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Simultaneous detection of microsatellite repeats and SNPs in the macrophage migration inhibitory factor (MIF) gene by thin-film biosensor chips and application to rural field studies

  • Xiao Bo Zhong
  • , Lin Leng
  • , Anna Beitin
  • , Rui Chen
  • , Courtney McDonald
  • , Betty Hsiao
  • , Robert D. Jenison
  • , Insoo Kang
  • , Sung Hwan Park
  • , Annette Lee
  • , Peter Gregersen
  • , Philip Thuma
  • , Patricia Bray-Ward
  • , David C. Ward
  • , Richard Bucala
  • Yale University
  • University of Kansas
  • Thermo Electron, Corp.
  • Northwell Health System
  • Macha Malaria Research Institute
  • Macha Malaria Research Institute
  • University of California at San Diego

Research output: Contribution to journal › Article › peer-review

83 Scopus citations

Abstract

Microsatellite repeat and single nucleotide polymorphisms (SNPs) are abundant sources of genetic variation, but existing methodologies cannot simultaneously detect these variants in a facile or inexpensive way. We describe herein a thin-film biosensor chip based on an allele-discriminating oligonucleotide array that enables genotyping for both microsatellite repeats and SNPs in a single analysis. We validated this methodology for the functionally polymorphic -794 CATT5-8 repeat and -173 G/C SNP present in the promoter of the human gene for macrophage migration inhibitory factor (MIF). In a comparison of 30 samples collected at a rural hospital in Zambia, we observed a 100% concordance for both the CATT repeat and G/C SNP between the biosensor methodology and the conventional capillary electrophoresis. The biosensor chips are low in cost and once printed, they are robust and require no instrumentation for analysis. When combined with multiple displacement amplification, this methodology can be utilized in primitive settings for the genotyping of nanogram quantities of DNA present in blood, dried and stored on filter paper samples. We applied this methodology to a field study of MIF genotype in children with malaria, and provide first evidence for a potential association between MIF alleles and malaria infection. We also present data supporting significant population stratification of the low- versus high-expression forms of MIF that may bear on the role of this gene in infectious diseases.

Original languageEnglish
Pages (from-to)1-8
Number of pages8
JournalNucleic Acids Research
Volume33
Issue number13
DOIs
StatePublished - 2005

Bibliographical note

Funding Information:
We thank Drs J. R. Kidd and K. K. Kidd for generously providing DNA samples from the Yoruba, Chagga, Hausa and Ibo African tribes, which were collected by their collaborators: Drs Sylvester L. J. Kajuna and Nganyirwa J. Karoma (Department of Biochemistry and Molecular Biology, Hubert Kairuki Memorial University, Dar es Salaam, Tanzania), Dr Selemani Kungulilo (Muhimbili University College of Health Sciences, Dar es Salaam Tanzania), Dr Adekunle Odunsi (Department of Gynecological Oncology, Roswell Park Cancer Institute, Buffalo, NY), Drs Friday Okonofua and F. Oronsaye (Department of Obstetrics and Gynecology, Faculty of Medicine, University of Benin, Benin City, Nigeria) and African-American DNA samples from the NIGMS Human Genetic Mutant Cell Repository, Coriell Institute for Medical Research. We thank Dr Efim Golub for preparing mutant Ampligase and Phi29 polymerase and Dr K. K. Kidd for thoughtful discussion. This work was supported by NIH grants 1RO1AI051306, 5RO1AI042310 and 1R01AR049610 (R.B.), 2P01GM57672 (D.C.W. and X.Z.), a Downs’s Fellowship from the Yale School of Epidemiology and Public Health (A.B.), and grant R11-2002-098-0000-0 from KOSEF through the Rheumatism Research Center at Catholic University, Seoul, Korea (S.-H.P.). A portion of these studies comprised the MPH thesis of A.B., which was awarded the 2005 Wilbur G. Downs International Health Prize for the study of biochip genotyping in patients with malaria. Funding to pay the Open Access publication charges for this article was provided by NIH grant 1RO1AI051306 (R.B.).

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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