New Paper: Metagenomic insights into the human gut resistome and the forces that shape it

Metagenomic insights into the human gut resistome and the forces that shape it by Kristoffer Forslund, Shinichi Sunagawa, Luis P. Coelho, Peer Bork in Bioessays (2014) DOI:10.1002/bies.201300143

This is a new paper which I was a part of. I will let Kristoffer Forslund (the first author) introduce it:

“Everyone knows” that feeding antibiotics to food animals are putting us on a path to the resistant bacterial apocalypse. However, published studies on the matter are less clear, with some authors arguing it is and others defending current use practices. So far progress in finding a definite answer has been limited due to experimental methods being expensive and cumbersome. Metagenomics offers new possibilities for understanding the evolution of antibiotic resistance and its causes, and in this review we both summarize the fledgling subfield, and present some new results of our own describing the distribution of antibiotics resistance genes in human gut microbial genomes, which we find reflects both medical and food production antibiotic use.

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Host-cell sensors for Plasmodium activate innate immunity against liver-stage infection

During the break, another paper where I played a part came out and now is it on the cover of the January edition of Nature Medicine:

Host-cell sensors for Plasmodium activate innate immunity against liver-stage infection by Liehl et al., in Nature Medicine 20, 47-53  (2014) [DOI]

Plasmodium, the malaria causing parasite, when entering the human body, first infects the liver. There, the small number of initial parasites (perhaps only a handful of them), multiply until they burst into the blood stream where they cause havoc, which can have potentially fatal consequences if left untreated.

The liver stage is clinically silent, with no visible symptoms. However, it does not go completely undetected by the host’s immune system. There were previous reports of an immune response in the liver, but we worked on understanding more of what was going on and observed a type-I interferon response using transcriptomics.

What I thought was most surprising (although this may be a function of my naïveté) was that the response seems to be activated by RNA sensing. The host detects the Plasmodium RNA and that triggers an immune response. This is some bad ass immune system stuff: using RNA sensors against eukariotic parasites instead of just viruses.

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Nature Medicine thought this was cool too and wrote up summary as well as putting the paper on the cover of January edition!

This excellent work must be credited to Peter Liehl and Maria Mota (the first and last authors). I am just happy that I got to play a role in this enterprise and learn some cool biology.

Year in Review: My Papers

In 2013, I also managed to get a few papers out:

1. Determining the subcellular location of new proteins from microscope images using local features by Coelho et al., in Bioinformatics (2013).

One sentence summary: Recognition of an organelle is a harder problem than recognition of a fluorescent marker, but local features can improve performance.

See previous posts on this paper or our video abstract

2. Mahotas: Open source software for scriptable computer vision by Coelho in Journal of Open Research Software (2013).

This paper presents mahotas, my Python package for computer vision and image processing.

One sentence summary: Python is great for computer vision.

3. Metagenomic species profiling using universal phylogenetic marker genes by Sunagawa et al. in Nature Methods (2013).

One sentence summary: We can profile species even without a reference genome by carefully using marker genes and linkage groups.

4. Host-cell sensors for Plasmodium activate innate immunity against liver-stage infection by Liehl et al. in Nature Medicine (2013).

One sentence summary: Plasmodium liver-stage infections trigger a type-I Interferon response.

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I also published a book in 2013: Building Machine Learning Systems with Python.

And I started a blog (you’re reading it now). So, overall, a pretty good year in publishing…

How Long Does Plos One Take to Accept A Paper?

How long do papers take to review?

Too long.

No, seriously, how long? I did a little measurement.

I downloaded the 360 most recent papers from Plos One (as of Friday). They are all annotated with submission and acceptance dates, so it was easy to just compute the differences.

The plot below is a histogram (one bin per day) in grey with a Kernel density estimate as a solid line.

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The result is it takes about 3 to 4 months to get a paper accepted, but with substancial variance.

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Looking at the figure, I had to ask who the poor people were who published that paper which was longest in revision.

Alternative Sigma Factor Over-Expression Enables Heterologous Expression of a Type II Polyketide Biosynthetic Pathway in Escherichia coli by David Cole Stevens, Kyle R. Conway, Nelson Pearce, Luis Roberto Villegas-Peñaranda, Anthony G. Garza, and Christopher N. Boddy. DOI: 10.1371/journal.pone.0064858

Submitted on 29 March 2011 and accepted on 22 April 2013, this paper was 755 days in revision.

The fastest acceptance was only 19 days. However, this being Plos One, it is possible that the paper had been reviewed for another Plos journal, rejected with positive reviews on significance grounds, and had those reviews transferred to Plos One. After this, acceptance followed without a new round of peer review.

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This is a gimmick. There is perhaps a paper to be written where this is extended to see what areas of research/keywords/&c matter to acceptance time. If I had more free time I might write that paper.

The code for the above is available on github.

Update: Followup with all PLoS Journals.