Biology subjects

Danchin, A.

Publications and source records attributed to Danchin, A..

8 recordsLinked to original sources

bioRxiv2022

Computation of Antigenicity Predicts SARS-CoV-2 Vaccine Breakthrough Variants

It has been reported that multiple SARS-CoV-2 variants of concerns (VOCs) including B.1.1.7 (Alpha), B.1.351 (Beta), P.1 (Gamma), and B.1.617.2 (Delta) can reduce neutralisation by antibodies, resulting in vaccine breakthrough infections. Virus-antiserum neutralisation assays are typically performed to monitor potential vaccine breakthrough strains. However, such experimental-based methods are slow and cannot instantly validate whether newly emerging variants can break through current vaccines or therapeutic antibodies. To address this, we sought to establish a computational model to predict the antigenicity of SARS-CoV-2 variants by sequence alone and in real time. In this study, we firstly identified the relationship between the antigenic difference transformed from the amino acid sequence and the antigenic distance from the neutralisation titres. Based on this correlation, we obtained a computational model for the receptor binding domain (RBD) of the spike protein to predict the fold decrease in virus-antiserum neutralisation titres with high accuracy (~0.79). Our predicted results were comparable with experimental neutralisation titres of variants, including B.1.1.7 (Alpha), B.1.351 (Beta), B.1.617.2 (Delta), B.1.429 (Epsilon), P.1 (Gamma), B.1.526 (Iota), B.1.617.1 (Kappa), and C.37 (Lambda), as well as SARS-CoV. Here, we firstly predicted the fold of decrease of B.1.1.529 (Omicron) as 17.4-fold less susceptible to neutralisation. We visualised all 1521 SARS-CoV-2 lineages to indicate variants including B.1.621 (Mu), B.1.630, B.1.633, B.1.649, and C.1.2, which can induce vaccine breakthrough infections in addition to reported VOCs B.1.351 (Beta), P.1 (Gamma), B.1.617.2 (Delta), and B.1.1.529 (Omicron). Our study offers a quick approach to predict the antigenicity of SARS-CoV-2 variants as soon as they emerge. Furthermore, this approach can facilitate future vaccine updates to cover all major variants. An online version can be accessed at http://jdlab.online.

evolutionary biology↗

bioRxiv2021

Queuine, a bacterial derived hypermodified nucleobase, shows protection in in vitro models of neurodegeneration

Growing evidence suggests that human gut bacteria, comprising the microbiome that communicates with the brain through the so-called gut-brain-axis, are linked to neurodegenerative disorders. Imbalances in the microbiome of Parkinsons disease (PD) and Alzheimers disease (AD) patients have been detected in several studies. Queuine is a hypermodified nucleobase enriched in the brain and exclusively produced by bacteria and salvaged by humans through their gut epithelium. Queuine replaces guanine at the wobble position of tRNAs with GUN anticodons and promotes efficient cytoplasmic and mitochondrial mRNA translation. To elucidate whether queuine could facilitate protein folding and prevent aggregation and mitochondrial defects, hallmarks of neurodegenerative disorders, we tested the effect of chemically synthesized queuine, STL-101, in several in vitro models of neurodegeneration. Treatment with STL-101 led to increased neuronal survival as well as a significant decrease in hyper-phosphorylated alpha-synuclein, a marker of alpha-synuclein aggregation in a PD model and a decrease in tau hyperphosphorylation in an AD model. Our work has identified a new role for queuine in neuroprotection uncovering a therapeutic potential for STL-101 in neurological disorders.

neuroscience↗

bioRxiv2020

Biochemical and mathematical lessons from the evolution of the SARS-CoV-2 virus: paths for novel antiviral warfare

In the fight against the spread of COVID-19 the emphasis is on vaccination or on reactivating existing drugs used for other purposes. The tight links that necessarily exist between the virus as it multiplies and the metabolism of its host are systematically ignored. Here we show that the metabolism of all cells is coordinated by the availability of a core building block of the cells genome, cytidine triphosphate (CTP). This metabolite is also the key to the synthesis of the viral envelope and to the translation of its genome into proteins. This unique role explains why evolution has led to the early emergence in animals of an antiviral immunity enzyme, viperin, that synthesizes a toxic analogue of CTP. The constraints arising from this dependency guide the evolution of the virus. With this in mind, we explored the real-time experiment taking place before our eyes using probabilistic modelling approaches to the molecular evolution of the virus. We have thus followed, almost on a daily basis, the evolution of the composition of the viral genome to link it to the progeny produced over time, particularly in the form of blooms that sparked a firework of viral mutations. Some of those certainly increase the propagation of the virus. This led us to make out the critical role in this evolution of several proteins of the virus, such as its nucleocapsid N, and more generally to begin to understand how the virus ties up the host metabolism to its own benefit. A way for the virus to escape CTP-dependent control in cells would be to infect cells that are not expected to grow, such as neurons. This may account for unexpected body sites of viral development in the present epidemic.

microbiology↗

bioRxiv2020

A path towards SARS-CoV-2 attenuation: metabolic pressure on CTP synthesis rules the virus evolution

Fighting the COVID-19 epidemic summons deep understanding of the way SARS-CoV-2 taps into its host cell metabolic resources. We describe here the singular metabolic background that creates a bottleneck constraining coronaviruses to evolve towards likely attenuation in the long term. Cytidine triphosphate (CTP) is at the crossroad of the biosynthetic processes that allow the virus to multiply. This is because CTP is in demand for three essential steps. It is a building block of the virus genome, it is required for synthesis of the cytosine-based liponucleotide precursors of the viral envelope and, finally, it is a critical building block of the host transfer RNAs synthesis. The CCA 3-end of all the transfer RNAs required to translate the RNA genome and further transcripts into the proteins used to build active virus copies is not coded in the human genome. It must be synthesized de novo from CTP and ATP. Furthermore, intermediary metabolism is built on compulsory steps of synthesis and salvage of cytosine-based metabolites via uridine triphosphate (UTP) that keep limiting CTP availability. As a consequence, accidental replication errors tend to replace cytosine by uracil in the genome, unless recombination events allow the sequence to return to its ancestral sequences. We document some of the consequences of this situation in the function of viral proteins. We also highlight and provide a raison detre to viperin, an enzyme of innate antiviral immunity, which synthesizes 3-deoxy-3',4-didehydro-CTP (ddhCTP) as an extremely efficient antiviral nucleotide.

genomics↗

bioRxiv2020

Phylogenomics of expanding uncultured environmental Tenericutes provides insights into their pathogenicity and evolutionary relationship with Bacilli

The metabolic capacity, stress response and evolution of uncultured environmental Tenericutes have remained elusive, since previous studies have been largely focused on pathogenic species. In this study, we expanded analyses on Tenericutes lineages that inhabit various environments using a collection of 840 genomes. Several novel environmental lineages were discovered inhabiting the human gut, ground water, bioreactors and hypersaline lake and spanning the Haloplasmatales and Mycoplasmatales orders. A phylogenomics analysis of Bacilli and Tenericutes genomes revealed that some uncultured Tenericutes are affiliated with novel clades in Bacilli, such as RF39, RFN20 and ML615. Erysipelotrichales and two major gut lineages, RF39 and RFN20, were found to be neighboring clades of Mycoplasmatales. We detected habitat-specific functional patterns between the pathogenic, gut and the environmental Tenericutes, where genes involved in carbohydrate storage, carbon fixation, mutation repair, environmental response and amino acid cleavage are overrepresented in the genomes of environmental lineages. We hypothesize that the two major gut lineages, namely RF39 and RFN20, are probably acetate and hydrogen producers. Furthermore, deteriorating capacity of bactoprenol synthesis for cell wall peptidoglycan precursors secretion is a potential adaptive strategy employed by these lineages in response to the gut environment. This study uncovers the characteristic functions of environmental Tenericutes and their relationships with Bacilli, which sheds new light onto the pathogenicity and evolutionary processes of Mycoplasmatales. IMPORTANCEEnvironmental Tenericutes bacteria were recently discovered in numerous environments. However, our current collection of Tenericutes genomes was overrepresented by those for pathogens. Our phylogenomics study displays the relationships between all the available Tenericutes, as well as those between Tenericutes and the clades in Bacilli, which casts lights into the uncertain boundary between the environmental lineages of Tenericutes and Bacilli. By comparing the genomes of the environmental and pathogenic Tenericutes, we revealed the metabolic pathways and adaptive strategies of the Tenericutes in the different environments and hosts. We also predicted the metabolism of the two major gut lineages RF39 and RFN20 of Tenericutes, indicating their potential importance in stabilization of the gut microbiome and contribution to human health.

microbiology↗

bioRxiv2019

Evaluating the Probability of CRISPR-based Gene Drive Contaminating Another Species

The probability D that a given CRISPR-based gene drive element contaminates another, non-target species can be estimated by the following Drive Risk Assessment Quantitative Estimate (DRAQUE) Equation: D = (hyb+transf).express.cut.flank.immune.nonextinct with\nhyb = probability of hybridization between the target species and a non-target species\ntransf = probability of horizontal transfer of a piece of DNA containing the gene drive cassette from the target species to a non-target species (with no hybridization)\nexpress = probability that the Cas9 and guide RNA genes are expressed\ncut = probability that the CRISPR-guide RNA recognizes and cuts at a DNA site in the new host\nflank = probability that the gene drive cassette inserts at the cut site\nimmune = probability that the immune system does not reject Cas9-expressing cells\nnonextinct = probability of invasion of the drive within the population\n\n\nWe discuss and estimate each of the seven parameters of the equation, with particular emphasis on possible transfers within insects, and between rodents and humans. We conclude from current data that the probability of a gene drive cassette to contaminate another species is not insignificant. We propose strategies to reduce this risk and call for more work on estimating all the parameters of the formula.

genetics↗

bioRxiv2019

Hypothesis, analysis and synthesis: it's all Greek to me!

The linguistic foundations of science and technology have relied on a range of terms many of which are borrowed from ancient languages, a known but little researched fact from a statistical perspective. Precise definitions and novel concepts are often crafted with those -- frequently used -- terms, yet their etymology from Greek or Latin might not always be fully appreciated. Herein, we demonstrate that frequently used terms span almost the entire PubMed(R) database, while a handful of terms of Greek origin retrieve 80% of all entries. We argue that the etymology of those critical terms needs to be fully grasped to ensure correct use, in conjunction with other concepts. We further propose a number of terms for genomics, using prepositions that can accurately define subtle sub-disciplines of this ever-expanding field. Finally, we invite commentary by both the science community and the humanities, for possible adoption of suggested terms, not least to avoid inaccurate usage or inappropriate notions that may compromise clarity of meaning.

scientific communication and education↗

bioRxiv2018

Interpretable and accurate prediction models for metagenomics data

Biomarker discovery using metagenomic data is becoming more prevalent for patient diagnosis, prognosis and risk evaluation. Selected groups of microbial features provide signatures that characterize host disease states such as cancer or cardio-metabolic diseases. Yet, the current predictive models stemming from machine learning still behave as black boxes. Moreover, they seldom generalize well when learned on small datasets. Here, we introduce an original approach that focuses on three models inspired by microbial ecosystem interactions: the addition, subtraction, and ratio of microbial taxon abundances. While being extremely simple, their performance is surprisingly good and compares to or is better than Random Forest, SVM or Elastic Net. Such models besides being interpretable, allow distilling biological information of the predictive core-variables. Collectively, this approach builds up both reliable and trustworthy diagnostic decisions while agreeing with societal and legal pressure that require explainable AI models in the medical domain.

bioinformatics↗