Joint project with the Royal Cornwall Hospital

Clinical Microbiology Team crop40%

picture courtesy of Louise Molloy

Aimee Murray, Lihong Zhang, Will Gaze (picture, left) and myself (right, back) have recently been involved in research led by Senior Biomedical Scientist John Lee (far right), Head of Department Dr. Richard Bendall (next to me) with help from many others in the Pathology Unit of the Royal Cornwall Hospital in Truro. The project focuses on the emerging human pathogen Staphylococcus pseudintermedius (a cousin of the more familiar Staphylococcus aureus of MRSA fame, which superficially looks a lot alike). S. pseudintermedius is associated with animals, particularly pet dogs, and has been reported from infections following dog bites. John has found out that, upon more careful examination, S. pseudintermedius are more common than previously thought and that dog bites form just a small portion of human infection cases. A team from RCHT will present findings at the 24th European Congress of Clinical Microbiology and Infectious Diseases in Barcelona in May. We are hoping to submit a publication in the very near future as well so watch this space.



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IMG_8966Last week I had the pleasure of being the guest of Pål Jarle Johnsen at the University of Tromsø, the northernmost university in the world. I have recently been awarded a NERC ‘pump priming’ grant on incipient bacterial speciation for which both Pål and Gabriel Perron are international partners. We will use the bacterium Acinetobacter baylyi, a model system for transformation related to the emerging pathogen A. baumannii. Pål and his group are experts on this model system and it was really interesting to hear about the experiments they have been doing. Both Pål and Gabe will visit Cornwall later this year and I hope to post about ongoing experiments then!



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always have a plan B!

job prospectsFrom the Royal Society’s 2010 report ‘The Scientific Century’ via Athene Donald’s blog (via Gabriel Perron via Adam Dunn), which features a highly interesting discussion on what this graph means.

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Gaming for Science

Just a quick link to a Guardian post summarizing a bunch of cool online games that help advance science along the way. The human brain is very good at pattern recognition, sometimes better than computers. Sequence alignment or protein folding are examples of biological problems computers (and scientists) have difficulty solving. Scientists are now exploiting the combined brain power of online gamers as a tool in computational biology. Just as fun as a game of tetris it seems, and knowing you are solving real problems is of course a bonus (although some might just see it as another Candy Crush Saga, which of course is fine as well as long as they are solving problems!). Foldit is one of the oldest such games. From Wikipedia:

In 2011, players of Foldit helped to decipher the crystal structure of the Mason-Pfizer monkey virus (M-PMV) retroviral protease, an AIDS-causing monkey virus. While the puzzle was available to play for a period of three weeks, players produced an accurate 3D model of the enzyme in just ten days. The problem of how to configure the structure of the enzyme had stumped scientists for 15 years.

Phylo also looks neat. Unfortunately the computing power involved precludes these games from being played on a smart phone (at the moment).


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I am currently preparing lectures and a lab practical for a Masters course in Environment and Human Health. A lot of work, but lectures do give you the opportunity to take a step back and identify key concepts in the field; something which can get lost a bit in the minutiae of daily activities. As the students following this course are from a wide range of undergraduate backgrounds, I really need to get down to the basics however. I have decided on four lectures, one on DNA, one on DNA methodologies (mainly PCR and sequencing), one on environmental microbiology and one on clinical microbiology. The lab work will consist of a colony (multiplex) PCR and running an agarose gel. Luckily Lihong and Will still have waste water isolates they need to screen for the presence of antibiotic resistance genes, so the student’s results will actually contribute to ongoing work. I think (hope) doing a PCR should be doable for the students and give them a real taste of what lab work is about. Also, it will nicely tie in the concepts from genetics and microbiology covered by the lectures. Anyway, I just discovered some amazing youtube videos which will certainly be very helpful getting across concepts. This is my favourite:



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Paper out: Impact of Matric Potential and Pore Size Distribution on Growth Dynamics of Filamentous and Non-Filamentous Soil Bacteria

At the very last day of 2013, a paper came out that I was involved in when I was doing a postdoc at the Netherlands Institute of Ecology in Wageningen. First author is Alexandra Wolf, who developed an artificial soil which enabled her to vary key soil characteristics to study their effect on bacterial growth. From the Abstract:

The filamentous growth form is an important strategy for soil microbes to bridge air-filled pores in unsaturated soils. In particular, fungi perform better than bacteria in soils during drought, a property that has been ascribed to the hyphal growth form of fungi. However, it is unknown if, and to what extent, filamentous bacteria may also display similar advantages over non-filamentous bacteria in soils with low hydraulic connectivity. In addition to allowing for microbial interactions and competition across connected micro-sites, water films also facilitate the motility of non-filamentous bacteria. To examine these issues, we constructed and characterized a series of quartz sand microcosms differing in matric potential and pore size distribution and, consequently, in connection of micro-habitats via water films. Our sand microcosms were used to examine the individual and competitive responses of a filamentous bacterium (Streptomyces atratus) and a motile rod-shaped bacterium (Bacillus weihenstephanensis) to differences in pore sizes and matric potential. The Bacillus strain had an initial advantage in all sand microcosms, which could be attributed to its faster growth rate. At later stages of the incubation, Streptomyces became dominant in microcosms with low connectivity (coarse pores and dry conditions). These data, combined with information on bacterial motility (expansion potential) across a range of pore-size and moisture conditions, suggest that, like their much larger fungal counterparts, filamentous bacteria also use this growth form to facilitate growth and expansion under conditions of low hydraulic conductivity. The sand microcosm system developed and used in this study allowed for precise manipulation of hydraulic properties and pore size distribution, thereby providing a useful approach for future examinations of how these properties influence the composition, diversity and function of soil-borne microbial communities.

Wolf AB, Vos M, de Boer W, Kowalchuk GA (2013) Impact of Matric Potential and Pore Size Distribution on Growth Dynamics of Filamentous and Non-Filamentous Soil Bacteria. PLoS ONE 8(12): e83661. doi:10.1371/journal.pone.0083661

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Citation counts: Google Scholar vs. Web of Science

As most scientists do, I occasionally find myself talking to colleagues about scientific impact. This discussion often centers on the prestigiousness of journals and their Impact Factors (for a very good discussion on this subject see this blog post). The other topic that comes up is the number of citations papers receive. Although the brilliance of science does not perfectly correlate with the number of times colleagues cite you, it is a much better indication of one’s success (which is not the same as one’s abilities!) than being able to report having published in a high IF journal. Again, this measure is not perfect, for instance, some research fields are smaller and consequently there is a smaller pool of people that could cite you. Also, it seems that by citing more papers, you will receive more citations yourself in what seems to be a tit-for-tat game.

My colleagues and I had noted that the number of citations given by Google Scholar was always higher than that given by Web of Science.  There were some suspicions of Google Scholar algorithms including dodgy references and Web of Science being more limited in the number of journals it included (it does not need saying that we were all in favour of Google Scholar…). Although far from putting an end to this debate, I still thought that it could be illuminating to take a single paper to check where the differences in citation counts could lie. (I have not looked at the other two main resources Scopus and PubMed as I don’t use these myself.) I used my best-cited paper, a meta-analysis of homologous recombination rates in bacteria which was a collaboration with Xavier Didelot, now at Imperial College London. This paper re-analyzed published data; such a meta-analysis lies somewhere between a paper on one’s own data and a review paper. Review papers are usually better cited than data papers and therefore excluded from some Impact measurements (such as ‘the REF’ here in the UK). Web of Science says it has been cited 89 times, Google Scholar says it was cited 125 times: 40% more!

I downloaded all 89 WoS references into Endnote to check them against the GS list and to export the 36 missing references to the GS ‘My Library’ list. The strange thing was that the numbers did not add up: I missed five references (I first blamed myself but after rechecking the list they were still not there). Then I noticed that there were twelve search results pages displaying ten papers each: 120 hits, not the 125 citations listed below the paper. Google thus was contradicting itself*. This instantly reminded me of a conversation I had with my ECEHH colleague Marco Palomino who researches ‘horizon scanning’; the identification of emerging technologies or risks using internet searches (combining keywords of interest with phrases such as ‘break through’ and ‘cutting edge’ for instance). Marco found out that there are huge discrepancies between actual search results and the the number of total reported hits by Google search algorithms (see here). Perhaps Google’s ‘Don’t be Evil‘ should be followed by ‘but it’s OK if you’re slightly disingenuous’…

Now for the remaining 31 (120-89) GS references not covered by WoS. First I checked whether there were any references found by WoS and not by GS. There was one (a 2011 paper in the American Journal of Clinical Pathology). GS also linked to a pre-published paper whereas WoS had a complete reference. Only one GS false negative, how about the WoS false negatives? Frustratingly, I found 33 GS references not present in WoS instead of the expected 32 (120-89-1). Re-checking did not solve this and I hope the reader will forgive me for one reference gone astray. Among these 33 references were four book chapters and eleven dissertations. It is perhaps debatable if these (especially the latter) should be counted, as their availability might be more limited compared to papers and they go through a more informal type of peer review (and also the contents of dissertations should find their way into papers). I personally think they represent proper scientific output and should be counted. One reference was a comment in Science which is not peer-reviewed (and very brief) and one could argue whether to include that one as well (I’ll include it!). One reference was in Chinese. I would argue that all references should be in the lingua franca English (I am not a native English speaker so I can say that…).

A total of 16 papers were missed by WoS, including ones in well-known journals such as Environmental Microbiology, Nature Reviews Microbiology, PLoS ONE and BMC Evolutionary Biology. Other journals missed were less well known, eg Mobile Genetic Elements and Applied Microbiology and Biotechnology; the former is not indexed by WoS but the latter is (you can check for WoS indexed journals here). Nine papers were from 2013 and so might have been missed by WoS due to a time lag but that should not be an excuse.

Of course I have cited myself on occasion. Some funders require a reference list with (WoS) citation counts  minus self citations. It is true that researchers to an extent can inflate their citation counts by citing themselves and that a self citation on average is worth less than a citation of your work by someone else. However, it must also be said that these same funders usually insist on seeing an overarching research theme by the applicant and it makes complete sense that your work is built on your previous (published) work (see here for an interesting discussion on the topic of self-citations). Anyway, the strange thing is that I have cited this paper both in a Trends in Microbiology paper in 2009 and in a paper in the same journal in 2011 and WoS has only found the 2011 one: very strange!

Below I have plotted the Google Scholar and Web of Science citation counts, as well as the ‘real’ count (125 minus 5 false positives plus one false negative minus one none-English paper). (A ‘real’ papers-only count would amount to 115 citations (120 minus 15)). Despite evident faults, it is clear that GS is a better predictor of actual citation numbers than is WoS. Perhaps some of the confusion will clear in the near future now it seems that Google Scholar and Web of Science/Knowledge will start to cooperate



*=I see that the citation count has increased to 129 while writing but still only 120 citations show up


P.S. I found out that (of course) I wasn’t the first to make this comparison, see here for another blog post:

Google Scholar vs. Scopus and Web of Science


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