Here we present a protocol to describe the development and validation of a single molecule array digital ELISA assay, which enables the ultra-sensitive detection of all IFN-α subtypes in human samples.
The main aim of this protocol is to describe the development and validation of an interferon (IFN)-α single molecule array digital Enzyme-Linked ImmunoSorbent Assay (ELISA) assay. This system enables the quantification of human IFN-α protein with unprecedented sensitivity, and with no cross-reactivity for other species of IFN.
The first key step of the protocol is the choice of the antibody pair, followed by the conjugation of the capture antibody to paramagnetic beads, and biotinylation of the detection antibody. Following this step, different parameters such as assay configuration, detector antibody concentration, and buffer composition can be modified until optimum sensitivity is achieved. Finally, specificity and reproducibility of the method are assessed to ensure confidence in the results. Here, we developed an IFN-α single molecule array assay with a limit of detection of 0.69 fg/mL using high-affinity autoantibodies isolated from patients with biallelic mutations in the autoimmune regulator (AIRE) protein causing autoimmune polyendocrinopathy syndrome type 1/autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy (APS1/APECED). Importantly, these antibodies enabled detection of all 13 IFN-α subtypes.
This new methodology allows the detection and quantification of IFN-α protein in human biological samples at attomolar concentrations for the first time. Such a tool will be highly useful in monitoring the levels of this cytokine in human health and disease states, most particularly infection, autoimmunity, and autoinflammation.
Type I IFNs are a family of cytokines which play a central role in orchestrating antiviral immune responses. They were first discovered by Isaacs and Lindenmann 60 years ago1,2 and it is now known that this heterogeneous family of polypeptides comprises 14 different subclasses (13 IFN-α subtypes and 1 IFN-β). Type I IFNs are essential to the clearance of viral infections, but have also been implicated in the pathology of a variety of human disease states, including the autoimmune disorders systemic lupus erythematosus (SLE), juvenile dermatomyositis (JDM), and the type I interferonopathies in which constitutive type I IFN-induced signaling results in pathology3,4,5,6,7.
Studying type I IFN protein levels in biological samples has been challenging since its initial identification as an "interfering substance"1,2. Currently, sandwich Enzyme-Linked ImmunoSorbent Assay (ELISA) is the most widely used method for detection of IFN-α protein. Despite being specific, simple, and rapid, type I IFN ELISAs present important limitations, such as limited sensitivity. In addition, the measurement of all IFN-α subtypes requires the use of multiple assays each with their own detection capacity and sensitivity. While there are commercial ELISAs that detect different subtypes of IFN-α, their sensitivity is limited (1.95 pg/mL, 12.5 pg/mL, and 12.5 pg/mL, respectively) which is often insufficient to detect IFN-α protein in biological samples. To overcome this limitation, several biological proxy assays have been developed to quantify type I IFN by measuring induced gene expression or functional activity8,9,10,11,12,13,14. Nonetheless, these assays do not provide a direct measurement of the IFN-α protein.
In this study, single molecule array digital ELISA technology was used to develop an assay for the detection of single IFN-α protein molecules. Digital ELISA utilizes the same basic chemistry as conventional ELISA, however, the reaction takes place in arrays comprising 50,000 individual 46 femtoliter sized wells15,16. Single protein molecules are captured by antibody-coated paramagnetic beads and labeled with a biotinylated detection antibody, followed by binding of an enzyme conjugate, streptavidin-β-galactosidase (SBG). Subsequently, the beads are suspended with a fluorogenic enzyme substrate, resorufin-β-D-galactopyranoside (RGP), into single-molecule arrays. By decreasing the volume reaction 2 billion times17, a high local concentration of fluorescent signal is achieved and single molecule counts become feasible, as each molecule generates a signal that can now be reliably measured18. In essence single molecule arrays are capable of counting single immunocomplexes and determining an average number of enzymes per bead (AEB). Counting the microwells in which a signal is detected permits quantification/digitalization of protein molecules, as there is a direct correlation between protein concentration and the ratio between immunocomplexed-beads and a total number of beads present in the femtoliter-sized chambers.
Yeung et al. performed an extensive cross-platform evaluation study using nine different technologies and four cytokine immunoassays with the aim of comparing assay precision, sensitivity, and data correlation across the different platforms19. One of the key findings of the study was that single molecule arrays and single molecule counting immunoassay presented the highest sensitivity for detection of cytokines in human serum within the sub-pg/mL concentration range. Single molecule array digital ELISA cytokine assays have been used to study the role of TNF-α and IL-6 in Crohn's disease20, IFN-α in interferonopathy and auto-immune patients 7, and the different post-translationally modified forms of C-X-C motif chemokine 10 (CXCL10) in chronic hepatitis and healthy donors receiving sitagliptin21,22. Other applications include measurement of rhodopsin in patients with diabetic retinopathy23; the study of brain pathologies through serum/plasma measurements of neurofilament light24 and amyloid-β 1-42 peptide25, in the context of multiple sclerosis and Alzheimer's disease, respectively. Single molecule array assays can also be used for improved pathogen detection such as characterization of the HIV viral reservoir26, and also for detection of DNA27 and micro RNAs28. A major advantage of the single molecule array technology is this high versatility, as an assay against any analyte of interest can be developed if a specific antibody pair is available. In addition, homebrew assay kits are commercially available, allowing the development of new assays, the protocol of which is detailed in a modified form below.
Here, a detailed description of the development and validation steps for a single molecule array assay is presented that results in enhanced sensitivity for IFN-α protein detection. Antibodies for single molecule array assays should be highly specific, avoiding cross reactivity with related proteins (with species specificity considered if relevant). Ideally, antibodies with a KD smaller than 10-9 M should be chosen; high affinity ensures strong binding, with the production of a higher signal. The kinetics of the antibody-antigen binding are also important, and fast Kon and slow Koff will favor antigen-antibody complex assembly. Starting with an antibody pair that has a good performance in classical ELISA, with a limit of detection (LOD) of 1 – 100 pg/mL, increases the chances of obtaining a highly sensitive single molecule array assay. Chang and colleagues performed detailed kinetic studies of the biomolecular interactions occurring at every single step, proposing a set of equations to predict analytical sensitivity18. They showed that single molecule array digital ELISA appears to be effective within a broad range of antibody affinities (KD~10−11 – 10−9 M), as well as that signal generation is more dependent on the on-rate of such antibodies.
To utilize high affinity antibodies we took advantage of antibodies isolated from patients with the autoimmune polyendocrinopathy syndrome type 1/autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy (APS1/APECED)29. For reasons that are not yet understood, the large majority of AIRE-deficient individuals develop a core set of high-avidity antibodies against all IFN-α subtypes29, and we selected two anti-IFN-α antibody clones of complementary binding affinities for the different IFN-α subtypes, as estimated by IC50 values. The combination of these unique high-affinity antibodies with single molecule array technology enabled the direct quantification of IFN-α at attomolar (fg/mL) concentrations. Such ultrasensitive IFN-α protein detection will contribute to a better understanding of the nature, regulation and biological impact of the IFN-induced response in different disease settings.
1. Selection of Antibodies
2. Conjugation of Capture Antibody to Paramagnetic Beads and Testing of Different Concentrations
NOTE: Always keep Bead Conjugation Buffer (BCB) and Bead Wash Buffer (BWB) on the ice during the antibody conjugation process.
3. Detection Antibody Biotinylation
4. Assay Optimization
NOTE: Use of the single molecule array analyzer software in a Homebrew configuration30.
The single molecule array analyzer machine is controlled by software that allows to run assay standardizations, to perform sample quantifications, to modify external parameters (bead, detector, SBG, RGP concentrations; sample dilutions…) and internal parameters (number of steps, incubation times…) to achieve optimal assay conditions, and can also be used to calculate results (background, LOD, quantities). For the setup of the single molecule array analyzer and to calculate the reagent volumes required for each round of optimization, see manufacturer's instructions. Perform the first rounds of optimization using a 2-step configuration.
Figure 1: Selection of antibody orientation, capture antibody concentration on beads and biotinylation ratio. The two possible different configurations were tested, using the anti-IFN-α A as capture antibody and anti-IFN-α B as detection antibody (A), and vice versa (B). IFNα-2c was used as antigen. Different capture antibody concentrations as well as biotin:antibody (B:A) ratios were also tested for both configurations. Dotted line shows LOD for the best condition; anti-IFN-α A 0.3 mg/mL as capture and anti-IFN-α B biotin:detector antibody ratio of 30 (LOD = 11.6 mg/mL corresponding to an AEB value of 0.017265). A 2-step configuration was used. Biotin:antibody (B:A). Please click here to view a larger version of this figure.
Figure 2: 2 vs 3-step configuration comparison. The 2 and 3-step configurations were assessed using 0.3 mg/mL of anti-IFN-α A antibody as capture and anti-IFN-α B as detection antibody in a 30 biotin:antibody ratio. IFNα-2c was used as antigen. In a 3-step condition setting, there are three different incubation steps, one with the capture antibody, one with the detection antibody and a final third one for the SBG enzyme labelling. However, in a 2-step configuration, capture and detection antibodies are incubated simultaneously with the analyte of interest. Please click here to view a larger version of this figure.
Figure 3: Detector and SBG concentration optimization. Three different concentrations of biotinylated detector antibody (0.1, 0.3, and 0.6 µg/ml) together with three different concentrations of SBG (50, 150, and 250 pM) were assessed. Dotted line shows LOD for the best condition; detector antibody at 0.3 mg/mL and SBG 150pM (LOD = 0.09 mg/mL corresponding to an AEB value of 0.017184). Please click here to view a larger version of this figure.
5. Assay Specificity and Reproducibility
Figure 4: Specificity and sensitivity of the optimized IFNα single molecule array assay. (A) IFN-β, IFN-λ1, IFN-λ2, IFN-ω, and IFN-γ recombinant proteins were tested, together with (B) 16 subtypes of IFN-α, including three IFN-α2 types (IFN-α2a, IFN-α2b, and IFN-α2c). Adapted from Rodero et al. 2017. Please click here to view a larger version of this figure.
Figure 5: Reproducibility of the optimized pan-IFN-α single molecule array assay. Three independent runs were performed using two different lots of beads. For the second lot, two independent experiments were performed. Each measurement was acquired in duplicates. The dotted line represents the LOD, defined by mean blank average enzyme per bead + SD of all runs. IFN-α17 was used as a reference, taking into account that the derived standard curve is representative of all other IFN-α subtypes, as shown in Figure 4b. Plot shows mean value and SD (error bars). Dotted lines show LOD for the different runs; Run 1: 0.073 fg/mL AEB = 0.006238, Run 2: 0.113 fg/mL AEB = 0.007119, Run 3: 0.043 fg/mL AEB = 0.05518). Adapted from Rodero et al. 2017. Please click here to view a larger version of this figure.
6. Protein Competition Assay
Figure 6: Protein competition assay. Competition experiments were performed using samples from five different SLE patients. Biological samples were centrifuged at 10.000 g for 15 min at 4 °C. They were diluted 1/3 with Detector/Sample diluent containing NP40 for viral inactivation. 15µl of anti-IFN-α antibody A (initial concentration 1 mg/mL, final concentration 50 µg/mL) or buffer were added to a total volume of 300 µL. Incubation was performed at room temperature for 30 min. Control group is shown in grey and samples treated with anti-IFN-α A antibody are shown in black. Graph shows mean value and SD (error bars). Dotted line represents LOD (AEB = 0.024774, 0.8037 fg/mL). Adapted from Rodero et al. 2017 Please click here to view a larger version of this figure.
In summary, a pan-IFN-α single molecule array assay with a limit of detection of 0.69 fg/mL, using a 2-step configuration with capture beads coated with 0.3 mg/mL of anti-IFN-α A antibody and anti-IFN-α B detection antibody biotinylated at a biotin:antibody ratio of 30 was developed. The concentrations used for biotinylated detection antibody and SBG were 0.3 µg/mL and 150 pM, respectively. This highly specific assay is capable of detecting all 13 IFN-α subtypes and does not cross react with other type of IFNs. Thus, while it is not possible to identify and quantify each individual species of IFN-α, all of them can be detected and measured together giving a total concentration value for IFN-α, that comprises the 13 different subclasses.
To explore the potential diagnostic value of this newly developed assay, IFN-α protein in plasma and serum from healthy individuals were measured and compared with samples from patients suffering from SLE and JDM. As illustrated in Figure 7, high levels of IFN-α protein were detected in both disease cohorts as compared to healthy controls. The dotted line indicates the LOD of a conventional commercially available ELISA, illustrating how this approach would not detect IFN-α protein in these patient groups despite the known associations of this cytokine with these phenotypes. Furthermore, IFN-α could be quantified over 5 logs of magnitude, illustrating the wide dynamic range of the assay, with detectable levels between 1 – 10 fg/mL confirming the highly sensitive nature of the assay.
Figure 7: Quantification of IFN-α protein in plasma and serum from patient cohorts. This figure has been modified from Rodero et al. 2017. Plasma from healthy controls (n = 20) and patients suffering from SLE (n = 72) and JDM (n = 43) were tested with the pan-IFNα single molecule array assay. Analysis was performed using one-way ANOVA test (Kruskal-Wallis) and Dunn's multiple comparison testing between groups. Median is depicted. Dotted line indicates LOD of a reference human anti-IFN-α ELISA (1.95 pg/mL = 1950 fg/mL). Please click here to view a larger version of this figure.
Step | Considerations | Reference |
1. Antibody pair choice | Target different epitopes | Table 2 |
High affinity | ||
Fast Kon / Slow Koff | ||
2. Antibody pair orientation | Choose conditions with the lowest Limit of Detection | Figure 1 |
3. Capture antibody concentration | ||
4. Biotin:Detector antibody ratio | ||
5. 2 vs. 3-step configuration | Choose condition with the highest Signal:Background ratio | Figure 2 |
6. Detector antibody concentration | Choose conditions with the lowest Limit of Detection | Figure 3 |
7. SBG concentration | ||
8. Specificity | Assess cross-reactivity | Figure 4 |
9. Sensitivity | Assess recognition of subtypes (if applicable) | |
10. Reproducibility | Assess assay variability | Figure 5 |
Table 1: Summary of steps for development and optimization of a single molecule array assay. This table summarizes the different steps required for the development and optimization of a single molecule array assay, from the initial choice of antibody pair until the assessment of reproducibility.
Antigen | 8H1 (A) | 12H5 (B) | Sifalimumab | Rontalizumab |
IFNα1 | 28.3 | 51.3 | 460 | 22.63 |
IFNα2 | 2563 | 10.7 | 9.02 | 2.15 |
IFNα4 | 5.11 | 2.99 | 35.35 | 325.3 |
IFNα5 | 2.01 | 19.6 | 93.29 | 2.49 |
IFNα6 | 64.7 | 3.03 | 4.97 | – |
IFNα7 | 0.9 | 0.63 | 233.1 | – |
IFNα8 | 302 | 0.83 | 691 | 10.86 |
IFNα10 | 2.54 | 0.71 | 43.2 | – |
IFNα14 | 3224 | 2.1 | 14.52 | 0.9 |
IFNα16 | 1.83 | 32.99 | 59.18 | 28.65 |
IFNα17 | 2.21 | 0.77 | 890.9 | 23.86 |
IFNα21 | 2.78 | 12.87 | 1769 | 5.8 |
Table 2: Pan-alpha antibody selection. IC50 (ng/mL) determined using the interferon-stimulated response element (ISRE)-Luciferase neutralization assay. Table shows IC50 values of mAbs used in single molecule array assay for all IFN-α subtypes. 10,000 HEK 293 MSR cells were seeded in white half-area 96-well plates and reverse-transfected with 50 ng premixed ISRE-Firefly luciferase reporter and Renilla luciferase constructs using transfection reagents according to the manufacturer's instructions. The luciferase-expressing construct served as an internal normalization control. Cells were incubated overnight in Reduced Serum Medium supplemented with 0.1 mM nonessential amino acids, 1 mM sodium pyruvate, 0.5% fetal bovine serum at 37 °C, 5% CO2 in a humidified atmosphere. After overnight incubation, cells were stimulated for 24 h with medium containing mixtures of recombinant human IFN-α with or without anti-IFN-α mAbs or control IgG that had been preincubated for 1 h at 37 °C. After 24 h of stimulation, dual luciferase reporter assays were performed according to the manufacturer's instructions. « – » Not determined. Sifalimumab is a fully human, immunoglobulin G1 κ monoclonal antibody that binds to and neutralizes the majority of IFN-α subtypes; Rontalizumab is a humanized monoclonal antibody against IFN-α. Adapted from Meyer et al. 2016 and Rodero et al. 2017.
Supplementary Table 1: Selection of antibody orientation, capture antibody concentration on beads and biotinylation ratio. The two possible different configurations were tested, using the anti-IFN-α A as capture antibody and anti-IFN-α B as detection antibody (A), and vice versa (B). IFNα-2c was used as antigen. Different capture antibody concentrations as well as biotin:antibody (B:A) ratios were also tested for both configurations. Saturation (Sat). Orange: AEB values that were used for LOD calculation; these concentrations were considered blank as the AEB values remained steady. LOD was calculated as Mean Blank + 3SD. Please click here to download this file.
Supplementary Table 2: Test of 2 vs 3-step configuration. The 2 and 3 -step configurations were assessed using IFNα-2c as antigen. AEB values as well as signal/background rations (S/B) are shown for both conditions. Please click here to download this file.
Supplementary Table 3: Detector and SBG concentration optimization. Three different concentrations of biotinylated detector antibody (0.1, 0.3, and 0.6 µg/mL) together with three different concentrations of SBG (50, 150, and 250 pM) were assessed. AEB values are shown for the nine tested conditions. Orange: AEB values that were used for LOD calculation; these concentrations were considered blank as the AEB values remained steady. LOD was calculated as Mean Blank + 3SD. Please click here to download this file.
Supplementary Table 4: Specificity and sensitivity of the optimized IFNα single molecule array assay. Average enzyme per beads values are shown when IFN-β, IFN-λ1, IFN-λ2, IFN-ω, and IFN-γ recombinant proteins were tested (A), together with the 16 subtypes of IFN-α (B). « – » Not determined. Please click here to download this file.
Supplementary Table 5: Reproducibility of the optimized IFNα single molecule array assay. The mean AEB values for all three independent runs are shown up to a concentration of 10.000 fg/mL. « – » Not determined. Saturation (Sat). Please click here to download this file.
Supplementary Table 6: Protein competition assay. Average enzyme per beads values are shown for all conditions tested. Measurements were done in duplicate. Please click here to download this file.
Herein, we described the development and validation of a highly reproducible, ultrasensitive single molecule array digital ELISA for direct quantification of IFN-α protein in human samples (steps summarized in Table 1). One of the most critical steps in the development of the assay is the choice of antibody pair16, with the characteristics in terms of kinetics and epitope binding being key to a successful assay. It is important to avoid the use of paired monoclonal antibodies that target the same epitope or that cause steric impediment. Polyclonal antibodies could be used as detection antibodies to overcome such limitations. If at any given step the desired sensitivity is not achieved, further optimization possibilities should be considered. This may include the use of alternative antibody pairs, changes in parameters such as protein type (e.g. BSA < casein), pH (6.0 – 8.5), ionic strength, buffering capacity (e.g. NaCl and phosphate concentrations), carrier beads, and/or presence of surfactants. A wide range of parameters con be optimized when developing a single molecule array assay. However, overall, conditions that give high signal:background ratios and minimal LODs are the ones preferred (see Figure 1, Figure 2, and Figure 3).
Regarding specificity, the IFN-α assay showed no cross reactivity for any other IFNs tested (β, γ, λ1, λ2, ω) (Figure 4a) and was capable of detecting all 13 IFN-α subtypes (Figure 4b). However, the assay showed a lower affinity for the IFN-α2 subtype, (Figure 4b and Supplementary Table 4). Interestingly, different sensitivities for the different classes of IFN-α2 (a, b, c) were also observed, which may be due to distinct manufacturing procedures or different amino acid sequences, as the IFN-α2 subtypes were obtained from different commercial suppliers. With this sole exception, all the IFN-α species gave very similar responses. The specificity of the assay was further demonstrated by pre-treatment of the samples with the anti-IFN-α A clone, which abrogated the signal (Figure 6 and Supplementary Table 6).
One of the main advantages of this technology is that any analyte of interest can potentially be targeted16. Furthermore, different biological specimens can be tested, such as serum, plasma, cerebrospinal fluid, cellular lysates, culture supernatants31 and even breath32. Usually, a 1:3 dilution of plasma is performed to avoid potential clogging of the single molecule array analyzer. However, the analyte of interest could be present at very low concentrations in the relevant biological sample and higher concentrations of sample might be required (depending on assay sensitivity)33. Although there is potential for multiplexing while maintaining good sensitivity34, it is a more challenging process and assays for measuring greater than 6 proteins within the same experiments have yet to be developed35.
The ability to detect and quantify cytokines and other biological relevant proteins at such low concentrations opens up a whole new range of applications33,36. It is well known that numerous proteins exert their effects even at very low concentrations, which up until now were below the limit of detection of the best ELISAs37. While other immunoassay technologies offer advantages over conventional ELISA19, we demonstrate here that single molecule array digital ELISA is a reproducible and robust platform for the ultrasensitive detection of low concentration cytokines in human samples. As such, this technology offers enormous potential for biomarker discovery and improved patient management of a wide range of diseases.
The authors have nothing to disclose.
DD and YJC acknowledge support from the ANR (Project IFNX, no. CE17001002) and ImmunoQure AG for providing monoclonal antibodies. We thank Brigitte Bader-Meunier, Nathalia Bellon, Christine Bodemer, Alex Belot, Isabelle Melki, and Pierre Quartier for providing clinical samples. YJC acknowledges the European Research Council (GA 309449: Fellowship to YJC), and a state subsidy managed by the National Research Agency (France) under the "Investments for the Future" program bearing the reference ANR-10-IAHU-01.
Anti-IFN-α antibody A (8H1 clone) | ImmunoQure AG | NA | Not commercially available |
Anti-IFN-α antibody B (12H5 clone) | ImmunoQure AG | NA | Not commercially available |
Anti-IFN-α antibody EBI-1 clone | eBioscience | BMS216C | |
Anti-IFN-α antibody BMS216BK clone | eBioscience | BMS216BK | Not an ELISA kit but bulk abs |
IFN α2c | eBioscience | BMS305 | OK |
IFN αI (17) | PBL | 11150-1 | |
IFN α2a | PBL | 11100-1 | |
IFN α2a | PeproTech | No longer available | |
IFN α2b | PBL | 11105-1 | |
IFN α1 | PBL | 11175-1 | |
IFN α4a (M1) | PBL | 11177-1 | |
IFN α4b (a4) | PBL | 11180-1 | |
IFN αB2 (a8) | PBL | 11115-1 | |
IFN αC (a10) | PBL | 11120-1 | |
IFN αD (a1) | PBL | 11125-1 | |
IFN αG (a5) | PBL | 11135-1 | |
IFN αF (a21) | PBL | 11130-1 | |
IFN αH2 (a14) | PBL | 11145-1 | |
IFN αJ1 (a7) | PBL | 11160-1 | |
IFN αK (a6) | PBL | 11165-1 | |
IFN αWA (a16) | PBL | 11190-1 | |
IFN λ1 | PeproTech | 300-02L | |
IFN λ2 | PeproTech | 300-02K | |
IFN ω | PeproTech | 300-02J | |
IFN β | PeproTech | 300-02BC | |
IFN γ | PeproTech | 300-02 | |
Anti-IFN-α ELISA | PBL | 41115.1 | |
96-well plates | Corning | 3904 | |
ISRE-Reporter | Qiagen | CCS-008L | |
Fu-GENE HD Transfection Reagent | Promega | E2311 | |
Opti-MEM Reduced Serum Mediuem | ThermoFischer Scientific | 31985062 | |
Dual-Luciferase Reporter assay | Promega | E1910 | |
Nonidet P40 Substitute | Sigma-Aldrich | 74385 | |
Spectrophotometer NanoDrop 1000 | Thermo Scientific | No longer available | |
Amicon micocentrifuge tubes – 0.5mL filtres | Merck Millipore | UFC505096 | |
Bead Conjugation Buffer | Quanterix | 102040 | Can not be ordered separately |
Non-Encoded Paramagnetic Beads | Quanterix | 101360 | |
Bead Wash Buffer | Quanterix | 102040 | Can not be ordered separately |
EDC | Fisher Scientific | 11844071 | |
Bead Blocking Buffer | Quanterix | 102040 | Can not be ordered separately |
Bead Diluent Buffer | Quanterix | 101362 | |
Detector and Sample Diluent | Quanterix | 101359 | |
Biotinylation Reaction Buffer | Quanterix | 102040 | Can not be ordered separately |
NHS-PEG4-Biotin | Fisher Scientific | 11891195 | |
diH2O | |||
Centrifuge for 1.7mL microcentrifuge tubes (Heraens Fresco 21 Centrifuge) | Thermo Scientific | 75002478 | |
Standard laboratory vortex mixer (MS2 Minishaker) | IKA | MS2 | |
Pipettes (10, 20, 200 and 1000 μl) | Thermo Scientific | ||
Tips (10, 20, 200 and 1000 μl) | Thermo Scientific | ||
1.7mL microcentrifuge tubes | Eppendorf | ||
Magnetic separator that accomodates 1.7mL microcentrifuge tubes (Life Technologies DynaMag-2) | ThermoFisher Scientific | 12321D | |
Mini benchtop centrifuge (Galaxy MinisStar) | VWR | 521-2844 | |
Mixer/Shaker (Eppendorf Thermomixer Comfort) | Eppendorf | ||
Single molecule array (Simoa) reagents | |||
SBG, Bead and Detector Barcode Labels | Quanterix | 101652 | |
15 mL Reagent Bottles | Quanterix | 102411 | |
Simoa specimen 96-well plates | Quanterix | 101457 | |
Simoa Discs | Quanterix | 100001 | |
Simoa 2.0 conductive Tips | Quanterix | 101726 | |
Simoa Cuvettes | Quanterix | 100803 | |
Simoa SBG Reagent | Quanterix | 102295 | |
Simoa RGP Reagent | Quanterix | 101736 | |
Simoa System Buffer 1 | Quanterix | 100486 | |
Simoa System Buffer 2 | Quanterix | 100487 | |
Sealing Oil | Quanterix | 100206 | |
ddH2O | |||
Simoa HD-1 Analyzer | Quanterix | 100032 | |
Technologies | |||
Single molecule array (Simoa) | Quanterix | ||
Single molecule counting Erenna Immunoassay Systems | Singluex |