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Biology subjects

Carta, G.

Publications and source records attributed to Carta, G..

2 recordsLinked to original sources

Genotype combinations drive variability in the microbiome configuration of the rhizosphere of Maize/Bean intercropping system

In intercropping system, the interplay between cereals and legumes, which is strongly driven by complementarity of below-ground structures and their interactions with the soil microbiome, raises a fundamental query: Can different genotypes alter the configuration of the rhizosphere microbial communities? To address this issue, we conducted a field study, probing the effects of intercropping and diverse maize (Zea mays L.) and beans (Phaseolus vulgaris L., Phaseolus coccineus L.) genotype combinations. Our results unveil that intercropping condition alters the rhizosphere bacterial communities, but that the degree of this impact is substantially affected by specific genotype combinations. Overall, intercropping allows the recruitment of exclusive bacterial species and enhance community complexity. Nevertheless, combinations of maize and beans genotypes determine two distinct groups characterized by higher or lower bacterial community diversity and complexity, which are influenced by the specific bean line associated. Moreover, intercropped maize lines exhibit varying propensities in recruiting bacterial members with more responsive lines showing preferential interactions with specific microorganisms. Our study conclusively shows that genotype has an impact on the rhizosphere microbiome and that a careful selection of genotype combinations for both species involved is essential to achieve compatibility optimization in intercropping.

plant biology↗

Expanding the Characterization of Microbial Ecosystems using DIA-PASEF Metaproteomics

Metaproteomics is gaining momentum in microbiome research due to the multi-dimensional information it provides. However, current approaches have reached their detection limits. We present a highly-sensitive metaproteomic workflow using the extra information captured by Parallel Accumulation-Serial Fragmentation (PASEF) technology. The comparison of different acquisition modes and data analysis software packages showed that DIA-PASEF and DIA-NN doubled protein identifications of mouse gut microbiota and, importantly, also of the host proteome. DIA-PASEF significantly improved peptide detection reproducibility and quantification accuracy, which resulted in more than twofold identified taxa, reaching depths comparable to metagenomic studies. Consequently, DIA-PASEF exhibited improved coverage of functional networks revealing 131 additional pathways compared to DDA-PASEF. We applied our optimized workflow to a pre-clinical mouse model of chronic pain, in which we deciphered novel host-microbiome interactions. In summary, we present here a metaproteomic approach that paves the way for increasing the functional characterization of microbiome ecosystems and is applicable to diverse fields of biological research.

microbiology↗