Prokaryotic Diversity in the Rhizosphere of Organic, Intensive, and Transitional Coffee Farms in Brazil

Abstract

Despite a continuous rise in consumption of coffee over the past 60 years and recent studies showing positive benefits linked to human health, intensive coffee farming practices have been associated with environmental damage, risks to human health, and reductions in biodiversity. In contrast, organic farming has become an increasingly popular alternative, with both environmental and health benefits. This study aimed to characterize and determine the differences in the prokaryotic soil microbiology of three Brazilian coffee farms: one practicing intensive farming, one practicing organic farming, and one undergoing a transition from intensive to organic practices. Soil samples were collected from 20 coffee plant rhizospheres (soil directly influenced by the plant root exudates) and 10 control sites (soil 5 m away from the coffee plantation) at each of the three farms for a total of 90 samples. Profiling of 16S rRNA gene V4 regions revealed high levels of prokaryotic diversity in all three farms, with thousands of species level operational taxonomic units identified in each farm. Additionally, a statistically significant difference was found between each farm’s coffee rhizosphere microbiome, as well as between coffee rhizosphere soils and control soils. Two groups of prokaryotes associated with the nitrogen cycle, the archaeal genus Candidatus Nitrososphaera and the bacterial order Rhizobiales were found to be abundant and statistically different in composition between the three farms and in inverse relationship to each other. Many of the nitrogen-fixing genera known to enhance plant growth were found in low numbers (e.g. Rhizobium, Agrobacter, Acetobacter, Rhodospirillum, Azospirillum), but the families in which they belong had some of the highest relative abundance in the dataset, suggesting many new groups may exist in these samples that can be further studied as potential plant growth-promoting bacteria to improve coffee production while diminishing negative environmental impacts.

Looking for Rhizobacterial Ecological Indicators in Agricultural Soils Using 16S rRNA metagenomic Amplicon Data

“…Other authors have reported similar changes associated to tillage and crop rotation/succession [12]; larger abundance of Actinobacteria in suppressive soils with greater changes after the addition of fungal pathogens [4]; long term fertilization and intensive herbivory plus mowing in grasslands [34]; intensive coffee farming [14]; desert versus cultivated soil [35]; and different depths of permafrost soil samples [36]. …”

“…The rhizobacterial community symbiotically adapts to specific substances secreted by the crop being cultivated. Bacterial diversity and soil health can be adversely affected by stresses throughout the cultivation periods [5], increased salinity [7], acidity [8,9], soil composition and climate changes [10,11], tillage [12,13], cultivation methods [14], pesticides and heavy metals[15]. Proper soil management strategies can reduce negative effects and restore the balance in the soil bacterial ecosystem, increasing soil health.…”

“…Proper soil management strategies can reduce negative effects and restore the balance in the soil bacterial ecosystem, increasing soil health. Organic farming may overcome or reduce these effects [5], although it may reduce yield as much as 20% [14]. Balanced fertilization has also been found to increase soil biomass and activity [16].…”

“…NGS studies have shown that soil diversity is far greater than originally expected, in the order of several thousand species [14,15]. Sequences can be assigned to known taxa using a variety of methods, although typically, a large fraction (~30%) of the sequences collected cannot be ascribed to any known taxa .…”

Barcoding the food chain: from Sanger to high-throughput sequencing

“…In the context of agro-ecosystems, these techniques could supplement studies of the ecological impacts of agriculture on species diversity, such as the impacts of run-off into adjacent waterways. eDNA could similarly be extracted from soil to monitor the diversity of soil-dwelling invertebrates, fungi and bacteria (Orgiazzi et al 2015), which are all affected by ongoing agricultural activity (Caldwell et al 2015), but are also linked to ecosystem functioning (Bender et al 2016).…”