning. Reliable electrophoresis is dependent on a number of factors which include standardized commercial equipment with respect to casting trays, combs, horizontal tanks and power supplies. The aforementioned systems come at a high initial cost; this is before factoring in the costs of standard electrophoresis grade agarose and associated reagent pricing. Here, we present a basic method for the additive manufacturing of a simple 3D printable agarose gel electrophoresis (AGE) unit with a built-in gel casting tray for standard size microscope slide-based AGE; named AG3D. The system presented was validated using different standard agarose-buffers (Tris Acetate EDTA and Tris Borate EDTA) and commercially available base-pair ladders. We provide a comparison between the AG3D and a commercial AGE system in respect to resolving power of the electrophoresis unit and discuss the overall reduction in cost afforded by the AG3D electrophoresis toolkit. The method presented has the potential for application in low resource educational environments by: O_LISignificantly lowering costs through the reduction of reagents (agarose, buffers etc). C_LIO_LIAllow for the use of low sample volumes. C_LIO_LIProviding an open-source toolkit for modification whether for research or teaching & learning C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=64 SRC="FIGDIR/small/533785v1_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@135b120org.highwire.dtl.DTLVardef@1ffca3eorg.highwire.dtl.DTLVardef@36ce4corg.highwire.dtl.DTLVardef@21dfb0_HPS_FORMAT_FIGEXP M_FIG C_FIG Specifications table O_TBL View this table: org.highwire.dtl.DTLVardef@1e4a30forg.highwire.dtl.DTLVardef@18d57c9org.highwire.dtl.DTLVardef@7e8b77org.highwire.dtl.DTLVardef@1f64979org.highwire.dtl.DTLVardef@51e36f_HPS_FORMAT_FIGEXP M_TBL C_TBL

scientific communication and education↗

bioRxiv2023

Likelihood-ratio test statistic for the finite-sample case in nonlinear ordinary differential equation models

Likelihood ratios are frequently utilized as basis for statistical tests, for model selection criteria and for assessing parameter and prediction uncertainties, e.g. using the profile likelihood. However, translating these likelihood ratios into p-values or confidence intervals requires the exact form of the test statistics distribution. The lack of knowledge about this distribution for nonlinear ordinary differential equation (ODE) models requires an approximation which assumes the so-called asymptotic setting, i.e. a sufficiently large amount of data. Since the amount of data from quantitative molecular biology is typically limited in applications, this finite-sample case regularly occurs for mechanistic models of dynamical systems, e.g. biochemical reaction networks or infectious disease models. Thus, it is unclear whether the standard approach of using statistical thresholds derived for the asymptotic large-sample setting in realistic applications results in valid conclusions. In this study, empirical likelihood ratios for parameters from 19 published nonlinear ODE benchmark models are investigated using a resampling approach for the original data designs. Their distributions are compared to the asymptotic approximation and statistical thresholds are checked for conservativeness. It turns out, that corrections of the likelihood ratios in such finite-sample applications are required in order to avoid anti-conservative results. Author summaryStatistical methods based on the likelihood ratio are ubiquitous in mathematical modelling in systems biology. For example confidence intervals of estimated parameters rely on the statistical properties of the likelihood-ratio test. However, it is often overlooked that these intervals sizes rely on assumptions on the amounts of data, which are regularly violated in typical applications in systems biology. By checking the appropriateness of these assumptions in models from the literature, this study shows that in a surprisingly large fraction confidence intervals might be too small. Using a geometric interpretation of parameter estimation in the so-called data space, it is motivated why these issues appear and how they depend on the identifiability of the model parameters. In order to avoid such problematic situations, this work makes suggestions on how to adapt the statistical threshold values for likelihood-ratio test. By this, it can be assured that valid statistical conclusions are drawn from the analysis, also in situations where only smaller data sets are available. Such corrections yield for example more conservative confidence interval sizes and thus decrease a potential underestimation of the parameter uncertainty.

systems biology↗

bioRxiv2023

A sweet new set of inducible and constitutive promoters for haloarchaea

Inducible promoters are one of cellular and molecular biologys most important technical tools. The ability to deplete, replete, and overexpress genes on demand is the foundation of most functional studies. Here, we developed and characterized a new xylose-responsive promoter (Pxyl), the second inducible promoter system for the model haloarcheon Haloferax volcanii. Generating RNA-seq datasets from cultures in the presence of four historically used inducers (arabinose, xylose, maltose, and IPTG), we mapped upregulated genomic regions primarily repressed in the absence of the above inducers. We found a highly upregulated promoter that controls the expression of the xacEA (HVO_B0027-28) operon in the pHV3 chromosome. To characterize this promoter region, we cloned msfGFP (monomeric superfold green fluorescent protein) under the control of two different 5 UTR fragments into a modified pTA962 vector: the first 250 bp (P250) and the whole 750 bp intergenic region (P750). The P250 region expressed msfGFP constitutively, and its expression did not respond to the presence or absence of xylose. However, the P750 promoter showed not only to be repressed in the absence of xylose but also expressed higher levels of msfGFP than the previously described inducible promoter PtnaA in the presence of the inducer. Finally, we validated the inducible Pxyl promoter by reproducing morphological phenotypes already described in the literature. By overexpressing the tubulin-like FtsZ1 and FtsZ2, we observed similar but slightly more pronounced morphological defects than the tryptophan-inducible promoter PtnaA. FtsZ1 overexpression created larger, deformed cells, whereas cells overexpressing FtsZ2 were smaller but mostly retained their shape. In summary, this work contributes a new xylose-inducible promoter, Pxyl, that can be used simultaneously with the well-established PtnaA in functional studies in H. volcanii.

microbiology↗

bioRxiv2023

Identifying widespread and recurrent variants of genetic parts to improve annotation of engineered DNA sequences

Engineered plasmids have been workhorses of recombinant DNA technology for nearly half a century. Plasmids are used to clone DNA sequences encoding new genetic parts and to reprogram cells by combining these parts in new ways. Historically, many genetic parts on plasmids were copied and reused without routinely checking their DNA sequences. With the widespread use of high-throughput DNA sequencing technologies, we now know that plasmids often contain variants of common genetic parts that differ slightly from their canonical sequences. Because the exact provenance of a genetic part on a particular plasmid is usually unknown, it is difficult to determine whether these differences arose due to mutations during plasmid construction and propagation or due to intentional editing by researchers. In either case, it is important to understand how the sequence changes alter the properties of the genetic part. We analyzed the sequences of over 50,000 engineered plasmids using depositor metadata and a metric inspired by the natural language processing field. We detected 217 uncatalogued genetic part variants that were especially widespread or were likely the result of convergent evolution or engineering. Several of these uncatalogued variants are known mutants of plasmid origins of replication or antibiotic resistance genes that are missing from current annotation databases. However, most are uncharacterized, and 3/5 of the plasmids we analyzed contained at least one of the uncatalogued variants. Our results include a list of genetic parts to prioritize for refining engineered plasmid annotation pipelines, highlight widespread variants of parts that warrant further investigation to see whether they have altered characteristics, and suggest cases where unintentional evolution of plasmid parts may be affecting the reliability and reproducibility of science. Author SummaryPlasmids are used in molecular biology and biotechnology for a wide variety of tasks such as cloning DNA, expressing recombinant proteins, and creating vaccines. One challenge in working with plasmids is that there has been a long, and often lost history of pieces of plasmids being copied and remixed by researchers to create new plasmids. Current databases used for annotating key genetic parts in plasmids are incomplete, especially with respect to cataloguing closely related versions of parts that can have very different characteristics. Some genetic part variants have arisen due to purposeful editing while others are the result of unplanned mutations and evolution. When a researcher finds differences between a database sequence and a genetic part in their newly constructed plasmid, it is often unclear how and when it arose and whether it will affect their experiments. We identified 217 genetic part variants that are either widespread or have likely arisen independently more than once on plasmids due to convergent evolution or engineering. We propose that these variants should be prioritized for inclusion in curated databases of engineered DNA sequences and for functional characterization to improve the reliability and reproducibility of science.

synthetic biology↗

bioRxiv2023

Touching the (almost) untouchable: a minimally-invasive workflow for microbiological and biomolecular analyses of cultural heritage objects

Microbiological and biomolecular approaches to cultural heritage research have expanded the established research horizon -from the prevalent focus on the cultural objects conservation and human health protection to the relatively recent applications to provenance inquiry and assessment of environmental impacts on heritage objects in a global context of a changing climate. Standard microbiology and molecular biology methods were developed for other materials, specimens, disciplines and contexts. Although they could in principle be applied to cultural heritage research, certain characteristics common to several heritage objects - such as uniqueness, fragility, high value and restricted access, demand tailored approaches. In addition, samples from heritage objects often yield low microbial biomass, rendering them highly susceptible to cross-contamination. Therefore, dedicated methodology that addresses these material limitations and operational hurdles along all procedural steps are needed. Here were propose a step-by-step standardized laboratory and bioinformatic workflow to analyse the microbiome of cultural heritage objects. The methodology was developed targeting the challenging side of the spectrum of cultural heritage objects, such as the delicate written record, while retaining modularity and flexibility to adapt and/or upscale the proposed workflow to heritage artefacts of a more robust nature or larger dimensions. We hope this review and workflow will facilitate the interdisciplinary inquiry and interactions among the cultural heritage research community.

microbiology↗

bioRxiv2023

Efficient Fisher Information Computation and Policy Search in Sampled Stochastic Chemical Reaction Networks through Deep Learning

Markov jump processes constitute the central class of Chemical Reaction Network models used to account for the intrinsic stochasticity observed in the dynamics of molecular species abundance throughout Molecular Biology. These models are specified in a parametric form, and their identification requires the use of inference procedures, and in particular the estimation of the Fisher Information. Here, a fast and accurate computation method is introduced in the case of partial observations at discrete time points, based on the use of a Mixture Density Network. We also demonstrate how this Neural Network can be used to perform fast policy search. The efficiency of these approaches is illustrated on a set of examples, and is compared to that of the current state-of-the-art.

systems biology↗

bioRxiv2023

GluK2 is a target for gene therapy in drug-resistant Temporal Lobe Epilepsy

ObjectiveTemporal lobe epilepsy (TLE) is characterized by recurrent seizures generated in the limbic system, particularly in the hippocampus. In TLE, recurrent mossy fiber sprouting from dentate gyrus granule cells (DGCs) creates an aberrant epileptogenic network between DGCs which operates via ectopically expressed GluK2/GluK5-containing kainate receptors (KARs). TLE patients are often resistant to anti-seizure medications and suffer significant comorbidities; hence there is an urgent need for novel therapies. Previously we have shown that GluK2 knockout mice are protected from seizures. This study aims at providing evidence that downregulating KARs in the hippocampus using gene therapy reduces chronic epileptic discharges in TLE. MethodsWe combined molecular biology and electrophysiology in rodent models of TLE and in hippocampal slices surgically resected from patients with drug-resistant TLE. ResultsHere we confirmed the translational potential of KAR suppression using a non-selective KAR antagonist that markedly attenuated Interictal-like Epileptiform Discharges (IEDs) in TLE patient-derived hippocampal slices. An adeno-associated virus (AAV) serotype-9 vector expressing anti-grik2 miRNA was designed to specifically downregulate GluK2 expression. Direct delivery of AAV9-anti grik2 miRNA into the hippocampus of TLE mice led to a marked reduction in seizure activity. Transduction of TLE patient hippocampal slices reduced levels of GluK2 protein and, most importantly, significantly reduced IEDs. InterpretationOur gene silencing strategy to knock down aberrant GluK2 expression demonstrates inhibition of chronic seizure in a mouse TLE model and IEDs in cultured slices derived from TLE patients. These results provide proof-of-concept for a gene therapy approach targeting GluK2 KARs for drug-resistant TLE patients.

neuroscience↗

bioRxiv2023

Pathfinder: protein folding pathway prediction based on conformational sampling

The study of protein folding mechanism is a challenge in molecular biology, which is of great significance for revealing the movement rules of biological macromolecules, understanding the pathogenic mechanism of folding diseases, and designing protein engineering materials. Based on the hypothesis that the conformational sampling trajectory contain the information of folding pathway, we propose a protein folding pathway prediction algorithm named Pathfinder. Firstly, Pathfinder performs large-scale sampling of the conformational space and clusters the decoys obtained in the sampling. The heterogeneous conformations obtained by clustering are named seed states. Then, a resampling algorithm that is not constrained by the local energy basin is designed to obtain the transition probabilities of seed states. Finally, protein folding pathways are inferred from the maximum transition probabilities of seed states. The proposed Pathfinder is tested on our developed test set (34 proteins). For 5 widely studied proteins, we correctly predicted their folding pathways. For 25 partial biological experiments proteins, we predicted folding pathways could be further verified. For the other 4 proteins without biological experiment results, potential folding pathways were predicted to provide new insights into protein folding mechanism. The results reveal that structural analogs may have different folding pathways to express different biological functions, homologous proteins may contain common folding pathways, and -helices may be more prone to early protein folding than {beta}-strands.

bioinformatics↗