“METHYLATION BIOMARKER FOR INFECTION RESISTANCE”

[0001] This application claims priority to Australian Provisional Patent Application No. 2022902106 entitled “Methylation Biomarker for Infection Resistance” filed 27 July 2022, the contents of which are incorporated herein by reference in their entirety.

FIELD OF THE INVENTION

[0002] This invention relates generally to biomarkers for assessing the likelihood of a subject being resistant to a virus infection.

BACKGROUND OF THE INVENTION

[0003] The reference in this specification to any prior publication (or information derived from it), or to any matter which is known, is not, and should not be taken as an acknowledgment or admission or any form of suggestion that that prior publication (or information derived from it) or known matter forms part of the common general knowledge in the field of endeavor to which this specification relates.

[0004] Most proteins undergo post-translational modifications (PTMs), and epigenetic enzymes fine-tune critical protein function in response to environmental cues via methylation and demethylation PTMs and histone PTMs that modify chromatin structure (Huang et al., 2007; Wang et al., 2008; Yang et al., 2010). It has been reported that ACE2 is methylated and demethylated at lysine 31 and that glutamine 493 in the SARS-CoV-2 spike protein receptor-binding domain (RBD) binds to this residue (Tu et al., 2021 ). In vitro, SARS-CoV-2 infection decreased ACE2 methylation, and ACE2 lysine 31 hypermethylation significantly decreased interactions with the SARS-CoV-2 spike protein (Tu et al., 2021 ).

[0005] SARS-CoV-2 is a single-stranded, positive-sense RNA virus. Like some other RNA viruses, SARS-CoV-2 exploits the importin nuclear shuttling machinery during infection to hijack host cell transcription and responses (Caly et al., 2021 ; Jans et al., 2019). Several studies have now shown that targeting the importin-mediated nuclear transport machinery may be critical for inhibiting SARS- CoV-2 infection. Importin-a plays a role in SARS-CoV-2 infection through nucleocytoplasmic shuttling of the SARS-CoV nucleocapsid protein and subsequent host cell division (Hiscox et al., 2001 ; Rowland et al., 2005; Timani et al., 2005; Wulan et al., 2015; Wurm et al., 2001 ). Finally, ivermectin, which inhibits the importin pathway, inhibits SARS-CoV-2 replication (Caly et al., 2020).

[0006] A highly conserved nuclear localization signal (NLS) within the C-terminal (cytoplasmic) tail of ACE2 has been reported (Tu et al., 2021 ). ACE2. Following SARS-CoV-2 infection, ACE2 translocates to the nucleus via its interaction with importin-a. The crystal structure of the ACE2 cytoplasmic tail-importin-a complex revealed a direct interaction between the lysine residues within the NLS motif of ACE2 and importin-a, as confirmed by microscale thermophoresis and fluorescence polarization (Tu et al., 2021 ). [0007] The successful development and rollout of COVID-19 vaccines has been one of the positive outcomes from the 2020 COVID-19 pandemic. Nevertheless, it is now becoming clear that vaccine efficacy can quickly wane, especially in the face of new variants. Therapies that complement vaccine-induced immune protection are still needed, especially for vulnerable individuals.

SUMMARY OF THE INVENTION

[0008] The present invention is predicated in part on the discovery that subjects resistant to sever SARS-CoV-2 infection had a significant induction of ACE2 ^me signal and increased neutralizing antibody titres against SARS-CoV-2.

[0009] Accordingly, in one aspect the present invention provides a method for assessing the likelihood of a subject having resistance to a coronavirus infection, the method comprising, consisting, or consisting essentially of detecting a methylated lysine reside in an ACE2 polypeptide sequence from the subject.

[0010] In some embodiments, the method comprises detecting methylation of ACE2-31 K (ACE2-31 K-Me) and assessing that the subject is likely to be resistant to a coronavirus infection.

[0011] In some preferred embodiments, the coronavirus is SARS-CoV-2.

[0012] In another aspect, the present invention provides a method of determining an indicator of the likelihood that a subject is resistant to a SARS-CoV-2 infection, the method comprising assessing the methylation status of an ACE2 polypeptide in a sample obtained from the subject, and determining an indicator of resistance to a SARS-CoV-2 infection in the subject on the basis of a positive methylation status of the ACE2 polypeptide.

[0013] In some embodiments, the methylation status includes the presence or absence of a methylated lysine at the residue corresponding to position 31 of the native human ACE2 amino acid sequence. In some embodiments, the methylation status is assessed by measuring the binding of a polyclonal antibody that is specific for ACE2 that is methylated at the amino acid residue corresponding to lysine 31 of the native human ACE2 amino acid sequence.

[0014] In some of the same embodiments and some other embodiments, the polyclonal antibody is selected is specific to an amino acid sequence comprising, consisting, or consisting essentially of amino acids 24-38 of SEQ ID NO. 1 .

[0015] In some of the same embodiments and some other embodiments, the sample comprises CD3+ cells, CD14+ cells, and/or CD8+/CD4+ T cells. In some embodiments, the sample comprises a monocyte cell.

[0016] In some embodiments, the sample comprises a PBMC sample or a tissue sample (such as a kidney sample, brain sample, or gut sample). By way of an illustrative example, the sample may comprise lung tissue.

[0017] In some embodiments, the methylation status of the ACE2 polypeptide is assessed using an ACE2 ^me antibody.

[0018] In another aspect, the present invention provides a method for detecting and quantifying the methylation status of an ACE2 polypeptide, the method comprising the step of putting into contact the ACE2 polypeptide isolated from the human body with a polyclonal or monoclonal antibody designed against at least a specific amino acid sequence of an ACE2 polypeptide, wherein the sequence consists of amino acid residues 24-38.

[0019] In another aspect, the present invention provides a polyclonal antibody that binds to an ACE2 polypeptide, wherein the antibody binds to the amino acid sequence, QAKTFLD(K ^me )FNHEAED, of the ACE2 polypeptide.

[0020] In yet another aspect, the present invention provides a kit for detecting and/or quantifying the methylation status of an ACE2 polypeptide. In some embodiments, the kit may comprise the ACE2 antibody described above and/or elsewhere herein, together with reagents suitable for immunoflourscent staining of a biological sample (e.g., PBMCs or tissues). Alternatively, in some embodiments the kit may comprise the ACE2 antibody described above and/or elsewhere herein, together with reagents suitable for performing an ELISA to detect the methylated ACE2 protein in a biological sample (e.g., a liquid biopsy sample or a tissue sample). In some specific embodiments, the kit comprises a micro-plate wherein some wells are coated with a polyclonal antibody that binds to a methylated lysine at a position corresponding to lysine 31 of the full length native ACE2 amino acid sequence (e.g., SEQ ID NO: 1 ), and a container for a control sample comprising an ACE2 polypeptide with a methylated lysine residue at a position corresponding to position 31 of the sequence set forth in SEQ ID NO: 1.

[0021] In yet another aspect, the present invention provides a composition comprising a biological sample (e.g., a liquid biopsy or a tissue sample) and a reagent for detecting the presence of a methylated lysine at a position Lys31 of the full length native ACE2 amino acid sequence (e.g., as set forth in SEQ ID NO: 1 ).

[0022] In some embodiments, the reagent is a polyclonal antibody that specifically binds to a methylated lysine at a position corresponding to lysine 31 of the full length native ACE2 amino acid sequence (e.g., as set forth in SEQ ID NO:1 ),

[0023] In some of the same embodiments and in some other embodiments the biological sample comprises one or more PBMC.

[0024] In some of the same embodiments and in some other embodiments the biological sample comprises whole blood.

[0025] In some of the same embodiments and in some other embodiments the biological sample comprises a tissue (e.g., lung, kidney, gut, etc).

BRIEF DESCRIPTION OF THE FIGURES

[0026] Figu e 1. Generation of a novel antibody specific for ACE2 methylated at lysine 31 (“ACE2 ^me antibody”). (A) ACE2 was pulled down from Caco2 cells (ACE2 antibody (Abeam, ab15348), which targets the ACE2 NLS region), and samples were then subjected to western blot analysis with ACE2 ^me antibodies. Lane 1 : no-antibody control (Neg), Lane 2: ACE2 pull down, Lane 3: precision plus protein ladder (L) used for molecular weight determination (kDa). (B) Caco2 cells were permeabilized as described in the methods and either stained with secondary antibody anti rabbit (AF 568) only, ACE2 ^me primary rabbit polyclonal antibody only, or ACE2 ^me rabbit polyclonal and anti-rabbit secondary antibody (AF 568). Stained cells were imaged with the ASI Digital pathology platform at 100x. Example images are depicted above with 10 mM scale bars in orange. Images show staining was only achieved in group C, indicating that the IF signal seen is specific for staining by the ACE2 ^me antibody. (C) Representative images of uninfected or SARS-CoV-2-infected Caco-2 cells using the ASI Digital Pathology microscopy system are depicted. Cells were permeabilized (intracellular) for immunostaining with the ACE2 ^me antibodies. (D) Representative images of uninfected or SARS-CoV-2-infected Caco-2 cells using the ASI Digital Pathology microscopy system are depicted. Cells were permeabilized (intracellular) for immunostaining with ACE2 ^unmod antibodies. DAPI (cyan) was used to visualize nuclei. Depicted orange scale bar is 10 mm (inset). The nuclear (NFI) fluorescent intensity or cytoplasmic (CFI) fluorescent intensity was determined using imageJ-Fij i analysis of capture images (n = 20 cells analyzed). Data are mean ± SEM. Mann-Whitney test was used to calculate differences: ****p < 0.0001 .

[0027] Figure 2. ACE2 methylation in the bronchial epithelial cells of the lungs is inversely proportional to positive SARS-CoV-2 infected cells. (A) Images (taken with ASI Digital pathology system) showing ACE2 methylation in the bronchial epithelial cells of the lung FFPE section in SARS-CoV-2 infected Syrian golden hamsters at day 2 and day 5. Lung tissue FFPE was stained for SARS-CoV-2 spike and ACE2 ^me , DAPI was used to stain the nucleus. (B-C) Depicts dot blots or grouped plots for the analysis and imaging that was carried out using ASI Digital pathology analysis of captured images (n > 2000 cells analyzed) from (A). Data is plotted with (B) mean ± SEM and represents population dynamics (cells positive for each marker) and the fluorescent intensity of ACE2 ^me . (C) Population dynamics for CD3+ cells and CD3+ACE2 ^me + cells out of total CD3 cells in lung tissues. Data is plotted with (C) mean ± SEM and represents population dynamics (cells positive for each marker) and the fluorescent intensity of SARS-COV-2. One-way ANOVA was used to calculate differences: NS = non-significant, * = 0.015 ** = 0.0047, *** = 0.0007, ****<0.0001 .

[0028] Figure 3. ACE2 ^me is inhibited in severe Covid-19 disease and enriched in patient PBMCs following SARS-CoV-2 vaccination. (A) Representative image of PBMCs derived from Covid-19 patients using the ASI digital pathology system with a 10 mm scale bar (orange included). Cells were permeabilized (intracellular) for immunostaining for our custom antibody ACE2 ^me . DAPI (cyan) was used to visualize nuclei. Dot plot/bar quantification of the fluorescence intensity (cytoplasmic/CFI) of ACE2 ^me and population % dynamics in mild, moderate or severe Covid-19 patient PBMCs of ACE2 ^me (n = 3 patients per a group) are depicted. (B) Representative image of PBMCs obtained from patients before and after vaccinated for Covid-19. Images were taken using the ASI digital pathology system with a 10 mm scale bar (orange line). Cells were permeabilized (intracellular) for immunostaining for the custom ACE2 ^me antibody. DAPI (cyan) was used to visualize nuclei. Dot plot/bar quantification of the fluorescence intensity (cytoplasmic/CFI) of ACE2 ^me is plotted with significance differences indicated in in pre- and post-vaccinated PBMCs of ACE2 ^me (n = 13 patients per a group) are depicted. (C) Dot plots are from PBMCs derived from either convalescent Covid-19 or uninfected patients after vaccinated for Covid-19. PBMCs were analyzed using the ASI digital pathology system with a 10mm scale bar (orange included). Cells were permeabilized (intracellular) for immunostaining for our custom antibody ACE2 ^me . DAPI (cyan) was used to visualize nuclei. Dot plot/bar quantification of the fluorescence intensity (cytoplasmic/CFI) of ACE2 ^me in post vaccinated PBMCs of ACE2 ^me (n = 13 patients (uninfected) and n = 19 (Covid-19 infected/convalescent) are depicted. (D) Dot plots are from PBMCs derived from convalescent Covid-19 patients taken before and after vaccination for Covid-19. PBMCs were analyzed using the ASI digital pathology system with a 10 mm scale bar (orange line). Cells were permeabilized (intracellular) for immunostaining for our custom antibody ACE2 ^me . DAPI (cyan) was used to visualize nuclei. Dot plot/bar quantification of the fluorescence intensity (cytoplasmic/CFI) of ACE2 ^me in pre and post vaccinated PBMCs of ACE2 ^me (n = 3 patients, 2 mild disease and one severe) are depicted. (E) Schematic showing blood sample collection from vaccinated patients (post 3 ^rd dose) who subsequently developed and recovered from COVID-19. (F) Depicts the fluorescence intensity (Fl) of ACE2 ^me , IL-6, and SARS-CoV-2 spike protein in CD14+ monocytes from vaccinated patients recovered from COVID-19 treated with or without 10 mM = NACE2L The Fl was determined using ASI Digital Pathology analysis of captured images (>20 cells analyzed) in CD14+ monocytes. Data plotted are means ± SEM. Tukey’s post hoc test, * p < 0.05, ** p < 0.003, *** p < 0.001 , **** p < 0.0001 . PB = Post-boost, PI = Post-infection.

[0029] Figure 4. ACE2 ^me is enriched in patient PBMCs following SARS-CoV-2 vaccination and correlates with increased titers of neutralizing spike protein antibody. (A) Schematic showing blood sample collection from pre- and post-vaccination individuals. (B) Plots of individuals pre- and post-vaccination showing the population dynamics of ACE2 ^me + cells compared with the neutralizing antibody titer for that patient against the parental or delta SARS-CoV-2 strain, n = 13 individuals. Data plotted are means ± SEM. Paired t-test, *p < 0.05, *** p < 0.001 . (Individual plots are in Figure 4C). Plots of individuals pre- and post-vaccination showing the population dynamics of ACE2 ^me + cells compared with the neutralizing antibody titer for that patient against the parental or delta SARS-CoV-2 strain, n = 13 individuals.

[0030] Figure 5 shows a significant increase in expression of ACE2 ^me + in CD14+ cells relative to total PBMCs after vaccination. Individual plots for each patient comparing the protein expression dynamics of ACE2 ^me expression in either bulk ACE2 ^me + cells (green) or CD14b+ cells (purple) contrasting to the neutralizing antibody titer for that patient against the parent (black) or delta SARS-CoV-2 (red) strain. Graphs depict the cytoplasmic fluorescent intensity of ACE2 in either bulk ACE2 ^me + positive cells or in CD14b+ cells on the left-hand Y axis and the neutralizing antibody on the right-hand Y axis, pre and post vaccination. Pre and post vaccination samples were taken approximately 3 months apart, with post vaccination samples taken approximately 1 month after second dose, the vaccine used is indicated in graph.

[0031] Figure 6 provides graphical representations of the ACE2 ^me antibody specificity for the methylated form of ACE2. (A) Depicts plasmid maps of ACE2 wild type (ACE2_WT) or ACE2 mutant plasmid (ACE2 K31 A: lysine to alanine mutation at position 31 ). (B) Depicts graphs and example images of Fl analysis of MRC5 cells that have been transfected with either ACE2_WT or ACE2 K31 A plasmids and stained for either ACE2 ^me or ACE2. Images were taken using the ASI Digital Pathology system (scale bar 10 pm) and data represent mean ± SEM, n = 4. Tukey’s post test, *** p< 0.001 , ****p < 0.0001 . DETAILED DESCRIPTION OF THE INVENTION

1. Definitions

[0032] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the art to which the invention belongs. Although any methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, preferred methods and materials are described. For the purposes of the present invention, the following terms are defined below.

[0033] The articles "a" and "an" are used herein to refer to one or to more than one (i.e. to at least one) of the grammatical object of the article. By way of example, "an element" means one element or more than one element.

[0034] The term "about" as used herein refers to the usual error range for the respective value readily known to the skilled person in this technical field. Reference to "about" a value or parameter herein includes (and describes) embodiments that are directed to that value or parameter perse.

[0035] The "amount" or "level" of a biomarker is a detectable level or amount in a sample. These can be measured by methods known to one skilled in the art and also disclosed herein. These terms encompass a quantitative amount or level (e.g., weight or moles), a semi-quantitative amount or level, a relative amount or level (e.g., weight % or mole % within class), a concentration, and the like. Thus, these terms encompass absolute or relative amounts or levels or concentrations of a biomarker in a sample. The expression level or amount of biomarker assessed can be used to determine the response to treatment.

[0036] As used herein, "and/or” refers to and encompasses any and all possible combinations of one or more of the associated listed items, as well as the lack of combinations when interpreted in the alternative (or).

[0037] The term "antibody" herein is used in the broadest sense and specifically covers monoclonal antibodies (including full length monoclonal antibodies), polyclonal antibodies, chimeric antibodies, humanized antibodies, human antibodies, multispecific antibodies (e.g., bispecific antibodies), and single variable domain antibodies so long as they exhibit the desired biological activity. The term "antibody” includes immunoglobulin molecules comprising four polypeptide chains, two heavy (H) chains and two light (L) chains inter-connected by disulfide bonds, as well as multimers thereof (e.g., IgM). Each heavy chain comprises a heavy chain variable region (which may be abbreviated as HCVR or VH) and a heavy chain constant region. The heavy chain constant region comprises three domains, C _H1 , C _H2 and C _H3 . Each light chain comprises a light chain variable region (which may be abbreviated as LCVR or VL) and a light chain constant region. The light chain constant region comprises one domain (C _L1 ) . The V and VL regions can be further subdivided into regions of hypervariability, termed complementarity determining regions (CDRs), interspersed with regions that are more conserved, termed framework regions (FR). Each VH and VL is composed of three CDRs and four FRs, arranged from amino-terminus to carboxy-terminus in the following order: FR1 , CDR1 , FR2, CDR2, FRS, CDRS, FR4. In different embodiments of the invention, the FRs of an antibody (or antigen-binding portion thereof) may be identical to the human germline sequences, or may be naturally or artificially modified. An amino acid consensus sequence may be defined based on a side- by-side analysis of two or more CDRs. Included within the scope of the term “antibody” is an antibody of any class, such as IgG, IgA, or IgM (or sub-class thereof), and the antibody need not be of any particular class. Depending on the antibody amino acid sequence of the constant region of its heavy chains, immunoglobulins can be assigned to different classes. There are five major classes of immunoglobulins: IgA, IgD, IgE, IgG, and IgM, and several of these may be further divided into subclasses (isotypes), e.g., lgG1 , lgG2, lgG3, lgG4, IgAI and lgA2. The heavy-chain constant regions that correspond to the different classes of immunoglobulins are called a, δ, ε, y, and μ, respectively. The subunit structures and three-dimensional configurations of different classes of immunoglobulins are well known.

[0038] The term “biomarker” as used herein refers to an indicator, e.g., predictive, diagnostic, and/or prognostic, which can be detected in a sample. The biomarker may serve as an indicator of a particular subtype of a disease or disorder (e.g., cancer), characterized by certain, molecular, pathological, histological, and/or clinical features, and/or may serve as an indicator of a particular cell type or state (e.g., epithelial, mesenchymal etc.) and/or or response to therapy. Biomarkers include, but are not limited to, polynucleotides (e.g., DNA, and/or RNA), polynucleotide copy number alterations (e.g., DNA copy numbers), polypeptides, polypeptide and polynucleotide modifications (e.g., posttranslational modifications), carbohydrates, and/or glycolipid-based molecular markers. A biomarker may be present in a sample obtained from a subject before the onset of a physiological or pathophysiological state (e.g., primary cancer, metastatic cancer, etc.), including a symptom, thereof (e.g., response to therapy). Thus, the presence of the biomarker in a sample obtained from the subject can be indicative of an increased risk that the subject will develop the physiological or pathophysiological state or symptom thereof. Alternatively, or in addition, the biomarker may be normally expressed in an individual, but its expression may change (i.e., it is increased (upregulated; over-expressed) or decreased (downregulated; under-expressed) before the onset of a physiological or pathophysiological state, including a symptom thereof. Thus, a change in the level of the biomarker may be indicative of an increased risk that the subject will develop the physiological or pathophysiological state or symptom thereof. Alternatively, or in addition, a change in the level of a biomarker may reflect a change in a particular physiological or pathophysiological state, or symptom thereof, in a subject, thereby allowing the nature (e.g., severity) of the physiological or pathophysiological state, or symptom thereof, to be tracked over a period of time. This approach may be useful in, for example, monitoring a treatment regimen for the purpose of assessing its effectiveness (or otherwise) in a subject. As herein described, reference to the level of a biomarker includes the concentration of a biomarker, or the level of expression of a biomarker, or the activity of the biomarker.

[0039] The terms “biomarker signature”, “signature”, “biomarker expression signature”, or “expression signature” are used interchangeably herein and refer to one or a combination of biomarkers whose expression is an indicator, e.g., predictive, diagnostic, and/or prognostic. The biomarker signature may serve as an indicator of a particular subtype of a disease or disorder (e.g., primary cancer, metastatic cancer, etc.) or symptom thereof (e.g., response to therapy, drug resistance, and/or disease burden) characterized by certain molecular, pathological, histological, and/or clinical features. In some embodiments, the biomarker signature is a “gene signature.” The term “gene signature” is used interchangeably with “gene expression signature” and refers to one or a combination of polynucleotides whose expression is an indicator, e.g., predictive, diagnostic, and/or prognostic. In some embodiments, the biomarker signature is a “protein signature.” The term "protein signature" is used interchangeably with “protein expression signature” and refers to one or a combination of polypeptides whose expression is an indicator, e.g., predictive, diagnostic, and/or prognostic. A biomarker signature may comprise at least 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23, 24, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 100 or more biomarkers.

[0040] The term “cellular compartment” includes a part of a cell including organelles (such as mitochondria, Golgi apparatus, endoplasmic reticulum, ribosomes, etc.), the nucleus, the cytoplasm (optionally including the organelles), the nuclear membrane, the cell membrane and other cellular regions.

[0041] Throughout this specification, unless the context requires otherwise, the words “comprise,” “comprises” and “comprising” will be understood to imply the inclusion of a stated step or element or group of steps or elements but not the exclusion of any other step or element or group of steps or elements. Thus, use of the term “comprising” and the like indicates that the listed elements are required or mandatory, but that other elements are optional and may or may not be present. By “consisting of’ is meant including, and limited to, whatever follows the phrase “consisting of’. Thus, the phrase “consisting of’ indicates that the listed elements are required or mandatory, and that no other elements may be present. By “consisting essentially of’ is meant including any elements listed after the phrase, and limited to other elements that do not interfere with or contribute to the activity or action specified in the disclosure for the listed elements. Thus, the phrase “consisting essentially of’ indicates that the listed elements are required or mandatory, but that other elements are optional and may or may not be present depending upon whether or not they affect the activity or action of the listed elements.

[0042] As used herein, the term “correlates” or “correlates with” and like terms, refers to a statistical association between two or more things, such as events, characteristics, outcomes, numbers, data sets, etc., which may be referred to as “variables”. It will be understood that the things may be of different types. Often the variables are expressed as numbers (e.g., measurements, values, likelihood, risk), wherein a positive correlation means that as one variable increases, the other also increases, and a negative correlation (also called anti-correlation) means that as one variable increases, the other variable decreases.

[0043] By “corresponds to” or “corresponding to” is meant an amino acid sequence that displays substantial sequence similarity or identity to a reference amino acid sequence. In general the amino acid sequence will display at least about 70, 71 , 72, 73, 74, 75, 76, 77, 78, 79, 80, 81 , 82, 83, 84, 85, 86, 97, 88, 89, 90, 91 , 92, 93, 94, 95, 96, 97, 98, 99% or even up to 100% sequence similarity or identity to at least a portion of the reference amino acid sequence.

[0044] An “effective amount” is at least the minimum amount required to effect a measurable improvement or prevention of a particular disorder. An effective amount herein may vary according to factors such as the disease state, age, sex, and weight of the patient, and the ability of the antibody to elicit a desired response in the individual. An effective amount is also one in which any toxic or detrimental effects of the treatment are outweighed by the therapeutically beneficial effects. For prophylactic use, beneficial or desired results include results such as eliminating or reducing the risk, lessening the severity, or delaying the onset of the disease, including biochemical, histological and/or behavioral symptoms of the disease, its complications and intermediate pathological phenotypes presenting during development of the disease. For therapeutic use, beneficial or desired results include clinical results such as decreasing one or more symptoms resulting from the disease, increasing the quality of life of those suffering from the disease, decreasing the dose of other medications required to treat the disease, enhancing effect of another medication such as via targeting, delaying the progression of the disease, and/or prolonging survival. In the case of a virus infection, an effective amount of the drug may have the effect in reducing the viral loadre; inhibit (/.e., slow to some extent and desirably stop) tumour metastasis; inhibiting to some extent tumour growth; and/or relieving to some extent one or more of the symptoms associated with the cancer or tumour. In the case of an infection, an effective amount of the drug may have the effect in reducing pathogen (bacterium, virus, etc.) titers in the circulation or tissue; reducing the number of pathogen infected cells; inhibiting (/.e., slow to some extent or desirably stop) pathogen infection of organs; inhibit (/.e., slow to some extent and desirably stop) pathogen growth; and/or relieving to some extent one or more of the symptoms associated with the infection. An effective amount can be administered in one or more administrations. For purposes of this invention, an effective amount of drug, compound, or pharmaceutical composition is an amount sufficient to accomplish prophylactic or therapeutic treatment either directly or indirectly. As is understood in the clinical context, an effective amount of a drug, compound, or pharmaceutical composition may or may not be achieved in conjunction with another drug, compound, or pharmaceutical composition. Thus, an “effective amount” may be considered in the context of administering one or more therapeutic agents, and a single agent may be considered to be given in an effective amount if, in conjunction with one or more other agents, a desirable result may be or is achieved.

[0045] The term "expression" refers the biosynthesis of a gene product. For example, in the case of a coding sequence, expression involves transcription of the coding sequence into mRNA and translation of mRNA into one or more polypeptides. Conversely, expression of a non-coding sequence involves transcription of the non-coding sequence into a transcript only. The term "expression" is also used herein to refer to the presence of a protein or molecule in a particular location and, thus, may be used interchangeably with "localization".

[0046] The term “expression” with respect to a gene sequence refers to transcription of the gene to produce a RNA transcript (e.g., mRNA, antisense RNA, siRNA, shRNA, miRNA, etc.) and, as appropriate, translation of a resulting mRNA transcript to a protein. Thus, as will be clear from the context, expression of a coding sequence results from transcription and translation of the coding sequence. Conversely, expression of a non-coding sequence results from the transcription of the noncoding sequence.

[0047] As used herein, the term “increase” or “increased” with reference to a biomarker or biomarker complex level refers to a statistically significant and measurable increase in the biomarker or biomarker complex level compared to the level of another biomarker or biomarker complex or to a control level. The increase is preferably an increase of at least about 10%, or an increase of at least about 20%, or an increase of at least about 30%, or an increase of at least about 40%, or an increase of at least about 50%.

[0048] As used herein, the term “higher” with reference to a biomarker or biomarker complex measurement refers to a statistically significant and measurable difference in the level of a biomarker or biomarker complex measurement compared to the level of another biomarker or biomarker complex or to a control level where the biomarker or biomarker complex measurement is greater than the level of the other biomarker or biomarker complex or the control level. The difference is preferably at least about 10%, or at least about 20%, or of at least about 30%, or of at least about 40%, or at least about 50%.

[0049] As used herein, the term “reduce” or “reduced” with reference to a biomarker or biomarker complex level refers to a statistically significant and measurable reduction in the biomarker or biomarker complex level compared to the level of another biomarker or biomarker complex or to a control level. The reduction is preferably a reduction of at least about 10%, or a reduction of at least about 20%, or a reduction of at least about 30%, or a reduction of at least about 40%, or a reduction of at least about 50%.

[0050] As used herein, the term “lower” with reference to a biomarker or biomarker complex measurement refers to a statistically significant and measurable difference in the level of a biomarker or biomarker complex measurement compared to the level of another biomarker or biomarker complex or to a control level where the biomarker or biomarker complex measurement is less than the level of the other biomarker or biomarker complex or the control level. The difference is preferably at least about 10%, or at least about 20%, or of at least about 30%, or of at least about 40%, or at least about 50%.

[0051] The term “housekeeping biomarker” refers to a biomarker or group of biomarkers (e.g., polynucleotides and/or polypeptides) which are typically similarly present in ail cell types. In some embodiments, the housekeeping biomarker is a “housekeeping gene”. A “housekeeping gene" refers herein to a gene or group of genes which encode proteins whose activities are essential for the maintenance of cell function and which are typically similarly present in all cell types.

[0052] The term “host cell” includes an individual cell or cell culture which can be or has been a recipient of any recombinant vector(s) or isolated polynucleotide of the invention. Host cells include progeny of a single host cell and the progeny may not necessarily be completely identical (in morphology or in total DNA complement) to the original parent cell due to natural, accidental or deliberate mutation and/or change. A host cell includes cells transfected or infected in vivo or in vitro with a recombinant vector or a polynucleotide of the invention. A host cell which comprises a recombinant vector of the invention is a recombinant host cell.

[0053] “Hybridization” is used herein to denote the pairing of complementary nucleotide sequences to produce a DNA-DNA hybrid or a DNA-RNA hybrid. Complementary base sequences are those sequences that are related by the base-pairing rules. In DNA, A pairs with T and C pairs with G. In RNA U pairs with A and C pairs with G. In this regard, the terms “match” and “mismatch” as used herein refer to the hybridization potential of paired nucleotides in complementary nucleic acid strands. Matched nucleotides hybridize efficiently, such as the classical A-T and G-C base pair mentioned above. Mismatches are other combinations of nucleotides that do not hybridize efficiently. In the present invention, the preferred mechanism of pairing involves hydrogen bonding, which may be Watson-Crick, Hoogsteen or reversed Hoogsteen hydrogen bonding, between complementary nucleoside or nucleotide bases (nucleobases) of the strands of oligomeric compounds. For example, adenine and thymine are complementary nucleobases which pair through the formation of hydrogen bonds. Hybridization can occur under varying circumstances as known to those of skill in the art.

[0054] The term “inhibitor” as used herein refers to an agent that decreases or inhibits at least one function or biological activity of a target molecule.

[0055] As used herein, “instructional material” includes a publication, a recording, a diagram, or any other medium of expression which can be used to communicate the usefulness of the compositions and methods of the invention. The instructional material of the kit of the invention may, for example, be affixed to a container which contains the therapeutic or diagnostic agents of the invention or be shipped together with a container which contains the therapeutic or diagnostic agents of the invention.

[0056] As used herein, the term “isolated” refers to material that is substantially or essentially free from components that normally accompany it in its native state. For example, an “isolated peptide” refers to in vitro isolation and/or purification of a SETDB1 peptide mimetic from its natural cellular environment and from association with other components of the cell. “Substantially free” means that a preparation of peptide is at least 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 91 , 92, 93, 94, 95, 96, 97, 98 or 99% pure. In a preferred embodiment, the preparation of peptide has less than about 30, 25, 20, 15, 10, 9, 8, 7 , 6, 5, 4, 3, 2 or 1 % (by dry weight) of molecules that are not the subject of this invention (also referred to herein as “contaminating molecules”). When a peptide is recombinantly produced, it is also desirably substantially free of culture medium, i.e. , culture medium represents less than about 20, 15, 10, 5, 4, 3, 2 or 1% of the volume of the preparation. The invention includes isolated or purified preparations of at least 0.01 , 0.1 , 1 .0, and 10 milligrams in dry weight.

[0057] The term “label” when used herein refers to a detectable compound or composition. The label is typically conjugated or fused directly or indirectly to a reagent, such as a polynucleotide probe or an antibody, and facilitates detection of the reagent to which it is conjugated or fused. The label may itself be detectable (e.g ., radioisotope labels or fluorescent labels) or, in the case of an enzymatic label, may catalyze chemical alteration of a substrate compound or composition which results in a detectable product.

[0058] As used herein, the terms “peptide”, “polypeptide” and “protein” are used interchangeably to refer to a polymer of amino acid residues and to variants and synthetic analogues of the same. Thus, these terms apply to amino acid polymers in which one or more amino acid residues is a synthetic non-naturally-occurring amino acid, such as a chemical analogue of a corresponding naturally-occurring amino acid, as well as to naturally-occurring amino acid polymers. These terms do not exclude modifications, for example, glycosylations, acetylations, phosphorylations and the like. Soluble forms of the subject peptides are particularly useful. Included within the definition are, for example, peptides containing one or more analogues of an amino acid including, for example, unnatural amino acids or polypeptides with substituted linkages.

[0059] The term “predictive” and grammatical forms thereof, generally refer to a biomarker or biomarker signature that provides a means of identifying, directly or indirectly, a likelihood of a patient responding to a therapy or obtaining a clinical outcome in response to therapy.

[0060] The term “prognostic” and grammatical forms thereof, generally refer to an agent or method that provides information regarding the likely progression or severity of a disease or condition in an individual. In some embodiments, prognosis also refers to the ability to demonstrate a positive or negative response to therapy or other treatment regimens, for the disease or condition in the subject. In some embodiments, prognosis refers to the ability to predict the presence or diminishment of disease/condition associated symptoms. A prognostic agent or method may comprise classifying a subject or sample obtained from a subject into one of multiple categories, wherein the categories correlate with different likelihoods that a subject will experience a particular outcome. For example, categories can be low risk and high risk, wherein subjects in the low risk category have a lower likelihood of experiencing a poor outcome (e.g., within a given time period such as 5 years or 10 years) than do subjects in the high risk category. A poor outcome could be, for example, disease progression, disease recurrence, or death attributable to the disease.

[0061] The term “sample” as used herein includes any biological specimen that may be extracted, untreated, treated, diluted or concentrated from a subject. Samples may include, without limitation, biological fluids such as whole blood, serum, red blood cells, white blood cells, plasma, saliva, urine, stool (/.e., feces), tears, sweat, sebum, nipple aspirate, ductal lavage, tumour exudates, synovial fluid, ascitic fluid, peritoneal fluid, amniotic fluid, cerebrospinal fluid, lymph, fine needle aspirate, amniotic fluid, any other bodily fluid, cell lysates, cellular secretion products, inflammation fluid, semen and vaginal secretions. Samples may include tissue samples and biopsies, tissue homogenates and the like. Advantageous samples may include ones comprising any one or more biomarkers as taught herein in detectable quantities. Suitably, the sample is readily obtainable by minimally invasive methods, allowing the removal or isolation of the sample from the subject. In certain embodiments, the sample contains blood, especially peripheral blood, or a fraction or extract thereof. Typically, the sample comprises blood cells such as mature, immature or developing leukocytes, including lymphocytes, polymorphonuclear leukocytes, neutrophils, monocytes, reticulocytes, basophils, coelomocytes, hemocytes, eosinophils, megakaryocytes, macrophages, dendritic cells natural killer cells, or fraction of such cells (e.g., a nucleic acid or protein fraction). In specific embodiments, the sample comprises leukocytes including peripheral blood mononuclear cells (PBMC).

[0062] A “reference sample”, “reference cell”, “reference tissue”, “reference level”, “control sample”, “control cell”, “control tissue” or “control level”, as used herein, refers to a sample, cell, tissue, standard, or level that is used for comparison purposes. In one embodiment, a reference sample, reference cell, reference tissue, control sample, control cell, or control tissue is obtained from a healthy and/or non-diseased part of the body (e.g., tissue or cells) of the same subject or individual, but at different time-points, e.g. before and after therapy. In another embodiment, a reference sample, reference cell, reference tissue, control sample, control cell, or control tissue is obtained from a healthy individual who is not the subject or individual being assessed.

[0063] Various methodologies of the instant invention include a step that involves comparing a value, level, feature, characteristic, property, etc. to a “suitable control”, referred to interchangeably herein as an “appropriate control”, a “control sample”, or a “reference”. A “’’suitable control”, “appropriate control”, “control sample”, or a “reference” is any control or standard familiar to one of ordinary skill in the art useful for comparison purposes. In some embodiments, a “suitable control” or “appropriate control” is a value, level, feature, characteristic, property, etc., determined in a cell, tissue, or patient, e.g., a control cell, cell population, tissue, or patient, exhibiting, for example, a particular biomarker profile. A “suitable control” can be a pattern of levels/ratios of one or more biomarkers of the present invention that correlates to a particular biomarker profile, to which a cell sample can be compared. The cell sample can also be compared to a negative control. Such reference levels may also be tailored to specific techniques that are used to measure levels of biomarkers in biological samples (e.g., LC-MS, GC-MS, ELISA, PCR, etc.), where the levels of biomarkers may differ based on the specific technique that is used.

[0064] The terms “subject”, “patient”, “host” or “individual” used interchangeably herein, refer to any subject, particularly a vertebrate subject, and even more particularly a mammalian subject, for whom therapy or prophylaxis is desired. Suitable vertebrate animals that fall within the scope of the invention include, but are not restricted to, any member of the subphylum Chordata including primates (e.g., humans, monkeys and apes, and includes species of monkeys such from the genus Macaca (e.g., cynomologus monkeys such as Macaca fascicularis, and/or rhesus monkeys (Macaca mulatta)) and baboon (Papio ursinus), as well as marmosets (species from the genus Callithrix), squirrel monkeys (species from the genus Saimiri) and tamarins (species from the genus Saguinus), as well as species of apes such as chimpanzees (Pan troglodytes)), rodents (e.g., mice rats, guinea pigs), lagomorphs (e.g., rabbits, hares), bovines (e.g., cattle), ovines (e.g., sheep), caprines (e.g., goats), porcines (e.g., pigs), equines (e.g., horses), canines (e.g., dogs), felines (e.g., cats), avians (e.g., chickens, turkeys, ducks, geese, companion birds such as canaries, budgerigars etc.), marine mammals (e.g., dolphins, whales), reptiles (snakes, frogs, lizards etc.), and fish. A preferred subject is a human in need of eliciting an immune response, including an immune response with enhanced T- cell activation. However, it will be understood that the aforementioned terms do not imply that symptoms are present.

[0065] Each embodiment described herein is to be applied mutatis mutandis to each and every embodiment unless specifically stated otherwise.

2. Anti-ACE2 ^me Biomarker

[0066] ACE2 is a protein that may exist in transmembrane and soluble forms. The present invention discloses that different post-translational modifications of a lysine at position 31 of the ACE2 polypeptide sequence affect the ability of and ACE2 polypeptide to bind the SARS-CoV-2 spike protein. Moreover, ACE2 polypeptides with post-translational modifications of lysine 31 is associated with an increased resistance to a SARS-CoV-2 infection (e.g., a severe SARS-CoV-2 infection). [0067] A representative ACE2 polypeptide comprises the following amino acid sequence:

FNHEAEDLFYQSSLASWNYNTNITEENVQNMNNAGDKWSAFLKEQSTLAQMYPLQEI QNLTVK LQLQALQQNGSSVLSEDKSKRLNTILNTMSTIYSTGKVCNPDNPQECLLLEPGLNEIMAN SLDY NERLWAWESWRSEVGKQLRPLYEEYVVLKNEMARANHYEDYGDYWRGDYEVNGVDGYDYS RGQLIEDVEHTFEEIKPLYEHLHAYVRAKLMNAYPSYISPIGCLPAHLLGDMWGRFWTNL YSLT VPFGQKPNIDVTDAMVDQAWDAQRIFKEAEKFFVSVGLPNMTQGFWENSMLTDPGNVQKA V CHPTAWDLGKGDFRILMCTKVTMDDFLTAHHEMGHIQYDMAYAAQPFLLRNGANEGFHEA VG EIMSLSAATPKHLKSIGLLSPDFQEDNETEINFLLKQALTIVGTLPFTYMLEKWRWMVFK GEIPK DQWMKKWWEMKREIVGVVEPVPHDETYCDPASLFHVSNDYSFIRYYTRTLYQFQFQEALC QA AKHEGPLHKCDISNSTEAGQKLFNMLRLGKSEPWTLALENVVGAKNMNVRPLLNYFEPLF TWL KDQNKNSFVGWSTDWSPYADQSIKVRISLKSALGDKAYEWNDNEMYLFRSSVAYAMRQYF LK VKNQMILFGEEDVRVANLKPRISFNFFVTAPKNVSDIIPRTEVEKAIRMSRSRINDAFRL NDNSLE FLGIQPTLGPPNQPPVSIWLIVFGVVMGVIVVGIVILIFTGIRDRKKKNKARSGENPYAS IDISKGE NNPGFQNTDDVQTSF [SEQ ID NO: 1], wherein the lysine at position 31 (i.e., 31 K) is highlighted in bold typeface.

[0068] The present inventors have found that methylation (e.g., methylation of the lysine at position 31 of ACE2 (i.e., ACE2-31 K-Me)) was associated with a resistance to a SARS-CoV-2 infection. This methylated form of ACE2 tended to localize more to the intracellular compartments rather than the cell membrane.

[0069] Thus, in accordance with the present invention, ACE2-31 K-Me (“ACE2 ^me ”) can be employed as a biomarker for assessing the likelihood that a subject will be resistant to a severe coronavirus infection (e.g., a severe SARS-CoV-2 infection).

[0070] ACE2 polypeptides for the practice of the present invention can be obtained from any suitable ACE2 polypeptide containing patient samples, illustrative examples of which include an epithelial cell sample; or a PBMC sample. In some embodiments, the sample is obtained prior to treatment with a therapy (e.g., a SARS-CoV-2 vaccine). In other embodiments, the sample is obtained after treatment with a therapy (e.g., a SARS-Cov-2 vaccine). In some embodiments, the sample is whole blood. In some other preferred embodiments, the sample comprises lung bronchioles. In some other preferred embodiments, the sample comprises PBMCs.

[0071] In some embodiments of any of the methods, an elevated level refers to an overall increase of about any of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 95%, 96%, 97%, 98%, 99% or greater, in the level of biomarker (e.g., an ACE2 polypeptide), detected by standard art known methods such as those described herein, as compared to a reference sample, reference cell, reference tissue, control sample, control cell, or control tissue. In certain embodiments, an elevated level refers to the increase in level/amount of a biomarker in the sample wherein the increase is at least about any of 1 .5x, 1 ,75x, 2x, 3x, 4x, 5x, 6x, 7x, 8x, 9x, 10x, 25x, 50x, 75x, or 100x the level/amount of the respective biomarker in a reference sample, reference cell, reference tissue, control sample, control cell, or control tissue. In some embodiments, an elevated level refers to an overall increase of greater than about 1 .5-fold, about 1 .75-fold, about-2 fold, about 2.25-fold, about 2.5-fold, about 2.75-fold, about 3.0-fold, or about 3.25-fold as compared to a reference sample, reference cell, reference tissue, control sample, control cell, control tissue, or internal control (e.g., housekeeping gene).

[0072] In some embodiments of any of the methods, a reduced level refers to an overall reduction of about any of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 95%, 96%, 97%, 98%, 99% or greater, in the level of biomarker (e.g., protein or nucleic acid (e.g., gene or mRNA)), detected by standard art known methods such as those described herein, as compared to a reference sample, reference cell, reference tissue, control sample, control cell, or control tissue.

[0073] In certain embodiments, reduced level refers to a decrease in level/amount of a biomarker in the sample wherein the decrease is at least about any of 0.9x, 0.8x, 0.7x, 0.6x, 0.5x, 0.4x, 0.3x, 0.2x, 0.1 x, 0.05x, or 0.01 x the level/amount of the respective biomarker in a reference sample, reference cell, reference tissue, control sample, control cell, or control tissue.

[0074] Presence and/or level/amount of various biomarkers in a sample can be analysed by a number of methodologies, many of which are known in the art and understood by the skilled artisan, including, but not limited to, immunohistochemistry (“IHC”), Western blot analysis, immunoprecipitation, molecular binding assays, ELISA, ELIFA, fluorescence activated cell sorting (“FACS”), MassARRAY, proteomics, quantitative blood based assays (as for example Serum ELISA), biochemical enzymatic activity assays, in situ hybridization, Southern analysis, Northern analysis, whole genome sequencing, polymerase chain reaction (“PCR”) including quantitative real time PCR (“qRT-PCR”) and other amplification type detection methods, such as, for example, branched DNA, SISBA, TMA and the like), RNA-Seq, FISH, microarray analysis, gene expression profiling, and/or serial analysis of gene expression (“SAGE”), as well as any one of the wide variety of assays that can be performed by protein, gene, and/or tissue array analysis. Typical protocols for evaluating the status of genes and gene products are found, for example in Ausubel et al., eds., 1995, Current Protocols In Molecular Biology, Units 2 (Northern Blotting), 4 (Southern Blotting), 15 (Immunoblotting) and 18 (PCR Analysis). Multiplexed immunoassays such as those available from Rules Based Medicine or Meso Scale Discovery (“MSD”) may also be used.

[0075] In preferred embodiments, presence and/or level/amount is measured by observing protein levels. In certain embodiments, the method comprises contacting the biological sample (such as a sample from a patient at risk of being exposed to SARS-CoV-2) with an antigenbinding molecule (e.g., an antibody) specific for a response to therapy biomarker (e.g., ACE2 ^me ) under conditions permissive for binding of the biomarker(s), and detecting whether a complex is formed between the antigen-binding molecule or molecules and the biomarker(s). Such method may be an in vitro or in vivo method. In some embodiments, one or more anti-biomarker antigen-binding molecules are used to select subjects eligible for a therapy e.g., an SARS-CoV-2 vaccine.

[0076] In certain embodiments, the presence and/or expression level/amount of biomarker proteins in a sample is examined using immunohistochemistry (IHC) or immunofluorescence microscopy (IF) protocols. In some embodiments, the level of a response to therapy biomarker (e.g., ACE2 ^Me ) in a sample from an individual is an elevated level and, in further embodiments, is determined using IHC or IF. In one embodiment, the level of biomarker is determined using a method comprising: (a) performing IHC or IF analysis of a sample (such as a sample from a subject at risk of being exposed to SARS-CoV-2) with an antigen-binding molecule; and (b) determining the level of a biomarker in the sample. In some embodiments, IHC or IF staining intensity is determined relative to a reference. In some embodiments, the reference is a reference value. In some embodiments, the reference is a reference sample (e.g., a sample from subject known to be resistant to a severe SARS- CoV-2 infection or sample from a patient prior to having a severe SARS-CoV-2 infection).

[0077] In particular methods, the sample may be contacted with an antigen-binding molecule specific for said biomarker under conditions sufficient for a molecule-biomarker complex to form, and then detecting said complex. The presence of the biomarker may be detected in a number of ways, such as by microscopy (e.g., IF microscopy), Western blotting and ELISA procedures for assaying a wide variety of tissues and samples, including blood. A wide range of immunoassay techniques using such an assay format are available, see, e.g., U.S. Pat. Nos. 4,016,043, 4,424,279 and 4,018,653. These include both single-site and two-site or “sandwich” assays of the noncompetitive types, as well as in the traditional competitive binding assays. These assays also include direct binding of a labelled antibody to a target biomarker.

[0078] In certain embodiments, the samples are normalized for both differences in the amount of the biomarker assayed and variability in the quality of the samples used, and variability between assay runs. Such normalization may be accomplished by detecting and incorporating the expression of certain normalizing biomarkers.

[0079] In certain embodiments, a reference sample, reference cell, reference tissue, control sample, control cell, or control tissue is a single sample or combined multiple samples from the same subject or individual that are obtained at one or more different time points than when the test sample is obtained. For example, a reference sample, reference cell, reference tissue, control sample, control cell, or control tissue is obtained at an earlier time point from the same subject or individual than when the test sample is obtained. Such reference sample, reference cell, reference tissue, control sample, control cell, or control tissue may be useful if the reference sample is obtained before treatment and the test sample is later obtained after treatment.

[0080] In certain embodiments, a reference sample, reference cell, reference tissue, control sample, control cell, or control tissue is a combination of multiple samples from one or more healthy individuals who are not the subject or individual. In certain embodiments, a reference sample, reference cell, reference tissue, control sample, control cell, or control tissue is a combination of multiple samples from one or more individuals with a severe SARS-CoV-2 infection who are not the subject or individual.

[0081] In some embodiments, the sample is a clinical sample. In some embodiments, the sample is a liquid biopsy, such as blood. In some embodiments, the tissue sample is lung tissue.

[0082] In some embodiments, the methylation status biomarker is analysed in combination with at least one immune response biomarker. The at least one immune response biomarker is/are detected in the sample using a method selected from the group consisting of FACS, Western blot, ELISA, immunoprecipitation, immunohistochemistry, immunofluorescence, radioimmunoassay, dot blotting, immunodetection methods, HPLC, surface plasmon resonance (“SPR”), optical spectroscopy, mass spectrometry, HPLC, qPCR, RT-qPCR, multiplex qPCR or RT- qPCR, RNA-seq, microarray analysis, SAGE, MassARRAY technique, and FISH, and combinations thereof. In some embodiments, the at least one immune response biomarker is/are detected using FACS analysis or immunofluorescence microscopy. In some embodiments, the at least one response to therapy biomarker is detected in blood samples. In some embodiments, the at least one immune response biomarker is detected in bronchioles, epithelial cells, PBMCs, CD3+ cells, and/or monocytes. Any suitable method to isolate/enrich such population of cells may be used including, but not limited to, cell sorting.

[0083] In some embodiments, ACE2 ^me expression is elevated in samples from individuals that have an increased resistance to a SARS-CoV-2 infection. In some embodiments, ACE2 ^me expression is reduced in samples from individuals that are susceptible to a severe SARS-CoV-2 infection. In some particular examples, the ratio of biomarkers is assessed, e.g. the ratio of ACE2 ^me to ACE2 ^unmod , or vice versa.

[0084] In some embodiments, the expression level of one or more biomarkers may be compared to a reference which may include, for example, a sample comprising lung bronchioles, CD14+ cells, and/or CD3+ cells, a monocyte cell, a sample from a subject who does not have a severe SARS-CoV-2 infection, or a sample from a subject with severe SARS-CoV-2 infection but not receiving a therapy (e.g., an antiviral therapy). In some embodiments, a reference may include a reference value from multiple subjects or samples. A set of samples obtained from subjects having a shared characteristic (e.g., exposure to a common therapy (e.g., vaccine)) may be studied from a population, such as with a clinical outcome study. This set may be used to derive a reference (e.g., a reference number) to which a subject’s sample may be compared.

[0085] Certain aspects of the present disclosure relate to measurement of the expression level of one or more biomarkers (e.g., gene expression products including mRNAs and proteins) in a sample comprising ACE2 polypeptide. In some embodiments, the sample may be a peripheral blood sample (e.g., from a patient at risk of being exposed to SARS-CoV-2). In some embodiments, the sample may be processed to separate or isolate one or more cell types (e.g., CD3+ cells, CD14+ cells, and/or CD8 ⁺ /CD4 ⁺ T cells). In some embodiments, the sample may be used without separating or isolating cell types.

[0086] In some embodiments, the sample may be a peripheral blood sample. A peripheral blood sample may include white blood cells, PBMCs, and the like. Any technique known in the art for isolating leukocytes from a peripheral blood sample may be used. For example, a blood sample may be drawn, red blood cells may be lysed, and a white blood cell pellet may be isolated and used for the sample. In another example, density gradient separation may be used to separate leukocytes (e.g., PBMCs) from red blood cells. In some embodiments, a fresh peripheral blood sample (i.e., one that has not been prepared by the methods described above) may be used. In some embodiments, a peripheral blood sample may be prepared by incubation in a solution to preserve mRNA and/or protein integrity.

[0087] In some embodiments, a severe SARS-CoV-2 infection may refer the presence of any one or more of: an oxygen saturation of less than 94% on room air at sea level; a ratio of arterial partial pressure of oxygen to fraction of inspired oxygen (PaOz/FiOz) of less than 300 mm Hg; a respiratory rate of less than 30 breaths/min; lung infiltrates of greater than 50%;respiratory failure; septic shock; and or multiple organ dysfunction.

[0088] A disease or infection resistant subject may refer to a subject whose symptoms are mild or an asymptomatic subject. In this regard, subjects with an “asymptomatic infection” or “presymptomatic infection” include those who test positive for SARS-CoV-2 using a virologic test (i.e. , a nucleic acid amplification test or a rapid antigen test) but who have no symptoms that are consistent with Covid-19. Similarly, subjects with only mild illness include those who have any of the various signs and symptoms of Covid-19 (e.g., fever, cough, sore throat, malaise, headache, muscle pain, nausea, vomiting, diarrhea, loss of taste and smell) but who do not have shortness of breath, dyspnea, or abnormal chest imaging.

2.1 Biomarker panels

[0089] The biomarkers of the present invention can be used in predictive and/or prognostic tests to assess, determine, and/or qualify (used interchangeably herein) infection resistance status of a patient and therefore, direct treatment of the patient. The phrase “infection resistance status” includes a high resistance to infection signature (IR high) and a low resistance to infection signature (IR low). Based on this status, further procedures may be indicated, including additional tests or therapeutic procedures or regimens.

[0090] The resistance to infection signature panel suitably includes one or more additional biomarkers. For example, the resistance to infection signature may comprise ACE2 ^me , and CD14.

[0091] The power of an assay to correctly predict response to therapy is commonly measured as the sensitivity of the assay, the specificity of the assay or the area under a receiver operated characteristic (“ROC”) curve. Sensitivity is the percentage of true positives that are predicted by a test to be positive, while specificity is the percentage of true negatives that are predicted by a test to be negative. An ROC curve provides the sensitivity of a test as a function of 1 -specificity. The greater the area under the ROC curve, the more powerful the predictive value of the test. Other useful measures of the utility of a test are positive predictive value and negative predictive value. Positive predictive value is the percentage of people who test positive that are actually positive. Negative predictive value is the percentage of people who test negative that are actually negative.

[0092] In particular embodiments, the biomarker signatures of the present invention may show a statistical difference in different response to therapy statuses of at least p<0.05, p<10 ^-2 , p<10 ^-3 , p<10 ^-4 or p<10 ^-5 . Predictive or prognostic tests that use these biomarkers may show an ROC of at least 0.6, at least about 0.7, at least about 0.8, or at least about 0.9.

[0093] In certain embodiments, the biomarkers are measured in a patient sample using the methods described herein and an infection resistance signature status is calculated. In particular embodiments, the measurement(s) may then be compared with a relevant predictive or prognostic amount(s), cut-off(s), or multivariate model scores that distinguish a high infection resistance signature (IR high) status from a low infection resistance signature (IR low) status. The predictive or prognostic amount(s) represents a measured amount of a biomarker(s) above which or below which a patient is classified as having a particular infection resistance signature status. As is well understood in the art, by adjusting the particular predictive or prognostic cut-off(s) used in an assay, one can increase sensitivity or specificity of the assay depending on the preference of the skilled person. In particular embodiments, the particular predictive or prognostic cut-off can be determined, for example, by measuring the level or amount of biomarkers in a statistically significant number of samples from patients with different infection resistance signature statuses, and drawing the cut-off to suit the desired levels of specificity and sensitivity.

[0094] Furthermore, in certain embodiments, the values measured for biomarkers of a biomarker panel are mathematically combined and the combined value is correlated to the underlying predictive or prognostic question of high or low resistance to infection signature.

[0095] Biomarker values may be combined by any appropriate mathematical method known in the art. Well-known mathematical methods for correlating a biomarker combination to a disease status employ methods like discriminant analysis (DA) (e.g., linear-, quadratic-, regularized- DA), Discriminant Functional Analysis (DFA), Kernel Methods (e.g., SVM), Multidimensional Scaling (MDS), Nonparametric Methods (e.g., k-Nearest-Neighbour Classifiers), PLS (Partial Least Squares), Tree-Based Methods (e.g., Logic Regression, CART, Random Forest Methods, Boosting/Bagging Methods), Generalized Linear Models (e.g., Logistic Regression), Principal Components based Methods (e.g., SIMCA), Generalized Additive Models, Fuzzy Logic based Methods, Neural Networks and Genetic Algorithms based Methods. The skilled artisan will have no problem in selecting an appropriate method to evaluate a biomarker combination of the present invention. In some embodiments, the method used in a correlating a biomarker combination of the present invention is selected from DA (e.g., Linear-, Quadratic-, Regularized Discriminant Analysis), DFA, Kernel Methods (e.g., SVM), MDS, Nonparametric Methods (e.g., k-Nearest-Neighbour Classifiers), PLS (Partial Least Squares), Tree-Based Methods (e.g., Logic Regression, CART, Random Forest Methods, Boosting Methods), or Generalized Linear Models (e.g., Logistic Regression), and Principal Components Analysis. Details relating to these statistical methods are found in the following references: Ruczinski et al., J. of Computational and Graphical Statistics, 475-51 1 (2003); Friedman, J. H, J. of the American Statistical Association, 165-75 (1989); Hastie, Trevor, Tibshirani, Robert, Friedman, Jerome, The Elements of Statistical Learning, Springer Series in Statistics (2001 ); Breiman, L., Friedman, J.H, Olshen, R. A., Stone, C. J. Classification and regression trees, California : Wadsworth (1984); Breiman, L., Machine Learning 5-32 (2001 ); Pepe, M. S., The Statistical Evaluation of Medical Tests for Classification and Prediction, Oxford Statistical Science Series, 28 (2003); and Duda, R. 0., Hart, P. E., Stork, D. G., Pattern Classification, Wiley Interscience, 2nd Edition (2001 ).

3. Classification algorithms for qualifying resistance to infection status

[0096] In some embodiments, data that are generated using samples such as “known samples” can then be used to “train” a classification model. A “known sample” is a sample that has been pre-classified. The data that are used to form the classification model can be referred to as a “training data set”. The training data set that is used to form the classification model may comprise raw data or pre-processed data. Once trained, the classification model can recognize patterns in data generated using unknown samples. The classification model can then be used to classify the unknown samples into classes. This can be useful, for example, in predicting whether or not a particular biological sample is associated with a certain biological condition. [0097] Classification models can be formed using any suitable statistical classification or learning method that attempts to segregate bodies of data into classes based on objective parameters present in the data. Classification methods may be either supervised or unsupervised. Examples of supervised and unsupervised classification processes are described in Jain, “Statistical Pattern Recognition: A Review”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 22, No. 1 , January 2000, the teachings of which are incorporated by reference.

[0098] In supervised classification, training data containing examples of known categories are presented to a learning mechanism, which learns one or more sets of relationships that define each of the known classes. New data may then be applied to the learning mechanism, which then classifies the new data using the learned relationships. Examples of supervised classification processes include linear regression processes (e.g., multiple linear regression (MLR), partial least squares (PLS) regression and principal components regression (PCR)), binary decision trees (e.g., recursive partitioning processes such as CART), artificial neural networks such as back propagation networks, discriminant analyses (e.g., Bayesian classifier or Fischer analysis), logistic classifiers, and support vector classifiers (support vector machines).

[0099] Another supervised classification method is a recursive partitioning process. Recursive partitioning processes use recursive partitioning trees to classify data derived from unknown samples. Further details about recursive partitioning processes are provided in U.S. Patent Publication No. 2002/0138208 to Paulse et al., “Method for analysing mass spectra.”

[0100] In other embodiments, the classification models that are created can be formed using unsupervised learning methods. Unsupervised classification attempts to learn classifications based on similarities in the training data set, without pre-classifying the spectra from which the training data set was derived. Unsupervised learning methods include cluster analyses. A cluster analysis attempts to divide the data into “clusters” or groups that ideally should have members that are very similar to each other, and very dissimilar to members of other clusters. Similarity is then measured using some distance metric, which measures the distance between data items, and clusters together data items that are closer to each other. Clustering techniques include the MacQueen’s K-means algorithm and the Kohonen’s Self-Organizing Map algorithm.

[0101] Learning algorithms asserted for use in classifying biological information are described, for example, in PCT International Publication No. WO 01/31580 (Barnhill et al., titled “Methods and devices for identifying patterns in biological systems and methods of use thereof); and U.S. Patent Application Publication No. 2002/0193950 (Gavin et al., “Method or analyzing mass spectra”), U.S. Patent Application Publication No. 2003/0004402 (Hitt et al., “Process for discriminating between biological states based on hidden patterns from biological data”), and U.S. Patent Application Publication No. 2003/0055615 (Zhang and Zhang, “Systems and methods for processing biological expression data”).

[0102] The classification models can be formed on and used on any suitable digital computer. Suitable digital computers include micro, mini, or large computers using any standard or specialized operating system, such as a Unix, Windows® or Linux™ based operating system. In embodiments utilizing a mass spectrometer, the digital computer that is used may be physically separate from the mass spectrometer that is used to create the spectra of interest, or it may be coupled to the mass spectrometer.

[0103] The training data set and the classification models according to embodiments of the invention can be embodied by computer code that is executed or used by a digital computer. The computer code can be stored on any suitable computer readable media including optical or magnetic disks, sticks, tapes, etc., and can be written in any suitable computer programming language including R, C, C ⁺⁺ , visual basic, etc.

[0104] The learning algorithms described above are useful both for developing classification algorithms for the biomarkers already discovered, and for finding new biomarker biomarkers. The classification algorithms, in turn, form the base for diagnostic tests by providing diagnostic values (e.g., cut-off points) for biomarkers used singly or in combination.

[0105] In some embodiments any of the classification methods disclosed herein may be performed at least in part by one or more computers and/or may be stored in a database on a non- transitory computer medium. In some embodiments any of the classification methods disclosed herein may be embodied or stored at least in part on a computer-readable medium having computerexecutable instructions thereon. In some embodiments a computer-readable medium comprises any non-transitory and/or tangible computer-readable medium.

4. Antibodies and cell lines

[0106] The present invention discloses the localization, detection and quantitation of resistance to infection biomarkers, particularly ACE2-31 K-Me, using antigen-binding molecules that bind specifically to these biomarkers. Such antigen binding molecules are typically isolated methylation site-specific antigen-biding molecules that bind specifically to ACE2 only when 31 K is methylated. Such antigen-binding molecules may be produced by standard antibody production methods, such as anti-peptide antibody methods, using the methylation site sequence information provided herein, and as described for example in the Examples. For example, an antibody that binds specifically to ACE2-31 K-Me, can be produced by immunizing an animal with a peptide antigen comprising all or part of the amino acid sequence encompassing the respective methylated residue (e.g., a peptide antigen comprising the sequence set forth in SEQ ID NO: 2 (which encompasses the methylated lysine at position 31 of ACE2 to produce an antibody that only binds ACE2 when methylated at position 31 K.

[0107] Polyclonal antibodies of the invention may be produced according to standard techniques by immunizing a suitable animal (e.g., rabbit, goat, etc.) with a peptide antigen corresponding to the protein methylation site of interest, collecting immune serum from the animal, and separating the polyclonal antibodies from the immune serum, in accordance with standard procedures. For example, if an antibody that only binds ACE2 when methylated at 31 K is desired, the peptide antigen includes the methylated form of lysine (e.g., K(Me) or K(Me2)). Conversely, if an antibody that only binds ACE2 when not methylated at 31 K is desired, the peptide antigen includes the non-methylated, conventional form of lysine.

[0108] Peptide antigens suitable for producing antibodies of the invention may be designed, constructed and employed in accordance with well-known techniques (see, for example, Antibodies: A Laboratory Manual, Chapter 5, p. 75-76, Harlow & Lane Eds., Cold Spring Harbor Laboratory (1988); Czernik, Methods In Enzymology, 201 : 264-283 (1991 ); Merrifield, J. Am. Chem. Soc. 85:21 -49 (1962)).

[0109] It will be appreciated by those of skill in the art that longer or shorter methylpeptide antigens may be employed. For example, a peptide antigen may comprise an amino acid sequence set forth in SEQ ID NO: 2, or it may comprise additional amino acids flanking that sequence, or may comprise only a portion of the disclosed sequence immediately flanking the methylatable lysine. Typically, a desirable peptide antigen will comprise four or more amino acids flanking each side of the methylatable amino acid and encompassing it. Polyclonal antibodies produced as described herein may be screened as further described below.

[0110] In some preferred embodiments, the antibody does not bind to a protein or peptide that contains an un-methylated lysine residue at the position corresponding to lysine 31 of the full length ACE2 polypeptide (e.g., as set forth in SEQ ID NO: 1 ).

[0111] Monoclonal antibodies of the invention may be produced in a hybridoma cell line according to the well-known technique of Kohler and Milstein. See Nature 265:495-97 (1975); Kohler and Milstein, Eur. J. Immunol. 6: 511 (1976); see also, Current Protocols in Molecular Biology, Ausubel et al. Eds. (1989). Monoclonal antibodies so produced are highly specific, and improve the selectivity and specificity of diagnostic assay methods provided by the invention. For example, a solution containing the appropriate antigen may be injected into a mouse or other species and, after a sufficient time (in keeping with conventional techniques), the animal is sacrificed and spleen cells obtained. The spleen cells are then immortalized by fusing them with myeloma cells, typically in the presence of polyethylene glycol, to produce hybridoma cells. Rabbit fusion hybridomas, for example, may be produced as described in U.S. Patent No. 5,675,063, to Knight. The hybridoma cells are then grown in a suitable selection media, such as hypoxanthine-aminopterin-thymidine (HAT), and the supernatant screened for monoclonal antibodies having the desired specificity, as described below. The secreted antibody may be recovered from tissue culture supernatant by conventional methods such as precipitation, ion exchange or affinity chromatography, or the like.

[0112] Monoclonal Fab fragments may also be produced in Escherichia coli by recombinant techniques known to those skilled in the art (see, for example, W. Huse, Science 246: 1275-81 (1989); Mullinax et al., Proc. Nat'l Acad. Sci. 87: 8095 (1990)). If monoclonal antibodies of one isotype are preferred for a particular application, particular isotypes can be prepared directly, by selecting from the initial fusion, or prepared secondarily, from a parental hybridoma secreting a monoclonal antibody of different isotype by using the sib selection technique to isolate class-switch variants (Steplewski, et al., Proc. Nat'l. Acad. Sci., 82: 8653 (1985); Spira et al., J. Immunol. Methods, 74: 307 (1984)).

[0113] The preferred epitope of a methylation-site specific antibody of the invention is a peptide fragment consisting essentially of about 8 to 17 amino acids including the methylatable lysine, wherein about 3 to 8 amino acids are positioned on each side of the methylatable lysine. Antibodies of the invention thus specifically bind to a post-translationally modified ACE2 polypeptide comprising such epitopic sequence. Particularly preferred epitopes bound by the antibodies of the invention comprise all or part of a methylatable site sequence, including the methylatable amino acid.

[0114] Included within the scope of the present invention are equivalent non-antibody molecules, such as antigen-binding fragments, which bind, in a methyl-specific manner, to essentially the same methylatable epitope to which the or methyl-specific antigen-binding molecules of the invention bind (see, for example, Neuberger et al., Nature, 312: 604 (1984)). Such equivalent nonantibody reagents may be suitably employed in the methods of the invention further described below.

[0115] Antigen-binding molecules contemplated by the invention may be any type of antibody including immunoglobulins, including IgG, IgM, IgA, IgD, and IgE, and antigen-binding fragments thereof. The antibodies may be monoclonal or polyclonal and may be of any species of origin, including (for example) mouse, rat, rabbit, horse, or human, or may be chimeric antibodies (see, for example, M. Walker et al., Molec. Immunol. 26: 403-11 (1989); Morrision et al., Proc. Nat'l. Acad. Sci. 81 : 6851 (1984); Neuberger et al., Nature 312:604 (1984)). The antibodies may be recombinant monoclonal antibodies produced according to the methods disclosed in U.S. Patend No. 4,474,893 (Reading) or U.S. Patent No. 4,816,567 (Cabilly et al.) The antibodies may also be chemically constructed by specific antibodies made according to the method disclosed in U.S. Patent No. 4,676,980 (Segel et al.).

[0116] The invention also provides immortalized cell lines that produce an antibody of the invention. For example, hybridoma clones, constructed as described above, that produce monoclonal antibodies to the ACE2 methylation site disclosed herein are also provided. Similarly, the invention includes recombinant cells producing an antibody of the invention, which cells may be constructed by well-known techniques. For example, the antigen combining site of the monoclonal antibody can be cloned by PCR and single-chain antibodies produced as phage-displayed recombinant antibodies or soluble antibodies in E. coll (see, e.g., Antibody Engineering Protocols, 1995, Humana Press, Sudhir Paul editor.)

[0117] Methylation site-specific antibodies of the invention, whether polyclonal or monoclonal, may be screened for epitope and methyl-specificity according to standard techniques (see, for example, Czemik et al., Methods in Enzymology, 201 : 264-283 (1991 )). For example, the antibodies may be screened against the methyl and non-methyl peptide by ELISA to ensure specificity for both the desired antigen and for reactivity only with the methylated (or non-methylated) form of the antigen. Peptide competition assays may be carried out to confirm lack of reactivity with other methylepitopes on the given protein methylation signalling protein. The antibodies may also be tested by Western blotting against cell preparations containing the signalling protein, e.g., cell lines overexpressing the target protein, to confirm reactivity with the desired methylated epitope/target.

[0118] Specificity against the desired methylated epitope may also be examined by constructing mutants lacking methylatable residues at positions outside the desired epitope that are known to be methylated, or by mutating the desired methyl epitope and confirming lack of reactivity. Methylation-site specific antigen binding molecules of the invention may exhibit some limited crossreactivity to related epitopes in non-target proteins. This is not unexpected as most antigen-binding molecules exhibit some degree of cross-reactivity, and anti-peptide antibodies will often cross-react with epitopes having high homology to the immunizing peptide (see, e.g., Czemik, supra). Crossreactivity with non-target proteins is readily characterized by Western blotting alongside markers of known molecular weight. Amino acid sequences of cross-reacting proteins may be examined to identify sites highly homologous to the ACE2 epitope for which the antigen-binding molecules of the invention are specific.

[0119] In certain cases, polyclonal antisera may exhibit some undesirable general crossreactivity to methyl-lysine (suitably, dimethyl lysine) itself, which may be removed by further purification of antisera, e.g., over a methyltyramine column. Antigen-binding molecules of the invention specifically bind ACE2 only when methylated (or only when not methylated, as the case may be) at 31 K.

[0120] Antigen-binding molecules may be advantageously conjugated to fluorescent dyes (e.g., Alexa Fluor 488) for use in multi-parametric analyses.

[0121] Methylation-site specific antigen-binding molecules of the invention specifically bind to human ACE2 polypeptide, only when methylated at 31 K, but are not limited only to binding the human species, perse. The invention includes antigen-binding molecules that also bind conserved and highly homologous or identical methylation sites in respective ACE2 proteins from other species (e.g., mouse, rat, monkey, yeast), in addition to binding the human methylation site. Highly homologous or identical sites conserved in other species can readily be identified by standard sequence comparisons, such as using BLAST, with the human ACE2 methylation site disclosed herein.

5. Patient classification and treatment management

[0122] present invention extends to methods of selecting or identifying individuals who are appropriate candidates for treatment with a therapy (e.g., a SARS-CoV-2 vaccine therapy) for treatment or prevention of a SARS-CoV-2 infection. Such individuals include patients that are predicted to be susceptible to a sever SARS-CoV-2 infection and thus have an increased likelihood of benefiting from administration of the therapy relative to other patients having different characteristic(s) (e.g., those that are already resistant to a severe SARS-CoV-2 infection). In certain embodiments an appropriate candidate is one who is reasonably likely to benefit from treatment or prevention or at least sufficiently likely to benefit as to justify administering the treatment in view of its risks and side effects. The invention also encompasses methods of selecting or identifying individuals who are not appropriate candidates for treatment with a therapy (e.g., a vaccine) for treatment or prevention of a SARS-CoV-2 infection. Such individuals include patients that are predicted to be non-resistant to developing a severe SARS-CoV-2 infection and thus have a decreased likelihood of benefiting from administration of the therapy relative to other patients having different characteristic(s) (e.g., likelihood or risk of developing a severe SARS-CoV-2 infection), or a low or substantially no likelihood of benefiting from such treatment. In some embodiments, whether a subject is an appropriate candidate for therapy (i.e. , treatment or prevention) is determined based on an assay of at least one infection resistance biomarker in a sample obtained from the subject.

[0123] In some aspects, described herein are methods of identifying and/or selecting a subject to receive a SARS-CoV-2 therapy to treat or prevent a severe infection. In specific embodiments, the therapy is an immunotherapy, suitably with an anti-immune checkpoint inhibitor. The phrase “SARS-CoV-2 therapy”, encompasses embodiments pertaining to treatment with a single therapeutic agent and embodiments pertaining to treatment with two or more therapeutic agents in combination.

[0124] The present invention also encompasses the use of methods for assessing ACE2 methylation status of a subject described herein in methods of selecting or identifying individuals with impaired or reduced resistance to a severe SARS-CoV-2.

6. Kits

[0125] The present invention also extends to kits for determining expression of biomarkers, including the infection resistance biomarker(s) and other biomarkers disclosed herein, which include reagents that allow detection and/or quantification of the biomarkers. Such reagents include, for example, compounds or materials, or sets of compounds or materials, which allow quantification of the biomarkers. In specific embodiments, the compounds, materials or sets of compounds or materials permit determining the expression level of a protein or the expression level of a gene, including without limitation, antigen-binding molecules (e.g., antibodies), material for extraction of RNA, primers for the synthesis of a corresponding cDNA, primers for amplification of DNA, and/or probes capable of specifically hybridizing with the RNAs (or the corresponding cDNAs) encoded by the genes, TaqMan probes, etc.

[0126] The kits may also optionally include appropriate reagents for detection of labels, positive and negative controls, washing solutions, blotting membranes, microtiter plates, dilution buffers and the like. For example, a protein-based detection kit may include (i) at least one ACE2 polypeptide, which is suitably selected from ACE2-31 K-Me, or a fragments thereof that comprises 31 K-Me, and an ACE2 polypeptide that is not methylated (which may be used as a control), and (ii) one or more antigen-binding molecules that bind specifically to an ACE2 polypeptide (e.g., ACE2-31 K- Me, and/or an ACE2 polypeptide that is not methylated). The antigen-binding molecules are suitably detectably labeled. The kit can also feature various devices (e.g., one or more) and reagents (e.g., one or more) for performing one of the assays described herein; and/or printed instructional material for using the kit to quantify the expression of an infection resistance biomarker gene.

[0127] Materials suitable for packing the components of the diagnostic kits may include crystal, plastic (polyethylene, polypropylene, polycarbonate and the like), bottles, vials, paper, envelopes and the like. Additionally, the kits of the invention can contain instructional material for the simultaneous, sequential or separate use of the different components contained in the kit. The instructional material can be in the form of printed material or in the form of an electronic support capable of storing instructions such that they can be read by a subject, such as electronic storage media (magnetic disks, tapes and the like), optical media (CD-ROM, DVD) and the like.

[0128] Alternatively or in addition, the media can contain Internet addresses that provide the instructional material.

[0129] In order that the invention may be readily understood and put into practical effect, particular preferred embodiments will now be described by way of the following non-limiting examples. EXAMPLE 1

ACE2 ^ME ANTIBODY SPECIFICALLY TARGETS ACE2 METHYLATION AT LYSINE 31

[0130] The antibody developed by the present inventors is demonstrated to be specific for ACE2 polypeptide that is methylated at lysine 31 . No significant background or off-target binding is observed. Immunoprecipitation data using the global ACE2 antibody in Caco2 cell lysates followed by immunoblotting with ACE2 ^me antibody was performed to confirm specificity. As expected, ACE2 ^me was detected by immunoblotting in ACE2 pull downs from Caco2 cells (Figure 1 A).

[0131] ELISA results are depicted in Table 1 , showing specificity of the antibodies to their targets with appropriate blank/negative controls demonstrating no signals.

TABLE 1

ELISA RESULTS DEMONSTRATING SPECIFICITY OF THE POLYCLONAL ANTIBODIES

[0132] These data clearly show that the specificity of the custom antibodies designed for the ACE2 methylation motif with either no methylation or with the QAKTFLD(K ^me )FNHEAED [SEQ ID NO: 2] methylation motif. Rabbits 1 and 2 were used to raise antibodies against the modified peptide and also generated the non-methyl antibodies as well via affinity purification. These ELISA data clearly indicate that the antibodies raised against the methylated forms of ACE2 are specific only for the specific methylation and do not recognize or bind to the unmodified peptide (which also functions as a negative control for the specificity of the antibodies).

[0133] These results also show the optimisation and negative controls for our polyclonal ACE2 ^me antibody, showing the optimized staining (ACE2 ^me ), and the two negative controls to show that the staining is specific for the primary polyclonal antibody (Secondary Antibody only or Primary AB only) (Figure 1 C, D). The staining was carried out in Caco-2 cells. Based on these data, the present inventors then probed in Caco-2 cells infected with SARS-CoV-2 virus at a MOI of either 0.1 or 1 .0. We found that in highly infected cells (MOI of 1 .0) that was significantly less ACE2 ^me and there was significantly more unmodified ACE2 in the nucleus of the infected Caco-2 cells. Indicating that ACE2 ^me was downregulated by successful infection and nuclear expression of ACE2 ^me upregulated by the same.

Materials & Methods Custom polyclonal antibody generation

[0134] Custom polyclonal rabbit antibodies against ACE2 target sequence QAKTFLD(K ^me )FNHEAED were generated by MIMOTOPES™. Briefly, for antibody generation, a cysteine was incorporated at the C-terminus of the peptide (peptide sequence CQAKTFLD(K ^me )FNHEAED) and reacted to conjugate the peptide to an immunogenic carrier protein Keyhole Limpet Hemocyanin (KLH). No special immunization protocols were required to generate antimethylated peptide antibodies. Rabbits were immunized several weeks apart. The first immunization was with an emulsion of the peptide conjugate with complete Freund’s adjuvant, the second using incomplete Freund’s adjuvant. Potent anti-peptide sera were obtained after several weeks. Methylated/unmodified-peptide antisera were conveniently tested using an enzyme-linked immunosorbent assay (ELISA), where the sera were titrated on microtitre plates coated with non- methylated-peptide and methylated-peptides. For methylated peptide antibody enhancement, the nonmethylated analogue of the peptide used for the immunization was coupled to a gel Sulfo Link (Thermo Fisher Scientific 20401 :05273) using the available cysteine residue following the manufacturer’s instructions. The resultant gel was incubated with aliquots of the antisera to absorb antibodies specific to the non-methylated peptide. The resultant antiserum had enhanced specificity for the methylated peptide sequence. To produce affinity purified antibodies specific to the methylated peptide only, it was necessary to first perform enhancement to remove antibodies from the serum to the non-methylated peptide. Specificity of the affinity purified antibodies was tested by ELISA back onto both the non-methylated and the methylated peptides coated onto the plate.

ELISA

[0135] Testing for methylated peptide is performed using an enzyme linked immunosorbent assay (ELISA). Briefly, the sera are titrated on microtiter plates coated with non- methylated-peptide and methylated-peptide and resultant antibodies are screen against the unmodified (non-methylated) or modified (methylated) peptides with a blank (negative control).

Immunofluorescent Imaging

[0136] Protein targets were localized by digital pathology laser scanning microscopy. Single 0.5 pm sections were obtained using an ASI Digital pathology characterization of both the fluorescent intensity as per normal immunofluorescent imaging as well as the ability to count the population of cells positive or negative for antibodies, allow population dynamics to be investigation using powerful custom designed algorithms and automated stage. This also allows the imaging and counting of large cell numbers for statistical power) microscope using either a 20x dry or a 100x oil immersion lens running ASI software. The final image was obtained by averaging four sequential images of the same section. Digital images were analyzed using automated ASI software as described previously (Applied Spectral Imaging, Carlsbad, CA) to determine the distribution and intensities automatically with automatic thresholding and background correction of the average nuclear fluorescence intensity (N Fl), allowing for the specific targeting of expression of proteins of interest. Digital images were also analyzed using Imaged software (Imaged, NIH, Bethesda, MD, USA) to determine the total cell fluorescence or cell surface only fluorescence for non-permeabilized cells. Imaged software with automatic thresholding and manual selection of regions of interest (ROIs) was used to calculate the Pearson’s co-efficient correlation (PCC) for each pair of antibodies. PCC values range from: -1 = inverse of co-localization, 0 = no co-localization, +1 = perfect co-localization. The Mann-Whitney nonparametric test was used to determine significant differences between datasets.

[0137] Appropriate controls were used for all experiments including no antibody controls, primary only, or secondary only controls in both tissue and cell imaging. Appropriate controls were used for custom antibody validation (see, Figure 1 B).

EXAMPLE 2

BRONCHIAL EPITHELIAL CELL ACE2 METHYLATION ACE2 METHYLATION INVERSELY CORRELATES TO SARS-COV-2-INFECTED CELLS

[0138] Analysis of population dynamics showed significantly increased expression of cytoplasmic ACE2 ^me on day 5 as compared to day 2 (Figure 2A,B). However, while there was also an increase in total positive cells for ACE2 ^me , this was not significant (Figure 2B). Interestingly, there was a significant influx of CD3+ cells of which more than 50% were positive for ACE2 ^me on day 5 (Figure 2C).

[0139] SARS-CoV-2 positive expression and spike protein expression significantly reduced on day 5 as compared to day 2 (Figure 2D). The present inventors also noted that ACE2 expression was higher in areas without SARS-CoV-2 positive cells. This suggests a possible correlation between higher ACE2 ^me expression and no viral infection

Materials & Methods

Hamster studies

[0140] Female golden Syrian hamsters (6-8 weeks) were obtained from Janiver Labs (Le Genest-Saint-lsle, France) and studies conducted by ONCODESIGN® Biotechnology (Dijon Cedex, France). Animal viability, behaviour and rectal temperature were recorded every two hours over a six hour period post-administration and body weights were measured daily. For all biomarker studies, hamsters were SARS-Cov-2 infected on day 0 (104 PFU; intranasal (IN) administration) with the SARS-CoV-2 strain “Slovakia/SK-BMC5/2020”, originally provided by the European Virus Archive global. All procedures on golden Syrian hamsters were submitted to the Institutional Animal Care and Use Committee of CEA approved by French authorities.

Immunofluorescence

[0141] IFA imaging and analysis was carried out using previously established and optimized protocols. Cells were fixed with formaldehyde (3.7%) and then immuno-stained with antibodies targeting the SARS-CoV-2 viral spike, custom antibodies ACE2 ^me , ACE2 ^unmod . Cells were permeabilized by incubating with 0.5% Triton X-100 for 15 min, blocked with 1 % BSA in PBS, and were probed with primary antibodies followed by visualization with secondary donkey anti-rabbit, mouse, or goat antibodies conjugated to Alexa Fluor 488, 568, or 647. Coverslips were mounted on glass microscope slides with ProLong Glass Antifade reagent (Life Technologies, Carlsbad, CA). Protein targets were localized by digital pathology laser scanning microscopy. Single 0.5 pm sections were obtained using an ASI Digital pathology (ASI Digital pathology is characterization of both the fluorescent intensity as per normal immunofluorescent imaging as well as the ability to count the population of cells positive or negative for antibodies, allow population dynamics to be investigation using powerful custom designed algorithms and automated stage. This also allows the imaging and counting of large cell numbers for statistical power) microscope using a 100x oil immersion lens running ASI software. The final image was obtained by averaging four sequential images of the same section. Digital images were analyzed using automated ASI software as described previously (Applied Spectral Imaging, Carlsbad, CA) to determine the distribution and intensities automatically with automatic thresholding and background correction of the average nuclear fluorescence intensity (N Fl), allowing for the specific targeting of expression of proteins of interest. Digital images were also analyzed using ImageJ software (Imaged, NIH, Bethesda, MD, USA) to determine the total cell fluorescence or cell surface only fluorescence for non-permeabilized cells. Appropriate controls were used for all experiments including no antibody controls, primary only, or secondary only controls.

[0142] Opal Tyramide staining, unlike traditional IFA allows the use of antibodies from the same host species. Imaging and analysis was carried out using previously established and optimized protocols for permeabilization and antigen retrieval. All FFPE sections were stained with Opal Tyramide staining. Samples were dewaxed using a decloaking chamber and were prepared using either 0.1 % Triton X-100 20 min, Biocare Medical Denaturing Solution, or Dako pH6.0/pH 9.0 for antigen retrieval. Sniper+BSA was used for blocking (10 minutes). Primary antibodies employed include CD3, perforin, SARS-CoV-2 spike and custom antibody ACE2 ^me with VGY or DVG buffers. Primary antibodies were detected with MACH2 HRP secondary with Opal fluorochromes 520, 570 or 650. Imaging and analysis was then carried out as per Immunofluorescent staining and analysis described above using the ASI Digital Pathology platform for automated counting and intensity analysis.

EXAMPLE 3

ACE2 EXPRESSION ON PBMCS OF VACCINATED OR COVID19 PATIENTS

[0143] Using the custom ACE2 ^me antibody the present inventors examined the expression profile of ACE2 ^me in patients infected with Covid-19, and how the expression profile correlates to disease severity.

[0144] ACE2 ^me was significantly reduced in expression in more severe disease and higher in milder disease (see, Figure 3A). The percentage cells that were positive for ACE2 ^me were also higher in milder disease.

[0145] The present inventors observed an increased level of ACE2 ^Me in cells showing enhanced resistance to infection, and more ACE2 ^unmod in the nucleus of CaCo2 cells that were more susceptible to infection (see, Figure 1 C, D).

[0146] A similar profile was observed in patients vaccinated for Covid-19, insofar as there was a significant increase in the total cells positive for ACE2 ^me and a significant increase in the overall expression per a cell for post-vaccinated patients (see, Figure 3B).

[0147] Strikingly, comparing uninfected and infected (convalescent) patients post vaccination demonstrated a significantly lower population of cells positive for ACE2 ^me in the infected (convalescent) patients (data not shown). Moreover, the overall expression of ACE2 in each cell was strikingly and significantly higher in the infected (convalescent) cohort (Figure 3C).

[0148] Comparing ACE2 ^me dynamics in two mild and one severe infected (i.e., convalescent) patient PBMCs pre and post vaccination clearly demonstrates an increase in the overall positive cells for the severe patient. However, overall in all three patients a significant increase in the cellular expression of ACE2 ^me was observed.

[0149] Finally, we examined SARS-CoV-2 spike and ACE2 ^me expression profiles in PBMCs derived from two (P008, P01 1 ) vaccinated patients who subsequently developed and recovered from COVID-19 (Figure 3E). CD14+ACE2 ^me expression was significantly decreased in PBMCs derived from post-infection (PI) patients compared with post-booster (PB) patients (Figure 3E, 3F). Furthermore, IL-6 expression was significantly higher in the monocytes after COVID-19 recovery (Figure 3F). In vitro NACE2i treatment significantly induces ACE2 ^me expression and decreased IL-6 expression in CD14+ monocytes. Strikingly, spike protein expression was also significantly reduced in CD14+ cells following NACE2i treatment (Figure 3F). This suggests that there is a virus reservoir in CD14+ monocytes/macrophages and that ACE2 ^me expression in CD14+ cells is a potential protective signature correlating with neutralizing antibodies targeting SARS-CoV-2 and a reduced reservoir of SARS-CoV-2 spike protein expression.

[0150] Overall, ACE2 ^me is abrogated in severe Covid-19 infection, whereas postconvalescent patients had enriched ACE2 ^me expression despite lower overall positive cells. ACE2 ^me was also increased in mild disease, as measured by both expression and population of positive cells. Vaccination induced a trend of increased expression of ACE2 ^me in addition in an increase in positive cells. Overall, these data indicate that ACE2 ^me is linked to reduced disease severity and recovery from Covid-19, indicating a protective signature.

EXAMPLE 3

SARS-CoV-2 VACCINATION ENRICHES ACE2 ^ME IN PBMC

[0151] The present inventors next sought We next established whether there was correlation between expression of ACE2 ^me and neutralizing antibodies targeting SARS-CoV-2 after vaccination. In PBMCs isolated from individuals vaccinated for COVID-19 (Figure 4A), there was a significant increase in ACE2 ^me expression in PBMCs and CD14+ monocytes post-vaccination (Figure 4B). In PBMCs, in 1 1 out of 13 individuals, ACE2 ^me and neutralizing antibody titers against the parental strain were positively correlated, with ten individuals demonstrating increased ACE2 ^me and neutralizing antibody titers and one individual showing only minor changes in both (Figure 4C). The other two individuals demonstrated a decrease in ACE2 ^me and only a moderate increase in neutralizing antibody titers (Figure 4C). An almost identical pattern was observed for antibodies targeting the delta strain of SARS-CoV-2 (Figure 4B, 4C). Strikingly, CD14+ cells isolated from donor PBMCs demonstrated much higher expression of ACE2 ^me post vaccination than bulk PBMCs (Figure 4B). In CD14+ cells, 12 of out 13 individuals had a positive correlation between increased ACE2 ^me (more highly expressed than bulk PBMCs) and the neutralizing antibody titers (Figure 4C).

Materials & Methods ACE2 plasmid transfections

[0152] Briefly, ACE2_WT or ACE2 K31 A mutant sequences were cloned into the pTracer-CMV vector in frame with a C-terminal HA tag. MRC5 cells were transfected with either vector only (VO) plasmid, ACE2_WT, or ACE2 K31 A (lysine to alanine mutation at position 31 ) mutant plasmids using the Lipofectamine 2000 Transfection System Kit according to the manufacturer’s instructions (Thermo Fisher Scientific; 1 1668019). Cells were then subsequently fixed and stained for ACE2 or ACE2 ^me .

Immunofluorescence

[0153] Immunofluorescence imaging and analysis were carried out using previously established and optimized protocols. Cells were fixed with formaldehyde (3.7%) and then immune- stained with antibodies targeting the custom antibodies of ACE2 ^me and ACE2 ^unmod . Cells were permeabilized by incubating with 0.5% Triton X-100 for 15 min, blocked with 1 % bovine serum albumin in PBS, and probed with primary antibodies followed by visualization with secondary donkey anti-rabbit, mouse, or goat antibodies conjugated to Alexa Fluor 488, 568, or 647. Coverslips were mounted on glass microscope slides with Prolong Glass Antifade reagent (Life Technologies). ASI Digital Pathology characterizes both the fluorescence intensity, similar to normal immunofluorescent imaging protocols, but also provides the ability to count the population of immunopositive or immunonegative cells. Digital images were also analyzed using Imaged software (Imaged, NIH, Bethesda, MD) to determine the total cell fluorescence or cell surface only fluorescence for non- permeabilized cells. Appropriate controls were used for all experiments including primary only control, secondary only control, and ACE2 ^me blocking peptide control.

EXAMPLE 4

FURTHER VALIDATION OF ACE2 ^ME ANTIBODY SPECIFICITY

[0154] MRC5 cells are resistant to SARS-CoV-2 infection due to a lack of ACE2 expression. The present inventors then sought to further validate the specificity of the custom ACE2 ^me antibody by mutant transfection studies in MRC5 cells lacking ACE2 protein. Transfection of ACE2 (ACE2_WT: can be methylated) and ACE2 mutant (ACE2 K31 A: lysine to alanine mutation at position 31 that cannot be methylated) into MRC5 cells (Figure 6A) and immunofluorescence analysis clearly demonstrate that the ACE2 ^me antibody only detects ACE2_WT but not ACE2 K31 A mutant (Figure 16B). In comparison, the global ACE2 antibody detects both wild-type and mutant transfected samples.

Summary

[0155] There appears to be a correlation between significant induction of ACE2 ^me signal and increased neutralizing antibody titres against SARS-CoV-2. This indicates a potential epigenetic mediated mechanism of protection linked to the generation of the spike peptide by the mRNA vaccine (Pfizer or Astra-Zeneca). [0156] The disclosure of every patent, patent application, and publication cited herein is hereby incorporated herein by reference in its entirety.

[0100] The citation of any reference herein should not be construed as an admission that such reference is available as “Prior Art” to the instant application.

[0101] Throughout the specification the aim has been to describe the preferred embodiments of the invention without limiting the invention to any one embodiment or specific collection of features. Those of skill in the art will therefore appreciate that, in light of the instant disclosure, various modifications and changes can be made in the particular embodiments exemplified without departing from the scope of the present invention. All such modifications and changes are intended to be included within the scope of the appended claims.