Frédéric Mahé’s research while affiliated with Université de Montpellier and other places

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Publications (139)


O Short-branch Microsporidia, Where Art Thou? Identifying diversity hotspots for future sampling
  • Preprint
  • File available

April 2024

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95 Reads

Megan Gross

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Frederic Mahe

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[...]

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Micah Egge Dunthorn

Short-branch Microsporidia were previously shown to form a basal grade within the expanded Microsporidia clade and to branch near the classical, long-branch Microsporidia. Although they share simpler versions of some morphological characteristics, they do not show accelerated evolutionary rates, making them ideal candidates to study the evolutionary trajectories that has led to long-branch microsporidians unique characteristics. However, most sequences assigned to the short-branch Microsporidia are undescribed, novel environmental lineages for which the identification requires knowledge of where they can be found. To direct future isolation, we used the EukBank database of the global UniEuk initiative that contains the majority of the publicly available environmental V4 SSU-rRNA gene sequences of protists. The curated OTU table and corresponding metadata were used to evaluate the occurrence of short-branch Microsporidia across freshwater, hypersaline, marine benthic, marine pelagic, and terrestrial environments. Presence-absence analyses infer that short-branch Microsporidia are most abundant in freshwater and terrestrial environments, and alpha- and beta-diversity measures indicate that focusing our sampling effort on these two environments would cover a large part of their overall diversity. These results can be used to coordinate future isolation and sampling campaigns to better understand the mysterious evolution of microsporidians unique characteristics.

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Predicting global distributions of eukaryotic plankton communities from satellite data

September 2023

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408 Reads

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10 Citations

ISME Communications

Satellite remote sensing is a powerful tool to monitor the global dynamics of marine plankton. Previous research has focused on developing models to predict the size or taxonomic groups of phytoplankton. Here, we present an approach to identify community types from a global plankton network that includes phytoplankton and heterotrophic protists and to predict their biogeography using global satellite observations. Six plankton community types were identified from a co-occurrence network inferred using a novel rDNA 18 S V4 planetary-scale eukaryotic metabarcoding dataset. Machine learning techniques were then applied to construct a model that predicted these community types from satellite data. The model showed an overall 67% accuracy in the prediction of the community types. The prediction using 17 satellite-derived parameters showed better performance than that using only temperature and/or the concentration of chlorophyll a . The constructed model predicted the global spatiotemporal distribution of community types over 19 years. The predicted distributions exhibited strong seasonal changes in community types in the subarctic–subtropical boundary regions, which were consistent with previous field observations. The model also identified the long-term trends in the distribution of community types, which suggested responses to ocean warming.


Interpreting phylogenetic placements for taxonomic assignment of environmental DNA

July 2023

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124 Reads

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1 Citation

Journal of Eukaryotic Microbiology

Taxonomic assignment of operational taxonomic units (OTUs) is an important bioinformatics step in analyzing environmental sequencing data. Pairwise alignment and phylogenetic-placement methods represent two alternative approaches to taxonomic assignments, but their results can differ. Here we used available colpodean ciliate OTUs from forest soils to compare the taxonomic assignments of VSEARCH (which performs pairwise alignments) and EPA-ng (which performs phylogenetic placements). We showed that when there are differences in taxonomic assignments between pairwise alignments and phylogenetic placements at the subtaxon level, there is a low pairwise similarity of the OTUs to the reference database. We then showcase how the output of EPA-ng can be further evaluated using GAPPA to assess the taxonomic assignments when there exist multiple equally likely placements of an OTU, by taking into account the sum over the likelihood weights of the OTU placements within a subtaxon, and the branch distances between equally likely placement locations. We also inferred the evolutionary and ecological characteristics of the colpodean OTUs using their placements within subtaxa. This study demonstrates how to fully analyze the output of EPA-ng, by using GAPPA in conjunction with knowledge of the taxonomic diversity of the clade of interest.


A global perspective of the pan-Arctic community of unicellular eukaryotic plankton. (A) North Pole-centered bathymetric map of sampling stations (yellow circles) during the Tara Oceans Polar Circle expedition. Numbers indicate station groupings based on the Arctic Marine Biodiversity Monitoring Plan (Gill et al., 2011; CAFF, 2017): (1) Atlantic inflow shelf, (2) Siberian shelf (inner), (3) Pacific inflow shelf, (4) Canadian Archipelago and West Baffin, and (5) East Baffin. (B) Dynamic map of contextual information on sea ice concentration (%) and chlorophyll a (mg m⁻³) during the sampling period (derived from a 250-km latitudinal band following the timing and location of the cruise track). Black line represents the ship track; yellow circles, station locations. Satellite-derived datasets of chlorophyll and sea ice were obtained, respectively, from the European Space Agency GlobColour project (http://www.globcolour.info) and the National Snow and Ice Data Center (https://nsidc.org). For the Kara Sea and the Chukchi/Beaufort region, the actual ice-edge zone was south of that obtained via satellite. (C) Stations from the global Tara Oceans dataset (2009–2013) mapped on the world ocean bathymetry. (D) Principal coordinates analysis based on Bray-Curtis community dissimilarities for unicellular eukaryotes from the surface ocean, with proportion of variance on each axis (%). Each circle represents a community at a given sampling station (panels A and C), with colors indicating respective oceanic basins: North and South Atlantic Ocean (NAO and SAO), North and South Pacific Ocean (NPO and SPO), and Southern Ocean (SO). Filled versus open circles distinguish stations with depths below 200 m (filled) from stations shallower than 200 m (open). Six oceanographic variables were overlaid on the ordination through “envfit” function: sea surface temperature (SST), mixed layer depth (MLD), chlorophyll a (Chl a), station depth, daylength, and simulated iron concentration (statistics in Table S3). Arrows point toward the ordination space with maximal correlation; their length refers to relative strength of the correlation.
Globally contextualized biogeographic categories of Arctic OTUs and their distribution patterns. (A) Schematic representation of the different biogeographic categories where each shape represents an individual OTU colored by its biogeographic category. (B) Abundance-occupancy patterns of Arctic OTUs. Occupancy is scaled 0–1, with a value of 1 indicating that an OTU was present in all 18 stations. The rectangular frame encompasses OTUs that were present in ≥90% of the stations (a proxy for pan-Arctic distribution), which make up 6% of the total pool (Table S4). A log10-transformation of the y-axis is used for visual purposes. Each circle represents a single OTU, colored according to its biogeographic category. The inset pie chart shows the relative contribution of each biogeographic category to the total pool of Arctic OTUs; box plots show the median (and 75 percentile) abundance of OTUs for each biogeographic group (n = 18 stations). (C) Example global distributions of selected OTUs from each biogeographic category, with the name of the deep-branching lineage specified for each OTU. The size of each circle represents the relative abundance of the OTU. Data correspond to the V9 region of the 18S rRNA gene (see Methods).
Biogeographic and diversity patterns across deep-branching lineages of Arctic unicellular eukaryotic plankton. For each lineage we determined: (A) proportions of OTUs associated with each of the 5 biogeographic categories; (B) total number of OTUs in the global Tara Oceans data base, which we refer to as the global pool (PG); and (C) the fraction (%) of the global pool detected in the Arctic Ocean (PAO). The dark gray color indicates the contribution of Arctic/Polar indicators and Arctic-exclusive OTUs to this fraction. (D) Box plots for percentage identity of OTUs with matching sequence from the reference database (see Methods). Data correspond to the V9 region of the 18S rRNA gene. Taxonomic groups are sorted by phylogeny (de Vargas et al., 2015), with lineages clustered in supergroups for visual purposes and with the caveat that classification of unicellular eukaryotes is under constant revision. Lineages with <10 OTUs were not included in the figure.
OTU occurrence pattern across Arctic regions. (A) Each circle band represents one of the 5 Arctic regions (see Methods). OTUs are split by lineage and colored according to their biogeographic category defined in the context of the global sampling. Gray color means absence. Only a selection of prominent lineages containing Arctic/Polar indicators are shown (see full panel at https://doi.org/10.6084/m9.figshare.14562606). (B) A summary of panel A depicting the contribution of each biogeographic category to the total number of OTUs detected in each Arctic region and (C) the relative read abundance per biogeographic category in each Arctic region (denoted by number code as in Figure 1). Panels B and C correspond to the complete dataset as compared to panel A. Because the relative abundance of non-Polar indicators, background and Arctic-exclusive OTUs are low, we have provided an insert that only includes these categories to better visualize their abundance patterns across the different regions of the AO.
Gross change in species identity and dominance structure across the North Atlantic-Arctic domain. (A) Schematic representation of the analysis output interpretation per quadrant. (B) Comparison between and within North Atlantic and Arctic surface ocean communities of unicellular eukaryotes. Dots represent pairwise comparisons between samples and are colored by oceanic region combinations. See Table S5 for statistics supporting this analysis.
Pan-Arctic plankton community structure and its global connectivity

April 2023

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741 Reads

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10 Citations

The Arctic Ocean (AO) is being rapidly transformed by global warming, but its biodiversity remains understudied for many planktonic organisms, in particular for unicellular eukaryotes that play pivotal roles in marine food webs and biogeochemical cycles. The aim of this study was to characterize the biogeographic ranges of species that comprise the contemporary pool of unicellular eukaryotes in the AO as a first step toward understanding mechanisms that structure these communities and identifying potential target species for monitoring. Leveraging the Tara Oceans DNA metabarcoding data, we mapped the global distributions of operational taxonomic units (OTUs) found on Arctic shelves into five biogeographic categories, identified biogeographic indicators, and inferred the degree to which AO communities of unicellular eukaryotes share members with assemblages from lower latitudes. Arctic/Polar indicator OTUs, as well as some globally ubiquitous OTUs, dominated the detection and abundance of DNA reads in the Arctic samples. OTUs detected only in Arctic samples (Arctic-exclusives) showed restricted distribution with relatively low abundances, accounting for 10–16% of the total Arctic OTU pool. OTUs with high abundances in tropical and/or temperate latitudes (non-Polar indicators) were also found in the AO but mainly at its periphery. We observed a large change in community taxonomic composition across the Atlantic-Arctic continuum, supporting the idea that advection and environmental filtering are important processes that shape plankton assemblages in the AO. Altogether, this study highlights the connectivity between the AO and other oceans, and provides a framework for monitoring and assessing future changes in this vulnerable ecosystem.


Figure 1 -Sequence identity distribution analysis of viral sequences from the army ant virome. Each dot represents an assembled sequence contig with the corresponding protein identity (best BLASTx e-values < 0.001) to plant (top) and animal virus (bottom) in the GenBank nonredundant database.
Figure 3 -Phylogenies of the sequences of the viruses in the families Iflaviridae, Bidnaviridae, Hepeviridae and Polycipiviridae, as well as Picorna-like viruses. Sequences in red refer to army antassociated contigs. Neighbor joining phylogenetic trees were generated using alignments of Iflaviridae polyprotein protein sequences ranging from 965 aa to 3229 aa, Hepeviridae polyprotein protein sequences (669 aa), Picorna-like viruses polyprotein protein sequences (2487-2858 aa), Bidnaviridae major capsid protein sequences (515-615 aa) and Polycipiviridae ORF5 protein sequences (1479-2331 aa) . One thousand bootstrap replicates were performed to quantify branch support. The scale bar depicts the number of amino acid substitutions per site.
African army ants at the forefront of virome surveillance in a remote tropical forest

March 2023

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241 Reads

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3 Citations

Peer Community Journal

In this study, we used a predator-enabled metagenomics strategy to sample the virome of a remote and difficult-to-access densely forested African tropical region. Specifically, we focused our study on the use of army ants of the genus Dorylus that are obligate collective foragers and group predators that attack and overwhelm a broad array of animal prey. Using 209 army ant samples collected from 29 colonies and the virion-associated nucleic acid-based metagenomics approach, we showed that a broad diversity of bacterial, plant, invertebrate and vertebrate viral sequences were accumulated by army ants: including sequences from 157 different viral genera in 56 viral families. This suggests that using predators and scavengers such as army ants to sample broad swathes of tropical forest viromes can shed light on the composition and the structure of viral populations of these complex and inaccessible ecosystems.


African army ants at the forefront of virome surveillance in a remote tropical forest

December 2022

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182 Reads

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1 Citation

In this study, we used a predator-enabled metagenomics strategy to sample the virome of a remote and difficult-to-access densely forested African tropical region. Specifically, we focused our study on the use of army ants of the genus Dorylus that are obligate collective foragers and group predators that attack and overwhelm a broad array of animal prey. Using 209 army ant samples collected from 29 colonies and the virion-associated nucleic acid-based metagenomics approach, we showed that a broad diversity of bacterial, plant, invertebrate and vertebrate viral sequences were accumulated by army ants: including sequences from 157 different viral genera in 56 viral families. This suggests that using predators and scavengers such as army ants to sample broad swathes of tropical forest viromes can shed light on the composition and the structure of viral populations of these complex and inaccessible ecosystems.


Comparison of phylogenetic placements to pairwise alignments for taxonomic assignment of ciliate OTUs

November 2022

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110 Reads

Taxonomic assignment of OTUs is an important bioinformatics step in analyzing environmental sequencing data. Pairwise-alignment and phylogenetic-placement methods represent two alternative approaches to taxonomic assignments, but their results can differ. Here we used available colpodean ciliate OTUs from forest soils to compare the taxonomic assignments of VSEARCH (which performs pairwise alignments) and EPA-ng (which performs phylogenetic placements). We showed that when there are differences in taxonomic assignments between pairwise alignments and phylogenetic placements at the subtaxon level, there is a low pairwise similarity of the OTUs to the reference database. We then showcase how the output of EPA-ng can be further evaluated using GAPPA to assess the taxonomic assignments when there exist multiple equally likely placements of an OTU, by taking into account the sum over the likelihood weights of the OUT placements within a subtaxon, and the branch distances between equally likely placement locations. We also inferred evolutionary and ecological characteristics of the colpodean OTUs using their placements within subtaxa. This study demonstrates how to fully analyse the output of EPA-ng, by using GAPPA in conjunction with knowledge of the taxonomic diversity of the clade of interest.


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EukRibo: a manually curated eukaryotic 18S rDNA reference database to facilitate identification of new diversity

November 2022

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429 Reads

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11 Citations

EukRibo is a manually curated, public reference database of small-subunit ribosomal RNA gene (18S rDNA) sequences of eukaryotes, specifically aimed at taxonomic annotation of high-throughput metabarcoding datasets. Unlike other reference databases of ribosomal genes, it is not meant to exhaustively capture all publicly available 18S rDNA sequences from the INSDC repositories, but to represent a subset of highly trustable sequences covering the whole known diversity of eukaryotes. EukRibo strives to include only sequences with verified, up-to-date taxonomic identifications, with a strong focus on protists, and relatively low genetic redundancy, to keep the database compact yet comprehensive. Environmental clone sequences representing previously identified novel diversity are accepted as reference sequences only if they have a precise lineage designation, useful for taxonomic annotation. EukRibo is part of a suite of public resources generated by the UniEuk project, which all follow a common taxonomic framework for maximal interoperability. The high level of taxonomic accuracy of EukRibo allows higher confidence in the taxonomic annotation of environmental metabarcodes, and should facilitate identification of new eukaryotic diversity at various taxonomic levels. The database is currently in version 2, and all versions are permanently stored and made available via the FAIR open platform Zenodo. It is our hope that EukRibo will help ongoing curation efforts of other 18S rDNA reference databases, and we welcome suggestions of corrections and new features to be included in subsequent versions.


Figure S1. Comparison of satellite-derived parameters acquired by the Aqua and the Terra satellite. Pearson's correlation coefficient was shown for each parameter pairs.
Figure S2. Location of satellite-derived parameter samples used for leaning UMAP. Dark grey points are location of grid cells used to learn a map with UMAP. Sampling month was also randomly selected for each grid cell.
Figure S5. Spatial resampling of metabarcoding data. A Geographic location of 653 metabarcoding samples (bins) before spatial resampling. B 177 samples retained and used for the analysis.
Figure S12. Permutation importance of each parameter in the full SVM model. Blue bars show mean of parameter importance over 5 times repeats. Error bars show standard deviation over repeats. CHL: chlorophyll a concentration, KD490: diffuse attenuation coefficient for downwelling irradiance at 490 nm, PIC/POC: particulate organic/inorganic carbon concentration, PAR: photosynthetically available radiation, FLH: normalized fluorescence line height, SST: sea surface temperature, RRS: remote sensing reflectance
Global observation of plankton communities from space

September 2022

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621 Reads

Satellite remote sensing from space is a powerful way to monitor the global dynamics of marine plankton. Previous research has focused on developing models to predict the size or taxonomic groups of phytoplankton. Here we present an approach to identify representative communities from a global plankton network that included both zooplankton and phytoplankton and using global satellite observations to predict their biogeography. Six representative plankton communities were identified from a global co-occurrence network inferred using a novel rDNA 18S V4 planetary-scale eukaryotic metabarcoding dataset. Machine learning techniques were then applied to train a model that predicted these representative communities from satellite data. The model showed an overall 67% accuracy in the prediction of the representative communities. The prediction based on 17 satellite-derived parameters showed better performance than based only on temperature and/or the concentration of chlorophyll a. The trained model allowed to predict the global spatiotemporal distribution of communities over 19-years. Our model exhibited strong seasonal changes in the community compositions in the subarctic-subtropical boundary regions, which were consistent with previous field observations. This network-oriented approach can easily be extended to more comprehensive models including prokaryotes as well as viruses.


Citations (56)


... These methods have been employed in ecology to divide communities based on species composition (e.g., [13]) or in oceanography to describe communities of marine plankton (e.g., [14]). Network methods are particularly useful for dividing large datasets with many associated variables, such as amplicon sequencing data [15,16] or satellite remote sensing data [17,18], into a smaller number of communities with similar features. Thus, these methods offer an ideal approach for the challenge of integrating remote sensing information and PCC information across scales. ...

Reference:

Phytoplankton communities quantified from hyperspectral ocean reflectance correspond to pigment-based communities
Predicting global distributions of eukaryotic plankton communities from satellite data

ISME Communications

... A primary task in metagenomics is taxon assignment, wherein organisms present in a sequenced sample are classified. Pairwise alignment and phylogenetic placement represent two alternative methods for taxonomic assignments [3]. While sequence alignment can be time-intensive and lacks evolutionary context, phylogenetic placement is highly effective for taxon identification as it determines the evolutionary position of sequences in relation to a reference phylogenetic tree [4]. ...

Interpreting phylogenetic placements for taxonomic assignment of environmental DNA

Journal of Eukaryotic Microbiology

... It is essential to acknowledge that both Archambault et al. (2010) and Poulin et al. (2011) conducted their analyses based on literature reviews predominantly reliant on microscopic observations. In more recent comprehensive pan-Arctic taxonomic inventories using genomic techniques, Lovejoy et al. (2017) and Ibarbalz et al. (2023) reported 2241 and 3082 different operational taxonomic unit (OTU) taxa, respectively. The discrepancy in reported taxa between our study and the aforementioned studies can be attributed to the fundamental differences in our respective approaches -our reliance on mainly microscopic observations (i.e. ...

Pan-Arctic plankton community structure and its global connectivity

... b. a circovirid identified in a fecal sample of a New Zealand black robin was named robinz virus (derived from robin New Zealand virus) [41]; c. a circovirid identified in army ant samples from Gabon was named army ant associated cyclovirus [42]; ...

African army ants at the forefront of virome surveillance in a remote tropical forest

Peer Community Journal

... Protist ribosomal RNA (rRNA) sequences with a minimum sequence length of 2,000 bp were collected from the PR 2 reference sequence database (Guillou et al. 2013). The R package pr2database was used to select 18S rRNA sequences from specific groups of taxa (phyla Discosea, Heterolobosea, and Tubulinea), reference sequences of the major taxa within these groups, and sequences that are annotated in EukRibo v2 Berney et al. (2022). For all amoebae sequenced, additional almost complete 18S rRNA sequences were added to cross-validate the specific strains we sequenced. ...

EukRibo: a manually curated eukaryotic 18S rDNA reference database to facilitate identification of new diversity

... Historically, the Roscoff Biological Station was established in this area because of the high species diversity. Indeed, coastal plankton [23,24], algae [25][26][27] and macro-organisms [28][29][30] have all now been intensively studied in the Roscoff region where they show high biodiversity and habitat variability. This area is also characterised by human influences such as tourism and fishing activities, for which the impact on the meiobenthos remains poorly described. ...

Seasonal dynamics of marine protist communities in tidally mixed coastal waters

Molecular Ecology

... Strikingly, the variation space of both bacterial and fungal communities was not uniformly distributed; instead, there were three distinct clusters separated by insect groups (Fig. 1C through F). These results indicated that community composition variation is more pronounced among insect groups than within groups, and thus similarity in both microbiome and mycobiome among insect groups likely mirrors the host phylogeny, although evidence of phylosym biosis requires further exploration (40,41). While sharing a diet may weaken potential microbiota composition differences among ants, flies, and beetles, each insect species harbors its own specific bacteria or fungi. ...

Fruit fly phylogeny imprints bacterial gut microbiota

... The prevalence rate is higher in low-and middle-income countries and among the elderly [3][4][5][6]. Periodontitis and caries can lead to various issues, such as discolored teeth, irreversible alveolar bone absorption, and tooth loss, ultimately increasing the risk of developing chronic and lethal diseases, if left untreated [7][8][9]. The gradual progression from gingivitis to periodontitis involves over ten types of bacteria, heightening the risk of conditions including cancer, cardiovascular disease, and inflammatory bowel diseases [2,7,[10][11][12][13][14]. ...

Periodontitis associates with species-specific gene expression of the oral microbiota

npj Biofilms and Microbiomes

... Along the French coasts, some studies investigated the communities of marine microorganisms using molecular approaches. For example, Caracciolo et al. (2021) used eDNA metabarcoding to confirm the seasonal dynamics of marine protists communities on the English Channel, while Lambert et al. (2021) studied the seasonal succession of marine microorganisms on the NW Mediterranean coast focusing on the winter period (January-March). In southern Brittany, to our knowledge, our study is the first specifically exploring the autumn-winter protistan community with a new tool, the eDNA metabarcoding, that provides a quite exhaustive characterisation of the relative abundance of protist genera and groups as well as the detection of rare taxa in the environment. ...

Seasonal temporal dynamics of marine protists communities in tidally mixed coastal waters

... The developed mutants exhibited improved growth and increased hydrolytic enzymatic activity (for pectinase and cellulase) compared to their native isolates ( Figure 2B-D), indicating enhanced biological/symbiotic nitrogen fixation (BNF) ability of these mutants. While hydrolytic enzymes (pectinase and cellulase) play a crucial role in the central event of infection during symbiosis [36], host choice and BNF behave as independent traits [37]. ...

Genetic Variation in Host-Specific Competitiveness of the Symbiont Rhizobium leguminosarum Symbiovar viciae