Dynamic PhD candidate in Microbial Ecology at the University of Reims Champagne-Ardenne, building on research experience at NIOO (Striga–sorghum–microbiome ecology), EIAR (plant–microbe interactions), and now focusing on metataxonomic and shotgun metagenomic analyses in viticulture. Skilled in combining molecular techniques, bioinformatics, and greenhouse assays to identify key microbial taxa and develop biocontrol solutions for sustainable agriculture.
Metataxonomic investigations of Champagne grapevine microbiome (soil, rhizosphere, phyllosphere, Carposphere):
· Sampling from different plant compartments and vineyard environments.
· DNA extraction and quality control.
· Amplicon sequencing (16S rRNA for bacteria, ITS for fungi) using Illumina platforms.
· Bioinformatics processing (quality filtering, OTU/ASV clustering, taxonomy assignment, diversity and differential abundance analysis).
· Network and co-occurrence analysis to reveal keystone taxa.
Shotgun metagenomics studies to complement amplicon data:
· DNA library preparation and whole-metagenome sequencing.
· Assembly, annotation, and functional gene prediction.
· Taxonomic and functional analysis to identify species and functional traits associated with grapevine health and disease suppression.
Microbiome-driven BCA development:
· Identification of microbial taxa with central ecological roles and potential antagonistic functions against Plasmopara viticola.
· Guided isolation of candidate microbes, focusing on Bacillus spp. and other promising taxa.
· Characterization and identification of isolates through morphology, biochemical tests, and molecular sequencing.
In vitro and greenhouse screening of BCAs:
· Antagonistic assays against P. viticolazoospores.
· Testing both single strains and microbial consortia.
· Evaluating plant protection effects in planta under controlled greenhouse conditions.
Mode of action studies:
· Direct inhibition of P. viticolazoospores.
· Indirect inhibition through induced systemic resistance (ISR) in grapevine.
Molecular plant–pathogen interaction studies:
· qPCR assays for monitoring grapevine defense gene expression after BCA application.
· Digital droplet PCR (ddPCR) for precise quantification of Plasmopara viticola biomass in infected plant tissues.
Integration of multi-omics and experimental data:
· Correlating metataxonomic and metagenomic findings with experimental BCA performance.
· Linking microbial community structure and function to pathogen suppression mechanisms.
· Establishing a framework for targeted BCA development in sustainable viticulture.
Focus on Plant–Microbe Interaction Research Activities including the following subjects:
· Microbiome investigations in the sorghum rhizosphere to study the tripartite interaction between Striga hermonthica, mycorrhizal fungi, and sorghum.
· In vitro assays to evaluate microbial effects on Striga seed germination, haustorium formation, and attachment to sorghum roots.
· Volatile-mediated suppression studies: analysis of microbial and plant volatile organic compounds (VOCs) in regulating Striga seed germination and early parasitic development.
· Root exudate modification assays: testing chemical and microbial treatments that alter sorghum root exudate composition to suppress Striga germination and haustorium initiation.
· Greenhouse infection assays for Striga–sorghum interactions:
· Establishment and management of infection assays (watering, thinning, nutrient management using Hoagland solution).
· Quantifying Striga emergence and attachment on sorghum roots.
· Biocontrol candidate (BCA) screening and evaluation:
· Collection and preparation of fungal spores and beneficial microbial inocula.
· Pathogenicity tests of microbial isolates against Striga attachment on sorghum.
· Screening of microbial isolates and consortia for growth-promoting and Striga-suppressing potential in controlled conditions.
· Soil and microbial enzyme studies related to Striga–sorghum interactions: quantitative and qualitative assessment of microbial enzyme activity, protein estimation, and metabolite profiling.
· Innovative fertiliser solutions and microbial formulations aimed at reducing Striga infestation in sorghum fields.
· Pathogen–parasite–host interaction studies:
· Exploring the effect of Fusarium spp. and other antagonists on Striga germination and attachment.
· Identification of microbial phenotypes in vitro with activity against Striga and their role in shaping the sorghum rhizosphere
Focus on Plant–Microbe Interaction Research Activities including the following subjects:
· Sorghum microbiome and plant growth studies:
· Investigating sorghum rhizosphere microbiome structure and its role in nutrient uptake and stress tolerance.
· Functional analysis of plant growth–promoting endophytes and rhizobacteria to enhance sorghum growth and resilience.
· Effects of phytobeneficial soil microbes on nutrient acquisition and stress tolerance in sorghum and finger millet under low-input sustainable agriculture systems.
· Bt cry gene characterization:
· Molecular characterization of Bt cry genes.
· Evaluating their impact on bollworm growth and development in cotton.
· Microbial enzymes, metabolites, and proteins:
· Investigating microbial enzyme activity, protein estimation, and metabolite profiling.
· Characterizing microbial enzymes, secondary metabolites, and proteins involved in biosynthetic pathways and signaling.
· Studying microbial–entomopathogen symbiosis interactions.
· Soil organic matter and carbon dynamics:
· Characterization of soil organic matter composition and functional role in ecosystem services.
· Identifying signatures of soil core microbiome and its interaction with host plants.
· Phytobeneficial microorganisms and soil engineering:
· Application of plant-beneficial microbes for sustainable agriculture and soil engineering.
· Screening of microbial isolates for plant growth–promoting and weed-suppressive traits.
· Novel microbial resources from diverse environments:
· Exploring extremophilic environments (forests, wetlands, volcanic areas, hot springs, and water bodies) in Ethiopia for the discovery of novel microbial products.
· Identifying microbial isolates with antimicrobial activity against plant pathogens.
· Molecular characterization of novel rhizobia from Ethiopian legumes for biofertilizer development.
· Molecular plant–pathogen studies:
· Genetic diversity analysis of Xanthomonas campestris pv. musacearum (XCM) isolates from enset production areas.
· Development of microbial secondary metabolite–based BCAs against African fall armyworm (FAW).
Molecular & Microbial Techniques
DNA/RNA extraction (soil, rhizosphere, phyllosphere, endosphere, plant tissue, pathogens)
PCR, qPCR, and digital droplet PCR (ddPCR) for gene expression and pathogen quantification
Amplicon library preparation (16S rRNA, ITS) for metataxonomics
Shotgun metagenome library preparation and QC
Isolation, culturing, and characterization techniques
Greenhouse and in planta assays and microbial formulation
Bioinformatics & Computational Analysis
Metataxonomic data analysis:
QIIME2, DADA2, USEARCH, mothur for quality filtering, ASV/OTU clustering, taxonomy assignment
Diversity analysis (alpha, beta, differential abundance, community composition)
Metagenomic & functional annotation:
Assembly (MEGAHIT, SPAdes)
Gene prediction and annotation (EggNOG, KEGG, COGs, CAZy, VFDB, PHI)
Metabolic pathway reconstruction and visualization (KEGG Mapper, iPATH)
Microbial community ecology:
Co-occurrence network analysis (igraph in R)
Multivariate statistics for microbiome-environment interactions (R: vegan, phyloseq, microbiomeSeq, MicroViz)
Data Science, Statistical & Visualization Tools
Programming & scripting: R, Python, Bash for data wrangling, statistics, and visualization
Statistical analysis: R packages (vegan, phyloseq, ade4, lme4, ggplot2), Python (pandas, scikit-bio, matplotlib)
Network & functional visualization: Cytoscape, Gephi, iTOL, MicrobiomeAnalyst
Quantitative ecology & data integration: ordination (PCA, PCoA, NMDS), PERMANOVA, correlation & regression models
Software & Platforms
Bioinformatics pipelines: QIIME2, DADA2, mothur, USEARCH, MetaPhlAn, Kraken2, Bracken, Galaxy
Functional annotation & databases: EggNOG-mapper, KEGG, Pfam, InterPro, CAZy, MetaCyc
Metagenomics assembly & analysis: MEGAHIT, GTDB-Tk