Tag Archives: metagenome

Video Tip of the Week: Microbiome Resources From JGI

Just over a month ago an issue of Nature had two articles from the Human Microbiome Project Consortium – you may have seen them, or noticed the Friday SNPets items we had on them. I promised myself that I’d read the articles (which I did), and that I’d visit my old friends the IMG (Integrated Microbial Genomes) & IMG/M (IMG with Microbiome Samples) to see what is new at these powerful microbial genome resources. In today’s tip I decided to take you along on my visit with me, because I found that IMG now has a resource dedicated to the analysis of genomes related to the Human Microbiome Project called the Integrated Microbial Genomes-Human Microbiome Project, or IMG/HMP. We visit both IMG/M (briefly) and the IMG/HMP in today’s tip.

When I referred to IMG as an old friend, I really do feel that way – our tutorial on IMG* was one of my first projects for OpenHelix. I was new, and IMG was new, having been released in March of 2005, only a few months before I created our tutorial (on their June 2005 release, if I am remembering correctly). They have grown into such an extensive, powerful resource. To give you an idea of how fast they have grown & developed, our current IMG tutorial is version 12 and I’ll be working on version 13 as soon as I finish updating our SGD tutorial. When we first created our IMG/M tutorial*, metagenomes were a relatively new concept and the resource included a total of 24 microbiome samples – now it has over 1000!

But enough with the nostalgia, let’s get to the resources! :) IMG/M integrates metagenome data with isolate microbial genome sequences from the integrated microbial genome (IMG) system to enable the analysis of phylogenetic composition and functional or metabolic potential of the aggregate genomes (metagenomes) in microbial communities (microbiomes). Genomes generated as part of the Human Microbiome Project (HMP) are included into IMG/M from RefSeq via IMG. IMG/M resources allow users analyze metagenomes, genomes, genes and functions by making lists of items and then manipulating them in “analysis carts”. Metagenomes can also be analyzed using the tools provided from their ‘Metagenome Details’ page. These options are explained in much more detail than I can cover here in the IMG/M reference that I site below. I also link to the most recent IMG publication, since an understanding of it is essential to understand any IMG/M-based resource.

* OpenHelix tutorial for this resource available for individual purchase or through a subscription.

Quick Links:
Integrated Microbial Genomes (IMG): http://img.jgi.doe.gov/cgi-bin/pub/main.cgi

Integrated Microbial Genomes with Microbiomes (IMG/M): http://img.jgi.doe.gov/cgi-bin/m/main.cgi

Integrated Microbial Genomes-Human Microbiome Project (IMG/HMP): http://www.hmpdacc-resources.org/imgm_hmp/

OpenHelix Introductory Tutorial on IMG: http://www.openhelix.com/cgi/tutorialInfo.cgi?id=54

OpenHelix Introductory Tutorial on IMG/M: http://www.openhelix.com/cgi/tutorialInfo.cgi?id=24

Victor M. Markowitz, I-Min A. Chen, Ken Chu, Ernest Szeto, Krishna Palaniappan, Yuri Grechkin, Anna Ratner, Biju Jacob, Amrita Pati, Marcel Huntemann, Konstantinos Liolios, Ioanna Pagani, Iain Anderson, Konstantinos Mavromatis, Natalia N. Ivanova, & Nikos C. Kyrpides (2012).
IMG/M: the integrated metagenome data management and comparative analysis system Nucl. Acids Res. , 40 DOI: 10.1093/nar/gkr975

Victor M. Markowitz1, I-Min A. Chen, Krishna Palaniappan, Ken Chu, Ernest Szeto, Yuri Grechkin, Anna Ratner, Biju Jacob, Jinghua Huang, Peter Williams, Marcel Huntemann, Iain Anderson, Konstantinos Mavromatis, Natalia N. Ivanova, & Nikos C. Kyrpides (2012). IMG: the integrated microbial genomes database and comparative analysis system Nucl. Acids Res., 40 DOI: 10.1093/nar/gkr1044

Tip of the Week: Comparing Microbial Databases

A few weeks ago a commenter asked me to compare IMG (Integrated Microbial Genomes) to the UCSC Microbial Genome browser. I’ve been exploring & thinking since then & am going to give a very brief comparison of those two resources in today’s tip & I’ll expand the comparison to other resources here in the text of this post.

Continue reading

Do You Have a Metagenome Sequence that Needs Taxonomic Analysis?

I was catching up on reading past BioMed Central Article Alert emails & I saw a resource that I wanted to pass on to you. The resource is WebCARMA, and is a web version of the CARMA analysis program (not too hard to guess that, though huh?!?). Yea, but what is CARMA (the software version with a “C” rather than the philosophical one with a “K”)? According to Krause et al., 2008 CARMA is:

The algorithm searches for conserved Pfam domain and protein families in the unassembled reads of a sample. These gene fragments (environmental gene tags, EGTs), are classified into a higher-order taxonomy based on the reconstruction of a phylogenetic tree of each matching Pfam family. The method exhibits high accuracy for a wide range of taxonomic groups, and EGTs as short as 27 amino acids can be phylogenetically classified up to the rank of genus.

To quote Gerlach et al., 2009 WebCARMA is:

WebCARMA, a refined version of CARMA available as a web application for the taxonomic and functional classification of unassembled (ultra-)short reads from metagenomic communities.

I didn’t actually run WebCARMA because, well, I don’t actually have a metagenome in my back pocket (but later I might just sneak over to IMG/M & download some FASTA metagenomic sequence so I can play…). I did read the documentation & it sounds pretty neat. CARMA doesn’t actually create taxonomic profiles, but it does create taxonomic assignments for your short metagenome reads, outputs lots of output files full of information, and provides some perl scripts for creating the taxonomic profiles. You can read about what WebCARMA does here, and download example output files here.

You do need to email for a login URL, and there are limits to how much you can analyze online (100 megabytes within 4 weeks in total), but I’m not sure that I’ve seen a resource that does exactly what CARMA/WebCARMA does. If you use WebCARMA, could you let me know what you think of it? And if you use other similar software, what is it? Thanks!


W. Gerlach, S. Jünemann, F. Tille, A.Goesmann and J. Stoye
WebCARMA: A Web Application for the Functional and Taxonomic Classification of Unassembled Metagenomic Reads
BMC Bioinformatics 2009, 10:430

L. Krause, N.N. Diaz, A. Goesmann, F. Rohwer, S. Kelley, R.A. Edwards J. Stoye,
Phylogenetic Classification of Short Environmental DNA Fragments,
Nucleic Acids Research 2008 36(7):2230-2239; doi:10.1093/nar/gkn038.

Metagenomes in Nature

Nature had a nice feature on metagenomics last week and another on the Human microbiome metagenomics. You’ll need to have a subscription to access those :(, but the gist of the latter news feature is the possibilities of Human microbiome research, pros and cons and the projects out there. There are a lot. In order of amount of funding they are:

Continue reading

Tip of the Week: Functional Abundance Profile Searching in Genomes

Wow, how can you resist blogging about an article who’s title begins “Dissecting biological ‘‘dark matter’’…”? I found the article while working on a new ‘sponsored’ (read ‘free’) tutorial on the Integrated Microbial Genomes with Microbiome Samples (or IMG/M) resource. (I’m hoping the tutorial will be released in the near future & I’ll post when it is available.) IMG/M is a microbial resource that specializes in the analysis of metagenomes. Metagenomes are becoming hot – we’ve blogged about them in the past, as have lots of others. According to the article I found, “biological dark matter” refers to our paltry knowledge & understanding of the Earth’s microbial diversity. The article reports a method for isolating individual bacterial cells from the microbiome of the human mouth, but for my contribution to understanding microbial diversity, I want to give you a tip on using the IMG/M resource to select protein families in genomes based on their relative abundance. Click the image above to view the tip, or follow the links in this post to learn more on your own.
ResearchBlogging.orgMarcy, Y., Ouverney, C., Bik, E.M., Losekann, T., Ivanova, N., Martin, H.G., Szeto, E., Platt, D., Hugenholtz, P., Relman, D.A., Quake, S.R. (2007). Inaugural Article: Dissecting biological “dark matter” with single-cell genetic analysis of rare and uncultivated TM7 microbes from the human mouth. Proceedings of the National Academy of Sciences, 104(29), 11889-11894. DOI: 10.1073/pnas.0704662104