Skip to main page content

• HOME
• Current Issue
• Archive
• Alerts
• About ASM
• Contact us
• Tech Support
• Journals.ASM.org

This Article Abstract Full Text (PDF) Supplemental material Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Reprints and Permissions Copyright Information Books from ASM Press MicrobeWorld Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Davignon, L. Search for Related Content PubMed PubMed Citation Articles by Davignon, L.

 Previous Article  |  Next Article 

Journal of Clinical Microbiology, November 2005, p. 5690-5695, Vol. 43, No. 11
0095-1137/05/$08.00+0     doi:10.1128/JCM.43.11.5690-5695.2005

Use of Resequencing Oligonucleotide Microarrays for Identification of Streptococcus pyogenes and Associated Antibiotic Resistance Determinants

Louis Davignon,¹ Elizabeth A. Walter,^2,3 Kate M. Mueller,⁴ Christopher P. Barrozo,⁵ David A. Stenger,⁶ Baochuan Lin,^6* on behalf of the Epidemic Outbreak Surveillance Consortium,

Malcolm Grow Medical Center, Andrews Air Force Base, Maryland 20762,¹ Epidemic Outbreak Surveillance Advanced Diagnostics Laboratory, Lackland Air Force Base, San Antonio, Texas 78236,² Texas A&M University Systems, San Antonio, Texas 78223,³ Nova Research Inc., Alexandria, VA 22308,⁴ DoD Center for Deployment Health Research, Naval Health Research Center, San Diego, California 92152,⁵ Center for Bio/Molecular Science & Engineering, Code 6900, Naval Research Laboratory, Washington, DC 20375⁶

Received 25 February 2005/ Returned for modification 19 May 2005/ Accepted 15 August 2005

Top Abstract Introduction Materials and Methods Results Discussion References

 
Group A streptococci (GAS) are responsible for a wide variety of human infections associated with considerable morbidity and mortality. Ever since the first systematic effort by Lancefield to group Streptococcus species by M protein variants, the detection and characterization of Streptococcus by different methods have been an evolving process. The ideal assay for GAS identification not only would provide quick and accurate diagnostic results but also would reveal antibiotic resistance patterns and genotype information, aiding not only in treatment but in epidemiologic assessment as well. The oligonucleotide microarray is a promising new technology which could potentially address this need. In this study, we evaluated the usefulness of oligonucleotide resequencing microarrays for identifying GAS and its associated antibiotic resistance markers. We demonstrated an assay platform that combines the use of resequencing DNA microarrays with either random nucleic acid amplification or multiplex PCR for GAS detection. When detecting Streptococcus pyogenes from coded clinical samples, this approach demonstrated an excellent concordance with a more established culture method. To this end, we showed the potential of resequencing microarrays for efficient and accurate detection of GAS and its associated antibiotic resistance markers with the benefit of sequencing information from microarray analysis.

Top Abstract Introduction Materials and Methods Results Discussion References

 
Streptococcus pyogenes, one of the most important human bacterial pathogens, causes a variety of diseases, such as pharyngitis (strep throat), scarlet fever, and impetigo, etc. In addition, S. pyogenes is responsible for a number of nonsuppurative sequelae, such as acute rheumatic fever, acute glomerulonephritis, and reactive arthritis (6, 15, 24, 25). Extremely prevalent, S. pyogenes has been the source of numerous outbreaks of pharyngitis at military installations and college campuses, making early detection of the organism an important epidemiologic concern. Complicating the treatment of S. pyogenes further is the increasing incidence of erythromycin resistance as documented by the PROTEKT surveillance group (3).

The traditional microbial diagnosis of S. pyogenes relied on a throat culture that appeared as beta-hemolytic colonies on 5% sheep blood agar (6). The considerable lag time (24 to 48 h) for throat cultures could result in delayed diagnosis, deferred treatments, and decreased compliance (5). Rapid detection of group A streptococci (GAS) offers several advantages, such as providing earlier and appropriate treatment, decreasing transmission, and reducing symptom duration and suppurative complications, and is preferred by patients and physicians if the diagnosis can be made on the same day and antibiotic therapy can be provided immediately (5, 31). Rapid diagnostic tests, such as antigen tests, have evolved during the last 20 years to become more sensitive (in the range of 70 to 95% compared with the culture method). However, studies have shown that there still are substantial false-negative rates with rapid antigen testing, and a controversy exists regarding whether or not these rapid tests require a confirmatory assay(s) when the result is negative (5, 12, 30, 31). Further, Johnson et al. reported that false-positive rapid antigen detection caused by cross-reactive organisms may be more common than previously reported (17).

With the advancement of molecular techniques, the last 10 years have seen increasing emphasis on molecular diagnosis using PCR-based assays (2). PCR-based assays resulting in rapid amplification of the bacterial genome are the mainstay of new analysis methods, including Vir typing using restriction fragment length polymorphism (RFLP), fluorescent RFLP, PCR M typing, immuno-PCR, and real-time PCR (9, 14, 22, 24, 35, 36). Although PCR-based methods have clearly facilitated the detection of GAS, these detection techniques require multistep procedures and special laboratory setups and are subject to equivocal results.

With substantial progress in microarray technology, it is now possible to combine the sensitivity afforded by nucleic acid amplification with the specificity afforded by DNA-DNA hybridization for the detection of human pathogens (4, 16, 19-21, 28, 29, 37). Recently, high-density microarrays with resequencing capability have been used to identify pathogen species and drug resistance in a series of in vitro experiments using cultured microorganisms, including human immunodeficiency virus, mycobacteria, and rifampin-resistant Mycobacterium tuberculosis strains (13, 20, 34). More recently, sequence-specific identification of Francisella tularensis and Yersinia pestis was demonstrated in environmental samples with high-density microarrays with resequencing capability (39, 40).

We have previously described an Affymetrix resequencing respiratory pathogen microarray (RPM v.1) for simultaneous detection and characterization of the many different types of respiratory tract pathogens that cause common diseases with similar clinical symptoms (Lin et al., submitted for publication). RPM v.1 consists of prototype regions for the detection of human adenoviruses, influenza A virus (subtypes H1, H3, H5, N1, and N2), 12 other common respiratory pathogens (influenza B virus, parainfluenza virus, rhinovirus, respiratory syncytial virus, West Nile virus, coronavirus, Streptococcus pneumoniae, Streptococcus pyogenes, Mycobacterium pneumoniae, Neisseria meningitidis, Bordetella pertussis, and Chlamydia pneumoniae), and six Centers for Disease Control and Prevention category A bioterrorism pathogens (Bacillus anthracis, variola major virus, Ebola virus, Lassa virus, Francisella tularensis, and Yersinia pestis) known to cause febrile respiratory illness (i.e., "flu-like" symptoms). We demonstrated that we could unequivocally detect and type both DNA and RNA viruses from clinical samples as well as validate each tiled sequence on the RPM v.1 (with the exception of West Nile virus) using clinical and/or controlled laboratory samples (Lin et al., submitted for publication). Building on this foundation, a more comprehensive study was undertaken to evaluate the use of resequencing arrays for the detection of S. pyogenes and associated antibiotic resistance markers.

Top Abstract Introduction Materials and Methods Results Discussion References

 
Prototype Streptococcus pyogenes and erythromycin-resistant markers. Prototype Streptococcus pyogenes (strain MGAS 8232) was obtained from the American Type Culture Collection (Manassas, VA). The PCR controls for erythromycin-resistant markers, erm(B), erm(TR), and mef, were amplified by PCR and cloned into TOPO PCR 2.1 vector (Invitrogen Life Technologies, Carlsbad, CA). All clones were verified by sequencing.

Primer design and PCR amplification. The primers used for PCR are listed in Table 1. PCRs were performed in 25-µl volumes containing 20 mM Tris-HCl (pH 8.4), 50 mM KCl, 2 mM MgCl₂, 200 µM each of the deoxynucleoside triphosphates (dNTPs), 200 to 300 nM primers, 1 U of Platinum Taq DNA polymerase (Invitrogen Life Technologies, Carlsbad, CA), and 1 µl of purified DNA template from clinical samples. The amplification reaction was carried out in Peltier PTC225 thermal cycler (MJ Research Inc., Reno, NV) with preliminary denaturation at 94°C for 3 min; followed by 40 cycles of 94°C for 30 s, 50°C for 30 s, 72°C for 40 s; and a final extension at 72°C for 10 min. The amplified products were electrophoresed on 2.5 to 3% Tris-acetate-EDTA (TAE) agarose gels and visualized by ethidium bromide staining. PCRs for GAS detection were carried out as previously described (18).

View this table: [in this window] [in a new window]

TABLE 1. Oligonucleotide primers used for real-time PCR and multiplex PCR

Random amplification strategy. Random amplification for DNA samples was carried out with bacteriophage 29 DNA polymerase with random hexamers that was performed according to the instructions of the GenomiPhi DNA amplification kit (Amersham Biosciences Corp., Sunnyvale, CA). The amplified products were ethanol precipitated according to the manufacturer's recommended protocol.

Clinical samples. Throat swabs were collected by the Respiratory Disease Laboratory-Naval Health Research Center (NHRC) from patients with acute respiratory disease symptoms and immediately placed in 2-ml cryogenic vials containing 1.5 ml of transport medium. Nasal washes from the Epidemic Outbreak Surveillance (EOS) team at Lackland Air Force Base were collected from basic military trainees with acute respiratory disease symptoms. In both instances, samples were tested at the site of collection using conventional culture techniques and submitted for microarray-based detection in a masked fashion. GAS-positive samples were identified among culture plates by colony morphology (beta-hemolytic colonies) on 5% sheep blood agar plates after 24 h of incubation. Beta-hemolytic colonies were confirmed to be GAS by susceptibility to bacitracin and a positive reaction to the latex agglutination test (Hardy Diagnostics, Santa Maria, CA). The collection and transport of all clinical samples complied with the Wilford Hall Medical Center protocol for clinical investigation (FWH20020124H). Nucleic acid was extracted from clinical samples using the MasterPure DNA purification kit (Epicenter Technologies, Madison, WI) following the manufacturer's recommended protocol with slight modification. We omitted the RNase digestion step. Informed consent was obtained from all participants after the nature and possible consequences of the studies were explained.

Microarray hybridization and processing. Nucleic acids of clinical samples were subjected to either multiplex PCR or random amplification. The amplified products were fragmented and labeled according to the recommended protocol by Affymetrix (Santa Clara, CA) prior to hybridization. Microarray hybridization and processing were carried out according to the manufacturer's recommended protocol (Affymetrix, Santa Clara, CA). After scanning, the GCOS software is used to reduce the raw image (.DAT) file to a simplified file format (.CEL file) with intensities assigned to each of the corresponding probe positions. Finally, the GDAS software is used to apply an embedded version of the ABACUS algorithm (7) to produce an estimate of the correct base calls, comparing the respective intensities for the sense and antisense probe sets. To increase the percentage of base calls, we adjusted the parameters to allow highly permissive base calls (increased percentage) as described previously (supplemental material). The sequences from base calls made for each tiled region of the resequencing array then were exported from GDAS as the FASTA-formatted files. Resequencing pathogen identification (REPI) software was used to parse the output of the FASTA file into a format suitable for sequence similarity searches using the NCBI BLASTN algorithm (J. A. Thornton, 2004, U.S. patent application).

Top Abstract Introduction Materials and Methods Results Discussion References

 
Gene selection for microarray fabrication. Two major criteria were used for the sequence selection to be tiled on RPM v.1: pathogenicity-related genes and drug resistance genes. For pathogenicity-related genes, the gene coding for S. pyogenes exotoxin B, which is a chromosomally carried structural gene (speB), was selected. speB is associated with pyrogenicity, T-lymphocyte mitogenicity, and the ability to increase susceptibility to endotoxic shock in individuals infected with S. pyogenes. The conserved and stable feature of speB and its presence in almost all GAS make it a good target gene for Streptococcus identification (6, 24). In addition to pathogenicity-related genes, rapid increasing antimicrobial resistance in S. pneumoniae and S. pyogenes is of major clinical concern. While S. pyogenes remains susceptible to penicillin G, in patients with ß-lactam-associated allergies or treatment failure, macrolides are the treatment of choice. However, the increasing incidence of macrolide resistance in GAS has become an issue (3). Due to the increasing concern about erythromycin resistance in GAS, three genes were chosen as targets for identification of erythromycin-resistant markers. Macrolide resistance in streptococci occurs predominantly by two mechanisms. (i) The first is target modification, whereby a specific adenine residue on the 23S rRNA is methylated. Two different erm (erythromycin ribosome methylation) methylase genes, erm(B) and erm(A) (TR variant), are the most common in S. pyogenes (11). (ii) The second mechanism is antibiotic efflux, whereby macrolide efflux (mef) is facilitated by Mef protein (8, 11, 26, 27, 33). Thus, erm(B), erm(TR), and mef were chosen as target genes used as a tiled sequence on RPM v.1. (For probe information about RPM v.1, see Table S1 in the supplemental material.)

Multiplex PCR versus random amplification. In developing microarray technology for identifying pathogens, front-end amplification is required to reach low levels of detection sensitivity without culturing the organisms (23). Two different amplification strategies, multiplex PCR and random amplification, were used as front-end amplification for GAS identification prior to hybridization to RPM v.1 chips. PCR or multiplex PCR is the most commonly employed front-end amplification method with microarrays for detection of pathogens. In this study, four sets of primers [speB, erm(B), erm(TR), and mef genes; Table 1], which we selected for detecting S. pyogenes as well as its antibiotic resistance markers on RPM v.1 chips, were combined in a single multiplex PCR assay and evaluated under various conditions to obtain amplification of all four target genes. The PCR products were verified by 2.5 to 3% TAE agarose gel electrophoresis (data not shown). The capability of the resequencing microarray to detect GAS was tested using RPM v.1 to interrogate PCR amplicons from prototype S. pyogenes (strain MGAS 8232). Primary sequence data generated by the hybridization revealed that RPM v.1 unequivocally identifies prototype S. pyogenes (strain MGAS 8232) without erythromycin resistance markers. In addition to multiplex PCR, we successfully demonstrated random amplification provides great utilities for the purpose of broad-spectrum respiratory pathogen surveillance. It combines the use of resequencing DNA microarrays with methods for microbial nucleic acid enrichment, random nucleic acid amplification, and automated sequence similarity searching for pathogen detection (Lin et al., submitted for publication). Similar data were observed when hybridizing randomly amplified nucleic acid from prototype S. pyogenes (strain MGAS 8232) to RPM v.1. Both PCR and random amplification achieved nearly identical levels of hybridization specificity (data not shown), with PCR showing higher sensitivity. Figure 1A shows a representative hybridization pattern of one of the S. pyogenes-positive clinical samples. The sequence information derived from GDAS base-calling algorithm (Fig. 1B and C) was used to query a database using a similarity search algorithm with REPI software (Fig. 1C), which was developed in our laboratory. Proof-of-concept experiments, utilizing clinical samples obtained from patients presenting GAS-induced illness, unequivocally demonstrated the ability of RPM v.1 chips for correct species and antibiotic marker identification.

View larger version (48K): [in this window] [in a new window]

FIG. 1. Representative RPM v.1 chip image of GAS-positive clinical sample. (A) S. pyogenes-positive clinical sample hybridized to RPM v.1 chip following nucleic acid isolation and amplification using multiplex PCR primers. No significant cross-hybridization is observed. (B) Hybridization-based primary sequences generated through the chip image. GDAS software is used to apply an embedded version of the ABACUS (7) algorithm to produce an estimate of the correct base calls, comparing the respective intensities for the sense and antisense probe sets. (C) FASTA sequence output file and REPI analysis result of S. pyogenes showing the highest BLAST bit score across all respective tile regions where amplicons hybridized.

RPM v.1 for S. pyogenes detection in clinical samples. After successfully demonstrating the utility of the RPM v.1 chip for GAS identification, clinical samples (n = 35; 22 throat swabs, 13 nasal washes) collected from the NHRC and EOS team at Lackland Air Force Base were used to assess and compare the utility of the microarray-based diagnostic to more established methods of S. pyogenes detection—culture and/or PCR (18). The comparison demonstrated a concordance for 18 of 19 samples. Two clinical samples that were negative for S. pyogenes by conventional methods (culture and/or PCR) also were not detected in our microarray analysis (Table 2). Furthermore, RPM v.1 chip results identified antibiotic-resistant markers simultaneously without further testing, thus demonstrating an additional benefit of this assay. In addition, we identified eight S. pneumoniae-positive, six B. pertussis-positive, and two adenovirus-positive samples out of the same sample set with a random amplification strategy (see Table S2 in the supplemental material). The disagreement over the one sample in GAS identification may have resulted from the difference in sensitivity and specificity of the methods. Our data demonstrate the ability of the microarray-based diagnostic to correctly identify S. pyogenes in a manner consistent with the conventional "gold standard" culture method (Table 3). Also, this result showed no cross-reactivity among different pathogens and demonstrated the great specificity of the assay. The accuracy of RPM v.1 chips for sequence-specific pathogen detection was further validated using clinical and/or controlled laboratory samples (with the exception of West Nile virus); no false-positive results were obtained due to microarray base call or analysis errors (Lin et al., submitted for publication). Furthermore, a nonbiased random amplification strategy with the sequencing capability of RPM v.1 chips promised the great potential of using this assay for broader-spectrum surveillance purposes.

View this table: [in this window] [in a new window]

TABLE 2. Comparison of resequencing microarray to culture results for S. pyogenes-positive clinical samples

View this table: [in this window] [in a new window]

TABLE 3. Evaluation of RPM v.1 for S. pyogenes detection in clinical samples

Top Abstract Introduction Materials and Methods Results Discussion References

 
The purpose of this study was to evaluate the use of resequencing microarray for diagnosis of S. pyogenes and associated antibiotic-resistant markers. In this study, we demonstrated that the combination of either PCR or random amplification with Affymetrix resequencing RPM v.1 allows for accurate detection of S. pyogenes with the additional benefit of identifying associated antibiotic markers from microarray analysis. The ability to identify antibiotic resistance markers without further assays demonstrated the great potential of the resequencing microarray as an aid in treatment without empirical antibiotic therapy. Also, this approach will assist epidemiological assessment of the spatial and temporal distribution of resistance genes. In addition, the sequencing capability of the resequencing microarray provides genotyping information which will greatly aid in epidemiologic surveillance.

It is important that the new assay provide a cost-effective alternative to conventional approaches to the diagnosis, management, and surveillance of infectious diseases, most particularly respiratory infections. In the current format, the RPM v.1 assay is not yet optimized for speed (12 to 24 h) or cost (400 U.S. dollars per chip, approximately 20 U.S. dollars per pathogen species) relative to those desired for rapid infectious disease diagnostics. However, the approach is highly amenable to improvement via reduction in array size (i.e., lower cost), process automation, and the availability of portable hardware for processing resequencing arrays. In the event of lower-cost or easily automated microarray alternatives, the resequencing array can be a higher-echelon component in a diagnostics/surveillance pipeline. With this objective in mind, we are currently working on developing automated technologies that will enable for point-of-care diagnostics applications using resequencing microarray technologies.

Since the mid-1980, incidents of S. pyogenes infection have been on the rise and have been associated with life-threatening diseases (6). Genotyping is essential for GAS outbreak investigation and surveillance. Traditional typing methods, such as serologic typing methods, rely on available antisera and often produce ambiguous results (2, 6). Recently, molecular typing methods, such as PCR M typing (PCR with rapid sequencing), PCR-enzyme-linked immunosorbent assay, and sequencing, Vir typing using RFLP, and fluorescent RFLP (2, 8, 9, 14, 21, 31, 32) have provided sensitive alternative methods. Despite the sensitivity and specificity associated with molecular typing methods, these methods are often limited to targeting one gene for genotyping purpose. With resequencing microarrays, we could target more than one gene for diagnostic and genotyping purposes, which will provide more accurate genotyping information for surveillance.

We choose the speB gene, coding for a cysteine proteinase produced by all group A streptococci, as the target gene for S. pyogenes detection on Affymetrix RPM v.1 due to its conserved and stable characteristics (24). Though useful in detecting S. pyogenes, the sequences obtained from microarrays do not provide enough genotype information for epidemiological assessment. S. pyogenes strains are commonly categorized by antigenic differences in M protein, a transmembrane surface protein that is also a crucial virulence factor (1). M protein is encoded by the emm gene of S. pyogenes. The 5' ends of the emm gene are hypervariable and code for serotype specificity for more than 80 distinct serotypes (10). Due to the size limitation of RPM v.1 "real estate," the RPM v.1 group A streptococcus genotyping capability was not fully explored in this study. Nonetheless, this study showed the potential of using a resequencing microarray for genotyping group A streptococci in future studies. Indeed, we included M protein (emm genes) in version 2 resequencing microarrays, which will enable us to detect and provide serotype information of GAS in future studies. Although not commonly considered a bioterror agent, outbreaks of streptococcal pharyngitis are common in military barracks. With the increasing prevalence of antibiotic resistance documented worldwide by the PROTEKT surveillance group (3) and with the increased deployment tempo of the U.S. military, the potential importance of rapid identification of emerging resistance becomes obvious. Three genes, erm(B), erm(TR), and mef, were chosen as targets for identification of erythromycin resistance markers. The primers used for amplifying these genes have been used successfully in surveying erythromycin resistance mechanisms with PCR-based assays (11, 26, 30). In this study, we successfully adapted the amplification strategy and expanded the direct sequencing capability of amplified PCR products with a resequencing microarray. The sequence information yielded can be used for comparison with available sequences in database. However, the present study did not generate sufficient sequence information (amplicons are too small) to reach a general conclusion about the specificity of the antibiotic resistance markers. Nonetheless, this method proved that the resequencing microarray-based assay can be expanded to include longer sequences for future study and provide more specific answers for antibiotic resistance markers.

In summary, we have demonstrated the potential of resequencing microarrays for efficient and accurate detection of GAS with the benefit of sequencing information from microarray analysis. With this method, we are able to show the capability of the resequencing microarray to provide unequivocal means for detecting S. pyogenes and its associated antibiotic-resistant markers. With further improvement of gene selection, we should be able to provide genotyping information of S. pyogenes and improve the specificity of antibiotic markers in future studies.

 
Support for research efforts of the EOS was provided by the Defense Threat Reduction Agency, the United States Army Medical Materiel Research Command, the Air Force Medical Service (Office of HQ USAF Surgeon General), and the Office of Naval Research. We also thank the Naval Health Research Center (Respiratory Disease Laboratory) for providing clinical samples.

The opinions and assertions contained herein are those of the authors and are not to be construed as official or reflecting the views of the Department of Defense or the U.S. Government.

 
* Corresponding author. Mailing address: Center for Bio/Molecular Science & Engineering, Code 6900, Naval Research Laboratory, Washington, DC 20375. Phone: (202) 767-0289. Fax: (202) 767-9594. E-mail: blin{at}cbmse.nrl.navy.mil.

Supplemental material for this article may be found at http://jcm.asm.org/.

The Epidemic Outbreak Surveillance Consortium is an Air Force Medical Service initiative. The following are participating members of the EOS Consortium: (i) sponsorship, Peter F. Demitry (USAF/SGR) and Theresa Lynn Difato (USAF/SGR); (ii) executive board and principal investigators, Eric H. Hanson (The George Washington University [IPA]), Rosana R. Holliday (USAF/SGR [Ctr]), Robb K. Rowley (The George Washington University [IPA]), and Clark Tibbetts (The George Washington University [IPA]); (iii) operational board and senior scientists, Brian K. Agan (Wilford Hall Medical Center), Jerry Diao (USAF/SGR [Ctr]), Russell P. Kruzelock (Virginia Tech [IPA]), David A. Stenger (Naval Research Laboratory), and Elizabeth A. Walter (Texas A&M University Systems San Antonio [IPA]); (iv) technical advisors and collaborating investigators, Luke Daum (Air Force Institute for Operational Health), David Metzgar (Navy Health Research Center), Debra Niemeyer (USAF/SGR), and Kevin Russell (Navy Health Research Center); (v) research and clinical staff, Marie J. Archer (Naval Research Laboratory), Roger Bravo (Lackland AFB, Tex.), Nikki Freed (Naval Health Research Center), Julie Fuller (Naval Health Research Center), John Gomez (Lackland AFB, Tex.), Kevin Gratwick (Naval Health Research Center), Michael Jenkins (Wilford Hall Medical Center), Margaret Jesse (Lackland AFB, Tex.), Barry Johnson (Lackland AFB, Tex.), Erin Lawrence (Naval Health Research Center), Baochuan Lin (Naval Research Laboratory), Carolyn E. Meador (NOVA Research Incorporated), Hernan Melgarejo (Lackland AFB, Tex.), Kate M. Mueller (NOVA Research Incorporated), Chris Olsen (USAF/SGR [Ctr]), David Pearson (Lackland AFB, Tex.), Anjan Purkayastha (USAF/SGR [Ctr]), Jose J. Santiago (Lackland AFB, Tex.), Donald Seto (George Mason University [IPA]), Francine Fuentes Stotler (Lackland AFB, Tex.), Dzung Thach (Naval Research Laboratory), Jennifer A. Thornton (NOVA Research Incorporated), Zheng Wang (Naval Research Laboratory), Daisy Watson (Lackland AFB, Tex.), Sue A. Worthy (Lackland AFB, Tex.), and Gary J. Vora (Naval Research Laboratory); and (vi) operations support staff, Kenya Grant (USAF/SGR [Ctr]), Cheryl J. James (USAF/SGR [Ctr]), and Kathy Word (USAF/SGR [Ctr]).

Top Abstract Introduction Materials and Methods Results Discussion References

 

1
1. Banks, D. J., S. B. Beres, and J. M. Musser. 2002. The fundamental contribution of phages to GAS evolution, genome diversification and strain emergence. Trends Microbiol. 10:515-521.[CrossRef][Medline]
2
2. Beall, B., R. Facklam, and T. Thompson. 1996. Sequencing emm-specific PCR products for routine and accurate typing of group A streptococci. J. Clin. Microbiol. 34:953-958.[Abstract]
3
3. Canton, R., E. Loza, M. I. Morosini, and F. Baquero. 2002. Antimicrobial resistance amongst isolates of Streptococcus pyogenes and Staphylococcus aureus in the PROTEKT antimicrobial surveillance programme during 1999-2000. J. Antimicrob. Chemother. 50(Suppl. 1):9-24.[Abstract]
4
4. Chizhikov, V., M. Wagner, A. Ivshina, Y. Hoshino, A. Z. Kapikian, and K. Chumakov. 2002. Detection and genotyping of human group A rotaviruses by oligonucleotide microarray hybridization. J. Clin. Microbiol. 40:2398-2407.[Abstract/Free Full Text]
5
5. Corneli, H. M. 2004. Rapid detection and diagnosis of group A streptococcal pharyngitis. Curr. Infect. Dis. Rep. 6:181-186.[Medline]
6
6. Cunningham, M. W. 2000. Pathogenesis of group A streptococcal infections. Clin. Microbiol. Rev. 13:470-511.[Abstract/Free Full Text]
7
7. Cutler, D. J., M. E. Zwick, M. M. Carrasquillo, C. T. Yohn, K. P. Tobin, C. Kashuk, D. J. Mathews, N. A. Shah, E. E. Eichler, J. A. Warrington, and A. Chakravarti. 2001. High-throughput variation detection and genotyping using microarrays. Genome Res. 11:1913-1925.[Abstract/Free Full Text]
8
8. Del Grosso, M., F. Iannelli, C. Messina, M. Santagati, N. Petrosillo, S. Stefani, G. Pozzi, and A. Pantosti. 2002. Macrolide efflux genes mef(A) and mef(E) are carried by different genetic elements in Streptococcus pneumoniae. J. Clin. Microbiol. 40:774-778.[Abstract/Free Full Text]
9
9. Desai, M., A. Efstratiou, R. George, and J. Stanley. 1999. High-resolution genotyping of Streptococcus pyogenes serotype M1 isolates by fluorescent amplified-fragment length polymorphism analysis. J. Clin. Microbiol. 37:1948-1952.[Abstract/Free Full Text]
10
10. Facklam, R., B. Beall, A. Efstratiou, V. Fischetti, D. Johnson, E. Kaplan, P. Kriz, M. Lovgren, D. Martin, B. Schwartz, A. Totolian, D. Bessen, S. Hollingshead, F. Rubin, J. Scott, and G. Tyrrell. 1999. emm typing and validation of provisional M types for group A streptococci. Emerg. Infect. Dis. 5:247-253.[Medline]
11
11. Farrell, D. J., I. Morrissey, S. Bakker, and D. Felmingham. 2001. Detection of macrolide resistance mechanisms in Streptococcus pneumoniae and Streptococcus pyogenes using a multiplex rapid cycle PCR with microwell-format probe hybridization. J. Antimicrob. Chemother. 48:541-544.[Abstract/Free Full Text]
12
12. Gieseker, K. E., T. Mackenzie, M. H. Roe, and J. K. Todd. 2002. Comparison of two rapid Streptococcus pyogenes diagnostic tests with a rigorous culture standard. Pediatr. Infect. Dis. J. 21:922-927.[CrossRef][Medline]
13
13. Gingeras, T. R., G. Ghandour, E. Wang, A. Berno, P. M. Small, F. Drobniewski, D. Alland, E. Desmond, M. Holodniy, and J. Drenkow. 1998. Simultaneous genotyping and species identification using hybridization pattern recognition analysis of generic Mycobacterium DNA arrays. Genome Res. 8:435-448.[Abstract/Free Full Text]
14
14. Hartas, J., M. Hibble, and K. S. Sriprakash. 1998. Simplification of a locus-specific DNA typing method (Vir typing) of Streptococcus pyogenes. J. Clin. Microbiol. 36:1428-1429.[Abstract/Free Full Text]
15
15. Hoe, N. P., K. E. Fullerton, M. Liu, J. E. Peters, G. D. Gackstetter, G. J. Adams, and J. M. Musser. 2003. Molecular genetic analysis of 675 group A streptococcus isolates collected in a carrier study at Lackland Air Force Base, San Antonio, Texas. J. Infect. Dis. 188:818-827.[CrossRef][Medline]
16
16. Hwang, T. S., J. K. Jeong, M. Park, H. S. Han, H. K. Choi, and T. S. Park. 2003. Detection and typing of HPV genotypes in various cervical lesions by HPV oligonucleotide microarray. Gynecol. Oncol. 90:51-56.[CrossRef][Medline]
17
17. Johnson, D. R., and E. L. Kaplan. 2001. False-positive rapid antigen detection test results: reduced specificity in the absence of group A streptococci in the upper respiratory tract. J. Infect. Dis. 183:1135-1137.[CrossRef][Medline]
18
18. Kaltwasser, G., J. Diego, P. L. Welby-Sellenriek, R. Ferrett, M. Caparon, and G. A. Storch. 1997. Polymerase chain reaction for Streptococcus pyogenes used to evaluate an optical immunoassay for the detection of group A streptococci in children with pharyngitis. Pediatr. Infect. Dis. J. 16:748-753.[CrossRef][Medline]
19
19. Kawaguchi, K., S. Kaneko, M. Honda, H. F. Kawai, Y. Shirota, and K. Kobayashi. 2003. Detection of hepatitis B virus DNA in sera from patients with chronic hepatitis B virus infection by DNA microarray method. J. Clin. Microbiol. 41:1701-1704.[Abstract/Free Full Text]
20
20. Kozal, M. J., N. Shah, N. Shen, R. Yang, R. Fucini, T. C. Merigan, D. D. Richman, D. Morris, E. Hubbell, M. Chee, and T. R. Gingeras. 1996. Extensive polymorphisms observed in HIV-1 clade B protease gene using high-density oligonucleotide arrays. Nat. Med. 2:753-759.[CrossRef][Medline]
21
21. Lapa, S., M. Mikheev, S. Shchelkunov, V. Mikhailovich, A. Sobolev, V. Blinov, I. Babkin, A. Guskov, E. Sokunova, A. Zasedatelev, L. Sandakhchiev, and A. Mirzabekov. 2002. Species-level identification of orthopoxviruses with an oligonucleotide microchip. J. Clin. Microbiol. 40:753-757.[Abstract/Free Full Text]
22
22. Liang, H., S. E. Cordova, T. L. Kieft, and S. Rogelj. 2003. A highly sensitive immuno-PCR assay for detecting group A streptococcus. J. Immunol. Methods 279:101-110.[CrossRef][Medline]
23
23. Lopez, M. M., E. Bertolini, A. Olmos, P. Caruso, M. T. Gorris, P. Llop, R. Penyalver, and M. Cambra. 2003. Innovative tools for detection of plant pathogenic viruses and bacteria. Int. Microbiol. 6:233-243.[CrossRef][Medline]
24
24. Louie, L., A. E. Simor, M. Louie, A. McGeer, and D. E. Low. 1998. Diagnosis of group A streptococcal necrotizing fasciitis by using PCR to amplify the streptococcal pyrogenic exotoxin B gene. J. Clin. Microbiol. 36:1769-1771.[Abstract/Free Full Text]
25
25. Mandell, G. L., J. E. Bennett, and R. Dolin (ed.). 2000. Principles and practice of infectious diseases, 5th ed. Churchill Livingstsone, New York, N.Y.
26
26. Nagai, K., Y. Shibasaki, K. Hasegawa, T. A. Davies, M. R. Jacobs, K. Ubukata, and P. C. Appelbaum. 2001. Evaluation of PCR primers to screen for Streptococcus pneumoniae isolates and beta-lactam resistance, and to detect common macrolide resistance determinants. J. Antimicrob. Chemother. 48:915-918.[Abstract/Free Full Text]
27
27. Roberts, M. C., J. Sutcliffe, P. Courvalin, L. B. Jensen, J. Rood, and H. Seppala. 1999. Nomenclature for macrolide and macrolide-lincosamide-streptogramin B resistance determinants. Antimicrob. Agents Chemother. 43:2823-2830.[Free Full Text]
28
28. Roth, S. B., J. Jalava, O. Ruuskanen, A. Ruohola, and S. Nikkari. 2004. Use of an oligonucleotide array for laboratory diagnosis of bacteria responsible for acute upper respiratory infections. J. Clin. Microbiol. 42:4268-4274.[Abstract/Free Full Text]
29
29. Sachse, K., H. Hotzel, P. Slickers, T. Ellinger, and R. Ehricht. 2005. DNA microarray-based detection and identification of Chlamydia and Chlamydophila spp. Mol. Cell Probes 19:41-50.[CrossRef][Medline]
30
30. Santos, O., L. L. Weckx, A. C. Pignatari, and S. S. Pignatari. 2003. Detection of group A beta-hemolytic Streptococcus employing three different detection methods: culture, rapid antigen detecting test, and molecular assay. Braz. J. Infect. Dis. 7:297-300.[Medline]
31
31. Sheeler, R. D., M. S. Houston, S. Radke, J. C. Dale, and S. C. Adamson. 2002. Accuracy of rapid strep testing in patients who have had recent streptococcal pharyngitis. J. Am. Board Fam. Pract. 15:261-265.[Abstract]
32
32. Smoot, J. C., K. D. Barbian, J. J. Van Gompel, L. M. Smoot, M. S. Chaussee, G. L. Sylva, D. E. Sturdevant, S. M. Ricklefs, S. F. Porcella, L. D. Parkins, S. B. Beres, D. S. Campbell, T. M. Smith, Q. Zhang, V. Kapur, J. A. Daly, L. G. Veasy, and J. M. Musser. 2002. Genome sequence and comparative microarray analysis of serotype M18 group A Streptococcus strains associated with acute rheumatic fever outbreaks. Proc. Natl. Acad. Sci. USA 99:4668-4673.[Abstract/Free Full Text]
33
33. Sutcliffe, J., T. Grebe, A. Tait-Kamradt, and L. Wondrack. 1996. Detection of erythromycin-resistant determinants by PCR. Antimicrob. Agents Chemother. 40:2562-2566.[Abstract]
34
34. Troesch, A., H. Nguyen, C. G. Miyada, S. Desvarenne, T. R. Gingeras, P. M. Kaplan, P. Cros, and C. Mabilat. 1999. Mycobacterium species identification and rifampin resistance testing with high-density DNA probe arrays. J. Clin. Microbiol. 37:49-55.[Abstract/Free Full Text]
35
35. Uhl, J. R., S. C. Adamson, E. A. Vetter, C. D. Schleck, W. S. Harmsen, L. K. Iverson, P. J. Santrach, N. K. Henry, and F. R. Cockerill. 2003. Comparison of LightCycler PCR, rapid antigen immunoassay, and culture for detection of group A streptococci from throat swabs. J. Clin. Microbiol. 41:242-249.[Abstract/Free Full Text]
36
36. Vitali, L. A., C. Zampaloni, M. Prenna, and S. Ripa. 2002. PCR M typing: a new method for rapid typing of group A streptococci. J. Clin. Microbiol. 40:679-681.[Abstract/Free Full Text]
37
37. Wang, D., L. Coscoy, M. Zylberberg, P. C. Avila, H. A. Boushey, D. Ganem, and J. L. DeRisi. 2002. Microarray-based detection and genotyping of viral pathogens. Proc. Natl. Acad. Sci. USA 99:15687-15692.[Abstract/Free Full Text]
38
38. Whatmore, A. M., V. Kapur, D. J. Sullivan, J. M. Musser, and M. A. Kehoe. 1994. Non-congruent relationships between variation in emm gene sequences and the population genetic structure of group A streptococci. Mol. Microbiol. 14:619-631.[Medline]
39
39. Wilson, K. H., W. J. Wilson, J. L. Radosevich, T. Z. DeSantis, V. S. Viswanathan, T. A. Kuczmarski, and G. L. Andersen. 2002. High-density microarray of small-subunit ribosomal DNA probes. Appl. Environ. Microbiol. 68:2535-2541.[Abstract/Free Full Text]
40
40. Wilson, W. J., C. L. Strout, T. Z. DeSantis, J. L. Stilwell, A. V. Carrano, and G. L. Andersen. 2002. Sequence-specific identification of 18 pathogenic microorganisms using microarray technology. Mol. Cell Probes 16:119-127.[CrossRef][Medline]

---

Journal of Clinical Microbiology, November 2005, p. 5690-5695, Vol. 43, No. 11
0095-1137/05/$08.00+0     doi:10.1128/JCM.43.11.5690-5695.2005

This article has been cited by other articles:

• Lin, B., Malanoski, A. P., Wang, Z., Blaney, K. M., Long, N. C., Meador, C. E., Metzgar, D., Myers, C. A., Yingst, S. L., Monteville, M. R., Saad, M. D., Schnur, J. M., Tibbetts, C., Stenger, D. A. (2009). Universal Detection and Identification of Avian Influenza Virus by Use of Resequencing Microarrays. J. Clin. Microbiol. 47: 988-993 [Abstract] [Full Text]  
• Malanoski, A. P., Lin, B., Stenger, D. A. (2008). A model of base-call resolution on broad-spectrum pathogen detection resequencing DNA microarrays. Nucleic Acids Res 36: 3194-3201 [Abstract] [Full Text]  
• Corless, C. E., Kaczmarski, E., Borrow, R., Guiver, M. (2008). Molecular Characterization of Neisseria meningitidis Isolates Using a Resequencing DNA Microarray. J. Mol. Diagn. 10: 265-271 [Abstract] [Full Text]  
• Pandya, G. A., Holmes, M. H., Sunkara, S., Sparks, A., Bai, Y., Verratti, K., Saeed, K., Venepally, P., Jarrahi, B., Fleischmann, R. D., Peterson, S. N. (2007). A bioinformatic filter for improved base-call accuracy and polymorphism detection using the Affymetrix GeneChip(R) whole-genome resequencing platform. Nucleic Acids Res 35: e148-e148 [Abstract] [Full Text]  
• Lin, B., Blaney, K. M., Malanoski, A. P., Ligler, A. G., Schnur, J. M., Metzgar, D., Russell, K. L., Stenger, D. A. (2007). Using a Resequencing Microarray as a Multiple Respiratory Pathogen Detection Assay. J. Clin. Microbiol. 45: 443-452 [Abstract] [Full Text]  
• Malanoski, A. P., Lin, B., Wang, Z., Schnur, J. M., Stenger, D. A. (2006). Automated identification of multiple micro-organisms from resequencing DNA microarrays. Nucleic Acids Res 34: 5300-5311 [Abstract] [Full Text]  

This Article Abstract Full Text (PDF) Supplemental material Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Reprints and Permissions Copyright Information Books from ASM Press MicrobeWorld Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Davignon, L. Search for Related Content PubMed PubMed Citation Articles by Davignon, L.