WO2007053165A2 - Virus protein microarray and uses therefor - Google Patents

Abstract

A virus protein micorarray that can serve as a rapid, sensitive and simple tool for identification of viral specific antibodies in sera, such as a SARS coronavirus protein microarray and methods of using the protein microarray.

Description

VIRUS PROTEIN MICRO ARRAY AND USES THEREFOR

Inventors: Heng Zhu, Mike Snyder, Jian Wang, Guozhen Liu, Shaohui Hu, Ghil Jona, and Xiaowei Zhu

GOVERNMENT FUNDING

This invention was made with government support under Grant Number GM 62480 awarded by the National Institutes of Health. The government has certain rights in the invention.

CROSS REFERENCETORELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Application No. 60/642,824, entitled SARS Diagnostics Using A Coronavirus Protein Chip and filed January 11, 2005. The entire teachings of the referenced application are incorporated herein by reference.

BACKGROUND OF THE INVENTION

In November 2002, an outbreak of atypical pneumonia termed severe acute respiratory syndrome (SARS) occurred in southern China and rapidly spread to locations across five continents. SARS was characterized by fever and respiratory compromise; the World Health Organization (WHO) estimated that SARS infected 8,439 individuals with a mortality rate of -9% overall and 40% in people older than 60 years (1). A novel coronavirus (SARS-CoV) was identified as the etiological agent for the illness and was found to be related, but distinct from, other coronaviruses, including the two previously identified human coronaviruses, HCoV-229E and HCoV-OC43, which are single stranded RNA viruses that collectively cause about 30% of the common colds in humans (2). Like other coronaviruses, SARS-CoV encodes two RNA-dependent replicases Ia and Ib, a spike (S) protein, a small envelope (E) protein, a membrane (M) protein, and a nucleocapsid (N) protein, as well as nine predicted proteins that lack significant similarity to any known proteins. The WHO classification for SARS infection in adults is based on four different criteria: fever, respiratory symptoms, close proximity to infected individuals and radiological evidence of lung infiltrates (3). Several diagnostic approaches have also been employed for detecting SARS-CoV, including reverse transcription-PCR (RT- PCR) techniques, ELISAs, and Indirect Immunofluorescence Test (IIFT). RT-PCR is sensitive and specific and useful during the period of infection (4-7). However, it is not useful once the infection is cleared and it can be challenging to implement in clinical application; the collection of samples such as nasopharyngeal or bronchial alveolar aspirates from SARS patients is a dangerous procedure that can put health care workers at high risk. ELISA assays tend not to be highly sensitive and usually require large amounts of sample (8-11). Moreover, existing ELISA assays, such as one manufactured by Euroimmun, use whole viral extracts, thereby increasing the chance of false- positives due to cross-reactivity with proteins from other viruses and resulting in misdiagnosis. Currently, a IIFT kit (Euroimmun, Germany) to detect SARS IgG antibody response is considered the serological gold standard method in the clinic.

However, IIFT limitations include (1) difficulty in diagnosis in the urgent acute phases of the disease, (2) failure to diagnose ~5% of sera that contain high concentrations of anti-nuclear factor, and 3) visual inspection of fluorescently stained cells which is both subjective and of modest throughput. Thus, more tests for diagnosing the disease need to be developed.

At present, no effective treatment of SARS is available. Isolation and stringent infection control practices were the sole means to control the epidemic. Hence, it is important to develop rapid and early diagnostic tests to monitor the course of the disease.

SUMMARY OF THE INVENTION

Described herein are virus protein microarrays useful to diagnose (or aid in the diagnosis of), monitor and assess viral infection in an individual in need thereof. Virus protein microarrays of the present invention comprise viral protein(s) that are useful for identifying viral antibodies in a biological sample, such as serum or any antibody- containing fluid or tissue. The presence of viral specific antibodies (antibodies that bind a virus protein present on the array) in a biological sample being assessed indicates that the individual from whom the sample was obtained is or was infected by the vims of which the protein is a component. Thus, virus protein microarrays of the present invention are useful to determine or aid in the determination of infection (currently or in the past) of an individual (human or nonhuman) by a virus of interest. Such virus protein microarrays are useful in diagnosing or aiding in the diagnosis of infection by a wide variety of viruses, as well as in monitoring the course of infection of an individual by a virus of interest. They can be used to determine the presence/absence and/or quantity of antibodies in serum and, thus, the presence/absence and/or extent of infection. Particularly useful components of virus protein microarrays of the present invention are viral protein markers, which are proteins that are characteristic of a virus of interest and recognized by antibodies produced by an individual infected by the virus of interest. Detection of a viral marker protein on a viral protein microarray to which a biological sample (e.g., serum) has been added indicates the presence of antibodies to the virus of interest in the biological sample being assessed. Further, presence in the biological sample of such antibodies to the virus of interest is indicative of infection (presently or previously) of the individual by the virus of interest. The term "protein" as used herein, includes peptides, polypeptides, protein fragments and proteins, hi preferred embodiments, viral marker proteins on the protein microarray are specific viral marker proteins. That is, detection of antibodies to such specific viral marker proteins in a biological sample being assessed indicates that the antibodies detected bind only (or essentially only) the viral marker protein(s). hi this embodiment, detection is highly specific.

A virus protein microarray of the present invention can comprise any of a wide variety of protein(s), including, but not limited to, all protein(s) from all viruses or one or more marker protein(s) from all viruses (either of which can be seen to be a universal virus protein microarray); all protein(s) from a group of viruses or one or more marker protein(s) from a group of viruses (e.g., all RNA viruses, all Coronavirases, all flu viruses); all protein(s) from a single virus or one or more marker protein(s) from a single virus (e.g. from the SARS Coronavirus). hi addition to protein(s) from a virus of interest, virus protein microarrays of the present invention optionally additionally comprise protein(s), referred to as reference protein(s), which are not protein(s) of the virus(es) of interest. For example, reference protein(s) can be protein(s) from a virus in the same class or family as the virus whose presence in a sample is being assessed (e.g., protein(s) from a corresponding virus from one or more different host species, such as a murine, bovine, feline or canine protein that corresponds to a virus that infects the individual (who can be human or nonhuman). Alternatively, reference protein(s) can be protein(s) from the virus of interest that are not marker protein(s) but, for example, protein(s) common to the virus of interest and other viruses (sufficiently similar in these viruses) that antibodies in the biological sample recognize the protein(s) from the virus of interest and the additional viruses. In a particular embodiment, the viral protein microarrays of the present invention are coronavirus protein-microarrays that comprise one or more SARS- Coronavirus (SARS-CoV) proteins and, optionally, proteins from one or more additional coronaviruses other than SARS-CoV. In certain embodiments, these SARS- CoV protein microarrays comprise all SARS-CoV proteins (the entire or essentially/substantially all of the SARS proteome) and protein (e.g., partial proteomes) from one or more (e.g., one, two, three, four, five or more) additional coronaviruses. In other embodiments, the SARS-CoV protein microarrays comprise less than all of the SARS-CoV proteins (less than the entire SARS proteome). In such embodiments, the SARS-CoV component of the microarray can consist of, for example, proteins and/or protein fragments that, together, do not make up all of the SARS-CoV proteins. For example, in one such embodiment, the SARS-CoV component of the protein microarray can be one or more marker or signature protein, such as envelope (E) protein or fragments thereof; nucleocapsid (N) protein or fragments thereof; spike protein or fragments thereof; or any other protein encoded by the SARS CoV. In a particular embodiment, the SARS-CoV component can be SARS N protein(s) and/or fragments thereof and C-terminal fragments of the N protein. As described herein, Applicants found that several of the C-terminal fragments of the S ARS N protein, which contains a short lysine-rich region (KTFPPTEKKDKKKKTDEAQ; amino acids 362-381) unique to SARS CoV, exhibits the highest antigenic activity (SARS-N-C2). SARS-CoV protein microarrays of the present invention are useful for identifying antibodies to SARS-CoV in a biological sample, such as serum or any antibody-containing fluid or tissue. The presence of SARS-CoV specific antibodies (antibodies that bind a SARS-CoV protein present on the array) in a biological sample being assessed indicates that the individual from whom the sample was obtained is or was infected by SARS-CoV. Thus, virus protein niicroarrays of the present invention are useful to determine or aid in the determination of infection (currently or in the past) of an individual (e.g., a human) by SARS-CoV. SARS-CoV protein microarrays of the present invention are useful to monitor and assess SARS-CoV and, as described herein, have been shown to serve as the basis for rapid, sensitive and simple analysis of biological samples for the occurrence of viral specific (e.g., SARS-CoV specific) antibodies. A particular advantage of the protein microarray of the present invention is that it can serve as a rapid, sensitive and simple tool for large-scale identification of viral specific antibodies in sera.

As also described herein, the SARS-CoV protein microarray has been used to identify individuals with sera reactive against other coronavirus proteins. Applicants developed a computer algorithm that uses multiple classifiers to predict samples from SARS patients, and used it to predict 206 sera from Chinese fever patients. The test assigned the patients into two distinct groups: those with antibodies to SARS-CoV and those without. Results from use of the SARS-CoV protein microarray correlated well with an indirect immunofluorescence test, and demonstrated that viral infection can be monitored for many months after infection. Specific embodiments of the SARS-CoV protein microarray of the present invention, referred to as coronavirus proteome microarrays, comprise the entire proteome of the human SARS-CoV virus, the entire proteome of the HCoV-229E virus, and the partial proteomes of human HCoV-OC43, Mouse MHV- A59, Bovine coronavirus BCoV, and Feline coronavirus FIPV. The coronavirus protein microarrays were used to screen serum samples collected from fever and respiratory patients during the period of SARS outbreak in Beijing, China and Toronto, Canada. Algorithms to optimally diagnose SARS infected patients were devised to generate a microarray test that is rapid, sensitive and accurate and adaptable for detection of many other types of viral infections. Alternatively, SARS-CoV protein microarrays an comprise less than the entire proteome of the SARS-CoV virus, less than the entire proteome of the HCoV-229E virus and the partial proteomes of human HCoV-OC43, Mouse MHV- A59, Bovine coronavirus BCoV, and Feline coronavirus FlPV. The present invention also relates to a method of diagnosing or aiding in the diagnosis of a viral infection in an individual through the use of a viral protein microarray of the present invention. In the method, a biological sample, such as serum, is obtained from an individual to be assessed for a viral infection, which can be any type of viral infection including, but not limited to, flu, SARS, infection by West Nile virus, bird flu, and, further, other types of conditions and diseases, such as cancer. The biological sample is contacted with an appropriate viral protein microarray, such as a SARS-CoV protein microarray, under conditions appropriate for binding of antibodies to viral proteins on the microarray.

BRIEF DESCRIPTION OF THE DRAWINGS

The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee.

Figure 1. Regions of six coronaviruses represented on the microarray. The positions of the cloned and expressed fragments are marked with light grey bars in the figure. The pink bars represent the SARS features selected as classifiers in the supervised cluster analysis (both A-NN and LR). The light blue bars are the features bound by the MHV infected mouse serum.

Figures 2A-2B. Analysis of patient serum samples in a protein microarray format. 2A: A SARS-CoV positive serum from a diagnosed SARS-Co V-infected patient in Beijing was tested at eight dilutions. The signals for the five SARS N protein fragments are shown on the chart. The vertical line indicates the detection limit. Figure 2B: Examples of coronavirus protein microarrays probed with various sera from SARS- Co V-infected or uninfected individuals. Top left panel: Probing with and anti-GST antibody. Top right panel: Probing with a serum from a SARS patient. The N protein and its fragments were the most antigenic protein on the array (indicated by the yellow boxes in the middle panel). Bottom left panel: Probing with a serum from a non-SARS patient. Bottom right panel: Probing with a serum from MHV infected mouse. Light blue boxes: the MHV N protein; Pink boxes: the BCoV N protein. The red boxes indicate the signals from the human IgG used as the positive controls. Figures 3A-3B. Unsupervised 2-dimensional clustering of the Toronto sera and microarray features. The 399 Toronto IgG sera were clustered according to their reactivity to the microarray signals, and the microarray features were clustered according to their sera reactivity. The corresponding Euroimmun IIFT SARS-CoV IgG results are indicated on the top of the diagram, where black and white bars represent SARS-positive and -negative sera, respectively. The different coronaviruses are color- coded on the left part of the diagrams. The yellow color is low or background signal on the arrays, whereas the orange color represents signals above the background level. The black box highlights the features that help to classify SARS infected sera from the microarray assays. All the classifiers in the black rectangle are SARS N proteins and SARS N fragments.

Figures 4A-4B: Models generated by K nearest neighbors (4A) and logistic regression (4B). The cutoff for the prediction is the probability of 0.5, which is indicated by the black horizontal line: a) signals for the selected classifiers, b) confidence calculated from the classifier signals (range from 0 to 1), and c) the IIFT annotations, where the black and white boxes represent IIFT positive and negative, respectively. On the top are depicted the names of the features that were selected by the Ic-NN and LR models.

Figure 5. Time course analysis of sera reactivity of five Canadian individuals. On the top are graphs from two individuals with non-SARS respiratory disease, whereas on bottom depicts results from 3 SARS-patients. The relative levels of antibodies against 4 of the S ARS N protein-constructs along with that of HCoV-229E N protein were monitored at different times. The vertical lines indicate the time at which the persons were diagnosed as SARS-positive by biochemical assays. Figure 6. List of proteins on a representative microarray or protein chip.

Figure 7 shows regions of coronaviruses present on a representative microarray. DETAILED DESCRIPTION OF THE INVENTION

Presented herein is the construction and use of a coronavirus protein microarray to screen human sera for antibodies against human SARS and related coronaviruses. Applicants tested >600 sera from two different parts of the world and predicted the nature of serum samples with >90% accuracy. To Applicants' knowledge it is the largest study of this type conducted thus far, and the first to analyze patients from the two major geographical locations of the SARS epidemic. Results were compared with the currently available methods and the comparison showed that the coronavirus protein microarray is at least as sensitive as and more specific than the available ELISA tests, and has the advantage that multiple antigens from different coronavirus are tested simultaneously. Thus, this system has enormous potential to be used as an epidemiological tool to screen human and other sera for many types of viral infections as well as other types of disease (e.g. cancer).

Described herein is a virus protein microarray comprising one or more proteins of a SARS-coronavirus. In one embodiment, the one or more proteins of a SARS- coronavirus is selected from the group consisting of: SARS spike (S) protein or a fragment thereof; SARS small envelope (E) protein or a fragment thereof; SARS membrane (M) protein or a fragment thereof; SARS nucleocapsid (N) protein or a fragment thereof; and a SARS protein identified in Figure 6 or a fragment thereof. In specific embodiments, the one or more proteins of a SARS coronavirus is the N protein or a fragment thereof; for example, the N protein comprises a short lysine-rich region or is a C-terminal fragment of the SARS N protein.

In certain embodiments, the virus protein microarray additionally comprises at least one reference protein. The at least one reference protein can be, for example, from a virus selected from the group consisting of: Human Coronavirus (HCoV) 229E; mouse MHV A59; Bovine coronavirus (BCoV); HCoV OC43; Avian infectious bronchitis virus; Canine coronavirus; Murine hepatitis virus; Porcine epidemic diarrhea virus; Porcine hemagglutinating encephalomyelitis virus; Porcine transmissible gastroenteritis virus; Rat coronavirus; Turkey coronavirus; Rabbit coronavirus; Feline infectious peritonitis virus (FIPV); an animal Torovirus; Berne virus; and Breda virus. In further embodiments, a virus protein microarray of the present invention comprises the entire or essentially all of the proteome of a coronavirus, such as SARS coronavirus.

The virus protein microarray of this invention, such as one which comprises the entire or essentially all of the proteome of SARS coronavirus, can additionally comprise the partial proteome of at least one coronavirus other than SARS coronavirus. The at least one coronavirus other than SARS coronavirus can be, for example, selected from the group consisting of: Human Coronavirus (HCoV) 229E; mouse MHV A59; Bovine coronavirus (BCoV); HCoV OC43; Avian infectious bronchitis virus; Canine coronavirus; Murine hepatitis virus; Porcine epidemic diarrhea virus; Porcine hemagglutinating encephalomyelitis virus; Porcine transmissible gastroenteritis virus; Rat coronavirus; Turkey coronavirus; Rabbit coronavirus; Feline infectious peritonitis virus (FIPV); an animal Torovirus; Berne virus; and Breda virus.

In another embodiment, a virus protein microarray of the present invention comprises all essentially all of the SARS coronvavirus proteins and at least one protein from a coronavirus which is not SARS coronavirus. This virus protein microarray can additionally comprise at least one of the following protein from a coronavirus which is not SARS coronavirus: all or a portion of the proteome of the HCoV-229E virus; all or a portion of the proteome of human HCoV-OC43; all or a portion of the proteome of Mouse MHV-A59; all or a portion of the proteome of Bovine coronavirus BCoV; all or a portion of the proteome of Feline coronavirus FIPV, all or a portion of the proteome of Avian infectious bronchitis virus, all or a portion of the proteome of Canine coronavirus, all or a portion of the proteome of Murine hepatitis virus, all or a portion of the proteome of Porcine epidemic diarrhea virus, all or a portion of the proteome of Porcine hemagglutinating encephalomyelitis virus, all or a portion of the proteome of Porcine transmissible gastroenteritis virus, all or a portion the proteome of Rat coronavirus, all or a portion of the proteome of Turkey coronavirus, all or a portion of the proteome of Rabbit coronavirus, all or a portion of the proteome of an animal Torovirus, all or a portion of the proteome of Berne virus, and all or a portion of the proteome of Breda virus.

A coronavirus protein microarray is also an embodiment of the present invention. It comprises, for example, at least one SARS coronavirus marker protein. It can further comprise, for example, a set of proteins selected from the proteins listed in Figure 6, or fragments thereof, wherein the set of proteins or fragments thereof on the microarray is specific for antibodies to SARS coronavirus proteins and is useful to distinguish between sera that contain antibodies to SARS coronavirus proteins and sera that do not contain antibodies to SARS coronavirus proteins. In this embodiment as well, the coronavirus protein microarray can additionally comprise at least one protein from a coronavirus which is not SARS coronavirus. It can additionally comprise at least one of the following proteins from a coronavirus which is not SARS coronavirus: all or a portion of the HCoV-229E virus; all or a portion of human HCoV-OC43; all or a portion of Mouse MHV-A59; all or a portion of Bovine coronavirus BCoV; all or a portion of Feline coronavirus FIPV, all or a portion of Avian infectious bronchitis virus, all or a portion of Canine coronavirus, all or a portion of Murine hepatitis virus, all or a portion of Porcine epidemic diarrhea virus, all or a portion of Porcine hemagglutinating encephalomyelitis virus, all or a portion of Porcine transmissible gastroenteritis virus, all or a portion of Rat coronavirus, all or a portion of Turkey coronavirus, all or a portion of Rabbit coronavirus, all or a portion of an animal Torovirus, all or a portion of Berne virus, and all or a portion of Breda virus. A coronavirus protein microarray that comprises at least one SARS coronavirus marker protein can additionally comprise a set of proteins selected from the proteins listed in Figure 6, or fragments thereof, wherein the set of proteins or fragments thereof on the microarray is specific for antibodies to SARS coronavirus proteins and is useful to distinguish between sera that contain antibodies to SARS coronavirus proteins and sera that do not contain antibodies to SARS coronavirus protein Alternatively, a coronavirus protein microarray that comprises at least one SARS cornoavirus marker protein can additionally comprise all or a portion of the HCoV-229E virus; all or a portion of human HCoV-OC43; all or a portion of Mouse MHV- A59; all or a portion of Bovine coronavirus BCoV; all or a portion of Feline coronavirus FIPV, all or a portion of Avian infectious bronchitis virus, all or a portion of Canine coronavirus, all or a portion of Murine hepatitis virus, all or a portion of Porcine epidemic diarrhea virus, all or a portion of Porcine hemagglutinating encephalomyelitis virus, all or a portion of Porcine transmissible gastroenteritis virus, all or a portion of Rat coronavirus, all or a portion of Turkey coronavirus, all or a portion of Rabbit coronavirus, all or a portion of an animal Torovirus, all or a portion of Berne virus, and all or a portion of Breda virus. Any coronavirus protein microarray of the present invention can comprise at least one SArS coronavirus marker protein that is the SARS N protein or a fragment thereof. The N protein comprises a short lysine-rich region or is, for example, a C-terminal fragment of the SARS N protein.

A further embodiment of the present invention is a method for detecting one or more antibodies to a SARS-coronavirus in a sample, which can be any tissue, fluid or organ in which such antibodies occur. The method can comprise, for example, a. providing one or more marker proteins of a SARS-coronavirus; b. combining the one or more marker proteins with the sample; c. determining if interaction occurs between one or more marker proteins and one or more proteins (antibodies) in the sample, wherein the detection of interaction between one or more marker proteins with one or more proteins (antibodies)in the sample is indicative of the presence of one or more antibodies to SARS-coronavirus.

Typically, the one or more marker proteins are present on a protein microarray. In all embodiments of the present invention the sample can be a serum sample from an individual or any other sample in which antibodies to SARS coronavirus occur (e.g., but not limited to, sputum, urine, CS fluid, organs such as spleen, kidney, liver, bone marrow, nasal fluids, sweat)

This method is useful, for example, wherein the individual is thought to be infected with a SARS-coronavirus or has recovered from infection by a SARS coronavirus. The method is also useful where the individual is suspected of ongoing infection by a SARS-coronavirus and the method is carried out periodically in order to monitor the progression of infection by the SARS coronavirus and/or the effect of treatment.

In a further embodiment, the present invention is a method of identifying a drug that binds to a SARS coronavirus protein, comprising contacting a drug to be assessed for its ability to bind a SARS coronavirus protein with a SARS coronavirus protein microarray (e.g., a microarray of any of the claims herein), under conditions appropriate for binding of the drug to a SARS coronavirus protein and determining if binding occurs, wherein, if binding is detected, the drug to be assessed is a drug that binds a SARS coronavirus protein. The drag to be assessed can be any type of molecule or compound, such as a small molecule or an antibody. A library of drugs can be contacted with the SARS coronaviras protein microarray or individual drugs can be assessed. The library of drugs can be a library of small molecules. A further embodiment of the invention is a method of assessing the effect of treatment provided to an individual infected with SARS coronavirus, comprising assessing a sample (e.g., a sample of serum) from the individual for antibodies to SARS coronaviras prior to treatment and following treatment and determining if there is a difference in the quantity of antibodies in the individual's serum after treatment, wherein a difference is indicative of an effect of the treatment. For example, a decrease in antibody levels after treatment is an indication that treatment is having an effect.

Sensitivity and Accuracy of the Protein Microarray Assay

Using the Euroimmun IIFT plus epidemiological data as the reference, the protein microarray assay offered several advantages relative to the commercially available Euroimmun ELISA assay. First, the assays were sensitive and functioned at high dilutions allowing small amounts of sera to be used (1/200 dilution was used here instead of the 1/50 commonly used in ELISA assays). This is particularly important for SARS research; the sera are extremely precious and not replaceable. Consistent with an increased sensitivity, more Chinese patients were diagnosed as SARS positive using the protein microarray over the Chinese ELISA assay. Secondly, the accuracy of the assay described herein is as good as, if not better than, the Euroimmun ELISA assay; 92% vs. 91% accuracy. Thirdly, Applicants' assay has greater reliability in that multiple antigens are followed and a weighted scoring scheme based on probabilities was developed, instead of relying on the results of one or a mix of antigens. To Applicants' knowledge, this is the first time a probabilistic test of this type has been devised for viral detection using sera and it is expected to be of general utility. Fourth, Applicants' assay can monitor the presence of antibodies to multiple viruses, thus allowing their potential simultaneous detection. Fifth, the present assay can be automated to robotically probe hundreds of sera in parallel, a major advantage over the visual analysis in IIFT. Finally, unlike IIFT, in which results can be masked by the presence of high concentrations of anti nuclear factor (60 such patients were present in the study described herein), the protein array is not affected by such antibodies.

One concern with using protein microarrays is the reproducibility of the assay. After unblinding of the initial screening, Applicants retested the ~30 sera that exhibited either false positive or false negative reactions; 22 were correctly reclassified. Furthermore, retesting 97 sera that were correctly classified but were close to the borderline resulted in misclassification of 13%. These results indicate that the assay as performed is 90% reproducible. The reason for this variation is currently unclear. Probing sera in triplicate will likely increase the reproducibility of the assay to 98% if the majority results are scored.

A subset of eight sera yielded false negative results while the patients had been classified as SARS-CoV cases using clinical and laboratory tests. This misclassification by the protein microarray assay occurred regardless of the array interpretation method used. Applicants presume that either these patients were misclassified clinically or HFT is a more sensitive assay than the protein microarray. Possible explanations for the latter include that the HFT was tested at a lower serum dilution (1/10) as compared to the arrays (1/200); or that the SARS proteins had been purified from yeast cells, which have different post-translational modifications compared to those of mammalian cells. Some sera may recognize glycosylated antigens modified in humans that are not present on the antigens prepared in yeast (see (28)). Consistent with this hypothesis, the infected sera primarily recognized the SARS-CoV encapsulated N protein, but none of the six surface glycoproteins. The purification of viral proteins from human cell lines could potentially relieve this problem.

Specificity of the Coronavirus Microarray for Detecting Different Viral Infections

Most of the human sera did not cross-react with antigens from other species, indicating the assay is specific. However, 82 individuals had antibodies reactive to HCoV-229E antigens. These were observed both in SARS-CoV-positive and SARS- CoV-negative patients. Since these antibodies were observed in both types of patients, the simplest explanation is that these patients were exposed to HCoV-229E (or a closely related virus). It is unlikely that the antibodies present in SARS-CoV infected patients cross react with HCoV-229E antigens, since the HCoV-229E and SARS-CoV belong to different phylogenetic groups and their N antigens are only 27% identical. Thus, it is reasonable to conclude that the protein microarray assay monitors exposure to several types of coronaviruses. hi summary, Applicants have constructed coronavirus protein microarrays that cover proteins from six coronavirus proteomes and have used them to classify sera from potential SARS infected patients. The approaches developed here are applicable to potentially all viruses and are expected to have great impact in epidemiological studies, and possibly in clinical diagnosis.

In certain embodiments, the invention provides protein microarrays or protein chips. Methods of making and using protein chips are described U.S. Patent

Application Publication Nos. 20050182242 and 20030207467. For review, see Jona and Snyder, Curr Opin MoI Ther. 2003 Jun;5(3):271-7; Espina et al., Proteomics. 2003 Nov;3(ll):2091-100; Zhu et al., Annu Rev Biochem. 2003;72:783-812.

In certain embodiments, a microarray of the invention comprises one or more proteins, such as marker proteins, from one or more pathogens. Examples of pathogens include viruses, bacteria, and fungi. Examples of disease causing viruses that may be used in accord with the methods described herein include: Retroviridae (e.g., human immunodeficiency viruses, such as HTV-I (also referred to as HTLV-III, LAV or HTLV-III/LAV, See Ratner, L. et al., Nature, Vol. 313, Pp. 227-284 (1985); Wain Hobson, S. et al, Cell, Vol. 40: Pp. 9-17 (1985)); HIV-2 (See Guyader et al., Nature,

Vol. 328, Pp. 662-669 (1987); European Patent Publication No. 0 269 520; Chakraborti et al., Nature, Vol. 328, Pp. 543-547 (1987); and European Patent Application No. 0 655 501); and other isolates, such as HIV-LP (International Publication No. WO 94/00562 entitled "A Novel Human Immunodeficiency Virus"; Picornaviridae (e.g., polio viruses, hepatitis A virus, (Gust, I. D., et al., Intervirology, Vol. 20, Pp. 1-7 (1983); entero viruses, human coxsackie viruses, rhinoviruses, echoviruses); Calciviridae (e.g., strains that cause gastroenteritis); Togaviridae (e.g., equine encephalitis viruses, rubella viruses); Flaviridae (e.g., dengue viruses, encephalitis viruses, yellow fever viruses); Coronaviridae (e.g., coronaviruses); Rhabdoviridae (e.g., vesicular stomatitis viruses, rabies viruses); Filoviridae (e.g., ebola viruses);

Paramyxoviridae (e.g., parainfluenza viruses, mumps virus, measles virus, respiratory syncytial virus); Orthomyxoviridae (e.g., influenza viruses); Bungaviridae (e.g., Hantaan viruses, bunga viruses, phleboviruses and Nairo viruses); Arena viridae (hemorrhagic fever viruses); Reoviridae (e.g., reoviruses, orbiviurses and rotaviruses); Birnaviridae; Hepadnaviridae (Hepatitis B virus); Parvoviridae (parvoviruses); Papovaviridae (papilloma viruses, polyoma viruses); Adenoviridae (most adenoviruses); Herpesviridae (herpes simplex virus (HSV) 1 and 2, varicella zoster virus, cytomegalovirus (CMV), herpes viruses'); Poxviridae (variola viruses, vaccinia viruses, pox viruses); and Iridoviridae (e.g., African swine fever virus); and unclassified viruses (e.g., the etiological agents of Spongiform encephalopathies, the agent of delta hepatities (thought to be a defective satellite of hepatitis B virus), the agents of non-A, non-B hepatitis (class l=internally transmitted; class 2=parenterally transmitted (i.e., Hepatitis C); Norwalk and related viruses, and astro viruses).

The coronaviruses are enveloped positive single-stranded RNA viruses with genomes approximately 30 kb in length - the largest of any of the RNA viruses — that replicate in the cytoplasm of host cells without going through DNA intermediates. Coronaviruses have been reported to cause common colds in humans, and to cause respiratory, enteric, and neurological diseases, as well as hepatitis, in animals. Human coronaviruses are usually difficult to culture in vitro, whereas most animal coronaviruses and SARS-CoV can easily be cultured in Vero E6 cells. There are three groups of coronaviruses: Groups 1 and 2 encompass mammalian viruses, whereas Group 3 encompasses avian viruses. Within each group, the coronaviruses are classified into distinct species according to host range, antigenic relationships, and genomic organization. Human coronaviruses (HCoVs) were previously reported to belong in Group 1 (HCoV-229E) and Group 2 (HCoV-OC43), and are responsible for mild respiratory illnesses. Examples of infectious bacteria include: Helicobacter pylori, Borrelia burgdorferi, Legionella pneumophilia, Mycobacterium sps. (e.g. M. tuberculosis, M. avium, M. intracellulare, M. kansaii, M. gordonae), Staphylococcus aureus, Neisseria gonorrhoeae, Neisseria meningitidis, Listeria monocytogenes, Streptococcus pyogenes (Group A Streptococcus), Streptococcus agalactiae (Group B Streptococcus), Streptococcus (viridans group), Streptococcus faecalis, Streptococcus bovis,

Streptococcus (anaerobic sps.), Streptococcus pneumoniae, pathogenic Campylobacter sp., Enterococcus sp., Haemophilus influenzae, Bacillus anthracis, Corynebacterium diphtheriae, Corynebacterium sp., Erysipelothrix rhusiopathiae, Clostridium perfringers, Clostridium tetani, Enterobacter aerogenes, Klebsiella pneumoniae, Pasturella multocida, Bacteroides sp., Fusobacterium nucleatum, Streptobacillus moniliformis, Treponema pallidium, Treponema pertenue, Leptospira, and Actinomyces israelii.

Examples of infectious fungi include: Cryptococcus neoformans, Histoplasma capsulatum, Coccidioides immitis, Blastomyces dermatitidis, Chlamydia trachomatis, Candida albicans. Other infectious organisms (i.e., protists) include: Plasmodium falciparum and Toxoplasma gondii. Genomic information (including nucleotide sequences, amino acid sequences, protein expression information, and/or protein structure information) for a variety of microorganisms may be found in the databases maintained by The Institute for Genomic Research (TIGR) (www.tigr.org) and/or the National Center for Biotechnology Information (NCBI) (www.ncbi.nlm.nih.gov). Examples of bacteria for which genomic information is available, include, for example, Agrobacterium tumefaciens str. C58 (Cereon) (NC_003062 & NC_003063), Agrobacterium tumefaciens str. C58 (U. Washington) (NC_003304 & NC_003305), Aquifex aeolicus (NC_000918), Bacillus halodurans (NC_002570), Bacillus subtilis (NC_000964), Borrelia burgdorferi (NC_001318), Brucella melitensis (NC_003317 & NC_003318), Buchnera sp. APS (NC_002528), Campylobacter jejuni (NC_002163), Caulobacter crescentus -CB 15 (NC_002696), Chlamydia muridarum (NC_002620), Chlamydia trachomatis (NCJ)OOl 17), Chlamydophila pneumoniae AR39 (NC_002179), Chlamydophila pneumoniae CWL029 (NC_000922), Chlamydophila pneumoniae J138 (NC_002491), Clostridium acetobutylicum (NC_003030), Clostridium perfringens (NC_003366), Corynebacterium glutamicum (NC_003450), Deinococcus radiodurans (NCJ)01263 & NCJ)01264), Escherichia coli Kl 2 (NC_000913), Escherichia coli O157:H7 (NC_002695), Escherichia coli O157:H7 EDL933 (NCJD02655), Fusobacterium nucleatum subsp. nucleatum ATCC 25586 (NC_003454), Haemophilus influenzae Rd (NC_000907), Helicobacter pylori 26695 (NC_000915), Helicobacter pylori J99 (NC_000921), Lactococcus lactis subsp. lactis (NC_002662), Listeria innocua (NC_003212), Listeria monocytogenes EGD-e (NC_003210), Mesorhizobium loti (NC_002678), Mycobacterium leprae (NC_002677), Mycobacterium tuberculosis CDCl 551 (NC_002755), Mycobacterium tuberculosis H37Rv (NC_000962), Mycoplasma genitalium (NC_000908), Mycoplasma pneumoniae (NC_000912), Mycoplasma pulmonis (NC_002771), Neisseria meningitidis MC58 (NC_003112), Neisseria meningitidis (NC_003116), Nostoc sp. (NC_003272), Pasteurella multocida (NC_002663), Pseudomonas aeruginosa (NC_002516), Ralstonia solanacearum

(NC_003295 & NC_003296), Rickettsia conorii (NC_003103), Rickettsia prowazekii (NC_000963), Salmonella enterica subsp. enterica serovar Typhi (NC_003198), Salmonella typhi (NC_002305), Salmonella typhimurium LT2 (NC_003197), Sinorhizobium meliloti (NC_003047), Staphylococcus aureus subsp. aureus MW2 (NC_003923), Staphylococcus aureus subsp. aureus Mu50 (NC_002758),

Staphylococcus aureus subsp. aureus N315 (NC_002745), Streptococcus pneumoniae R6 (NC_003098), Streptococcus pneumoniae TIGR4 (NC_003028), Streptococcus pyogenes Ml GAS (NC_002737), Streptococcus pyogenes MGAS8232 (NC_003485), Streptomyces coelicolor A3(2) (NC_OO3888), Synechocystis sp. PCC 6803 (NC_000911), Thermoanaerobacter tengcongensis (NC_003869), Thermotoga maritima (NC_000853), Treponema pallidum (NC_000919), Ureaplasma urealyticum (NC_002162), Vibrio cholerae (NC_002505 & NC_002506), Xanthomonas axonopodis pv. cirri str. 306 (NC_003919), Xanthomonas campestris pv. campestris str. ATCC 33913 (NC_003902), Xylella fastidiosa 9a5c (NC_002488), and Yersinia pestis (NC_003143).

Examples of archaea for which genomic information is available from TIGR and/or NCBI, include, for example, Aeropyrum pernix (NC_000854), Archaeoglobus fulgidus (NC_000917), Halobacterium sp. NRC-I (NC_002607), Methanococcus jannaschii (NC_000909), Methanopyrus kandleri AV19 (NC_003551), Methanosarcina acetivorans str. C2A (NC_003552), Methanosarcina mazei Goel (NC_003901), Methanothermobacter thermautotrophicus (NC_000916), Pyrobaculum aeropliilum (NC_003364), Pyrococcus abyssi (NC_000868), Pyrococcus furiosus DSM 3638 (NC_003413), Pyrococcus horikoshii (NC_000961), Sulfolobus solfataricus (NC_002754), Sulfolobus tokodaii (NC_003106), Thermoplasma acidophilum (NC_002578), and Thermoplasma volcanium (NC_002689).

Examples of eukaryotes for which genomic information is available from TIGR and/or NCBI, include, for example, Anopheles gambiae, Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Encephalitozoon cuniculi, Guillardia theta nucleomorpli, Saccharomyces cerevisiae, and Schizosaccharomyces pombe.

Genomic information for over 900 viral species is available from TIGR and/or NCBI, including, for example, information about deltaviruses, retroid viruses, satellites, dsDNA viruses, dsRNA viruses, ssDNA viruses, ssRNA negative-strand viruses, ssRNA positive-strand viruses, unclassified bacteriophages, and other unclassified viruses.

Examples of nucleotide and protein sequences of coronaviruses and coronavirus proteins are available in GenBank as follows: Virus Gene GenBank#

HCV-OC43 M gene M93390

HCV-OC43 S gene Z32768

HCV-229E complete genome NC_002645

MHV- A59 complete genome NC_001846 BCV-Mebus complete genome U00735

FIPV 79-1146 M and N genes X56496

Example 1 Development of a coronavirus protein microarray and a SARS detection assay A protein microarray approach was developed to rapidly identify SARS-CoV and other coronavirus-infected patients with high sensitivity and accuracy. Gene or gene fragments that cover the entire genome of SARS-CoV, and the majority of the HCoV-229E and MHV A59 genomes were amplified using PCR and cloned into a yeast expression vector that expresses the viral proteins with glutathione-S-transferase (GST) at their N-terminus (Fig. 1). Using the limited sequence information available at the time, regions of the BCoV, HCoV-OC43 and FIPV genomes were also cloned (Fig. 1). A total of 82 expression constructs, about one third (25) of which originate from SARS-CoV and the rest from the other coronaviruses, were purified from yeast cells using their GST tags. Immunoblot analysis revealed that most purified proteins could be detected and migrated at their expected molecular weights, including the glycoproteins.

To test whether a protein microarray approach could be used to detect SARS- CoV infection, Applicants fabricated a microarray containing the 82 purified proteins. Serial dilutions prepared from four serum samples collected from Chinese patients who were clinically diagnosed as SARS-positive and who also tested positive by a local ELISA assay (one very strong positive, one medium, and 2 weak) were used to probe the array. The presence of human anti-SARS antibodies was detected with Cy-3 labeled goat anti-human IgG antibodies (12-16). As shown in Fig. 2 A, the sensitivity of the microarray assay is extremely high; reactivity is readily detected at 1 : 10,000 fold dilution for the strong positive serum and 1 :800 for the weakly positive sera. The assay is approximately 50-fold more sensitive than ELISA assays performed using the same sera. Importantly, less than lμl of serum is needed for the protein microarray assay, which is crucial since the sera from SARS patients are extremely precious.

Example 2 Serum probing of the coronavirus proteome microarray with human sera

The coronavirus protein microarrays were used to screen sera from 399 Canadian and 203 Chinese infected and non-infected individuals in a double blind format. The Canadian samples included 181 clinical and laboratory-confirmed SARS- CoV sera (see methods) (3), as well as anonymized clinical samples from patients who had presented with respiratory illness during the outbreak period, but who failed to meet the case definition, and did not develop SARS. Other S ARS-Co V-negative sera were from asymptomatic healthcare workers. The Chinese sera were from patients with fever during the SARS outbreak; some of these were classified as SARS-positive and others as SARS -negative.

To accomplish the screening, each of the 82 purified coronavirus proteins was spotted in duplicate on eight identical blocks per microscope slide. Human IgG protein was also included as positive control (see below). The amount of immobilized coronavirus proteins and protein fragments present on the microarray was quantified by probing with anti-GST antibodies (Fig. 2B). Reactive protein was evident for each protein. The serum samples were screened at a 200-fold dilution, and the bound antibodies were detected with Cy-3 labeled goat anti-human IgG. The signals were analyzed using algorithms Applicants developed. Positive sera usually exhibited strong reactivity for approximately 10% of the proteins on the microarrays. The full-length and two C-terminal derivatives of SARS N-protein were strongly recognized by the antibodies present in the SARS-CoV infected patient sera, but not in sera from non- infected individuals (Fig. 2B). The C-terminal fragments of the SARS N protein, which contains a short lysine-rich region (KTFPPTEKKDKKKKTDEAQ (SEQ ID NO. 1); amino-acids 362-381) unique to SARS CoV, exhibit the highest antigenic activity (SARS-N-C2; Fig. 2, top right panel). These results are consistent with previous studies that identified the N proteins of coronaviruses as the most abundant and reactive antigens (11).

Although the N proteins are conserved among coronaviruses, the SARS-CoV infected sera from the Chinese and Canadian patients showed little cross-reactivity with proteins of other coronaviruses. including N proteins, on the array. One exception is that many (88%) of the sera from the Chinese patients showed a slight reactivity to the first half of BCoV N-protein, which shares -40% identity through its first 210 amino acids with the SARS-CoV N protein. Interestingly, the sera from infected Canadian patients did not react with this protein, hi addition, approximately 20% of the sera from both SARS positive and negative Canadian individuals specifically recognized the HCoV-229E N protein, but not the N proteins from the other species. We expect that many Canadian patients may have been exposed to HCoV-229E (see below).

To further test the specificity of the assays, Applicants probed the coronavirus protein microarray with ~30 sera from MHVA59-infected and control mice. As shown in Fig. 2B (bottom right panel), a mouse-infected serum recognized the MHV A59 N protein, whereas control mouse sera did not react with proteins on the array. This serum also cross-reacted with the N protein from BCoV, and not with proteins from other coronaviruses. Since the N proteins from MHV and BCoV share 70.7% identity and 87.9% similarity over their entire protein sequences, cross reactivity between these two proteins is not surprising. hi summary, although a few instances of cross-reactivity occurred among highly similar proteins, the protein microarray approach demonstrated that different serum samples could be differentiated at a high degree of specificity. Most importantly, the protein microarray was able to distinguish reactivity between two human coronaviruses tested (HCoV-229E and SARS).

Example 3 Detection of SARS-infected patients in the Canadian samples

To determine if an accurate SARS diagnostic test can be devised using the protein microarray data, Applicants analyzed the results obtained from the Canadian patients using computational approaches. The sera were first clustered according to the relative signal intensities of all the coronavirus proteins immobilized on the microarrays in an unsupervised fashion(17). The sera fell into two major groups, which upon subsequent comparison with clinical IIFT data were largely correlated with SARS-positive and SARS-negative sera (Fig. 3). The unsupervised method correctly predicted 138 of 181 infected serum samples (76% sensitivity, with sensitivity defined as the percentage of correct positives of the total positives), and 210 of 218 sera from healthy individuals (96% specificity, with specificity defined as the percentage of correctly classified negatives out of the total negatives). In the cluster of markers, 5 of the SARS N protein fragments associated tightly (Fig. 3, bottom). Most of the sera clustered as originating from SARS-infected patients exhibited unambiguous reactivity with this group of markers as expected (Fig. 2B). The SARS sera also exhibited statistically significant binding to one S protein fragment.

Applicants next set out to improve our predictions by identifying the meaningful classifiers and conducting a supervised classification. Since only a limited number of proteins/fragments showed differences between the SARS-CoV-positive and -negative patients (Fig. 3), they selected the top ten features that demonstrated the most significant differences between these two types of patients as candidates for classifier selection (18). Many of the selected candidates were SARS N protein fragments.

To determine the best classifiers and classification model, Applicants applied two different supervised analysis approaches, &-NN (k nearest neighbors){\9) and LR {logistic regression)(2Q). &-NN measures the similarity between a new case and all the known cases to make a prediction, and is determined by the identities of its 'k' closest neighbors (Fig. 4A). Using this method five features were selected by the algorithm as the best classifiers: SARS N (pEGH-55 (Y)), SARS N (pEGH-B4), SARS N-Cl (pEGH-B7), 229E-S 1/4, and SARS S (1st half (Y)) (note that 229E-S1/4 negatively correlates with SARS). The best A: value selected by the model is 9, indicating that the 9 closest neighboring samples to the tested case were used for the prediction. At the confidence cutoff of 0.5, this model achieved 91% accuracy with 15 positive and 18 negative cases missed (163 of 181 positive cases were correct (90% sensitivity); and 203 of 218 negative sera correct (93% specificity)) (Table).

Table. Prediction performance of the two classification methods

Microarray results were also analyzed using an independent method, Logistic

Regression (LR). LR is a generalized linear regression for binary responses (Fig. 4B). The features selected by LR included SARS N-Cl (pEGH-B7), SARS N (pEGH-55) (Y)₅ SARS N (pEGH-B4), and SARS N-C2 (pEGH-B8 #1). The accuracy of this model was 92% (89% sensitivity and 94% specificity). To determine which model, k-NN or LR, performed better, Applicants took advantage of the receiver operating characteristic curve (ROC)(21) (data not shown), and plotted the rate of true positives against that of false positives at different cutoff points. The quality of the model was measured using the area under the curve (AUR). Both AUR values were close to 0.95, indicating that both models performed equally well. Interestingly, although both LR and k-NN predictions exhibited only ~ 92% overlap with the IIFT results (Table 1), 97% of their predictions were shared, indicating that the discrepancy between the models and the standard IIFT test does not depend on the analysis method, but rather on the experimental data. Moreover, although both methods shared only three of the four or five classifiers, they performed equally well. The fact that both k-NN and LR performed similarly prompted Applicants to repeat the probings of the 33 discrepant sera along with some of those that agreed with the predictions. After these probings, eight reproducibly false negative samples remained by both methods, even after a third round of probings. To test whether IgM would yield better results than IgG, particularly for patients during the acute phase of the disease, -90% of the Toronto sera were also probed for IgM reactivity on the microarray. Except for one serum, the probings performed equal to or worse than the IgG probings, consistent with previous results (22-24).

Example 4 Validation of the SARS Proteome Array Classification Method

To further examine the accuracy, sensitivity and specificity of the approach, Applicants conducted another double-blind experiment using 56 sera collected from Chinese patients; 36 of the patients were diagnosed as SARS infected and 20 were diagnosed as uninfected. The experiment differed from the analysis of Canadian patients in that all of the sera were collected from SARS patients who recovered from respiratory disease and the patients came from a different country. Of the 56 serum samples, only one serum was misclassified by Applicants' models (98% accuracy; 100% sensitivity, 95% specificity). Importantly, both the k-^~NN and the LR models predicted this serum to be positive with a confidence value of 1 on a 0 to 1 scale. Taken together, these results demonstrated that the prediction algorithms performed well and accurately identified the SARS infected samples from a large population.

Example 5 Comparing the protein microarray results with ELISAs

To determine how the viral protein microarray compared with the current methods of diagnosis, Applicants compared the performance of two independent ELISA tests on the serum samples from both Canada and China. The Euroimmun ELISA was used on all but three of the serum samples taken from Canadian patients and resulted in 2 false positives, 6 false negative and 26 borderline

(uncertain/inconsistent) classifications. Thus, the Euroimmun ELISA assay is 91% accurate, as compared to 92% accuracy for the proteome array method. The samples missed by the two assays were not identical.

The microarray approach was also compared with a local ELISA used in China that used only the purified N protein. A set of 147 serum samples collected from fever patients during the SARS outbreak in China was used to probe the coronavirus protein microarray. The SARS status of these patients is not known. Similar to the results presented above, Applicants found 85% agreement between the predictions made from the microarray assay and those made from the ELISA; all 70 sera that were SARS-CoV positive by the ELISA were also positive by microarray. The microarray identified an additional 21 sera as SARS-CoV positive that were not found using the ELISA. Since (a) 15 of the 21 serum samples had confidence scores >0.72, the lowest confidence score for the 56 known Chinese SARS infected sera presented above, and (b) the rate of false positives in the assays is less than 7% (the overall specificity for the sera from characterized patients is >99.56%), it is likely that most of these samples originated from SARS patients. In summary, these results indicate that the protein microarray method is at least as sensitive as the Euroimmun ELISA and more sensitive than the local Chinese ELISA, and therefore is an excellent assay for detecting SARS.

Example 6 Anti-SARS antibodies can persist long after initial infection

One useful feature of a serum test relative to a nucleic acid diagnostic test is that anti-SARS antibodies can potentially be detected long after infection. Applicants therefore tested how long anti-SARS antibodies remained present in recovering patients post infection. Serum samples that had been drawn from five Canadian individuals (two respiratory illness other than SARS and three confirmed SARS-CoV cases) at different times post-infection were tested using the protein microarrays (Fig. 5). Reactivity to 5 N proteins (4 SARS N proteins, and one CoV-229E N protein) was scored. Sera from non-SARS patients (1 and 4 in Fig. 5) did not exhibit significant reactivity to any of the five SARS-CoV markers. In contrast, sera from SARS-Co V-positive patients (2, 3 and 5) reacted strongly with each of the SARS N peptides, and for the two cases that were monitored over a long period (120 — 320 days), this reactivity remained high for two N peptides. Furthermore, the above two SARS CoV N antigens were the same ones that reacted most strongly in the 36 SARS confirmed patients from the group of 56 Chinese respiratory patients. These results demonstrate at least some patients retain reactive antibodies for extended periods and they can be detected by protein microarrays.

Example 7 Extending the protein microarray approach to detecting other coronaviruses

Although this study was aimed at developing a systematic screen for SARS infected sera, proteins from other human coronaviruses, such as the HCoV-229E, were included on the microarray, thus, allowing the detection of antibodies directed towards other coronaviruses (25-27). Using 10 HCoV-229E related proteins as classifiers, Applicants identified 82 serum samples with substantial signal (52 of 218 S ARS-Co V- negative (23.9%) and 30 of the 218 SARS-Co V-positive sera (13.8%). The presence of 52 HCoV-229E positive sera in SARS-CoV-negative patients suggests that these patients were or had been infected with the HCoV-229E.

The reactivity of sera from SARS-CoV patients with the HCoV-229E antigens indicates that these patients either have cross-reactive antibodies in their sera, or more likely, had a previous or concurrent HCoV-229E infection in addition to the SARS- CoV infection. The observation that many (150) patients are SARS-CoV positive and lack HCoV-229E antibodies is consistent with the explanation that HCoV-229E infection can occur independently of SARS-CoV infection. Because these sera were not tested for HCoV-229E infection, the number of false positives and negative could not be scored. Nonetheless, these results indicate that our approach can likely be used to diagnose infections from related human coronaviruses.

Materials and methods

The following materials and methods were used in the work described herein. Serum samples The 399 serum samples tested from Canada included 40 acute and 164 convalescent sera from 92 patients who met the clinical and laboratory criteria for SARS-CoV infection during the Toronto SARS outbreak in 2003. Sera from 112 Toronto patients who presented with non-SARS respiratory illness, and 83 sera from health professionals were also included. None of the acute, all 164 of the convalescent and 17 of the sera from 12 healthcare workers demonstrated IgG antibodies as detected using the Euroimmun IIFT test. All positive results were repeated and any unexpected result was confirmed using the SARS-CoV neutralization assay. The Chinese samples were collected from several hospitals in Beijing by the BGI. These sera were collected from 147 non-confirmed fever patients and 56 respiratory patients (36 confirmed SARS-patients and 20 none-SARS individuals). Gene cloning from the coronaviruses

Gene-specific primer pairs were designed based on the sequence of SARS-CoV (GeiiBank accession number: AY278488). The SARS ORFs were amplified by RT- PCR from the SARS-CoV isolate BJOl and cloned into pGEM-T. The SARS ORFs were further cloned into a yeast GST expression vector (pEGH) described previously (12). The same approach was used for the cloning of other coronavirus genes. All clones were confirmed by sequencing their inserts.

Protein purification and protein microarray fabrication The constructs were transformed into yeast and proteins were purified as described previously (13). The GST fusion proteins were eluted into printing buffer containing 20% glycerol in 50 mM HEPES (pH 7.0). For samples that exhibited low yields, the purification was repeated using 50 ml cultures and/or up to 4 times. The coronavirus protein microarrays were fabricated by spotting the purified proteins along with positive control proteins onto 8-pad FAST slides (Schleicher & Schuell, Germany) using a microarrayer (Bio-Rad, USA). The printed arrays were allowed to sit at 4° C overnight and stored at -20° C.

Serum assays on coronavirus protein microarrays An 8-hole rubber gasket (Schleicher & Schuell, Germany) was applied to each microarray to form eight individual chambers. The surfaces were blocked (SuperBlock, Pierce, USA) at room temperature (RT) with gentle shaking. Each serum sample was diluted 200-fold in SuperBlock, and incubated on microarrays at RT for one hour with gentle shaking. The Chinese sera were further filtered before probing the arrays. After gasket removal, the microarrays were washed extensively in a large volume of PBS wash buffer with shaking. To visualize the presence of human antibodies, Cy3- and Cy5-labled anti-human IgG and IgM antibodies (Jackson, Laboratories) were incubated on microarrays at 1000-fold dilution. The arrays were washed with PBS buffer, briefly rinsed with water, and dried. The slides were scanned and signals analyzed using the GenePix Pro 3.0 software.

Reproducibility of the assay was examined both in a blinded and unblinded fashion. First, multiple aliquots of 14 sera from 13 patients were embedded into the serum selection for a total of 32 samples; 19 and 13 sera were derived from SARS- CoV-positive and non-SARS individuals, respectively. Each sample was repeated at least once. Upon unblinding, the IIFT results were compared with those obtained by the arrays. Second, the results obtained from 111 convalescent sera drawn on different dates from 35 SARS-positive patients (2-11 specimens per patient) and for 32 convalescent sera received from 7 none-SARS individuals (2-9 specimens) were evaluated by comparison with those from the microarray probing assays. Array results correlated within patients and agreed for all 70 sera received from 23 of 35 SARS-CoV positive patients, one of whom had a series of 11 positive samples from different dates over nearly a year of follow-up. However, for 6 of 35 patient series (20 samples) a single sample per patient yielded a discrepant negative result by arrays, and in a further 5 patient series (15 samples) two samples gave false negatives. For the unblinded method, 1/4 of the serum samples (97) that were classified correctly and near the borderline were probed a second time. -90% yielded results similar to the first probings.

Data normalization and hierarchical clustering

Given the nature of each serum we collected, we expected a wide range of antibody titer. To compensate for this effect in the final clustering and classification, we log transformed the intensities and then normalized the numbers in a way that each probing had the same median and MAD (median absolute deviation) values (see online supporting data). Divisive hierarchical clustering was then applied to both the sera and the array features using S-Plus 6.1 (17).

K-nearest neighbor

X-Nearest Neighbor stores a group of known cases and classifies new instances based on a similarity measure (19). The new instance is classified according to the identities of its nearest neighbors. The number of the neighbors is determined by the parameter k, and the similarity is measured as the Euclidean distance using the signals of the classifiers. The best parameters were selected in the learning process and applied in the predicting process. In the learning process, all parameters including possible k's and candidate classifiers were tested and their performance was evaluated by ten fold cross validation to find the best values (29). In the prediction process, the k nearest neighbors were retrieved for each new instance, and classifications were made according to the memberships of the neighbors.

Logistic regression

Logistic regression is a generalized linear regression model designed for binary responses(20). However, no missing values for the candidate features are allowed in model construction; thus the number of sera analyzed (~370) was less than the total screened. The candidate features were selected by the model using both-direction stepwise search with Akaike information criterion (30). We performed this analysis using S-Plus 6.1 software that selected the top four features out of the candidate list for the prediction step. Finally, the probability of each serum to be positive was calculated using those features, and those that had a value greater than 0.5 were classified as SARS-CoV positive.

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INCORPORATION BY REFERENCE

All publications and patents mentioned herein are hereby incorporated by reference in their entirety as if each individual publication or patent was specifically and individually indicated to be incorporated by reference.

EQUIVALENTS

While the above description contains many specific details of methods in accordance with this invention, these specific details should not be construed as limitations on the scope of the invention, but merely as exemplifications of preferred embodiments thereof. Those skilled in the art will envision many other possible variations that fall within the scope and spirit of the invention as defined by the claims appended hereto.

Claims

We claim:

1. A virus protein microarray comprising one or more proteins of a SARS- coronavirus.

2. The virus protein microarray of claim 1, wherein the one or more proteins of a SARS-coronavirus is selected from the group consisting of: SARS spike

(S)protein or a fragment thereof; SARS small envelope (E) protein or a fragment thereof; SARS membrane (M) protein or a fragment thereof; SARS nucleocapsid (N) protein or a fragment thereof; and a SARS protein identified in Figure 6 or a fragment thereof 3. The virus protein microarray of claim 2, wherein the microarray additionally comprises at least one reference protein.

4. The virus protein microarray of claim 3, wherein the at least one reference protein is from a virus selected from the group consisting of: Human Coronavirus (HCoV) 229E; mouse MHV A59; Bovine coronavirus (BCoV); HCoV OC43; Avian infectious bronchitis virus; Canine coronavirus; Murine hepatitis virus; Porcine epidemic diarrhea virus; Porcine hemagglutinating encephalomyelitis virus; Porcine transmissible gastroenteritis virus; Rat coronavirus; Turkey coronavirus; Rabbit coronavirus; Feline infectious peritonitis virus (FIPV); an animal Torovirus; Berne virus; and Breda virus.

5. The virus protein microarray of claim 2, wherein the one or more proteins of a SARS coronavirus is the N protein or a fragment thereof.

6. The virus protein mocroarray of claim 5, wherein the N protein comprises a short lysine-rich region or is a C-terminal fragment of the SARS N protein.

7. A virus protein microarray comprising the entire or essentially all of the proteome of a coronavirus.

8. The virus protein microarray of claim 7, wherein the coronavirus is SARS coronavirus.

9. The virus protein microarray of claim 8, which additionally comprises the partial proteome of at least one coronavirus other than SARS coronavirus.

10. The virus protein microarray of claim 9, wherein the at least one coronavirus other than SARS coronavirus is selected from the group consisting of: Human Coronaviras (HCoV) 229E; mouse MHV A59; Bovine coronaviras (BCoV); HCoV OC43; Avian infectious bronchitis virus; Canine coronaviras; Murine hepatitis virus; Porcine epidemic diarrhea virus; Porcine hemagglutinating encephalomyelitis virus; Porcine transmissible gastroenteritis virus; Rat coronavirus; Turkey coronaviras;

Rabbit coronaviras; Feline infectious peritonitis virus (FIPV); an animal Torovirus; Berne virus; and Breda virus.

11. A virus protein microarray comprising all or essentially all of the SARS coronvavirus proteins and at least one protein from a coronaviras which is not SARS coronaviras.

12. The virus protein microarray of claim 11, which additionally comprises at least one of the following proteins from a coronaviras which is not SARS coronaviras: all or a portion of the proteome of the HCoV-229E virus; all or a portion of the proteome of human HCoV-OC43; all or a portion of the proteome of Mouse MHV-A59; all or a portion of the proteome of Bovine coronaviras BCoV; all or a portion of the proteome of Feline coronavirus FIPV, all or a portion of the proteome of Avian infectious bronchitis virus, all or a portion of the proteome of Canine coronaviras, all or a portion of the proteome of Murine hepatitis virus, all or a portion of the proteome of Porcine epidemic diarrhea virus, all or a portion of the proteome of Porcine hemagglutinating encephalomyelitis virus, all or a portion of the proteome of Porcine transmissible gastroenteritis virus, all or a portion the proteome of of Rat coronaviras, all or a portion of the proteome of Turkey coronaviras, all or a portion of the proteome of Rabbit coronaviras, all or a portion of the proteome of an animal Torovirus, all or a portion of the proteome of Berne virus, and all or a portion of the proteome of Breda virus.

13. A coronaviras protein microarray comprising at least one SARS coronaviras marker protein.

14. The coronavirus protein microarray of claim 13, which comprises a set of proteins selected from the proteins listed in Figure 6, or fragments thereof, wherein the set of proteins or fragments thereof on the microarray is specific for antibodies to SARS coronaviras proteins and is useful to distinguish between sera that contain antibodies to SARS coronavirus proteins and sera that do not contain antibodies to SARS coronavirus proteins.

15. The coronavirus protein microarray of claim 14, which additionally comprises at least one protein from a coronavirus which is not SARS coronavirus.

16. The coronavirus protein microarray of claim 15, which additionally comprises at least one of the following proteins from a coronavirus which is not SARS coronavirus: all or a portion of the HCoV-229E virus; all or a portion of human HCoV-OC43; all or a portion of Mouse MHV- A59; all or a portion of Bovine coronavirus BCoV; all or a portion of Feline coronavirus FIPV, all or a portion of Avian infectious bronchitis virus, all or a portion of Canine coronavirus, all or a portion of Murine hepatitis virus, all or a portion of Porcine epidemic diarrhea virus, all or a portion of Porcine hemagglutinating encephalomyelitis virus, all or a portion of Porcine transmissible gastroenteritis virus, all or a portion of Rat coronavirus, all or a portion of Turkey coronavirus, all or a portion of Rabbit coronavirus, all or a portion of an animal Torovirus, all or a portion of Berne virus, and all or a portion of Breda virus.

17. The coronavirus protein microarray of claim 14, which additionally comprises all or a portion of the HCoV-229E virus; all or a portion of human HCoV-OC43; all or a portion of Mouse MHV- A59; all or a portion of Bovine coronavirus BCoV; all or a portion of Feline coronavirus FIPV, all or a portion of Avian infectious bronchitis virus, all or a portion of Canine coronavirus, all or a portion of Murine hepatitis virus, all or a portion of Porcine epidemic diarrhea virus, all or a portion of Porcine hemagglutinating encephalomyelitis virus, all or a portion of Porcine transmissible gastroenteritis virus, all or a portion of Rat coronavirus, all or a portion of Turkey coronavirus, all or a portion of Rabbit coronavirus, all or a portion of an animal Torovirus, all or a portion of Berne virus, and all or a portion of Breda virus.

18. The coronavirus protein microarray of any one of claims 13-17, wherein the at least one SARS coronavirus marker protein is the SARS N protein or a fragment thereof.

19. The coronavirus protein microarray of claim 18, wherein the SARS N protein comprises a short lysine-rich region or is a C-terminal fragment of the SARS N protein.

20. A method for detecting one or more antibodies to a SARS -coronavirus in a sample comprising: a. providing one or more marker proteins of a S ARS-coronavirus; b. combining the one or more marker proteins with the sample; c. determining if interaction occurs between one or more marker proteins and one or more proteins (antibodies) in the sample, wherein the detection of interaction between one or more marker proteins with one or more proteins (antibodies)in the sample is indicative of the presence of one or more antibodies to SARS -coronavirus.

21. The method of claim 20, wherein the one or more marker proteins are present on a protein microarray.

22. The method of claim 21, wherein the sample is a serum sample from an individual.

23. The method of claim 22, wherein the individual is thought to be infected with a SARS-coronavirus or has recovered from infection by a SARS coronavirus.

24. The method of claim 23, wherein the individual is suspected of ongoing infection by a SARS-coronavirus and the method is carried out periodically in order to monitor the progression of infection by the SARS coronavirus

25. A method of identifying a drug that binds to a SARS coronavirus protein, comprising contacting a drug to be assessed for its ability to bind a SARS coronavirus protein with a SARS coronavirus protein microarray of any one of claims 1-19, under conditions appropriate for binding of the drug to a SARS coronavirus protein and determining if binding occurs, wherein, if binding is detected, the drug to be assessed is a drug that binds a SARS coronavirus protein.

26. The method of claim 25, wherein the drag to be assessed is a small molecule or an antibody.

27. The method of claim 25, wherein a library of drags is contacted with the SARS coronavirus protein microarray.

28. The method of claim 27, wherein the library of drags is a library of small molecules.

29. A method of assessing the effect of treatment provided to an individual infected with SARS coronavirus, comprising assessing a sample of serum from the individual for antibodies to SARS coronavirus prior to treatment and following treatment and determining if there is a difference in the quantity of antibodies in the individual's serum after treatment, wherein a difference is indicative of an effect of the treatment.