Development and validation of a biosensor-based immunoassay for progesterone in bovine milk

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  • Development and validation of a biosensor-based immunoassay

    for progesterone in bovine milk

    Els H. Gillis a, James P. Gosling b, Joseph M. Sreenan c, Marian Kane a,*

    aNational Diagnostic Centre, National University of Ireland, Galway, IrelandbDepartment of Biochemistry, National University of Ireland, Galway, IrelandcAnimal Reproduction Department, Teagasc, Athenry, Co. Galway, Ireland

    Received 30 January 2002; received in revised form 22 April 2002; accepted 2 May 2002


    We have developed a rapid automated immunoassay, using the BIACOREk surface plasmon resonance (SPR) biosensor, tomeasure progesterone in bovine milk. The assay was designed as an inhibition assay with progesterone covalently immobilised

    to the carboxymethyl dextran matrix of a CM5 sensor chip. A fixed amount of monoclonal anti-progesterone antibody 39C5H7

    was mixed 9:1 with the sample and the amount of free antibody was then determined using biomolecular interaction analysis

    (BIA) by injection of the mixture over the immobilised progesterone sensor surface. The assay was designed to cover the

    concentration range 0.5 to 50 ng/ml. The limit of detection (LOD) was 3.56 ng/ml. Reproducibility of the assay was very good

    with both intra-assay and inter-assay coefficients of variation < 5%. As results become available within minutes of injection and

    the procedure involves fully automated instrumentation, we believe that this BIA assay for progesterone in milk could be used

    in-line in the milking parlour and, thus, provide an important tool for reproductive management of dairy cattle to detect heat and

    predict pregnancy.

    D 2002 Elsevier Science B.V. All rights reserved.

    Keywords: SPR; Biosensor assays; Progesterone; Heat detection

    1. Introduction

    Reproductive performance is a major factor affect-

    ing the production and economic efficiency of dairy and

    beef cow herds. According to Sreenan and Diskin

    (1992), a dairy herd is reproductively efficient when

    the calving interval is 365 days, when 90% of the cows

    calve in a 10-week period andwhen 5%or less cows are

    culled for reproductive failure. For herds using artificial

    insemination (AI), failure to detect heat is one of the

    major causes of a prolonged calving interval. Visual

    observation is currently the primary method for heat

    0022-1759/02/$ - see front matter D 2002 Elsevier Science B.V. All rights reserved.

    PII: S0022 -1759 (02 )00166 -7

    Abbreviations: AI, Artificial insemination; CV, Coefficient of

    variation; BIA, Biomolecular interaction analysis; CMO, Carbox-

    ymethyloxime; EDC, N-ethyl-NV(3-ethylaminopropyl) carbodiimide;ELISA, Enzyme-linked immunoassay; DMF, N,N-dimethylforma-

    mide; HBS-EP, HEPES-buffered saline; HEPES, N-[2-hydroxye-

    thyl]piperazine-NV-[2-ethanesulfonic acid]; LOD, Limit of detection;NHS, N-hydroxysuccinimide; SD, Standard deviation; SPR, Surface

    plasmon resonance.* Corresponding author. Tel.: +353-91-586559; fax: +353-91-


    E-mail address: (M. Kane).

    Journal of Immunological Methods 267 (2002) 131138

  • detection, but this is time consuming and repetitive.

    Farmers frequently achieve a heat detection rate of only

    3570% and up to 20% of cows presented for insemi-

    nation are not in heat (Sreenan andDiskin, 1992; Diskin

    and Sreenan, 2000).

    According to Senger (1994), an ideal system for

    detecting oestrous should have the following charac-

    teristics: (i) continuous surveillance of the cow; (ii)

    accurate and automatic identification of the cow in

    oestrous; (iii) operation for the productive life-time

    of the cow; (iv) minimal labour requirements; and

    (v) high accuracy and efficiency (95%) for identify-

    ing the appropriate physiological events that corre-

    late with oestrous or ovulation or both. Elevated

    milk progesterone concentrations indicate luteal

    dominance, while low amounts of progesterone are

    associated with oestrous. Progesterone measurement

    tests based on enzyme-linked immunoassays

    (ELISA) are available as kits for on-farm use (Nebel,

    1988). Most of these tests are, however, manual and

    designed as qualitative tests for the confirmation of

    oestrous and determination of pregnancy or non-

    pregnancy, rather than providing a precise concen-

    tration. Attempts at automation and in-line applica-

    tion of quantitative enzyme immunoassays for

    progesterone have been described (Koelsch et al.,

    1994; Claycomb et al., 1998; Pemberton et al.,

    2001), but, to date, such methods either suffer from

    poor sensitivity or are still too cumbersome for use

    in the milking parlour.

    Biomolecular interaction analysis (BIA) from Bia-

    core Ab uses the optical phenomenon of surface

    plasmon resonance (SPR) to monitor biomolecular

    interactions in real time without labelling. SPR meas-

    ures changes in refractive index of the solution close

    to the sensor surface, resulting from changes in the

    mass concentration of molecules in the solution

    (reviewed by Hashimoto, 2000; Markey, 2000). BIA-

    CORE instrumentation was developed primarily for

    use as a research tool, with a variety of applications

    such as screening biological samples for binding

    partners, the determination of kinetic and equilibrium

    constants for complex formation, epitope mapping

    and ligand fishing for known receptors. Recently, this

    principle has also gained popularity as an analytical

    tool for the determination of concentrations of analy-

    tes in biological fluids. In 1993, Minunni and Mascini

    described a BIACORE assay for the determination of

    the pesticide, atrazine, in drinking water, while Ster-

    nesjo et al. (1995) used a BIACORE to develop a

    biosensor-based immunoassay for the detection of

    sulfamethazine residues in milk. Since then, BIA

    assays have been described for other veterinary drug

    residues (Elliott et al., 1999; Gaudin and Maris,

    2001), toxins (Mullett et al., 1998; Daly et al.,

    2000) and vitamins (Bostrom Caselunghe and Linde-

    berg, 2000; Indyk et al., 2000).

    When compared to traditional techniques, BIA-

    CORE technology offers several significant advan-

    tages, such as high precision, speed, simplicity, and

    automation (Mellgren et al., 1996). This paper

    describes the development and validation, according

    to principles set out by Wong et al. (1997), of a BIA

    assay for real-time measurement of progesterone in

    bovine milk.

    2. Materials and methods

    2.1. Instrumentation

    A BIACORE 2000k biosensor instrument andCM5 sensor chips (research grade) were used (Biacore

    Ab, Uppsala, Sweden). The BIACORE 2000k wascontrolled by BIACORE Control Software version

    3.1.1 running underWindows 95. The software also in-

    cludes an interface to the separate BIAevalution soft-

    ware. The instrument running temperature was 25 jC.

    2.2. Reagents

    HEPES-buffered saline (HBS-EP) buffer pH7.4

    (10 mM N-[2-hydroxyethyl]piperazine-NV-[2-ethane-sulfonic acid] (HEPES), 0.15 M NaCl, 3.4 mM

    EDTA, 0.005% Surfactant P-20), and amine coupling

    kit (containing N-hydroxysuccinimide (NHS), N-

    ethyl-NV(3-ethylaminopropyl) carbodiimide (EDC),and ethanolamine hydrochloride) were obtained from

    Biacore Ab (Uppsala, Sweden). The Ridgeway milk

    progesterone ELISA was purchased from Ridgeway

    Science (Alvington, Gloucestershire, UK). Progester-

    one-3-carboxymethyloxime (CMO) was purchased

    from Steraloids (Wilton, NH, USA). Progesterone

    (MW 314.5) and N,N-dimethylformamide (DMF)

    were purchased from Sigma. All other reagents were

    of analytical grade.

    E.H. Gillis et al. / Journal of Immunological Methods 267 (2002) 131138132

  • 2.3. Monoclonal antibody

    The monoclonal antibody used was that described

    by ORorke et al. (1994). The antibody was raised

    against 11a-hydroxyprogesterone hemisuccinatebovine serum albumin conjugate, which was prepared

    by modification of the mixed anhydride method

    (Erlanger et al., 1957). Ascites fluid from mice

    infected with hybridoma cells secreting antibody

    39C5H7 was diluted 1/5000 in HBS-EP before use.

    2.4. Immobilisation of progesterone-3-CMO deriva-


    Simultaneous immobilisation of progesterone onto

    all four flowcells of a CM5 sensor chip was performed

    outside the biosensor system using conventional amine

    coupling (Sternesjo et al., 1995). For covalent immo-

    bilisation, carboxyl groups of the sensor chip surface

    are activated by derivatisation with N-hydroxysuccini-

    mide (NHS) mediated by N-ethyl-NV(3-ethylamino-propyl) carbodiimide (EDC). The resulting active

    ester groups will react spontaneously with amino

    groups (Johnsson et al., 1991). EDC and NHS were

    mixed (1:1) and 40 Al of the mixture were deposited onthe gold film for 10 min activation. An amine surface

    was then prepared by placing 40 Al of 1M ethylenediamine pH8.5 in contact with the activated surface for

    20 min. Capping any remaining active carboxyl groups

    was achieved by exposing the surface to 40 Al 1Methanolamine for 10 min. Progesterone-3-CMO (2 mg)

    was dissolved in 900 Al DMF and mixed with 450 Al of10 mM sodium acetate solution pH4.6 containing 5 mg

    EDC and 2 mg NHS. Progesterone was then immobi-

    lised on the surface by placing 40 Al of this solution incontact with the amine surface for approximately 15

    min. Prior to use, the immobilised surface was condi-

    tioned with repeated injections of 25 Al regenerationbuffer (10% acetonitrile in 50 mM NaOH) to remove

    any non-covalently bound progesterone.

    2.5. Milk samples

    Milk samples were collected from dairy cows

    throughout the oestrous cycle. Samples were collected

    into 10 ml plastic containers, with one Lactab mark III

    tablet (Thompson and Capper, Cheshire, UK) added as

    a preservative or alternatively 15 Al of 0.068 M sodium

    dichromate solution. Samples were then stored at 4 jC.Before analysis, samples were heated for 40 min in a

    water bath at 21 jC and dispersed by gentle mixing on arock and roller for 10 min. No difference was noted

    between the results obtained in the BIACORE assay

    with preserved or unpreserved milk samples.

    2.6. Assay

    Progesterone standards were prepared by dilution in

    preserved whole milk from an oestrous animal. The

    concentrations used to construct standard curves were

    0.5, 1, 2, 5, 10, 20, and 50 ng/ml (i.e. 3.18, 6.36, 15.9,

    31.8, 63.6 and 159 nmol/l). The curves were fitted

    using a four-parameter equation with BIAevaluation


    The assay was designed as an inhibition assay. A

    fixed amount of the monoclonal anti-progesterone

    antibody was mixed 9:1 with the standard/sample.

    The amount of free antibodies remaining was then

    determined by injection of 50 Al of the mixture overthe progesterone surface at a rate of 25 Al/min. Aftereach measurement the surface was regenerated by

    injection of 25 Al of 10% acetonitrile in 50 mMNaOH at the same flow rate. The analysis cycle time,

    including regeneration was 5 min 8 s.

    3. Results

    3.1. Stability of sensor chip during regeneration

    Regeneration performance was evaluated by re-

    peated analysis of a negative whole milk sample using

    the standard assay procedure. Baseline readings and

    antibody binding responses are shown in Fig. 1. The

    baseline response showed less than 1% change over

    129 cycles and the binding capacity was also unaf-

    fected, with less than 5% change being observed from

    the beginning to the end of the analysis. The progester-

    one sensor surface went through 3600 regeneration

    cycles over a 9-month period before any loss in binding

    capacity was observed.

    3.2. Limit of detection

    The assay was designed to cover the concentration

    range 0.5 to 50 ng/ml. The standard curve in Fig. 2

    E.H. Gillis et al. / Journal of Immunological Methods 267 (2002) 131138 133

  • represents the mean of 10 curves, obtained separately,

    eachwith triplicate concentrations of the standards. The

    precision of the response for each standard was < 7%

    coefficient of variation (CV). The limit of detection

    (LOD), determined as the concentration corresponding

    to the mean response for negative whole milk minus

    three times the standard deviation (SD),was 3.56 ng/ml.

    3.3. Reproducibility

    Repeated assays in one run (n= 15) of three quality

    control samples resulted in the following concentra-

    tion-dependent intra-assay CVs: at 3.5 ng/ml, 3.67%;

    at 18.41 ng/ml, 1.87% and at 56.03 ng/ml, 3.95%.

    Inter-assay variation (n = 10) was determined over 10

    consecutive assays using another set of control sam-

    ples and was 4.79%, 4.57%, and 3.85% at 3.25, 23.15

    and 48.81 ng/ml, respectively. The chip-to-chip vari-

    ability was examined by comparison of the standard

    Fig. 2. Standard curve of progesterone in bovine milk, produced on

    the BIACORE 2000k. The standard curve is derived from resultsfor 10 sets of standards analysed in triplicate. The error bars indicate

    the standard deviations.

    Fig. 3. Relationship between the effective volume of milk assayed

    and the concentration of progesterone measured. Milk samples were

    diluted 1/2, 1/5, 1/10 and 1/20 in negative whole milk before assay.

    Fig. 1. Baseline readings (.) and antibody binding response (o)following 129 successive antibody binding regeneration cycles

    over the progesterone coated surface with a negative whole milk


    Fig. 4. Regression analysis of the correlation between the Ridgeway

    ELISA and the BIACORE assay for progesterone in milk samples

    taken at various times during the oestrous cycle (n= 70). The inset

    graph shows the analysis of a subset of samples (n= 24) with

    progesterone concentrations lower than 15 ng/ml. The dotted lines

    represent the lines of perfect agreement and the solid lines the

    correlation plots.

    E.H. Gillis et al. / Journal of Immunological Methods 267 (2002) 131138134

  • curves obtained with three sensor chips coated at

    different times. The standard curves obtained were

    identical when overlaid (data not shown).

    3.4. Linearity/parallelism

    Milk samples from five animals were diluted 1/2,

    1/5, 1/10 and 1/20 in negative whole milk before

    assay. The amount of progesterone measured was

    directly related to the effective milk volume assayed

    over the range examined (Fig. 3), indicating minimal

    interference of the milk matrix. The lowest effective

    volume resulted in an over-estimation of progesterone

    for some samples but these were below the LOD of

    the assay. Regression analysis of the correlation

    between actual and measured values of diluted sam-

    ples confirmed linearity of the assay with R2 values

    > 0.98.

    3.5. Recovery

    Samples containing various levels of endogenous

    progesterone were spiked with 2, 5, 10 and 20 ng/ml

    progesterone. The total concentration of progesterone

    present in each sample was then determined to calcu-

    late the recovery in each case. The percentage recov-

    ery ranged from 88.9% to 112.4%, the mean was

    101.7% (F 7.8 SD, n = 12).

    3.6. Correlation with Ridgeway ELISA

    Seventy samples collected at various times through-

    out the oestrous cycle were analysed by both the

    Fig. 5. Comparison of standard curves obtained by the BIA assay

    (.) and the Ridgeway ELISA (o) for progesterone in bovine milk.Duplicate readings for each assay are indicated on the graph.

    Fig. 6. Progesterone levels estimated by the BIA (.) and the Ridgeway assay (o) in daily milk samples. These milk samples were collected for26...


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