WO2015164617A1

WO2015164617A1 - Tuberculosis biomarkers in urine and uses thereof

Info

Publication number: WO2015164617A1
Application number: PCT/US2015/027318
Authority: WO
Inventors: Urs Ochsner; David Sterling; Stephen Kraemer; Nebojsa Janjic
Original assignee: Somalogic, Inc.
Priority date: 2014-04-24
Filing date: 2015-04-23
Publication date: 2015-10-29

Abstract

The present application relates generally to biomarkers for tuberculosis infection and methods of detection thereof. In various embodiments, the invention relates to one or more biomarkers, biomarker panels, methods, devices, reagents, systems, and kits for detecting and/or characterizing tuberculosis infection in an individual from a urine sample.

Description

TUBERCULOSIS BIOMARKERS IN URINE AND USES THEREOF

FIELD

BACKGROUND

Tuberculosis (TB) is caused by a bacterium called Mycobacterium tuberculosis. The bacteria usually attack the lungs, but TB bacteria can attack any part of the body such as the kidney, spine, and brain. If not treated properly, TB disease can be fatal. Not everyone infected with TB bacteria becomes sick. As a result, two TB-related conditions exist: latent TB infection and TB disease. Both latent TB infection and TB disease can be treated.

SUMMARY

In some embodiments, methods are provided for detecting the level of at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, at least ten, at least eleven, at least twelve, or at least thirteen Mtb biomarkers identified in experiments conducted during development of embodiments of the present invention. In some embodiments, biomarkers are selected from MP64, ACR, CH602, PstSl, DnaK, MASZ, CH10, RL7, TPX, CF30, KAD, MPT51, EsxB, EsxA, A85A, A85B, A95C, or any sub- combinations thereof. In some embodiments, a method comprises detecting the level of one or more biomarkers in a sample from a subject. In some embodiments, a sample is a urine sample

In some embodiments, a method of detecting or diagnosing TB infection in a subject comprises forming a biomarker panel having N biomarker proteins from Mtb biomarkers identified in experiments conducted during development of embodiments of the present invention (e.g., comprising MP64, ACR, CH602, PstSl, DnaK, MASZ, CH10, RL7, TPX, CF30, KAD, MPT51 , EsxB, EsxA, A85 A, A85B, A95C, or any sub-combinations thereof), and detecting the level of each of the N biomarker proteins of the panel in a sample from the subject. In some embodiments, N is 1 to 5. In some embodiments, N is 2 to 10. In some embodiments, N is 3 to 10. In some embodiments, N is 4 to 10. In some embodiments, N is 5 to 10. In some embodiments, N is 10 to 20. In some embodiments, N is 5 to 20. In some embodiments, N is 5 to 30. In some embodiments, N is 10 to 30. In some embodiments, N is 20 to 30. In some embodiments, at least one (e.g., 1-13) of the N biomarker proteins is selected from MP64, ACR, CH602, PstSl, DnaK, MASZ, CHIO, RL7, TPX, CF30, KAD, MPT51, EsxB, EsxA, A85A, A85B, and A95C. In some embodiments, methods comprise panels of any combination of the Mtb biomarkers identified in experiments conducted during development of embodiments of the present invention (e.g., MP64, ACR, CH602, PstSl, DnaK, MASZ, CHIO, RL7, TPX, CF30, KAD, MPT51, EsxB, EsxA, A85A, A85B, A95C, or any sub-combinations thereof), in addition to any other TB biomarkers.

In some embodiments, biomarker panels are provided having reagents for the detection of N biomarker proteins from the Mtb biomarkers identified in experiments conducted during development of embodiments of the present invention (e.g., comprising MP64, ACR, CH602, PstSl, DnaK, MASZ, CHIO, RL7, TPX, CF30, KAD, MPT51, EsxB, EsxA, A85A, A85B, A95C, or any sub-combinations thereof). In some embodiments, N is 1 to 5. In some embodiments, N is 2 to 10. In some embodiments, N is 3 to 10. In some embodiments, N is 4 to 10. In some embodiments, N is 5 to 10. In some embodiments, N is 10 to 20. In some embodiments, N is 5 to 20. In some embodiments, N is 5 to 30. In some embodiments, N is 10 to 30. In some embodiments, N is 20 to 30. In some embodiments, at least one (e.g., 1-13) of the N biomarker proteins is selected from MP64, ACR, CH602, PstSl, DnaK, MASZ, CHIO, RL7, TPX, CF30, KAD, MPT51, EsxB, EsxA, A85A, A85B, and A95C. In some embodiments, panels of any combination of the Mtb biomarkers identified in experiments conducted during development of embodiments of the present invention (e.g., MP64, ACR, CH602, PstSl, DnaK, MASZ, CHIO, RL7, TPX, CF30, KAD, MPT51, EsxB, EsxA, A85A, A85B, A95C, or any sub-combinations thereof), in addition to any other TB biomarkers.

In any of the embodiments described herein, the each biomarker may be a protein biomarker. In any of the embodiments described herein, the method may comprise contacting biomarkers of the sample from the subject with a set of biomarker capture reagents, wherein each biomarker capture reagent of the set of biomarker capture reagents specifically binds to a biomarker being detected. In some embodiments, each biomarker capture reagent of the set of biomarker capture reagents specifically binds to a different biomarker being detected. In any of the embodiments described herein, each biomarker capture reagent may be an antibody or an aptamer. In any of the embodiments described herein, each biomarker capture reagent may be an aptamer. In any of the embodiments described herein, at least one aptamer may be a slow off-rate aptamer. In any of the embodiments described herein, at least one slow off-rate aptamer may comprise at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, or at least 10 nucleotides with modifications. In some embodiments, the modifications are hydrophobic modifications. In some embodiments, the modifications are hydrophobic base modifications. In some embodiments, each slow off-rate aptamer binds to its target protein with an off rate (t½) of > 30 minutes, > 60 minutes, > 90 minutes, > 120 minutes, > 150 minutes, > 180 minutes, > 210 minutes, or > 240 minutes.

In any of the embodiments described herein, the sample may be a urine sample. In some embodiments, the urine sample is filtered, concentrated (e.g., 2-fold, 5-fold, 10 fold, 20-fold, 50-fold, 100-fold, or more), diluted, or un-manipulated.

In any of the embodiments described herein, a method may further comprise treating the subject for TB infection. In some embodiments, treating the subject for TB infection comprises a treatment regimen of administering one or more of: isoniazid (INH), rifampin (RIF), rifapentine (RPT), ethambutol (EMB), pyrazinamide (PZA), and/or another approved TB therapeutic to the subject.

In some embodiments, methods of monitoring progression or severity of TB infection and/or monitoring effectiveness of treatment in a subject are provided. In some

embodiments, a method comprises detecting the level of one or more TB biomarkers identified in experiments conducted during development of embodiments of the present invention (e.g., MP64, ACR, CH602, PstSl, DnaK, MASZ, CH10, RL7, TPX, CF30, KAD, MPT51, EsxB, EsxA, A85A, A85B, and A95C) in a sample from the subject at a first time point. In some embodiments, the method further comprises measuring the level one or more of the biomarkers at a second time point. In some embodiments, TB infection severity is improving (e.g., declining) if the level of said biomarkers improved at the second time point than at the first time point.

In some embodiments, kits are provided. In some embodiments, a kit comprises at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, or at least nine aptamers, at least ten aptamers, wherein each aptamer specifically binds to a different target protein selected from the Mtb biomarkers identified in experiments conducted during development of embodiments of the present invention (e.g., MP64, ACR, CH602, PstSl, DnaK, MASZ, CH10, RL7, TPX, CF30, KAD, MPT51, EsxB, EsxA, A85A, A85B, and A95C). In some embodiments, a kit comprises N aptamers. In some

embodiments, N is 1 to 30. In some embodiments, N is 2 to 30. In some embodiments, N is 3 to 30. In some embodiments, N is 4 to 30. In some embodiments, N is 5 to 30. In some embodiments, N is 1 to 10. In some embodiments, N is 2 to 10. In some embodiments, N is 3 to 10. In some embodiments, N is 4 to 10. In some embodiments, N is 5 to 10. In some embodiments, at least one of the N biomarker proteins is selected from the Mtb biomarkers identified in experiments conducted during development of embodiments of the present invention (e.g., MP64, ACR, CH602, PstSl, DnaK, MASZ, CH10, RL7, TPX, CF30, KAD, MPT51, EsxB, EsxA, A85A, A85B, and A95C).

In some embodiments, compositions are provided comprising proteins of a sample from a subject and at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, or nine aptamers, or more (e.g., 10, 11, 12, 13, or more) wherein each aptamer specifically binds to a different target protein selected from the Mtb biomarkers identified in experiments conducted during development of embodiments of the present invention (e.g., MP64, ACR, CH602, PstSl, DnaK, MASZ, CH10, RL7, TPX, CF30, KAD, MPT51, EsxB, EsxA, A85A, A85B, and A95C). In some embodiments, a composition comprises proteins of a sample from a subject and N aptamers. In some embodiments, N is 1 to 30. In some embodiments, N is 2 to 30. In some embodiments, N is 3 to 30. In some embodiments, N is 4 to 30. In some embodiments, N is 5 to 30. In some embodiments, N is 1 to 10. In some embodiments, N is 2 to 10. In some embodiments, N is 3 to 10. In some embodiments, N is 4 to 10. In some embodiments, N is 5 to 10.

In any of the embodiments, described herein, the sample in a composition is a urine sample. In some embodiments, the urine sample is filtered, concentrated (e.g., 2-fold, 5-fold, 10 fold, 20-fold, 50-fold, 100-fold, or more), diluted, or un-manipulated.

In any of the embodiments described herein, a kit or composition may comprise at least one aptamer that is a slow off-rate aptamer. In any of the embodiments described herein, each aptamer of a kit or composition may be a slow off-rate aptamer. In some embodiments, at least one slow off-rate aptamer comprises at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, or at least 10 nucleotides with modifications. In some embodiments, at least one nucleotide with a modification is a nucleotide with a hydrophobic base modification. In some embodiments, each nucleotide with a modification is a nucleotide with a hydrophobic base modification. In some embodiments, each slow off-rate aptamer in a kit binds to its target protein with an off rate (t½) of > 30 minutes, > 60 minutes, > 90 minutes, > 120 minutes, > 150 minutes, > 180 minutes, > 210 minutes, or > 240 minutes.

BRIEF DESCRIPTION OF FIGURES Figure 1 shows SDS-PAGE analysis of Mtb proteins used for SELEX.

Figure 2 shows a schematic of the SELEX process, including the structures of certain modified bases used in the randomized libraries.

Figure 3A-B shows qualification of t£-specific SOMAmers for SOMAscan by slide hybridization assay using (A) protein titrations, and (B) pull-down assays.

Figure 4 shows examples of validation of Mtb SOMAmers with fractions from a human macrophage infection model (quadruplicate samples).

Figure 5 shows a volcano plot of TB markers in urine, from a small pilot study.

Figure 6 shows scatter plots of Mtb SOMAmer measurements in urine of TB versus non-TB patients, in HIV-negative and HIV-positive populations. Samples with elevated Mtb SOMAmer measurements are highlighted.

Figure 7 shows detection of Mtb proteins in urine, shown as the number of proteins with elevated cut-off 2.5-5 standard deviations above the non-TB medians.

Figure 8 shows correlation of protein size and detection in urine.

Figure 9 shows spike and recovery of EsxB in urine, serum, and plasma.

Figure 10 shows a volcano plot of TB markers in plasma, from a small pilot study.

Figure 11 shows a volcano plot of TB markers in urine, from a small pilot study.

Figure 12 shows background signals of Mtb SOMAmers compared to spuriomers observed in 40% serum (Non-TB serum from FIND and QC serum).

Figure 13 shows a schematic of post-SELEX modifications to optimize performance of lead candidate reagents, via truncations from both ends until activity is lost (red line), identification of nonessential positions (-) to be replaced by linker (HEG, hexaethylene glycol) and positions that can accommodate 2'0-methyl substitutions (m), and introduction of 5-position variants (iB, isobutyl-dU, Th, thiophene-dU).

Figure 14 shows an example of SOMAscan accuracy determined via spike and recovery assays and dilution linearity assessment.

DETAILED DESCRIPTION

Experiments conducted during development of embodiments of the present invention to develop a proteomic signature for the diagnosis of pulmonary TB (e.g., in adult subjects) that is based (e.g., based solely) on Mtb proteins that are identifiable and detectable, for example in a urine sample from an individual, and allow discrimination between a TB infected and non-infected individuals.

While the invention will be described in conjunction with certain representative embodiments, it will be understood that the invention is defined by the claims, and is not limited to those embodiments.

One skilled in the art will recognize many methods and materials similar or equivalent to those described herein may be used in the practice of the present invention. The present invention is in no way limited to the methods and materials described.

Unless defined otherwise, technical and scientific terms used herein have the meaning commonly understood by one of ordinary skill in the art to which this invention belongs. Although any methods, devices, and materials similar or equivalent to those described herein can be used in the practice of the invention, certain methods, devices, and materials are described herein.

All publications, published patent documents, and patent applications cited herein are hereby incorporated by reference to the same extent as though each individual publication, published patent document, or patent application was specifically and individually set forth in full herein.

As used in this application, including the appended claims, the singular forms "a," "an," and "the" include the plural, unless the context clearly dictates otherwise, and may be used interchangeably with "at least one" and "one or more." Thus, reference to "an aptamer" includes mixtures of aptamers, reference to "a probe" includes mixtures of probes, and the like.

As used herein, the terms "comprises," "comprising," "includes," "including," "contains," "containing," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, product-by-process, or composition of matter that comprises, includes, or contains an element or list of elements may include other elements not expressly listed.

As used herein, a "capture agent' or "capture reagent" refers to a molecule that is capable of binding specifically to a biomarker. A "target protein capture reagent" refers to a molecule that is capable of binding specifically to a target protein. Nonlimiting exemplary capture reagents include aptamers, antibodies, adnectins, ankyrins, other antibody mimetics and other protein scaffolds, autoantibodies, chimeras, small molecules, nucleic acids, lectins, ligand-binding receptors, imprinted polymers, avimers, peptidomimetics, hormone receptors, cytokine receptors, synthetic receptors, and modifications and fragments of any of the aforementioned capture reagents. In some embodiments, a capture reagent is selected from an aptamer and an antibody.

The term "antibody" refers to full-length antibodies of any species and fragments and derivatives of such antibodies, including Fab fragments, F(ab')₂ fragments, single chain antibodies, Fv fragments, and single chain Fv fragments. The term "antibody" also refers to synthetically-derived antibodies, such as phage display-derived antibodies and fragments, affybodies, nanobodies, etc.

As used herein, "marker" and "biomarker" are used interchangeably to refer to a target molecule that indicates or is a sign of a normal or abnormal process in an individual or of a disease or other condition in an individual. More specifically, a "marker" or

"biomarker" is an anatomic, physiologic, biochemical, or molecular parameter associated with the presence of a specific physiological state or process, whether normal or abnormal, and, if abnormal, whether chronic or acute. Biomarkers are detectable and measurable by a variety of methods including laboratory assays and medical imaging. In some embodiments, a biomarker is a target protein.

As used herein, "biomarker level" and "level" refer to a measurement that is made using any analytical method for detecting the biomarker in a biological sample and that indicates the presence, absence, absolute amount or concentration, relative amount or concentration, titer, a level, an expression level, a ratio of measured levels, or the like, of, for, or corresponding to the biomarker in the biological sample. The exact nature of the "level" depends on the specific design and components of the particular analytical method employed to detect the biomarker.

A "control level" of a target molecule refers to the level of the target molecule in the same sample type from an individual that does not have the disease or condition, or from an individual that is not suspected or at risk of having the disease or condition, or from an individual that has a non-progressive form of the disease or condition. A "control level" of a target molecule need not be determined each time the present methods are carried out, and may be a previously determined level that is used as a reference or threshold to determine whether the level in a particular sample is higher or lower than a normal level. In some embodiments, a control level in a method described herein is the level that has been observed in one or more subjects without TB infection or active TB. In some embodiments, a control level in a method described herein is the average or mean level, optionally plus or minus a statistical variation, that has been observed in a plurality of subjects without TB infection or active TB.

As used herein, "individual" and "subject" are used interchangeably to refer to a test subject or patient. The individual can be a mammal or a non-mammal. In various embodiments, the individual is a mammal. A mammalian individual can be a human or non- human. In various embodiments, the individual is a human. A healthy or normal individual is an individual in which the disease or condition of interest (such as TB) is not detectable by conventional diagnostic methods.

"Diagnose", "diagnosing", "diagnosis", and variations thereof refer to the detection, determination, or recognition of a health status or condition of an individual on the basis of one or more signs, symptoms, data, or other information pertaining to that individual. The health status of an individual can be diagnosed as healthy / normal (i.e., a diagnosis of the absence of a disease or condition) or diagnosed as ill / abnormal (i.e., a diagnosis of the presence, or an assessment of the characteristics, of a disease or condition). The terms "diagnose", "diagnosing", "diagnosis", etc., encompass, with respect to a particular disease or condition, the initial detection of the disease; the characterization or classification of the disease; the detection of the progression, remission, or recurrence of the disease; and the detection of disease response after the administration of a treatment or therapy to the individual.

"Prognose", "prognosing", "prognosis", and variations thereof refer to the prediction of a future course of a disease or condition in an individual who has the disease or condition (e.g., predicting patient survival), and such terms encompass the evaluation of disease response after the administration of a treatment or therapy to the individual.

As used herein, "detecting" or "determining" with respect to a biomarker level includes the use of both the instrument used to observe and record a signal corresponding to a biomarker level and the material/s required to generate that signal. In various embodiments, the level is detected using any suitable method, including fluorescence, chemiluminescence, surface plasmon resonance, surface acoustic waves, mass spectrometry, infrared

spectroscopy, Raman spectroscopy, atomic force microscopy, scanning tunneling

microscopy, electrochemical detection methods, nuclear magnetic resonance, quantum dots, and the like.

"Solid support" refers herein to any substrate having a surface to which molecules may be attached, directly or indirectly, through either covalent or non-covalent bonds. A "solid support" can have a variety of physical formats, which can include, for example, a membrane; a chip (e.g., a protein chip); a slide (e.g., a glass slide or coverslip); a column; a hollow, solid, semi-solid, pore- or cavity- containing particle, such as, for example, a bead; a gel; a fiber, including a fiber optic material; a matrix; and a sample receptacle. Exemplary sample receptacles include sample wells, tubes, capillaries, vials, and any other vessel, groove or indentation capable of holding a sample. A sample receptacle can be contained on a multi-sample platform, such as a microtiter plate, slide, microfluidics device, and the like. A support can be composed of a natural or synthetic material, an organic or inorganic material. The composition of the solid support on which capture reagents are attached generally depends on the method of attachment (e.g., covalent attachment). Other exemplary receptacles include microdroplets and microfluidic controlled or bulk oil/aqueous emulsions within which assays and related manipulations can occur. Suitable solid supports include, for example, plastics, resins, polysaccharides, silica or silica-based materials, functionalized glass, modified silicon, carbon, metals, inorganic glasses, membranes, nylon, natural fibers (such as, for example, silk, wool and cotton), polymers, and the like. The material composing the solid support can include reactive groups such as, for example, carboxy, amino, or hydroxyl groups, which are used for attachment of the capture reagents. Polymeric solid supports can include, e.g., polystyrene, polyethylene glycol tetraphthalate, polyvinyl acetate, polyvinyl chloride, polyvinyl pyrrolidone, polyacrylonitrile, polymethyl

methacrylate, polytetrafluoroethylene, butyl rubber, styrenebutadiene rubber, natural rubber, polyethylene, polypropylene, (poly)tetrafluoroethylene, (poly)vinylidenefluoride,

polycarbonate, and polymethylpentene. Suitable solid support particles that can be used include, e.g., encoded particles, such as Luminex^®-type encoded particles, magnetic particles, and glass particles.

As used herein "host biomarkers" are biological molecules (e.g., proteins) that are endogenous to an individual, the expression or level of which is altered (e.g., increased or decreased) upon infection by a pathogenic agent (e.g., Mycobacterium tuberculosis).

Detection and/or quantification of host biomarkers allows for diagnosis of pathogen infection.

As used herein "pathogen biomarkers" are molecules (e.g., proteins) that are not endogenous to an individual, but produced by a pathogen (e.g., Mycobacterium tuberculosis) that has infected the individual. Detection and/or quantification of pathogen biomarkers (e.g., Mtb biomarkers) allows for diagnosis of pathogen infection.

The present application includes biomarkers, methods, devices, reagents, systems, and kits for detecting, identifying, characterizing, and/or diagnosing infection of a subject (e.g., human subject) with Mycobacterium tuberculosis {Mtb) infection (e.g., TB infection) or tuberculosis (TB).

In one aspect, one or more biomarkers (e.g., Mtb biomarkers) are provided for use either alone or in various combinations to identify TB infection. As described in herein, exemplary embodiments include the TB biomarkers identified in experiments conducted during development of embodiments of the present invention (e.g., MP64, ACR, CH602, PstSl, DnaK, MASZ, CH10, RL7, TPX, CF30, KAD, MPT51, EsxB, EsxA, A85A, A85B, and A95C).

While the described biomarkers are useful alone or in combination for detecting TB infection, methods are also described herein for grouping the one or more of the biomarkers with additional biomarkers not described herein. In some embodiments, panels of at least two, at least three, at least four, at least five, or at least 6 biomarkers described herein are provided.

In some embodiments, methods comprises contacting a sample (e.g., urine, concentrated urine, filtered urine, diluted urine, etc.) or a portion of the sample from a subject with at least one capture reagent, wherein each capture reagent specifically binds a biomarker whose presence or levels are being detected. In some embodiments, the method comprises contacting the sample, or proteins from the sample, with at least one aptamer, wherein each aptamer specifically binds a biomarker whose levels are being detected.

Exemplary Uses of Biomarkers

In various exemplary embodiments, methods are provided for determining whether a subject is infected with Mycobacterium tuberculosis (TB infection) and/or is suffering from Tuberculosis (TB). Methods are also provided for assessing the effectiveness of TB treatment. In some embodiments, biomarkers are indicative of co-infection with TB and human immunodeficiency virus (HIV). In some embodiments, biomarkers are indicative of infection with TB but not HIV. In some embodiments, methods comprise detecting the presence of one or more biomarkers (e.g., Mtb biomarkers). In some embodiments, methods comprise measuring the level or concentrations of one or more biomarkers by any number of analytical methods, including any of the analytical methods described herein. These biomarkers are, for example, present at different levels in TB-positive and TB-negative subjects (e.g., present in TB⁺ subjects and absent in TB^" subjects). In some embodiments, detection of the differential levels of a biomarker in an individual can be used, for example, to permit the determination of whether the individual has TB infection, active TB, etc. ). In some embodiments, detection of the presence of a biomarker in an individual can be used, for example, to permit the determination that the individual has TB infection and/or active TB, etc. In some embodiments, any of the biomarkers described herein may be used to monitor TB infection in an individual over time, and to permit the determination of treatment is effective.

In addition to testing biomarker levels and/or presence (e.g., one or more of the TB biomarkers identified in experiments conducted during development of embodiments of the present invention (e.g., MP64, ACR, CH602, PstSl, DnaK, MASZ, CHIO, RL7, TPX, CF30, KAD, MPT51, EsxB, EsxA, A85A, A85B, and A95C) as a stand-alone diagnostic test, in some embodiments, biomarker levels are tested in conjunction with other markers or assays indicative of TB (e.g., skin test, sputum culture, blood test, tissue culture, body fluid culture, chest x-ray, etc.). In addition to testing biomarker levels in conjunction with other TB diagnostic methods, information regarding the biomarkers can also be evaluated in conjunction with other types of data, particularly data that indicates an individual's risk for TB (e.g., lifestyle, location, age, etc.). These various data can be assessed by automated methods, such as a computer program/software, which can be embodied in a computer or other apparatus/device.

Detection and Determination of Biomarkers and Biomarker Levels

Detection of a biomarker and/or determining biomarker level for the biomarkers described herein can be done using any of a variety of known analytical methods. In one embodiment, biomarker presence and/or level is detected using a capture reagent. In various embodiments, the capture reagent can be exposed to the biomarker in solution or can be exposed to the biomarker while the capture reagent is immobilized on a solid support. In other embodiments, the capture reagent contains a feature that is reactive with a secondary feature on a solid support. In these embodiments, the capture reagent can be exposed to the biomarker in solution, and then the feature on the capture reagent can be used in conjunction with the secondary feature on the solid support to immobilize the biomarker on the solid support. The capture reagent is selected based on the type of analysis to be conducted.

Capture reagents include but are not limited to aptamers, antibodies, adnectins, ankyrins, other antibody mimetics and other protein scaffolds, autoantibodies, chimeras, small molecules, F(ab')₂ fragments, single chain antibody fragments, Fv fragments, single chain Fv fragments, nucleic acids, lectins, ligand-binding receptors, affybodies, nanobodies, imprinted polymers, avimers, peptidomimetics, hormone receptors, cytokine receptors, and synthetic receptors, and modifications and fragments of these.

In some embodiments, a biomarker level is detected using a biomarker/capture reagent complex.

In some embodiments, the biomarker presence and/or level is derived from the biomarker/capture reagent complex and is detected indirectly, such as, for example, as a result of a reaction that is subsequent to the biomarker/capture reagent interaction, but is dependent on the formation of the biomarker/capture reagent complex.

In some embodiments, the biomarker presence and/or level is detected directly from the biomarker in a biological sample (e.g., urine).

In some embodiments, biomarkers are detected using a multiplexed format that allows for the simultaneous detection of two or more biomarkers in a biological sample. In some embodiments of the multiplexed format, capture reagents are immobilized, directly or indirectly, covalently or non-covalently, in discrete locations on a solid support. In some embodiments, a multiplexed format uses discrete solid supports where each solid support has a unique capture reagent associated with that solid support, such as, for example quantum dots. In some embodiments, an individual device is used for the detection of each one of multiple biomarkers to be detected in a biological sample. Individual devices can be configured to permit each biomarker in the biological sample to be processed simultaneously. For example, a microtiter plate can be used such that each well in the plate is used to analyze one or more of multiple biomarkers to be detected in a biological sample.

In one or more of the foregoing embodiments, a fluorescent tag is used to label a component of the biomarker/capture reagent complex to enable the detection of the biomarker level. In various embodiments, the fluorescent label can be conjugated to a capture reagent specific to any of the biomarkers described herein using known techniques, and the fluorescent label can then be used to detect the corresponding biomarker level.

Suitable fluorescent labels include rare earth chelates, fluorescein and its derivatives, rhodamine and its derivatives, dansyl, allophycocyanin, PBXL-3, Qdot 605, Lissamine, phycoerythrin, Texas Red, and other such compounds.

In some embodiments, the fluorescent label is a fluorescent dye molecule. In some embodiments, the fluorescent dye molecule includes at least one substituted indolium ring system in which the substituent on the 3 -carbon of the indolium ring contains a chemically reactive group or a conjugated substance. In some embodiments, the dye molecule includes an AlexFluor molecule, such as, for example, AlexaFluor 488, AlexaFluor 532, AlexaFluor 647, AlexaFluor 680, or AlexaFluor 700. In some embodiments, the dye molecule includes a first type and a second type of dye molecule, such as, e.g., two different AlexaFluor molecules. In some embodiments, the dye molecule includes a first type and a second type of dye molecule, and the two dye molecules have different emission spectra.

Fluorescence can be measured with a variety of instrumentation compatible with a wide range of assay formats. For example, spectrofluorimeters have been designed to analyze microtiter plates, microscope slides, printed arrays, cuvettes, etc. See Principles of Fluorescence Spectroscopy, by J.R. Lakowicz, Springer Science + Business Media, Inc., 2004. See Bio luminescence & Chemiluminescence: Progress & Current Applications; Philip E. Stanley and Larry J. Kricka editors, World Scientific Publishing Company, January 2002.

In one or more embodiments, a chemiluminescence tag can optionally be used to label a component of the biomarker/capture complex to enable the detection of a biomarker level. Suitable chemiluminescent materials include any of oxalyl chloride, Rodamin 6G,

Ru(bipy)₃ ²⁺ , TMAE (tetrakis(dimethylamino)ethylene), Pyrogallol (1,2,3-trihydroxibenzene), Lucigenin, peroxyoxalates, Aryl oxalates, Acridinium esters, dioxetanes, and others.

In some embodiments, the detection method includes an enzyme/substrate

combination that generates a detectable signal that corresponds to the biomarker level.

Generally, the enzyme catalyzes a chemical alteration of the chromogenic substrate which can be measured using various techniques, including spectrophotometry, fluorescence, and chemiluminescence. Suitable enzymes include, for example, luciferases, luciferin, malate dehydrogenase, urease, horseradish peroxidase (HRPO), alkaline phosphatase, beta- galactosidase, glucoamylase, lysozyme, glucose oxidase, galactose oxidase, and glucose-6- phosphate dehydrogenase, uricase, xanthine oxidase, lactoperoxidase, microperoxidase, and the like.

In some embodiments, the detection method can be a combination of fluorescence, chemiluminescence, radionuclide or enzyme/substrate combinations that generate a measurable signal. In some embodiments, multimodal signaling could have unique and advantageous characteristics in biomarker assay formats.

In some embodiments, the biomarker presence and/or levels for the biomarkers described herein can be detected using any analytical methods including, singleplex aptamer assays, multiplexed aptamer assays, singleplex or multiplexed immunoassays, mRNA expression profiling, miRNA expression profiling, mass spectrometric analysis,

histological/cyto logical methods, etc. as discussed below. Determination of Biomarker Levels using Aptamer-Based Assays

Assays directed to the detection and quantification of physiologically significant molecules in biological samples and other samples are important tools in scientific research and in the health care field. One class of such assays involves the use of a microarray that includes one or more aptamers immobilized on a solid support. The aptamers are each capable of binding to a target molecule in a highly specific manner and with very high affinity. See, e.g., U.S. Patent No. 5,475,096 entitled "Nucleic Acid Ligands"; see also, e.g., U.S. Patent No. 6,242,246, U.S. Patent No. 6,458,543, and U.S. Patent No. 6,503,715, each of which is entitled "Nucleic Acid Ligand Diagnostic Biochip". Once the microarray is contacted with a sample, the aptamers bind to their respective target molecules present in the sample and thereby enable a determination of a biomarker level corresponding to a biomarker.

As used herein, an "aptamer" refers to a nucleic acid that has a specific binding affinity for a target molecule. It is recognized that affinity interactions are a matter of degree; however, in this context, the "specific binding affinity" of an aptamer for its target means that the aptamer binds to its target generally with a much higher degree of affinity than it binds to other components in a test sample. An "aptamer" is a set of copies of one type or species of nucleic acid molecule that has a particular nucleotide sequence. An aptamer can include any suitable number of nucleotides, including any number of chemically modified nucleotides. "Aptamers" refers to more than one such set of molecules. Different aptamers can have either the same or different numbers of nucleotides. Aptamers can be DNA or RNA or chemically modified nucleic acids and can be single stranded, double stranded, or contain double stranded regions, and can include higher ordered structures. An aptamer can also be a photoaptamer, where a photoreactive or chemically reactive functional group is included in the aptamer to allow it to be covalently linked to its corresponding target. Any of the aptamer methods disclosed herein can include the use of two or more aptamers that specifically bind the same target molecule. As further described below, an aptamer may include a tag. If an aptamer includes a tag, all copies of the aptamer need not have the same tag. Moreover, if different aptamers each include a tag, these different aptamers can have either the same tag or a different tag.

An aptamer can be identified using any known method, including the SELEX process. Once identified, an aptamer can be prepared or synthesized in accordance with any known method, including chemical synthetic methods and enzymatic synthetic methods. The terms "SELEX" and "SELEX process" are used interchangeably herein to refer generally to a combination of (1) the selection of aptamers that interact with a target molecule in a desirable manner, for example binding with high affinity to a protein, with (2) the amplification of those selected nucleic acids. The SELEX process can be used to identify aptamers with high affinity to a specific target or biomarker.

SELEX generally includes preparing a candidate mixture of nucleic acids, binding of the candidate mixture to the desired target molecule to form an affinity complex, separating the affinity complexes from the unbound candidate nucleic acids, separating and isolating the nucleic acid from the affinity complex, purifying the nucleic acid, and identifying a specific aptamer sequence. The process may include multiple rounds to further refine the affinity of the selected aptamer. The process can include amplification steps at one or more points in the process. See, e.g., U.S. Patent No. 5,475,096, entitled "Nucleic Acid Ligands". The SELEX process can be used to generate an aptamer that covalently binds its target as well as an aptamer that non-covalently binds its target. See, e.g., U.S. Patent No. 5,705,337 entitled "Systematic Evolution of Nucleic Acid Ligands by Exponential Enrichment: Chemi- SELEX."

The SELEX process can be used to identify high-affinity aptamers containing modified nucleotides that confer improved characteristics on the aptamer, such as, for example, improved in vivo stability or improved delivery characteristics. Examples of such modifications include chemical substitutions at the ribose and/or phosphate and/or base positions. SELEX process-identified aptamers containing modified nucleotides are described in U.S. Patent No. 5,660,985, entitled "High Affinity Nucleic Acid Ligands Containing Modified Nucleotides", which describes oligonucleotides containing nucleotide derivatives chemically modified at the 5'- and 2'-positions of pyrimidines. U.S. Patent No. 5,580,737, see supra, describes highly specific aptamers containing one or more nucleotides modified with 2^*-amino (2^*-NH2), 2^*-fluoro (2^*-F), and/or 2^*-0-methyl (2^*-OMe). See also, U.S. Patent Application Publication No. 2009/0098549, entitled "SELEX and PHOTOSELEX", which describes nucleic acid libraries having expanded physical and chemical properties and their use in SELEX and photoSELEX.

SELEX can also be used to identify aptamers that have desirable off-rate

characteristics. See U.S. Publication No. US 2009/0004667, entitled "Method for Generating Aptamers with Improved Off-Rates", which describes improved SELEX methods for generating aptamers that can bind to target molecules. Methods for producing aptamers and photoaptamers having slower rates of dissociation from their respective target molecules are described. The methods involve contacting the candidate mixture with the target molecule, allowing the formation of nucleic acid-target complexes to occur, and performing a slow off- rate enrichment process wherein nucleic acid-target complexes with fast dissociation rates will dissociate and not reform, while complexes with slow dissociation rates will remain intact. Additionally, the methods include the use of modified nucleotides in the production of candidate nucleic acid mixtures to generate aptamers with improved off-rate performance. In some embodiments, an aptamer comprises at least one nucleotide with a modification, such as a base modification. In some embodiments, an aptamer comprises at least one nucleotide with a hydrophobic modification, such as a hydrophobic base modification, allowing for hydrophobic contacts with a target protein. Such hydrophobic contacts, in some

embodiments, contribute to greater affinity and/or slower off-rate binding by the aptamer. In some embodiments, an aptamer comprises at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, or at least 10 nucleotides with hydrophobic modifications, where each hydrophobic modification may be the same or different from the others. In some embodiments, an aptamer comprises at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, or at least 10 hydrophobic modifications. In some embodiments, a slow off-rate aptamer (including an aptamers comprising at least one nucleotide with a hydrophobic modification) has an off-rate (t½) of > 30 minutes, > 60 minutes, > 90 minutes, > 120 minutes, > 150 minutes, > 180 minutes, > 210 minutes, or > 240 minutes. In some embodiments, an assay employs aptamers that include photoreactive functional groups that enable the aptamers to covalently bind or "photocrosslink" their target molecules. See, e.g., U.S. Patent No.

6,544,776 entitled "Nucleic Acid Ligand Diagnostic Biochip". These photoreactive aptamers are also referred to as photoaptamers. See, e.g., U.S. Patent No. 5,763,177, U.S. Patent No. 6,001,577, and U.S. Patent No. 6,291,184, each of which is entitled "Systematic Evolution of Nucleic Acid Ligands by Exponential Enrichment: Photoselection of Nucleic Acid Ligands and Solution SELEX"; see also, e.g., U.S. Patent No. 6,458,539, entitled "Photoselection of Nucleic Acid Ligands". After the microarray is contacted with the sample and the photoaptamers have had an opportunity to bind to their target molecules, the photoaptamers are photoactivated, and the solid support is washed to remove any non- specifically bound molecules. Harsh wash conditions may be used, since target molecules that are bound to the photoaptamers are generally not removed, due to the covalent bonds created by the photoactivated functional group(s) on the photoaptamers. In this manner, the assay enables the detection of a biomarker level corresponding to a biomarker in the test sample. In some assay formats, the aptamers are immobilized on the solid support prior to being contacted with the sample. Under certain circumstances, however, immobilization of the aptamers prior to contact with the sample may not provide an optimal assay. For example, pre-immobilization of the aptamers may result in inefficient mixing of the aptamers with the target molecules on the surface of the solid support, perhaps leading to lengthy reaction times and, therefore, extended incubation periods to permit efficient binding of the aptamers to their target molecules. Further, when photoaptamers are employed in the assay and depending upon the material utilized as a solid support, the solid support may tend to scatter or absorb the light used to effect the formation of covalent bonds between the photoaptamers and their target molecules. Moreover, depending upon the method employed, detection of target molecules bound to their aptamers can be subject to imprecision, since the surface of the solid support may also be exposed to and affected by any labeling agents that are used. Finally, immobilization of the aptamers on the solid support generally involves an aptamer- preparation step (i.e., the immobilization) prior to exposure of the aptamers to the sample, and this preparation step may affect the activity or functionality of the aptamers.

Aptamer assays that permit an aptamer to capture its target in solution and then employ separation steps that are designed to remove specific components of the aptamer- target mixture prior to detection have also been described (see U.S. Publication No.

2009/0042206, entitled "Multiplexed Analyses of Test Samples"). The described aptamer assay methods enable the detection and quantification of a non-nucleic acid target (e.g., a protein target) in a test sample by detecting and quantifying a nucleic acid (i.e., an aptamer). The described methods create a nucleic acid surrogate (i.e, the aptamer) for detecting and quantifying a non-nucleic acid target, thus allowing the wide variety of nucleic acid technologies, including amplification, to be applied to a broader range of desired targets, including protein targets.

Aptamers can be constructed to facilitate the separation of the assay components from an aptamer biomarker complex (or photoaptamer biomarker covalent complex) and permit isolation of the aptamer for detection and/or quantification. In one embodiment, these constructs can include a cleavable or releasable element within the aptamer sequence. In other embodiments, additional functionality can be introduced into the aptamer, for example, a labeled or detectable component, a spacer component, or a specific binding tag or immobilization element. For example, the aptamer can include a tag connected to the aptamer via a cleavable moiety, a label, a spacer component separating the label, and the cleavable moiety. In one embodiment, a cleavable element is a photocleavable linker. The photocleavable linker can be attached to a biotin moiety and a spacer section, can include an NHS group for derivatization of amines, and can be used to introduce a biotin group to an aptamer, thereby allowing for the release of the aptamer later in an assay method.

Homogenous assays, done with all assay components in solution, do not require separation of sample and reagents prior to the detection of signal. These methods are rapid and easy to use. These methods generate signal based on a molecular capture or binding reagent that reacts with its specific target. In some embodiments of the methods described herein, the molecular capture reagents comprise an aptamer or an antibody or the like and the specific target may be a TB biomarkers identified in experiments conducted during development of embodiments of the present invention (e.g., MP64, ACR, CH602, PstSl, DnaK, MASZ, CH10, RL7, TPX, CF30, KAD, MPT51, EsxB, EsxA, A85A, A85B, and A95C).

In some embodiments, a method for signal generation takes advantage of anisotropy signal change due to the interaction of a fiuorophore-labeled capture reagent with its specific biomarker target. When the labeled capture reacts with its target, the increased molecular weight causes the rotational motion of the fiuorophore attached to the complex to become much slower changing the anisotropy value. By monitoring the anisotropy change, binding events may be used to quantitatively measure the biomarkers in solutions. Other methods include fluorescence polarization assays, molecular beacon methods, time resolved fluorescence quenching, chemiluminescence, fluorescence resonance energy transfer, and the like.

An exemplary solution-based aptamer assay that can be used to detect a biomarker level in a biological sample includes the following: (a) preparing a mixture by contacting the biological sample with an aptamer that includes a first tag and has a specific affinity for the biomarker, wherein an aptamer affinity complex is formed when the biomarker is present in the sample; (b) exposing the mixture to a first solid support including a first capture element, and allowing the first tag to associate with the first capture element; (c) removing any components of the mixture not associated with the first solid support; (d) attaching a second tag to the biomarker component of the aptamer affinity complex; (e) releasing the aptamer affinity complex from the first solid support; (f) exposing the released aptamer affinity complex to a second solid support that includes a second capture element and allowing the second tag to associate with the second capture element; (g) removing any non-complexed aptamer from the mixture by partitioning the non-complexed aptamer from the aptamer affinity complex; (h) eluting the aptamer from the solid support; and (i) detecting the biomarker by detecting the aptamer component of the aptamer affinity complex.

A nonlimiting exemplary method of detecting biomarkers in a biological sample using aptamers is described, for example, in Kraemer et al, PLoS One 6(10): e26332 (2011); herein incorporated by reference in its entirety.

Determination of Biomarker Levels using Immunoassays

Immunoassay methods are based on the reaction of an antibody to its corresponding target or analyte and can detect the analyte in a sample depending on the specific assay format. To improve specificity and sensitivity of an assay method based on immuno- reactivity, monoclonal antibodies and fragments thereof are often used because of their specific epitope recognition. Polyclonal antibodies have also been successfully used in various immunoassays because of their increased affinity for the target as compared to monoclonal antibodies. Immunoassays have been designed for use with a wide range of biological sample matrices. Immunoassay formats have been designed to provide qualitative, semi-quantitative, and quantitative results.

Quantitative results are generated through the use of a standard curve created with known concentrations of the specific analyte to be detected. The response or signal from an unknown sample is plotted onto the standard curve, and a quantity or level corresponding to the target in the unknown sample is established.

Numerous immunoassay formats have been designed. ELISA or EIA can be quantitative for the detection of an analyte. This method relies on attachment of a label to either the analyte or the antibody and the label component includes, either directly or indirectly, an enzyme. ELISA tests may be formatted for direct, indirect, competitive, or sandwich detection of the analyte. Other methods rely on labels such as, for example, radioisotopes (I¹²⁵) or fluorescence. Additional techniques include, for example,

agglutination, nephelometry, turbidimetry, Western blot, immunoprecipitation,

immunocytochemistry, immunohistochemistry, flow cytometry, Luminex assay, and others (see ImmunoAssay: A Practical Guide, edited by Brian Law, published by Taylor & Francis, Ltd., 2005 edition).

Exemplary assay formats include enzyme-linked immunosorbent assay (ELISA), radioimmunoassay, fluorescent, chemiluminescence, and fluorescence resonance energy transfer (FRET) or time resolved-FRET (TR-FRET) immunoassays. Examples of procedures for detecting biomarkers include biomarker immunoprecipitation followed by quantitative methods that allow size and peptide level discrimination, such as gel electrophoresis, capillary electrophoresis, planar electrochromatography, and the like.

Methods of detecting and/or for quantifying a detectable label or signal generating material depend on the nature of the label. The products of reactions catalyzed by

appropriate enzymes (where the detectable label is an enzyme; see above) can be, without limitation, fluorescent, luminescent, or radioactive or they may absorb visible or ultraviolet light. Examples of detectors suitable for detecting such detectable labels include, without limitation, x-ray film, radioactivity counters, scintillation counters, spectrophotometers, colorimeters, fluorometers, luminometers, and densitometers.

Any of the methods for detection can be performed in any format that allows for any suitable preparation, processing, and analysis of the reactions. This can be, for example, in multi-well assay plates (e.g., 96 wells or 386 wells) or using any suitable array or microarray. Stock solutions for various agents can be made manually or robotically, and all subsequent pipetting, diluting, mixing, distribution, washing, incubating, sample readout, data collection and analysis can be done robotically using commercially available analysis software, robotics, and detection instrumentation capable of detecting a detectable label.

Determination of Biomarker Levels using Gene Expression Profiling

Measuring mRNA in a biological sample may, in some embodiments, be used as a surrogate for detection of the level of the corresponding protein in the biological sample. Thus, in some embodiments, a biomarker or biomarker panel described herein can be detected by detecting the appropriate RNA.

In some embodiments, mRNA expression levels are measured by reverse transcription quantitative polymerase chain reaction (RT-PCR followed with qPCR). RT-PCR is used to create a cDNA from the mRNA. The cDNA may be used in a qPCR assay to produce fluorescence as the DNA amplification process progresses. By comparison to a standard curve, qPCR can produce an absolute measurement such as number of copies of mRNA per cell. Northern blots, microarrays, Invader assays, and RT-PCR combined with capillary electrophoresis have all been used to measure expression levels of mRNA in a sample. See Gene Expression Profiling: Methods and Protocols, Richard A. Shimkets, editor, Humana Press, 2004.

Detection of Biomarkers Using In Vivo Molecular Imaging Technologies In some embodiments, a biomarker described herein may be used in molecular imaging tests. For example, an imaging agent can be coupled to a capture reagent, which can be used to detect the biomarker in vivo.

In vivo imaging technologies provide non-invasive methods for determining the state of a particular disease in the body of an individual. For example, entire portions of the body, or even the entire body, may be viewed as a three dimensional image, thereby providing valuable information concerning morphology and structures in the body. Such technologies may be combined with the detection of the biomarkers described herein to provide information concerning the biomarker in vivo.

The use of in vivo molecular imaging technologies is expanding due to various advances in technology. These advances include the development of new contrast agents or labels, such as radiolabels and/or fluorescent labels, which can provide strong signals within the body; and the development of powerful new imaging technology, which can detect and analyze these signals from outside the body, with sufficient sensitivity and accuracy to provide useful information. The contrast agent can be visualized in an appropriate imaging system, thereby providing an image of the portion or portions of the body in which the contrast agent is located. The contrast agent may be bound to or associated with a capture reagent, such as an aptamer or an antibody, for example, and/or with a peptide or protein, or an oligonucleotide (for example, for the detection of gene expression), or a complex containing any of these with one or more macromolecules and/or other particulate forms.

The contrast agent may also feature a radioactive atom that is useful in imaging. Suitable radioactive atoms include technetium-99m or iodine- 123 for scintigraphic studies. Other readily detectable moieties include, for example, spin labels for magnetic resonance imaging (MRI) such as, for example, iodine-123, iodine-131, indium-111, fiuorine-19, carbon-13, nitrogen-15, oxygen- 17, gadolinium, manganese or iron. Such labels are well known in the art and could easily be selected by one of ordinary skill in the art.

Standard imaging techniques include but are not limited to magnetic resonance imaging, computed tomography scanning, positron emission tomography (PET), single photon emission computed tomography (SPECT), and the like. For diagnostic in vivo imaging, the type of detection instrument available is a major factor in selecting a given contrast agent, such as a given radionuclide and the particular biomarker that it is used to target (protein, mRNA, and the like). The radionuclide chosen typically has a type of decay that is detectable by a given type of instrument. Also, when selecting a radionuclide for in vivo diagnosis, its half-life should be long enough to enable detection at the time of maximum uptake by the target tissue but short enough that deleterious radiation of the host is minimized.

Exemplary imaging techniques include but are not limited to PET and SPECT, which are imaging techniques in which a radionuclide is synthetically or locally administered to an individual. The subsequent uptake of the radiotracer is measured over time and used to obtain information about the targeted tissue and the biomarker. Because of the high-energy (gamma-ray) emissions of the specific isotopes employed and the sensitivity and

sophistication of the instruments used to detect them, the two-dimensional distribution of radioactivity may be inferred from outside of the body.

Commonly used positron-emitting nuclides in PET include, for example, carbon- 11, nitrogen-13, oxygen-15, and fluorine-18. Isotopes that decay by electron capture and/or gamma-emission are used in SPECT and include, for example iodine- 123 and technetium- 99m. An exemplary method for labeling amino acids with technetium-99m is the reduction of pertechnetate ion in the presence of a chelating precursor to form the labile technetium- 99m-precursor complex, which, in turn, reacts with the metal binding group of a

bifunctionally modified chemotactic peptide to form a technetium-99m-chemotactic peptide conjugate.

Antibodies are frequently used for such in vivo imaging diagnostic methods. The preparation and use of antibodies for in vivo diagnosis is well known in the art. Similarly, aptamers may be used for such in vivo imaging diagnostic methods. For example, an aptamer that was used to identify a particular biomarker described herein may be appropriately labeled and injected into an individual to detect the biomarker in vivo. The label used will be selected in accordance with the imaging modality to be used, as previously described. Aptamer-directed imaging agents could have unique and advantageous characteristics relating to tissue penetration, tissue distribution, kinetics, elimination, potency, and selectivity as compared to other imaging agents.

Such techniques may also optionally be performed with labeled oligonucleotides, for example, for detection of gene expression through imaging with antisense oligonucleotides. These methods are used for in situ hybridization, for example, with fluorescent molecules or radionuclides as the label. Other methods for detection of gene expression include, for example, detection of the activity of a reporter gene.

Another general type of imaging technology is optical imaging, in which fluorescent signals within the subject are detected by an optical device that is external to the subject. These signals may be due to actual fluorescence and/or to bioluminescence. Improvements in the sensitivity of optical detection devices have increased the usefulness of optical imaging for in vivo diagnostic assays.

For a review of other techniques, see N. Blow, Nature Methods, 6, 465-469, 2009.; herein incorporated by reference in its entirety.

Determination of Biomarkers using Histology/Cytology Methods

In some embodiments, the biomarkers described herein may be detected in a variety of tissue samples using histological or cytological methods. For example, endo- and trans- bronchial biopsies, fine needle aspirates, cutting needles, and core biopsies can be used for histology. Bronchial washing and brushing, pleural aspiration, and sputum, can be used for cyotology. Any of the biomarkers identified herein can be used to stain a specimen as an indication of disease.

In some embodiments, one or more capture reagent/s specific to the corresponding biomarker/s are used in a cytological evaluation of a sample and may include one or more of the following: collecting a cell sample, fixing the cell sample, dehydrating, clearing, immobilizing the cell sample on a microscope slide, permeabilizing the cell sample, treating for analyte retrieval, staining, destaining, washing, blocking, and reacting with one or more capture reagent/s in a buffered solution. In another embodiment, the cell sample is produced from a cell block.

In some embodiments, one or more capture reagent/s specific to the corresponding biomarkers are used in a histological evaluation of a tissue sample and may include one or more of the following: collecting a tissue specimen, fixing the tissue sample, dehydrating, clearing, immobilizing the tissue sample on a microscope slide, permeabilizing the tissue sample, treating for analyte retrieval, staining, destaining, washing, blocking, rehydrating, and reacting with capture reagent/s in a buffered solution. In another embodiment, fixing and dehydrating are replaced with freezing.

In another embodiment, the one or more aptamer/s specific to the corresponding biomarker/s are reacted with the histological or cytological sample and can serve as the nucleic acid target in a nucleic acid amplification method. Suitable nucleic acid amplification methods include, for example, PCR, q-beta replicase, rolling circle amplification, strand displacement, helicase dependent amplification, loop mediated isothermal amplification, ligase chain reaction, and restriction and circularization aided rolling circle amplification.

In one embodiment, the one or more capture reagent/s specific to the corresponding biomarkers for use in the histological or cytological evaluation are mixed in a buffered solution that can include any of the following: blocking materials, competitors, detergents, stabilizers, carrier nucleic acid, polyanionic materials, etc.

A "cytology protocol" generally includes sample collection, sample fixation, sample immobilization, and staining. "Cell preparation" can include several processing steps after sample collection, including the use of one or more aptamers for the staining of the prepared cells.

Determination of Biomarker Levels using Mass Spectrometry Methods

A variety of configurations of mass spectrometers can be used to detect biomarker levels. Several types of mass spectrometers are available or can be produced with various configurations. In general, a mass spectrometer has the following major components: a sample inlet, an ion source, a mass analyzer, a detector, a vacuum system, and instrument- control system, and a data system. Difference in the sample inlet, ion source, and mass analyzer generally define the type of instrument and its capabilities. For example, an inlet can be a capillary-column liquid chromatography source or can be a direct probe or stage such as used in matrix-assisted laser desorption. Common ion sources are, for example, electrospray, including nanospray and microspray or matrix-assisted laser desorption.

Common mass analyzers include a quadrupole mass filter, ion trap mass analyzer and time- of-flight mass analyzer. Additional mass spectrometry methods are well known in the art (see Burlingame et al. Anal. Chem. 70:647 R-716R (1998); Kinter and Sherman, New York (2000)).

Protein biomarkers and biomarker levels can be detected and measured by any of the following: electrospray ionization mass spectrometry (ESI-MS), ESI-MS/MS, ESI- MS/(MS)n, matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS), surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS), desorption/ionization on silicon (DIOS), secondary ion mass spectrometry (SIMS), quadrupole time-of-flight (Q-TOF), tandem time-of-flight (TOF/TOF) technology, called ultraflex III TOF/TOF, atmospheric pressure chemical ionization mass spectrometry (APCI-MS), APCI-MS/MS, APCI-(MS)^N, atmospheric pressure photoionization mass spectrometry (APPI-MS), APPI-MS/MS, and APPI-(MS)^N, quadrupole mass spectrometry, Fourier transform mass spectrometry (FTMS), quantitative mass spectrometry, and ion trap mass spectrometry.

Sample preparation strategies are used to label and enrich samples before mass spectroscopic characterization of protein biomarkers and determination biomarker levels. Labeling methods include but are not limited to isobaric tag for relative and absolute quantitation

(iTPvAQ) and stable isotope labeling with amino acids in cell culture (SILAC). Capture reagents used to selectively enrich samples for candidate biomarker proteins prior to mass spectroscopic analysis include but are not limited to aptamers, antibodies, nucleic acid probes, chimeras, small molecules, an F(ab')₂ fragment, a single chain antibody fragment, an Fv fragment, a single chain Fv fragment, a nucleic acid, a lectin, a ligand-binding receptor, affybodies, nanobodies, ankyrins, domain antibodies, alternative antibody scaffolds (e.g. diabodies etc) imprinted polymers, avimers, peptidomimetics, peptoids, peptide nucleic acids, threose nucleic acid, a hormone receptor, a cytokine receptor, and synthetic receptors, and modifications and fragments of these.

The foregoing assays enable the detection of biomarker levels that are useful in the methods described herein, where the methods comprise detecting, in a biological sample from an individual, at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, or at least nine biomarkers selected from the TB biomarkers identified in experiments conducted during development of embodiments of the present invention (e.g., MP64, ACR, CH602, PstSl, DnaK, MASZ, CHIO, RL7, TPX, CF30, KAD, MPT51, EsxB, EsxA, A85A, A85B, and A95C).

Classification of Biomarkers and Calculation of Disease Scores

In some embodiments, a biomarker "signature" for a given diagnostic test contains a set of markers, each marker having characteristic levels in the populations of interest.

Characteristic levels, in some embodiments, may refer to the mean or average of the biomarker levels for the individuals in a particular group. In some embodiments, a diagnostic method described herein can be used to assign an unknown sample from an individual into one of two groups, either TB positive or TB negative. The assignment of a sample into one of two or more groups is known as classification, and the procedure used to accomplish this assignment is known as a classifier or a classification method. Classification methods may also be referred to as scoring methods. There are many classification methods that can be used to construct a diagnostic classifier from a set of biomarker levels. In some instances, classification methods are performed using supervised learning techniques in which a data set is collected using samples obtained from individuals within two (or more, for multiple classification states) distinct groups one wishes to distinguish. Since the class (group or population) to which each sample belongs is known in advance for each sample, the classification method can be trained to give the desired classification response. It is also possible to use unsupervised learning techniques to produce a diagnostic classifier.

Common approaches for developing diagnostic classifiers include decision trees; bagging + boosting + forests; rule inference based learning; Parzen Windows; linear models; logistic; neural network methods; unsupervised clustering; K-means; hierarchical ascending/ descending; semi-supervised learning; prototype methods; nearest neighbor; kernel density estimation; support vector machines; hidden Markov models; Boltzmann Learning; and classifiers may be combined either simply or in ways which minimize particular objective functions. For a review, see, e.g., Pattern Classification, R.O. Duda, et al, editors, John Wiley & Sons, 2nd edition, 2001; see also, The Elements of Statistical Learning - Data Mining, Inference, and Prediction, T. Hastie, et al, editors, Springer Science+Business Media, LLC, 2nd edition, 2009.

To produce a classifier using supervised learning techniques, a set of samples called training data are obtained. In the context of diagnostic tests, training data includes samples from the distinct groups (classes) to which unknown samples will later be assigned. For example, samples collected from individuals in a control population and individuals in a particular disease population can constitute training data to develop a classifier that can classify unknown samples (or, more particularly, the individuals from whom the samples were obtained) as either having the disease or being free from the disease. The development of the classifier from the training data is known as training the classifier. Specific details on classifier training depend on the nature of the supervised learning technique. Training a naive Bayesian classifier is an example of such a supervised learning technique (see, e.g., Pattern Classification, R.O. Duda, et al, editors, John Wiley & Sons, 2nd edition, 2001; see also, The Elements of Statistical Learning - Data Mining, Inference, and Prediction, T.

Hastie, et al, editors, Springer Science+Business Media, LLC, 2nd edition, 2009). Training of a naive Bayesian classifier is described, e.g., in U.S. Publication Nos: 2012/0101002 and 2012/0077695.

Since typically there are many more potential biomarker levels than samples in a training set, care must be used to avoid over-fitting. Over-fitting occurs when a statistical model describes random error or noise instead of the underlying relationship. Over- fitting can be avoided in a variety of way, including, for example, by limiting the number of markers used in developing the classifier, by assuming that the marker responses are independent of one another, by limiting the complexity of the underlying statistical model employed, and by ensuring that the underlying statistical model conforms to the data. An illustrative example of the development of a diagnostic test using a set of biomarkers includes the application of a naive Bayes classifier, a simple probabilistic classifier based on Bayes theorem with strict independent treatment of the biomarkers. Each biomarker is described by a class-dependent probability density function (pdf) for the measured RFU values or log RFU (relative fluorescence units) values in each class. The joint pdfs for the set of markers in one class is assumed to be the product of the individual class- dependent pdfs for each biomarker. Training a naive Bayes classifier in this context amounts to assigning parameters ("parameterization") to characterize the class dependent pdfs. Any underlying model for the class-dependent pdfs may be used, but the model should generally conform to the data observed in the training set.

The performance of the naive Bayes classifier is dependent upon the number and quality of the biomarkers used to construct and train the classifier. A single biomarker will perform in accordance with its KS-distance (Kolmogorov-Smirnov). The addition of subsequent markers with good KS distances (>0.3, for example) will, in general, improve the classification performance if the subsequently added markers are independent of the first marker. Using the sensitivity plus specificity as a classifier score, many high scoring classifiers can be generated with a variation of a greedy algorithm. (A greedy algorithm is any algorithm that follows the problem solving metaheuristic of making the locally optimal choice at each stage with the hope of finding the global optimum.)

Another way to depict classifier performance is through a receiver operating characteristic (ROC), or simply ROC curve or ROC plot. The ROC is a graphical plot of the sensitivity, or true positive rate, vs. false positive rate (1 - specificity or 1 - true negative rate), for a binary classifier system as its discrimination threshold is varied. The ROC can also be represented equivalently by plotting the fraction of true positives out of the positives (TPR = true positive rate) vs. the fraction of false positives out of the negatives (FPR = false positive rate). Also known as a Relative Operating Characteristic curve, because it is a comparison of two operating characteristics (TPR & FPR) as the criterion changes. The area under the ROC curve (AUC) is commonly used as a summary measure of diagnostic accuracy. It can take values from 0.0 to 1.0. The AUC has an important statistical property: the AUC of a classifier is equivalent to the probability that the classifier will rank a randomly chosen positive instance higher than a randomly chosen negative instance (Fawcett T, 2006. An introduction to ROC analysis. Pattern Recognition Letters .27: 861-874). This is equivalent to the Wilcoxon test of ranks (Hanley, J.A., McNeil, B.J., 1982. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 143, 29- 36.).

Exemplary embodiments use any number of the TB biomarkers identified in experiments conducted during development of embodiments of the present invention (e.g., MP64, ACR, CH602, PstSl, DnaK, MASZ, CH10, RL7, TPX, CF30, KAD, MPT51, EsxB, EsxA, A85A, A85B, and A95C) in various combinations to produce diagnostic tests for identifying individuals with TB. The markers can be combined in many ways to produce classifiers. For example, certain combinations of biomarkers may produce tests that are more sensitive (or more specific) than other combinations.

In some embodiments, once a panel is defined to include a particular set of biomarkers and a classifier is constructed from a set of training data, the diagnostic test parameters are complete. In some embodiments, a biological sample is run in one or more assays to produce the relevant quantitative biomarker levels used for classification. The measured biomarker levels are used as input for the classification method that outputs a classification and an optional score for the sample that reflects the confidence of the class assignment.

In some embodiments, a biological sample is optionally diluted and run in a multiplexed aptamer assay, and data is assessed as follows. First, the data from the assay are optionally normalized and calibrated, and the resulting biomarker levels are used as input to a Bayes classification scheme. Second, the log-likelihood ratio is computed for each measured biomarker individually and then summed to produce a final classification score, which is also referred to as a diagnostic score. The resulting assignment as well as the overall

classification score can be reported. In some embodiments, the individual log-likelihood risk factors computed for each biomarker level can be reported as well.

Kits

Any combination of the biomarkers described herein can be detected using a suitable kit, such as for use in performing the methods disclosed herein. Furthermore, any kit can contain one or more detectable labels as described herein, such as a fluorescent moiety, etc. In some embodiments, a kit includes (a) one or more capture reagents (such as, for example, at least one aptamer or antibody) for detecting one or more biomarkers in a biological sample, and optionally (b) one or more software or computer program products for predicting whether the individual from whom the biological sample was obtained suffers from or is infected with TB. Alternatively, rather than one or more computer program products, one or more instructions for manually performing the above steps by a human can be provided.

In some embodiments, a kit comprises a solid support, a capture reagent, and a signal generating material. The kit can also include instructions for using the devices and reagents, handling the sample, and analyzing the data. Further the kit may be used with a computer system or software to analyze and report the result of the analysis of the biological sample. The kits can also contain one or more reagents (e.g., solubilization buffers, detergents, washes, or buffers) for processing a biological sample. Any of the kits described herein can also include, e.g., buffers, blocking agents, mass spectrometry matrix materials, antibody capture agents, positive control samples, negative control samples, software and information such as protocols, guidance and reference data.

In some embodiments, kits are provided for the analysis of TB, wherein the kits comprise PCR primers for one or more biomarkers described herein. In some embodiments, a kit may further include instructions for use and correlation of the biomarkers with TB diagnosis. In some embodiments, a kit may include a DNA array containing the complement of one or more of the biomarkers described herein, reagents, and/or enzymes for amplifying or isolating sample DNA. The kits may include reagents for real-time PCR, for example, TaqMan probes and/or primers, and enzymes.

For example, a kit can comprise (a) reagents comprising at least one capture reagent for determining the level of one or more biomarkers in a test sample, and optionally (b) one or more algorithms or computer programs for performing the steps of comparing the amount of each biomarker quantified in the test sample to one or more predetermined cutoffs. In some embodiments, an algorithm or computer program assigns a score for each biomarker quantified based on said comparison and, in some embodiments, combines the assigned scores for each biomarker quantified to obtain a total score. Further, in some embodiments, an algorithm or computer program compares the total score with a predetermined score, and uses the comparison to determine whether a subject is infected with TB. Alternatively, rather than one or more algorithms or computer programs, one or more instructions for manually performing the above steps by a human can be provided.

Computer Methods and Software

Once a biomarker or biomarker panel is selected, a method for assessing TB in an individual may comprise the following: 1) collect or otherwise obtain a biological sample; 2) perform an analytical method to detect and measure the biomarker or biomarkers in the panel in the biological sample; and 3) report the results of the biomarker levels. In some embodiments, the results of the biomarker levels are reported qualitatively rather than quantitatively, such as, for example, a proposed diagnosis (e.g., "TB infection", "X% risk of TB infection," etc.) or simply a positive TB / negative TB result. In some embodiments, a method for assessing TB in an individual may comprise the following: 1) collect or otherwise obtain a biological sample; 2) perform an analytical method to detect and measure the biomarker or biomarkers in the panel in the biological sample; 3) perform any data normalization or standardization; 4) calculate each biomarker level; and 5) report the results of the biomarker levels. In some embodiments, the biomarker levels are combined in some way and a single value for the combined biomarker levels is reported. In this approach, in some embodiments, the reported value may be a single number determined from the sum of all the marker calculations that is compared to a pre - set threshold value that is an indication of the presence or absence of disease. Or the diagnostic score may be a series of bars that each represent a biomarker value and the pattern of the responses may be compared to a pre- set pattern for determination of the presence or absence of disease.

Methods of Treatment

In some embodiments, following a determination that a subject is infected with or suffers from TB, the subject is treated for TB infection. In some embodiments, medications used to treat latent TB infection include: isoniazid (INH), rifampin (RIF), and rifapentine (RPT). In some embodiments, TB disease is treated by taking several drugs for 6 to 9 months. There are 10 drugs currently approved by the U.S. Food and Drug Administration (FDA) for treating TB. Of the approved drugs, the first- line anti-TB agents that form the core of treatment regimens include: isoniazid (INH), rifampin (RIF), ethambutol (EMB), and pyrazinamide (PZA). Regimens for treating TB disease have an initial phase of 2 months, followed by a choice of several options for the continuation phase of either 4 or 7 months (total of 6 to 9 months for treatment).

EXAMPLES

Example 1

Optimization of TB microbial panel

A set of 17 M. tuberculosis (Mtb) proteins have been over-expressed in E. coli and purified in recombinant, tagged form (Table 1, Figure 1). These proteins include

extracellular, cell-surface associated, and intracellular factors present in TB patients and detectable with a sensitive and specific assay. Mtb genes encoding antigen-85 (FpvA, FpvB, FpvC), ESAT-6, CFP10, and PstSl were cloned into the pET-51b vector that features an amino-terminal Strep-tag and a carboxy-terminal His-tag. Additional plasmids for over- expression of His-tagged MPT64, Acr, GroEL2, OnaK, GlcB, GroES, RpIL, Tpx, Cfp30, Adk, and MPT51 were from BEI Resources.

SELEX was performed on the Mtb proteins, using multiple ssDNA libraries containing different modified nucleotides (Figure 2). For each selection, the starting library contained of 1 nmol (10¹⁴-10 ¹⁵ molecules) of sequences with a 40mer random region flanked by 20mer fixed regions for PCR amplification between the rounds of SELEX (Gold, 2010; herein incorporated by reference in its entirety). After 6-11 rounds, 48 individual clones from each active pool were sequenced and tested in ³²P-radiolabel affinity binding assays. The best candidates were produced synthetically by solid support phosphoramidite chemistry as 50mer truncated versions with a 5'PBOC (photocleavable biotin D-spacer-cy3). Evaluation of these binding reagents in functional assays such as pull-downs of cognate Mtb protein, binding assays and hybridization to complementary nucleic acid probe arrays resulted in a final set of 31 unique SOMAmers for 16 different Mtb protein targets (Table 2, Figure 3). These TB SOMAmers were prepared at 1 μιτιοΐ scale, HPLC -purified, and combined with the existing SOMAmers for the 1129 human proteins in the SOMAscan assay, using Agilent

hybridization slides containing the antisense probes.

For the validation of the Mtb-specific SOMAmers as binding agents, not only were the recombinant Mtb proteins used, but also fractions from a human macrophage (THP-1) infection model with M. tuberculosis H37Rv and M. bovis BCG, including macrophage lysates, exosomes, and media supernatants at 6 h, 24 h, and 72 h (Giri, 2010; herein incorporated by reference in its entirety). Testing these fractions on SOMAscan produced robust signals for several of the Mtb SOMAmers that distinguished the Mtb-infected from uninfected macrophages (Figure 4). CFP10 (EsxB) was the strongest marker and also distinguished H37Rv from BCG. The esxB gene is located in the RD1 region of the chromosome that is deleted in the BCG vaccine strain (Harboe, 1996; Teutschbein, 2007; herein incorporated by reference in their entireties). EsxB levels increased over time in lysates and media supernatants from Mtb H37Rv-infected macrophages, but EsxB was not detected in exosome preparations. RL7 (ribosomal protein RpIL) was detected in exosomes, lysates and supernatants from t¾-infected macrophages, and the RL7 levels increased over time. Two other Mtb proteins, CH10 (GroES) and CH602 (GroEL), were also detected in preparations from t¾-infected macrophages. The antigen-85 proteins, also known as fibronectin-binding proteins FnbA, FnbB, and FnbC, were not detected by the corresponding SOMAmers. Among the strongest macrophage-derived markers was fibronectin, which was present at lower levels in exosomes and in supernatant from t¾-infected macrophages compared to uninfected macrophages. The data are consistent with sequestration of antigen- 85 and fibronectin upon complex formation between these bacterial and host proteins

(Kumar, 2013; herein incorporated by reference in its entirety ). The Mtb SOMAmers proved useful for the detection of Mtb proteins in various sample matrices, including plasma and urine from some TB patients, but showed high background in serum when added to the SOMAmer mix used for detection of low-abundance proteins in 40% serum.

Example 2

TB biomarker discovery

Pilot studies for TB biomarker discovery were performed with randomly chosen matched urine samples for 20 TB positive subject and 20 non-T8 subjects. SomaScan used 20% urine. A volcano plot is shown in Figure 5. Analysis of the study with 40 urine samples indicated that the t¾-SOMAmers produced clearly elevated signals in some of the TB samples, in particular in samples from HIV-positive patients. Examples that highlight elevated measurements of several Mtb proteins in urine include two patients in the TB/HIV co-infection group and one in the TB/ HIV negative group (Figure 6). Combined

measurements of 14 of the 16 Mtb proteins in urine (except DnaK and Tpx, which did not produce signals above background) were used to estimate performance of such a test in this study. The numbers of Mtb proteins measured at levels above a cut-off (median of all non-TB samples plus multiple standard deviations) in the 40 samples (10 per group) are shown in Figure 7. Defining the test outcome as positive if at least one of the 14 Mtb proteins is above a certain cut-off showed up to 85% sensitivity / 95% specificity in the study (Table 3).

Table 3

Example 3

Mtb protein detection in urine

Experiments conducted during development of embodiments of the present invention demonstrated urine to be a very clean matrix for SOMAscan assay, resulting in extremely low background and promising results with respect to Mtb protein detection. Most Mtb proteins are small (e.g., <40 kDa) and have therefore an increased likelihood to pass through the kidneys and to end up in urine. Correlation between protein size and the frequency with which the Mtb proteins were detectable in urine of TB patients was observed (Figure 8). Several similarly small Mtb proteins have been identified and characterized previously (Kashino. 2008; Napolitano, 2008; Pollock, 2013; herein incorporated by reference in their entireties). Spike and recovery assays comparing 10% urine, 40% serum, and 40%> plasma, shown for EsxB SOMAmers as an example (Figure 9) indicate that urine is a favorable matrix for detection of Mtb proteins.

Normalization and calibration of the SOMAscan urine measurements was done using the standard hybridization and median normalization procedures, with measurement of creatinine levels and total protein in urine as basis for alternate means of normalization.

Small urine samples (50 μΙ_, of 20%> urine) have been tested, which likely contained very low amounts of the targets. It is contemplated that concentrating urine will, in some embodiments, increase assay sensitivity. Such a step will not only concentrate the proteins in urine (e.g., at least 10-fold), but will also eliminate small molecules such as urea that could have

detrimental effects on protein and for SOMAmer during the assay.

Protocols have been established to generate SOMAmer pairs for sandwich-type assays and have isolated such reagent pairs for a panel of cardiovascular risk biomarkers, and the utility of filter-, plate-, or bead-based sandwich assays using combinations of antibodies and SOMAmers or SOMAmers alone has been demonstrated (Ochsner, 2013; Ochsner, 2014; herein incorporated by reference in their entireties). Such assays not only allow the use of larger sample sizes (1 mL or more), but also the concentration of analytes via capture prior to detection with quantitative colorimetric and fluorescent readouts. SOMAmer pairs for the Mtb proteins can be developed. Reagent pairs can be identified among existing SOMAmers or selected via sandwich SELEX using protein-SOMAmer complexes. SOMAmer pairs would be particularly useful to detect Mtb proteins in urine, where the low-abundant antigens can be concentrated from a large sample volume via a capture SOMAmer, but also as reagents generally applicable to many possible platforms for the development of a TB test. The levels of detection in bead- and plate -based assays may be determined, and algorithms for calling a positive or negative result can be developed. Potential loss of sensitivity in a sandwich assay compared to a hybridization assay will be off-set by a larger sample volume and concentration effect in this assay.

Example 4

TB biomarker discovery

Experiments were conducted during development of embodiments of the present invention to identify TB biomarkers with randomly chosen matched plasma and urine samples for 20 TB positive subject and 20 non-T8 subjects. SomaScan used 40%, 1%, and 0.005% plasma (all Mtb-SOMAmers in the 1% mix) and 20% urine. Volcano plots are shown for plasma (Figure 10) and for urine (Figure 11). In plasma, several of the top serum biomarkers from the HR9 model ranked near the top by KS distance (kallistatin, BGH3, afamin, FCG38, and DERM), and markers with the largest median fold change were concordant (SAA, NPS-PLA2, IP 10, CA6). In urine, the top host markers were IL-2 sRa, myokinase, and suPAR. Urine was clearly a less complex matrix compared to either serum or plasma. While signals were generally lower, background was extremely low (typical medians <50 RFU for irrelevant spuriomers).

Example 5

Assay Development

Experiments are conducted during development of embodiments of the present invention on reagent improvement, assay refinement, development of a small-plex TB panel (e.g., combination of host and Mtb biomarkers), optimization of the classifier, and reaching a good sensitivity/high specificity for a rapid test using SOMAmer-based detection of TB biomarkers. Reagent improvement

Experiments were conducted during development of embodiments of the present invention to identify a TB biosignature based on host markers, and a 9-marker model distinguishing TB from non-TB in a blinded sample set with 80% sensitivity and 84% specificity at the operating point selected for the verification. It is contemplated that the specificity of the test will be improved by the inclusion of SOMAmers specific for Mtb proteins. Experiments are conducted during development of embodiments of the present invention to improve Mtb proteins as biomarkers. Improved Mtb protein SOMAmers will be developed, addressing present issues (Table 4), most notably a high background of most Mtb SOMAmers when used in 40%> serum (Figure 12).

Table 4. Possible reasons for the poor performance of the Mtb SOMAmers in serum, and ways of mitigation to overcome the shortcomings

It is contemplated that Mtb SOMAmers exhibited high background due to nonspecific binding to other serum components, which led to poor detection limits under nonoptimized conditions. In contrast, many of the Mtb SOMAmers performed well in a less complex sample matrix such as urine, where low background was observed.

The strategy for generation of "low background" Mtb SOMAmers involves passive counter-selection with human serum during the SELEX process to remove sequences that are potential serum protein binders: Selection in round 1 is performed in the presence of 40% serum, subsequent rounds with 8% serum, using serum competitor buffer prepared as a concentrated stock (80% human serum, 2 μΜ prothrombin, and 2 μΜ casein). Alternating rounds of SELEX (R5, R7, R9, Rl 1) will not use serum counter-selection to avoid carry-over of sequences that may be bound to certain serum proteins that form complexes with the Mtb protein targets. Proof-of-concept has already been done with 6 Mtb proteins for which SELEX with the selrum counter-selection step has led to new SOMAmer pools. All new candidate clones are screened for lower background compared to previous SOMAmers for these targets via radiolabel filter binding assays and slide hybridization screening assays in the presence of 0-40% serum.

SELEX to generate additional and/or improved Mtb SOMAmers will be performed with new and previous targets (Table 5).

Table 5. New selections of Mtb-specific SOMAmers

A total of 82 selections (2 SELEX plates) will be performed. Active pools obtained after 7-11 rounds will be sent for Ion Torrent ePCR and Sequencing (estimated 50 pools). Clone picks (6 per pool, estimated 300 total) will be synthesized as 5' PBDC 50-mers for screening in standard filter binding assays and then moved into the slide screening assay. The best performing SOMAmers (1-3 per target, estimated 40-80 total) that also show low background in the serum titrations as part of the slide screening assays will be synthesized at larger (1 μιηοΐ) scale, HPLC-purified, and incorporated into SOMAscan. Prior to testing any clinical samples, the Mtb SOMAmer reagents will be validated for binding to native Mtb proteins in SOMAscan using fractions from a human macrophage infection model, specifically, using lysates, supernatants, and exosomes collected at 72 h post-infection from quadruplicate cultures of infected vs. uninfected cells (estimated 24 samples). The Mtb SOMAmers will also be evaluated in competition immunoassays, which will allow the direct comparison with available antibodies.

In some embodiments, performance of SOMAmers is improved substantially by post- SELEX modifications (Davies, 2012; Gelinas, 2014; herein incorporated by reference in their entireties), which involves both systematic and targeted changes of the original modified 50mer DNA SOMAmer (Figure 13). All SOMAmers are prepared at small scale by high through-put synthesis in house. First, the sequence is truncated from both the 5' and 3' end to a minimal length. Second, a linker scan identifies nonessential positions via replacement of individual nucleotides by a C3 spacer (lacking the sugar ring and the base but maintaining the three carbons between phosphates), and positions are identified that can accommodate 2Ό- methyl substitutions. Third, specific point substitutions are introduced to screen 5-position variants of the modified bases. For example post-SELEX optimization of SOMAmer 5557-2 for EsxB (CFP1 0) is contemplated. The original SOmer of 5557-2 (2Nap-dU) had demonstrated moderately good activity in the radiolabel filter binding assay, with Kd=1.46 nM for the original eDNA obtained in SELEX and Kd=l .23 nM for the PSDC 50mer. In past studies affinity improvements of up to 100-fold have been observed for SOMAmers with initial affinity in this range when they were optimized post-SELEX. SOMAmer 5557-2 was validated as a specific reagent to detect CFP10 in fractions from the macrophage infection model, where it distinguished Mtb from M. bovis BCG. Furthermore, this SOMAmer showed low background in SOMAscan of serum and was capable to identify some of the TB patients using urine samples. A sequential series of truncations, linker scan, and substitutions, requiring the synthesis of 100 analogs at 50 nmol scale is contemplated. The best candidate(s) are identified in radiolabel filter binding assays and will be synthesized at larger (1 μιηοΐ) scale, HPLC -purified, and incorporated into SOMAscan.

Assay refinement

Circulating antigens in serum are likely complexed with antibodies which hinder detection. Immune complex dissociation under mild acidic conditions prior to antigen or antibody detection has been described for HIV (p24), hepatitis C (antibody), leishmaniasis, dengue (NS-1 antigen). Typically, serum is mixed with one volume of 1.5 M glycine pH 2.8 and incubated for 1 h at 37°C to dissociate Ab-Ag immune complexes, followed by neutralization with one volume of 1.5 M Tris-HCI pH 9.7. In a published example for dengue, this treatment increased the rate of NS-1 antigen detection in serum from infected patients from 18% to 78% (Koraka, 2003; herein incorporated by reference in its entirety). The utility and feasibility of mild acid treatment for Mtb antigen detection will be evaluated. First, all SOMAmer reagents are screened to compare binding of Mfb targets (spiked into buffer) with and without acid treatment. Second, experiemnts will be conducted to compare the performance of Mtb SOMAmers in the SOMAscan assay, using 20 clinical serum samples from TB and non-TB with and without mild acid treatment.

The assay refinement strategy will focus on the optimization of serum dilutions to establish performance criteria for the Mtb SOMAmers. Mtb SOMAmers suffered from high background signals when used in the SOMAmer mix for 40% serum to detect low-abundant proteins. Matrix titrations will be performed to define the optimal serum concentrations for each analyte. Since Mtb proteins are not present in normal serum, spike and recovery and dilution linearity assessments will be used to characterize the performance of SOMAscan with respect to accuracy, signal-to-noise ratio and lower/upper limits of detection for Mtb- specific SOMAmers, as shown for an example (Figure 14). In particular, the dilution of serum from 40% to 1%, although concomitantly diluting the Mtb proteins, can increase the signal-to-noise ratios, which ultimately defines the overall assay performance. Thus, optimized serum dilutions can lead to improved detection of Mtb proteins and accuracy of the proteomic measurements. In reference to the nine host markers in the current HR9 model, four of them were measured in 1% serum and five of them in 0.005% (so these are medium to high abundance proteins) based on previous optimization of the conditions for each individual SOMAmer.

The top TB biomarkers identified as the classifier (host and microbial) are assembled and measured in a TB panel, where measurements can be reported in concentration space and can be optimized for performance and validated to the level acceptable for clinical research applications. Panels can also be moved to alternate read-out formats for better turn-around times and reduced cost. The feasibility of developing a streamlined multiplexed SOMAmer- based assay (SOMApanel) that is robust, sensitive, and quantitative and permits seamless transition from biomarker panels identified in SOMAscan to diagnostic applications has been demonstrated (Kraemer, 2011; herein incorporated by reference in its entirety). The bio- analytical work plan for panel assay development is based on guidance for the validation of immunoassays for protein biomarkers to support pre-clinical and clinical studies (Valentin, 2011; herein incorporated by reference in its entirety). A SOMAmer-based multiplex panel assay for the quantitative determination of the Mtb proteins, for the 9 host response (HR9) markers, and for other markers identified will be developed. The performance will be verified in the standard slide hybridization assay, except that only panel SOMAmers will be present during the incubation and that only probes for the panel SOMAmers will be required on the slides. Panel assay performance is assessed on a suspension microarray (Luminex) platform using a different bead type (color) for each SOMAmer-specific anti-sense probe.

Hybridization to the bead-immobilized probes and fluorescent measurements using the Luminex platform will replace the backend part of the SOMAscan assay (hybridization to a slide array and slide reading) and will reduce cost several-fold. Minimum required dilution and linear dilution range in matrix for each marker in the panel will be determined by using protein calibrator standard curves run in parallel in the same experiments. REFERENCES

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Claims

1. A method of detecting tuberculosis infection is a subject, comprising detecting at least one Mtb biomarker selected from MP64, ACR, CH602, PstSl, DnaK, MASZ, CHIO, RL7, TPX, CF30, KAD, MPT51 , EsxB, EsxA, A85 A, A85B, and A95C in a urine sample from the subject.

2. The method of claim 1, wherein detecting comprises detecting the presence of said at least one Mtb biomarker.

3. The method of claim 1 or claim 2, wherein detecting comprises detecting the level of said at least one Mtb biomarker.

4. The method of any one of claims 1 to 3, wherein the method comprises detecting 2 or more Mtb biomarkers.

5. The method of any one of claims 1 to 3, wherein the method comprises detecting 9 or more Mtb biomarkers.

6. The method of any one of the preceding claims, wherein the method comprises detecting 100 or fewer biomarkers.

7. The method of any one of the preceding claims, wherein the method comprises detecting 15 or fewer Mtb biomarkers.

8. The method of any one of the preceding claims, wherein the method comprises detecting 12 or fewer Mtb biomarkers.

9. The method of any one of the preceding claims, wherein the method comprises identifying the subject as having latent TB infection.

10. The method of any one of claims 1 to 8, wherein the method comprises identifying the subject as having active TB infection.

11. The method of any one of claims 1 to 9, wherein the subject has latent TB infection.

12. The method of any one of claims lto 8 and 10, wherein the subject has active TB infection.

13. The method of any one of the preceding claims, further comprising treating said subject for tuberculosis.

14. The method of claim 13, comprising treating the subject for latent tuberculosis infection.

15. The method of claim 13, comprising treating the subject for active tuberculosis infection.

16. The method of any one of claims 13 to 15, comprising administering isoniazid (ΓΝΗ), rifampin (RIF), rifapentine (RPT), ethambutol (EMB), pyrazinamide (PZA), and/or another approved TB therapeutic to the subject.

17. The method of any one of the preceding claims, further comprising one or more additional TB-diagnostic steps.

18. The method of claim 17, wherein an additional TB-diagnostic step comprises a chest x-ray.

19. The method of any one of the preceding claims, further comprising generating a report indicating said subject has TB infection.

20. The method of any one of the preceding claims, wherein the method comprises concentrating the urine prior to detecting at least one Mtb biomarker.

21. The method of any one of the preceding claims, wherein each biomarker is a protein biomarker.

22. The method of any one of the preceding claims, wherein the method comprises contacting biomarkers of the sample from the subject with a set of biomarker capture reagents, wherein each biomarker capture reagent of the set of biomarker capture reagents specifically binds to a different biomarker being detected.

23. The method of claim 22, wherein each biomarker capture reagent is an antibody or an aptamer.

24. The method of claim 23, wherein each biomarker capture reagent is an aptamer.

25. The method of claim 24, wherein at least one aptamer is a slow off-rate aptamer.

26. The method of claim 25, wherein at least one slow off-rate aptamer comprises at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, or at least 10 nucleotides with modifications.

27. The method of claim 25 or claim 26, wherein each slow off-rate aptamer binds to its target protein with an off rate (t½) of > 30 minutes, > 60 minutes, > 90 minutes, > 120 minutes, > 150 minutes, > 180 minutes, > 210 minutes, or > 240 minutes.

28. A composition comprising one or more capture reagents for detecting one or more Mtb biomarker selected from MP64, ACR, CH602, PstSl, DnaK, MASZ, CHIO, RL7, TPX, CF30, KAD, MPT51 , EsxB, EsxA, A85A, A85B, and A95C.

29. The composition of claim 28, wherein the composition comprises capture reagents for detecting 2 or more Mtb biomarkers.

30. The composition of claim 28 or claim 29, wherein the composition comprises capture reagents for detecting 9 or more Mtb biomarkers.

31. The composition of any one of claims 28 to 30, wherein the composition comprises capture reagents for detecting 100 or fewer biomarkers.

32. The composition of any one of claims 28 to 31, wherein the composition comprises aptamers for detecting 15 or fewer Mtb biomarkers.

33. The composition of any one of claims 28 to 32, wherein the composition comprises capture reagents for detecting 12 or fewer Mtb biomarkers.

34. The composition of any one of claims 28 to 33, wherein each biomarker is a protein biomarker.

35. The composition of any one of claims 28 to 34, wherein each biomarker capture reagent specifically binds to a different Mtb biomarker.

36. The composition of any one of claims 28 to 35, wherein each biomarker capture reagent is an antibody or an aptamer.

37. The composition of claim 36, wherein each biomarker capture reagent is an aptamer.

38. The composition of claim 37, wherein at least one aptamer is a slow off-rate aptamer.

39. The composition of claim 38, wherein at least one slow off-rate aptamer comprises at least one, at least two, at least three, at least four, at least five, at least six, at least seven, at least eight, at least nine, or at least 10 nucleotides with modifications.

40. The composition of claim 38 or claim 39, wherein each slow off-rate aptamer binds to its target protein with an off rate (t½) of > 30 minutes, > 60 minutes, > 90 minutes, > 120 minutes, > 150 minutes, > 180 minutes, > 210 minutes, or > 240 minutes.

41. The composition of any one of claims 28 to 40, wherein the capture reagents are detectably labeled.

42. The composition of any one of claims 28 to 41, wherein the aptamers are attached to a solid surface.

43. The composition of any one of claims 28 to 42, further comprising one or more capture reagents for detecting one or more host biomarkers.