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This article is from Sensors (Basel, Switzerland) , volume 12 . Abstract We have developed a novel microarray technology based on total internal reflection fluorescence (TIRF) in combination with DNA and protein bioassays immobilized at the TIRF surface. Unlike conventional microarrays that exhibit reduced signal-to-background ratio, require several stages of incubation, rinsing and stringency control, and measure only end-point results, our TIRF microarray technology provides several orders of magnitude better signal-to-background ratio, performs analysis rapidly in one step, and measures the entire course of association and dissociation kinetics between target DNA and protein molecules and the bioassays. In many practical cases detection of only DNA or protein markers alone does not provide the necessary accuracy for diagnosing a disease or detecting a pathogen. Here we describe TIRF microarrays that detect DNA and protein markers simultaneously, which reduces the probabilities of false responses. Supersensitive and multiplexed TIRF DNA and protein microarray technology may provide a platform for accurate diagnosis or enhanced research studies. Our TIRF microarray system can be mounted on upright or inverted microscopes or interfaced directly with CCD cameras equipped with a single objective, facilitating the development of portable devices. As proof-of-concept we applied TIRF microarrays for detecting molecular markers from Bacillus anthracis, the pathogen responsible for anthrax.

This article is from Sensors (Basel, Switzerland) , volume 12 . Abstract We have developed a novel microarray technology based on total internal reflection fluorescence (TIRF) in combination with DNA and protein bioassays immobilized at the TIRF surface. Unlike conventional microarrays that exhibit reduced signal-to-background ratio, require several stages of incubation, rinsing and stringency control, and measure only end-point results, our TIRF microarray technology provides several orders of magnitude better signal-to-background ratio, performs analysis rapidly in one step, and measures the entire course of association and dissociation kinetics between target DNA and protein molecules and the bioassays. In many practical cases detection of only DNA or protein markers alone does not provide the necessary accuracy for diagnosing a disease or detecting a pathogen. Here we describe TIRF microarrays that detect DNA and protein markers simultaneously, which reduces the probabilities of false responses. Supersensitive and multiplexed TIRF DNA and protein microarray technology may provide a platform for accurate diagnosis or enhanced research studies. Our TIRF microarray system can be mounted on upright or inverted microscopes or interfaced directly with CCD cameras equipped with a single objective, facilitating the development of portable devices. As proof-of-concept we applied TIRF microarrays for detecting molecular markers from Bacillus anthracis, the pathogen responsible for anthrax.

This article is from Sensors (Basel, Switzerland) , volume 12 . Abstract We have developed a novel microarray technology based on total internal reflection fluorescence (TIRF) in combination with DNA and protein bioassays immobilized at the TIRF surface. Unlike conventional microarrays that exhibit reduced signal-to-background ratio, require several stages of incubation, rinsing and stringency control, and measure only end-point results, our TIRF microarray technology provides several orders of magnitude better signal-to-background ratio, performs analysis rapidly in one step, and measures the entire course of association and dissociation kinetics between target DNA and protein molecules and the bioassays. In many practical cases detection of only DNA or protein markers alone does not provide the necessary accuracy for diagnosing a disease or detecting a pathogen. Here we describe TIRF microarrays that detect DNA and protein markers simultaneously, which reduces the probabilities of false responses. Supersensitive and multiplexed TIRF DNA and protein microarray technology may provide a platform for accurate diagnosis or enhanced research studies. Our TIRF microarray system can be mounted on upright or inverted microscopes or interfaced directly with CCD cameras equipped with a single objective, facilitating the development of portable devices. As proof-of-concept we applied TIRF microarrays for detecting molecular markers from Bacillus anthracis, the pathogen responsible for anthrax.

We describe a new method consisting of enzymatic manipulation of genomic DNA or mRNA with DNA microarrays that is capable of monitoring or profiling any organisms presented in a biological sample without priori knowledge of genomic sequences. The method we have developed seeks to store all genomic DNA information in the bacterial communities found in a patch of soil, water or air sample. The goal is to use genomic information at the population or community scale to monitor and detect the existence of new biota (such as pathogens) in the environment. The scope of organisms with their genomic DNA sequenced is fairly small. Thus, much information at the genomic level is not available with conventional techniques. In addition, many organisms are not amenable to laboratory analysis. However, bio-agents used by terrorist group will be a major threat to our national security. The DNA-based memory potentially provides a way to access information from all organisms in a community (airports, train terminals, etc.) to assess impact by human and non-human biomaterials, does not require explicit sequence knowledge, and is quick, flexible, and inexpensive to implement. Thus, it could provide a holistic view of the genomic status of the whole environment.

Background: Diagnostic DNA arrays for detection of point mutations as markers for cancer usually function in the presence of a large excess of wild type DNA. This excess can give rise to false positives due to competitive hybridization of the wild type target at the mutation spot. The analysis of the DNA array data is typically qualitative aiming to establish the presence or absence of a particular point mutation. Our theoretical approach yields methods for quantifying the analysis so as to obtain the ratio of concentrations of mutated and wild type DNA. Method: The theory is formulated in terms of the hybridization isotherms relating the hybridization fraction at the spot to the composition of the sample solutions at thermodynamic equilibrium. It focuses on samples containing an excess of single stranded DNA and on DNA arrays with low surface density of probes. The hybridization equilibrium constants can be obtained by the nearest neighbor method. Results: Two approaches allow us to obtain quantitative results from the DNA array data. In one the signal of the mutation spot is compared with that of the wild type spot. The implementation requires knowledge of the saturation intensity of the two spots. The second approach requires comparison of the intensity of the mutation spot at two different temperatures. In this case knowledge of the saturation signal is not always necessary. Conclusions: DNA arrays can be used to obtain quantitative results on the concentration ratio of mutated DNA to wild type DNA in studies of somatic point mutations.

This article is from BMC Genomics , volume 13 . Abstract Background: DNA microarrays are used both for research and for diagnostics. In research, Affymetrix arrays are commonly used for genome wide association studies, resequencing, and for gene expression analysis. These arrays provide large amounts of data. This data is analyzed using statistical methods that quite often discard a large portion of the information. Most of the information that is lost comes from probes that systematically fail across chips and from batch effects. The aim of this study was to develop a comprehensive model for hybridization that predicts probe intensities for Affymetrix arrays and that could provide a basis for improved microarray analysis and probe development. The first part of the model calculates probe binding affinities to all the possible targets in the hybridization solution using the Langmuir isotherm. In the second part of the model we integrate details that are specific to each experiment and contribute to the differences between hybridization in solution and on the microarray. These details include fragmentation, wash stringency, temperature, salt concentration, and scanner settings. Furthermore, the model fits probe synthesis efficiency and target concentration parameters directly to the data. All the parameters used in the model have a well-established physical origin. Results: For the 302 chips that were analyzed the mean correlation between expected and observed probe intensities was 0.701 with a range of 0.88 to 0.55. All available chips were included in the analysis regardless of the data quality. Our results show that batch effects arise from differences in probe synthesis, scanner settings, wash strength, and target fragmentation. We also show that probe synthesis efficiencies for different nucleotides are not uniform. Conclusions: To date this is the most complete model for binding on microarrays. This is the first model that includes both probe synthesis efficiency and hybridization kinetics/cross-hybridization. These two factors are sequence dependent and have a large impact on probe intensity. The results presented here provide novel insight into the effect of probe synthesis errors on Affymetrix microarrays; furthermore, the algorithms developed in this work provide useful tools for the analysis of cross-hybridization, probe synthesis efficiency, fragmentation, wash stringency, temperature, and salt concentration on microarray intensities.

We present a maskless microscope projection lithography system (MPLS), in which photomasks have been replaced by a Digital Micromirror Device type spatial light modulator (DMD, Texas Instruments). Employing video projector technology high resolution patterns, designed as bitmap images on the computer, are displayed using a micromirror array consisting of about 786000 tiny individually addressable tilting mirrors. The DMD, which is located in the image plane of an infinity corrected microscope, is projected onto a substrate placed in the focal plane of the microscope objective. With a 5x(0.25 NA) Fluar microscope objective, a fivefold reduction of the image to a total size of 9 mm2 and a minimum feature size of 3.5 microns is achieved. Our system can be used in the visible range as well as in the near UV (with a light intensity of up to 76 mW/cm2 around the 365 nm Hg-line). We developed an inexpensive and simple method to enable exact focusing and controlling of the image quality of the projected patterns. Our MPLS has originally been designed for the light-directed in situ synthesis of DNA microarrays. One requirement is a high UV intensity to keep the fabrication process reasonably short. Another demand is a sufficient contrast ratio over small distances (of about 5 microns). This is necessary to achieve a high density of features (i.e. separated sites on the substrate at which different DNA sequences are synthesized in parallel fashion) while at the same time the number of stray light induced DNA sequence errors is kept reasonably small. We demonstrate the performance of the apparatus in light-directed DNA chip synthesis and discuss its advantages and limitations.

Aptamers are ideal recognition elements, but integrating aptamers onto a sensor platform has two main challenges: (1) aptamers are selected in solution and, as such, their sequences are not optimized to function when immobilized onto a surface, and (2) the initial aptamer selection process is time consuming. Alternatively, oligonucleotide microarrays are attractive tools for aptamer selection and sensor applications and offer several advantages over solution-based selection. First, selection is performed with oligonucleotides immobilized on a substrate, thus binding is not affected by proximity to the sensor surface. Another advantage is that arrays are commercially available and contain upwards of a million unique sequences which can be tested in a single experiment, greatly reducing the time-frame of selection. While the initial library is composed of fewer sequences than solution-based methods, in silico selection provides an optimization step on the starting pool to increase the probability of identifying sequences with strong ligand binding. Therefore, we will improve the efficiency of aptamer selection in a microarray experimental setting using oligonucleotide libraries enriched by pre-screening the potential landscape of binders in silico. This work focuses on identification of specific, high-affinity binders for target molecules including biomarkers and chemical warfare agents for future applications in sensors.

It has recently been shown that in some DNA microarrays the time needed to reach thermal equilibrium may largely exceed the typical experimental time, which is about 15h in standard protocols (Hooyberghs et al. Phys. Rev. E 81, 012901 (2010)). In this paper we discuss how this breakdown of thermodynamic equilibrium could be detected in microarray experiments without resorting to real time hybridization data, which are difficult to implement in standard experimental conditions. The method is based on the analysis of the distribution of fluorescence intensities I from different spots for probes carrying base mismatches. In thermal equilibrium and at sufficiently low concentrations, log I is expected to be linearly related to the hybridization free energy $\Delta G$ with a slope equal to $1/RT_{exp}$, where $T_{exp}$ is the experimental temperature and R is the gas constant. The breakdown of equilibrium results in the deviation from this law. A model for hybridization kinetics explaining the observed experimental behavior is discussed, the so-called 3-state model. It predicts that deviations from equilibrium yield a proportionality of $\log I$ to $\Delta G/RT_{eff}$. Here, $T_{eff}$ is an effective temperature, higher than the experimental one. This behavior is indeed observed in some experiments on Agilent arrays. We analyze experimental data from two other microarray platforms and discuss, on the basis of the results, the attainment of equilibrium in these cases. Interestingly, the same 3-state model predicts a (dynamical) saturation of the signal at values below the expected one at equilibrium.

It has recently been shown that in some DNA microarrays the time needed to reach thermal equilibrium may largely exceed the typical experimental time, which is about 15h in standard protocols (Hooyberghs et al. Phys. Rev. E 81, 012901 (2010)). In this paper we discuss how this breakdown of thermodynamic equilibrium could be detected in microarray experiments without resorting to real time hybridization data, which are difficult to implement in standard experimental conditions. The method is based on the analysis of the distribution of fluorescence intensities I from different spots for probes carrying base mismatches. In thermal equilibrium and at sufficiently low concentrations, log I is expected to be linearly related to the hybridization free energy $\Delta G$ with a slope equal to $1/RT_{exp}$, where $T_{exp}$ is the experimental temperature and R is the gas constant. The breakdown of equilibrium results in the deviation from this law. A model for hybridization kinetics explaining the observed experimental behavior is discussed, the so-called 3-state model. It predicts that deviations from equilibrium yield a proportionality of $\log I$ to $\Delta G/RT_{eff}$. Here, $T_{eff}$ is an effective temperature, higher than the experimental one. This behavior is indeed observed in some experiments on Agilent arrays. We analyze experimental data from two other microarray platforms and discuss, on the basis of the results, the attainment of equilibrium in these cases. Interestingly, the same 3-state model predicts a (dynamical) saturation of the signal at values below the expected one at equilibrium.

It has recently been shown that in some DNA microarrays the time needed to reach thermal equilibrium may largely exceed the typical experimental time, which is about 15h in standard protocols (Hooyberghs et al. Phys. Rev. E 81, 012901 (2010)). In this paper we discuss how this breakdown of thermodynamic equilibrium could be detected in microarray experiments without resorting to real time hybridization data, which are difficult to implement in standard experimental conditions. The method is based on the analysis of the distribution of fluorescence intensities I from different spots for probes carrying base mismatches. In thermal equilibrium and at sufficiently low concentrations, log I is expected to be linearly related to the hybridization free energy $\Delta G$ with a slope equal to $1/RT_{exp}$, where $T_{exp}$ is the experimental temperature and R is the gas constant. The breakdown of equilibrium results in the deviation from this law. A model for hybridization kinetics explaining the observed experimental behavior is discussed, the so-called 3-state model. It predicts that deviations from equilibrium yield a proportionality of $\log I$ to $\Delta G/RT_{eff}$. Here, $T_{eff}$ is an effective temperature, higher than the experimental one. This behavior is indeed observed in some experiments on Agilent arrays. We analyze experimental data from two other microarray platforms and discuss, on the basis of the results, the attainment of equilibrium in these cases. Interestingly, the same 3-state model predicts a (dynamical) saturation of the signal at values below the expected one at equilibrium.

Infections by agents of bioterrorism, especially bacterial agents such as Bacillus anthracis and Yersinia pestis present their initial symptoms in a way that does not reveal their identity or permit rapid diagnosis. However, as was shown in the recent anthrax attacks on the United States, rapid diagnosis can make the difference between life and death for the patient. Bacteria especially virulent bacteria, have a profound effect on the immune system of the human host. Cellular and physiological studies have shown that while many similarities exist in the host immune response to bacterial infection, there are distinctive features that represent classes of organism and, in some cases, individual organisms themselves. The current proposal was designed to use advanced techniques in molecular analysis to analyze the effect of individual biothreat agents on the human immune system.

Test experiments of hybridization in DNA microarrays show systematic deviations from the equilibrium isotherms. We argue that these deviations are due to the presence of a partially hybridized long-lived state, which we include in a kinetic model. Experiments confirm the model predictions for the intensity vs. free energy behavior. The existence of slow relaxation phenomena has important consequences for the specificity of microarrays as devices for the detection of a target sequence from a complex mixture of nucleic acids.

We analyze a series of publicly available controlled experiments (Latin square) on Affymetrix high density oligonucleotide microarrays using a simple physical model of the hybridization process. We plot for each gene the signal intensity versus the hybridization free energy of RNA/DNA duplexes in solution, for perfect matching and mismatching probes. Both values tend to align on a single master curve in good agreement with Langmuir adsorption theory, provided one takes into account the decrease of the effective target concentration due to target-target hybridization in solution. We give an example of a deviation from the expected thermodynamical behavior for the probe set 1091\_at due to annotation problems, i.e. the surface-bound probe is not the exact complement of the target RNA sequence, because of errors present in public databases at the time when the array was designed. We show that the parametrization of the experimental data with RNA/DNA free energy improves the quality of the fits and enhances the stability of the fitting parameters compared to previous studies.

We analyze a series of publicly available controlled experiments (Latin square) on Affymetrix high density oligonucleotide microarrays using a simple physical model of the hybridization process. We plot for each gene the signal intensity versus the hybridization free energy of RNA/DNA duplexes in solution, for perfect matching and mismatching probes. Both values tend to align on a single master curve in good agreement with Langmuir adsorption theory, provided one takes into account the decrease of the effective target concentration due to target-target hybridization in solution. We give an example of a deviation from the expected thermodynamical behavior for the probe set 1091\_at due to annotation problems, i.e. the surface-bound probe is not the exact complement of the target RNA sequence, because of errors present in public databases at the time when the array was designed. We show that the parametrization of the experimental data with RNA/DNA free energy improves the quality of the fits and enhances the stability of the fitting parameters compared to previous studies.

We analyze a series of publicly available controlled experiments (Latin square) on Affymetrix high density oligonucleotide microarrays using a simple physical model of the hybridization process. We plot for each gene the signal intensity versus the hybridization free energy of RNA/DNA duplexes in solution, for perfect matching and mismatching probes. Both values tend to align on a single master curve in good agreement with Langmuir adsorption theory, provided one takes into account the decrease of the effective target concentration due to target-target hybridization in solution. We give an example of a deviation from the expected thermodynamical behavior for the probe set 1091\_at due to annotation problems, i.e. the surface-bound probe is not the exact complement of the target RNA sequence, because of errors present in public databases at the time when the array was designed. We show that the parametrization of the experimental data with RNA/DNA free energy improves the quality of the fits and enhances the stability of the fitting parameters compared to previous studies.

This article is from Journal of Nanobiotechnology , volume 9 . Abstract Background: Light-directed in situ synthesis of DNA microarrays using computer-controlled projection from a digital micromirror device--maskless array synthesis (MAS)--has proved to be successful at both commercial and laboratory scales. The chemical synthetic cycle in MAS is quite similar to that of conventional solid-phase synthesis of oligonucleotides, but the complexity of microarrays and unique synthesis kinetics on the glass substrate require a careful tuning of parameters and unique modifications to the synthesis cycle to obtain optimal deprotection and phosphoramidite coupling. In addition, unintended deprotection due to scattering and diffraction introduce insertion errors that contribute significantly to the overall error rate. Results: Stepwise phosphoramidite coupling yields have been greatly improved and are now comparable to those obtained in solid phase synthesis of oligonucleotides. Extended chemical exposure in the synthesis of complex, long oligonucleotide arrays result in lower--but still high--final average yields which approach 99%. The new synthesis chemistry includes elimination of the standard oxidation until the final step, and improved coupling and light deprotection. Coupling Insertions due to stray light are the limiting factor in sequence quality for oligonucleotide synthesis for gene assembly. Diffraction and local flare are by far the largest contributors to loss of optical contrast. Conclusions: Maskless array synthesis is an efficient and versatile method for synthesizing high density arrays of long oligonucleotides for hybridization- and other molecular binding-based experiments. For applications requiring high sequence purity, such as gene assembly, diffraction and flare remain significant obstacles, but can be significantly reduced with straightforward experimental strategies.

Quantifying interactions in DNA microarrays is of central importance for a better understanding of their functioning. Hybridization thermodynamics for nucleic acid strands in aqueous solution can be described by the so-called nearest-neighbor model, which estimates the hybridization free energy of a given sequence as a sum of dinucleotide terms. Compared with its solution counterparts, hybridization in DNA microarrays may be hindered due to the presence of a solid surface and of a high density of DNA strands. We present here a study aimed at the determination of hybridization free energies in DNA microarrays. Experiments are performed on custom Agilent slides. The solution contains a single oligonucleotide. The microarray contains spots with a perfect matching complementary sequence and other spots with one or two mismatches: in total 1006 different probe spots, each replicated 15 times per microarray. The free energy parameters are directly fitted from microarray data. The experiments demonstrate a clear correlation between hybridization free energies in the microarray and in solution. The experiments are fully consistent with the Langmuir model at low intensities, but show a clear deviation at intermediate (non-saturating) intensities. These results provide new interesting insights for the quantification of molecular interactions in DNA microarrays.

Most of the likely agents of bio-terrorism have profound effects on the host and, in particular, on the immune and inflammatory responses. For many of these agents, pathogenesis has been studies at the cellular and molecular levels. These studies indicate that each specific organism has distinctive effects on the host immune and inflammatory cells that contributes to the unique clinical characteristics of the disease. These studies largely have focused on how the agent and its toxins and other constituents modulate host cell expression of individual cytokines and other molecules of interest as well as activation pathways. We have proposed a broad-based approach to identify the unique signatures of infectious agents using host DNA micro-arrays. Because of the known diverse patterns of host cell interactions with these organisms, examination of the host transcriptional response has enormous potential to allow rapid diagnosis of infectious diseases in general and agents of bio-terrorism in particular.

Most of the likely agents of bio-terrorism have profound effects on the host and, in particular, on the immune and inflammatory responses. For many of these agents, pathogenesis has been studies at the cellular and molecular levels. These studies indicate that each specific organism has distinctive effects on the host immune and inflammatory cells that contributes to the unique clinical characteristics of the disease. These studies largely have focused on how the agent and its toxins and other constituents modulate host cell expression of individual cytokines and other molecules of interest as well as activation pathways. We have proposed a broad-based approach to identify the unique signatures of infectious agents using host DNA micro-arrays. Because of the known diverse patterns of host cell interactions with these organisms, examination of the host transcriptional response has enormous potential to allow rapid diagnosis of infectious diseases in general and agents of bio-terrorism in particular.

Most of the likely agents of bio-terrorism have profound effects on the host and, in particular, on the immune and inflammatory responses. For many of these agents, pathogenesis has been studies at the cellular and molecular levels. These studies indicate that each specific organism has distinctive effects on the host immune and inflammatory cells that contributes to the unique clinical characteristics of the disease. These studies largely have focused on how the agent and its toxins and other constituents modulate host cell expression of individual cytokines and other molecules of interest as well as activation pathways. We have proposed a broad-based approach to identify the unique signatures of infectious agents using host DNA micro-arrays. Because of the known diverse patterns of host cell interactions with these organisms, examination of the host transcriptional response has enormous potential to allow rapid diagnosis of infectious diseases in general and agents of bio-terrorism in particular.

Most of the likely agents of bio-terrorism have profound effects on the host and, in particular, on the immune and inflammatory responses. For many of these agents, pathogenesis has been studies at the cellular and molecular levels. These studies indicate that each specific organism has distinctive effects on the host immune and inflammatory cells that contributes to the unique clinical characteristics of the disease. These studies largely have focused on how the agent and its toxins and other constituents modulate host cell expression of individual cytokines and other molecules of interest as well as activation pathways. We have proposed a broad-based approach to identify the unique signatures of infectious agents using host DNA micro-arrays. Because of the known diverse patterns of host cell interactions with these organisms, examination of the host transcriptional response has enormous potential to allow rapid diagnosis of infectious diseases in general and agents of bio-terrorism in particular.

Most of the likely agents of bio-terrorism have profound effects on the host and, in particular, on the immune and inflammatory responses. For many of these agents, pathogenesis has been studies at the cellular and molecular levels. These studies indicate that each specific organism has distinctive effects on the host immune and inflammatory cells that contributes to the unique clinical characteristics of the disease. These studies largely have focused on how the agent and its toxins and other constituents modulate host cell expression of individual cytokines and other molecules of interest as well as activation pathways. We have proposed a broad-based approach to identify the unique signatures of infectious agents using host DNA micro-arrays. Because of the known diverse patterns of host cell interactions with these organisms, examination of the host transcriptional response has enormous potential to allow rapid diagnosis of infectious diseases in general and agents of bio-terrorism in particular.

Most of the likely agents of bio-terrorism have profound effects on the host and, in particular, on the immune and inflammatory responses. We have proposed a broad-based approach to identify the unique signatures of infectious agents using host DNA microarrays. Because of the known diverse patterns of host cell interactions with these organisms, examination of the host transcriptional response has enormous potential to allow rapid diagnosis of infectious diseases in general and agents of bio-terrorism in particular. Key signature genes will serve as the basis for rapid diagnostic approaches that could be accessed when an outbreak is suspected. The agents under initial investigation are Bacillus anthracis, Burkholderia Mallei, Francisella tularensis, multi- drug resistant Mycobacterium tuberculosis and Yersinia pestis. We have developed appropriate human and mouse models to explore the interactions of host cells with the pathogen.

We developed a bioinformatic method for the identification of unique sequences within the large genomes of bacteria. In support of this contract, we have generated unique sequence and microarray data demonstrating species-level discrimination between Bacillus anthracis, vaccinia virus and Yersinia pestis and strain-level discrimination between Escherichia coli 0157:H7 and the non-virulent K-12 strain. By assaying for the presence of: 1) unique sequences at various levels of the phylogenetic tree, 2) virulence genes, 3) antibiotic resistance genes, 4) virulence plasmid sequences and 5) ribosomal genes, we are in a unique position to develop a novel method for the identification and characterization of microorganisms. The application for this technology crosses many fields of research that are important to the Government including: Environmental testing for bioterrorism by the Department of Homeland Security, Forensic analysis by law enforcement agencies, Battlefield testing by the armed forces, Water quality testing by the EPA, Human diagnostics by the CDC and Agricultural testing by the USDA. In addition to the use of this method to identify known pathogens, we believe that our method will also permit the identification of naturally occurring virulent variants of non-pathogenic organisms, which may constitute an emerging threat to public health and the ability to detect genetically engineered pathogens. By utilizing many different organism-specific sequences for each organism assayed, coupled with statistical analysis methods, false positives simply become a phenomenon of past technology. This research represents a significant leap in technology for the identification and characterization of microorganisms.

We developed a bioinformatic method for the identification of unique sequences within the large genomes of bacteria. In support of this contract, we have generated unique sequence and microarray data demonstrating species-level discrimination between Bacillus anthracis, vaccinia virus and Yersinia pestis and strain-level discrimination between Escherichia coli 0157:H7 and the non-virulent K-12 strain. By assaying for the presence of: 1) unique sequences at various levels of the phylogenetic tree, 2) virulence genes, 3) antibiotic resistance genes, 4) virulence plasmid sequences and 5) ribosomal genes, we are in a unique position to develop a novel method for the identification and characterization of microorganisms. The application for this technology crosses many fields of research that are important to the Government including: Environmental testing for bioterrorism by the Department of Homeland Security, Forensic analysis by law enforcement agencies, Battlefield testing by the armed forces, Water quality testing by the EPA, Human diagnostics by the CDC and Agricultural testing by the USDA. In addition to the use of this method to identify known pathogens, we believe that our method will also permit the identification of naturally occurring virulent variants of non-pathogenic organisms, which may constitute an emerging threat to public health and the ability to detect genetically engineered pathogens. By utilizing many different organism-specific sequences for each organism assayed, coupled with statistical analysis methods, false positives simply become a phenomenon of past technology. This research represents a significant leap in technology for the identification and characterization of microorganisms.