Clinical Laboratory Strategies: September 9, 2010

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Using LIPS to Detect Lyme Disease
Will this technology be adopted in clinical labs?
By Genna Rollins

Current guidelines recommend a two-tier testing approach for Lyme disease diagnosis, with an immunoassay or immunoflourescence assay followed by Western blot testing for positive or borderline results. However, this strategy is costly, time-consuming, and has limited sensitivity in the early stages of infection. National Institutes of Health scientists recently evaluated the performance of a luciferase immunoprecipitation system test as a potential Lyme disease diagnostic, and this issue of Strategies reports on their findings. 

Immunoassays are the backbone of Lyme disease diagnostics, and in fact, the Centers for Disease Control and Prevention recommends a two-tier testing algorithm for the disease comprised of an initial immunoassay or immunoflourescence assay followed by Western blot testing for positive or borderline results. However, these assays have limited sensitivity in the early stages of infection, and the interpretation of Western blot bands can be subjective. In addition, the immunoassays involve time-consuming and tedious serum dilutions. These limitations prompted researchers at the National Institute of Dental and Craniofacial Research (NIDCR) and the National Institute of Allergy and Infectious Diseases to explore the use of a luciferase immunoprecipitation system (LIPS) test as a potential diagnostic for Lyme disease (Clin Vaccine Immunol 2010;17:904-9).

“With solid phase assays like ELISA or Western blot, you have to perform these cumbersome dilutions and calculations. But LIPS is a very scalable technology that enables you to genetically tag antigens with luciferase, and if the patient sample has antibodies, it will bind to the tagged protein. You then can further trap all the immunoglobulins using generic reagents,” explained lead author Peter Burbelo, PhD, research scientist at NIDCR. “One of the really remarkable things about luciferase enzyme used in the LIPS assay is that it’s linear over a million-fold range. This dynamic range creates a very big break between positive and negative reactions, so it offers less ambiguity in terms of who is positive and who is negative.”  

Burbelo believes that with further validation, LIPS could be particularly important in serial monitoring of patients’ response to therapy, in establishing how their antibody titers change over time, and in better characterizing the spectrum of Lyme disease. “The real need in the Lyme disease field is to look at patients longitudinally and monitor how their titers change over time. Because of the incredible signal and robustness of the LIPS assay, it may be more informative than ELISA where you just don’t get that much umpf from the signal,” he said. “It may be a way of understanding how different patients have different symptoms.”

LIPS has been used in autoimmune disorder testing such as type 1 diabetes, and to detect certain filarial, helminthic, and viral infectious agents, but the method has not been explored with bacterial pathogens, according to Burbelo. The assay is based on fusion of protein antigens to a light-emitting enzyme reporter, Renilla luciferase (Ruc). These antigen fusions in turn are used in immnoprecipitation assays with serum samples and protein A/G beads. After the beads are washed, the level of light production is measured, which gives highly quantitative antibody titers, according to the authors. As a liquid phase assay, LIPS, combined with the highly linear light output of the luciferase report, enables some antibodies to be detected without serum dilution over a wide range of detection, often spanning several orders of magnitude.

“This is particularly useful for Lyme disease because we can get an incredible dynamic range of essentially five or six logs without diluting the sera. There’s a need for that in therapeutic monitoring. You want to know what happens over time after you give the patient a course of antibiotics,” said Burbelo. “Their titers might drop a log after treatment, but on another assay it might not even be detected.” 

The researchers assembled synthetically and constructed a panel of 15 different Borrelia burgdorferi antigens as C-terminal fusions with Ruc. Using a training set of 46 samples, including 38 from patients with various manifestations of Lyme disease, they visualized immunoreactivities to this antigen panel with a heat map that graphically displayed the antibody responses on a log10 scale. The two most sensitive and specific antigens in the panel were VlsE-∆2 and VlsE-∆1, but they still had “less than optimal” performance. This lead the authors to create a new antigen, VOVO, which is a synthetic recombinant protein with two alternating copies of immunoreactive peptides from the IR6 region of VlsE and the conserved C-terminal region of OspC. The peptides were derived from different strains of Borrelia, B. burgdorferi B31, which is predominant in the U.S., and B. garinii IP 90, which is common in Europe. The researchers posited that the repeated antigenic peptides from different immunodominant epitopes in VOVO would detect more divergent strains, increase sensitivity through cooperative binding, thereby capturing low-affinity and/or low-titer antibodies.

VOVO proved to be the most useful antigen that the researchers evaluated, with a geometric mean titer (GMT) of 106,400 light units (LU) in the training set of patients with Lyme disease compared with a GMT of 559 LUs for controls. The researchers also tested VOVO in a validation set of 139 samples and found that the mean anti-VOVO antibody titer in patients with Lyme disease was 272,000 LUs versus 262 LUs in controls, a 1,038-fold difference. Using a cutoff of the control group mean plus 5 standard deviations, the VOVO LIPS test had 98% sensitivity and 100% specificity, compared with 98% sensitivity and specificity for a C6 ELISA test.

Researchers not involved with the study agreed that there is a need for Lyme disease diagnostics to capture the variability of the infection. “The antigens are somewhat variable. There are amino acid sequence differences between various strains of the organism,” explained Raymond Dattwyler, MD, professor of medicine and division chief of allergy/immunology and rheumatology at New York Medical College. “C6 is a very popular test and it’s based on one antigen. When it first came out, the thought was that C6 was very well conserved. But as more studies came out we realized that the C6 sequence had variability and that the variability made a difference, where initially it wasn’t thought to.”

Although the study “shows LIPS is a workable system and has some advantages,” Dattwyler questioned how readily the technology would be adopted. “Almost everybody uses ELISA and there’s a multiplex system out there already. I’m not aware of any major labs using LIPS, and it’s pretty unrealistic to think that we’re going to get them to buy into a new system in this day and age because of cost issues.”

Whether or not labs eventually adopt LIPS, Dattwyler indicated that the study should prompt laboratorians to take a close look at their assay methods for detecting Lyme disease. “They should start to think about moving away from whole Borrelia ELISAs. That’s still a very common assay, but it’s pretty primitive. They need to start thinking about using peptide-based assays or more limited antigen-type assays,” he said. “The LIPS test is along that evolutionary pathway.”

Burbelo and his colleagues have published about 25 studies involving LIPS and currently are investigating further validation of the test in a larger population of Lyme disease patients, as well as development of a point-of-care LIPS application. An online protocol and technical video of the LIPS assay is available via the Journal of Visualized Experiments at

Dr. Dattwyler serves on the CDC committee that produced the current Lyme disease diagnostic recommendations. His lab developed the first multi-antigen FDA approved test for Lyme disease and is developing a multiple peptide antigen test for Lyme disease.

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