Serological Profiling for Malaria Surveillance Using a Standard ELISA Protocol

Abstract

The enzyme-linked immunosorbent assay (ELISA) is a reliable and relatively low-cost method for measuring soluble ligands such as antibodies and proteins in biological samples. For analysis of specific antibodies in serum, a capture antigen is immobilized onto a solid polystyrene surface from which it can capture the antibodies. The captured antibodies are subsequently detected using a secondary antibody conjugated to an enzyme. Detection is accomplished by addition of a colorimetric substrate, and the readout is absorbance (optical density). Here, we provide a detailed standardized ELISA protocol for the quantification of antibodies against malaria antigens.

1. Introduction

Quantification of malaria-specific antibodies is important for the identification of correlates of protection or potential vaccine candidates, for surveillance of malaria transmission, and for evaluating the immunogenicity of malaria vaccines. The enzyme-linked immunosorbent assay (ELISA)-based approach has been used widely to quantify antibodies, replacing traditional methods such as the radioimmunoassay. The method is reliable, sensitive, reproducible, and relatively low-cost but is limited to measurement of one analyte at a time. Moreover, the volume of serum required increases in proportion with the number of antigens measured: a concern for field studies and clinical trials where serum volume may be limited.

Multiplexed assays are alternatives to the ELISA that can be used to simultaneously measure antibody responses to several antigens. Multiple antigens can be immobilized onto microspheres, beads (multiplexed bead array assay) or immobilized onto a solid matrix such as microarray slides or nitrocellulose membranes. In malaria, the multiplex bead and protein microarrays have been utilized for serological testing of up to 46 synthetic peptides [1] and over 1000 unique P. falciparum antigens [2, 3], respectively. A major advantage of the multiplex platform is that much more data can be obtained from a comparable volume of sample. The quantity of antigen utilized per assay is also considerably less than that in the ELISA. In addition, some studies have shown that these assays exhibit a wider dynamic range compared to the conventional ELISA [4, 5]. This linearity range is several orders of magnitude higher because of the wide dynamic range of fluorescence intensity compared with absorbance. As antibodies to different antigens occur at varying concentrations, a wide linear range is ideal for optimal quantification of concentrations. However, a major limitation of the multiplex bead-based assay is the need to have specialized technology to measure fluorescence of the beads such as flow cytometry or the Luminex system. Coupled to this is the expense: separate bead sets have to be purchased for each protein that is tested in a multiplex format. These costs can become prohibitive when both the number of samples and proteins to be tested is large. Protein microarrays are attractive with regard to high-throughput, minimal sample and antigen requirements [6]. However, as with the multiplexed assays, specialized equipment is required for slide printing and processing, as well as for data acquisition. The assay readout is based on advanced scanning technology, and the data have to undergo rigorous normalization processes before analysis.

With regard to ease of use and feasibility in resource-limited settings, ELISAs are widely accepted as the “gold standard.” The ELISA method was developed simultaneously and independently in 1971 by Engvall and Perlmann [7] and by van Weemen and Schuurs [8]. In its basic format, an antigen is immobilized onto a solid polystyrene surface from which it can capture soluble ligands such as antibodies. The captured ligand is subsequently detected using a secondary antibody conjugated to an enzyme. Detection is accomplished by addition of a colorimetric substrate, and the readout is absorbance (optical density) on a plate spectrophotometer. Here, we describe a standardized ELISA method for quantification of antibodies against malaria antigens.

2. Materials

1. Coating buffer: 15 mM Na₂CO₃, 35 mM NaHCO₃, pH 9.6. Weigh 1.59 g of Na₂CO₃ and 2.93 g NaHCO₃ in 1 L of distilled water. Mix and adjust pH to 9.6. Store at room temperature.

2. Wash buffer: 0.05% Tween 20 in 1 x PBS. Dissolve ten tablets of PBS in 1 L of distilled water, and add 500 μL of Tween 20.

3. Blocking buffer: 1% skimmed milk in wash buffer. Dissolve 1 g skimmed milk in 100 mL of wash buffer.

4. Secondary antibody: HRP-conjugated rabbit antihuman IgG.

5. Substrate solution: 0.1 M citric acid, 0.2 M Na₂HPO₄, o-phenylenediamine dihydrochloride tablets, hydrogen peroxide, and distilled water. To make up sufficient volume for one plate, dissolve 4 mg o-phenylenediamine dihydrochloride tablets in 5 mL distilled water. Add 2.4 mL of 0.1 M citric acid, 2.56 mL of 0.2 M Na₂HPO₄, and 8 μL of hydrogen peroxide.

6. Stop solution: 2 M H₂SO₄,

7. ELISA plates.

8. Microdilution tubes.

9. ELISA plate washer.

10. ELISA plate reader.

3. Methods

3.1. ELISA

1. Coat ELISA plates with 100 μL of the antigen. The appropriate coating concentration of the antigen is determined by titrating out the antigen (Fig. 1) (see Notes 1a, 2, and 3).

2. Incubate plates overnight at 4 ° C.

3. Wash the plates four times using an ELISA plate washer (see Notes 4 and 5).

4. Block the plates for 5 h with 200 μL of blocking buffer. Incubate the plates at room temperature (see Note 6).

5. Wash plates four times as above.

6. Incubate test samples; 100 μL/well at 1/1000 dilution in blocking buffer and leave overnight at 4 ° C. The appropriate serum dilution is determined by titration (Fig. 2) (see Note 1b).

7. Wash plates four times as above.

8. Incubate with 100 μL secondary antibody (1/5000, dilution in blocking buffer) for 3 h at room temperature. Determination of the optimal secondary antibody and serum dilutions can be performed simultaneously as shown in Fig. 2 (see Note 1c).

9. Wash plates four times as above.

10. Add 100 μL/well of substrate solution, and incubate for 15 min in the dark at room temperature.

11. Stop the reaction using 25 μL/well of 2 M H₂SO₄.

12. Promptly read the optical density (OD) at 492 nm.

Fig. 1.

The graph shows the optical density readings of pools of sera from malaria-exposed (red) and nonexposed donors (blue) at different concentrations of the coating antigen. The optimal coating concentration is shown by the black dotted line and corresponds to the maximum OD reading with low background and least antigen concentration

Fig. 2.

A checkerboard titration of a pool of malaria-exposed sera (1:500–1:100,000) and four secondary antibody dilutions: 1:5000 (red), 1:4000 (black), 1:2500 (green), and 1:1000 (orange). Serial dilutions of a pool of malaria nonexposed sera were also tested at 1:5000 secondary antibody dilution (gray). The appropriate serum dilution is shown by the vertical dotted line and clearly differentiates between the positive and the negative sera. The optimal secondary antibody dilution (horizontal dotted line) corresponds to the OD reading where the signal is strongest and the background is low

3.2. Data Quality and Analysis

1. Each plate includes blank wells, negative and positive controls (at least two blanks; two wells for positive controls; and a variable number on negative controls (2–20) depending on the total number of samples being tested and the purpose of the assay). Blank wells are used to establish the background or non-specific reactivity; ideally the reading of the blank well should be below 0.05 ELISA OD. If this is high, consider further optimization or subsequent subtraction of this reading from all wells. Negative controls are samples taken from malaria-nonexposed individuals. These samples are used to set threshold for seropositivity (usually mean plus three standard deviations of non-malaria-exposed sera). Positive controls include a pool of sera from long-term residents of a malaria endemic area. This pool allows for standardization of data across plates (plate to plate variation) and across days (day to day variation).

2. Serial dilutions of a pool of sera from malaria-exposed adults are included on every plate to generate a standard curve that allows for conversion of ELISA OD values to relative antibody units. Arbitrary units are assigned to this pool of serum.

3. Generate the standard curve using a five- or four-parameter logistic regression equation, and interpolate the concentration of the samples from this curve. Samples that fall outside the linear range of the standard curve (those with ODs above and below this range) are repeated at higher and lower dilutions, respectively.

4. All assays are conducted in duplicate. Once plate data are acceptable based on blank, negative, and positive controls, the coefficient of variation (CV) between duplicate test samples is calculated using the formula:

   $$\text{CV}=(\text{standard}\text{deviation}/\text{mean})\times 100\text{\%}.$$

   Samples with a CV of less than 20% are accepted, while those with a higher CV are retested.

5. For antigens that have a purification tag, e.g., maltose-binding protein (MBP) and glutathione S-transferase (GST), the final OD result is obtained by subtracting the OD result of the purification tag from that of the fusion protein.

3.3. Interpretation of Results

1. Samples are deemed seropositive if the ELISA OD value exceeds the cutoff, usually defined as the mean plus three standard deviations of non-malaria exposed sera.

2. Analysis and interpretation are dependent on the expected application of the results; the above represents the “standard” routinely used in studies of malaria immuno-epidemiology.

3.4. Data Reporting/Presentation

The magnitude of responses can be presented as raw ELISA optical density (OD) values [9, 10], end point titers [11, 12], or relative antibody units with reference to the units assigned to a pool of sera from malaria-exposed individuals [13] or a standard commercial reagent [14, 15]. Others have reported absolute antibody concentrations with reference to an antigen-specific standard [16] or using a mathematical conversion factor that converts arbitrary units to actual protein concentrations (in μg/mL) [17]. Calibration-free concentration analysis (CFCA) which measures the rate of binding of specific antibodies to their target antigens by surface plasmon resonance (SPR) also provides an absolute measure of antibody titers without using a standard [18, 19]. A standardized method of measurement and reporting of antibody responses would allow better comparison of data from different studies.

4. Notes

1. Titrations should be performed to determine the optimal antigen-coating concentration, serum dilution, and secondary antibody concentration to use in the assay:

   • (a)
     The optimal antigen-coating concentration should be at a point where there’s maximum OD reading with low background but with the least antigen concentration (Fig. 1).
   • (b)
     For serum, the optimal dilution factor should clearly differentiate between the positive and the negative controls (Fig. 2).
   • (c)
     The secondary antibody should be used at a dilution factor where the signal is strong and the background is low (Fig. 2).

2. The ELISA plate used to coat the antigen may need to be adapted for specific antigens; for example, if the antigen is biotinylated, one would need to use pre-coated streptavidin plates.

3. The coating buffer PH is crucial for effective immobilization on the plate; thus, for new assays it is important to test a number of coating buffers side by side for optimal antigen immobilization.

4. Do not allow the plate to dry completely at any step.

5. The plates can be washed manually.

6. Dilution of samples can be performed during this incubation period.

Acknowledgments

This paper is published with the permission of the director of KEMRI. F.H.A.O. is supported by an MRC/DFID African Research Leader Award jointly funded by the UK Medical Research Council (MRC) and the UK Department for International Development (DFID) under the MRC/DFID Concordat agreement (MR/L00450X/1); an EDCTP Senior Fellowship (TMA 2015 SF—1001); and a Sofja Kovalevskaja Award from the Alexander von Humboldt Foundation (3·2—1184811—KEN—SKP). L.M.M. is supported by the DELTAS Africa Initiative [DEL-15-003]. The DELTAS Africa Initiative is an independent funding scheme of the African Academy of Sciences (AAS)’s Alliance for Accelerating Excellence in Science in Africa (AESA) and supported by the New Partnership for Africa’s Development Planning and Coordinating Agency (NEPAD Agency) with funding from the Wellcome Trust [107769/Z/10/Z] and the UK government. The views expressed in this publication are those of the author (s) and not necessarily those of AAS, NEPAD Agency, Wellcome Trust, or the UK government. RKK and JT are supported by a Wellcome Trust Strategic Award (107499/Z/15/Z). GK was jointly supported by the MRC/DFID African Research Leader Award (MR/L00450X/1) and the DELTAS Africa Initiative [DEL-15-003].