دورية أكاديمية
Open-target sparse sensing of biological agents using DNA microarray.
| العنوان: | Open-target sparse sensing of biological agents using DNA microarray. |
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| المؤلفون: | Mohtashemi M; Emerging & Disruptive Technologies, The MITRE Corporation, McLean, Virginia, USA. mojdeh@mitre.org, Walburger DK, Peterson MW, Sutton FN, Skaer HB, Diggans JC |
| المصدر: | BMC bioinformatics [BMC Bioinformatics] 2011 Jul 29; Vol. 12, pp. 314. Date of Electronic Publication: 2011 Jul 29. |
| نوع المنشور: | Journal Article; Research Support, Non-U.S. Gov't |
| اللغة: | English |
| بيانات الدورية: | Publisher: BioMed Central Country of Publication: England NLM ID: 100965194 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2105 (Electronic) Linking ISSN: 14712105 NLM ISO Abbreviation: BMC Bioinformatics Subsets: MEDLINE |
| أسماء مطبوعة: | Original Publication: [London] : BioMed Central, 2000- |
| مواضيع طبية MeSH: | Bacteria/*genetics , Bacteria/*isolation & purification , Oligonucleotide Array Sequence Analysis/*methods, Bacteria/classification ; Computer Simulation ; Least-Squares Analysis ; Oligonucleotides/genetics ; Regression Analysis ; Sensitivity and Specificity |
| مستخلص: | Background: Current biosensors are designed to target and react to specific nucleic acid sequences or structural epitopes. These 'target-specific' platforms require creation of new physical capture reagents when new organisms are targeted. An 'open-target' approach to DNA microarray biosensing is proposed and substantiated using laboratory generated data. The microarray consisted of 12,900 25 bp oligonucleotide capture probes derived from a statistical model trained on randomly selected genomic segments of pathogenic prokaryotic organisms. Open-target detection of organisms was accomplished using a reference library of hybridization patterns for three test organisms whose DNA sequences were not included in the design of the microarray probes. Results: A multivariate mathematical model based on the partial least squares regression (PLSR) was developed to detect the presence of three test organisms in mixed samples. When all 12,900 probes were used, the model correctly detected the signature of three test organisms in all mixed samples (mean(R²)) = 0.76, CI = 0.95), with a 6% false positive rate. A sampling algorithm was then developed to sparsely sample the probe space for a minimal number of probes required to capture the hybridization imprints of the test organisms. The PLSR detection model was capable of correctly identifying the presence of the three test organisms in all mixed samples using only 47 probes (mean(R²)) = 0.77, CI = 0.95) with nearly 100% specificity. Conclusions: We conceived an 'open-target' approach to biosensing, and hypothesized that a relatively small, non-specifically designed, DNA microarray is capable of identifying the presence of multiple organisms in mixed samples. Coupled with a mathematical model applied to laboratory generated data, and sparse sampling of capture probes, the prototype microarray platform was able to capture the signature of each organism in all mixed samples with high sensitivity and specificity. It was demonstrated that this new approach to biosensing closely follows the principles of sparse sensing. |
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| المشرفين على المادة: | 0 (Oligonucleotides) |
| تواريخ الأحداث: | Date Created: 20110802 Date Completed: 20111101 Latest Revision: 20211020 |
| رمز التحديث: | 20231215 |
| مُعرف محوري في PubMed: | PMC3161048 |
| DOI: | 10.1186/1471-2105-12-314 |
| PMID: | 21801424 |
| قاعدة البيانات: | MEDLINE |
Find this article in full text from Springer Verlag. 
Full Text Finder | تدمد: | 1471-2105 |
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| DOI: | 10.1186/1471-2105-12-314 |