MG-RAST (Metagenomics Rapid Annotation using Subsystem Technology) is a server that allows registered members to upload raw data sequences derived from microbial samples (1). Users can elect to make their metagenomes accessible to the public (1).
Launched in 2007, MG-RAST has over 8000 members (2). There are 90,286 metagenomes of which ~13,000 are public (2). The server was adapted from the original RAST server that was used to annotate microbial genomes. It utilizes technology from the Argonne National Lab and the University of Chicago (2).
Uploaded sequences have summaries automatically generated and can be accessed through a variety of methods including phylogenetic and metabolic reconstructions (1). Abundance counts can also be performed (1).
These counts can include taxon or function counts. Users can also normalize data allowing for comparison of data from different metagenomes (2). Users can also perform a range of statistical tests of significance using MG-RAST's p-value tool (1).
Examples of UseEdit
Exploring One MetagenomeEdit
MG-RAST allows you to search by MG-RAST ID, by function or by organism (3) . Alternatively, browsing the public metagenomes is another way to find interesting data sets (Fig.1). Clicking the project name (Fig.1 - red arrow; Fig.2) of one of the results leads to a description of the project along with the funding source and other relevant information. Clicking the name (Fig.1 - blue arrow) leads to a summary of the data set.
- There are a number of ways to analyse the data. For example, to get an idea of the taxonomic distribution of the organisms found in the metagenome, the organism breakdown can be helpful. Checking the taxonomic hits distribution (Fig.3 - yellow arrow) will give you a breakdown by domain, class, order etc. If you then wanted to know more about the composition of the archaea domain in this metagenome, you could select that sector of the domain pie chart (Fig.4). That data would then be exported to your workbench which will open in a new window (Fig.5). After selecting the workbench data and choosing how you would like to view the data (in this case as a tree - Fig.5), the workbench will generate a breakdown of the archaea in the metagenome (Fig.6). You can display leaf weights and choose the maximum taxonomic level you wish to display (in this case order - Fig.6). You can also color code by any other taxonomic level (in this case phylum - Fig.6).
- To compare entire metagenomes you just need to change the data selection settings. You can select a project tyoe(s) you would like to use (in this case WGS - Fig.7). Hitting compare individually will allow you to choose from metagenomes within a WGS project (in this case cDNA-Plymouth Marine Coastal Lab Coastal Waters project - Fig.7). cDNA-Plymouth Marine Coastal Lab Coastal Waters project contains eight metagenomes and for this example two were chosen. After choosing two metagenomes, you will be able to create trees and barcharts etc. to compare them (Fig.8; Fig.9). Clicking one of the bars in a barchart will allow you to 'drill down' further within the domain (Fig.10).
- The Metagenome Overview mentioned above also has links to publications that make use of the metagenome data. The overview for the cDNA-Plymouth Marine Coastal Lab Coastal Waters project has two articles linked.
- The first paper details the findings of a controlled coastal ocean mesocosm study (4). The authors propose that this study 'confirms the finding of the first published metatranscriptomic studies of marine and soil environments that metatranscriptomics targets highly expressed sequences which are frequently novel' (4).
- The second paper presents a study in which DNA and cDNA libraries were constructed from samples taken from a phytoplankton bloom in the English Channel (5). Using this data, the authors were able to find evidence for phosphonoacetate utilization by marine bacteria (5). Based on this data, they cultured potential coral pathgens (Vibrionaceae) and found that they were able to grow using phosphonoacetate as their sole carbon and phosphate source (5). They further stated that their data provided evidence for the use of phoshoacetate by more marine organisms than previously thought (5).
1. MG-RAST for the impatient, MG-RAST, http://press.igsb.anl.gov/mg-rast/mg-rast-for-the-impatient-readme-1st/
3. Meyer F et al., (2008)The Metagenomics RAST server – A public resource for the automatic phylogenetic and functional analysis of metagenomes.BMC Bioinformatics, 9:386
4. Gilbert JA et al., (2008) Detection of large numbers of novel sequences in the metatranscriptomes of complex marine microbial communities., PLoS One 3(8): e3042.
5. Gilbert JA et al., (2009) Potential for phosphonoacetate utilization by marine bacteria in temperate coastal waters, Environ Microbiol, 11: 111–125. doi: 10.1111/j.1462-2920.2008.01745.