Skip to main content
Premium Trial:

Request an Annual Quote

Sanger Array Chief Cordelia Langford Talks Robots, Pins, & Chips

Cordelia Langford
Facility Head
Wellcome Trust Sanger Institute

Name: Cordelia Langford

Title: Microarray Facility Head, the Wellcome Trust Sanger Institute

Professional Background: 2002- present, Microarray Facility Head, the Wellcome Trust Sanger Institute; 1999-2002, senior research assistant, Wellcome Trust Sanger Institute.

Education: 2004 — PhD, molecular cytogenetics.

Cordelia Langford is a group leader and head of the Wellcome Trust Sanger Institute's Microarray Facility where she is responsible for providing training, support, and microarray technology to both Sanger and non-Sanger-affiliated researchers. According to Langford, the facility currently offers high-throughput production of spotted genomic, oligonucleotide, cDNA, and protein arrays for a range of organisms and applications, as well as access to commercial arrays such as Affymetrix and Illumina.

From this unique perch, Langford gets to evaluate most of the microarray-related technologies — from spotting robots to spotting pins to bioinformatics packages — on the market today. In order to provide greater insight to the Sanger's microarray facility, as well as the industry in general, Langford spoke with BioArray News following her presentation at the World Microarray Congress, held in Vancouver, BC, two weeks ago.

Can you provide me with some numbers on how many arrays you are printing at Sanger right now, and do you have any numbers on commercial use?

We print about 1,200 or 1,400 arrays per month. I don't have any numbers for Illumina, but for Affymetrix we probably use on average 50 to 100 arrays per month. That's a range of genotyping, resequencing, whole-genome expression applications.

What applications are dominating right now for Affymetrix?

Probably genotyping at the moment, but it changes. There's a very big project for the cancer genome group at the Sanger Institute where they wanted to analyze something like 500 or 1,000 samples. And so they were the heaviest user of Affymetrix last year using SNP chips. But they've come to the end of that project, so now, for the first quarter of this year, it's been gene expression in human and in mouse.

With regards to the spotted arrays it is often said that spotted arrays are really for those that are working with exotic species. Is that really the case at Sanger?

Yes. We spot about 40 different array types. And the species range from yeast to zebrafish, frog, dog, human and mouse.

All of the biology is interesting. Because of the subject of my PhD, I have a particular interest in canine genetics. I am collaborating with Matthew Breen, who works at North Carolina University at Raleigh, on printing canine arrays. Xenopus and zebrafish are interesting because when we started printing them there weren't really any [similar] products available and so it really was a novelty.

What's really your choice of robotics and pins right now?

We've actually got six MicroGrid II robots from Genomic Solutions. We originally purchased them through BioRobotics, which was subsequently acquired by Genomic Solutions. We had a collaborative relationship with BioRobotics to develop what's now their current model, the MicroGrid II 610. We liked it because of its small footprint, and you can print up to 120 slides in one go. It's quite user-friendly in terms of the operating software. So, because we've been exploring the accuracy and the spot definition, we felt that we can sort of use it as a tool for developing high density printing as well and so it does everything we need at the moment. We do talk to other companies about what's out in the market. We've been talking to companies like Arrayjet in particular who make non-contact inkjet printer to see if they have something that might be useful for us in the future.

As far as the MicroGrid is concerned, we usually spot with tungsten pins. We have two pin sizes and so for the high-density printing we use a finer tip. We have also been looking into ceramic pins and also silicon pins and other metal pins, like those made by TeleChem, for example.

Did you have any challenges in optimizing your existing setup for array comparative genomic hybridization arrays and ChIP-on-chip production?

Yes. For array CGH, there are a number of challenges. One of them is the fact that the samples spotted for the BAC array are very concentrated DNA and they are quite viscous. It's a challenge to actually spot those without getting cross contamination between spots. The pins could get blocked easily if they are not washed properly.

For a ChIP-chip study, we are printing high resolution arrays, and the challenge there is making sure enough DNA is spotted down in the spots so it is not the limiting factor in the hybridization. So each application has its own challenges.

What kind of resources have you devoted to the facility?

I have a postdoc who oversees the work for me. So there's myself and then the postdoc, and under him there are six individuals in the lab that are involved in certain stages of preparation of the arrays. So we actually employ three people who spend all their time printing the arrays — their job is setting up and running the robots. We have two other people that are involved in the PCR preparation for the samples that are then spotted on the arrays.

The main resources and time are taken up in preparing the samples. If the PCR that is carried out to prepare the samples for spotting fails then we have to go back to square one and repeat the reaction. So once a set of PCR reactions has been carried out, we then have sufficient resources for many thousands of arrays. So if we were preparing samples for an array that was going to be printed quite a lot, we would have to do PCR once a year, probably for several weeks to generate that resource. That way we don't have to do it continually, we can just use those samples until they run out. We can easily get 5,000 or sometimes 10,000 arrays after one PCR effort.

Are you looking to add to your current offering?

Well, we have been spotting microRNA arrays for about six months using the Ambion kit. We have been experimenting with printing proteins. So we print proteins not just on the glass slides, but also into 96-well plates.

Which commercial platforms do you use?

About two years ago we needed to provide a platform so that people could carryout whole-genome gene expression studies, and because there wasn't really anything else available we decided to purchase the Affymetrix platform. That served not just for gene expression but also for genotyping and other applications.

Since then other commercial platforms have become available, for example Illumina, which is technically very robust, has been used for human and mouse whole-genome expression, and we now have that in-house as well.

As far as NimbleGen is concerned, we entered into some discussion with them and introduced them to the institute and individual researchers have started having discussions on how they could provide a solution for them. The obvious disadvantage for them is that in the UK you cannot buy NimbleGen arrays and have them delivered to your lab [because of IP issues]. You can either have the company carry out your assay for you in Iceland, or you can set up your own lab in Iceland. So you can have a core lab agreement where you can have a dedicated researcher based in Iceland. So that's a disadvantage. But quite a few Sanger Institute researchers have been using NimbleGen already, particularly for array CGH applications where they want to get higher resolution.

During your talk you said that you are currently looking at different data analysis and management tools. Can you tell me what you are considering using?

Well I was trying to raise two issues. One of them is the fact that a lot of people are now embarking on very big studies. For example, there is one group that is going to be carrying out something like 200 hybridizations within one study. They wanted to have informatics tools for managing their data, in terms of wanting to know where experiments and samples were kept, and that sort of thing. So that's one client.

One of the other things that we've realized is that people are finding the limits of software like GeneSpring because they feel that it cannot manage the hundreds of experiments that people want to manage side by side. So our microarray research group has decided that they will explore all of the commercially available platforms to see which the best ones are so that we'll be in a position to recommend it or get it in house so people can use it.

There are currently about six large platforms being assessed at the moment.

Is the ideal to just have one package?

In an ideal world, it would be good to just go with one. But my experience with dealing with so many different [researchers] is that they want to have a choice. And so a few years ago we invested in what we saw as the best possible software on the market. We got it in-house and said this is what we were going to support. But then a couple months later another researcher started using a completely different software and expected us to support that as well, and it's just the way a large institute works. Different people from different labs have their own way of doing things.

File Attachments
The Scan

Study Links Evolution of Longevity, Social Organization in Mammals

With the help of comparative phylogenetics and transcriptomics, researchers in Nature Communications see ties between lifespan and social organization in mammals.

Tumor Microenvironment Immune Score Provides Immunotherapy Response, Prognostic Insights

Using multiple in situ analyses and RNA sequence data, researchers in eBioMedicine have developed a score associated with immunotherapy response or survival.

CRISPR-Based Method for Finding Cancer-Associated Exosomal MicroRNAs in Blood

A team from China presents in ACS Sensors a liposome-mediated membrane fusion strategy for detecting miRNAs carried in exosomes in the blood with a CRISPR-mediated reporter system.

Drug Response Variants May Be Distinct in Somatic, Germline Samples

Based on variants from across 21 drug response genes, researchers in The Pharmacogenomics Journal suspect that tumor-only DNA sequences may miss drug response clues found in the germline.