Biology subjects

Morel, B.

Publications and source records attributed to Morel, B..

At least 19 recordsLinked to original sources

bioRxiv2025

RACLET: the Ramp Above Critical Level Endurance Test to evaluate critical force in isometric task.

The Ramp Above Critical Level Endurance Test (RACLET) is a novel submaximal test designed to evaluate the parameters of the critical force model without strenuous exercise. This study aimed to validate the RACLET in healthy and pathological populations and to assess its reliability, concurrent validity, and predictive capacity. Sixteen healthy volunteers and ten patients with respiratory pathologies participated in this study. The RACLET consisted of a decreasing ramp force starting at 60% and ending at 15% of the maximum force for a total duration of 425 s with brief regular maximal voluntary contractions. The goodness of fit for the RACLET model on the maximal contraction force was excellent in both populations (median r2{approx} 0.95). In patients, RACLET parameters demonstrated excellent reliability (ICC > 0.90). The concurrent validity of the critical force estimate compared with the all-out method was high (error: -0.3{+/-}7.4%). The models predictive capacity for time-to-exhaustion and fatigue during constant-intensity exercise was excellent (r2 = 0.910 and 0.907, respectively). The RACLET provides a reliable and valid estimate of critical force model parameters opening up numerous practical applications in vulnerable populations, individualised physical activity programs, and longitudinal monitoring. The feasibility and performance of the test make it a promising tool for assessing muscle function in various contexts.

biophysics↗

bioRxiv2025

RACLET: the Ramp Above Critical Level Endurance Test to evaluate critical power in cycling.

This study introduces the Ramp Above Critical Level Endurance Test (RACLET), a novel method for evaluating critical power model parameters, and tests its reliability and concurrent validity. Twenty-three participants completed several RACLET and time-to-exhaustion tests (TTE). The RACLET involves a decreasing power ramp with intermittent maximal sprints, inducing moderate fatigue without exhaustion. The test demonstrated excellent reliability for the initial power (Pi) and critical power (Pc) (ICC > 0.97), with acceptable reliability for the time constant ({tau}) (ICC = 0.70). The concurrent validity against TTE was excellent for Pi and Pc (systematic errors: 1.7% and 3.0%, respectively), but moderate for{tau} and maximum work above the critical power (systematic errors {approx} 10%). The RACLET showed excellent predictive capacity for time-to-exhaustion (systematic error = -0.6%; random error = 10.3%). These results suggest that the RACLET is a reliable, valid, and efficient alternative to traditional critical power testing methods, offering comparable accuracy with a single test without inducing exhaustion. This approach could be particularly beneficial for populations in which exhaustive testing is challenging or impractical.

biophysics↗

bioRxiv2025

RACLET: the Ramp Above Critical Level Endurance Test to evaluate critical velocity in running.

Critical velocity (Vc) is an important fatigability threshold in running, but only strenuous methods exist to assess it (e.g. time-trials). Based on a novel mathematical model of fatigability, the Ramp Above Critical Level Endurance Test (RACLET), a simple, non-exhaustive, 5-min test to evaluate Vc was developed. This study aimed to test the reliability and validity of the RACLET. Thirty-eight participants performed two RACLET (session 1) and three time-trials (sessions 2-4). For the RACLET, velocity target tracking was guaranteed by either a pacing bike or cones and whistle signals. GPS was used to measure the participants running velocities. Vc,{tau} , and [Formula] were determined by adjusting the fatigability model on the measured Vmax. The RACLET test-retest and RACLET vs. time-trials parameters were compared for reliability and validity testing, respectively. The RACLET Vc is reliable and valid (mean difference=-1.7{+/-}1.9% and 6.2{+/-}6.5%, respectively). Although{tau} and [Formula] presented important variability (s.d. difference ~30%), the combination of the RACLET parameters enabled an excellent prediction of time-trials performance (mean error=-8.9{+/-}5.1%, 0.9{+/-}7.4%, -2.0{+/-}5.2% for 400, 1500, and 3000 m, respectively). RACLET is a novel non-exhausting test that enables a reliable and valid assessment of the velocity-time relationship parameters.

biophysics↗

bioRxiv2025

A single decreasing ramp friction sprint for torque-cadence relationship assessment during cycling

This study aimed to introduce and validate a novel method for assessing dynamic fatigue components through a single-sprint test, addressing the limitations of traditional multi-sprint evaluations. We tested this method on twenty-one participants by computing torque-cadence relationships from two iso-friction sprints at varying friction levels (3% and 9% of body mass), the traditional combination of these iso-friction sprints and a novel decreasing ramp friction sprint (FrD). The accuracy of this new method through fatigue was also tested with ten 6-s FrD sprints interspersed with a 24-s passive rest. FrD outperformed single iso-friction sprints and provided accurate and valid torque-cadence relationships parameters estimates (T0, C0, and Pmax) with systematic bias < 3%, typical error of estimate < 6% and very high r2 (median of 0.962). The quality of the input data from this method was also high, as evidenced by the well-distributed and wide-range cadence spectrum (51.3% of C0; skewness = -0.51, p < 0.05) and was maintained throughout the fatiguing exercise. Our novel method not only allows the dynamic fatigue components evaluation with only one sprint but also maintains accuracy and validity across varying fatigue states, offering significant advantages for both research and practical applications.

physiology↗

bioRxiv2024

Step-by-step methodology for building a capsule to sample small intestine content

BackgroundResearch on the intestinal microbiome has been hindered by limited access to intestinal content. Recently, a few capsule prototypes have demonstrated their potential for sampling intestinal material while using the natural pathway. However, access to these capsules is restricted because most of them are not yet commercially available. Pigs offer significant potential to inform human research due to the many physiological similarities between the two species. The unique features of pig anatomy have made it difficult to conduct research using swallowable devices. This article provides a detailed account of the manufacturing process and composition of a capsule, along with all the necessary steps for successfully sampling small intestine content in pigs. ResultsThe capsule moves passively through the digestive tract, relying solely on intestinal peristalsis for propulsion. Engineered to open when it encounters a pH level greater than 6, the upper part dissolves, allowing intestinal fluids to enter the inner chamber. This triggers a plunger to expand, drawing luminal content into the storage chamber. Once the plunger mechanism is fully extended the capsule is automatically sealed. The capsule has a size of a 0 hard capsule and consists of two main components: a dissolvable exterior with an enteric coating and a 3D-printed bottom part. The printing files of the 3D-printed bottom part are provided for replication. In vitro testing shows that the capsule can withstand two hours in an acidic medium and successfully samples within an hour of being transferred to a neutral medium. When tested in vivo in pigs, the capsule successfully collected intestinal content from the upper and middle sections of the small intestine. ConclusionsThis article provides essential details for the rapid development of a cost-effective tool that has been already validated for non-invasive sampling of small intestine content in pigs. By providing access to the exact production steps and printing files, this article empowers others to innovate and expand upon this foundational work. This open-source approach opens up new avenues for intestinal research, making it more accessible and adaptable for a wide range of studies in both animal and human models.

bioengineering↗

bioRxiv2024

Identifying the Last Universal Common Ancestor's protein domains resolves the order in which the amino acids were recruited into the genetic code

The current "consensus" order in which amino acids were added to the genetic code is based on potentially biased criteria, such as absence of sulfur-containing amino acids from the Urey-Miller experiment which lacked sulfur. More broadly, abiotic abundance might not reflect biotic abundance in the organisms in which the genetic code evolved. Here, we instead identify which protein domains date to the last universal common ancestor (LUCA), then infer the order of recruitment from deviations of their ancestrally reconstructed amino acid frequencies from the still-ancient post-LUCA controls. We find that smaller amino acids were added to the code earlier, with no additional predictive power in the previous "consensus" order. Metal-binding (cysteine and histidine) and sulfur-containing (cysteine and methionine) amino acids were added to the genetic code much earlier than previously thought. Methionine and histidine were added to the code earlier than expected from their molecular weights, and glutamine later. Early methionine availability is compatible with inferred early use of S-adenosylmethionine, and early histidine with its purine-like structure and the demand for metal-binding. Even more ancient protein sequences -- those that had already diversified into multiple distinct copies prior to LUCA -- have significantly higher frequencies of aromatic amino acids (tryptophan, tyrosine, phenylalanine and histidine), and lower frequencies of valine and glutamic acid than single copy LUCA sequences. If at least some of these sequences predate the current code, then their distinct enrichment patterns provide hints about earlier, alternative genetic codes. Significance StatementThe order in which the amino acids were added to the genetic code was previously inferred from consensus among forty metrics. Many of these reflect abiotic abundance on ancient Earth. However, the abundances that matter are those within primitive cells that already had sophisticated RNA and perhaps peptide metabolism. Here, we directly infer the order of recruitment from the relative ancestral amino acid frequencies of ancient protein sequences. Small size predicts ancient amino acid enrichment better than the previous consensus metric does. We place metal-binding and sulfur-containing amino acids earlier than previously thought, highlighting the importance of metal-dependent catalysis and sulfur metabolism to ancient life. Understanding early life has implications for our search for life elsewhere in the universe.

evolutionary biology↗

bioRxiv2023

AleRax: A tool for species and gene tree co-estimation and reconciliation under a probabilistic model of duplication, transfer, and loss

MotivationGenomes are a rich source of information on the pattern and process of evolution across biological scales. How best to make use of that information is an active area of research in phylogenetics. Ideally, phylogenetic methods should not only model substitutions along gene trees, which explain differences between homologous gene sequences, but also the processes that generate the gene trees themselves along a shared species tree. To conduct accurate inferences, one needs to account for uncertainty at both levels, that is, in gene trees estimated from inherently short sequences and in their diverse evolutionary histories along a shared species tree. ResultsWe present AleRax, a software that can infer reconciled gene trees together with a shared species tree using a simple, yet powerful, probabilistic model of gene duplication, transfer, and loss. A key feature of AleRax is its ability to account for uncertainty in the gene tree and its reconciliation by using an efficient approximation to calculate the joint phylogenetic-reconciliation likelihood and sample reconciled gene trees accordingly. Simulations and analyses of empirical data show that AleRax is one order of magnitude faster than competing gene tree inference tools while attaining the same accuracy. It is consistently more robust than species tree inference methods such as SpeciesRax and ASTRAL-Pro 2 under gene tree uncertainty. Finally, AleRax can process multiple gene families in parallel thereby allowing users to compare competing phylogenetic hypotheses and estimate model parameters, such as DTL probabilities for genome-scale datasets with hundreds of taxa Availability and ImplementationGNU GPL at https://github.com/BenoitMorel/AleRax and data are made available at https://cme.h-its.org/exelixis/material/alerax_data.tar.gz. ContactBenoit.Morel@h-its.org Supplementary informationSupplementary material is available.

bioinformatics↗

bioRxiv2023

The power and limitations of species tree-aware phylogenetics

Species tree-aware phylogenetic methods model how gene trees are generated along the species tree by a series of evolutionary events, including the duplication, transfer and loss of genes. Over the past ten years these methods have emerged as a powerful tool for inferring and rooting gene and species trees, inferring ancestral gene repertoires, and studying the processes of gene and genome evolution. However, these methods are complex and can be more difficult to use than traditional phylogenetic approaches. Method development is rapid, and it can be difficult to decide between approaches and interpret results. Here, we review ALE and GeneRax, two popular packages for reconciling gene and species trees, explaining how they work, how results can be interpreted, and providing a tutorial for practical analysis. It was recently suggested that reconciliation-based estimates of duplication and transfer frequencies are unreliable. We evaluate this criticism and find that, provided parameters are estimated from the data rather than being fixed based on prior assumptions, reconciliation-based inferences are in good agreement with the literature, recovering variation in gene duplication and transfer frequencies across lineages consistent with the known biology of studied clades. For example, published datasets support the view that transfers greatly outnumber duplications in most prokaryotic lineages. We conclude by discussing some limitations of current models and prospects for future progress. Significance statementEvolutionary trees provide a framework for understanding the history of life and organising biodiversity. In this review, we discuss some recent progress on statistical methods that allow us to combine information from many different genes within the framework of an overarching phylogenetic species tree. We review the advantages and uses of these methods and discuss case studies where they have been used to resolve deep branches within the tree of life. We conclude with the limitations of current methods and suggest how they might be overcome in the future.

evolutionary biology↗

bioRxiv2022

Asteroid: a new minimum balanced evolution supertree algorithm robust to missing data.

MotivationMissing data and incomplete lineage sorting are two major obstacles to accurate species tree inference. Gene tree methods such as ASTRAL and ASTRID have been developed to account for incomplete lineage sorting. However, they can be severely affected by high levels of missing data. ResultsWe present Asteroid, a novel supertree method that infers an unrooted species tree from a set of unrooted gene trees. We show on both empirical and simulated datasets that Asteroid is more robust to missing data than ASTRAL and ASTRID, while being several orders of magnitude faster than ASTRAL for datasets that contain thousands of genes. Asteroid offers advanced features such as parallelization, support value computation, and support for multi-copy and multifurcating gene trees. AvailabilityAsteroid is freely available at https://github.com/BenoitMorel/Asteroid Contactbenoit.morel@h-its.org online.

bioinformatics↗

bioRxiv2021

NetRAX: Accurate and Fast Maximum Likelihood Phylogenetic Network Inference

Phylogenetic networks are used to represent non-treelike evolutionary scenarios. Current, actively developed approaches for phylogenetic network inference jointly account for non-treelike evolution and incomplete lineage sorting (ILS). Unfortunately, this induces a very high computational complexity. Hence, current tools can only analyze small data sets. We present NetRAX, a tool for maximum likelihood inference of phylogenetic networks in the absence of incomplete lineage sorting. Our tool leverages state-of-the-art methods for efficiently computing the phylogenetic likelihood function on trees, and extends them to phylogenetic networks via the notion of "displayed trees". NetRAX can infer maximum likelihood phylogenetic networks from partitioned multiple sequence alignments and returns the inferred networks in Extended Newick format. On simulated data, our results show a very low relative difference in BIC score and a near-zero unrooted softwired cluster distance to the true, simulated networks. With NetRAX, a network inference on a partitioned alignment with 8, 000 sites, 30 taxa, and 3 reticulations completes within a few minutes on a standard laptop. Our implementation is available under the GNU General Public License v3.0 at https://github.com/lutteropp/NetRAX.

bioinformatics↗

bioRxiv2021

SpeciesRax: A tool for maximum likelihood species tree inference from gene family trees under duplication, transfer, and loss.

Species tree inference from gene family trees is becoming increasingly popular because it can account for discordance between the species tree and the corresponding gene family trees. In particular, methods that can account for multiple-copy gene families exhibit potential to leverage paralogy as informative signal. At present, there does not exist any widely adopted inference method for this purpose. Here, we present SpeciesRax, the first maximum likelihood method that can infer a rooted species tree from a set of gene family trees and can account for gene duplication, loss, and transfer events. By explicitly modelling events by which gene trees can depart from the species tree, SpeciesRax leverages the phylogenetic rooting signal in gene trees. SpeciesRax infers species tree branch lengths in units of expected substitutions per site and branch support values via paralogy-aware quartets extracted from the gene family trees. Using both empirical and simulated datasets we show that SpeciesRax is at least as accurate as the best competing methods while being one order of magnitude faster on large datasets at the same time. We used SpeciesRax to infer a biologically plausible rooted phylogeny of the vertebrates comprising 188 species from 31612 gene families in one hour using 40 cores. SpeciesRax is available under GNU GPL at https://github.com/BenoitMorel/GeneRax and on BioConda.

molecular biology↗

bioRxiv2020

Are fleas highly modified Mecoptera? Phylogenomic resolution of Antliophora (Insecta: Holometabola)

Insect orders have been defined and stable for decades, with few notable exceptions (e.g., Blattodea and Psocoptera). One of the few remaining questions of order-level monophyly is that of Mecoptera in respect to the phylogenetic placement of Siphonaptera (fleas). We used a large set of transcriptomic nucleotide sequence data representing 56 species and more than 3,000 single-copy genes to resolve the evolutionary history of Antliophora, including fleas (Siphonaptera), scorpionflies and relatives (Mecoptera), and true flies (Diptera). We find that fleas and mecopterans together are the sister group of flies. However, our data and/or analyses are unable to distinguish whether fleas are sister to a monophyletic Mecoptera, or whether they arose from within extant mecopteran families, rendering Mecoptera paraphyletic. We did not detect parameter bias in our dataset after applying a broad range of detection methods. Counter to a previous hypothesis that placed fleas within Mecoptera as the sister group to wingless boreids (snow fleas), we found a potential sister group relationship between fleas and the enigmatic family Nannochoristidae. Although we lack conclusive evidence, it seems possible that fleas represent the most-species rich group of modern mecopterans and that their parasitic lifestyle and morphological adaptations have simply made them unrecognizable in respect to their order-level classification.

evolutionary biology↗

bioRxiv2020

Phylogenetic analysis of SARS-CoV-2 data is difficult

Numerous studies covering some aspects of SARS-CoV-2 data analyses are being published on a daily basis, including a regularly updated phylogeny on nextstrain.org. Here, we review the difficulties of inferring reliable phylogenies by example of a data snapshot comprising all virus sequences available on May 5, 2020 from gisaid.org. We find that it is difficult to infer a reliable phylogeny on these data due to the large number of sequences in conjunction with the low number of mutations. We further find that rooting the inferred phylogeny with some degree of confidence either via the bat and pangolin outgroups or by applying novel computational methods on the ingroup phylogeny does not appear to be possible. Finally, an automatic classification of the current sequences into sub-classes based on statistical criteria is also not possible, as the sequences are too closely related. We conclude that, although the application of phylogenetic methods to disentangle the evolution and spread of COVID-19 provides some insight, results of phylogenetic analyses, in particular those conducted under the default settings of current phylogenetic inference tools, as well as downstream analyses on the inferred phylogenies, should be considered and interpreted with extreme caution.

evolutionary biology↗

bioRxiv2019

Treerecs: an integrated phylogenetic tool, from sequences to reconciliations

MotivationGene and species tree reconciliation methods are used to interpret gene trees, root them and correct uncertainties that are due to scarcity of signal in multiple sequence alignments. So far, reconciliation tools have not been integrated in standard phylogenetic software and they either lack performance on certain functions, or usability for biologists. ResultsWe present Treerecs, a phylogenetic software based on duplication-loss reconciliation. Treerecs is simple to install and to use. It is fast and versatile, has a graphic output, and can be used along with methods for phylogenetic inference on multiple alignments like PLL and Seaview. AvailabilityTreerecs is open-source. Its source code (C++, AGPLv3) and manuals are available from https://project.inria.fr/treerecs/ Contacteric.tannier@inria.fr or david.parsons@inria.fr

bioinformatics↗

bioRxiv2019

GeneRax: A tool for species tree-aware maximum likelihood based gene tree inference under gene duplication, transfer, and loss.

Inferring phylogenetic trees for individual homologous gene families is difficult because alignments are often too short, and thus contain insufficient signal, while substitution models inevitably fail to capture the complexity of the evolutionary processes. To overcome these challenges species tree-aware methods also leverage information from a putative species tree. However, only few methods are available that implement a full likelihood framework or account for horizontal gene transfers. Furthermore, these methods often require expensive data pre-processing (e.g., computing bootstrap trees), and rely on approximations and heuristics that limit the degree of tree space exploration. Here we present GeneRax, the first maximum likelihood species tree-aware phylogenetic inference software. It simultaneously accounts for substitutions at the sequence level as well as gene level events, such as duplication, transfer, and loss relying on established maximum likelihood optimization algorithms. GeneRax can infer rooted phylogenetic trees for multiple gene families, directly from the per-gene sequence alignments and a rooted, yet undated, species tree. We show that compared to competing tools, on simulated data GeneRax infers trees that are the closest to the true tree in 90% of the simulations in terms of relative Robinson-Foulds distance. On empirical datasets, GeneRax is the fastest among all tested methods when starting from aligned sequences, and it infers trees with the highest likelihood score, based on our model. GeneRax completed tree inferences and reconciliations for 1099 Cyanobacteria families in eight minutes on 512 CPU cores. Thus, its parallelization scheme enables large-scale analyses. GeneRax is available under GNU GPL at https://github.com/BenoitMorel/GeneRax.

bioinformatics↗

bioRxiv2019

ModelTest-NG: a new and scalable tool for the selection of DNA and protein evolutionary models

ModelTest-NG is a re-implementation from scratch of jModelTest and ProtTest, two popular tools for selecting the best-fit nucleotide and amino acid substitution models, respectively. ModelTest-NG is one to two orders of magnitude faster than jModelTest and ProtTest but equally accurate, and introduces several new features, such as ascertainment bias correction, mixture and FreeRate models, or the automatic processing of partitioned datasets. ModelTest-NG is available under a GNU GPL3 license at https://github.com/ddarriba/modeltest.

bioinformatics↗

bioRxiv2019

Data Distribution for Phylogenetic Inference with Site Repeats via Judicious Hypergraph Partitioning

The so-called site repeats (SR) technique can be used to accelerate the widely-used phylogenetic likelihood function (PLF) by identifying identical patterns among multiple sequence alignment (MSA) sites, thereby omitting redundant calculations and saving memory. However, this complicates the optimal data distribution of MSA sites in parallel likelihood calculations, as the cost of computing the likelihood for individual sites strongly depends on the sites-to-cores assignment. We show that finding a good sites-to-cores assignment can be modeled as a hypergraph partitioning problem, more specifically, a specific instance of the so-called judicious hypergraph partitioning problem. We initially develop, parallelize, and make available HyperPhylo, an efficient open-source implementation for this flavor of judicious partitioning where all vertices have the same degree. Using empirical MSA data, we then show that sites-to-core assignments computed via HyperPhylo are substantially better than those obtained via a previous na i ve approach for phylogenetic data distribution under SRs.

bioinformatics↗

bioRxiv2018

RAxML-NG: A fast, scalable, and user-friendly tool for maximum likelihood phylogenetic inference

MotivationPhylogenies are important for fundamental biological research, but also have numerous applications in biotechnology, agriculture, and medicine. Finding the optimal tree under the popular maximum like-lihood (ML) criterion is known to be NP-hard. Thus, highly optimized and scalable codes are needed to analyze constantly growing empirical datasets.\n\nResultsWe present RAxML-NG, a from scratch re-implementation of the established greedy tree search algorithm of RAxML/ExaML. RAxML- NG offers improved accuracy, flexibility, speed, scalability, and usability compared to RAxML/ExaML. On taxon-rich datasets, RAxML-NG typically finds higher-scoring trees than IQTree, an increasingly popular recent tool for ML-based phylogenetic inference (although IQ-Tree shows better stability). Finally, RAxML-NG introduces several new features, such as the detection of terraces in tree space and a the recently introduced transfer bootstrap support metric.\n\nAvailabilityThe code is available under GNU GPL at https://github.com/amkozlov/raxml-ng.RAxML-NG web service (maintained by Vital- IT) is available at https://raxml-ng.vital-it.ch/.\n\nContactalexey.kozlov@h-its.org

bioinformatics↗