Biology subjects

Lemoine, F.

Publications and source records attributed to Lemoine, F..

18 recordsLinked to original sources

bioRxiv2026

Accounting for Defective Viral Genomes in viral consensus genome reconstruction, application to influenza virus

In the context of viral epidemic surveillance, generating accurate consensus viral genomes from sequencing data is critical for tracking the emergence of mutations of concern, evaluating the genomic diversity of circulating viruses, and anticipating which viral strains could become most prevalent. However, this task is made difficult by the presence of Deletion-containing Viral Genomes (DelVGs), which contain truncated (or rearranged) and potentially mutated versions of the full length virus genome. Because these DelVGs can outnumber the full genome in terms of coverage, potential DelVG specific mutations may be erroneously incorporated into the final consensus, thereby compromising its accuracy. Automatic detection of these DelVGs and of the genomic positions that may harbor DelVG specific mutations is therefore crucial. Here, we present DIPScan, a new method able to (i) accurately and efficiently detect DelVGs in short read datasets, and (ii) mask or correct positions in the consensus genome that may be affected by DelVG-specific mutations. Using several hundreds of simulated and real patient-derived NGS datasets from the National Reference Center (NRC) for respiratory viruses at Institut Pasteur, we demonstrate the capacity of DIPScan to accurately and efficiently detect DelVGs and to correctly adjust the consensus sequences. DIPScan is implemented as a Nextflow workflow, making it highly flexible, scalable, and reproducible, and is now used routinely at the NRC.

bioinformatics↗

bioRxiv2024

Global evolutionary patterns of Yersinia pestis and its spread into Africa

The zoonotic pathogen Yersinia pestis, the etiologic agent of plague, has caused three major pandemics and diversified in different lineages currently established in endemic areas worldwide1-3. However, some regions like continental Africa have been poorly covered within the global diversity and epidemiological history of this pathogen2,4-6. Here, we report the whole-genome sequences of 1,124 Y. pestis isolates collected from endemic areas worldwide over 116 years, nearly doubling the available genomic data for the species. By integrating population genomics and historical research, we retrace the introduction of multiple Y. pestis lineages into continental Africa, revealing the diversity of the 1.ANT lineage, its historical emergence and its spread to and within Africa since the late 17th century. We identify key mechanisms of genome evolution, including signatures of adaptive evolution present in virulence and biofilm-related genes such as RovA, a master virulence regulator, which likely play a role in the pathogens adaptation and endemic persistence. Additionally, our findings reveal an increased trajectory of genome degradation and expansion of IS elements in different lineages. This trend appears especially pronounced in 1.ANT genomes, promoting the remarkable genomic variation within this lineage. Taken together, our findings shed light on the introduction and evolutionary history of plague in Africa and provide a comprehensive framework for understanding the global diversity and genome evolution of Y. pestis, revealing potential factors contributing to its long-term adaptation in endemic areas.

microbiology↗

bioRxiv2024

Escape of SARS-CoV-2 variants KP1.1, LB.1 and KP3.3 from approved monoclonal antibodies

First-generation anti-SARS-CoV-2 monoclonal antibodies (mAbs) used for prophylaxis or therapeutic purposes in immunocompromised patients have been withdrawn because of the emergence of resistant Omicron variants. In 2024, two novel mAbs, Pemivibart and Sipavibart, have been approved by health authorities, but their activity against contemporary JN.1 sublineages is poorly characterized. We isolated authentic JN.1.1, KP1.1, LB.1 and KP3.3 viruses and evaluated their sensitivity to neutralization by these mAbs in two target cell lines. Compared to ancestral strains, Pemivibart remained moderately active against JN.1 sub-variants, with a strong increase of 50% Inhibitory Concentration (IC50), reaching up to 3 to 15 g/ml for KP3.3. Sipavibart neutralized JN.1.1 but lost antiviral efficacy against KP1.1, LB.1 and KP3.3. Our results highlight the need for a close clinical monitoring of Pemivibart and raise concerns about the clinical efficacy of Sipavibart.

immunology↗

bioRxiv2024

The Bayesian Phylogenetic Bootstrap, Application to Short Trees and Branches

Felsensteins bootstrap is the most commonly used method to measure branch support in phylogenetics. Current sequencing technologies can result in massive sampling of taxa (e.g. SARS-CoV-2). In this case, the sequences are very similar, the trees are short, and the branches correspond to a small number of mutations (possibly 0). Nevertheless, these trees contain a strong signal, with unresolved parts but a low rate of false branches. With such data, Felsensteins bootstrap is not satisfactory. Due to the frequentist nature of bootstrap sampling, the expected support of a branch corresponding to a single mutation is [~]63%, even though it is highly likely to be correct. Here we propose a Bayesian version of the phylogenetic bootstrap in which sites are assigned uninformative prior probabilities. The branch support can then be interpreted as a posterior probability. We do not view the alignment as a small subsample of a large sample of sites, but rather as containing all available information (e.g., as with complete viral genomes, which are becoming routine). We give formulas for expected supports under the assumption of perfect phylogeny, in both the frequentist and Bayesian frameworks, where a branch corresponding to a single mutation now has an expected support of [~]90%. Simulations show that these theoretical results are robust to realistic data. Analyses on low-homoplasy viral and non-viral datasets show that Bayesian bootstrap support is easier to interpret, with high supports for branches very likely to be correct. As homoplasy increases, the two supports become closer and strongly correlated.

evolutionary biology↗

bioRxiv2023

Distinct evolution of SARS-CoV-2 Omicron XBB and BA.2.86 lineages combining increased fitness and antibody evasion

The unceasing circulation of SARS-CoV-2 leads to the continuous emergence of novel viral sublineages. Here, we isolated and characterized XBB.1, XBB.1.5, XBB.1.9.1, XBB.1.16.1, EG.5.1.1, EG.5.1.3, XBF, BA.2.86.1 and JN.1 variants, representing >80% of circulating variants in January 2024. The XBB subvariants carry few but recurrent mutations in the spike, whereas BA.2.86.1 and JN.1 harbor >30 additional changes. These variants replicated in IGROV-1 but no longer in Vero E6 and were not markedly fusogenic. They potently infected nasal epithelial cells, with EG.5.1.3 exhibiting the highest fitness. Antivirals remained active. Neutralizing antibody (NAb) responses from vaccinees and BA.1/BA.2-infected individuals were markedly lower compared to BA.1, without major differences between variants. An XBB breakthrough infection enhanced NAb responses against both XBB and BA.2.86 variants. JN.1 displayed lower affinity to ACE2 and higher immune evasion properties compared to BA.2.86.1. Thus, while distinct, the evolutionary trajectory of these variants combines increased fitness and antibody evasion.

microbiology↗

bioRxiv2023

BioConvert: a comprehensive format converter for life sciences

AO_SCPLOWBSTRACTC_SCPLOWBioinformatics is a field known for the numerous standards and formats that have been developed over the years. This plethora of formats, sometimes complementary, and often redundant, poses many challenges to bioinformatics data analysts. They constantly need to find the best tool to convert their data into the suitable format, which is often a complex, technical and time consuming task. Moreover, these small yet important tasks are often difficult to make reproducible. To over-come these difficulties, we initiated BioConvert, a collaborative project to facilitate the conversion of life science data from one format to another. BioConvert aggregates existing software within a single framework and complemented them with original code when needed. It provides a common interface to make the user experience more streamlined instead of having to learn tens of them. Currently, BioConvert supports about 50 formats and 100 direct conversions in areas such as alignment, sequencing, phylogeny, and variant calling. In addition to being useful for end-users, BioConvert can also be utilized by developers as a universal benchmarking framework for evaluating and comparing numerous conversion tools. Additionally, we provide a web server implementing an online user-friendly interface to BioConvert, hence allowing direct use for the community.

bioinformatics↗

bioRxiv2023

Robustness of Felsenstein's versus Transfer Bootstrap Supports with respect to Taxon Sampling

The bootstrap method is based on resampling alignments and re-estimating trees. Felsensteins bootstrap proportions (FBP) is the most common approach to assess the reliability and robustness of sequence-based phylogenies. However, when increasing taxon-sampling (i.e., the number of sequences) to hundreds or thousands of taxa, FBP tends to return low supports for deep branches. The Transfer Bootstrap Expectation (TBE) has been recently suggested as an alternative to FBP. TBE is measured using a continuous transfer index in [0,1] for each bootstrap tree, instead of the {0,1} index used in FBP to measure the presence/absence of the branch of interest. TBE has been shown to yield higher and more informative supports, without inducing falsely supported branches. Nonetheless, it has been argued that TBE must be used with care due to sampling issues, especially in datasets with high number of closely related taxa. In this study, we conduct multiple experiments by varying taxon sampling and comparing FBP and TBE support values on different phylogenetic depth, using empirical datasets. Our results show that the main critic of TBE stands in extreme cases with shallow branches and highly unbalanced sampling among clades, but that TBE is still robust in most cases, while FBP is inescapably negatively impacted by high taxon sampling. We suggest guidelines and good practices in TBE (and FBP) computing and interpretation.

bioinformatics↗

bioRxiv2023

APOBEC3F is the main source of editing identified during the 2022 outbreak of human monkeypox virus

On May 6, 2022, a powerful outbreak of monkeypox virus (MPXV) had been reported outside of Africa, with many continuing new cases being reported around the world. Analysis of mutations among the two different lineages present in the 2021 and 2022 outbreaks revealed the presence of G->A mutations occurring in the 5GpA context, indicative of APOBEC3 cytosine deaminase activity. By using a sensitive PCR (3D-PCR) method allowing differential amplification of AT-rich DNA, we demonstrate that G->A hypermutated MPXV genomes can be recovered experimentally from APOBEC3 transfection followed by MPXV infection. Here, among the 7 human APOBEC3 cytidine deaminases (A3A-A3C, A3DE, A3F-A3H), only APOBEC3F was capable of extensively deaminating cytidine residues in MPXV genomes. Hyperedited genomes were also recovered in ~42% of analyzed patients, indicating that editing is part of the natural cycle of MPXV infection. Moreover, we demonstrate that substantial repair of these mutations occurs. Upon selection, corrected G->A mutations escaping drift loss contribute to the MPXV evolution observed in the current epidemics. Thus, stochastic or transient overexpression of APOBEC3F gene exposes the MPXV genome to a broad spectrum of mutations that may be modeling the mutational landscape after multiple cycles of viral replication.

microbiology↗

bioRxiv2022

Enhanced neutralization escape to therapeutic monoclonal antibodies by SARS-CoV-2 Omicron sub-lineages

The landscape of SARS-CoV-2 variants dramatically diversified with the simultaneous appearance of multiple sub-variants originating from BA.2, BA.4 and BA.5 Omicron sub-lineages. They harbor a specific set of mutations in the spike that can make them more evasive to therapeutic monoclonal antibodies. In this study, we compared the neutralizing potential of monoclonal antibodies against the Omicron BA.2.75.2, BQ.1, BQ.1.1 and XBB variants, with a pre-Omicron Delta variant as a reference. Sotrovimab retains some activity against BA.2.75.2, BQ.1 and XBB as it did against BA.2/BA.5, but is less active against BQ.1.1. Within the Evusheld/AZD7442 cocktail, Cilgavimab lost all activity against all subvariants studied, resulting in loss of Evusheld activity. Finally, Bebtelovimab, while still active against BA.2.75, also lost all neutralizing activity against BQ.1, BQ.1.1 and XBB variants.

microbiology↗

bioRxiv2022

A new route for integron cassette dissemination among bacterial genomes

Integrons are genetic elements involved in bacterial adaptation. They can capture, shuffle and express adaptive functions embedded in cassettes. These events are governed by the integron integrase through site-specific recombination between attC and attI integron sites. Here, we demonstrated that the integrase can efficiently catalyze insertion of cassettes in bacterial genomes, outside the att sites. We showed that, once inserted in genomes, cassettes can be expressed, if located near bacterial promoters, and can be excised at the insertion point and even outside, inducing chromosomal modifications in the latter case. Analysis of more than 5 x 105 independent insertion events revealed a very large genomic insertion landscape with recombination sites greatly different, in terms of sequence and structure, from classical att sites. We named these new sites attG. These results unveil a new efficient route for dissemination of adaptive functions and expand the role of integrons in bacterial evolution.

genetics↗

bioRxiv2021

Considerable escape of SARS-CoV-2 variant Omicron to antibody neutralization

The SARS-CoV-2 Omicron variant was first identified in November 2021 in Botswana and South Africa1,2. It has in the meantime spread to many countries and is expected to rapidly become dominant worldwide. The lineage is characterized by the presence of about 32 mutations in the Spike, located mostly in the N-terminal domain (NTD) and the receptor binding domain (RBD), which may enhance viral fitness and allow antibody evasion. Here, we isolated an infectious Omicron virus in Belgium, from a traveller returning from Egypt. We examined its sensitivity to 9 monoclonal antibodies (mAbs) clinically approved or in development3, and to antibodies present in 90 sera from COVID-19 vaccine recipients or convalescent individuals. Omicron was totally or partially resistant to neutralization by all mAbs tested. Sera from Pfizer or AstraZeneca vaccine recipients, sampled 5 months after complete vaccination, barely inhibited Omicron. Sera from COVID-19 convalescent patients collected 6 or 12 months post symptoms displayed low or no neutralizing activity against Omicron. Administration of a booster Pfizer dose as well as vaccination of previously infected individuals generated an anti-Omicron neutralizing response, with titers 5 to 31 fold lower against Omicron than against Delta. Thus, Omicron escapes most therapeutic monoclonal antibodies and to a large extent vaccine-elicited antibodies.

immunology↗

bioRxiv2021

Sensitive Detection of Site-wise Convergent Evolution in Large Protein Alignments with ConDor

Evolutionary convergences are observed at all levels, from phenotype to DNA and protein sequences, and changes at these different levels tend to be highly correlated. Notably, convergent and parallel mutations can lead to convergent changes in phenotype, such as changes in metabolism, drug resistance, and other adaptations to changing environments. We propose a two-step approach to detect mutations under convergent evolution in protein alignments. We first select mutations that emerge more often than expected under neutral evolution and then test whether their emergences correlate with the convergent phenotype under study. The first step can be used alone when no phenotype is available, as is often the case with microorganisms. In the first step, a phylogeny is inferred from the data and used to simulate the evolution of each alignment position. These simulations are used to estimate the expected number of mutations under neutral conditions, which is compared to what is observed in the data. Next, using a comparative phylogenetic approach, we measure whether the presence of mutations occurring more often than expected correlates with the convergent phenotype. Our method is implemented in a standalone workflow and a webserver, called ConDor. We apply ConDor to three datasets: sedges PEPC proteins, HIV reverse transcriptase and fish rhodopsin. The results show that the two components of ConDor complement each other, with an overall accuracy that compares favorably to other available tools, especially on large datasets.

evolutionary biology↗

bioRxiv2021

Gotree/Goalign : Toolkit and Go API to facilitate the development of phylogenetic workflows

Besides computer intensive steps, phylogenetic analysis workflows are usually composed of many small, reccuring, but important data manipulations steps. Among these, we can find file reformatting, sequence renaming, tree re-rooting, tree comparison, bootstrap support computation, etc. These are often performed by custom scripts or by several heterogeneous tools, which may be error prone, uneasy to maintain and produce results that are challenging to reproduce. For all these reasons, the development and reuse of phylogenetic workflows is often a complex task. We identified many operations that are part of most phylogenetic analyses, and implemented them in a toolkit called Gotree/Goalign. The Gotree/Goalign toolkit implements more than 120 user-friendly commands and an API dedicated to multiple sequence alignment and phylogenetic tree manipulations. It is developed in Go, which makes executables efficient, easily installable, integrable in workflow environments, and parallelizable when possible. This toolkit is freely available on most platforms (Linux, MacOS and Windows) and most architectures (amd64, i386). Sources and binaries are available on GitHub at https://github.com/evolbioinfo/gotree, Bioconda, and DockerHub.

bioinformatics↗

bioRxiv2021

Deep learning from phylogenies to uncover the transmission dynamics of epidemics

Widely applicable, accurate and fast inference methods in phylodynamics are needed to fully profit from the richness of genetic data in uncovering the dynamics of epidemics. Standard methods, including maximum-likelihood and Bayesian approaches, generally rely on complex mathematical formulae and approximations, and do not scale with dataset size. We develop a likelihood-free, simulation-based approach, which combines deep learning with (1) a large set of summary statistics measured on phylogenies or (2) a complete and compact representation of trees, which avoids potential limitations of summary statistics and applies to any phylodynamics model. Our method enables both model selection and estimation of epidemiological parameters from very large phylogenies. We demonstrate its speed and accuracy on simulated data, where it performs better than the state-of-the-art methods. To illustrate its applicability, we assess the dynamics induced by superspreading individuals in an HIV dataset of men-having-sex-with-men in Zurich. Our tool PhyloDeep is available on github.com/evolbioinfo/phylodeep.

bioinformatics↗

bioRxiv2020

Differing impacts of global and regional responses on SARS-CoV-2 transmission cluster dynamics

Although the global response to COVID-19 has not been entirely unified, the opportunity arises to assess the impact of regional public health interventions and to classify strategies according to their outcome. Analysis of genetic sequence data gathered over the course of the pandemic allows us to link the dynamics associated with networks of connected individuals with specific interventions. In this study, clusters of transmission were inferred from a phylogenetic tree representing the relationships of patient sequences sampled from December 30, 2019 to April 17, 2020. Metadata comprising sampling time and location were used to define the global behavior of transmission over this earlier sampling period, but also the involvement of individual regions in transmission cluster dynamics. Results demonstrate a positive impact of international travel restrictions and nationwide lockdowns on global cluster dynamics. However, residual, localized clusters displayed a wide range of estimated initial secondary infection rates, for which uniform public health interventions are unlikely to have sustainable effects. Our findings highlight the presence of so-called "super-spreaders", with the propensity to infect a larger-than-average number of people, in countries, such as the USA, for which additional mitigation efforts targeting events surrounding this type of spread are urgently needed to curb further dissemination of SARS-CoV-2.

genomics↗

bioRxiv2020

COVID-Align: Accurate online alignment of hCoV-19 genomes using a profile HMM

MotivationThe first cases of the COVID-19 pandemic emerged in December 2019. Until the end of February 2020, the number of available genomes was below 1,000, and their multiple alignment was easily achieved using standard approaches. Subsequently, the availability of genomes has grown dramatically. Moreover, some genomes are of low quality with sequencing/assembly errors, making accurate re-alignment of all genomes nearly impossible on a daily basis. A more efficient, yet accurate approach was clearly required to pursue all subsequent bioinformatics analyses of this crucial data. ResultshCoV-19 genomes are highly conserved, with very few indels and no recombination. This makes the profile HMM approach particularly well suited to align new genomes, add them to an existing alignment and filter problematic ones. Using a core of [~]2,500 high quality genomes, we estimated a profile using HMMER, and implemented this profile in COVID-Align, a user-friendly interface to be used online or as standalone via Docker. The alignment of 1,000 genomes requires less than 20mn on our cluster. Moreover, COVID-Align provides summary statistics, which can be used to determine the sequencing quality and evolutionary novelty of input genomes (e.g. number of new mutations and indels). Availabilityhttps://covalign.pasteur.cloud, hub.docker.com/r/evolbioinfo/covid-align Contactsolivier.gascuel@pasteur.fr, frederic.lemoine@pasteur.fr Supplementary informationSupplementary information is available at Bioinformatics online.

bioinformatics↗

bioRxiv2018

Distribution and asymptotic behavior of the phylogenetic transfer distance

The transfer distance (TD) was introduced in the classification framework and studied in the context of phylogenetic tree matching. Recently, Lemoine et al. (2018) showed that TD can be a powerful tool to assess the branch support of phylogenies with large data sets, thus providing a relevant alternative to Felsensteins bootstrap. This distance allows a reference branch {beta} in a reference tree [T] to be compared to a branch b from another tree T, both on the same set of n taxa. The TD between these branches is the number of taxa that must be transferred from one side of b to the other in order to obtain {beta}. By taking the minimum TD from {beta} to all branches in T we define the transfer index, denoted by{phi} ({beta}, T), measuring the degree of agreement of {beta} with T. Let us consider a reference branch {beta} having p tips on its light side and define the transfer support (TS) as 1 -{phi} ({beta}, T)/(p - 1). The aim of this article is to provide evidence that p 1 is a meaningful normalization constant in the definition of TS, and measure the statistical significance of TS, assuming that {beta} is compared to a tree T drawn according to a null model. We obtain several results that shed light on these questions in a number of settings. In particular, we study the asymptotic behavior of TS when n tends to {infty}, and fully characterize the distribution of{phi} when T is a caterpillar tree.

evolutionary biology↗

bioRxiv2017

Boosting Felsenstein Phylogenetic Bootstrap

Felsensteins article describing the application of the bootstrap to evolutionary trees, is one of the most cited papers of all time. That statistical method, based on resampling and replications, is used extensively to assess the robustness of phylogenetic inferences. However, increasing numbers of sequences are now available for a wide variety of species, and phylogenies with hundreds or thousands of taxa are becoming routine. In that framework, Felsensteins bootstrap tends to yield very low supports, especially on deep branches. We propose a revised version, in which the presence of inferred branches in replications is measured using a gradual \"transfer\" distance, as opposed to the original version using a binary presence/absence index. The resulting supports are higher, while not inducing falsely supported branches. Our method is applied to large simulation, mammal and HIV datasets, for which it reveals the phylogenetic signal, while Felsensteins bootstrap fails to do so.

evolutionary biology↗