Gisèle Bronner
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Gisèle Bronner has a total of 21 co-authors. Here are the top co-authors by number of shared publications:
- Anne Moné
CNRS, Laboratoire Microorganismes: Génome et Environnement, Université Clermont Auvergne Clermont‐Ferrand France
3 shared publications - Cécile Lepère
CNRS, Laboratoire Microorganismes: Génome et Environnement, Université Clermont Auvergne Clermont‐Ferrand France
3 shared publications - Didier Debroas
CNRS, Laboratoire Microorganismes: Génome et Environnement Université Clermont Auvergne Clermont‐Ferrand France
3 shared publications Agnès Vellet
CNRS, Laboratoire Microorganismes: Génome et Environnement Université Clermont Auvergne Clermont‐Ferrand France
2 shared publications- Arthur Monjot
CNRS, Laboratoire Microorganismes: Génome et Environnement, Université Clermont Auvergne Clermont‐Ferrand France
2 shared publications - Marina Chauvet
CNRS, Laboratoire Microorganismes: Génome et Environnement, Université Clermont Auvergne Clermont‐Ferrand France
2 shared publications
Latest Publications
- Open Access
- 24 April 2026
- Published by Pensoft Publishers in Metabarcoding and Metagenomics
- Vol. 10
Profiling the eukaryotic diversity over a year in a lake ecosystem through short- and long-read metabarcoding
Microbial eukaryotes play a vital role in biogeochemical cycles and aquatic food webs. Over past decades, their taxonomic diversity has been investigated using short-read DNA metabarcoding, which, while effective, is hampered by the limited resolution of the targeted regions. In this study, we utilised both short-read (Illumina) and long-read (PacBio) metabarcoding approaches to analyse eukaryotic diversity in a lake ecosystem over one year, allowing for a direct comparison of the results obtained from each method. Our metabarcoding analysis revealed a high degree of congruence between long-read and short-read data at broad taxonomic levels. However, at finer taxonomic scales, such as the genus level, long-read sequencing achieved higher resolution, enabling more precise identification of microbial eukaryotes. This enhanced taxonomic resolution proved especially valuable for tracking seasonal dynamics within key groups, including ciliates and chytrid fungi. The resolution offered by long-read sequencing provides a more detailed picture of the microbial eukaryotic community, thereby facilitating the exploration of ecological interactions at a finer scale. For example, this approach allowed us to monitor the dynamics of the chytrid genus Zygorhizidium in relation to various diatom genera, which are primary targets for chytrid parasitism.
- 24 April 2026
- Published by Pensoft Publishers in Metabarcoding and Metagenomics
- Vol. 10
Open AccessProfiling the eukaryotic diversity over a year in a lake ecosystem through short- and long-read metabarcoding
Microbial eukaryotes play a vital role in biogeochemical cycles and aquatic food webs. Over past decades, their taxonomic diversity has been investigated using short-read DNA metabarcoding, which, while effective, is hampered by the limited resolution of the targeted regions. In this study, we utilised both short-read (Illumina) and long-read (PacBio) metabarcoding approaches to analyse eukaryotic diversity in a lake ecosystem over one year, allowing for a direct comparison of the results obtained from each method. Our metabarcoding analysis revealed a high degree of congruence between long-read and short-read data at broad taxonomic levels. However, at finer taxonomic scales, such as the genus level, long-read sequencing achieved higher resolution, enabling more precise identification of microbial eukaryotes. This enhanced taxonomic resolution proved especially valuable for tracking seasonal dynamics within key groups, including ciliates and chytrid fungi. The resolution offered by long-read sequencing provides a more detailed picture of the microbial eukaryotic community, thereby facilitating the exploration of ecological interactions at a finer scale. For example, this approach allowed us to monitor the dynamics of the chytrid genus Zygorhizidium in relation to various diatom genera, which are primary targets for chytrid parasitism.
- 2 November 2023
- Published by Wiley in Environmental Microbiology
- Vol. 25 (12) , 3406-3422
Functional diversity of microbial eukaryotes in a meromictic lake: Coupling between metatranscriptomic and a trait‐based approach
The advent of high‐throughput sequencing has led to the discovery of a considerable diversity of microbial eukaryotes in aquatic ecosystems, nevertheless, their function and contribution to the trophic food web functioning remain poorly characterized especially in freshwater ecosystems. Based on metabarcoding data obtained from a meromictic lake ecosystem (Pavin, France), we performed a morpho‐physio‐phenological traits‐based approach to infer functional groups of microbial eukaryotes. Metatranscriptomic data were also analysed to assess the metabolic potential of these groups across the diel cycle, size fraction, sampling depth, and periods. Our analysis highlights a huge microbial eukaryotic diversity in the monimolimnion characterized by numerous saprotrophs expressing transcripts related to sulfur and nitrate metabolism as well as dissolved and particulate organic matter degradation. We also describe strong seasonal variations of microbial eukaryotes in the mixolimnion, especially for parasites and mixoplankton. It appears that the water mixing (occurring during spring and autumn) which benefits photosynthetic host communities also promotes parasitic fungi dissemination and over‐expression of genes involved in the zoospore phototaxis and stage transition in the parasitic cycle. Mixoplanktonic haptophytes over‐expressing photosynthesis‐, endocytosis‐ and phagosome‐linked genes under nutrient limitation also suggest that phagotrophy may provide them an advantage over non‐phagotrophic phytoplankton.
- 2 November 2023
- Published by Wiley in Environmental Microbiology
- Vol. 25 (12) , 3406-3422
Functional diversity of microbial eukaryotes in a meromictic lake: Coupling between metatranscriptomic and a trait‐based approach
The advent of high‐throughput sequencing has led to the discovery of a considerable diversity of microbial eukaryotes in aquatic ecosystems, nevertheless, their function and contribution to the trophic food web functioning remain poorly characterized especially in freshwater ecosystems. Based on metabarcoding data obtained from a meromictic lake ecosystem (Pavin, France), we performed a morpho‐physio‐phenological traits‐based approach to infer functional groups of microbial eukaryotes. Metatranscriptomic data were also analysed to assess the metabolic potential of these groups across the diel cycle, size fraction, sampling depth, and periods. Our analysis highlights a huge microbial eukaryotic diversity in the monimolimnion characterized by numerous saprotrophs expressing transcripts related to sulfur and nitrate metabolism as well as dissolved and particulate organic matter degradation. We also describe strong seasonal variations of microbial eukaryotes in the mixolimnion, especially for parasites and mixoplankton. It appears that the water mixing (occurring during spring and autumn) which benefits photosynthetic host communities also promotes parasitic fungi dissemination and over‐expression of genes involved in the zoospore phototaxis and stage transition in the parasitic cycle. Mixoplanktonic haptophytes over‐expressing photosynthesis‐, endocytosis‐ and phagosome‐linked genes under nutrient limitation also suggest that phagotrophy may provide them an advantage over non‐phagotrophic phytoplankton.
- 8 August 2022
- Published by Wiley in Molecular Ecology Resources
- Vol. 23 (1) , 222-232
FreshOmics: A manually curated and standardized –omics database for investigating freshwater microbiomes
Freshwater is a critical resource for human survival but severely threatened by anthropogenic activities and climate change. These changes strongly impact the abundance and diversity of the microbial communities which are key players in the functioning of these aquatic ecosystems. Although widely documented since the emergence of high‐throughput sequencing approaches, the information on these natural microbial communities is scattered among thousands of publications and it is therefore difficult to investigate the temporal dynamics and the spatial distribution of microbial taxa within or across ecosystems. To fill this gap and in the FAIR principles context we built a manually curated and standardized microbial freshwater –omics database (FreshOmics). Based on recognized ontologies (ENVO, MIMICS, GO, ISO), FreshOmics describes 29 different types of freshwater ecosystems and uses standardized attributes to depict biological samples, sequencing protocols and article attributes for more than 2487 geographical locations across 71 countries around the world. The database contains 24,808 sequence identifiers (i.e., Run_Id / Exp_ID, mainly from SRA/DDBJ SRA/ENA, GSA and MG‐RAST repositories) covering all sequence‐based ‐omics approaches used to investigate bacteria, archaea, microbial eukaryotes, and viruses. Therefore, FreshOmics allows accurate and comprehensive analyses of microbial communities to answer questions related to their roles in freshwater ecosystems functioning and resilience, especially through meta‐analysis studies. This collection also highlights different sort of errors in published works (e.g., wrong coordinates, sample type, material, spelling).
- 8 August 2022
- Published by Wiley in Molecular Ecology Resources
- Vol. 23 (1) , 222-232
FreshOmics: A manually curated and standardized –omics database for investigating freshwater microbiomes
Freshwater is a critical resource for human survival but severely threatened by anthropogenic activities and climate change. These changes strongly impact the abundance and diversity of the microbial communities which are key players in the functioning of these aquatic ecosystems. Although widely documented since the emergence of high‐throughput sequencing approaches, the information on these natural microbial communities is scattered among thousands of publications and it is therefore difficult to investigate the temporal dynamics and the spatial distribution of microbial taxa within or across ecosystems. To fill this gap and in the FAIR principles context we built a manually curated and standardized microbial freshwater –omics database (FreshOmics). Based on recognized ontologies (ENVO, MIMICS, GO, ISO), FreshOmics describes 29 different types of freshwater ecosystems and uses standardized attributes to depict biological samples, sequencing protocols and article attributes for more than 2487 geographical locations across 71 countries around the world. The database contains 24,808 sequence identifiers (i.e., Run_Id / Exp_ID, mainly from SRA/DDBJ SRA/ENA, GSA and MG‐RAST repositories) covering all sequence‐based ‐omics approaches used to investigate bacteria, archaea, microbial eukaryotes, and viruses. Therefore, FreshOmics allows accurate and comprehensive analyses of microbial communities to answer questions related to their roles in freshwater ecosystems functioning and resilience, especially through meta‐analysis studies. This collection also highlights different sort of errors in published works (e.g., wrong coordinates, sample type, material, spelling).