Characterization of Coastal Urban Watershed Bacterial Communities Leads to Alternative Community-Based Indicators

BACKGROUND: Microbial communities in aquatic environments are spatially and temporally dynamic due to environmental fluctuations and varied external input sources. A large percentage of the urban watersheds in the United States are affected by fecal pollution, including human pathogens, thus warranting comprehensive monitoring. METHODOLOGY/PRINCIPAL FINDINGS: Using a high-density microarray (PhyloChip), we examined water column bacterial community DNA extracted from two connecting urban watersheds, elucidating variable and stable bacterial subpopulations over a 3-day period and community composition profiles that were distinct to fecal and non-fecal sources. Two approaches were used for indication of fecal influence. The first approach utilized similarity of 503 operational taxonomic units (OTUs) common to all fecal samples analyzed in this study with the watershed samples as an index of fecal pollution. A majority of the 503 OTUs were found in the phyla Firmicutes, Proteobacteria, Bacteroidetes, and Actinobacteria. The second approach incorporated relative richness of 4 bacterial classes (Bacilli, Bacteroidetes, Clostridia and alpha-proteobacteria) found to have the highest variance in fecal and non-fecal samples. The ratio of these 4 classes (BBC:A) from the watershed samples demonstrated a trend where bacterial communities from gut and sewage sources had higher ratios than from sources not impacted by fecal material. This trend was also observed in the 124 bacterial communities from previously published and unpublished sequencing or PhyloChip- analyzed studies. CONCLUSIONS/SIGNIFICANCE: This study provided a detailed characterization of bacterial community variability during dry weather across a 3-day period in two urban watersheds. The comparative analysis of watershed community composition resulted in alternative community-based indicators that could be useful for assessing ecosystem health

Phylogenetic and functional marker genes to study ammonia-oxidizing microorganisms (AOM) in the environment

The oxidation of ammonia plays a significant role in the transformation of fixed nitrogen in the global nitrogen cycle. Autotrophic ammonia oxidation is known in three groups of microorganisms. Aerobic ammonia-oxidizing bacteria and archaea convert ammonia into nitrite during nitrification. Anaerobic ammonia-oxidizing bacteria (anammox) oxidize ammonia using nitrite as electron acceptor and producing atmospheric dinitrogen. The isolation and cultivation of all three groups in the laboratory are quite problematic due to their slow growth rates, poor growth yields, unpredictable lag phases, and sensitivity to certain organic compounds. Culture-independent approaches have contributed importantly to our understanding of the diversity and distribution of these microorganisms in the environment. In this review, we present an overview of approaches that have been used for the molecular study of ammonia oxidizers and discuss their application in different environments

Achievements and new knowledge unraveled by metagenomic approaches

Metagenomics has paved the way for cultivation-independent assessment and exploitation of microbial communities present in complex ecosystems. In recent years, significant progress has been made in this research area. A major breakthrough was the improvement and development of high-throughput next-generation sequencing technologies. The application of these technologies resulted in the generation of large datasets derived from various environments such as soil and ocean water. The analyses of these datasets opened a window into the enormous phylogenetic and metabolic diversity of microbial communities living in a variety of ecosystems. In this way, structure, functions, and interactions of microbial communities were elucidated. Metagenomics has proven to be a powerful tool for the recovery of novel biomolecules. In most cases, functional metagenomics comprising construction and screening of complex metagenomic DNA libraries has been applied to isolate new enzymes and drugs of industrial importance. For this purpose, several novel and improved screening strategies that allow efficient screening of large collections of clones harboring metagenomes have been introduced