ABSTRACT
Networks of engineered waterways are critical in meeting the growing water demands in megacities. To capture and treat rainwater in an energy-efficient manner, approaches can be developed for such networks that use ecological services from microbial communities. Traditionally, engineered waterways were regarded as homogeneous systems with little responsiveness of ecological communities and ensuing processes. This study provides ecogenomics-derived key information to explain the complexity of urban aquatic ecosystems in well-managed watersheds with densely interspersed land-use patterns. Overall, sedimentary microbial communities had higher richness and evenness compared to the suspended communities in water phase. On the basis of PERMANOVA analysis, variation in structure and functions of microbial communities over space within same land-use type was not significant. In contrast, this difference was significant between different land-use types, which had similar chemical profiles. Of the 36 environmental parameters from spatial analysis, only three metals, namely potassium, copper and aluminum significantly explained between 7% and 11% of the variation in taxa and functions, based on distance-based linear models (DistLM). The ecogenomics approach adopted here allows the identification of key drivers of microbial communities and their functions at watershed-scale. These findings can be used to enhance microbial services, which are critical to develop ecologically friendly waterways in rapidly urbanizing environments.
Subject(s)
Metals/analysis , Water Microbiology , Water Pollutants, Chemical/analysis , Bacteria/classification , Bacteria/genetics , Bacteria/isolation & purification , Biodiversity , Cities , DNA, Bacterial/analysis , Ecosystem , Genomics , Urbanization , Water SupplyABSTRACT
SUMMARY: Data processing, analysis and visualization (datPAV) is an exploratory tool that allows experimentalist to quickly assess the general characteristics of the data. This platform-independent software is designed as a generic tool to process and visualize data matrices. This tool explores organization of the data, detect errors and support basic statistical analyses. Processed data can be reused whereby different step-by-step data processing/analysis workflows can be created to carry out detailed investigation. The visualization option provides publication-ready graphics. Applications of this tool are demonstrated at the web site for three cases of metabolomics, environmental and hydrodynamic data analysis. AVAILABILITY: datPAV is available free for academic use at http://www.sdwa.nus.edu.sg/datPAV/.
Subject(s)
Computer Graphics , Software , Metabolomics , User-Computer Interface , WorkflowABSTRACT
SUMMARY: Analysis of high throughput metabolomics experiments is a resource-intensive process that includes pre-processing, pre-treatment and post-processing at each level of experimental hierarchy. We developed an interactive user-friendly online software called Metabolite Data Analysis Tool (MetDAT) for mass spectrometry data. It offers a pipeline of tools for file handling, data pre-processing, univariate and multivariate statistical analyses, database searching and pathway mapping. Outputs are produced in the form of text and high-quality images in real-time. MetDAT allows users to combine data management and experiment-centric workflows for optimization of metabolomics methods and metabolite analysis. AVAILABILITY: MetDAT is available free for academic use from http://smbl.nus.edu.sg/METDAT2/. CONTACT: sanjay@nus.edu.sg
