The quantification and identification of new plasmid-acquiring bacteria in representative mating conditions is critical to characterize the risk of horizontal gene transfer in the environment. This study aimed to quantify conjugation events resulting from manure application to soils and identify the transconjugants resulting from these events. Conjugation was quantified at multiple time points by plating and flow cytometry, and the transconjugants were recovered by fluorescence-activated cell sorting and identified by 16S rRNA sequencing. Overall, transconjugants were only observed within the first 4 days after manure application and at values close to the detection limits of this experimental system (1.00–2.49 log CFU/g of manured soil, ranging between 10–5 and 10–4 transconjugants-to-donor ratios). In the pool of recovered transconjugants, we found amplicon sequence variants (ASVs) of genera whose origin was traced to soils (Bacillus and Nocardioides) and manure (Comamonas and Rahnella). This work showed that gene transfer from fecal to soil bacteria occurred despite the less-than-optimal conditions faced by manure bacteria when transferred to soils, but these events were rare, mainly happened shortly after manure application, and the plasmid did not colonize the soil community. This study provides important information to determine the risks of AMR spread via manure application.
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Eight new primer sets were designed for PCR detection of (i) mono-oxygenase and dioxygenase gene sequences involved in initial attack of bacterial aerobic BTEX degradation and of (ii) catechol 2,3-dioxygenase gene sequences responsible for meta-cleavage of the aromatic ring. The new primer sets allowed detection of the corresponding genotypes in soil with a detection limit of 10(3)-10(4) or 10(5)-10(6) gene copies g(-1) soil, assuming one copy of the gene per cell. The primer sets were used in PCR to assess the distribution of the catabolic genes in BTEX degrading bacterial strains and DNA extracts isolated from soils sampled from different locations and depths (vadose, capillary fringe and saturated zone) within a BTEX contaminated site. In both soil DNA and the isolates, tmoA-, xylM- and xylE1-like genes were the most frequently recovered BTEX catabolic genes. xylM and xylE1 were only recovered from material from the contaminated samples while tmoA was detected in material from both the contaminated and non-contaminated samples. The isolates, mainly obtained from the contaminated locations, belonged to the Actinobacteria or Proteobacteria (mainly Pseudomonas). The ability to degrade benzene was the most common BTEX degradation phenotype among them and its distribution was largely congruent with the distribution of the tmoA-like genotype. The presence of tmoA and xylM genes in phylogenetically distant strains indicated the occurrence of horizontal transfer of BTEX catabolic genes in the aquifer. Overall, these results show spatial variation in the composition of the BTEX degradation genes and hence in the type of BTEX degradation activity and pathway, at the examined site. They indicate that bacteria carrying specific pathways and primarily carrying tmoA/xylM/xylE1 genotypes, are being selected upon BTEX contamination.
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Background: Profiling the plant root architecture is vital for selecting resilient crops that can efficiently take up water and nutrients. The high-performance imaging tools available to study root-growth dynamics with the optimal resolution are costly and stationary. In addition, performing nondestructive high-throughput phenotyping to extract the structural and morphological features of roots remains challenging. Results: We developed the MultipleXLab: a modular, mobile, and cost-effective setup to tackle these limitations. The system can continuously monitor thousands of seeds from germination to root development based on a conventional camera attached to a motorized multiaxis-rotational stage and custom-built 3D-printed plate holder with integrated light-emitting diode lighting. We also developed an image segmentation model based on deep learning that allows the users to analyze the data automatically. We tested the MultipleXLab to monitor seed germination and root growth of Arabidopsis developmental, cell cycle, and auxin transport mutants non-invasively at high-throughput and showed that the system provides robust data and allows precise evaluation of germination index and hourly growth rate between mutants. Conclusion: MultipleXLab provides a flexible and user-friendly root phenotyping platform that is an attractive mobile alternative to high-end imaging platforms and stationary growth chambers. It can be used in numerous applications by plant biologists, the seed industry, crop scientists, and breeding companies.
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