Identification and testing of control peptides for antigen microarrays.
BACKGROUND
Peptide microarray slides usually contain positive control spots to gauge for antibody binding. Unlike the good response on earlier prototype microarrays, human immunoglobulin controls do not function consistently on newer generation slides. This may be due to technical problems in high-density printing or degradation. Our objective was to identify and print reliable control peptides that did not suffer from the same problems as proteins.


METHODS
Peptide microarray slides containing 10,000-23,000 synthetic peptides spanning proteins involved in M. tuberculosis or Bordatella pertussis were incubated with secondary antibody in sample dilution buffer. After removal of artefacts due to slide architecture, we identified peptides that gave a high mean response and low co-efficient of variation across all replicates. These control peptides were tested for their performance on newly manufactured slides.


RESULTS
We selected three peptides on the TB slides and three peptides on the B. pertussis slides that had a mean response index of at least 5 and a coefficient of variation less than 15%. When used as controls in newly-designed slides, these peptides gave consistently high responses: the median index ranged from 4.5 to 9.5 in the absence of patient serum and was of a somewhat lesser magnitude when incubated with patient serum. We illustrate the use of these control responses to normalize the peptide responses on a set of slides prepared with human serum.


CONCLUSIONS
Our work shows that it is possible to identify control peptides that can be used when protein controls do not function consistently. This has important consequences for the storage of peptide-microarrays and their use in the field: protein chips need to be kept at +4 degrees C while peptide chips can be kept at room temperature. Although we focused on TB and B. pertussis, our methodology has relevance for any disease or disorder where peptide arrays are used to assess immune response.
Ngo
Yen
Y
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Sweden.
Advani
Reza
R
Valentini
Davide
D
Gaseitsiwe
Simani
S
Mahdavifar
Shahnaz
S
Maeurer
Markus
M
Reilly
Marie
M
D000595:Amino Acid Sequence; D000906:Antibodies / Q000276:immunology / Q000378:metabolism*; D000942:Antigens, Bacterial / Q000276:immunology / Q000378:metabolism*; D001886:Bordetella pertussis / Q000276:immunology; D006801:Humans; D008969:Molecular Sequence Data; D009169:Mycobacterium tuberculosis / Q000276:immunology; D010455:Peptides / Q000276:immunology / Q000378:metabolism*; D040081:Protein Array Analysis / Q000379:methods*; D015203:Reproducibility of Results; D012984:Software
D000906:Antibodies; D000942:Antigens, Bacterial; D010455:Peptides