What should a core offer?
The authors of the Science TranslationalMedicine paper list four things a core needs: (i) sophisticated instruments, (ii)staff expertise in their operation, (iii) expertise in analysing the data and (iv) an ability to provide advice through consultation with users.
In my case the volume of samples being processed and the varied services being provided in my core make number (iii) difficult. There is a separate Bioinformatics core here at CRI so much of the analysis within my lab focuses on primary QC of data to make sure project data are of high quality before it is returned for secondary and tertiary analysis. This QC can be a job in itself, I rarely get time to actually analyse data and when I do I’m not far past page one for most packages. I try to make sure I understand the impact of biology on the experiment, how the analysis works in basic terms and consider how we can affect the results by changing what we do in the lab by tweaking the application.
I completely agree with the authors view that the consultation and advice provided by core labs can be as important as any actual data provided. I’d be interested to hear the view of core users on this as well. Core heads can be significantly more up-to-date on research methods and applications than users. From a sequencing stand point a PI knows they want to sequence something but it can be a long time since they did this themselves and the state of the art has changed fundamentally. Having someone local who can answer questions, suggest alternative methods and give impartial advice and feedback helps. I’d also like to think that when talking to someone in a local core people are less afraid of asking what he or she might consider “stupid” questions.
How much money is spent on core facilities?
Apparently the NIH spends about $900m a year on core facilities. The paper produces data from an analysis of 520 P30 (core infrastructure support) awards for 2010 totalling $637m. The $900m assumes a 40% underestimate of activity because of the difficulty in collecting this data. That seems like a huge margin for error to me and I’d suggest to the NIH they find a better way of recording and accounting for core activity.
It was interesting to me to find out that the NIH spent $300M of recovery act investment on shared and/or high-end instrumentation and that more confocal microscopes, mass specs or biomedical imagers were bought then next-gen sequencers. I guess this just shows how much I have my head in the sand when it comes to other research areas outside genomics. I also can’t help but wonder how many more genomes we could have sequenced and does the world need that many confocal microscopes?
How are UK core facilities organised?
In the UK there are examples of small, medium and large cores. Some offer services to single groups or institutes, others multiple institutes or anyone in the UK. Some operate on a consumables only recovery model and others work towards full economic cost recovery. So the UK has every possible type of core according to the NIH models, can we say which works best in the UK?
There are examples of all these in how UK next-generation sequencing is provided with over half of instruments being in large-medium sized core-labs. There are around 30-40 next-generation sequencing labs in the UK that together have over 120 instruments (65% Illumina, 20% Roche, 15% Life Technologies). The largest funder of these is the Wellcome Trust with the Wellcome Trust Sanger Institute the largest single lab in the UK (35 instruments), however services are mainly internal to the WTSI. The MRC has decided on a distributed hub model with 4 centres (collectively nearly 30 instruments). BBSRC has funded the Genome Analysis Centre (8 instruments) to provide services to all BBSRC grant holders. And CRUK, who I work for, has invested in 2 core labs (collectively 5 instruments), CRI where the sequencing is a collaborative service across four local Institutes and LRI that primarily offers services internally. There are at least another 50 instruments in smaller UK labs. (All data from googlemap).
I would not argue that the smaller labs should be consolidated with the larger ones, nor that the UK should have one Ã¼berlab but I doubt all 120 instruments are being used at maximum capacity and the total investment in instruments has been huge. I estimate a three year total for next-generation sequencing spend as likely to be over Â£100M. With Â£40M on instrument purchases alone (not including upgrades of obsolete instruments e.g. GA to HiSeq or SOLiD to 5500XL). My estimate is based on a 25% discount for instruments and consumables plus around 100 staff engaged in running or supporting the sequencing. Could the UK, or any other country achieve more “bang for its buck”?
How do you find a core?
There is not a single place to go for information. Certain communities have their own resources and the funding agencies don’t put a lot of effort into this. I already suggested that Google might not be the best place to start as a search on ‘DNA sequencing core facility’ returns 1.2m hits!
I am happy to point out my conflict of interest before suggesting a great example is the Google map of next-gen sequencers. This has over 500 facilities on it but of course is limited to next-gen sequencing. We have been thinking about extending this to other technologies and making more distinction between academic stand alone and/or core labs versus fully commercial facilities. I’d be happy to get readers of this blogs views on that idea.
Both the ABRF and the Vermont Genetics Network host databases of core facilities. They can be more comprehensive if harder to navigate and the information is perhaps more comprehensive. Two new projects funded by NCRR are VIVO and eagle-i. Both of which are aiming to catalogue information about core facility people and resources. However most users find a core because it is in their institution or down the hall in the university. And many times they seek out a particular lab through word-of-mouth recommendation.
It pays for us as core lab managers to run our lab as efficiently and courteously as possible, always generating the highest quality data, whilst maintaining up to date applications and technologies, for as little money as possible and still keeping one eye open for that next career move. An impossible job perhaps?
Yes. But one I still happily get out of bed for every day.