NEW YORK (GenomeWeb News) – Metatranscriptomics can detect known and previously unrecognized small RNAs in ocean microbial communities, according to a new paper appearing online today in Nature.
A team of researchers from the Massachusetts Institute of Technology sampled microbial communities from four different ocean depths at a sampling station near Hawaii, using pyrosequencing to find transcripts within each community. After throwing out known coding and ribosomal RNA sequences, the researchers sorted through remaining sequences to catalog groups of sRNAs and "putative sRNAs" — offering a window on the variety, taxonomy, and frequency of these regulatory transcripts in ocean microbes.
"The unexpected presence and abundance of these small RNAs, which can act as switches to regulate gene expression, will allow us to get an even deeper view of gene expression and microbial response to environmental changes," senior author Edward DeLong, a biological engineering researcher at MIT, said in a statement.
Metagenomics and metatranscriptomic studies, which sequence and assess collections of DNA and RNA from environmental samples, provide an opportunity to glean microbial sequence data without culturing organisms. For instance, previous studies have used metatranscriptomics to get a handle on the expression of protein-coding sequences in microbial communities.
For the latest study, DeLong and his team applied the approach to catalogue microbial sRNAs — 50 to 500 nucleotide untranslated RNAs, often expressed from intergenic parts of the genome, that are thought to be involved in gene regulation and signaling processes related to environmental response.
The researchers used pyrosequencing to sequence complementary DNA generated from microbial samples collected at ALOHA, a research station north of Oahu, as part of the Hawaii Ocean Time series. The communities were collected from four different depths: 25 meters (82'), 75 meters (246'), 125 meters (410') or 500 meters (1640') below the surface.
Once they tossed out known protein and rRNA coding sequences, the researchers searched the remaining transcripts to find sequences or structures resembling known sRNAs. Their search turned up 13 known sRNA families. Of these, the most commonly detected sRNAs corresponded to sRNA families that are ubiquitous or very abundant in microbial communities.
In an effort to uncover new sRNAs, the researchers used a self-clustering approach to group their sequence data into 66 groups, each representing 100 or more reads. Nine corresponded to sRNAs in the RNA family database Rfam.
Consistent with their proposed role as sRNAs, most of the putative sRNAs that the team detected mapped to intergenic regions in microbe metagenomic sequences. Computational analyses of structure and other features also suggested that most of these sequences represented real sRNAs.
"[A] big percentage of those sequences are non-coding sequences derived from yet-to-be-cultivated microorganisms in the ocean," lead author Yanmei Shi, an MIT graduate student, said in a statement. "This was very exciting to us because this metatranscriptomic approach ... opens up a new window of discovering naturally occurring sRNAs, which may further provide ecologically relevant implications."
Based on their results, the team speculated that differences in sRNAs and psRNAs found at varying depths in the ocean may reflect niche adaptation by microbes in each location. If so, they noted, sRNAs may have a previously under-appreciated role in regulating processes such as nutrient acquisition and energy metabolism.
The researchers delved into some of these potential links in their subsequent analyses, looking at how sRNA identity and abundance relates to microbial taxonomy, sampling depth, and so on.
"The diversity and abundance of sRNAs in microbial metatranscriptomic data sets indicates that natural microbial assemblages use a wide variety of sRNAs for regulating gene expression in response to variable environmental conditions," DeLong and his co-authors wrote. "These data, in conjunction with metatranscriptomic field experiments linking environmental variation with changes in RNA pools, have potential to provide new insights into environmental sensing and response in natural microbial communities."