OPUS: MCS Synthesis of longitudinal '-omics' research of microbial communities in Hudson River Valley freshwater streams

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Bacterial contamination of surface waters is an important issue nationwide. There is a critical need to understand the source and persistence of this pollution to protect our Nation's freshwater resources. The purpose of this OPUS:MCS grant is to enable a new synthesis of ongoing research on this topic by a mid-career scientist at Dominican College of Blauvelt. This will be facilitated through partnership with a colleague at the University of Massachusetts to gain new capabilities to enhance the PI's research productivity and teaching repertoire. For a number of years, the PI's undergraduate students at Dominican College have been involved in collection and characterization of microbiome samples from various streams in the Hudson River watershed with the goal of identifying sources of organic pollution. The objective of this project is to synthesize these datasets to more clearly understand microbial distribution patterns, especially in relationship to headwater location, local weather and climate. Additional datasets will be analyzed to better understand dynamic fluctuations in community structure and function at selected sites. Training of students in computational genomics while synthesizing these data will garner them more opportunities when entering the STEM workforce. Dissemination of this work includes the creation of training workshops for interested citizen science groups concerned about their own communities, and making genomic data available via a public database. This project will explore the use of advanced methodologies to elucidate the nature of microbial communities in surface waters of creeks and streams in the Hudson River watershed. Data derived from next-generation meta-genomic and -transcriptomic sequencing will enable researchers to examine the overall vitality and stability of these streams, providing baseline information by which impacts related to further pollution and environmental change can be measured. By integrating community profiling and meta-'omics data of samples derived from a polluted freshwater creek, the results will inform local water keeper and citizen science groups as they document water quality and develop more reliable methods by which to locate contamination sources. Genomic and expression data derived from microbiome communities in sediment and water from Sparkill Creek will be used to determine the nature and impact of the contamination. These analyses have the potential to identify problems regarding sources and sinks of microbial pollution, and assess the utility of this type of comparative analysis in elucidating unseen problems.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.