Tag: Microbial ecology

Metaxa updated to 1.0.2

I was informed by a Metaxa user of a bug in the current Metaxa version (1.0.1). This bug caused problems when Metaxa-output was directed to another directory than the current directory Metaxa was run from. I have fixed this issue as fast as I could, as this could cause problems when Metaxa is included in larger analysis pipelines. The update to 1.0.2 is therefore strongly recommended for all Metaxa users. The update to 1.0.2 also introduces better handling of input files created in Windows environments, as well as improving the handling of extremely long sequence identifiers. The update can be downloaded using this link.

New features:
  • Improves import of sequence sets from Windows environments.
Fixed bugs:
  • Fixed a bug causing trouble with sequences with extremely long identifiers.
  • Fixed an output-related bug causing problems with output directed to another directory.

Published paper: Metaxa

It is a pleasure to annonce that the paper on Metaxa is now available as an Online early article in Antonie van Leeuwenhoek. In short, the paper describes a software tool that is able to extract small subunit (SSU) rRNA sequences from large data sets, such as metagenomes and environmental PCR libraries, and classify them according to bacterial, archaeal, eukaryote, chloroplast or mitochondrial origin. The program makes it easy to distinguish between e.g. the bacterial SSU sequences you like to analyze, and the SSU sequences you would like to remove prior to the analysis (e.g. mitochondrial and chloroplast sequences). This task is particularly important in metagenomics, where sequences can potentially derive from a variety of origins, but bacterial diversity often is the desired target for analysis. The software can be downloaded here, and the article can be read here. I would like to thank all the co-authors on this paper for a brilliant collaboration, and hope to be working with them again.

Reference:

Metaxa updated

Just a short note; Metaxa has been updated to version 1.0.1. This incremental version brings two small new features, and a minimal bug fix.

  • Added the option to select whether HMMER’s heuristic filtering should be used or not. This can be configured using the –heuristics option:
    –heuristics {T or F} : Selects whether to use HMMER’s heuristic filtering, off (F) by default
  • Removed some redundant information written to the screen, as output to the screen was a bit cluttered.

Bug fix:

  • Fixed a rare bug affecting detection sensivity of some SSU sequences.

Of course I would recommend it to every Metaxa user as it fixes a small bug, but the update is not in anyway critical for normal use.  The updated version can be downloaded using this link.

Metaxa released

I proudly announce that today Metaxa has been officially released. Metaxa is a a software tool for automated detection and discrimination among ribosomal small subunit (12S/16S/18S) sequences of archaea, bacteria, eukaryotes, mitochondria, and chloroplasts in metagenomes and environmental sequence datasets. We have been working on Metaxa for quite some time, and it has now been in beta for about two months. However, it seems to be stable enough for public consumption. In addition, the software package is today presented in a talk at the SocBiN conference in Helsinki.

A more thorough post on the rationale behind Metaxa, and how it works will follow when I am not occupied by the SocBiN conference. A paper on Metaxa is to be published in the journal Antonie van Leeuwenhoek. The  software can be downloaded from here.

Moving on…

So, last week I started my Ph.D. in Joakim Larsson’s group at the Sahlgrenska Academy. While I am very happy about how things have evolved, I will also miss the ecotox group and the functional genomics group a lot (though both do their research within 10 minutes walking distance from my new place…) I spent last week getting through the usual administrative hassle; getting keys and cards, signing papers, installing bioinformatics software on my new monster of a computer etc. Slowly, the new room starts to feel like it is mine (after nailing phylogenetic trees, my favorite map of the amino acids, and my remember-why-Cytoscape-visualisation-might-not-be-a-good-idea-for-all-network-like-structures poster to the billboard).

So what will this change of positions mean? Will I quit doing research on microbial communities? Of course not! In my new position, my subject of investigation will be bacterial communities subjected to antibiotics. We will look for resistance genes in such communities, and try to answer questions like: How do a high antibiotic selection pressure affect abundance of resistance genes and mobile elements that could facilitate their transfer between bacteria? Can resistance genes found in environmental bacteria be transferred to the microbes of the human gut? Can the environmental bacteria tell us what resistance genes that will be present in clinical situations in the near future? All these questions could, at least partially, be answered by metagenomic approaches and good bioinformatics tools, and my role will be to come up with the solutions provide answers to them.

I am excited over this new project, which involves my favorite subject – metagenomics and community analysis – as well as important factors, such as the clinical connections, the possibility to add pieces to the antibiotic resistance puzzle, and the role of gene and species transfer in resistance development. I also like the fact that I will need to handle high-throughput  sequence data, meaning that there will be many opportunities to develop tools, a task I highly enjoy. I think the next couple of years will be an exciting time.

Thesis presentation

I will present my master thesis “Metagenomic Analysis of Marine Periphyton Communities”, on Tuesday the 22nd of March, at 13.00. The presentation will take place in the room Folke Andreasson at Medicinaregatan 11 in Gothenburg. The presentation is open for everyone, but the number of seats are limited.

Raising the bar for genome sequencing

In a recent Nature article (1), Craig Venter and his co-workers at JCVI has not only sequenced one marine bacterium, but 137 different isolates. Their main goal of this study was to better understand the ecology of marine picoplankton in the context of Global Ocean Sampling (GOS) data (2,3). As I see it, there are at least two really interesting things going on here:

First, this is a milestone in sequencing. Were not talking one genome – one article anymore. Were talking one article – 137 new genomes. This vastly raises the bar for any sequencing efforts in the future, but even more importantly, it shifts the focus even further from the actual sequencing to the purpose of the sequencing. One sequenced genome might be interesting enough if it fills a biological knowledge gap, but just sequencing a bacterial strain isn’t worth that much anymore. With the arrival of second- and third-generation sequencing techniques, this development was pretty obvious, but this article is (to my knowledge) the first real proof of that this has finally happened. I expect that five to ten years from now, not sequencing an organism of interest for your research will be viewed as very strange and backwards-looking. “Why didn’t you sequence this?” will be a highly relevant review question for many publications. But also the days when you could write “we here publish for the first time the complete genome sequence of <insert organism name here>” and have that as the central theme for an article will soon be over. Sequencing will simply be reduced to the (valuable) tool it actually is. Which is probably good, as it brings us back to biology again. Articles like this one, where you look at ~200 genomes to investigate ecological questions, are simply providing a more relevant biological perspective than staring at the sequence of one genome in a time when DNA-data is flooding over us.

Second, this is the first (again, to my knowledge) publication where questions arising from metagenomics (2,3,4) has initiated a huge sequencing effort to understand the ecology or the environment to which the metagenome is associated. This highlights a new use of metagenomics as a prospective technique, to mine various environments for interesting features, and then select a few of its inhabitants and look closer at who is responsible for what. With a number of emerging single cell sequencing and visualisation techniques (5,6,7,8) as well as the application of cell sorting approaches to environmental communities (5,9), we can expect metagenomics to play a huge role in organism, strain and protein discovery, but also in determining microbial ecosystem services. Though Venter’s latest article (1) is just a first step towards this new role for metagenomics, it’s a nice example of what (meta)genomics could look like towards the end of this decade, if even not sooner.

  1. Yooseph et al. Genomic and functional adaptation in surface ocean planktonic prokaryotes. Nature (2010) vol. 468 (7320) pp. 60-6
  2. Yooseph et al. The Sorcerer II Global Ocean Sampling expedition: expanding the universe of protein families. Plos Biol (2007) vol. 5 (3) pp. e16
  3. Rusch et al. The Sorcerer II Global Ocean Sampling expedition: northwest Atlantic through eastern tropical Pacific. Plos Biol (2007) vol. 5 (3) pp. e77
  4. Rusch et al. Characterization of Prochlorococcus clades from iron-depleted oceanic regions. Proceedings of the National Academy of Sciences of the United States of America (2010) pp.
  5. Woyke et al. Assembling the marine metagenome, one cell at a time. PLoS ONE (2009) vol. 4 (4) pp. e5299
  6. Woyke et al. One bacterial cell, one complete genome. PLoS ONE (2010) vol. 5 (4) pp. e10314
  7. Moraru et al. GeneFISH – an in situ technique for linking gene presence and cell identity in environmental microorganisms. Environ Microbiol (2010) pp.
  8. Lasken. Genomic DNA amplification by the multiple displacement amplification (MDA) method. Biochem Soc Trans (2009) vol. 37 (Pt 2) pp. 450-3
  9. Mary et al. Metaproteomic and metagenomic analyses of defined oceanic microbial populations using microwave cell fixation and flow cytometric sorting. FEMS microbiology ecology (2010) pp.