bioRxiv Science⌕ Search

Biology subjects

Wasimuddin, W.

Publications and source records attributed to Wasimuddin, W..

2 recordsLinked to original sources

Component specific responses of the microbiomes to common chemical stressors in the human food chain

Along a food chain, microbiomes occur in each component and often contribute to the functioning or the health of their host or environment. One Health emphasizes the connectivity of each components health. Chemical stress typically causes dysbiotic microbiomes, but it remains unclear whether chemical stressors consistently affect the microbiomes along food chain components. Here, we systematically challenged a model food chain, including water, sediments, soil, plants, and animals, with three chemical stresses consisting of arsenic (a toxic trace element), benzoxazinoids (an abundant bioactive plant metabolites), and terbuthylazine (an herbicide typically found along a human food chain). The analysis of 1,064 microbiome profiles for commonalities and differences in their stress responses indicated that chemical stressors decreased microbiome diversity in soil and animal, but not in the other microbiomes. In response to stress, all food chain communities strongly shifted in their composition, generally becoming compositionally more similar to each other. In addition, we observed stochastic effects in host-associated communities (plant, animal). Dysbiotic microbiomes were characterized by different sets of bacteria, which responded specifically to the three chemical stressors. Microbial co-occurrence patterns significantly shifted with either decreased (water, sediment, plant, animal) or increased (soil) network sparsity and numbers of keystone taxa following stress treatments. This suggested major re-distribution of the roles that specific taxa may have, with the community stability of plant and animal microbiomes being the most affected by chemical stresses. Overall, we observed stress- and component-specific responses to chemical stressors in microbiomes along the model food chain, which could have implications on food chain health.

microbiology↗

Evaluation of primer pairs for microbiome profiling across a food chain from soils to humans within the One Health framework

The "One Health" framework emphasizes the ecological relationships between soil, plant, animal and human health. Microbiomes play important roles in these relationships, as they modify the health and performance of the different compartments and influence the transfer of energy, matter and chemicals between them. Standardized methods to characterize microbiomes along food chains are, however, currently lacking. To address this methodological gap, we evaluated the performance of DNA extractions kits and commonly recommended primer pairs targeting different hypervariable regions (V3-V4, V4, V5-V6, V5-V6-V7) of the 16S rRNA gene, on microbiome samples along a model food chain, including soils, maize roots, cattle rumen, and cattle and human faeces. We also included faeces from gnotobiotic mice colonized with defined bacterial taxa and mock communities to confirm the robustness of our molecular and bioinformatic approaches on these defined low microbial diversity samples. Based on Amplicon Sequence Variants, the primer pair 515F-806R led to the highest estimates of species richness and diversity in all sample types and offered maximum diversity coverage of reference databases in in silico primer analysis. The influence of the DNA extraction kits was negligible compared to the influence of the choice of primer pairs. Comparing microbiomes using 515F-806R revealed that soil and root samples have the highest estimates of species richness and inter-sample variation. Species richness decreased gradually along the food chain, with the lowest richness observed in human faeces. Primer pair choice directly influenced the estimation of community changes (beta diversity) within and across compartments and may give rise to preferential detection of specific taxa. This work demonstrates why a standardized approach is necessary to analyse microbiomes within and between source compartments along food chains in the context of the One Health framework.

microbiology↗