Bacterial community diversity in the tomato phyllosphere
Bacterial community diversity and variation in spray water sources and the tomato phyllosphere
Tomato (Solanum lycopersicum) consumption has been one of the most common causes of produce-associated salmonellosis in the United States. Contamination may originate from animal waste, insects, soil or water. Current guidelines for fresh tomato production recommend the use of potable water for applications coming in direct contact with the fruit, but due to high demand, water from other sources is frequently used. We sought to describe the overall bacterial diversity on the surface of tomato fruit and the effect of two different water sources (ground and surface water) when used for direct crop applications by generating a 454-pyrosequencing 16S rRNA dataset of these different environments. This study represents the first in depth characterization of bacterial communities in the tomato phyllosphere and the water sources commonly used in commercial vegetable production.    The two water sources tested had a significantly different bacterial composition. Proteobacteria was predominant in groundwater samples, whereas in the significantly more diverse surface water, abundant phyla also included Firmicutes, Actinobacteria and Verrucomicrobia. The phyllosphere bacterial communities on tomatoes sprayed with both water sources could not be differentiated using various statistical methods. Both phyllosphere environments had a high representation of Gammaproteobacteria, and within this class the genera Pantoea and Enterobacter were the most abundant.    Despite the major differences observed in the bacterial composition of ground and surface water, the season long use of these very different water sources did not have a significant impact on the bacterial composition of the tomato phyllosphere. This study has provided the first next-generation sequencing database describing the bacterial communities living in the phyllosphere of a tomato crop under two different spray water regimes, and therefore represents an important step forward towards the development of science-based metrics for Good Agricultural Practices.