Interactions of the Human Recombinant Proteins JUNO and IZUMO1

(1)

Interactions of the Human Recombinant Proteins JUNO and IZUMO1

A master thesis project by Emma Lundell

Department of Industrial Biotechnology in cooperation with Spermosens AB

Prof. Per Berglund Lic. Kushagr Punyani

August – December 2019

(2)

2

Acknowledgements

Jag vill tacka Per Berglund som har varit en fantastisk handledare och alltid varit ett bollplank när jag har behövt det.

Thank you, Kush Punyani and Mohamad Takwa, for giving birth to the idea of an exciting project that came to be my master thesis.

Tack Johan Nilvebrant och Per-Åke Nygren för all er hjälp med Biacore, era idéer och för allt ni lärt mig.

Tack Adam för att du har korrekturläst och stöttat mig under de sista intensiva veckorna.

(3)

3

Sammanfattning

Det uppskattas att 15% av alla par världen över lider av infertilitet. Ungefär hälften beror på manlig infertilitet och 40% av dessa fall kan ännu inte förklaras. Därmed är nuvarande metoder för att diagnostisera manlig infertilitet otillräckliga och ytterligare tekniker behövs. En lyckad befruktning kräver att spermierna uttrycker membranproteinet Izumo1 som måste känna igen dess receptorprotein Juno, belägen vid ytan av äggmembranet. Bindningen mellan Juno och Izumo1 är essentiell för befruktning hos däggdjur då den bidrar till att gameterna binder och skapar en ny distinkt organism.

Juno är ett relativt nyupptäckt protein och mekanismen med Izumo1 är fortfarande okänd.

Ett nystartat företag vid namn Spermosens vill mäta interaktionen mellan Juno och Izumo1 i ett nytt diagnostikverktyg som ska diagnostisera manlig infertilitet. Tanken är att Juno ska immobiliseras på guld-nanopartiklar och användas för att mäta interaktionen med spermaprover. Det nya verktyget ska hjälpa par att fastställa felet i befruktningen, vilket som en följd skulle hjälpa paret att välja lämplig assisterad reproduktionsmetod. I utvecklingen av det nya diagnostikverktyget behöver det konfirmeras att den Juno som används i enheten kan binda korrekt till mänskligt Izumo1. Därför måste interaktionerna mellan de mänskliga, rekombinanta proteinerna Juno och Izumo1 mätas och karakteriseras.

Syftet med detta projekt var att utveckla en metod för att immobilisera Juno på guld-nanopartiklar och sedan mäta interaktionerna med Izumo1 genom UV-Vis spektroskopi. Detta är teoretiskt möjligt eftersom guld-nanopartiklarna framkallar ett fenomen som kallas lokaliserad ytplasmonresonans som varierar beroende på storleken på guld-nanopartikelkomplexet. Immobiliseringsmetoden var en process som involverade flera steg som designades, polerades och förbättrades under arbetets gång.

Dithiobis(C2-NTA) konjugerades till guldytan och koboltjoner konjugerades till NTA. Det sista steget som innebar konjugering av Juno till kobolt genom en His-tag lyckades inte, och interaktionerna kunde därför inte mätas genom denna metod.

Istället mättes protein-protein-interaktionen genom SPR-mätningar med Biacore, ett instrument som också är baserat på ytplasmonresonans. Interaktioner mellan Izumo1 och Juno kunde uppmätas både vid användning av Juno producerad från E. coli och från däggdjursceller. Dissociationskonstanten (Kd) beräknades till 7-33 nM (för Juno och Izumo1 producerade i däggdjursceller) vilket kan jämföras med ett experiment från 2016 där 48 nM beräknades. Ett mer exakt Kd kunde inte fastställas och en trolig anledning till detta var att regenereringen av sensorytan som utfördes med NaOH varierade i effektivitet, vilket ledde till en osäkerhet då ytförhållandena kan ha varierat mellan mätningarna. De två Juno- proteinerna, som är producerade i olika organismer, visade två skilda affinitetsprofiler med Izumo1 vilket tyder på att glykosyleringen påverkar bindningsmekanismen mellan Juno och Izumo1.

(4)

4

Abstract

It is estimated that 15% of all couples worldwide suffer from infertility. Roughly half is male-factor infertility and 40% of these cases cannot be explained. Thus, current methods for diagnosing male infertility are not enough and further techniques are needed. To have a successful fertilisation event, it is required that the sperm expresses membrane surface-protein Izumo1 which must recognise its counterpart protein Juno, located at the surface of the egg membrane. The recognition step between Juno and Izumo1 is essential in mammalian fertilisation for the gametes to bind and start the creation of a new distinct organism, but the molecular mechanism is still unknown.

A start-up company named Spermosens want to measure the Juno-Izumo1 interaction in a new diagnostic device designed to diagnose male infertility. The idea is to have Juno immobilised on gold nanoparticles and measure the interaction between Juno and various semen samples. The new device is supposed to help couples pin-point the procreation issue which would help in the selection of suitable assisted reproductive technology. In the development of the new device, it had to be established that the Juno used in the device will bind correctly to human Izumo1. Therefore, the interactions between the human recombinant proteins Juno and Izumo1 had to be measured and characterized.

The objectives of this project were to develop a method to immobilise Juno on gold nanoparticles and then measure the interactions with Izumo1 using UV-vis spectroscopy. This is theoretically possible since the gold nanoparticles exhibit a phenomenon called localized surface plasmon resonance that vary depending on the size of the gold nanoparticle-complex. The immobilisation procedure was a process involving several steps that were designed, polished and improved along the way. Dithiobis(C2-NTA) was conjugated to the gold surface and a cobalt ion was conjugated to the NTA. The last step involving conjugation of Juno to the cobalt through a His-tag was not succeeded, and the interactions could therefore not be measured this way.

Instead, the protein-protein interaction was measured through SPR-measurements using Biacore, an instrument that is based on surface plasmon resonance as well. Interactions between Izumo1 and Juno could be detected using Juno produced in E. coli and in mammalian cells. The dissociation constant (Kd) could be calculated to 7-33 nM which can be compared to a previously published Kd of 48 nM. A more precise Kd could not be established, possibly due to that the regeneration of the sensor surface with NaOH varied in efficiency, leading to changing surface conditions during the measurements. The two Juno proteins, that were produced in different hosts, showed two different affinity profiles with Izumo1, which contributes to the suggestion that the glycosylation plays a role in the binding mechanism between Juno and Izumo1.

(5)

5

1 Abbreviations

Izumo1 Izumo sperm-egg fusion protein 1

Juno Folate receptor 4, Izumo1R

GPI Glycosylphosphatidylinositol

ART Assisted Reproductive Technology

IVF in vitro fertilisation

ICSI Intracytoplasmic Sperm Injection

AuNP Gold Nanoparticle

SPR Surface Plasmon Resonance

LSPR Localized Surface Plasmon Resonance

UV-VIS Ultraviolet-visible

OD Optical Density

MLWA Modified Long Wavelength Approximation

RT Room Temperature

NTA Nitrilotriacetic acid

BSA Bovine Serum Albumin

C2-NTA 3,3'-Dithiobis[N-(5-amino-5-carboxypentyl)propionamide-N,N'-diacetic- acid] dihydrochloride

EDTA Ethylenediaminetetraacetic acid

NMWL Nominal Molecular Weight Limit

PBS Phosphate-Buffered Saline

HEPES 2-[4-(2-hydroxyethyl)piperazin-1-yl]ethanesulfonic acid SDS-PAGE

Sodium Dodecyl Sulfate–Polyacrylamide Gel Electrophoresis

Fc Flow cell

(8)

8

2 Introduction

How many couples that today suffer from infertility is extremely difficult to estimate due to lack of reports, varying definitions of infertility and the presence of both male and female parameters.

According to the World Health Organization, the global infertility is estimated to 10-25%, a number that is most likely underestimated.¹ Historically, the cause of an unsuccessful pregnancy has been blamed on the female. Back in the 1940s when infertility became a spoken topic, doctors diagnosed women with sterility based on various made-up psychiatric problems, suggesting for example that an unconscious hatred towards their husbands’ was causing the lack of pregnancy.² Medical diagnostic procedures and treatments were eventually evolved and improved, but the focus remained on the woman.

As a consequence today, there exist many diagnostic techniques to investigate female infertility and fewer methods for diagnosis of male infertility. Today we know that male infertility accounts for roughly 50% of the infertility cases and that the causes can be many. Even though a range of diagnostic techniques exist today, more than one out of three male infertility cases are still unexplained, thus further techniques are needed.³

3 Background

3.1 Current diagnostic methods

The commercial methods for semen analysis currently used investigate the physical aspects of sperm quality in terms of semen volume, sperm number and concentration, sperm motility, vitality and sperm morphology^4,5. These analyses may not be able to establish an error in the actual fertilisation process between the sperm and egg cells, which might be the infertility cause in several cases. Further diagnostic techniques that are addressed to the biochemical interactions during the fertilisation are thus needed.⁴

3.2 Fertilisation

Fertilisation is an important biological process in human reproduction and involves interactions between egg and sperm. A male and a female gamete (sperm and oocyte/egg cells) are fused together to form a new, genetically distinct organism, a process involving biochemical interactions between receptor proteins on the gamete surfaces. Although several surface proteins have been identified, the molecular mechanism of gamete recognition in mammals has not yet been established. The major reasons for this are the scarceness of oocytes and the difficulties that arise when solubilizing membrane-bound proteins.

However, studies in 2014 found a vital recognition between a sperm cell-surface protein named Izumo1 and its receptor Juno (Izumo1R) that is present at the oocyte surface, see illustration in figure 1.

Knockdown of either protein in mice yields infertile organisms, suggesting that the receptor pair recognition is essential for mammalian fertilisation.^6,7

(9)

9 Merging of two gametes is conducted in a two-step mechanism in which Izumo1 first recognises Juno on the egg cell surface which is followed by a second step where the two plasma membranes are fused together.⁷ A study from 2005 showed that Izumo1-deficient sperm combined with healthy oocytes yielded no offspring but was proven effective if it was injected directly into the cytoplasm of the oocyte,⁸ suggesting that the Izumo1-Juno interaction provides an essential adhesion step for the fusion of the two gametes.⁹ After successful fusion, the genetic information from the sperm and oocyte are combined into a zygote that will hold all the genes necessary for the creation of a new organism.¹⁰

Figure 1: Izumo1 can bind to Juno when the sperm has reached the oocyte membrane.

Mutagenesis studies show that Juno and Izumo1 are connected through multiple van der Waals, aromatic, electrostatic and hydrophobic interactions.⁷

3.2.1 Juno

Juno is a glycosylphosphatidylinositol-anchored (GPI-anchored) globular protein consisting of five short alpha-helices, three 310-helices and two antiparallel beta-sheets containing two strands each (see figure 2).⁷ Even though the prominence of the Izumo1-Juno interaction seems to be restricted to the fusion process of the plasma membranes, Juno is thought to have further functions after the fertilisation has occurred. When sperm and oocyte have fused, the oocyte performs several mechanisms to prevent additional sperm from binding (polyspermy) and creating an inviable polyploid embryo. For instance,

(10)

10 the zona pellucida, a glycoprotein layer surrounding the oocyte, will harden and become less permeable.

Furthermore, it has been discovered that Juno is shed from the membrane surface almost instantaneously after the fusion and ends up in extracellular vesicles. The quick loss of Juno from the surface is possibly a part of the membrane block to prevent polyspermy in mammals.⁹

Figure 2: Structure of Juno in orange (pdb 5f4q).

3.2.2 Izumo1

The extracellular domain of human, unbound Izumo1 (residues 22-254) is shaped like a boomerang and consists of two domains that are connected through a hinge consisting of two antiparallel beta-strands (figure 3). One domain constitutes a bundle of four alpha-helices, while the other is an immunoglobulin (Ig) domain containing seven ꞵ-strands in two sheets connected through a disulphide bond. While the seven stranded ꞵ-sandwich reminds of an Ig-domain, it is here organised in an 5+2 manner compared to previously 3+4 organisations, suggesting that the Izumo1 Ig-domain belongs to a new subtype of Ig- superfamilies.⁷

Figure 3: Structure of Izumo1 showing alpha-helices in green, hinge in yellow and immunoglobulin-domain in red (pdb 5jk9).

(11)

11

3.3 Assisted reproductive technology 3.3.1 Traditional in vitro fertilisation

The most well-known assisted reproductive technology (ART) used today is traditional in vitro fertilisation (IVF) where the fertilisation event occurs outside of the body. Eggs are produced from the female reproductive tract after hormonal stimulation and allowed to interact with the male partner’s sperm in laboratory environment. After a sperm has fertilised the egg, the zygote is grown in artificial media for a few days before the formed embryo is put back into the uterus where it can continue to grow into a fetus.¹¹

3.3.2 Intracytoplasmic sperm injection

Another in vitro fertilisation method used today is intracytoplasmic sperm injection (ICSI) where a sperm is directly inserted into the egg through a glass needle. This procedure is often used in case of low sperm count since ICSI entails only one single sperm whereas classic IVF requires thousands of sperms. Although debated, ICSI has in certain cases shown an increased risk of sex chromosomal anomalies within the infants.¹²

3.3.3 IVF success rates

The success rate for couples having a baby through IVF in Sweden is 27% (birth rate per cycle) for women under 30 years, a rate that decreases as the woman’s age increases.¹³ In Sweden, the fertility treatments are performed both at hospitals and at private clinics. Since the IVF-treatments are expensive and time consuming, the free health care only provides a limited number of IVF-cycles (usually 2-3 but it depends on the region) and the waiting list can be up to two years.¹⁴ At the private clinics there is minimal waiting but the couple must pay for the IVF-treatment themselves at a cost that lies around 39 000 kr/cycle¹⁵, which is low in comparison with other countries that provide similar care. Since less than one out of three IVF-cycles yields a baby, couples often need to undergo several cycles before the treatment is successful. Each cycle is wearisome for the woman who needs to undergo hormonal treatment and retrieval of eggs through a needle in the ovaries¹². Moreover, performing cycle after cycle without success and without knowing if the treatment is ever going to work is emotionally exhausting for the couple in question. Undoubtedly, the doctor and couple need further information on where the issue in the fertilisation process lies, to be able to make a rational decision regarding the course of treatment.

3.3.4 Better ART-selection with new diagnostic device

The start-up company Spermosens are developing a new diagnostic device with the goal of diagnosing male infertility based on the interactions of the egg and sperm. The new technology will enable a

(12)

12 simulation of the fertilisation that can establish if the biochemical interactions of the gametes are working properly. Knowing that the sperm cannot bind well to the egg cell surface would rule out traditional IVF and save the couple and the healthcare money, time and trouble on several IVF-cycles that are never going to work. It would give the couple the possibility to choose their course of action at an earlier stage; they could rationally select between ICSI, sperm donation, adoption etc. before having to go through several unsuccessful IVF-cycles.

The diagnostic device that is being developed will contain Juno, and sperm samples will be tested by measuring the interaction between Juno and Izumo1. Juno will be immobilised on gold nanoparticles that will work as a biosensor and enable analysis of the interaction, see figure 4.

Figure 4: Overview of the diagnostic device that is currently being developed by Spermosens.

A semen sample will be loaded (3) into the electrochemical workstation in form of a chip (2) where the biosensor electrode (1) will give an electrochemical signal (5) as the sperms bind to Juno, which is immobilised on gold nanoparticles (4).

(13)

13

3.3.5 Kinetics & Affinity

To describe the binding affinity between biomolecules, e.g. a protein and its ligand, the dissociation constant is often used. For a model reaction in equilibrium such as:

𝑃 + 𝐿 𝐾_𝑎

⇌ 𝐾_𝑑

𝑃𝐿

the dissociation constant, Kd, is defined as:

𝐾

_d

=

^[𝑃][𝐿]

[𝑃𝐿] (1)

where [P], [L] and [PL] are molar concentrations of the protein, ligand and protein-ligand-complex respectively. As can be deducted from equation 1, a small Kd-value equals a strong binding since we then have a small ratio of free ligand vs. bound ligand. Sometimes the association constant Ka is used, which is the inverse of the dissociation constant and we thus expect it to be large for a strong binding.

The protein-ligand binding is reversible, and the forward and backward reactions that occur simultaneously are described in equation 2 and 3. At equilibrium, the forward and backward reactions have the same reaction rates (equation 4). 𝑟_a, 𝑘_a, 𝑟_b and 𝑘_b are reactions rates and reaction rate constants forward and backward respectively.

𝑟_a= 𝑘_a[𝑃][𝐿] (2)

𝑟_b = 𝑘_b [𝑃𝐿] (3)

𝑟_a= 𝑟_b (4)

Combining equation 1-4 generates equation 5 that shows the correlation between the dissociation constant and the reaction rate constants at equilibrium.

𝐾

_d

=

^[𝑃][𝐿]

[𝑃𝐿]

=

^𝑘^b

𝑘_a (5)

In an equilibrium binding experiment, the protein concentration is kept constant while the amount of ligand is increased until the maximum response is reached, and no more ligand can bind. The binding response is plotted against ligand concentration and the aim is to find Kd, which is the concentration where half of all binding sites are occupied by ligands.¹⁶

(14)

14

3.4 Optical properties of noble metal nanoparticles

Noble metal nanoparticles are today widely used for various applications in the fields of biology and technology.¹⁷ The most frequently used noble metals for nanoparticles are gold and silver due to their low reactivity, high stability and biocompability, which makes them easy to work with and well suited for biomedical applications.¹⁸ Furthermore, these particles exhibit unique optical properties that can be exploited for medical and diagnostic purposes as they are non-toxic. The optical properties that these nanoparticles display are due to an interaction between light and electrons at the particle surface that gives rise to a phenomenon called localized surface plasmon resonance (LSPR) seen in figure 5. Light at the appropriate wavelength causes collective oscillation of the electrons which leads to an enhancement in the electric fields near the particle surface, resulting in a strong absorption and scattering of light.^17,19 The LSPR of the nanoparticles generates a strong absorption band around 500-700 nm and can thus be measured using UV-VIS spectroscopy. The absorption, or optical density (OD), has a linear correlation to the nanoparticle concentration in solution.²⁰ The surface plasmon resonance is dependent on both shape and size of the particles; as the size or irregularity of the nanoparticle surface is altered, the local refractive index on the particle surface will be different and lead to a shift in the LSPR peak frequency, which is visualized as a shift of the absorption maxima.¹⁷

Figure 5: Localized surface plasmon resonance of gold nanoparticles is induced by light of appropriate wavelength.

To explain or understand the parameters that affect the increased absorption and scattering, the Mie theory is often suggested. The theory, which is named after the German physicist Gustav Mie, is a solution to Maxwell’s equations. Spherical boundary conditions enable description of the extinction coefficient, 𝐶_𝑒𝑥𝑡, for spherical nanoparticles. An extension of the theory called the Modified Long

(15)

15 Wavelength Approximation (MLWA) allows for more accurate calculations of different particle shapes and of dielectric constants at various wavelengths:²¹

𝐶

_𝑒𝑥𝑡

=

^{24 𝜋}²^𝑅³^𝜀^𝑚

3/2𝑁 𝜆 ln (10)

𝜀_𝑖

(𝜀_𝑟+𝜒𝜀_𝑚)²+𝜀_𝑖² (6)

R = particle radius εm= dielectric constant of surrounding media N = electron density λ = wavelength of light beam

χ = particle shape factor ε = εr + iεi= complex dielectric constant of the metal in bulk

Equation 6 shows that the resonance is affected by several factors such as particle size and shape (as mentioned earlier), the wavelength of the incident light and choice of metal and surrounding media. It is thus possible to detect a biomolecule that interacts with the particle surface, since the increased size and altered shape of the particle complex will result in a so-called redshift (increase of wavelength) which is illustrated in figure 6.

Figure 6: UV-vis spectrum of spherical gold nanoparticles before (blue) and after (green) immobilisation of a biomolecule.²⁰

The redshift, Δ𝜆, is often described by equation 7.²¹ All these parameters are responsible for the size of the LSPR shift and gives noble metal particles their unique sensitivity towards interacting

biomolecules.

Δ𝜆 = 𝑚(Δ𝑛) [1 − exp (^−2𝑑

𝑙𝑑 )] (7)

m = refractive index sensitivity ∆n = change in refractive index

d = thickness of adsorbent layer ld= length of electromagnetic field decay

(16)

16 Monodisperse gold nanoparticles (size 15 nm) in colloid solution have a red colour and absorb around 520 nm whereas agglomerated gold nanoparticles are blue/violet in solution and absorb at a higher wavelength and give broader peaks, as can be seen in figure 7.

Figure 7: UV-vis spectrum of A: monodisperse and B: agglomerated gold nanoparticles (spherical with size 15 nm).¹⁷

3.5 SPR-based Biosensors

Biosensors are used for detection of chemical substances and consist of one biological element that recognises the analyte and one detector element that can transform one signal into another through physicochemical properties. Biomolecules, such as proteins, have binding sites that only interact with specific ligands and can be functionalized to the surface of noble metal nanoparticles without losing their biological activity. As mentioned earlier, the LSPR is extremely sensitive to changes in the refractive index at the nanoparticle surface and can thus detect interacting biomolecules. The great specificity of a protein scaffold in combination with the high sensitivity of a noble metal nanoparticle creates an optimal biosensor that is of interest to several research areas today.²²

3.5.1 Gold nanoparticles as biosensors

When it comes to immobilisation of proteins such as enzymes, antibodies, antigens or other biomolecules, gold nanoparticles are the most commonly used nanomaterials. One example where gold nanoparticles are used as biosensors is in the detection of algal toxins in freshwater and seafood. As the algal bloom is increasing globally today in marine waters creating a threat towards aquatic and human life, new detections methods have been exploited. Biosensors have successfully been used to screen seafood and freshwater samples for harmful algal toxins; biomolecules with the toxin as target was immobilised on gold nanoparticles and the biorecognition signal was transduced optically or electrochemically.¹⁸

(17)

17

3.5.2 Biosensing with Biacore

Commonly used instruments for biomolecular interaction assays are the Biacore systems. Involving a thin gold layer, the technique is based on the same principle as gold nanoparticle biosensors, namely surface plasmon resonance (SPR). Similarly to the nanoparticle biosensors, a biomolecule is immobilised on a gold surface, called the ‘ligand’ (see figure 8), and then the association and dissociation of an ‘analyte’ can be followed due to the change in refractive index. The analyte solution is injected in a continuous flow over the ligand at different known concentrations and the generated data is used to calculate kinetic and affinity parameters.

Figure 8: Illustration of the ligand-analyte interaction in Biacore instruments.

The signal over time is visualised in a sensorgram which is a plot where the response signal is measured in resonance units (RU), an example is shown in figure 9. The ligand can be attached in many ways, and two main approaches are used for binding measurements; single-cycle and multi-cycle kinetics.¹⁶

Figure 9: Example of a typical sensorgram. (1) Stable baseline, (2) Positive response signal during association, (3) Stable response during combined association/dissociation, (4) Negative response during dissociation, (5) Stabilisation of baseline.

3.5.2.1 Immobilisation of ligand

The gold surface is located in a sensor chip that usually is coated with carboxymethyl-dextran residues (CM-series sensor chips). The ligand can basically be immobilised in one of two ways; through

(18)

18 covalent immobilisation or high affinity capture. During covalent immobilisation, the ligand binds irreversibly to the carbomethyl groups and remains bound throughout the lifetime of the chip. In high affinity capture, a specific capture molecule is covalently immobilised to the surface and is then used to attach the ligand.

3.5.2.2 Reference surface

As always when performing measurements, it is important with a reference. The sensor chip contains several flow cells where at least one, normally flow cell 1, is used as a reference surface where no ligand is attached. The analyte is allowed to pass over the reference surface and the measurement surface so that all unspecific bindings that are not interactions with the ligand can be subtracted. In use of a capture molecule, it can be good to have one reference cell with capture molecule and one

without.

3.5.2.3 Regeneration of the sensor surface

Regeneration is a procedure that removes unwanted molecules from the sensor surface after a measurement has been made, in preparation for a new cycle. If the ligand is covalently bound, the regeneration should wash away the analyte but leave the ligand intact on the surface. Regeneration of a surface where the ligand is attached through high affinity capture will wash away both the analyte and the ligand but leave the capture molecule intact. In that case, new ligand must be captured at the start of each cycle.

3.5.2.4 Single-cycle kinetics

Increasing analyte concentrations are injected over the immobilised ligand during one cycle. The biomolecules bind during the injection of the analyte and then there is a pause-time after each injection when the analyte dissociate from the ligand before new analyte is injected. A sensorgram of a typical single-cycle run is illustrated in figure 10. No regeneration is performed between the injections.

Figure 10: Sensorgram illustrating single-cycle kinetics.

(19)

19 3.5.2.5 Multi-cycle kinetics

One analyte concentration per cycle is measured and several cycles are run. After each analyte injection the surface is regenerated and a new cycle is started, see figure 11. If the ligand is attached through high affinity capture, each cycle must start with capture of new ligand.

Figure 11:Top: sensorgram illustrating one cycle of a multi-cycle approach, bottom: overlay of several cycles.¹⁶

The benefit of the single-cycle approach is that no regeneration i.e. less chemicals are needed, and the downside is that the ligand dissociates over time which means that the amount of ligand might not be the same at the first and last analyte injection. This problem is avoided during multi-cycle kinetics since the surface is regenerated with the same conditions for each cycle, but the regeneration requires optimisation and more time.

4 Objectives

The aim of this master thesis project was to measure the biomolecular interactions between the human recombinant proteins Juno and Izumo1 in terms of kinetics and affinity. The first objective was to develop a method to immobilise Juno on gold nanoparticles and the second to measure the interactions with Izumo1. If the development of the immobilisation method was not successful, the goal was to measure the protein-protein binding in an alternative way.

(20)

20

5 Methods & Material

5.1 Immobilisation of Juno to gold nanoparticles 5.1.1 Original immobilisation procedure

The following procedure was applied in the beginning, later some adjustments were made to optimise the process (see results and discussion). Concentrations, volumes, incubation times etc. was varied according to table 1.

5.1.1.1 Conjugation of NTA

➢ Dithiobis(C2-NTA) and AuNPs were mixed in an Eppendorf tube.

➢ The sample was incubated at room temperature.

➢ After incubation the sample was centrifuged with 200 µl PBS at 7000 g for 30 min.

➢ The red gold-pellet was separated from the supernatant.

→ Checkpoint 1: a UV-vis spectra was taken of the pellet to see if the conjugation step was successful.

5.1.1.2 Conjugation of Co2+

➢ The gold nanoparticle-NTA-complex was mixed with CoSO4.

➢ The sample was incubated at room temperature.

➢ After incubation the sample was centrifuged with 200 µl PBS at 7000 g for 30 min.

➢ The red gold-pellet was separated from the supernatant.

5.1.1.3 Conjugation of Juno

➢ The gold nanoparticle-NTA-Co²⁺-complex was mixed with Juno.

➢ The sample was incubated at 4^⸰C.

(21)

21

Table 1: Varied parameters during the optimisation of the immobilisation process. All samples were made in duplicates, triplicates or quadruplicates. Next step was only continued if the previous step seemed successful.

5.2 SPR-measurements with Biacore

Table 2: Parameters for the Biacore-measurements with Juno and Izumo1.

Substance Specification

Running buffer* 10 mM HEPES, 150 mM NaCl, 0.005 % Tween 20

Capture molecule Monoclonal anti-FLAG antibodies M2

Captured ligand Izumo1 (triple FLAG-tag)

Analyte in solution Juno

*The running buffer was degassed with helium prior to the measurements to avoid air bubbles.

5.2.1 Optimising the regeneration

A multi-cycle approach was chosen, and several cycles were performed without analyte to optimise the regeneration process. The regeneration solution was injected as a pulse of 30µl during 1 min.

Tested regeneration methods were:

▪ HCl 10 mM

▪ NaOH 20 mM + HCl 20 mM (two separate pulses)

▪ HCl 20 mM + SDS 0.1% (two separate pulses)

▪ NaOH 20 mM

Sample AuNP [µl] C2-NTA [µl] Shaking Incubation [h] CoSO4 [µl] Shaking Incubation [h] Juno [µl] Incubation [h]

B 10 10 (25 mM) Yes 2

C 10 10 (0.1 mM) Yes 2 10 (10 mM) 2

D 40 10 (1 mM) Yes 2 10 (10 mM) No 2

E 40 10 (10 mM) For 15 min then no 24 10 (10 mM) Yes 2

F 40 10 (10 mM) Yes 4.5 10 (10 mM) No 15

G 20 10 (1 mM) Yes 2 10 (10 mM) Yes >50

H 20 20 (1 mM) For 15 min then no 27 I 0.5, 4.5, 10 10, 10, 100 (1mM) Yes 27 J 2, 4, 4, 8 20, 20, 8, 8 (25 mM) For 15 min then no >50 K 10 10 (25 mM) For 15 min then no >50 L 8 8 (25 mM) For 15 min then no >50

M 8 8 (25 mM) For 15 min then no >50 2 (1 mM) No 1 1 (0.3 mg/ml) 0.5

N 8 6 (25 mM) For 15 min then no >20

O 10 10 (25 mM) For 15 min then no >20 2 (1 mM) No 1

Q 20 20 (25 mM) For 15 min then no >50 3-5 (1 mM) No 1 3 (0.7 mg/ml) >15

Step 1 Step 2 Step 3

(22)

22

5.2.2 Measurements with recombinant human Juno produced in E. coli

The runs were performed using a CM5 sensor chip with anti-FLAG antibodies as immobilised capture molecules. The ligand, Izumo1 containing a triple FLAG-tag, was attached through high affinity capture.

Anti-FLAG was immobilised on flow cell 2 but not on flow cell 1, which was used as a reference surface to see if Juno interacts with the sensor surface. The analyte Juno was injected at different concentrations using a multi-cycle approach. Two pulse injections of sodium hydroxide and hydrochloric acid was used to regenerate the sensor surface at the end of each cycle. New Izumo1 was captured at the start of each cycle. To ensure that the Juno-Izumo1 binding was specific, Juno was exchanged for BSA in a similar multi-cycle run.

5.2.2.1 Immobilisation of anti-FLAG antibody

➢ The sensor surface was activated through EDC/NHS chemistry.

➢ 30 µl of anti-FLAG antibodies 0.01 mg/ml in NaOAc were injected over flow cell 2 to an RU- increase of ~7800 (constant flow 5 µl/min).

➢ Deactivation of the surface was made with ethanolamine.

5.2.2.2 Multi-cycle procedure

A constant flow rate of 10 µl/min was kept throughout the run unless stated otherwise.

➢ 60 µl of Izumo1 1 µM was injected over flow cell 2 to an increase of 150-225 RU.

➢ Buffer was run for 5 min in order to stabilize the baseline.

➢ 50 µl of Juno was injected according to table 3 over flow cell 1 and 2.

➢ The flow cell 1 and 2 were regenerated with 20 mM NaOH followed by 20 mM HCl (30 µl of each at a flow rate of 30 µl/min).

Table 3: Juno concentration per cycle. The concentrations were diluted from a stock solution of 10 µM.

Cycle 1 2 3

Juno [µM] 0 0.8 1.6

(23)

23

5.2.3 Measurements with recombinant human Juno produced in mammalian cells

5.2.3.1 Immobilisation of anti-FLAG antibody

➢ The sensor surface was activated through EDC/NHS chemistry.

➢ 20 µl of anti-FLAG antibodies 0.01 mg/ml in NaOAc were injected over flow cell 1, 2, 3 and 4 to an RU-increase of ~11 000-13 000 (constant flow 5 µl/min). Flow cell 2 and 4 were used as test cells with 1 and 3 as reference cells respectively.

➢ Deactivation of the surface was made with ethanolamine.

5.2.3.2 Single-cycle procedure

➢ 150 µl of Izumo1 3 µM was injected over flow cell 2 to an increase of ~340 RU.

➢ Buffer was run for a few minutes to stabilize the baseline.

➢ 25 µl of Juno was injected over flow cell 1 and 2 at increasing concentration; 2, 4, 8, 16, 32, 63, 125, 250, 500, 1000 nM. After each Juno-injection, only buffer was run for a few minutes to let the proteins dissociate and to stabilise the baseline.

5.2.3.3 Multi-cycle procedure

➢ 100 µl of Izumo1 3 µM was injected over flow cell 2 to an increase of 100-300 RU (multi-cycle 1) or over flow cell 4 to an increase of 450-500 RU (multi-cycle 2).

➢ Buffer was run for a few minutes to stabilize the baseline.

➢ 30 µl of Juno was injected according to table 4 over flow cell 1 and 2 (multi-cycle 1) or flow cell 3 and 4 (multi-cycle 2).

➢ The flow cells were regenerated with 30 µl of 20 mM NaOH (multi-cycle 1) or 30+30 µl of 25 mM NaOH (multi-cycle 2) at a flow rate of 30 µl/min.

Table 4: Juno-concentrations during multi-cycle runs. The concentrations were diluted from a stock solution of 22 µM.

Cycle 1 2 3 4 5 6 7 8 9 10 11 12

Juno [nM]

0 2 4 8 16 32 63 125 250 500 1000 2000

(24)

24 5.2.3.4 Calculations of the equilibrium dissociation constant

The data generated from Biacore was analysed with the aim of finding a value of the dissociation constant for the proteins Juno and Izumo1.

5.2.3.4.1 Equilibrium analysis

The relative response for each Juno-pulse where equilibrium/steady state had been reached between the two proteins was plotted against the injected Juno-concentration. An equilibrium binding analysis was made in Excel where a curve was fitted to the data points to find the maximum response and the dissociation constant.

5.2.3.4.2 Kinetic analysis

The curves generated in the sensorgram were fitted against a Langmuir 1:1 binding model that is based on the association and dissociation rate of the protein complex and allows for calculation of Kd.

5.3 SDS-PAGE preparation

➢ Loading dye was diluted 4 times in the protein sample and heated at 95^⸰C for 5 min.

➢ 5 µl prestained protein ladder was added in the first well of the gel.

➢ 10 µl of heated protein-loading dye sample was loaded in a well.

➢ The gel was run at 150 V for ~55 min.

➢ The gel was stained with PageBlue over night and then decoloured with water.

Table 5: Summary of items used for SDS-PAGE.

Substance Specification Company

Gel Mini-PROTEAN TGX gel (#456-1033) BIO-RAD

1x Running buffer 25 mM Tris, 192 mM Glycine, 0.1% SDS -

Prestained Protein Ladder PageRuler Plus (#26619) Thermo Fischer Scientific

Protein Staining Solution PageBlue, Coomassie G-250 (#24620) Thermo Fischer Scientific

(25)

25

5.4 HEPES buffer preparation

➢ HEPES-buffer suited for Biacore was prepared according to table 5.

➢ pH was adjusted to 7.4 with NaOH.

➢ The buffer was filtrated through a 0.22 um filter.

Table 6: Content of running buffer.

Substance Specification

HEPES-buffer 10 mM HEPES, 150 mM NaCl, 0.005 % Tween 20

5.5 Buffer exchange of Juno

Since the storage buffers of Juno contained glycerol and beta-mercaptoethanol which could cause problems during the Biacore measurements, an exchange of buffer was performed. The exchange of buffer was made using an Amicon ultra-0.5 centrifugal filter unit with 3 kDa NMWL.

➢ Protein sample in old buffer was diluted to 500 µl in new buffer and added to the filer unit.

➢ The filter unit was centrifuged at 14 000 g for 30 min to a volume of 50 µl.

➢ The filter unit was filled up to 500 µl with new buffer.

➢ The filter unit was centrifuged at 14 000 g for 30 min to a volume of 50 µl.

➢ The filter unit was turned upside down in a clean tube and centrifuged at 1000 g for 2 min.

➢ The recovered protein concentrate was diluted to desired concentration.

(26)

26

5.6 Chemicals

Table 7: Information about all chemicals used throughout the project.

Substance Specification Company

Nitrilotriacetic acid (NTA) Powder Sigma-Aldrich

Dithiobis(C2-NTA) Crystalline powder Dojindo

Phosphate-buffered saline (PBS) Aqueous solution, 1x, pH 7.4 Gibco

Gold nanoparticles (AuNPs)

nm

15 nm in colloid water solution BBI

Sodium hydroxide (NaOH) Pellets Merck

Cobalt sulfate heptahydrate (CoSO4.

7H2O)

Crystalline powder, 98% Alfa Aesar

Monoclonal anti-FLAG M2 antibody In 10 mM sodium phosphate, 150 mM NaCl, pH 7.4, containing 0.02% sodium azide

Sigma-Aldrich

HEPES 1 M in water Fluka

Sodium Chloride (NaCl) Crystalline powder Merck

Tween 20 Viscous liquid Sigma-Aldrich

Hydrochloric acid (HCl) Pellets Sigma-Aldrich

Sodium dodecyl sulfate (SDS) Viscous liquid Sigma-Aldrich

Glycine 10 mM, pH 2.5

(27)

27

5.7 Proteins

Table 8: Information about the proteins used in this project.

Property BSA Juno I Juno 2 Izumo1

M [kDa] 66.5 30 (apparent), 30.3

(predicted)

27 (predicted) 112.5 (monomer,

predicted) 562 (pentamer, predicted)

Construct Monomeric

recombinant human

Monomeric recombinant human

Pentameric recombinant human, ectodomain

Tags - N-terminal 6xHis-tag N-terminal 6xHis-tag C-terminal 6xHis-tag

Triple FLAG-tag Beta lactamase Rat Cd4 Storage

buffer

PBS 1x, pH 7.4

10 mM Tris-HCl, 1 mM EDTA, pH 8.0, 20% glycerol

20 mM Tris, 150 mM NaCl, 40% glycerol

Cell-lysate

Expression host

E.coli Mammalian HEK2936E cells (Homo

sapiens)

Purity >90% Unspecified

5.8 Instruments and Software programs

Table 9: Specifications regarding the instruments used in the project.

Instrument Model Software Company

Centrifuge RT/4^⸰C

f

Micro Star 17/17R - VWR (part of avantor)

Spectrophotometer NanoDrop 1000 NanoDrop 1000 v3.8 Thermo Fisher Scientific

Biacore Biacore 3000 Control Software

BIAevalutation

GE Healthcare

Gel Documentation LAS-1000 Plus Image Reader FUJIFILM

Structure visualization Swiss-PdbViewer Swiss-PdbViewer v4.1.0

Swiss Institute of Bioinformatics

(28)

28

6 Results and discussion

6.1 Immobilisation of Juno to gold nanoparticles

Juno was to be immobilised on gold nanoparticles in a three-step-process called the His-tag method.

The method is based on that the to-be-immobilised protein contains a polyhistidine tag that coordinates strongly with metal ions such as nickel and cobalt. A good chelator such as nitrilotriacetic acid (NTA, figure 12) can be immobilised on the gold and chelate to cobalt that in turn will bind the His-tag on the protein. NTA can be conjugated to gold nanoparticles through a linker as dithiobis(C2-NTA) seen in figure 13. A scheme of the entire immobilisation process can be seen in figure 14.

Figure 13: Molecular structure of dithiobis(C2-NTA). The disulfide bond is cleaved and sulfur conjugates to the gold surface.

NTA, Co²⁺ and Juno were to be conjugated one after the other to the gold nanoparticles. To see if each conjugation step worked, the LSPR of the gold nanoparticles was measured using UV-vis spectroscopy.

Spectra was taken before and after each conjugation step. If a wavelength shift was observed between two steps and the sample colour remained red, the conjugation step was considered successful. If the sample turned blue/violet the process was not continued, as an agglomerated state of the particles would complicate the conjugation of Juno.

Figure 12: Structure formula of nitrilotriacetic acid.

(29)

29

Figure 14: Immobilisation method to conjugate Juno to gold nanoparticles.

(30)

30

6.1.1 Conjugation of NTA

In order to use gold nanoparticles to measure the Juno-Izumo1 interaction, a functioning method to immobilise Juno on the gold nanoparticle surface had to be established. The first step of the immobilisation process was to add NTA to gold nanoparticles. In the beginning, pure nitrilotriacetic acid was used and the first problem was faced when the crystals of NTA did not solubilize in water at the desired concentration. Quite alkaline conditions were required to solubilize NTA which probably caused agglomeration of the AuNPs as the colour of the solution went from red to violet. It was concluded that the high pH made it difficult or impossible to succeed with an addition of NTA in this form.

A variant of NTA specially made to immobilise nickel or cobolt ions to solid supports called dithiobis(C2-NTA) was therefore ordered and used instead. Various ratios of NTA:AuNP were tested against different incubation times and it was found that a successful addition took place when a sample at ratio 100:1 (NTA:nanoparticle) was incubated for at least 20 h in room temperature (higher yield if incubated even longer). The samples were analysed with UV-vis spectroscopy and spectra can be seen before and after conjugation of NTA where the nanoparticles absorb at 520 nm and 527 nm respectively (figure 15).

Figure 15: Spectra before (520 nm) and after (527 nm) conjugation of NTA to the gold nanoparticles.

(31)

31

6.1.2 Conjugation of Co

²⁺

The next step was to chelate a cobalt ion to NTA and for this cobalt sulfate was used. The addition of CoSO4 turned the red AuNP-NTA-sample purple, suspecting agglomeration once again. Since both dithiobis(C2-NTA) and CoSO4 are acidic the pH was now suspected of being too low and dilution in PBS pH 7.4 instead of water was therefore tested in order to prevent a decrease in pH. Unfortunately, using PBS did not help since a blue/purple precipitation was formed. It is possible that the phosphate ions from the PBS buffer bound to the cobalt ions forming the insoluble tetrahydrate cobalt sulphate Co3(PO4)2.4H2O. At some points a black precipitation was also observed after centrifugation (known black cobalt precipitates are cobalt oxide, cobalt sulfide and pure cobalt, but it is hard to say which/if any of these could have been formed).

To avoid the problems with PBS, HEPES-buffer was tried. However, similar problems as before were experienced; addition of CoSO4 with HEPES-buffer led to either lack of pellet or formation of blue/purple precipitations. It was now suspected that the pH of the solution was not the problem but instead the ionic strength. One theory is that the ions in the buffers can screen off the electrostatic repulsions that are keeping the AuNPs apart and thus cause agglomeration that leads to precipitation during centrifugation. Avoiding buffers, trying different concentrations of CoSO4 in water and different incubation times finally led to something that might have been a positive conjugation of Co²⁺. In figure 16 the UV-vis spectrum generated after addition of Co²⁺ is seen with a peak at 532 nm, a 5 nm shift compared to the previous step (figure 15). The successful conditions were addition of 2 µl CoSO4 1 mM, and a short incubation time of 1 h. However, the pellet was significantly smaller than during the previous step which means that a big amount of sample is lost during the cobalt-step (compare the intensities in figure 15 and 16).

Figure 16: UV-Vis spectrum of an AuNP-NTA-Co-sample. Some noise due to low concentration.

(32)

32 To conclude, it is difficult to work with cobalt ions in solution as it can form insoluble solids with various anions. Furthermore, the pH and the ionic strength are tricky parameters that need to be monitored. In the future it would be interesting to try the complexation of cobalt and NTA using an ion exchange column, which has been done with nickel instead of cobalt in a previous study²³.

6.1.3 Conjugation of Juno

Juno was diluted in PBS and then mixed with the red pellet from the previous step. After incubation at 4^⸰C a UV-Vis spectrum was taken that showed peaks at 224 nm and 275 nm that most likely were due to the aromatic amino acids of the protein, but no peak around 520-540 nm that indicated that the AuNP- Juno-complex was formed. Suspecting that the sample may have been too diluted, centrifugation was performed but no pellet was yielded. A spectrum was taken from the bottom of the tube nonetheless, but there was no change. One hypothesis is that the lack of pellet might be due to the phenomena “salting in” where the protein is surrounded by the salt counterions and increase the solubility of the protein in solution. Maybe centrifugation at a higher speed would have resulted in the formation of a pellet.

Another problem could be that the pH of the solution probably was below 7, since no buffer had been used in the previous step, and this could have caused the protein to denature.

A new test was made using Juno after the buffer exchange to HEPES-buffer. Juno was added without dilution (3µl of 0.66 mg/ml) but after incubation nothing was shown in the spectrum. However, centrifugation with 20 µl HEPES gave a small red pellet. A new spectrum (figure 17) revealed a weak signal at 542 nm that could indicate a protein-nanoparticle complex, but due to the low concentration, the baseline was rather noisy and therefore hard to confirm that there really is a peak there. Instead, there were two strong peaks at 230 and 275 nm indicating that a large portion of the protein was still free in solution.

(33)

33

Figure 17: UV-Vis spectrum after addition of Juno.

The small amount of dithiobis(C2-NTA) that was left and lack of time at the end of the project hindered further tests that would have been necessary to complete the last step of the immobilisation. In the future, the biggest problems to solve is probably the drastic decrease of product yield after the cobalt-addition along with optimising pH and ionic strength prior to the addition of protein.

6.2 Biacore-measurements

Alternative methods to measure the Juno-Izumo1 interaction were investigated when it was unsure whether the gold nanoparticle approach was going to work. Luckily, a possibility to perform binding assays with Biacore opened up. All sensorgrams shown are working cell minus reference cell (Fc2- Fc1) unless stated otherwise.

6.2.1 Improving the regeneration

To ensure that no Juno was left in between analyte injections and to avoid problems with baseline decay, a multi-cycle approach was chosen. The plan was to regenerate the anti-FLAG surface after each cycle, i.e. remove both Juno and Izumo1, hence an effective regeneration procedure had to be found. Several regeneration cycles without injecting Juno was performed. Firstly, 10 mM HCl was used, but the baseline at the end and start of each cycle was not the same, suggesting that the regeneration method was not optimal, see figure 18.

(34)

34

Figure 18: Regeneration test with HCl. The RU-increase at 250 s is injection of Izumo1, the dip at 1550 s is injection of HCl.

A new regeneration test was made using 20 mM NaOH followed by 20 mM HCl. After several multi- cycle procedures it was observed that less Izumo1 could be captured for each cycle, indicating that the anti-FLAG antibodies had been damaged from the regeneration. Suspecting that the NaOH had caused the damage, a new regeneration method was tested using 0.1% SDS and 20 mM HCl. However, the RU increase of Izumo1 decreased drastically, and after 4 cycles Izumo1 could not be captured (figure 19).

It seems that the SDS damaged the antibodies, since HCl had been used earlier with less drastic results.

Figure 19: Sensorgram of regeneration test with SDS and HCl. The decrease for each cycle suggest damage to the anti-FLAGs.

This sensorgram is zoomed in for better visualisation (the regeneration pulses are not visible here, see appendix).

(35)

35 New anti-FLAG antibodies were applied to flow cell 3 and 4 of the chip (with 3 as reference), since flow cell 2 now was destroyed. Glycine 10 mM pH 2.5 was tried as the next regeneration media, but still less Izumo1 could be added for each cycle. Next approach was to use only alkaline regeneration, hence 20 mM NaOH was tried. Finally, it seemed that a good regeneration method was found; the baseline was similar at start and end and the capture of Izumo1 was similar for each cycle, see figure 20.

Figure 20: Sensorgram of regeneration test with NaOH.

From the optimisation of regeneration methods, it could be concluded that the anti-FLAG antibodies are rather sensitive, but that the regeneration with 20 mM NaOH worked well.

6.2.2 Measurements with recombinant human Juno produced in E. coli

As can be seen in figure 21, three cycles were performed with 0, 0.8 and 1.6 µM Juno respectively. Each cycle started with capture of Izumo1 followed by baseline stabilisation, injection of Juno and regeneration. As this was before the optimal regeneration had been found, the regeneration was made with NaOH and HCl and as the sensogram shows; less Izumo1 can be captured for each cycle.

Injection of Juno generated signals that indicate binding and are proportional to the Juno concentrations (after subtraction of the reference cell). Further runs could not be made with this Juno due to limited amount of protein, and therefore it was not possible to calculate a value of the affinity. However, the measurements clearly show that the proteins do bind which is a nice result since there are no previously published studies using E. coli-expressed Juno in combination with Izumo1 produced in mammalian

(36)

36 cells. The squared shape of the curve indicates that the proteins dissociate fast; the relative response stop increasing shortly after the start of injection and stabilises since association and dissociation occur at the same time, and at the end of the injection the steep decrease is a result of an instant dissociation. Based on the shape of the sensorgram, a hypothesis was made that Kd probably lies within the micromolar- range. This is widely different from a study in 2016 where both recombinant human proteins were expressed in insect cells and a Kd of 48 nM was found⁷.

Figure 21: Sensorgram of Juno-Izumo1 binding.

6.2.3 Measurements with recombinant human Juno produced in mammalian cells

6.2.3.1 Single-cycle approach

Even though optimisation of the regeneration had been investigated the regeneration was not perfect, and it was therefore decided to try a single-cycle approach. Since the Juno that was used in the previous runs indicated a weak binding in the micro-molar range, the first single-cycle run was made with rather high Juno-concentrations of 0.05 – 30 µM. Interactions between the two proteins was measured, but surprisingly the curves had a widely different shape, indicating a slower dissociation than with the previously used Juno. Furthermore, the relative response of the peaks only differed for the lower concentrations and remained constant for the higher concentrations, see figure 22. Since these curves indicated a stronger binding, it was suspected that this run was using concentrations way above the dissociation constant Kd, which would explain why the relative response was unchanged.

(37)

37

Figure 22: Sensorgram of single-cycle run with Juno at 0.05, 0.1, 0.2, 0.4, 0.8, 1.7, 3.3, 7.5 and 15 µM. The relative response of the peaks only changes slightly, and there is a constant drift of the baseline.

A new single-cycle run was performed using concentrations of 2 – 1000 nM, see figure 23. Here there was a clear increase in relative response as the concentration of Juno increased, indicating that we were now covering the right concentration span to find Kd. Since it is easier to do kinetics calculations from multi-cycle data in the software, the same protein concentrations were used in two multi-cycle runs.

Figure 23: Sensorgram of a single-cycle run with Juno-concentrations of 2, 4, 8, 16, 32, 63, 125, 250, 500 and 1000 nM.

1840 1890 1940 1990 2040

0 1000 2000 3000 4000 5000 6000 7000 8000

Tim e s

Resp. Diff.

RU

1880 1900 1920 1940 1960 1980 2000 2020 2040

0 2000 4000 6000 8000 10000

Tim e s

Resp. Diff.

RU

(38)

38 6.2.3.2 Multi-cycle 1

Twelve cycles were performed (fig. 24 and 25) as previously described in the method. During the first run, it was clear that the regeneration of the sensor surface was a problem since the amount of Izumo1 that could be captured at the start of each cycle was not the same, see figure 24. The first 9 cycles captured Izumo1 with varying relative responses between 250-300 RU and for the last three cycles the capture was 200, 140 and 100 RU respectively. It seems that the regeneration of 20 mM NaOH was less effective towards the higher concentrations of Juno, maybe because these cycles would have needed more time for dissociation. This was an issue since the calculations used for calculating Kd are based on that the concentration of one of the proteins is kept constant while the other one is varied. Moreover, it is difficult to compensate for the varying Izumo1 capture in the calculations since it is unknown how this affects the binding assay. The ineffective regeneration could lead to that active Izumo1 is left on the surface so that more protein will be able to bind to Juno during the next cycle, or it could mean that inactive or still bound Izumo1 is left on the surface which would lead to that less active Izumo1 can be captured in the next cycle. A new multi-cycle run was made where a harsher regeneration method was applied in order to solve this issue.

Figure 24: Sensorgram showing multi-cycle run 1; the arrows indicate the amount of Izumo1 captured for the different cycles.

6.2.3.3 Multi-cycle 2

During the second multi-cycle run the regeneration was better and the capture of Izumo1 more even, but there is still a gap of ~50 RU in between cycles. The curves for the higher Juno pulses are closer together (see figure 26) which indicates that the maximum response where all binding sites are occupied is near, something that was not seen in the first multi-cycle run.

Interactions of the Human Recombinant Proteins JUNO and IZUMO1