ay
The w
of the
array Microarrays allow researchers to study proteins on a grand scale.
T
he culinary arts and the central dogma of molecular biology have a lot in common. If the DNA is the cookbook and the mRNA is the copied-out recipe, then proteins are the final presentation of the dish. Anybody who has choked down a well-intentioned but poorly executed meal knows that a recipe can have many possible outcomes; a skilled cook knows where to tweak the instructions and add the appropriate seasonings. Similarly, the cellular “chef” often embellishes a protein’s basic amino acid ingredients with posttranslational modifications, but there’s no way to divine these changes by looking at the DNA or RNA recipe alone. DNA microarrays were developed in the early 1990s to study those nucleic acid recipes in a massively parallel fashion, and by all accounts, they have been very successful research © 2 0 0 7 A m e r i ca n C h e m i ca l S o c i e t y
Jennifer Griffiths
and diagnostic tools. But scientists knew from the beginning that DNA microarrays were only revealing the basic instructions for protein synthesis, and efforts to capture proteins on a chip were soon under way. “Proteins are much more relevant than DNA because they reflect the physiological state of cell activities,” says Thomas Joos of the Natural and Medical Sciences Institute at the University of Tübingen (Germany). However, transitioning to protein chips has turned out to be a complex and challenging process.
Protein arrays come in many flavors
DNA microarrays consist of known complementary DNA (cDNA) or oligo probes that are designed to capture complementary mRNAs from the cellular milieu. The level of mRNA expression from certain genes gives scientists or clinicians information about which genes have been turned on within a particular cell. “With DNA arrays, ~98% of experiments have one goal and that is to measure expression levels of mRNAs,” D E C e m b e r 1 , 2 0 0 7 / A n a l y t i ca l C h e m i s t r y
8833
“The bottleneck comes down to content: what are the actual molecules that you are arraying, and how can you get your hands on them?”
says Gavin MacBeath of Harvard University. “Where protein arrays differ is that there are really two different aspects to the protein array field that are quite different in nature.” These two divisions have distinct goals and challenges that hardly overlap (Figure 1).
The two-antibody problem
Quantitative arrays capture proteins expressed within a cell and quantify expression levels; the tough part is the way those proteins are captured. “The applications of microarrays to proteomics are very similar to the applications of DNA microarrays to molecular biology or whole-genome profiling,” says Samir Hanash of the Fred Hutchinson Cancer Research Center. Functional array Quantitative array Reverse-phase array “Where it’s a little bit problematic is that unlike Incubation with Incubation with Incubation with DNA microarrays where you can array DNA for every gene, here we are proteins and fluorescently labeled protein detection antibody kind of short on capture detection antibodies or small molecule agents that are proteomewide in terms of their coverage.” Capturing DNA or RNA is straightforward and easy to predict: A Functional array Quantitative array Reverse-phase array pairs with T (or U), C pairs with G. “With DNA FIGURE 1. Different types of protein microarrays. you know from the sequence exactly how two One subset of the field makes quantitative arrays, which are strands are going to interact. You can calculate it,” says Brian analogous to DNA arrays: their purpose is to measure levels Haab of the Van Andel Institute. “But it’s completely empirof protein expression within a cell or tissue. This type of array ical at this point with proteins, so on a number of levels, it’s displays antibodies or other capture agents on its surface. A cell more complicated.” or tissue lysate or a serum sample is applied to the chip, the anMost quantitative arrays use antibodies as capture agents, tibodies selectively bind their target proteins, and the captured but a huge limitation to that method is that only a very small proteins are detected through a sandwich assay with a second, set of well-characterized antibodies are currently available. fluorescently labeled antibody. Add to that the fact that in most cases, two high-affinity, highMore recently, quantitative array researchers have been de- specificity antibodies are required—one for capture and one veloping reverse-phase protein arrays, which bypass the need for detection in a sandwich assay—and the pool is whittled for a capture antibody. In this type of array, the crude cellu- down even further. lar lysate is spotted directly onto the chip’s surface and then probed with a fluorescently labeled antibody. Instead of having Taking the bite out of the sandwich assay a variety of antibodies displayed on the surface of a single chip, Some researchers are trying to remove the need for two anas traditional quantitative arrays do, a reverse-phase experiment tibodies altogether. “We have to get away from the sandwich would spot the lysate on several different chips and then assay assay because it is severely limiting the library of analytes that each one with a single antibody. Besides halving the number we can effectively measure,” says Emanuel Petricoin of George of antibodies required to detect a protein, reverse-phase arrays Mason University. Petricoin and his colleague Lance Liotta, also have the advantage of needing only a very small cell or tis- also of George Mason University, created the reverse-phase sue sample for analysis. microarray to address this issue. “We needed to come up with The other subset of the field is called functional protein ar- different platforms that only require single antibodies, and rays. The purpose of this type of array is to quickly probe the that’s exactly what the reverse-phase array was developed for,” activity of a given protein against many targets simultaneously. he says. A functional protein chip consists of individual spots of purified But using just a single antibody also has drawbacks. Petproteins, usually from a whole proteome or subproteome. This ricoin cautions that researchers have to carefully choose and type of microarray has diverse applications, but as an example, a validate the antibody they use. “One of the nice attributes of binding interaction profile of a given protein could be assessed a sandwich assay is you increase your specificity by using two by applying a fluorescently labeled form of the protein to the antibodies, so that if you have a report that the analyte is there, chip and then monitoring where that protein binds (Figure 2). you have pretty high confidence that it is the analyte and not 8834
A n a l y t i ca l C h e m i s t r y / D E C e m b e r 1 , 2 0 0 7
FIGURE 2. A protein microarray containing 1133 purified protein spots is probed with fluorescently labeled antibodies. (Adapted with permission from Ref. 2. Copyright 2007 National Academy of Sciences, U.S.A.)
your antibody cross-reacting with something else,” he says. “With a one-antibody configuration, you are basically hanging yourself on the fact that the antibody is specific. It’s the Achilles’ heel of this approach and others, like immunohistochemistry, that rely on a one-antibody reaction.” So, although reverse-phase arrays somewhat ameliorate the antibody problem, Petricoin says that new antibodies are still sorely needed. “If you asked me, ‘What do you need? What would . . . make this work even better?’ I would say, ‘Just a great cadre of validated and well-performing antibodies.’” He adds, “The more we have of those, the more we’re going to be able to look at with confidence.” Hanash thinks that to fix the problem, a more organized effort to create good antibodies is necessary. “I’ve been advocating for many years now for NIH [National Institutes of Health] to invest in making capture agents,” he says. “NIH money is going into people buying antibodies that don’t work or buying antibodies that stay in their own freezer or refrigerator, and if the NIH were to take on that initiative more directly, then that set of reagents becomes available for everyone.” He also points out that these capture agents would be useful not just to protein microarray researchers but also to investigators in other fields. Though not formally organized by the NIH, projects do exist to address this problem. Michael Taussig and Oda Stoe vesandt of the Babraham Institute (U.K.) are coordinating ProteomeBinders, a European initiative that aims to provide a high-quality binder for every component of the human proteome (1). The program’s goals also include establishing criteria and methods for quality assessment and validation of antibodies and other binders, establishing a bioinformatics platform to display information on characterization of individual binders, and planning the long-term production strategy for binders. To work toward these goals, members of the project hold regular workshops, and the consortium posts information on the results of its activities online (www.proteomebinders.org).
Lessons in cloning and protein purification
In some ways, the major challenge faced in the functional protein microarray field is very similar to the antibody problem faced by the quantitative microarray researchers. “Really, the bottleneck in this area comes down to content: what are the actual molecules that you are arraying, and how can you get your hands on them?” asks MacBeath. In the case of quantitative arrays, the dearth of good antibodies is the limiting factor, but in the case of functional arrays, the purified proteins displayed on the surface of the chip can be difficult to come by. The more proteins displayed on the chip, the more tedious protein expression and purification can get. “The biggest challenge is, first, how do you make 10,000 different proteins?” asks Niroshan Ramachandran of Harvard Medical School. The initial step is to clone the genes of interest into expression vectors. Luckily, this usually needs to be done only once; the clone can be used indefinitely and is often shared freely among the microarray research community. “Once you make the expression collection—that’s a large upfront investment—then it’s certainly much easier to make the protein,” says Michael Snyder of Yale University. From there, it is a matter of expressing and purifying the proteins. Expression can be complicated because not all eukaryotic proteins express or fold properly in E. coli, the expression microorganism that is the easiest to work with. The alternatives are eukaryotic expression systems such as yeast or baculovirus, which take much longer to grow and can be trickier to cultivate. Once the proteins are expressed, purification of all of those different isolates can be a big job. “You need a costly infrastructure to set up protein purification at a large scale,” says Ramachandran. “Very rarely do academic institutes have such resources.” But when all that work is done, the researcher is rewarded with lots of protein payoff. “Once you make these proteins, you usually get a fair amount and can print many, many arrays,” says Snyder. D E C e m b e r 1 , 2 0 0 7 / A n a l y t i ca l C h e m i s t r y
8835
For example, Ramachandran worked with Joshua LaBaer, also of Harvard Medical School, to develop a system called a nucleic acid programmable protein array (NAPPA), in which cDNA is printed onto the surface of glass slides, and then the surface of the chip is flooded with rabbit reticulocyte for transcription and translation. The researchers engineered their cDNA to express each target protein as a glutathione S-transferase (GST) fusion, which binds to antiGST antibodies codisplayed on the surface of the chip. “The advantage of the approach . . . is that because we are printing DNA, we can make sure our arrays are stable,” says Ramachan dran. “Most of our arrays we FIGURE 3. A piezoelectric microarrayer spots proteins on aldehyde-functionalized glass (3 ). actually store in our desk drawers. They’re not even stored in the fridge.” Taussig, Stoevesandt, and Mingyue He, also of the BabraKeeping functional arrays functional ham Institute, have taken the idea one step further and have Once researchers have proteins in hand, the challenge is to developed a new system they call DAPA (DNA array to protein keep those proteins functional through the arraying process array). Whereas NAPPA displays both the DNA and its coded and during the storage of the chip. “With proteins, like with protein on a single surface, DAPA uses a DNA template to human beings, each individual has its own personality,” says print the proteins onto a separate chip. “One of the basic ideas Heng Zhu of Johns Hopkins University. “So you can’t treat was that it would be quite useful if we could generate a protein them identically, like you would DNA or RNA.” array which is really separate from the DNA array, in contrast The printing process can be tough on some proteins (Figure to the NAPPA method,” says Stoevesandt. “And the other 3). “If you are printing 10,000 different proteins, you have to thought was, could we possibly reuse the DNA template?” _ 20 arrays from each make sure that the first protein that you print stays active until The group has found that they can print > you are done printing the last one,” says Ramachandran. “You DNA template without a significant drop in the quality of the have to make sure you have the buffer conditions optimized so printed protein. “We think this has the potential to build up your proteins don’t dehydrate while they’re waiting.” very high throughput or multiplexed arrays with very diverse Good hydration is key for long-term storage as well. “You proteins on them,” says Taussig. “But we are at the stage, renever let them dry out if you want to keep them active,” says ally, of getting the thing published first.” Snyder. “That’s probably the number one thing.” Fortunately, most proteins that are stable in solution tend to be stable on The functional array payoff the surface with proper hydration, says MacBeath. “If the pro- Obviously, a lot of work has gone into merely getting the protein is intrinsically unstable, however, you are kind of toast no teins displayed on the surface of functional arrays, but once matter what you do.” you’ve got your chip, what can you do with it? Unlike quantitative arrays, which are used almost exclusively to measure On-surface translation protein abundance, functional arrays have a diverse set of apSeveral groups are working on alternative approaches for getting plications. “Most of the applications can be put into one of two those proteins displayed on the surface (4, 5). Instead of the long categories,” says Gregory Michaud of Novartis, “one where process of expressing, purifying, and then printing the proteins, you’re looking for noncovalent interactions and another where these methods borrow DNA array technology and display the you are looking for covalent modification of proteins.” For exDNA or mRNA encoding the protein of interest on the surface ample, researchers have used functional protein arrays to proof the chip. The proteins are expressed with an in vitro transcrip- file noncovalent interactions of DNA, RNA, small molecules, tion/translation system and are captured in a variety of ways. lipids, and proteins and to examine several types of covalent 8836
A n a l y t i ca l C h e m i s t r y / D E C e m b e r 1 , 2 0 0 7
“Proteins are much more relevant than DNA because they reflect the physiological state of cell activities.”
posttranslational modifications, including the phosphorylation carried out by protein kinases. Functional protein arrays also have the potential to make significant impacts on drug-discovery programs. “In my opinion, the application of functional protein microarrays that has the potential to literally find the needle in the haystack is the identification of targets for small molecules of unknown mechanism of action,” says Michaud. “At least in theory, if you have an entire proteome on a surface and the proteins are all functionally displayed, you could identify both targets and off-targets within just a few hours of experimental time.” Off-target binding is a potential source of side effects once the drug is moved in vivo. Another exciting application of functional protein microarrays is in the field of immunology. People with autoimmune diseases such as lupus and rheumatoid arthritis generate antibodies that circulate in their bloodstream and recognize “self” antigens—proteins and other molecules that the immune system should ignore. Currently, the diagnostic standard for these diseases is the detection by ELISA of autoantibodies in a patient’s serum. If a patient has a suspected autoimmune disease, a doctor might order 8–10 different antibody tests to try to diagnose the disease. P. J. Utz and William Robinson of Stanford University are using microarrays of antigens to speed up and improve the process. “The nice thing about the arrays is not only can we identify those same 10 autoantigens, but we can do 100 more and really get a much more comprehensive picture of what kind of autoimmune disease [a patient] may have,” says Utz. The biggest improvements come at the fine-diagnosis level. Testing for hundreds of autoantibodies at the same time could help to diagnose a disease and to predict which patients would respond to a particular treatment. “It’s likely that within a clinical disease, there are multiple different distinct molecular diseases,” says Robinson. On the basis of a patient’s microarray autoantibody profile, a physician could customize a treatment plan targeted toward that patient’s particular disease.
the George Mason University CLIA-compliant proteomics laboratory. “Our laboratory work is now entering a phase where we think we have some very good phosphoprotein biomarkers that can tailor therapy, predict outcome, or prognose the course of a disease—the ability to validate these markers under CLIA guidelines accelerates the information to the bedside,” says Petricoin. Larry Kricka of the University of Pennsylvania says that several issues need to be worked out before the technology can be integrated into routine clinical use. “No one has really sat down and thought about how you’d actually do this in a clinical laboratory according to the current rules . . . [for] quality control,” he says. For example, for a chip intended to test for 100 different biomarkers, what do you do if validation for 10 of them fails? If all of the data from the chip is required for diagnosis, then all 100 tests must be repeated. “If you put a lot of tests onto one device, you’ve got all your eggs in one basket,” cautions Kricka. The other consideration is an ethical one that stems from the differences in how researchers and clinicians operate. Researchers tend to want to put as many tests as possible onto a chip, but clinicians are used to ordering one test at a time. For example, say a lab is using a chip designed to test for 20 biomarkers for 20 different diseases. A doctor orders 10 of those tests, but after analyzing the microarray, the lab has 20 results, not just those that the doctor ordered. Should a lab look at those 10 extra tests and alert the doctor if there is a problem? Should it hold the results in case the doctor orders the additional tests? Or should it just discard the extra results? All of these issues will need to be worked out before protein microarrays can become the effective clinical tools that many hope for, but many researchers are still optimistic. “I think that there’s a lot of exciting work in the field, and it’s a very exciting time,” says Robinson. “Ultimately, there will be probably multiple different protein array technologies that are going to get commercialized in the diagnostic arena. I think it’s going to be very powerful.”
The future: clinical applications?
Jennifer Griffiths is an associate editor of Analytical Chemistry.
Protein microarray research has been very promising, and researchers are cautiously optimistic about the field’s prospects for creating routine clinical tools. “One question I usually get asked is, ‘Do you think these will ever be something that you’ll be able to order for a patient in the clinic?’ And for years I used to say no,” admits Utz. But, he adds, “I think I’m starting to change my mind. Now I think there may ultimately be relatively small, multiplexed arrays that will actually be CLIAcertified.” (CLIA stands for Clinical Laboratory Improvement Amendments, which are quality standards that have been established for all laboratory testing to ensure the accuracy, reliability, and timeliness of patients’ test results regardless of where the test is performed.) In fact, many protein arrays are currently being tested in clinical trials, including the reverse-phase protein microarray technology, which is currently undergoing formal testing at
References (1) (2) (3) (4) (5)
Taussig, M. J.; et al. Nat. Methods 2007, 4, 13–17. Popescu, S. C.; et al. Proc. Natl. Acad. Sci. U.S.A. 2007, 104, 4730–4735. Stiffler, M. A.; et al. J. Am. Chem. Soc. 2007, 128, 5913–5922. Ramachandran, N.; et al. Science 2004, 305, 86–90. Tao, S. C.; Zhu, H. Nat. Biotechnol. 2005, 24, 1253–1254.
D E C e m b e r 1 , 2 0 0 7 / A n a l y t i ca l C h e m i s t r y
8837
