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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2024

Simple recombinant monoclonal antibody production from E. coli.

AO_SCPLOWBSTRACTC_SCPLOWAntibodies are valuable biological reagents used in a wide range of discovery research, biotechnology, diagnostic and therapeutic applications. Currently both commercial and lab scale antibody production is reliant on expression from mammalian cells, which can be time consuming and requires use of specialist facilities and costly growth reagents. Here we describe a simple, rapid and cheap method for producing and isolating functional monoclonal antibodies and antibody fragments from bacterial cells that can be used in a range of laboratory applications. This simple method only requires access to basic microbial cell culture and molecular biology equipment, making scalable in-house antibody production accessible to the global diagnostics, therapeutics and molecular bioscience research communities.

molecular biology↗

bioRxiv2014

Sequence and primer independent stochastic heterogeneity in PCR amplification efficiency revealed by single molecule barcoding

The polymerase chain reaction (PCR) is one of the most widely used techniques in molecular biology. In combination with High Throughput Sequencing (HTS), PCR is widely used to quantify transcript abundance for RNA-seq and especially in the context of analysis of T cell and B cell receptor repertoires. In this study, we combine molecular DNA barcoding with HTS to quantify PCR output from individual target molecules. Our results demonstrate that the PCR process exhibits very significant unexpected heterogeneity, which is independent of the sequence of the primers or target, and independent of bulk experimental conditions. The mechanistic origin of this heterogeneity is not clear, but simulations suggest that it must derive from inherited differences between different DNA molecules within the reaction. The results illustrate that single molecule barcoding is important in order to derive reproducible quantitative results from any protocol which combines PCR with HTS.

Molecular Biology↗

bioRxiv2022

The SARS-CoV-2 Spike Protein Mutation Explorer: Using an Interactive Application to Improve the Public Understanding of SARS-CoV-2 Variants of Concern

SARS-CoV-2 is the virus responsible for the COVID-19 pandemic, which began in late 2019 and has resulted in millions of death globally. The need to understand the pandemic means that detailed descriptions of features of this virus are now of interest to non-expert audiences. In particular, there has been much public interest in the spike protein that protrudes from the surface of the SARS-CoV-2 virus particle. The spike is the major determinant of viral infectivity and the main target for protective immune responses, and included in vaccines, and so its properties influence the impact of the pandemic on peoples lives. This protein is rapidly evolving, with mutations that enhance transmissibility or weaken vaccine protection creating new variants of concern (VOCs) and associated sub-lineages. The spread of SARS-CoV-2 VOCs has been tracked by groups such as the COVID-19 Genomics UK consortium (COG-UK). Their online mutation explorer (COG-UK/ME), which analyses and shares SARS-CoV-2 sequence data, contains information about VOCs that is designed primarily for an expert audience but is potentially of general interest during a pandemic. We wished to make this detailed information about SARS-CoV-2 VOCs more widely accessible. Previously work has shown that visualisations and interactivity can facilitate active learning and boost engagement with molecular biology topics, while animations of these topics can boost understanding on protein structure, function, and dynamics. We therefore set out to develop an educational graphical resource, the SARS-CoV-2 Spike Protein Mutation Explorer (SSPME), which contains interactive 3D molecular models and animations explaining SARS-CoV-2 spike protein variants and VOCs. We performed user-testing of the original COG-UK/ME website and of the SSPME, using a within-groups design to measure knowledge acquisition and a between-groups design to contrast the effectiveness and usability. Statistical analysis demonstrated that, when compared to the COG-UK/ME, the SSPME had higher usability and significantly improved participant knowledge confidence and knowledge acquisition. The SSPME therefore provides an example of how 3D interactive visualisations can be used for effective science communication and education on complex biomedical topics, as well as being a resource to improve the public understanding of SARS-CoV-2 VOCs.

molecular biology↗

bioRxiv2025

Strand Displacement Chain Reaction (SDCR): New Hybrid Amplification Technique for Fast and Sensitive Detection of Genetic Materials

Nucleic acid amplification methods are widely used in science, medicine and forensics for molecular biological assays and for the detection of genetic material. The newly developed strand displacement chain reaction (SDCR) method is a hybrid amplification technique based on polymerase chain reaction (PCR) and isothermal nucleic acid amplification. Here, we compared conventional PCR, the "gold standard" for molecular diagnostic assays, with the SDCR method by performing real-time amplification assays using human, bacterial and viral genetic materials. In the assays, SDCR demonstrated very high sensitivity and amplification efficiency. We found that the SDCR method provided an amplification factor above three, which noticeably outperformed that of PCR amplification and enabled a marked reduction in the number of cycles in comparison with PCR. Therefore, the new hybrid amplification technique could be extremely useful for the detection of genetic material and the development of new diagnostic kits.

molecular biology↗

bioRxiv2020

The Giardia lamblia ribosome structure reveals divergence in translation and quality control pathways

Giardia lamblia is a human pathogen of worldwide importance with limited treatment options. Its unusual molecular biology presents targets for new therapies and the opportunity to explore the fundamental features of important biological mechanisms. We determined the structure of the G. lamblia 80S ribosome by cryoelectron microscopy, revealing how it combines eukaryotic and bacterial features. The structure reveals regions that are rapidly evolving, including depletion of A and U bases from its rRNA. Specific features of the G. lamblia ribosome suggest it is less prone to stall on problematic peptide sequences, and that the organism uses altered ribosome quality control pathways compared to other eukaryotes. Examination of translation initiation factor binding sites suggests these interactions are conserved despite a divergent initiation mechanism. This work defines key new questions regarding ribosome-centric biological pathways in G. lamblia and motivates new experiments to explore potential targetable mechanisms.

molecular biology↗

bioRxiv2017

Detection of functional protein domains by unbiased genome-wide forward genetic screening

Genetic and chemo-genetic interactions have played key roles in elucidating the molecular mechanisms by which certain chemicals perturb cellular functions. Many studies have employed gene knockout collections or gene disruption/depletion strategies to identify routes for evolving resistance to chemical agents. By contrast, searching for point-mutational genetic suppressors that can identify separation- or gain-of-function mutations, has been limited even in simpler, genetically amenable organisms such as yeast, and has not until recently been possible in mammalian cell culture systems. Here, by demonstrating its utility in identifying suppressors of cellular sensitivity to the drugs camptothecin or olaparib, we describe an approach allowing systematic, large-scale detection of spontaneous or chemically-induced suppressor mutations in yeast and in haploid mouse embryonic stem cells in a short timeframe, and with potential applications in essentially any other haploid system. In addition to its utility for molecular biology research, this protocol can be used to identify drug targets and to predict mechanisms leading to drug resistance. Mapping suppressor mutations on the primary sequence or three-dimensional structures of protein suppressor hits provides insights into functionally relevant protein domains, advancing our molecular understanding of protein functions, and potentially helping to improve drug design and applicability.

molecular biology↗

bioRxiv2025

Wuhan sharpbelly bornavirus (genus Cultervirus) can infect a wide range of host cells and establishes persistent infection in diverse cypriniform cells

Our recent study using in silico data mining identified novel culterviruses (family: Bornaviridae) in fish, including a variant of W[u]han sharpbelly bornavirus (WhSBV) in grass carp kidney and liver cell lines. Here, metagenomic sequencing of different fish cell lines revealed WhSBV in two cell lines from grass carp (Ctenopharyngodon idella; order: Cypriniformes). Using these cell lines, we investigated the ability of WhSBV to infect and establish persistent infection in other cell lines from bony fish (Cypriniformes, Chichliformes, Salmoniformes, Centrarchiformes and Spariformes), reptiles (Testudines and Squamata), birds (Galliformes) and mammals (Primates and Rodentia). WhSBV showed efficient replication and a time-dependent increase in viral RNA levels in cypriniform cells, whereas replication was limited, confined to single cells, and lacked a clear time-dependent increase in cells from other bony fish and reptiles. No replication was detected in avian and mammalian cells. In situ hybridisation and electron microscopy confirmed the presence of viral RNA and particles in infected cypriniform cells. Transcriptomic sequencing revealed minimal innate immune activation during early stages of infection and antiviral response only at later stages, suggesting that WhSBV establishes persistence by evading early immune recognition. In addition, we identified polycistronic viral mRNAs regulated by specific transcriptional start and termination sites and RNA splicing. Viral proteins were detected, confirming previous in silico predictions. These findings provide insights into the potential infectivity, persistence mechanisms and transcriptional strategies of WhSBV. This study validates previous findings from in silico data mining, further reinforcing its effectiveness as a powerful tool for discovering hidden viruses. IMPORTANCEUnderstanding the diversity and host range of viruses is crucial for assessing their ecological role, associated diseases and zoonotic potential. However, many newly discovered viruses are characterised using sequence data alone because isolates are often difficult to obtain. Using cell culture models, this study characterises W[u]han sharpbelly bornavirus (WhSBV), a member of the genus Cultervirus. Here we demonstrate its ability to establish persistent infection in cypriniform fish cell lines, while exhibiting restricted replication in certain non-cypriniform fish. The identification of polycistronic transcription, splicing events and immune evasion mechanisms advances our understanding of the molecular biology of WhSBV and culterviruses in general. By validating in silico predictions, this study highlights the power of computational approaches in uncovering viral diversity. As cypriniform fish include economically important species such as carp, understanding the dynamics of WhSBV host range and infection biology may be crucial for future aquaculture health management.

molecular biology↗

bioRxiv2018

Molecular tools for phytoplankton monitoring samples

HABs can have severe impacts in fisheries or human health by the consumption of contaminated bivalves. Monitoring assessment (quantitative and qualitative identification) of these organisms, is routinely accomplished by microscopic identification and counting of these organisms. Nonetheless, molecular biology techniques are gaining relevance, once these approaches can easily identify phytoplankton organisms at species level and even cell number quantifications. This work tests 12 methods/kits for genomic DNA extraction and seven DNA polymerases to determine which is the best method for routinely use in a common molecular laboratory, for phytoplankton monitoring samples analyses. From our work, Direct PCR master mix for tissue samples, proved to be the most adequate by its velocity of processivity, practicability, reproducibility, sensitiveness and robustness. However, brands such as Omega Biotek, GRISP, Qiagen and MP Biomedicals also showed good results for conventional DNA extraction as well as all the Taq brands tested (GRISP, GE Healthcare Life Sciences, ThermoFisher Scientific and Promega). Lugols solution, with our tested kits did not show negative interference in DNA amplification. The same can be said about mechanical digestion, with no significant differences among kits with or without this homogenization step.

molecular biology↗

bioRxiv2020

Integration of Machine Learning Improves the Prediction Accuracy of Molecular Modelling for M. jannaschii Tyrosyl-tRNA Synthetase Substrate Specificity

Design of enzyme binding pocket to accommodate substrates with different chemical structure is a great challenge. Traditionally, thousands even millions of mutants have to be screened in wet-lab experiment to find a ligand-specific mutant and large amount of time and resources is consumed. To accelerate the screening process, here we propose a novel workflow through integration of molecular modeling and data-driven machine learning method to generate mutant libraries with high enrichment ratio for recognition of specific substrate. M. jannaschii tyrosyl-tRNA synthetase (Mj. TyrRS) is used as an example system to give a proof of concept since the sequence and structure of many unnatural amino acid specific Mj. TyrRS mutants have been reported. Based on the crystal structures of different Mj. TyrRS mutants and Rosetta modeling result, we find D158G/P is the critical residue which influences the backbone disruption of helix with residue 158-163. Our results show that compared with random mutation, Rosetta modeling and score function calculation can elevate the enrichment ratio of desired mutants by 2-fold in a test library having 687 mutants, while after calibration by machine learning model trained using known data of Mj. TyrRS mutants and ligand, the enrichment ratio can be elevated by 11-fold. This molecular modeling and machine learning-integrated workflow is anticipated to significantly benefit to the Mj. tyrRS mutant screening and substantially reduce the time and cost of web-lab experiment. Besides, this novel process will have broad application in the field of computational protein design. CCS Concepts* Applied computing * Life and medical sciences * Computational biology * Molecular structural biology

bioinformatics↗

bioRxiv2018

Microbial contamination screening and interpretation for biological laboratory environments

Advances in microbiome researches have led us to the realization that the composition of microbial communities of indoor environment is profoundly affected by the function of buildings, and in turn may bring detrimental effects to the indoor environment and the occupants. Thus investigation is warranted for a deeper understanding of the potential impact of the indoor microbial communities. Among these environments, the biological laboratories stand out because they are relatively clean and yet are highly susceptible to microbial contaminants. In this study, we assessed the microbial compositions of samples from the surfaces of various sites across different types of biological laboratories. We have qualitatively and quantitatively assessed these possible microbial contaminants, and found distinct differences in their microbial community composition. We also found that the type of laboratories has a larger influence than the sampling site in shaping the microbial community, in terms of both structure and richness. On the other hand, the public areas of the different types of laboratories share very similar sets of microbes. Tracing the main sources of these microbes, we identified both environmental and human factors that are important factors in shaping the diversity and dynamics of these possible microbial contaminations in biological laboratories. These possible microbial contaminants that we have identified will be helpful for people who aim to eliminate them from samples.\n\nImportanceMicrobial communities from biological laboratories might hamper the conduction of molecular biology experiments, yet these possible contaminations are not yet carefully investigated. In this work, a metagenomic approach has been applied to identify the possible microbial contaminants and their sources, from the surfaces of various sites across different types of biological laboratories. We have found distinct differences in their microbial community compositions. We have also identified the main sources of these microbes, as well as important factors in shaping the diversity and dynamics of these possible microbial contaminations. The identification and interpretation of these possible microbial contaminants in biological laboratories would be helpful for alleviate their potential detrimental effects.

microbiology↗

bioRxiv2026

Hierarchical Value of Information in Microbial Predator-Prey Interactions

Information is fundamental to biological survival, but the amount of information and its biological value are not equivalent. Shannon information quantifies uncertainty reduction, whereas Volkenstein's value of information measures how information changes the probability of a biologically relevant outcome. Although originally developed for molecular biology contexts, the latter concept has rarely been applied to environmental sensing and ecological interactions. Here we develop a value-of-information framework for microbial predator-prey interactions based on hydrodynamic sensing, in which prey detect fluid disturbances generated by approaching predators. Using a mechanistic model that incorporates sensory thresholds, memory, false alarms, biological benefits and costs, and predator encounter probability, we characterize mutual information from three hierarchical measures of biological value: encounter-conditional value, ecological value, and lifetime fitness value. The framework reveals how small amounts of sensory information can produce disproportionately large survival benefits during predator encounters, generating encounter-level value amplification in which biological value exceeds Shannon information. However, although global sensitivity analysis shows that such amplification is common, it is not universal and becomes progressively diluted at broader ecological and lifetime scales by encounter rarity, background noise, and sensory costs. Across most parameter combinations, the encounter-conditional value exceeded the ecological value, which in turn exceeded the lifetime fitness value. These results demonstrate that environmental sensing should be evaluated not only by how accurately it represents the external world, but by how strongly it changes biologically relevant outcomes. More broadly, the framework extends Volkenstein's concept of information value to ecological interactions and provides a quantitative framework for predicting when environmental information enhances survival and fitness, thereby providing a platform for explaining the evolution, maintenance, diversification, and loss of sensory systems.

ecology↗

bioRxiv2025

3' to 5' Translation of Circular RNAs?

For decades, the 5[->]3 direction of translation has been a central dogma of molecular biology(1). Here we present evidence that eukaryotic circular RNAs (circRNAs) can serve as templates for 3[->]5 backward translation (BT), yielding polypeptides with distinct sequence and structural features not found in canonical proteomes. Mining of more than 6,000 multi-omics datasets identified [~]1 million candidate BT proteins across eukaryotes, including 59,000 high-confidence human BT proteins supported by mass spectrometry. Genetic combinatorial experiments (KO and KI) and cell-free translation of synthetic circRNAs establish BT as a conserved mechanism. Loss-of-function studies of hs.circCAPN15 in human and dm.circROLS in Drosophila underscore the functional importance of BT-derived proteins. Our work challenges the long-standing unidirectional translation paradigm, expands the functional landscape of the genetic code, and reveals a hitherto hidden layer of proteomic complexity with broad implications for biology and therapeutics.

molecular biology↗

bioRxiv2020

A simple RNA preparation method for SARS-CoV-2 detection by RT-qPCR

The technique RT-qPCR for viral RNA detection is the current worldwide strategy used for early detection of the novel coronavirus SARS-CoV-2. RNA extraction is a key pre-analytical step in RT-qPCR, often achieved using commercial kits. However, the magnitude of the COVID-19 pandemic is causing disruptions to the global supply chains used by many diagnostic laboratories to procure the commercial kits required for RNA extraction. Shortage in these essential reagents is even more acute in developing countries with no means to produce kits locally. We sought to find an alternative procedure to replace commercial kits using common reagents found in molecular biology laboratories. Here we report a method for RNA extraction that takes about 40 min to complete ten samples, and is not more laborious than current commercial RNA extraction kits. We demonstrate that this method can be used to process nasopharyngeal swab samples and yields RT-qPCR results comparable to those obtained with commercial kits. Most importantly, this procedure can be easily implemented in any molecular diagnostic laboratory. Frequent testing is crucial for individual patient management as well as for public health decision making in this pandemic. Implementation of this method could maintain crucial testing going despite commercial kit shortages.

molecular biology↗

bioRxiv2022

RNA cytometry of single-cells using semi-permeable microcapsules

Analytical tools for gene expression profiling of individual cells are critical for studying complex biological systems. However, the techniques enabling rapid measurements of gene expression on thousands of single-cells are lacking. Here, we report a high-throughput RNA cytometry for digital profiling of single-cells isolated in liquid droplets enveloped by a thin semi-permeable membrane (microcapsules). Due to selective permeability of the membrane, the desirable enzymes and reagents can be loaded, or replaced, in the microcapsule at any given step by simply changing the reaction buffer in which the microcapsules are dispersed. Therefore, complex molecular biology workflows can be readily adapted to conduct nucleic acid analysis on encapsulated mammalian cells, bacteria, or other biological species. The microcapsules support sequential multi-step enzymatic reactions, and remain intact under different biochemical conditions, freezing, thawing and thermocycling. Combining microcapsules with conventional FACS provides a high-throughput approach for conducting RNA cytometry of individual cells based on their digital gene expression signature.

molecular biology↗

bioRxiv2023

Effective High-Accuracy Prediction of Protein Structures from Easily Obtainable Artificial Homologous Sequences by Structure-Stability-Based Selection

High-resolution protein structure determination by experimental techniques is notoriously costly and labor intensive. This problem is mostly solved with arrival of deep-learning-based computational prediction by AlphaFold2 but only for those proteins with enough naturally occurring homologous sequences. Here, we attempt to close the remaining gap by employing artificially generated, structure-stability-selected homologous sequences as an input for AlphaFold2. We showed that only one round of selection of deeply mutated sequences of a few mutations is sufficient to bring the accuracy of predicted structures to better than 2 [A] RMSD from their respective native structures for four of the five proteins experimented. The performance for three out of five proteins is even better than AlphaFold2 with naturally occurring sequences. The only protein with predicted structure of >2 [A] (at 2.92 [A]) RMSD is due to a fully exposed (i.e., likely flexible) {beta}-hairpin. The result supports a future of determining protein structures at low cost and fast turnaround by integrating simple molecular biology experiments (deep mutational scanning and in vivo or in vitro selection) with high-throughput sequencing. The technique proposed here can be further extended to predict structures of protein complexes as well as proteins with posttranslational modifications.

molecular biology↗

bioRxiv2018

Evolutionarily informed deep learning methods: Predicting transcript abundance from DNA sequence

Deep learning methodologies have revolutionized prediction in many fields, and show potential to do the same in molecular biology and genetics. However, applying these methods in their current forms ignores evolutionary dependencies within biological systems and can result in false positives and spurious conclusions. We developed two novel approaches that account for evolutionary relatedness in machine learning models: 1) gene-family guided splitting, and 2) ortholog contrasts. The first approach accounts for evolution by constraining the models training and testing sets to include different gene families. The second, uses evolutionarily informed comparisons between orthologous genes to both control for and leverage evolutionary divergence during the training process. The two approaches were explored and validated within the context of mRNA expression level prediction, and have prediction auROC values ranging from 0.72 to 0.94. Model weight inspections showed biologically interpretable patterns, resulting in the novel hypothesis that the 3 UTR is more important for fine tuning mRNA abundance levels while the 5 UTR is more important for large scale changes.

molecular biology↗

bioRxiv2023

inDrops-2: a flexible, versatile and cost-efficient droplet microfluidics approach for high-throughput scRNA-seq of fresh and preserved clinical samples

The development of a large variety of single-cell analytical techniques has empowered researchers to explore diverse biological questions at the level of individual cells. Among these, droplet-based single-cell RNA sequencing (scRNA-seq) methods have been particularly prevalent owing to their high-throughput capabilities and reduced reaction volumes. While commercial systems have contributed to the widespread adoption of droplet-based scRNA-seq, the relatively high cost impose limitations for profiling large numbers of samples. Moreover, as the scope and scale of single cell sequencing methods keeps expanding, the possibility to accommodate diverse molecular biology workflows and inexpensively profile multiple biospecimens simultaneously becomes highly relevant. Herein, we present inDrops-2: an open-source scRNA-seq platform designed to profile fresh or preserved clinical samples with a sensitivity matching that of state-of-the-art commercial systems, yet at a few folds lower cost. Using inDrops-2, we conducted a comparative analysis of two prominent scRNA-seq protocols - those based on exponential and linear amplification of cDNA - and provide useful insights about the pros and cons inherited to each approach. We showcase the utility of inDrops-2 by simultaneously profiling 18 human lung carcinoma samples, all in one run, following cell preservation, long-term storage and multiplexing, to obtain a multiregional cellular profile of tumor microenvironment. The scalability, experimental flexibility and cost-efficiency offered by inDrops-2 should make it appealing for various single-cell transcriptomic studies.

molecular biology↗

bioRxiv2022

How the West(ern) Was Won: Solutions for Immunoblotting Large and Small Proteins

Relative protein quantification is a well-established technique in the vast majority of the molecular biology laboratories. However, western blot standard protocols may be unable to detect certain proteins depending on their size. When the protein of interest is out of 10-250 KDa range, its migration through the gel or transfer to the membrane are compromised, thus making its detection difficult. Here we present a set of modifications of the standard working procedure for western blotting based on the experience working with Small VCP Interacting Protein (SVIP) and Max-Gene Associated Protein (MGA), whose molecular weight are 8 and 350 kDa, respectively. We expect that these adaptations may help researchers to improve their experiments in a cost-effective manner.

molecular biology↗