Pathogen Detection and Identification Traditional microbial detection and identification methods are based on phenotypic traits, such as ability to grow on certain carbon sources or catalyze the conversion of specific substrates. While the use of genotypic methods, such as DNA sequencing or PCR, now provides greater discrimination and precision, microarrays offer a highly multiplexed capability to rapidly detect and identify multiple pathogens simultaneously in complex backgrounds.
In an initial demonstration of multiple pathogen detection capability, Wilson et al., developed the Multi-Pathogen Identification (MPID) microarray that detects eighteen different pathogenic viruses, prokaryotes, and eukaryotes, including several CDC Category A and B biothreat agents. In this study, researchers amplified unique regions of DNA from each microorganism that acted as genetic signatures, and then used the microarray to detect the absence or presence of pathogen-specific signatures. In some cases, the limit of detection was found to be as little as 10 femptograms (less than 10 genome equivalents) of Bacillus anthracis DNA, much below the detection limits of other existing technologies.
Affymetrix arrays could also be used to detect hundreds of more common, naturally occurring pathogens that present similar clinical symptoms, such as febrile respiratory illness caused by streptococci or influenza, enabling physicians to quickly determine the etiological agent responsible for the patients’ disease. Recent work by Davigon et al. examined the ability of a CustomSeq Array to detect Streptococcus pyogenes, which is a member of Group A Strep (GAS), and is the causative agent for several diseases ranging from pharyngitis (strep throat) to acute rheumatic fever. In comparing the detection of GAS in human clinical samples (either nasal wash or throat swab) using the GeneChip resequencing array to the conventional "gold standard" culture method, they found 95% (18 of 19 samples) concordance. In addition, they were able to determine erythromycin resistance in 13 of the 19 samples. Further, since this resequencing array was designed to simultaneously detect the presence of numerous upper
respiratory tract pathogens (RPM or Respiratory Pathogen Microarray), the group also detected co-infection of S. pneumoniae in eight of the samples, Bordetella pertussis in 6 samples, and adenovirus in two samples, clearly demonstrating that microarray-based analysis can provide broad spectrum surveillance of respiratory pathogens.
In another multi-pathogen detection effort, investigators at Affymetrix (Xing, G. et al.), in collaboration with Institut Pasteur, are developing a microarray-based pathogen detection method that can be used to type multiple pathogens in a single experiment, with high sensitivity and specificity. In addition, this technology will be used to identify genetically manipulated strains, through the detection of antibiotic resistance and toxin genes. This goal of this project, funded by a grant from the National Institute of Allergy and Infectious Diseases (NIAID), is to develop a comprehensive, single-step test capable of simultaneous identification of genetic fingerprints for over 50 bacterial and viral species selected from the NIAID high-priority pathogen list. As a result, this array could take the place of dozens of existing tests.
Another important attribute of microarray technology is the ability to identify all members of a complex microbial community or to identify a group of closely related organisms down to the species level. Because all organisms contain distinct genetic compositions and microarrays are able to examine all gene sequences, GeneChip microarrays are an ideal tool for this application. DeSantis et al. developed a Custom Express Array with 65,358 probes that represent the ribosomal RNA (small subunit) genes from numerous prokaryotic and eukaryotic microorganisms, allowing the group to identify up to 8,989 different taxa simultaneously. By adding known quantities of rRNA gene copies from diverse organisms to the nucleic acids extracted from natural outdoor aerosol samples, they were able to correlate signal intensity on the array across a 30-fold difference in rRNA sequence concentration, demonstrating the ability to quantify the identified taxa. This array was employed to study the microbial composition of
aerosol samples collected from various geographic regions during different seasons, providing a quantitative assessment of microbial diversity in an environmental background.
In a different study, Couzinet et al. used a custom GeneChip Staphylococcus Array to identify 201 different Staphylococcus strains to the species level in just 5 hours based on 16S ribosomal RNA gene sequence. These 201 strains represented 33 different species and consisted of 105 human clinical isolates, 27 veterinary isolates, 30 food specimens, 1 environmental isolate, 20 type strains, and 18 strains of unknown origin. In comparing the identification of all isolates using the GeneChip array to the "gold standard" ribosomal DNA sequence method, they found 92% (185 of 201 samples) concordance. Of the 16 incorrect identifications, all were consistently misidentified and were limited to 3 species; S. carnosus, S. lugdunensis, and S. saprophyticus. Analysis of the 16S rRNA sequences present on the array revealed only 1 or 2 nucleotide mismatches between the correct sequence and the misidentified sequence, which can be resolved through redesign of the relevant probes on the GeneChip array.
References
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Wilson, W. J. et al. Sequence-specific identification of 18 pathogenic microorganisms using microarray technology. Mol Cell Probes16: 119-27 (2002).
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Davigon, L. et al. Use of Resequencing Oligonucleotide Microarrays for Identification of Streptococcus pyogenes and Associated Antibiotic Resistance Determinants. J. Clin. Microbiol.43: 5690-5695 (2005).
DeSantis, T.Z. et al. Rapid quantification and taxonomic classification of environmental DNA from both prokaryotic and eukaryotic origins using a microarray. FEMS Microbiology Letters245: 271-278 (2005).
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Couzinet, S. et al. High-density DNA probe arrays for identification of staphylococci to the species level. J. Microbiol. Methods61: 201-208 (2005).
Related Scientific Publications
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Troesch, A. et al. Mycobacterium species identification and rifampin resistance testing with high-density DNA probe arrays. J. Clin. Microbiol.37: 49-55 (1999).
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Wilson, K.H. et al. High-density microarray of small-subunit ribosomal DNA probes. Appl. Environ. Microbiol.68: 2535?2541 (2002).
Traditional microbial detection and identification methods are based on phenotypic traits, such as ability to grow on certain carbon sources or catalyze the conversion of specific substrates. While the use of genotypic methods, such as DNA sequencing or PCR, now provides greater discrimination and precision, microarrays offer a highly multiplexed capability to rapidly detect and identify multiple pathogens simultaneously in complex backgrounds.
In another multi-pathogen detection effort, investigators at 
