Re-sequencing pathogen microarray

Abstract

The present invention relates to pathogen detection and identification by use of DNA resequencing microarrays. The present invention also provides resequencing microarray chips for differential diagnosis and serotyping of pathogens present in a biological sample. The present invention further provides methods of detecting the presence and identity of pathogens present in a biological sample.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS [0001] The present application claims priority to U.S. provisional Application Ser. No. 60 / 590,931, filed on Jul. 2, 2004, U.S. provisional Application Ser. No. 60 / 609,918 filed on Sep. 15, 2004, U.S. provisional Application Ser. No. 60 / 631,437 filed on Nov. 29, 2004, U.S. provisional Application Ser. No. 60 / 631,460 filed on Nov. 29, 2004 and U.S. provisional Application Ser. No. 60 / 691,768 filed on Jun. 16, 2005. This application is also related to U.S. non-provisional application Ser. No. ______, titled “Computer-Implemented Biological Sequence Identifier System and Method,” filed along with this application on Jul. 2, 2005. The entire contents of these applications are incorporated herein by reference. STATEMENT REGARDING FEDERALLY FUNDED PROJECT [0002] The United States Government owns rights in the present invention pursuant to funding from the Defense Threat Reduction Agency (DTRA; Interagency Cost Reimbursement Order (IACRO #02-4118), M...

AI Technical Summary

Benefits of technology

[0349] A very important bioinformatics aspect of the disclosed invention involves the assembly, annotation and selection of pathogen diagnostic targets into database(s) for incorporation into microarray design, as well as the concomitant task of relating detection events on the microarray to such database(s). An advantage of the present invention is that the information contained in the publicly available databases is ever increasing, thus further adding to the robust nature of the present invention. The present invention describes a process of manually selecting pathogen target sequences from the published literature (e.g. GenBank) and / or ascertaining an empirically determined diagnostic target sequence from published literature. The described approach has the advantage that a consortium of scientists, each possessing sufficient “domain expertise” for each of a large number of disparate pathogen species, can provide relevant, pathogen diagnostic sequence information that can be incorporated into an automated array design process without specific regard to specific probe, reagent, amplification, and sample preparation methods.

[0350] In one very preferred embodiment, the requisite domain expertise for each of a large number of unrelated pathogens will be maintained in an up-to-date fashion through a web-portal enabled database. Thus, an extended consortium, comprised of individual researchers of specific pathogens, would be able to provide the latest annotated target sequence information via a “pathogen page” formatted web portal, analogous to the “molecular page” model adopted by the Alliance for Cellular Signaling (AfCS). The AfCS database then maintains an otherwise incomprehensible amount of specific information on thousands of molecules involved in intracellular signaling cascades. In this format, individual researchers without specific knowledge about individual signaling molecules can access detailed parameters that can be used in numerical simulations of signaling events. Thus, in another very preferable embodiment, the annotated target sequence data for individual pathogens is organized into an automated data pipeline in which will impose user-defined design constraints (e.g. number of probe features, number of pathogen targets, the levels of sensitivity and specificity required for array performance, etc.) upon the total information content of a pathogen database, allowing automated, optimal target selection and submission of those targets to a vendor in a format necessary for microarray fabrication.

[0351] In yet another very preferred embodiment, the selected target sequences determined by the previous process will be correlated with the data that is collected in actual use of the microarray, such that metrics for probability and quality can readily used for decision-making. Two preferable approaches for performing such automated pipelining of data and algorithms are VIBE (Visual Integrated Bioinformatics Environment) software (Incogen, Inc., Williamsburg, Va.) and iNquiry (BioTeam, Boston, Mass.) which are representative of a class of integrated bioinformatics environments that could be used to equal effect for the intended purpose. Data Acquisition

[0352] Raw sequence data from the resequencing microarray chips is provided by the Genetic Data Analysis Software version 2.0 (GDAS) packaged with the microarray reader from Affymetrix.

[0353] The Affymetrix resequencing array contains a defined number of probe cells or features. During scanning, the software divides each feature into subunit squares or pixels (3×3 μm). Each feature contains many copies of a unique 25-base oligonucleotide probe of defined sequence, while a series of eight features query a specific site in a known reference sequence. Four features interrogate the sense strand and contain probes that are identical except for the central base which is A, C, G, or T and four features interrogate the anti-sense strand and contain probes that are identical except for the central base which is A, C, G, or T.

[0354] GDAS uses the cell intensity data to make base calls for every base position represented on the resequencing array. Under the manufacturer setting for GDAS, the algorithm uses the intensity data from multiple samples to improve its calling accuracy and assigns a quality score for each call.

Problems solved by technology

One technical challenge for pathogen detection with microarrays arises due to the difficulty in obtaining samples with a sufficient quantity of pathogen nucleic acid.

Unfortunately, conventional methods for this amplification do not scale well in comparison to the number of probes that can be placed on a microarray chip.

Although PCR-based assays are sensitive, accurate, and rapid, these methods also introduce a new set of problems.

Hybridizations patterns allow the detection of single point mutations or substitution / deletion events to a resolution of half probe lengths (e.g. 7-10 bp) but does not allow for exact determination of position(s) or the nature of the mutation.

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