GeoChip-based analysis of metabolic diversity of microbial communities at the Juan de Fuca Ridge hydrothermal vent

Abstract

Deep-sea hydrothermal vents are one of the most unique and fascinating ecosystems on Earth. Although phylogenetic diversity of vent communities has been extensively examined, their physiological diversity is poorly understood. In this study, a GeoChip-based, high-throughput metagenomics technology revealed dramatic differences in microbial metabolic functions in a newly grown protochimney (inner section, Proto-I; outer section, Proto-O) and the outer section of a mature chimney (4143-1) at the Juan de Fuca Ridge. Very limited numbers of functional genes were detected in Proto-I (113 genes), whereas much higher numbers of genes were detected in Proto-O (504 genes) and 4143-1 (5,414 genes). Microbial functional genes/populations in Proto-O and Proto-I were substantially different (around 1% common genes), suggesting a rapid change in the microbial community composition during the growth of the chimney. Previously retrieved cbbL and cbbM genes involved in the Calvin Benson Bassham (CBB) cycle from deep-sea hydrothermal vents were predominant in Proto-O and 4143-1, whereas photosynthetic green-like cbbL genes were the major components in Proto-I. In addition, genes involved in methanogenesis, aerobic and anaerobic methane oxidation (e.g., ANME1 and ANME2), nitrification, denitrification, sulfate reduction, degradation of complex carbon substrates, and metal resistance were also detected. Clone libraries supported the GeoChip results but were less effective than the microarray in delineating microbial populations of low biomass. Overall, these results suggest that the hydrothermal microbial communities are metabolically and physiologically highly diverse, and the communities appear to be undergoing rapid dynamic succession and adaptation in response to the steep temperature and chemical gradients across the chimney.

Fig. 1.

Proportion of functional gene categories detected. The percentages were calculated by dividing the total signal intensity values of each gene group by total signal intensity values of all genes detected on the array.

Fig. 2.

Rubisco genes detected in the samples. (A) Phylogenetic tree based on the RubisCO large-subunit amino acid sequences obtained by GeoChip hybridization. Tree topography and evolutionary distance are given by a neighbor-joining method with Kimura distances. This tree is unrooted, with 1,000 replicates of bootstrapping. Bootstrap values are indicated only at major nodes of the tree. The designation of different colors is as follows: Red indicates unique sequences in Proto-I (4 genes), and dark red signifies the single sequence discovered in both Proto-I and 4143-1; blue designates the common sequences from both Proto-O and 4143-1 (10 genes); and black indicates the unique sequences found in 4143-1. All genes detected in Proto-I and Proto-O are listed here, but only the genes with signal intensities greater than 1 from 4143-1 were included in the tree. All genes found in Proto-O could be found in 4143-1. (Scale bar: 0.1 substitutions per site.) (B) Percentage of different types of rbcL genes detected in 4143-1.