Protein microarrays: A new tool for profiling antibody cross-reactivity

Invitrogen Protein Microarray Center, 688 E Main St, Branford, CT 06405, USA.
Human antibodies 02/2005; 14(1-2):7-15.
Source: PubMed


Antibody cross-reactivity can compromise interpretation of experiments and derail therapeutic antibody development. Standard techniques such as immunohistochemistry or Western analysis provide important but often inadequate approaches to assess antibody specificity. Protein microarrays are providing a new approach to rapidly characterize antibody cross-reactivity against 1,000s of proteins simultaneously. This review will focus on reported examples of antibody cross-reactivity, methods used to characterize them, and the recent development and use of protein microarrays for assessing antibody specificity.

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    • "However, in the present series of CSF-NIND samples, there was no antigen-specific reactivity for either of the antibodies and the PTR 3 level also was not detected. There are several reports of cross-reactive antibodies that may recognize very similar epitopes from unrelated targets and the antigen-specific antibodies detected in some CSF-OIM may be related to cross reactivity with other infectious microorganisms rather than previous mycobacterial latent infection (Michaud et al. 2003, Predki et al. 2005). In the CSF-OIM of the present series, which were infected with S. pneumoniae and Cryptococcus, a mycobacterial antigen-specific reaction was observed mainly for IgA-16 kDa and the Lionex kit. "
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    ABSTRACT: To evaluate commercial Lionex TB together with four antigens of Mycobacterium tuberculosis (MPT-64, MT10.3, 16 kDa and 38 kDa) for IgG and IgA cerebrospinal fluid (CSF) detection in the diagnosis of tuberculosis meningitis (TBM) with CSF negative acid-fast bacilli staining, 19 cases of TBM, 64 cases of other infectious meningoencephalitis and 73 cases of other neurological disorders were tested by enzyme linked immunosorbent assay. IgA-MPT-64 and IgG Lionex showed the highest sensitivities, specificities, positive predictive value and negative predictive value (63.2%, 47.4%; 95%, 93.7%; 40%, 98% and 28.4%, 97.1%, respectively). However, while grey zone was 12.7% and 6%, respectively, lowering sensitivity but maintains high specificity (>or= 95%). High protein concentration in CSF was associated with antibody positivity CSF/HIV+ which did not influence the sensitivity of both tests. To our knowledge, this is the first description of IgA-MPT-64 and IgG Lionex antibodies in CSF-TBM and, although there is good specificity, adjustments are needed based on antigen composition to enhance sensitivity.
    Memórias do Instituto Oswaldo Cruz 08/2010; 105(5):722-8. DOI:10.1590/S0074-02762010000500022 · 1.59 Impact Factor
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    • "This may in part explain why certain immune epitopes from the same protein are recognized exclusively in TB+ and not in TB− individuals. Second, there is a vast literature concerning ‘crossreactive’ antibodies that may recognize very similar epitopes from unrelated targets [26], [27] or from closely related proteins, e.g. TB10.3 and TB12.9 in the case of peptides derived from TB10.4 [28]. "
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    ABSTRACT: Serum antibody-based target identification has been used to identify tumor-associated antigens (TAAs) for development of anti-cancer vaccines. A similar approach can be helpful to identify biologically relevant and clinically meaningful targets in M. tuberculosis (MTB) infection for diagnosis or TB vaccine development in clinically well defined populations. We constructed a high-content peptide microarray with 61 M. tuberculosis proteins as linear 15 aa peptide stretches with 12 aa overlaps resulting in 7446 individual peptide epitopes. Antibody profiling was carried with serum from 34 individuals with active pulmonary TB and 35 healthy individuals in order to obtain an unbiased view of the MTB epitope pattern recognition pattern. Quality data extraction was performed, data sets were analyzed for significant differences and patterns predictive of TB+/-. Three distinct patterns of IgG reactivity were identified: 89/7446 peptides were differentially recognized (in 34/34 TB+ patients and in 35/35 healthy individuals) and are highly predictive of the division into TB+ and TB-, other targets were exclusively recognized in all patients with TB (e.g. sigmaF) but not in any of the healthy individuals, and a third peptide set was recognized exclusively in healthy individuals (35/35) but no in TB+ patients. The segregation between TB+ and TB- does not cluster into specific recognition of distinct MTB proteins, but into specific peptide epitope 'hotspots' at different locations within the same protein. Antigen recognition pattern profiles in serum from TB+ patients from Armenia vs. patients recruited in Sweden showed that IgG-defined MTB epitopes are very similar in individuals with different genetic background. A uniform target MTB IgG-epitope recognition pattern exists in pulmonary tuberculosis. Unbiased, high-content peptide microarray chip-based testing of clinically well-defined populations allows to visualize biologically relevant targets useful for development of novel TB diagnostics and vaccines.
    PLoS ONE 02/2008; 3(12):e3840. DOI:10.1371/journal.pone.0003840 · 3.23 Impact Factor
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