I just got word from BMC Genomics that my most recent paper has just been published (in provisional form; we still have not seen the edited proofs). In this paper (1), which I have co-authored with Anders Blomberg, Magnus Alm Rosenblad and Mikael Molin, we utilize metagenomic data from the GOS-expedition (2) together with fully sequenced bacterial genomes to show that:
- Detoxification genes in general are underrepresented in marine planktonic bacteria
- Surprisingly, the detoxification that show a differential distribution are more abundant in open ocean water than closer to the coast
- Peroxidases and peroxiredoxins seem to be the main line of defense against oxidative stress for bacteria in the marine milieu, rather than e.g. catalases
- The abundance of detoxification genes does not seem to increase with estimated pollution.
From this we conclude that other selective pressures than pollution likely play the largest role in shaping marine planktonic bacterial communities, such as for example nutrient limitations. This suggests substantial streamlining of gene copy number and genome sizes, in line with observations made in previous studies (3). Along the same lines, our findings indicate that the majority of marine bacteria would have a low capacity to adapt to increased pollution, which is relevant as large amounts of human pollutants and waste end up in the oceans every year. The study exemplifies the use of metagenomics data in ecotoxicology, and how we can examine anthropogenic consequences on life in the sea using approaches derived from genomics. You can read the paper in its entirety here.
- Bengtsson-Palme J, Alm Rosenblad M, Molin M, Blomberg A: Metagenomics reveals that detoxification systems are underrepresented in marine bacterial communities. BMC Genomics. Volume 15, Issue 749 (2014). doi: 10.1186/1471-2164-15-749 [Paper link]
- Yooseph S, Sutton G, Rusch DB, Halpern AL, Williamson SJ, Remington K, Eisen JA, Heidelberg KB, Manning G, Li W, Jaroszewski L, Cieplak P, Miller CS, Li H, Mashiyama ST, Joachimiak MP, Van Belle C, Chandonia J-M, Soergel DA, Zhai Y, Natarajan K, Lee S, Raphael BJ, Bafna V, Friedman R, Brenner SE, Godzik A, Eisenberg D, Dixon JE, Taylor SS, et al: The Sorcerer II Global Ocean Sampling expedition: expanding the universe of protein families. PLoS Biology. 5:e16 (2007).
- Yooseph S, Nealson KH, Rusch DB, McCrow JP, Dupont CL, Kim M, Johnson J, Montgomery R, Ferriera S, Beeson KY, Williamson SJ, Tovchigrechko A, Allen AE, Zeigler LA, Sutton G, Eisenstadt E, Rogers Y-H, Friedman R, Frazier M, Venter JC: Genomic and functional adaptation in surface ocean planktonic prokaryotes. Nature. 468:60–66 (2010).
The guys at Pfam recently introduced a new database, called AntiFam, which will provide HMM profiles for some groups of sequences that seemingly formed larger protein families, although they were not actually real proteins. For example, rRNA sequences could contain putative ORFs, that seems to be conserved over broad lineages; with the only problem being that they are not translated into proteins in real life, as they are part of an rRNA .
With this initiative the Xfam team wants to “reduce the number of spurious proteins that make their way into the protein sequence databases.” I have run into this problem myself at some occasions with suspicious sequences in GenBank, and I highly encourage this development towards consistency and correctness in sequence databases. It is of extreme importance that databases remain reliable if we want bioinformatics to tell us anything about organismal or community functions. The Antifam database is a first step towards such a cleanup of the databases, and as such I would like to applaud Pfam for taking actions in this direction.
To my knowledge, GenBank are doing what they can with e.g. barcoding data (SSU, LSU, ITS sequences), but for bioinformatics and metagenomics (and even genomics) to remain viable, these initiatives needs to come quickly; and automated (but still very sensitive) tools for this needs to get our focus immediately. For example, Metaxa  could be used as a tool to clean up SSU sequences of misclassified origin. More such tools are needed, and a lot of work remains to be done in the area of keeping databases trustworthy in the age of large-scale sequencing.
- Tripp, H. J., Hewson, I., Boyarsky, S., Stuart, J. M., & Zehr, J. P. (2011). Misannotations of rRNA can now generate 90% false positive protein matches in metatranscriptomic studies. Nucleic Acids Research, 39(20), 8792–8802. doi:10.1093/nar/gkr576
- Bengtsson, J., Eriksson, K. M., Hartmann, M., Wang, Z., Shenoy, B. D., Grelet, G.-A., Abarenkov, K., et al. (2011). Metaxa: 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 sequencing datasets. Antonie van Leeuwenhoek, 100(3), 471–475. doi:10.1007/s10482-011-9598-6
This has happened along with the 25th release of the Pfam database (released 1st of April), and basically means that Wikipedia articles will be linked to Pfam families. Gradually, this will (hopefully) improve the annotation of Pfam families, which has in many cases been rather poor. The Xfam blog post related to Pfam release 25 says the change will be happening gradually, which might actually be good thing, given the quirks that might pop up.
(…) a major change is that Pfam annotation is now beginning to be co-ordinated via Wikipedia. Unlike Rfam, where every entry has a Wikipedia entry, we expect this to be a more gradual transition for Pfam, so not all entries currently have a corresponding Wikipedia article. For a more detailed discussion, check the help page. We actively encourage the addition of new/updated annotations via Wikipedia as they will appear far quicker than waiting for a Pfam release. If there are articles in Wikipedia that you think correspond to a family, then please mail us!
I have awaited this change for a long time, and is very happy that Pfam has finally taken this step. Congratulations and my sincerest thanks to the Pfam team! Now, let’s go editing!
Nature recently had a nice news article on Bio-wikis and biological databases connected to Wikipedia where Alex Bateman says they’re working on a protein-family wiki that will be hosted on Wikipedia, similar to the Rfam wiki, which he talked about at FEBS this summer. I am of course very excited about this, and hope that the new Pfam (?) wiki will come rather sooner than later. As pointed out earlier, the Nature article also underlines the problem of scientific wikis; currently there is no career incentive to get researchers to spend their time editing wiki-articles. That is a shame, and perhaps a system copying the system of Rfam and RNA Biology could help in this direction. The only question is which journal(s) that would be interested in such a commitment to open science…
I listened to a great talk by Alex Bateman (one of the guys behind Pfam and Rfam, as well as involved in HMMER development) at FEBS yesterday. In addition to talking about the problems of increasing sequence amounts, Alex also provided some reflections on co-operativity and knowledge-sharing – not only among fellow researchers, but also to a wider audience. The starting point of this discussion is Rfam, where the annotation of RNA families is entirely based on a community-driven wiki, tightly integrated with Wikipedia. This means that to make a change in the Rfam annotation, the same change is also made at the corresponding Wikipedia page for this RNA family. And what’s the use of this? Well, as Alex says, for most of the keywords in molecular biology (and I would guess in all of science), the top hit on Google will be a Wikipedia entry. If not, the Wikipedia entry will be in the top ten list of hits, if a good Wiki page exists. This means that Wikipedia is the primary source of scientific information for the general public, as well as many scientists. Wikipedia – not scientific journals.
The consequence of this is that to communicate your research subject, you should contribute to its Wikipedia page. In fact, Bateman argues, we have a responsibility as scientists to provide accurate and correct information to the public through the best sources available, which in most cases would be Wikipedia. To put this in perspective (and here I once again borrow Alex’ words), if somebody told you ten years ago that there would be one single internet site that everybody would visit to find scientific information, and where discussion and continuous improvement would be allowed, encouraged and performed, most people would have said that was too good to be true. But that’s what Wikipedia offers. It is time to get rid of the Wiki-sceptisism, and start improving it.
And so, what about the future of publishing? Bateman has worked hard to form an agreement with the journal RNA Biology to integrate the publishing into the process of adding to the easily accessible public information. To have an article on a new RNA family published under the journal’s RNA families track, the family must not only be submitted to the Rfam database, but the authors must also provide a Wikipedia formatted article, which undergo the same peer-review process as the journal article. This ensures high-quality Wikipedia material, as well as making new scientific discoveries public.
I don’t think there’s a long stretch to guess that in the future, more journals and/or funding agencies will take on similar approaches, as researchers and decision-makers discover the importance of correct, publicly available information. The scientific world is slowly moving towards being more open, also for non-scientists. This openness is of extremely high importance in these times of climate scepticism, GMO controversy, extinction of species, and nuclear power debate. For the public to make proper decisions and send a clear message to the politicians, scientists need to be much better at communicating the current state of knowledge, or what many people prefer to call “truth”.