Statistical approach of functional profiling for a microbial community

Differences in Precipitation Regime Shape Microbial Community Composition and Functional Potential in Namib Desert Soils

Precipitation is one of the major constraints influencing the diversity, structure, and activity of soil microbial communities in desert ecosystems. However, the effect of changes in precipitation on soil microbial communities in arid soil microbiomes remains unresolved. In this study, using 16S rRNA gene high-throughput sequencing and shotgun metagenome sequencing, we explored changes in taxonomic composition and functional potential across two zones in the Namib Desert with contrasting precipitation regime. We found that precipitation regime had no effect on taxonomic and functional alpha-diversity, but that microbial community composition and functional potential (beta-diversity) changed with increased precipitation. For instance, Acidobacteriota and 'resistance to antibiotics and toxic compounds' related genes were relatively more abundant in the high-rainfall zone. These changes were largely due to a small set of microbial taxa, some of which were present in low abundance (i.e. members of the rare biosphere). Overall, these results indicate that key climatic factors (i.e. precipitation) shape the taxonomic and functional attributes of the arid soil microbiome. This research provides insight into how changes in precipitation patterns associated with global climate change may impact microbial community structure and function in desert soils.

Environmental genes and genomes: understanding the differences and challenges in the approaches and software for their analyses

DNA-based taxonomic and functional profiling is widely used for the characterization of organismal communities across a rapidly increasing array of research areas that include the role of microbiomes in health and disease, biomonitoring, and estimation of both microbial and metazoan species richness. Two principal approaches are currently used to assign taxonomy to DNA sequences: DNA metabarcoding and metagenomics. When initially developed, each of these approaches mandated their own particular methods for data analysis; however, with the development of high-throughput sequencing (HTS) techniques they have begun to share many aspects in data set generation and processing. In this review we aim to define the current characteristics, goals and boundaries of each field, and describe the different software used for their analysis. We argue that an appreciation of the potential and limitations of each method can help underscore the improvements required by each field so as to better exploit the richness of current HTS-based data sets.