Correlation between microbial communities and volatile organic compounds in an urban soil provides clues on soil quality towards sustainability of city flowerbeds.

Soil functionality is critical to the biosphere as it provides ecosystem services relevant for a healthy planet. The soil microbial composition is significantly impacted by anthropogenic activities, including urbanization. In this context, the study of soil microorganisms associated to urban green spaces has started to be crucial toward sustainable city development. Microbes living in the soil produce and degrade volatile organic compounds (VOCs). The VOC profiles may be used to distinguish between soils with various characteristics and management practices, reflecting variations in the activity of soil microbes that use a variety of metabolic pathways. Here, a combined approach based on DNA metabarcoding and GC-MS analysis was used to evaluate the soil quality from urban flowerbeds in Prato (Tuscany, Italy) in terms of microbial biodiversity and VOC emission profiles, with the final aim of evaluating the possible correlation between composition of microbial community and VOC patterns. Results showed that VOCs in the considered soil originated from anthropic and biological activity, and significant correlations between specific microbial taxa and VOCs were detected. Overall, the study demonstrated the feasibility of the use of microbe-VOC correlation as a proxy for soil quality assessment in urban soils.

Genotype Combinations Drive Variability in the Microbiome Configuration of the Rhizosphere of Maize/Bean Intercropping System.

In an intercropping system, the interplay between cereals and legumes, which is strongly driven by the 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 bean (Phaseolus vulgaris L., Phaseolus coccineus L.) genotype combinations. Through amplicon sequencing of bacterial 16S rRNA genes from rhizosphere samples, our results unveil that the 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 enhances community complexity. Nevertheless, combinations of maize and bean 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.

Structural Refinement by Direct Mapping Reveals Assembly Inconsistencies near Hi-C Junctions.

High-throughput chromosome conformation capture (Hi-C) is widely used for scaffolding in de novo assembly because it produces highly contiguous genomes, but its indirect statistical approach can introduce connection errors. We employed optical mapping (Bionano Genomics) as an orthogonal scaffolding technology to assess the structural solidity of Hi-C reconstructed scaffolds. Optical maps were used to assess the correctness of five de novo genome assemblies based on long-read sequencing for contig generation and Hi-C for scaffolding. Hundreds of inconsistencies were found between the reconstructions generated using the Hi-C and optical mapping approaches. Manual inspection, exploiting raw long-read sequencing data and optical maps, confirmed that several of these conflicts were derived from Hi-C joining errors. Such misjoins were widespread, involved the connection of both small and large contigs, and even overlapped annotated genes. We conclude that the integration of optical mapping data after, not before, Hi-C-based scaffolding, improves the quality of the assembly and limits reconstruction errors by highlighting misjoins that can then be subjected to further investigation.