Development and clinical testing of a simple, low-density gel element array for influenza identification, subtyping, and H275Y detection.

The objectives of this study were to develop a user-friendly, gel element microarray test for influenza virus detection, subtyping, and neuraminidase inhibitor resistance detection, assess the performance characteristics of the assay, and perform a clinical evaluation on retrospective nasopharyngeal swab specimens. A streamlined microarray workflow enabled a single user to run up to 24 tests in an 8h shift. The most sensitive components of the test were the primers and probes targeting the A/H1 pdm09 HA gene with an analytical limit of detection (LoD) <100 gene copies (gc) per reaction.

Simplified microarray system for simultaneously detecting rifampin, isoniazid, ethambutol, and streptomycin resistance markers in Mycobacterium tuberculosis.

We developed a simplified microarray test for detecting and identifying mutations in rpoB, katG, inhA, embB, and rpsL and compared the analytical performance of the test to that of phenotypic drug susceptibility testing (DST). The analytical sensitivity was estimated to be at least 110 genome copies per amplification reaction. The microarray test correctly detected 95.

Development of a simple, low-density array to detect methicillin-resistant Staphylococcus aureus and mecA dropouts in nasal swabs.

Detection of methicillin-resistant Staphylococcus aureus (MRSA) is important for prevention and control of MRSA infections, but the discovery of mecA dropouts and SCCmec junction sequences with homology to coagulase-negative staphylococci (CoNS) has challenged several real-time PCR tests. The objective of this study was to develop a user-friendly, gel element microarray test for MRSA detection, to estimate the analytical performance characteristics of the test on bacterial isolates, and to perform an initial evaluation of the test on nasopharyngeal swabs from patients known to have a high prevalence of S. aureus containing mecA dropouts.

PoPS: a computational tool for modeling and predicting protease specificity.

Proteases play a fundamental role in the control of intra- and extracellular processes by binding and cleaving specific amino acid sequences. Identifying these targets is extremely challenging. Current computational attempts to predict cleavage sites are limited, representing these amino acid sequences as patterns or frequency matrices.

PoPS: a computational tool for modeling and predicting protease specificity.

Proteases play a fundamental role in the control of intra- and extra-cellular processes by binding and cleaving specific amino acid sequences. Identifying these targets is extremely challenging. Current computational attempts to predict cleavage sites are limited, representing these amino acid sequences as patterns or frequency matrices.