Optimization and clinical validation of a pathogen detection microarray

Christopher W. Wong¹, Charlie Lee Wah Heng², Leong Wan Yee¹, Shirlena W. L. Soh³, Cissy B. Kartasasmita⁴, Eric A. F. Simoes⁵, Martin L. Hibberd³, Wing-Kin Sung² and Lance D. Miller¹

¹Genomic Technologies, ²Computational & Mathematical Biology, ³Infectious Diseases, Genome Institute of Singapore, SINGAPORE; ⁴Department of Pediatrics, Faculty of Medicine, Universitas Padjadjaran, INDONESIA; ⁵Section of Infectious Diseases, The University of Colorado School of Medicine and The Children’s Hospital, Denver, CO, USA.

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This page contains supplementary information for the paper of the same name published in Genome Biology, 2007, 8:R93 doi:10.1186/gb-2007-8-5-r93

[Abstract] [Article pdf]

• Supplementary Methods
• Supplementary Figures
• Supplementary Tables
• Pathogen Microarray Data
• Software downloads

Supplementary Methods

1. Sample Amplification and Microarray Protocols [PDF]

2. RT-PCR Modeling and Amplification Efficiency Score (AES) [PDF]

3. Pathogen Detection Algorithm (PDA) [PDF]

Supplementary Figures

Figure S1. Probe design schema. Probes (40-mers) were tiled at an average 8-base resolution across each of the 35 viral genomes in the manner depicted above. Numbers represent the start and end positions of each probe. [JPG]

Figure S2. Choice of primer tag in random RT-PCR has significant effect on PCR efficiency. (A) Heatmap of probe signal intensities for a clinical hMPV sample following random RT-PCR using original primer A1 or (B) AES-optimized primer A2. [GIF] [TIFF]

Figure S3. Comparison of amplification efficiency of original primer A1 and AES-optimized primer A2. RNA from patients infected with RSV B (n=5) or hMPV (n=3) were reverse-transcribed and amplified using primer A1 or A2 and the percentage of r-signature probes with signal above detection threshold was determined. [JPG]

Figure S4. Diagnostic PCR results for RSV Patient #412 show that patient does not have a coronavirus infection. (A) PCR using Pancoronavirus primers. Lane 1: 1 kb ladder, Lane 2: blank, Lane 3: OC43 coronavirus positive control, Lane 4: 229E coronavirus positive control, Lane 5: RSV patient #412, Lane 6: PCR primers and reagents only, as a negative control. (B) PCR using OC43 specific primers. Lane 1: 50 bp ladder, Lane 2: blank, Lane 3: OC43 coronavirus positive control, Lane 4: RSV patient #412, Lane 5: purified RSV from ATCC, Lane 6: PCR negative control. (C) PCR using 229E specific primers. Lane 1: 229E coronavirus positive control, Lane 2: RSV patient #412, Lane 3: PCR negative control, Lane 4: 1 kb ladder. [JPG]

Supplementary Tables

Table S1. List of genomes represented on the pathogen detection microarray. [HTML]

Table S2. Comparison of E-Predict and PDA algorithms. [HTML]

Pathogen Array Data

All microarray data has been deposited in NCBI’s Gene Expression Omnibus and are accessible through GEO Series accession number: GSE7779

Alternatively, zip data file of all arrays described in the paper can be downloaded here: [ZIP] (27 MB)

Files may be opened using Microsoft Excel. In each data file, the 1^st column represents probe ID, signal intensities for each replicate in columns v2-v8, followed by median signal intensity and log₂-transformed median signal intensity.

Software Downloads

Amplification Efficiency Score software:

· Primerselect Readme.txt [download]

· Primerselect.java [download]

Pathogen Detection Algorithm (PDA):

· WKL Readme.txt [download]

· WKL.cpp [download]

Contact authors at wongc@gis.a-star.edu.sg

Last updated 5.28.2007