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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2023

A general prediction model for substrates of transport proteins

Transport proteins play a crucial role in cellular metabolism and are central to many aspects of molecular biology and medicine. Determining the function of transport proteins experimentally is challenging, as they become unstable when isolated from cell membranes. Machine learning-based predictions could provide an efficient alternative. However, existing methods are limited to predicting a small number of specific substrates or broad transporter classes. These limitations stem partly from using small datasets for model training and a choice of input features that lack sufficient information about the prediction problem. Here, we present SPOT, the first general machine learning model that can successfully predict specific substrates for arbitrary transport proteins, achieving an accuracy above 92% on independent and diverse test data covering widely different transporters and a broad range of metabolites. SPOT uses Transformer Networks to represent transporters and substrates numerically. To overcome the problem of missing negative data for training, it augments a large dataset of known transporter-substrate pairs with carefully sampled random molecules as non-substrates. SPOT not only predicts specific transporter-substrate pairs, but also outperforms previously published models designed to predict broad substrate classes for individual transport proteins. We provide a web server and Python function that allows users to explore the substrate scope of arbitrary transporters.

bioinformatics↗

bioRxiv2023

Calibrated Identification of Feature Dependencies in Single-cell Multiomics

Data-driven identification of functional relationships between cellular properties is an exciting promise of single-cell genomics, especially given the increasing prevalence of assays for multiomic and spatial transcriptomic analysis. Major challenges include dealing with technical factors that might introduce or obscure dependencies between measurements, handling complex generative processes that require nonlinear modeling, and correctly assessing the statistical significance of discoveries. VI-VS (Variational Inference for Variable Selection) is a comprehensive framework designed to strike a balance between robustness and interpretability. VI-VS employs nonlinear generative models to identify conditionally dependent features, all while maintaining control over false discovery rates. These conditional dependencies are more stringent and more likely to represent genuine causal relationships. VI-VS is openly available at https://github.com/YosefLab/VIVS, offering a no-compromise solution for identifying relevant feature relationships in multiomic data, advancing our understanding of molecular biology.

bioinformatics↗

bioRxiv2023

Antisense transcription interferes with heterologous expression of a codon-optimised mNeonGreen fluorescent reporter in the chloroplast of Chlamydomonas reinhardtii.

Although over 30 years have passed since Chlamydomonas reinhardtii chloroplast transformation was first achieved, robust genetic engineering of the chloroplast still remains a challenging task. The glass-bead transformation method has enabled simple and accessible chloroplast transformation of the C. reinhardtii TN72 strain, allowing generation of marker-free transplastomic strains for low-cost experimentation. However, lack of functional in vivo fluorescent reporters limit research and widespread development of chloroplast engineering. Here, we developed a chloroplast codon-optimised mNeonGreen fluorescent reporter, which can be detected in vivo through fluorescence microscopy and fluorometry, by context-aware construct engineering, leading up to a [~]6-fold increase in fluorescence. We found evidence for chloroplast post-transcriptional regulation of gene expression derived from formation of antisense pairing of mRNAs due to transcriptional readthrough of the convergent adjacent gene, which was validated through detection of the double-stranded RNA. In addition, engineering approaches were used to modulate transcriptional readthrough, allowing a better understanding of context effects that are relevant for heterologous expression. Finally, we characterised a suite of regulatory parts for transgene expression in a sense-transcriptional context regarding to the selectable marker, achieving up to [~]2-fold increase in mNeonGreen fluorescence levels regarding to the control, with the use of PrrnS, 5atpA and 3rbcL endogenous regulatory sequences from the chloroplast of C. reinhardtii. This work provides new tools for studying basic aspects of the molecular biology in the chloroplast in C. reinhardtii, as well as evidence for fundamental processes of gene regulation that may enable developing rules for more efficient chloroplast engineering.

plant biology↗

bioRxiv2023

Inositolphosphate glycans accumulate and suppress plant defense during Arabidopsis/Botrytis interaction

This study investigates the presence and significance of previously undiscovered oligosaccharides that accumulate during the interaction between Arabidopsis thaliana and Botrytis cinerea, a pathogenic fungus. Initially focused on characterizing cell wall-derived oligosaccharides, the research uncovered inositol phosphate glycans (IPGs) originating from plant sphingolipids, specifically glycosylinositol phosphorylceramides. Advanced chromatography, mass spectrometry techniques and molecular biology were employed to identify these IPGs, determine their origins, and study their role in the A. thaliana-B. cinerea interaction. Contrary to the conventional belief that oligosaccharides trigger plant defense, this research suggests that B. cinerea releases IPGs identical to those generated by host plant to actually downregulate plant defense mechanisms. This discovery offers insight into the dynamic strategies used by B. cinerea to evade plant defenses and establish successful infections. One-Sentence SummaryA plant pathogen releases products identical to those generated by host plant that aids in evasion of the plant defense.

plant biology↗

bioRxiv2023

Discovering Secondary Protein Structures via Local Euler Curvature

Protein structure analysis and classification, which is fundamental for predicting protein function, still poses formidable challenges in the fields of molecular biology, mathematics, physics and computer science. In the present work we exploit recent advances in computational topology to define a new intrinsic unsupervised topological fingerprint for proteins. These fingerprints, computed via Local Euler Curvature (LECs), identify secondary protein structures, such as Helices and Sheets, by capturing their distinctive topological signatures. Using an extensive protein residue database, the proposed computational framework not only distinguishes between structural classes via unsupervised clustering but also achieves remarkable accuracy in classifying proteins structures through supervised machine learning classifier. We also show that the internal structure of LEC space embeds the information about the secondary structure of proteins. Beyond its immediate implications for the advancement of critical application areas such as drug design and biotechnology, our approach opens a fascinating avenue towards characterizing the multiscale structures of diverse biopolymers based solely on their geometric and topological attributes.

biochemistry↗

bioRxiv2023

A simple methods for obtaining a multivalent protein with a variable number of binding sites and estimating its binding parameters

The study of natural and the design of artificial multivalent proteins is a promising field of molecular biology. Working with such proteins is much more difficult than with their monovalent analogues. In this paper, we show how using a ring of heptameric Sm-like protein as a scaffold, it is possible to create a multivalent protein with a different number of binding sites. This is an urgent task for the study of multivalent and multicenter protein-protein interactions. The method of analysis used in the work allows us to evaluate the stoichiometry and the dissociation constant of complexes of artificial chaperone with a non-native protein. It is shown that for reliable binding of non-native LA, its interaction with several apical domains of GroEL is necessary. At the same time, the dissociation constant of such a complex does not significantly change with an increase in the number of binding domains in the oligomer. Up to 4 LA molecules can be attached to the complete heptameric ring of apical domains. The proposed methods have a good cost-to-result ratio and can be applied to the study and design of other new proteins.

bioengineering↗

bioRxiv2023

Proteomic and Physiological Signatures of Altitude Adaptation in a Myrsine coriacea Population under Common Garden Conditions

Plants exhibit phenotypic plasticity in response to environmental variations, which can lead to stable genetic and physiological adaptations if exposure to specific conditions is prolonged. Myrsine coriacea demonstrates this through its ability to thrive in diverse environments. The objective of the article is to investigate the adaptive responses of M. coriacea by cultivating plants from seeds collected at four different altitudes in a common garden experiment. Through integrated physiological and proteomic analyses, we identified 170 differentially accumulated proteins and observed significant physiological differences among the populations. The high-altitude population (POP1) exhibited a unique proteomic profile with significant down-regulation of proteins involved in carbon fixation and energy metabolism, suggesting a potential reduction in photosynthetic efficiency. Physiological analyses showed lower leaf nitrogen content, net CO2 assimilation rate, specific leaf area, and relative growth rate in stem height for POP1, alongside higher leaf carbon isotopic composition ({delta}13C) and leaf carbon (C) content. These findings provide insight into the complex interplay between proteomic and physiological adaptations in M. coriacea and underscore the importance of local adaptations. This study enhances our understanding of how altitude-specific selection pressures can shape plant molecular biology and physiology, offering valuable perspectives for predicting plant responses to global environmental changes. HighlightThis study unveils proteomic and physiological adaptations in a high-altitude M. coriacea population with reduced carbon fixation and energy metabolism.

plant biology↗

bioRxiv2023

Epithelial N-methyl-D-aspartate (NMDA) receptors mediate renal vasodilation by affecting kidney autoregulation.

BackgroundN-methyl-D-aspartate receptor (NMDAR) are amino acid receptors that are well studied in brain physiology; however, their role in kidney is poorly understood. Nonetheless, NMDAR inhibitors can increase serum K+ and reduce GFR, which suggests they have an important physiological role in the kidney. We hypothesized that NMDARs in the distal nephron induce afferent-arteriole vasodilation through the vasodilator mechanism connecting-tubule-glomerular feedback (CNTGF) that involves ENaC activation. Methods and resultsUsing a tubule-specific transcriptome database combined with molecular biology and microscopy techniques, we showed kidney expression of NMDAR subunits along the nephron and specifically in ENaC-positive cells. This receptor is expressed in both male and female mice, with higher abundance in females (p=0.02). Microperfusing NMDAR agonists into the connecting tubule induced afferent-arteriole vasodilation (EC50 10.7 vs. 24.5 mM; p<0.001) that was blunted or eliminated with the use of NMDAR blocker MK-801 or with the ENaC inhibitor Benzamil, indicating a dependence on CNTGF of the NMDAR-induced vasodilation. In vivo, we confirmed this CNTGF-associated vasodilation using kidney micropuncture (Stop-flow pressure 37.9{+/-}2.6 vs. 28.6{+/-}1.9 mmHg, NMDAR agonist vs vehicle; p<0.01). We explored NMDAR and ENaC channel interaction by using mpkCCD cells and split-open connecting tubules. We observed increased amiloride-sensitive current following NMDAR activation that was prevented by MK-801 (1.14 vs. 0.4 Amp; p=0.03). In split-open tubules, NMDAR activation increased ENaC activity (Npo Vehicle vs. NMDA; p=0.04). ConclusionNMDARs are expressed along the nephron, including ENaC-positive cells, with higher expression in females. Epithelial NMDAR mediates renal vasodilation through the connecting-tubule-glomerular feedback, by increasing ENaC activity.

physiology↗

bioRxiv2023

The cryoEM structure of the Hendra henipavirus nucleoprotein reveals insights into paramyxoviral nucleocapsid architectures

We report the first cryoEM structure of the Hendra henipavirus nucleoprotein in complex with RNA, at 3.5 [A] resolution, derived from single particle analysis of homotetradecameric RNA-bound N protein rings exhibiting D14 symmetry. The structure of the HeV N protein adopts the common bi-lobed paramyxoviral N protein fold; the N-terminal and C-terminal globular domains are bisected by an RNA binding cleft containing six RNA nucleotides and are flanked by the N-terminal and C-terminal arms, respectively. In common with other paramyxoviral nucleocapsids, the lateral interface between adjacent N and N+1 protomers involves electrostatic and hydrophobic interactions mediated primarily through the N-terminal arm and globular domains with minor contribution from the C-terminal arm. However, the HeV N multimeric assembly uniquely identifies an additional interaction between N+1 and N-1 protomers. The model presented here broadens the understanding of RNA-bound paramyxoviral nucleocapsid architectures and provides a platform for further insight into the molecular biology of HeV, as well as the development of antiviral interventions.

microbiology↗

bioRxiv2024

Enhancing Antibody Language Models with Structural Information

The central tenet of molecular biology is that a proteins amino acid sequence determines its three-dimensional structure, and thus its function. However, proteins with similar sequences do not always fold into the same shape, and vice-versa, dissimilar sequences can adopt similar folds. In this work, we explore antibodies, a class of proteins in the immune system, whose local shapes are highly unpredictable, even with small variations in their sequence. Inspired by the CLIP method [1], we propose a multimodal contrastive learning approach, contrastive sequence-structure pre-training (CSSP), which amalgamates the representations of antibody sequences and structures in a mutual latent space. Integrating structural information leads both antibody and protein language models to show better correspondence with structural similarity and improves accuracy and data efficiency in downstream binding prediction tasks. We provide an optimised CSSP-trained model, AntiBERTa2-CSSP, for non-commercial use at https://huggingface.co/alchemab.

bioinformatics↗

bioRxiv2023

On the necessity to include multiple types of evidence when predicting molecular function of proteins

Machine learning-based platforms are currently revolutionizing many fields of molecular biology including structure prediction for monomers or complexes, predicting the consequences of mutations, or predicting the functions of proteins. However, these platforms use training sets based on currently available knowledge and, in essence, are not built to discover novelty. Hence, claims of discovering novel functions for protein families using artificial intelligence should be carefully dissected, as the dangers of overpredictions are real as we show in a detailed analysis of the prediction made by Kim et al 1 on the function of the YciO protein in the model organism Escherichia coli.

biochemistry↗

bioRxiv2023

Neutral evolution of snoRNA Host Gene long non-coding RNA affects cell fate control

A fundamental challenge in molecular biology is to understand how evolving genomes can acquire new functions. Several recent studies have underscored how non-conserved sequences can contribute to organismal diversification in the primate lineage1-3. Actively transcribed, non-coding parts of the genome provide a potential platform for the development of new functional sequences4, but their biological and evolutionary roles remain largely unexplored. Here we show that a set of neutrally evolving long non-coding RNAs (lncRNA) arising from small nucleolar RNA Host Genes (SNHGs) are highly expressed in skin and dysregulated in inflammatory conditions. SNHGs affect cell fate determination and can behave as evolutionary intermediates to develop new functions5. Using SNHG7 and human epidermal keratinocytes as a model, we describe a mechanism by which these lncRNAs can increase self-renewal and inhibit differentiation. SNHG7 lncRNAs activity has been acquired recently in the primate lineage and depends on a short sequence required for microRNA binding. Taken together, our results highlight the importance of understanding the role of fast-evolving transcripts in normal and diseased epithelia, and inform on how poorly conserved, actively transcribed non-coding sequences can participate in the evolution of genomic functionality.

cell biology↗

bioRxiv2024

Supercontinuum intrinsic fluorescence imaging heralds free view of living systems

Optimal imaging strategies remain underdeveloped to maximize information for fluorescence microscopy while minimizing the harm to fragile living systems. Taking hint from the supercontinuum generation in ultrafast laser physics, we generated supercontinuum fluorescence from untreated unlabeled live samples before nonlinear photodamage onset. Our imaging achieved high-content cell phenotyping and tissue histology, identified bovine embryo polarization, quantified aging-related stress across cell types and species, demystified embryogenesis before and after implantation, sensed drug cytotoxicity in real-time, scanned brain area for targeted patching, optimized machine learning to track small moving organisms, induced two-photon phototropism of leaf chloroplasts under two-photon photosynthesis, unraveled microscopic origin of autumn colors, and interrogated intestinal microbiome. The results enable a facility-type microscope to freely explore vital molecular biology across life sciences.

bioengineering↗

bioRxiv2024

Whole Genome Sequencing of DENV-2 isolated from Aedes aegypti mosquitoes in Esmeraldas, Ecuador. Genomic epidemiology of genotype III Southern Asian-American in the country.

Ecuador is a tropical country reporting Dengue virus (DENV) outbreaks with areas of hyperendemic viral transmission. Entomo-virological surveillance and monitoring effort conducted in the Northwestern border province of Esmeraldas in April 2022, five pools of female Aedes aegypti mosquitoes from a rural community tested positive for DENV serotype 2 by RT-qPCR. One pool was sequenced by Illumina MiSeq, and it corresponded to genotype III Southern Asian-American. Comparison with other genomes revealed genetic similarity to a human DENV genome sequenced in 2021, also from Esmeraldas. Potential introduction events to the country could have originated from Colombia, considering the vicinity of the collection sites to the neighboring country and high human movement. The inclusion of genomic information complements entomo-virological surveillance, providing valuable insights into genetic variants. This contribution enhances our understanding of Dengue virus (DENV) epidemiology in rural areas and guides evidence-based decisions for surveillance and interventions. Author SummaryIn this study, the complete genetic information of the dengue virus isolated from the mosquito vector Aedes aegypti was characterized using molecular biology, sequencing, and bioinformatics analysis. The isolation of the virus from the vector has contributed significantly to our understanding of the transmission dynamics of the disease and its genetic relationship with human cases. Identifying the serotypes and genotypes circulating in Ecuador has enabled us to comprehend the evolution of the virus from 2014 to 2023. Therefore, surveillance of genetic variability would aid in adapting precise prevention and control strategies to the genetic variants present in a specific geographical area. Entomo-virological surveillance is essential for assessing changes in risk and the impact of control measures.

genomics↗

bioRxiv2024

Streptavidin-drug conjugates streamline optimization of antibody-based conditioning for hematopoietic stem cell transplantation

Hematopoietic stem cell transplantation (HSCT) conditioning using antibody-drug conjugates (ADC) is a promising alternative to conventional chemotherapy- and irradiation-based conditioning regimens. The drug payload bound to an ADC is a key contributor to its efficacy and potential toxicities; however, a comparison of HSCT conditioning ADCs produced with different toxic payloads has not been performed. Indeed, ADC optimization studies in general are hampered by the inability to produce and screen multiple combinations of antibody and drug payload in a rapid, cost-effective manner. Herein, we used Click chemistry to covalently conjugate four different small molecule payloads to streptavidin; these streptavidin-drug conjugates can then be joined to any biotinylated antibody to produce stable, indirectly conjugated ADCs. Evaluating CD45-targeted ADCs produced with this system, we found the pyrrolobenzodiazepine (PBD) dimer SGD-1882 was the most effective payload for targeting mouse and human hematopoietic stem cells (HSCs) and acute myeloid leukemia cells. In murine syngeneic HSCT studies, a single dose of CD45-PBD enabled near-complete conversion to donor hematopoiesis. Finally, human CD45-PBD provided significant antitumor benefit in a patient-derived xenograft model of acute myeloid leukemia. As our streptavidin-drug conjugates were generated in-house with readily accessible equipment, reagents, and routine molecular biology techniques, we anticipate this flexible platform will facilitate the evaluation and optimization of ADCs for myriad targeting applications.

immunology↗

bioRxiv2024

A rapid and efficient in vivo inoculation method for introducing tree stem canker pathogens onto leaves, suitable for large-scale assessment of resistance in poplar breeding progeny

Hybrid breeding, a direct and efficient strategy for disease control and management in tree species, is currently limited by the selection method of resist clones: the "in vitro stem segment inoculation method." This method, constrained by the availability of inoculating materials, cannot rapidly, efficiently, and cost-effectively screen the resistance of all hybrid clones. To overcome these limitations, we introduce a novel pathogen inoculation method for the resistance assessment of hybrid clones in the poplar-Valsa sordida pathosystem. This method involves inoculating the stem canker pathogen on the host leaf, a unique and promising approach we have successfully validated. Results showed that stem canker pathogen V. sordida induced the extended necrotic lesion and even induced the formation of pycnidium structure and conidia on the leaf surface five days after mycelium inoculation; 1) the upper 5-7th leaves exhibited higher resistance than the middle 18-20th leaves; 2) the shading conditions induced more severe symptoms on the leaves than lighting conditions; 3) the juvenile mycelium inoculums (4-day-cultured) were more susceptible to poplar leaves than the old ones (7-day-cultured). Our results demonstrate the robustness of the "in vivo leaf inoculation method" in revealing the resistance differentiation in poplar hybrid clones. According to the leaf necrotic area disease index, we divided these poplar clones into seven different resistance groups. The resistance assessed by leaf assessment was validated in 15 selected poplar clones using the "in vitro stem segment inoculation method." Results showed that the effectiveness of these two methods was consistent. Moreover, the leaf inoculation method can be used to detect the pathogenicity diversity of the pathogen population of tree species. Compared to the conventional "in vitro stem segment inoculation method," the leaf method has the advantages of abundant inoculation materials, easy operation, rapid disease onset, and almost no adverse effect on the host. It is particularly suitable for the resistance screening of all progeny and the early (seedling) phenotypic selection of resistant poplar clones in poplar stem disease resistance breeding. The "in vivo leaf inoculation method" holds significant promise in poplar breeding, tree pathology, and molecular biology research on tree stem diseases.

plant biology↗

bioRxiv2024

Perturbation-aware predictive modeling of RNA splicing using bidirectional transformers

Predicting molecular function directly from DNA sequence remains a grand challenge in computational and molecular biology. Here, we engineer and train bidirectional transformer models to predict the chemical grammar of alternative human mRNA splicing leveraging the largest perturbative full-length RNA dataset to date. By combining high-throughput single-molecule long-read "chemical transcriptomics" in human cells with transformer models, we train AllSplice - a nucleotide foundation model that achieves state-of-the-art prediction of canonical and noncanonical splice junctions across the human transcriptome. We demonstrate improved performance achieved through incorporation of diverse noncanonical splice sites in its training set that were identified through long-read RNA data. Leveraging chemical perturbations and multiple cell types in the data, we fine-tune AllSplice to train ChemSplice - the first predictive model of sequence-dependent and cell-type specific alternative splicing following programmed cellular perturbation. We anticipate the broad application of AllSplice, ChemSplice, and other models fine-tuned on this foundation to myriad areas of RNA therapeutics development.

genomics↗

bioRxiv2024

A computational model for bacteriophage {varphi}X174 gene expression

Bacteriophage{phi} X174 has been widely used as a model organism to study fundamental processes in molecular biology. However, several aspects of{phi} X174 gene regulation are not fully resolved. Here we construct a computational model for{phi} X174 and use the model to study gene regulation during the phage infection cycle. We estimate the relative strengths of transcription regulatory elements (promoters and terminators) by fitting the model to transcriptomics data. We show that the specific arrangement of a promoter followed immediately by a terminator, which occurs naturally in the{phi} X174 genome, poses a parameter identifiability problem for the model, since the activity of one element can be partially compensated for by the other. We also simulate{phi} X174 gene expression with two additional, putative transcription regulatory elements that have been proposed in prior studies. We find that the activities of these putative elements are estimated to be weak, and that variation in{phi} X174 transcript abundances can be adequately explained without them. Overall, our work demonstrates that{phi} X174 gene regulation is well described by the canonical set of promoters and terminators widely used in the literature.

microbiology↗