WO2024020646A1 - Biomarqueur de méthylation pour la résistance à une infection - Google Patents

Biomarqueur de méthylation pour la résistance à une infection Download PDF

Info

Publication number
WO2024020646A1
WO2024020646A1 PCT/AU2023/050698 AU2023050698W WO2024020646A1 WO 2024020646 A1 WO2024020646 A1 WO 2024020646A1 AU 2023050698 W AU2023050698 W AU 2023050698W WO 2024020646 A1 WO2024020646 A1 WO 2024020646A1
Authority
WO
WIPO (PCT)
Prior art keywords
ace2
antibody
sample
amino acid
subject
Prior art date
Application number
PCT/AU2023/050698
Other languages
English (en)
Inventor
Sudha RAO
Original Assignee
The Council Of The Queensland Institute Of Medical Research
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from AU2022902106A external-priority patent/AU2022902106A0/en
Application filed by The Council Of The Queensland Institute Of Medical Research filed Critical The Council Of The Queensland Institute Of Medical Research
Publication of WO2024020646A1 publication Critical patent/WO2024020646A1/fr

Links

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/573—Immunoassay; Biospecific binding assay; Materials therefor for enzymes or isoenzymes
    • C—CHEMISTRY; METALLURGY
    • C07—ORGANIC CHEMISTRY
    • C07K—PEPTIDES
    • C07K16/00—Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies
    • C07K16/40—Immunoglobulins [IGs], e.g. monoclonal or polyclonal antibodies against enzymes
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/569—Immunoassay; Biospecific binding assay; Materials therefor for microorganisms, e.g. protozoa, bacteria, viruses
    • G01N33/56983—Viruses
    • C—CHEMISTRY; METALLURGY
    • C07—ORGANIC CHEMISTRY
    • C07K—PEPTIDES
    • C07K2317/00—Immunoglobulins specific features
    • C07K2317/30—Immunoglobulins specific features characterized by aspects of specificity or valency
    • C07K2317/34—Identification of a linear epitope shorter than 20 amino acid residues or of a conformational epitope defined by amino acid residues
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Y—ENZYMES
    • C12Y304/00—Hydrolases acting on peptide bonds, i.e. peptidases (3.4)
    • C12Y304/17—Metallocarboxypeptidases (3.4.17)
    • C12Y304/17023—Angiotensin-converting enzyme 2 (3.4.17.23)
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/005—Assays involving biological materials from specific organisms or of a specific nature from viruses
    • G01N2333/08—RNA viruses
    • G01N2333/165—Coronaviridae, e.g. avian infectious bronchitis virus
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
    • G01N2333/90—Enzymes; Proenzymes
    • G01N2333/914—Hydrolases (3)
    • G01N2333/948—Hydrolases (3) acting on peptide bonds (3.4)
    • G01N2333/95—Proteinases, i.e. endopeptidases (3.4.21-3.4.99)
    • G01N2333/964—Proteinases, i.e. endopeptidases (3.4.21-3.4.99) derived from animal tissue
    • G01N2333/96425—Proteinases, i.e. endopeptidases (3.4.21-3.4.99) derived from animal tissue from mammals
    • G01N2333/96427—Proteinases, i.e. endopeptidases (3.4.21-3.4.99) derived from animal tissue from mammals in general
    • G01N2333/9643—Proteinases, i.e. endopeptidases (3.4.21-3.4.99) derived from animal tissue from mammals in general with EC number
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2440/00—Post-translational modifications [PTMs] in chemical analysis of biological material
    • G01N2440/12—Post-translational modifications [PTMs] in chemical analysis of biological material alkylation, e.g. methylation, (iso-)prenylation, farnesylation
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/26—Infectious diseases, e.g. generalised sepsis
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/50—Determining the risk of developing a disease

Definitions

  • This invention relates generally to biomarkers for assessing the likelihood of a subject being resistant to a virus infection.
  • 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).
  • 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.
  • 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.
  • 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.
  • the coronavirus is SARS-CoV-2.
  • 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.
  • 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.
  • 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 .
  • the sample comprises CD3+ cells, CD14+ cells, and/or CD8+/CD4+ T cells. In some embodiments, the sample comprises a monocyte cell.
  • the sample comprises a PBMC sample or a tissue sample (such as a kidney sample, brain sample, or gut sample).
  • a tissue sample such as a kidney sample, brain sample, or gut sample.
  • the sample may comprise lung tissue.
  • the methylation status of the ACE2 polypeptide is assessed using an ACE2 me antibody.
  • 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.
  • 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.
  • the present invention provides a kit for detecting and/or quantifying the methylation status of an ACE2 polypeptide.
  • 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).
  • a biological sample e.g., PBMCs or tissues.
  • 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).
  • 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.
  • 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 )
  • 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.
  • the present invention provides a composition
  • 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 ).
  • a biological sample e.g., a liquid biopsy or a tissue sample
  • 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 .
  • 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 ),
  • the biological sample comprises one or more PBMC.
  • the biological sample comprises whole blood.
  • the biological sample comprises a tissue (e.g., lung, kidney, gut, etc).
  • a tissue e.g., lung, kidney, gut, etc.
  • Figu e Generation of a novel antibody specific for ACE2 methylated at lysine 31 (“ACE2 me antibody”).
  • ACE2 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).
  • FIG. 1 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.
  • FIG. 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 .
  • cytoplasmic/CFI fluorescence intensity
  • FIG. 1 Schematic showing blood sample collection from vaccinated patients (post 3 rd dose) who subsequently developed and recovered from COVID-19.
  • 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.
  • FIG. 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.
  • 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.
  • FIG. 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 ).
  • 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.
  • 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.
  • 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).
  • CDRs complementarity determining regions
  • FR framework regions
  • 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.
  • the FRs of an antibody 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.
  • 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.
  • immunoglobulins can be assigned to different classes.
  • immunoglobulins 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, ⁇ , ⁇ , y, and ⁇ , respectively.
  • the subunit structures and three-dimensional configurations of different classes of immunoglobulins are well known.
  • biomarker 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).
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • biomarker signature refers 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.
  • 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.
  • the biomarker signature is a “protein signature.”
  • 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.
  • 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.
  • organelles such as mitochondria, Golgi apparatus, endoplasmic reticulum, ribosomes, etc.
  • the nucleus such as mitochondria, Golgi apparatus, endoplasmic reticulum, ribosomes, etc.
  • the cytoplasm optionally including the organelles
  • nuclear membrane such as nuclear membrane, the cell membrane and other cellular regions.
  • 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.
  • numbers e.g., measurements, values, likelihood, risk
  • amino acid sequence that displays substantial sequence similarity or identity to a reference amino acid sequence.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • an effective amount of drug, compound, or pharmaceutical composition is an amount sufficient to accomplish prophylactic or therapeutic treatment either directly or indirectly.
  • 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.
  • 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.
  • expression refers the biosynthesis of a gene product.
  • expression involves transcription of the coding sequence into mRNA and translation of mRNA into one or more polypeptides.
  • expression of a non-coding sequence involves transcription of the non-coding sequence into a transcript only.
  • 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”.
  • RNA transcript e.g., mRNA, antisense RNA, siRNA, shRNA, miRNA, etc.
  • expression of a coding sequence results from transcription and translation of the coding sequence.
  • expression of a non-coding sequence results from the transcription of the noncoding sequence.
  • 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%.
  • 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%.
  • 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%.
  • 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%.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • nucleobases nucleoside or nucleotide bases
  • 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.
  • inhibitor refers to an agent that decreases or inhibits at least one function or biological activity of a target molecule.
  • “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.
  • isolated refers to material that is substantially or essentially free from components that normally accompany it in its native state.
  • 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.
  • 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”).
  • contaminating molecules molecules that are not the subject of this invention
  • 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.
  • 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.
  • peptide 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.
  • 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.
  • 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.
  • 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.
  • sample 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.
  • 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, peri
  • 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.
  • the sample is readily obtainable by minimally invasive methods, allowing the removal or isolation of the sample from the subject.
  • the sample contains blood, especially peripheral blood, or a fraction or extract thereof.
  • 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).
  • the sample comprises leukocytes including peripheral blood mononuclear cells (PBMC).
  • PBMC peripheral blood mononuclear cells
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • subject refers 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),
  • 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.
  • 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).
  • a representative ACE2 polypeptide comprises the following amino acid sequence:
  • methylation e.g., methylation of the lysine at position 31 of ACE2 (i.e., ACE2-31 K-Me)
  • ACE2 i.e., ACE2-31 K-Me
  • This methylated form of ACE2 tended to localize more to the intracellular compartments rather than the cell membrane.
  • 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).
  • 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.
  • the sample is obtained prior to treatment with a therapy (e.g., a SARS-CoV-2 vaccine).
  • the sample is obtained after treatment with a therapy (e.g., a SARS-Cov-2 vaccine).
  • the sample is whole blood.
  • the sample comprises lung bronchioles.
  • the sample comprises PBMCs.
  • 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.
  • biomarker e.g., an ACE2 polypeptide
  • 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.
  • 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).
  • 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.
  • biomarker e.g., protein or nucleic acid (e.g., gene or mRNA)
  • 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.
  • 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
  • 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.
  • MSD Meso Scale Discovery
  • presence and/or level/amount is measured by observing protein levels.
  • 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).
  • an antigenbinding molecule e.g., an antibody
  • therapy biomarker e.g., ACE2 me
  • Such method may be an in vitro or in vivo method.
  • one or more anti-biomarker antigen-binding molecules are used to select subjects eligible for a therapy e.g., an SARS-CoV-2 vaccine.
  • the presence and/or expression level/amount of biomarker proteins in a sample is examined using immunohistochemistry (IHC) or immunofluorescence microscopy (IF) protocols.
  • the level of a response to therapy biomarker e.g., ACE2 Me
  • 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.
  • IHC or IF staining intensity is determined relative to a reference.
  • the reference is a reference value.
  • 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).
  • 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.
  • 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
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • the sample is a clinical sample.
  • the sample is a liquid biopsy, such as blood.
  • the tissue sample is lung tissue.
  • 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.
  • FACS Western blot
  • ELISA immunoprecipitation
  • immunohistochemistry immunofluorescence
  • radioimmunoassay radioimmunoassay
  • dot blotting immunodetection methods
  • HPLC surface plasmon resonance (“SPR”)
  • the at least one immune response biomarker is/are detected using FACS analysis or immunofluorescence microscopy.
  • the at least one response to therapy biomarker is detected in blood samples.
  • 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.
  • 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.
  • 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).
  • 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.
  • a reference e.g., a reference number
  • 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.
  • the sample may be a peripheral blood sample (e.g., from a patient at risk of being exposed to SARS-CoV-2).
  • 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).
  • the sample may be used without separating or isolating cell types.
  • 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.
  • a fresh peripheral blood sample i.e., one that has not been prepared by the methods described above may be used.
  • a peripheral blood sample may be prepared by incubation in a solution to preserve mRNA and/or protein integrity.
  • 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.
  • a disease or infection resistant subject may refer to a subject whose symptoms are mild or an asymptomatic subject.
  • 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.
  • 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.
  • 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.
  • 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.
  • the resistance to infection signature panel suitably includes one or more additional biomarkers.
  • the resistance to infection signature may comprise ACE2 me , and CD14.
  • 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.
  • 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.
  • the biomarkers are measured in a patient sample using the methods described herein and an infection resistance signature status is calculated.
  • 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.
  • the particular predictive or prognostic cut-off(s) used in an assay can increase sensitivity or specificity of the assay depending on the preference of the skilled person.
  • 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.
  • 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.
  • 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.
  • DA discriminant analysis
  • DFA Discriminant Functional Analysis
  • 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.
  • DA e.g., Linear-, Quadratic-, Regularized Discriminant Analysis
  • DFA Kernel Methods
  • MDS Nonparametric Methods
  • PLS Partial Least Squares
  • Tree-Based Methods e.g., Logic Regression, CART, Random Forest Methods, Boosting Methods
  • Generalized Linear Models e.g.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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).
  • 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
  • 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.”
  • 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.
  • 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 LinuxTM based operating system.
  • 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.
  • 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.
  • 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 form the base for diagnostic tests by providing diagnostic values (e.g., cut-off points) for biomarkers used singly or in combination.
  • 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.
  • 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.
  • antigen binding molecules are typically isolated methylation site-specific antigen-biding molecules that bind specifically to ACE2 only when 31 K is methylated.
  • 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.
  • 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.
  • a peptide antigen comprising all or part of the amino acid sequence encompassing the respective methylated residue
  • SEQ ID NO: 2 which encompasses the methylated lysine at position 31 of ACE2
  • 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.
  • a suitable animal e.g., rabbit, goat, etc.
  • the peptide antigen includes the methylated form of lysine (e.g., K(Me) or K(Me2)).
  • the peptide antigen
  • 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)).
  • 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.
  • a desirable peptide antigen will comprise four or more amino acids flanking each side of the methylatable amino acid and encompassing it.
  • 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 ).
  • 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 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.
  • 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)).
  • 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.
  • 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.
  • 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.).
  • the invention also provides immortalized cell lines that produce an antibody of the invention.
  • hybridoma clones constructed as described above, that produce monoclonal antibodies to the ACE2 methylation site disclosed herein are also provided.
  • the invention includes recombinant cells producing an antibody of the invention, which cells may be constructed by well-known techniques.
  • 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.)
  • Methylation site-specific antibodies of the invention 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 )).
  • 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.
  • 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.
  • 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.
  • Antigen-binding molecules may be advantageously conjugated to fluorescent dyes (e.g., Alexa Fluor 488) for use in multi-parametric analyses.
  • fluorescent dyes e.g., Alexa Fluor 488
  • 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.
  • 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.
  • a therapy e.g., a SARS-CoV-2 vaccine therapy
  • 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).
  • 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.
  • a therapy e.g., a vaccine
  • 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.
  • whether a subject is an appropriate candidate for therapy is determined based on an assay of at least one infection resistance biomarker in a sample obtained from the subject.
  • a subject to receive a SARS-CoV-2 therapy to treat or prevent a severe infection.
  • the therapy is an immunotherapy, suitably with an anti-immune checkpoint inhibitor.
  • 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.
  • 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.
  • 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.
  • reagents include, for example, compounds or materials, or sets of compounds or materials, which allow quantification of the biomarkers.
  • 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.
  • antigen-binding molecules e.g., antibodies
  • material for extraction of RNA e.g., antibodies
  • primers for the synthesis of a corresponding cDNA primers for amplification of DNA
  • probes capable of specifically hybridizing with the RNAs (or the corresponding cDNAs) encoded by the genes, TaqMan probes, etc.
  • 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.
  • 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.
  • kits 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.
  • the media can contain Internet addresses that provide the instructional material.
  • 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).
  • Custom polyclonal rabbit antibodies against ACE2 target sequence QAKTFLD(K me )FNHEAED were generated by MIMOTOPESTM. 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.
  • KLH Keyhole Limpet Hemocyanin
  • 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.
  • ELISA enzyme-linked immunosorbent assay
  • 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.
  • 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.
  • 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).
  • ELISA enzyme linked immunosorbent assay
  • 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.
  • 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.
  • 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.
  • 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
  • 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.
  • 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.
  • 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.
  • 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).
  • 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.
  • ACE2 me is linked to reduced disease severity and recovery from Covid-19, indicating a protective signature.
  • 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 .
  • 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.
  • 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.

Landscapes

  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Chemical & Material Sciences (AREA)
  • Immunology (AREA)
  • Engineering & Computer Science (AREA)
  • Molecular Biology (AREA)
  • General Health & Medical Sciences (AREA)
  • Biomedical Technology (AREA)
  • Medicinal Chemistry (AREA)
  • Urology & Nephrology (AREA)
  • Hematology (AREA)
  • Organic Chemistry (AREA)
  • Biochemistry (AREA)
  • Microbiology (AREA)
  • Physics & Mathematics (AREA)
  • Cell Biology (AREA)
  • Proteomics, Peptides & Aminoacids (AREA)
  • Genetics & Genomics (AREA)
  • Biophysics (AREA)
  • Food Science & Technology (AREA)
  • Biotechnology (AREA)
  • Analytical Chemistry (AREA)
  • General Physics & Mathematics (AREA)
  • Pathology (AREA)
  • Virology (AREA)
  • Tropical Medicine & Parasitology (AREA)
  • Investigating Or Analysing Biological Materials (AREA)

Abstract

La divulgation concerne des méthodes d'évaluation de la probabilité qu'un sujet ait une résistance à une infection à coronavirus (par exemple, une infection à SARS-CoV-2). Plus particulièrement, la présente demande concerne des méthodes d'évaluation de la probabilité qu'un sujet ait une résistance à une infection à coronavirus sur la base de l'état de méthylation du sujet. Un lien a été établi entre la méthylation de la lysine 31 du polypeptide ACE2 et la résistance de sujets à une infection grave à SARS-CoV-2. La divulgation concerne également des réactifs et des kits permettant d'évaluer l'état de méthylation d'un sujet.
PCT/AU2023/050698 2022-07-27 2023-07-27 Biomarqueur de méthylation pour la résistance à une infection WO2024020646A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
AU2022902106 2022-07-27
AU2022902106A AU2022902106A0 (en) 2022-07-27 Methylation biomarker for infection resistance

Publications (1)

Publication Number Publication Date
WO2024020646A1 true WO2024020646A1 (fr) 2024-02-01

Family

ID=89704708

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/AU2023/050698 WO2024020646A1 (fr) 2022-07-27 2023-07-27 Biomarqueur de méthylation pour la résistance à une infection

Country Status (1)

Country Link
WO (1) WO2024020646A1 (fr)

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2021195723A1 (fr) * 2020-04-03 2021-10-07 The Council Of The Queensland Institute Of Medical Research Méthodes de traitement d'infections à coronavirus
CN113546173A (zh) * 2021-08-19 2021-10-26 徐州医科大学 Prmt5特异性抑制剂在预防冠状病毒感染中的应用
WO2022083675A1 (fr) * 2020-10-23 2022-04-28 中国科学院上海药物研究所 Anticorps monoclonal dirigé contre divers coronavirus et son utilisation
WO2022221920A1 (fr) * 2021-04-20 2022-10-27 The Council Of The Queensland Institute Of Medical Research Nouvelles compositions et nouvelles méthodes de traitement d'infections à coronavirus

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2021195723A1 (fr) * 2020-04-03 2021-10-07 The Council Of The Queensland Institute Of Medical Research Méthodes de traitement d'infections à coronavirus
WO2022083675A1 (fr) * 2020-10-23 2022-04-28 中国科学院上海药物研究所 Anticorps monoclonal dirigé contre divers coronavirus et son utilisation
WO2022221920A1 (fr) * 2021-04-20 2022-10-27 The Council Of The Queensland Institute Of Medical Research Nouvelles compositions et nouvelles méthodes de traitement d'infections à coronavirus
CN113546173A (zh) * 2021-08-19 2021-10-26 徐州医科大学 Prmt5特异性抑制剂在预防冠状病毒感染中的应用

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
LI ZHONGWEI, YONG HONGMEI, WANG WENWEN, GAO YUE, WANG PENGFEI, CHEN XINTIAN, LU JUN, ZHENG JUNNIAN, BAI JIN: "GSK3326595 is a promising drug to prevent SARS‐CoV‐2 Omicron and other variants infection by inhibiting ACE2‐R671 di‐methylation", JOURNAL OF MEDICAL VIROLOGY, JOHN WILEY & SONS, INC., US, vol. 95, no. 1, 1 January 2023 (2023-01-01), US , XP093136535, ISSN: 0146-6615, DOI: 10.1002/jmv.28158 *
RAGIA GEORGIA, MANOLOPOULOS VANGELIS G: "Assessing COVID-19 susceptibility through analysis of the genetic and epigenetic diversity of ACE2-mediated SARS-CoV-2 entry", PHARMACOGENOMICS, FUTURE MEDICINE, UK, vol. 21, no. 18, 1 December 2020 (2020-12-01), UK , pages 1311 - 1329, XP055935544, ISSN: 1462-2416, DOI: 10.2217/pgs-2020-0092 *
TU WEN JUAN, MCCUAIG ROBERT D., MELINO MICHELLE, RAWLE DANIEL J., LE THUY T., YAN KEXIN, SUHRBIER ANDREAS, JOHNSTON REBECCA L., KO: "Targeting novel LSD1-dependent ACE2 demethylation domains inhibits SARS-CoV-2 replication", CELL DISCOVERY, vol. 7, no. 1, 1 December 2021 (2021-12-01), XP093000362, DOI: 10.1038/s41421-021-00279-w *
TU WEN JUAN, MELINO MICHELLE, DUNN JENNY, MCCUAIG ROBERT D., BIELEFELDT-OHMANN HELLE, TSIMBALYUK SOFIYA, FORWOOD JADE K., AHUJA TA: "In vivo inhibition of nuclear ACE2 translocation protects against SARS-CoV-2 replication and lung damage through epigenetic imprinting", NATURE COMMUNICATIONS, NATURE PUBLISHING GROUP, UK, vol. 14, no. 1, UK, XP093136532, ISSN: 2041-1723, DOI: 10.1038/s41467-023-39341-4 *

Similar Documents

Publication Publication Date Title
US8617547B2 (en) Methods and compositions for diagnosing prostate cancer
US9448232B2 (en) Methods and materials for detecting C9ORF72 hexanucleotide repeat expansion positive frontotemporal lobar degeneration or C9ORF72 hexanucleotide repeat expansion positive amyotrophic lateral sclerosis
CN108883115A (zh) 用parp抑制剂治疗小细胞肺癌
EP3098602A1 (fr) Distinction de virus infectieux basée sur des biomarqueurs moléculaires et de neutralisation de virus causant un empoisonnement alimentaire
US10539565B2 (en) Methods for determining prognosis of colorectal cancer
WO2024020646A1 (fr) Biomarqueur de méthylation pour la résistance à une infection
JPWO2017159771A1 (ja) 肝細胞増殖因子（ｈｇｆ）のｐｄマーカー
US10370417B2 (en) Methods for the diagnosis of cancer through detection of human endogenous retrovirus WL (HERV-WL) envelope expression
JP6252949B2 (ja) 統合失調症マーカーセット及びその利用
US20230416836A1 (en) Method for predicting responsiveness to plk1 inhibition
CN105018576B (zh) 15种男性生育相关蛋白或其组合的应用
US10155008B2 (en) Use of 15 male fertility related proteins or combination thereof
TW201818972A (zh) 針對ｍｅｌｋ的單株抗體及其用途
EP2738252B1 (fr) Anticorps pour la détection d'un marqueur du cancer épithélial de l'ovaire et méthode pour le diagnostic du cancer épithélial de l'ovaire
US7588898B2 (en) Biomarker for gestational trophoblastic disease
US20140256583A1 (en) Detection of human endogenous retrovirus expression in cancer and normal cells
EP3364188B1 (fr) Biomarqueur sanguin pour utilisation dans l'évaluation de l'effet d'une pharmacothérapie sur le cancer du rein
WO2023156714A1 (fr) Procédé de détection et de sous-typage de maladies intestinales inflammatoires
JP2009065969A (ja) 胃ガン腹腔内転移判定用組成物及び方法
JP2009065969A5 (fr)
CN115104029A (zh) 用于检测和监测全身性炎症的非侵入性测定法
May et al. Highly Immunoreactive IgG Antibodies Directed against a Set of Twenty Human

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 23844693

Country of ref document: EP

Kind code of ref document: A1