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WO2003058250A2 - Analyse de la composition de proteines - Google Patents

Analyse de la composition de proteines Download PDF

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Publication number
WO2003058250A2
WO2003058250A2 PCT/GB2003/000133 GB0300133W WO03058250A2 WO 2003058250 A2 WO2003058250 A2 WO 2003058250A2 GB 0300133 W GB0300133 W GB 0300133W WO 03058250 A2 WO03058250 A2 WO 03058250A2
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Prior art keywords
protein
binding
sample
calibration
target protein
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WO2003058250A3 (fr
Inventor
Mikhail Soloviev
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Oxford Glycosciences UK Ltd
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Oxford Glycosciences UK Ltd
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Priority to AU2003201674A priority Critical patent/AU2003201674A1/en
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Publication of WO2003058250A3 publication Critical patent/WO2003058250A3/fr
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    • 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
    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids

Definitions

  • the present invention provides a method for determining the presence of at least one target protein in an experimental sample.
  • Existing methods of estimating protein concentration include colorimetric assays for total protein measurements (used for purified protein preparations or for total protein estimations), direct immunoassays or enzyme-linked immunoassays for measuring specific protein concentrations in a mixture of proteins.
  • Immunoassays where more than one affinity reagent is immobilised on a solid support are often referred to as protein arrays.
  • Arrays of affinity reagents may be comprised of biomolecules including both nucleic acids and proteins and generally employ at least one affinity reagent for each individual nucleic acid or protein to be measured where each affinity reagent is present in a unique position on the array.
  • a protein array would consist of a large number of high affinity, high specificity affinity reagents; one for each protein in the mixture e.g. the proteome to be analysed.
  • this could mean providing in the order of 100,000 monoclonal antibodies (or other specific affinity reagents) and in reality it would mean far more since post-translational modifications can alter a protein such that it may not be distinguishable from its unmodified form or may no longer be detectable.
  • affinity reagents such as antibodies
  • concentration (or level of expression) of biomolecules is estimated by measuring steady state binding levels of that protein to an affinity reagent which are then compared with controls, with calibration curves, or compared between samples from diseased and normal tissue, cells or body fluids.
  • the position of an affinity reagent on an array is known and the array is calibrated using a control sample containing all the proteins of interest.
  • nucleic acid arrays permit quantitation and hence fold-changes to be calculated. Indeed, fold-change estimates are generally limited to nucleic acid arrays, where individual affinities are typically similar between each "spot" of the array, being dependent on the number of base pairs formed, and hence the hybridisation signal is approximately proportional to the concentration of the nucleic acid probe.
  • the method of the invention disclosed herein enables the characterisation of a protein sample with an affinity reagent which may comprise different specificities and affinities; for example, a complex sample may be characterised on an array of affinity reagents.
  • affinity reagent which may comprise different specificities and affinities; for example, a complex sample may be characterised on an array of affinity reagents.
  • a method for determining the presence of at least one target protein within an experimental sample comprising:
  • the method comprises contacting a protein containing sample with one or more affinity reagents present as a protein recognition unit (PRU) immobilised on a substrate, under conditions that allow the affinity reagent(s) comprising the PRU to interact with antigenic determinants or binding motifs present in the protein and measuring an indicator of binding of the to the affinity reagents.
  • PRU protein recognition unit
  • the invention enables the advantageous use of affinity reagents with more than one reactivity, i.e. multiple specificities and/or different (i.e. more than one) affinities, such reagents being typically unusable in traditional affinity assays.
  • the method uses the collection of measurements (values) as an indicator of binding to determine the presence of, e.g.
  • each set of measurements is a signature for a particular interaction event for a given PRU with a given protein.
  • a set of respective calibration measurements i.e. a calibration data set
  • the use of an affinity reagent with more than one reactivity is enabled using the method of this invention, as is the analysis of a complex sample.
  • the method also enables the compositional quantitation of a complex sample by comparison with calibration data.
  • a PRU comprises at least one affinity reagent immobilised on a substrate.
  • the substrate may be any substrate known in the art for immobilising a affinity reagents such as, but not limited to, metal, glass, plastic, HydrogelsTM (Packard BioSciences, Meridian, CT) or membranes, or those documented by Walter etal. in 2000 (Curr. Opin. Microbiol. 3: 298-302) or other substrates such as beads.
  • the substrate comprises a metallic film or metal, e.g. gold, layer or other such suitable conducting surface which is preferably non-magnetic; the choice of substrate may depend upon the method to be used to measure the indicator of binding such that one skilled in the art will make the selection of substrate based upon this criterion.
  • a PRU preferably comprises at least one affinity reagent which possesses more than one reactivity such that it may recognise more than one antigen, i.e. it may be capable of recognising interacting proteins with more than one affinity; thus an affinity reagent may be multi-specific and may cross-react with related or unrelated proteins.
  • a PRU may comprise two or more affinity reagents which possess one reactivity each, i.e. they are mono-specific, e.g. monoclonal antibodies.
  • a PRU may comprise a combination of mono-specific and multi- specific affinity reagents.
  • a plurality of PRUs are used they are preferably arranged in a specific, co-ordinated pattern, e.g. in an array format such that the location of each PRU is known.
  • the array of PRUs comprises at least one individual PRU comprising multi-specific reactivities, or more than one mono-specific reactivity.
  • the PRUs may be of known or unknown sequence content but it is understood that the PRU must be calibrated with a target protein to allow subsequent identification and/or quantitation of that same protein in an experimental sample.
  • the method of the invention permits the use of an array comprised of a plurality of immobilised PRUs that are specific for target proteins of interest.
  • a plurality of PRUs is four or more PRUs, more preferably ten or more PRUs and even more preferably more than twenty-five PRUs.
  • Affinity reagents include individual antibodies, e.g. polyclonal, monoclonal, bispecific, humanized or chimeric antibodies, single chain antibodies, Fab fragments and F(ab') fragments, fragments produced by a Fab expression library, anti-idiotypic antibodies, and epitope-binding fragments of any of the above or complementarity determining regions (CDRs), antibody mimics, aptamers, polypeptides, or generic affinity reagents capable of interacting with more than one partner (e.g. Protein A and Protein G, related molecules and their derivatives, lectins, proteins interacting through the PDZ domains, SH domains, leucine zipper motifs or coiled-coil protein interactors).
  • CDRs complementarity determining regions
  • Affinity reagents may also be recombinant proteins.
  • the method of the invention may use completely non-specific protein binders, such as and without limitation, ion-exchange binders, metal chelate binders, or substances utilising hydrophobic interactions (e.g. reverse phase resins).
  • variable heavy and light chains each contribute three regions called CDRs which are responsible for binding antigen.
  • Each region is typically 7-20 amino acids long, e.g. 15-17 amino acids, and its sequence defines the specificity and affinity of that CDR for the antigen.
  • these regions of CDR- peptides are capable of autonomous specific binding to antigens, see for example Steinbergs, J. etal., 1996, Hum. Antibodies Hybridomas, 7: 106-112; William, W. et al., 1991 , J. Biol. Chem., 266: 5182-5190; Saragovi, H. et al., 1991 , 253: 792-795; Welling, W.
  • CDRs can be produced by recombinant means or can be chemically synthesized.
  • CDRs can be chemically synthesized according to known CDR sequences using either standard protein synthesis or using a combinatorial synthesis approach.
  • protein' includes proteins and glycoproteins, polypeptides and peptides and also includes protein-nucleic acid complexes. Proteins may comprise post-translational modifications (PTMs) such as but not limited to, phosphorylation, acetylation and methylation; a large number of PTMs are well known in the art.
  • PTMs post-translational modifications
  • a target protein(s) is that protein or proteins present within a sample, the identification, detection and/or quantification of which is desired.
  • Samples of proteins may be derived from for example, but not limited to, normal or diseased tissue, cells, blood, serum, or other body fluids or exudates. If desired, the sample may be subjected to preliminary processing, including preliminary separation techniques. For example, cells or tissues can be extracted and subjected to subcellular fractionation for separate analysis of proteins in distinct subcellular fractions or can be selectively depleted of, for example, high abundance proteins such as albumin, haptoglobin and/or immunoglobin G.
  • the samples to be analysed using the method of the invention comprise a plurality of peptides generated by enzymatic or non-enzymatic cleavage of proteins or combinations thereof (such as described in WO 02/25287).
  • an enzymatic digestion step is performed using trypsin that gives rise to a set of peptides possessing a carboxy-terminal lysine or arginine residue (the exception may be the extreme carboxy-terminal peptide).
  • the method of the invention provides a means of screening, diagnosis and/or prognosis of a disease in a human or animal subject, i.e.
  • said means comprising analysing a biological sample from a subject for a protein or proteins of interest, i.e. characteristic target proteins, known to be associated with that disease.
  • the characteristic target proteins may show differential expression such that they may be increased or decreased in a particular disease.
  • the presence of a set of characteristic target proteins some of which exhibit an increase and some of which exhibit a decrease in sample from a diseased subject compared to a sample from a subject free of a disease may be determined.
  • a the method of the invention in the screening, diagnosis or prognosis of a disease in a subject, for determining the stage or severity of said disease in a subject, for identifying a subject at risk of developing said disease, or for monitoring the effect of therapy administered to a subject suffering from said disease by determining the presence of at least one characteristic target protein within an experimental sample from said subject which method comprises:
  • (c) calculating a best fit determined from the data set of part (b) with a data set obtained for at least one calibration sample, in order to determine the presence of the characteristic target protein within the experimental sample. It is understood that the concentration of a characteristic target protein may be zero or close to zero, or below or above a pre-determined or known threshold value.
  • the method of the invention may also be used to characterize an array of PRUs comprising antibodies where the specificity of the antibodies is at least partially unknown.
  • the invention uses differences in indicators of binding measured during a phase of binding such as, for example but without limitation, the rate of association and/or dissociation of a protein sample with an individual PRU or a plurality of PRUs, e.g. presented as an array, to distinguish individual proteins present within said protein sample in a high throughput manner.
  • the term indicator may reflect a value when referring to a measurement of binding.
  • a preliminary measurement e.g. a background measurement, is taken before the PRU is contacted with sample.
  • Binding of target proteins within a sample of interest to the PRU or PRUs is measured during at least two time points during one or more phases of binding of the sample of interest to said PRU, i.e. during the association and/or dissociation phases and/or steady state phase.
  • more than one identical PRU or array of PRUs is used.
  • binding is measured during one or more phases at two or more time points and using one or more different phase of binding conditions, i.e. association and/or dissociation or steady state conditions.
  • Such conditions include, but are not limited to, using buffers with properties that vary, for example but without limitation, in composition, ionic strength, temperature or pH.
  • said conditions are changed in a continuous manner, for example but without limitation, by applying a gradient of increasing ionic strength or other continuous change in stringency. These differences are most preferably measured by sampling the real-time binding data during at least two time points during any one association phase and at least two time points during any one dissociation phase.
  • measurements are performed during at least two time points within the association phase, one of which is at or near steady state binding, and during at least two time points within the dissociation phase (after the removal of unbound proteins).
  • a plurality of binding measurements is performed corresponding to multiple time points during one or more phases of binding, i.e. during one association or dissociation phase or during both the association and dissociation phases.
  • a plurality of binding measurements is preferably, five or more, more preferably ten or more and even more preferably fifteen or more. It is understood that consecutive or parallel (using identical PRUs) association phases can be used, as can consecutive or parallel dissociation phases. For example, consecutive or parallel association and/or dissociation phases may be performed using different association conditions, different dissociation conditions or both.
  • Such data sets can be generated using one PRU or can be generated from an array of PRUs. Owing to the inherent heterogeneity of proteins, protein affinity reagents and protein- protein interactions (e.g. the interaction between a protein affinity reagent and a target protein), different protein-protein interactions are described by different data sets providing an indicator of binding (including protein concentration, k a and k d ).
  • the invention uses differences in these patterns for multiplexing an assay, e.g. as an array.
  • the invention does not require the measurement of the absolute values of these binding parameters (i.e. k a and k d ), but determines relative protein concentrations (e.g. the concentration of a target protein within an experimental protein sample relative to the concentration of the calibration material use) and/or identifies which calibration standard (or standards) the experimental sample most closely matches.
  • measurements are performed during at least two time points within each individual dissociation phase (after the removal of unbound proteins) permitting the detection of differences in the dissociation rates of proteins binding to the same affinity reagent. More preferably, measurements are performed during three or more time points within a dissociation phase. Even more preferably, measurements are performed during at least two time points during each dissociation phase using more than one dissociation condition.
  • Examples of different time points which may be used for measuring an indicator of binding in step (b) include: a) two or more time points during a dissociation phase; b) at least one time point during an association phase and at least one time point during a dissociation phase; c) at three or more time points, one or more of which is during an association phase and two or more of which are during a dissociation phase; d) at three or more time points, two or more of which are during an association phase and one or more of which is during a dissociation phase; and e) at three or more time points, two or more of which are during an association phase, one or more of which is at or near steady state, and one or more of which is during a dissociation phase.
  • the method of the invention permits the determination of the protein composition of an experimental sample and the individual target protein concentrations in said sample.
  • Association and dissociation rates (k a and k d ) of each of the identified components of the experimental sample will necessarily be identical to the ones, which characterise respective calibration samples. These may be either known prior to experiment, or if required may be measured using methods known in the art. It is understood that the disclosed method does not require and does not aim to measure the actual association and dissociation rate values (k a and k d ) for each of the PRUs used. Instead, only differences in these rates are being detected and used to deduce protein composition and/or concentration in the sample of interest.
  • Methods, known in the art, for measuring an indicator of binding such as steady state binding and k a and k d include methods for detecting protein binding to immobilised affinity reagents in solution in real-time such as those measuring Surface Plasmon Resonance (SPR), fluorescence (Planar Wave Guide technology) or Resonance Light Scattering.
  • SPR technology measures biomolecular interactions such as protein-protein interactions and as such is a measure of binding [Mirabella & Harrick, Internal Reflection Spectroscopy: Review and Supplement (Harrick Scientific Corporation) 3, 1985; de Mello, AJ, in Surface Analytical Techniques for Probing Biomaterial Processes, ed. CRC Press, Boca Raton, NY].
  • an indicator of binding is a measured data set.
  • the preferred method of measuring an indicator of binding is by means of a process comprising Surface Plasmon Resonance.
  • Surface Plasmon Resonance is preferably measured on PRU's immobilized on substrates which comprise a metal layer.
  • the metal layer is preferably a gold layer.
  • polyclonal antibodies may be considered. These are a typical example of heterogeneous mixtures of immunoglobulins of different types and of differing specificities. Such antibodies perform well in Western blotting applications but are less suitable for more scrupulous applications such as BIAcore SPR-based analysis or antibody microarrays where mono-specific reagents (i.e.
  • association binding phase will eventually reach equilibrium, that is the association phase of binding will eventually become the steady state phase (i.e. the steady state phase is not considered a separate phase to the association phase).
  • steady state phase i.e. the steady state phase is not considered a separate phase to the association phase.
  • affinity reagents such as antibodies
  • these properties mean that lower affinity antibodies or antibodies with smaller k a and k d are suitable. In the context of this invention, this is advantageous as lower affinity antibodies (or other affinity reagents) are typically easier and more cost effective to develop, for example using methods known in the art.
  • affinity arrays In general, affinity arrays, known in the art, concentrate on employing antibodies as affinity reagents with the particular desired properties of mono-specificity and high affinity binding in order to minimise cross-reactivity and false positive results, and to maximise reliability. In reality, the frequency with which commercially available antibodies cross-react with unrelated proteins is a serious problem with respect to confidence in detection specificity (Hayward et al., 2001 , Drug Discovery Today 6: 1263-1265).
  • antibodies could be considered to be cross-reacting; for example an antibody recognising an epitope or motif in a protein which exists as a number of post-tr anslationally modified isoforms (for example and without limitation, isoforms which are acetylated, amidated, carboxylated, glycosylated, hydroxylated, isoprenylated, methylated, myristylated, phosphorylated or sulphated etc.), will often react with more than one isoform, if not all isoforms.
  • the method of the invention uses the differences in the affinities of such multiple interactions and thus distinguishes different interacting proteins and can be used quantitatively. Larger differences in measurements of indicators of binding, for example between immunoglobulins of different types and Protein A, will result in easier and more reliable identification and quantitation.
  • a mono-specific antibody permits a single target protein, X ; to be detected with a signal at one position, Px , within an array and with the intensity of said signal (steady state binding signal, SSx ) reflecting the concentration of the applied protein, [X ⁇ ].
  • SSx steady state binding signal
  • [X ⁇ ] relates to the indicator of binding represented as a data set (Px ; SSx ) and; for n proteins the pd] to [X n ] relates to the data sets (P x ; SS X ) to (P x ; SS X ).
  • Data analysis is preferably performed by fitting experimental data sets with the data sets obtained using standard proteins or peptides or sets thereof for calibration of the PRUs.
  • Optimal data fit can be found preferably using non-linear regression algorithms or linear regression algorithms. It is understood by one of ordinary skill in the art that the comparison of the experimental data set with the calibration data set can be done using any appropriate mathematical method.
  • experimental data sets are compared with calibration data sets and the best fit obtained by maximizing the Covariance or alternatively minimising the standard deviation or the sum of squares of deviations of data sets from their sample means.
  • the correlation coefficient can also be used for data set comparison for optimal fit, as can a CHI TEST for independence.
  • Mode No. 1 - target protein identification mode Mode No. 2 - target protein quantitation mode.
  • Mode No 3 - a combined Mode No 1 plus Mode No 2, i.e. target protein identification plus target protein quantitation
  • the three modes are described below in more details.
  • Mode No 1 - target protein identification The following description is intended to illustrate mode 1 and is in no way meant to be limiting.
  • Mode 1 permits the identification of a target protein or proteins within an experimental sample using a PRU or PRUs calibrated with a sample containing said target protein(s).
  • the PRU calibration solutions must contain said target protein as one of the calibration sample components, for example to identify whether an experimental sample comprises IgA, IgG and IgM, the PRU should be calibrated with all three target proteins; if an experimental sample comprises only two of the three target proteins then a sufficient number of calibration measurements should be performed utilising all combinations of pairs of target proteins present in the calibration sample, i.e. such that each target protein is represented independently in a calibration measurement (thus calibrate with IgA + IgG; IgA + IgM; and IgG + IgM).
  • mode 1 can be carried out by performing calibration measurements and experimental sample measurements during one or more association phases, or during one or more dissociation phases, or using a combination of binding phases.
  • concentration of each of the calibration proteins is identical to the concentration of unknown experimental samples.
  • the most preferred way of doing the latter is to utilise all sample components (whether calibration and experimental sample components) at the same concentration.
  • all calibration components could be applied at 10 ⁇ g/ml and all experimental samples adjusted to 10 ⁇ g/ml protein prior to binding to PRU(s). Adjusting protein concentrations is not required if only data from dissociation phases are used.
  • a binding isotherm is a function of the amount of bound protein depending on time and is typically measured following protein application throughout an association phase, or a dissociation phase or throughout both binding phases.
  • the shape of each individual binding isotherm is determined by the combination of the measured indicators of binding to a PRU, each interacting protein and the reaction conditions. Individual binding isotherms can be described mathematically using equations known to one skilled in the art. In this particular example, the shape of the binding isotherm will become a function of the applied protein concentration and its association and dissociation rates k a and k d .
  • a PRU is calibrated with a sufficient set of calibration proteins (resulting in different binding isotherms) said PRU can be used to distinguish said proteins when said proteins are present in an experimental sample.
  • the maximum number of resolved proteins may be very large and in practice will be limited by the sensitivity of the binding detection system. Examples of mode 1 of operation include without limitation:
  • the protein concentration of the experimental samples must be adjusted to the same protein concentration as the calibration samples and target proteins must be represented among the calibration samples used, e.g. calibrating a PRU which comprises Protein A with 10 ⁇ g/ml solutions of IgA, IgG and IgM and determining which one of these three immunoglobulins was present in the experimental
  • Mode 2 permits measurement of the concentration of a particular target protein or target proteins within an experimental sample provided that the PRU(s) has been calibrated with said protein(s). If a target protein, X, is exposed to its cognate PRU (i.e. the PRU comprises an affinity reagent recognising X) at position Px, and binding measured at least three times, for example but without limitation, once during an association phase (Ax), once during steady state binding (SSx) and once during a dissociation phase (Dx), the resulting set of data points (i.e.
  • the binding of the target protein is measured a number of times throughout all binding phases, in order to more closely reflect the shape of the binding isotherm and reduce experimental measurement errors.
  • the obtained data set, or the shape of respective binding isotherm which can be described mathematically, uniquely reflects [X] as a function of the interaction parameters (k a and k d ) of X.
  • mode 2 (unlike most of the examples given for the mode No 1), experimental protein samples can be applied at any concentration, subject to signal detection thresholds and PRU saturation. It is understood that if the concentration of the target protein contained in the calibration sample is known then, by comparison with the indicators of binding measured for the experimental sample, an absolute concentration of the target protein present within said experimental sample can be predicted.
  • Mode No 3 - combined target protein identification and quantitation mode
  • Mode 3 permits the identification and quantitation of one or more target proteins by using one or more calibrated PRU(s) for identifying the target protein and measuring its concentration.
  • a single target protein, X 1 is exposed to its cognate PRU at position P Xl , and the binding measured at least three times, for example but without limitation, once during association phase (Ax ⁇ , once during or near the steady state binding (SSx ) and once during a single dissociation phase (Dx ⁇ , the resulting set of data points (i.e.
  • the obtained data set, or the shape of respective binding isotherm which can be described mathematically, will uniquely encode the identity and concentration of the target protein in the sample measured.
  • each binding isotherm encodes two completely independent interaction parameters k a and k d (i.e. "independent variables")
  • a single PRU permits a distinction to be made between the binding of two different target proteins that bind to the same PRU (i.e. the same spot) but with different binding rates.
  • Both of the target proteins can also be quantified by comparison of the experimentally measured binding isotherms with the binding isotherms of the samples used for calibration (which comprise both the target proteins); either absolute quantitation (if concentration of the respective target protein present in the calibration sample is known) or relative quantitation (if concentration of the respective target protein present in the calibration sample is unknown or the calibration solution was a mixture of different target proteins at different individual concentration) is achievable.
  • experimental protein samples can be applied at any concentration (subject to detection threshold limits and PRU saturation), but the number of resolvable proteins is limited by the number of independent calibration protein samples available, thus a sufficient number of calibration measurements where each target protein is represented independently (although not necessarily individually) must be performed. Increasing the number of independent PRUs will proportionally increase the maximum number of resolvable target proteins. Thus, if a single PRU resolves two different target proteins, then an array of "p" independent PRUs will be able to resolve "2 x p" proteins simultaneously, by comparison of the binding isotherms obtained for said different target proteins with the calibration binding isotherms (i.e. calculating the best fit of the experimental data set with the calibration data sets.
  • Calibrating said array of "p" PRUs using up to "2 x p" or less independent calibration samples permits the resolution of up to an equivalent number of different target proteins.
  • a further increase in the number of resolved target proteins can be obtained by measuring an indicator of binding under alternative reaction conditions such as, for example but without limitation, different buffer ionic strengths, different pH and/or different temperatures.
  • alternative reaction conditions such as, for example but without limitation, different buffer ionic strengths, different pH and/or different temperatures.
  • the indicators of binding measured for different target proteins are the same, the theory of the method may not allow one to distinguish said proteins.
  • the association phase can be measured using a calibration sample once followed by a measurement of the dissociation phase.
  • the reaction conditions of the dissociation phase may be altered (preferably from less stringent to more stringent). If the dissociation phase is repeated more than once using different dissociation conditions (e.g. using different pH, buffers or temperature), and at least one measurement is made during each such additional dissociation phase, each additional measurement will define an additional independent variable (reflecting respective k d ).
  • mode 3 examples include calibration of one or more PRUs or an array of PRU(s) with two or more target proteins thus permitting the identification and quantification of said proteins within an experimental sample.
  • the number of resolved and identified components is preferably less than or equal to the number of the independent (non-degenerate) calibrations used, thus in most cases:
  • Mode No 3 becomes Mode No 1 and the number of resolvable target proteins increases and may in theory become unlimited (see description of the Mode No 1). In practice this number will be limited by the sensitivity of the detection system used and the degree of variability of the interacting parameters for different samples (i.e. their k a and k d ). If, however, the concentration of the applied experimental samples differs only slightly from the calibration standards, the number of resolvable and quantifiable target proteins will be intermediate between the minimum resolvable (i.e. two) and maximum resolvable. In general, the nearer the concentration of the experimental samples to the concentration of the respective calibration samples, the greater the number of target proteins that can be resolved and quantitated. The preferred way of estimating the number of resolvable target proteins is by experimental trials. Calibration measurements
  • “Calibration” samples may include individual target proteins or mixtures of such which recognise a single PRU or may recognise multiple PRUs and may be applied to a PRU either individually or as mixtures with other calibration samples.
  • Each independent calibration sample (or mixture) applied to a PRU will determine a single dimension; thus, all such independent calibrations form a multidimensional space in which any experimental sample can be given a single vector, uniquely defining the target protein composition.
  • all examples described below refer to the mode No 3 of operation.
  • a generic PRU comprising, e.g.
  • the vector corresponding to such a sample will be (1 , 1 , 0).
  • a generic PRU for example Protein A
  • the target proteins i.e.
  • each target protein is represented independently using more than one dissociation phase measurement, for example: calibration target protein no.1 comprising 5 ⁇ g/ml IgA and 5 ⁇ g/ml IgG, calibration target protein no.2 comprising 10 ⁇ g/ml IgG and 10 ⁇ g/ml IgM and calibration target protein no.3 comprising 5 ⁇ g/ml IgM alone, then the unique vector for an experimental sample comprising 10 ⁇ g/ml lgA+10 ⁇ g/ml IgG will be (2, 0, 0). For another experimental sample comprising 10 ⁇ g/ml IgG only, the unique vector will be (0, 1 , -2). Negative numbers can occur if the samples used for calibration contain mixtures of different proteins.
  • relative quantitation is achieved in units of concentration relative to the concentration of the calibration target proteins. Absolute quantitation is possible if the absolute concentrations of the target proteins in the calibration samples are known.
  • affinity reagents reactive to proteins such as, but not limited to, antibodies possess some degree of cross-reactivity.
  • An affinity reagent's cross-reactivity may be due to its affinity for a number of different antigenic determinants such as is true of, but not limited to, polyclonal antibodies, or other motifs, or cross-reactivity may arise because more than one individual affinity reagent is present, for example but without limitation, the use of a combination of individual antibodies in one PRU.
  • an antibody possessing affinity for more than one antigenic determinant is used as a PRU, indicators of binding measured and compared with a calibration antigen using the disclosed method, permitting the user to distinguish between different antigens of interest and to quantitate the binding of said antigens to such a PRU.
  • the interactions can be measured individually using one PRU or a plurality of PRUs such as in an array format.
  • cross-reactivity can be introduced into the pool of affinity reagents used for each individual PRU. This could be done for example, but without limitation, by mixing together a number of antibodies with different antigenic specificities or by raising an antibody against a fragment common to more than one protein target, or by raising an antibody against a mixture of antigens.
  • the lower cost of the production of antibodies with mixed antigenic specificities will in turn reduce the cost of an antibody array.
  • PRU 1 is comprised affinity reagents for IgA, IgG and IgM proteins.
  • the major affinity reagent component comprising PRU 2 was anti-lgG while that of PRU 3 was Protein A.
  • Affinity reagents were loaded onto (i.e. immobilised) a CM5 chip to form the three individual PRUs (BIAcore AB Uppsala, Sweden) according to the manufacturers protocol, followed by contact with experimental samples comprising target proteins.
  • Table 1 shows the calibration binding phase data set obtained after 15 minutes of incubation with each calibration sample (association phase) applied individually, followed by 5 minutes washing (dissociation phase). Next the PRUs were regenerated and the association phase repeated (3 min incubation). Each indicator is a measurement (in arbitrary units) at the time point shown. Each indicator is the mean of two or three separate measurements for each individual sample used to calibrate each PRU. Table 1. Calibration Data
  • the total of the experimental sample measurements at each time point for a given PRU would be the same as the total of the indicators of binding of the calibration measurements at each time point for a given PRU (i.e. predicted indicators or values, see Table 2,).
  • the best fit (the predicted indicators or values) between the experimental data sets and the calibration data sets can be obtained by finding the best combination of the values of a "factor X" for each data set at each time point for a given PRU, where "factor X" is related to the absolute concentration of the components in the experimental sample.
  • the best fit was found by applying the Generalized Reduced Gradient (GRG2) non-linear optimisation algorithm (using Microsoft and Solver software).
  • GCG2 Generalized Reduced Gradient
  • the optimal fit is found by varying factor X such that the Covariance is maximal.
  • Table 3a shows data for a theoretical sample containing the target protein, lgG1 , at the same concentration used for the individual calibration of the PRUs
  • Table 3b shows theoretical data for a sample containing the target protein, lgG2, at the same concentration used for the individual calibration of the PRUs.
  • the indicators of binding for other target proteins used in the calibration but that are not present in the theoretical sample are all zero (i.e. not present).
  • an experimental sample contains one target protein for which a cognate PRU exists (i.e. a PRU reactive to the target protein) and the absolute concentration is the same as that used for calibration, then the predicted total binding indicators will be the same as the calibration values (see Tables 3a and 3b).
  • the model described above was used to characterise an experimental sample containing the target protein, lgG2.
  • a sample of lgG2 at the same concentration as that used for the calibration of the PRUs was contacted with the CM5 chip comprising the PRUs and measurements performed on a BIAcore 3000® machine (BIAcore AB, Uppsala, Sweden).
  • Table 5 shows the experimental data obtained after 15 minutes of incubation of the lgG2 target protein (association phase) with the PRUs, followed by 5 minutes washing (dissociation phase). Next the PRUs were regenerated and the association phase repeated (3 min incubation). Each indicator of binding is a measurement (in arbitrary units) at the time point shown.
  • the experimental sample was determined (predicted) to comprise lgG2 for 92.5% with the absolute concentration of the lgG2 in this sample being 0.877 units of concentration relative to the concentration of the lgG2 calibration sample used.
  • 100 - 98.3 1.7
  • the measurement of additional data sets will improve the accuracy of the method and increase the number of resolved proteins in a more complex sample.
  • PRU 1 comprised affinity reagents, anti-lgA, anti-lgG and anti-lgM target proteins; the major affinity reagent component of PRU 3 comprised an anti-lgG protein but it was also weakly reactive against other immunoglobulins; PRU 4 comprised Protein A as an affinity reagent.
  • the "predicted" indicators of binding for the dissociation phase were calculated separately, as arithmetic sums of the corresponding dissociation values for each of the affinity reagents used for calibration.
  • the model was used to characterise experimental samples comprising various target proteins.
  • association phase values except for 15min 35sec, 15min 40sec and 15min 45sec are shown relative to the binding reached after 1 minute of interaction.
  • the 15min 35sec, 15min 40sec and 15min 45sec values are absolute, i.e. relative to the background at time zero, prior to application of samples to the PRUs.
  • All "wash" values, except for recorded at 15min 45sec, are relative to the binding recorded after the 1 st minute of washing (dissociation) phase. The negative sign indicates that samples are washed away from the PRUs.
  • the washing recorded at 15min 45sec is the absolute value, i.e. the amount of the sample still bound to the PRUs at the end of recordings (relative to the time "0 min").
  • Table 8 shows binding data obtained for an experimental sample containing the target protein, hlgGI , at 10 ⁇ g/ml, i.e. the same concentration as used to calibrate the PRUs.
  • Table 9 shows experimental data obtained for an experimental sample containing the target protein, hlgGI , diluted 5 fold compared to that used in calibrations, i.e. 2 ⁇ g.ml.
  • both of these tables also list the best fit "predicted" values obtained based on the calibration binding data and the Sum of Squares (SUMSQ) value, used in optimisation of the fitting.
  • SUMSQ Sum of Squares
  • Table 10 summarises the results (target protein identity and concentration) as a relative quantitation (i.e. in units of concentration of the affinity reagent used for calibration) obtained in the above two examples as well as for a number of other experimental samples applied to the calibrated CM5 chip on which the PRUs were immobilised.
  • association phase values except for 15min 35sec, 15min 40sec and 15min 45sec are shown relative to the binding reached after 1 min of interaction.
  • the 15min 35sec, 15min 40sec and 15min 45sec values are absolute, i.e. relative to the background at time zero, prior to application of samples to the PRUs.
  • All "wash" values except for that recorded at 15min 45sec, are relative to the binding recorded after the 1 st minute of washing (dissociation) phase. The negative sign indicates that samples are washed away from the PRUs.
  • the washing recorded at 15min 45sec is the absolute value, i.e. the amount of the sample still bound to the PRUs at the end of recordings (relative to the time "0 min").
  • association phase values except for 15min 35sec, 15min 40sec and 15min 45sec are shown relative to the binding reached after 1min of interaction.
  • the 15min 35sec, 15min 40sec and 15min 45sec values are absolute, i.e. relative to the background at time zero, prior to application of samples to the PRUs.
  • All "wash" values except for that recorded at 15min 45sec, are relative to the binding recorded after the 1 st minute of washing (dissociation) phase. The negative sign indicates that samples are washed away from the PRUs.
  • the washing recorded at 15min 45sec is the absolute value, i.e. the amount of the sample still bound to the PRUs at the end of recordings (relative to the time "0 min").
  • Calibration binding phase data i.e. the values indicating the extent of binding
  • a single PRU PRU 4 from Example 2, see Table 7
  • Protein A reactive against a plurality of target proteins, i.e. immunoglobulins
  • the data fitting software contains two modules, the data parsing module (to read numerical data presented in a text format and to transform it into an ordered database), and the data fitting module, aimed to find the optimal combination of calibration samples (i.e. the sufficient number) required to fit the experimental data set corresponding to the "unknown" sample.
  • the raw data are selected and parsed into an ordered database.
  • a software user specifies which data should be used for calculations and can . omit data as required.
  • the software user specifies the data which corresponds to the calibration samples and which corresponds to that obtained from the experimental samples.
  • the experimental data is then compared to the calibration data mathematically to determine the best fit and hence determine the target protein composition of the experimental sample. Methods for making mathematical comparisons are routine and well known to those skilled in the art.
  • the best fit is obtained by minimising the sum of squares of deviations of each of the experimental data point from their predicted values, with the fitting based on the respective calibration samples data points.
  • the skilled person defines the nature of each data point recorded such that the binding phase is defined, for example, as an association phase (including a steady state phase), a dissociation phase data point, or an end point data point(s) (which also includes background data point)).
  • an association phase including a steady state phase
  • a dissociation phase data point or an end point data point(s) (which also includes background data point)
  • a 'weight' factor is included in the calculation. Weight factors are designed to help to compensate for the difference in the amount of data collected between association and/or dissociation and end point style data in order to compensate for any potential bias (in the SUM of SQUARES error calculation) towards one or another phase (association/dissociation or EndPoint data). In most cases equal weights are suitable (e.g. 1 and 1 , or 10 and 10, etc).
  • the weights may need to be adjusted (for example, but not limited to, 1 (for association) and 100 ((for the EndPoint data) in order to compensate a bias (in SUM of SQUARES error calculation) towards, in this example, an association state.
  • the weights are preferably found experimentally.
  • a weight function also allows a user to quickly "switch off" kinetic stages (i.e. association/dissociation) or EndPoint-style data in any application not requiring complete data sets.
  • the concentration of the samples used for calibration is entered as absolute values, for example but without limitation, as ⁇ g/ml; thus the concentration of the experimental sample is also expressed in these units.
  • the target protein concentrations within the experimental sample may be expressed as relative concentration units each compared to the respective calibration target protein concentration which need not be defined.
  • Experimental and/or calibration samples may be analysed singly, as duplicates, triplicates, etc as desired. Most preferably, when samples are duplicates or more, the mean of the data point is used in the comparison.
  • the software was used to identify the target protein composition and concentration within six experimental samples.
  • Input file six calibration standards. rpt Processing 1 channels : #4
  • the six numbers are the best values predicted based on the respective concentrations of each of the calibration target proteins, as if the experimental sample was a mixture of said calibration proteins.
  • the theoretically predicted best fit for this experimental sample indicates that the only target protein present is IgGI at a concentration of x ⁇ .95 relative to the concentration of the calibration standard.
  • the invention also provides a method for detecting at least one biomolecule within a sample comprising:

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Abstract

L'invention concerne un procédé pour déterminer la présence d'au moins une protéine cible dans un échantillon expérimental.
PCT/GB2003/000133 2002-01-11 2003-01-13 Analyse de la composition de proteines Ceased WO2003058250A2 (fr)

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GB9816514D0 (en) * 1998-07-29 1998-09-30 Smithkline Beecham Plc Novel method
EP1159615A2 (fr) * 1999-03-10 2001-12-05 National Institutes of Health, as represented by the Secretary, Department of Health and Human Services of the Government Systeme de groupement universel de proteines (upa)
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