Platform for Bio-functionalization

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IN

DEGREE PROJECT ENGINEERING PHYSICS, SECOND CYCLE, 30 CREDITS

STOCKHOLM SWEDEN 2019,

Superparamagnetic Hybrid Microspheres as a Reliable

Platform for Bio-functionalization

GIOVANNI MARCO SALADINO

KTH ROYAL INSTITUTE OF TECHNOLOGY SCHOOL OF ENGINEERING SCIENCES

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Superparamagnetic Hybrid

Microspheres as a Reliable Platform for Bio-functionalization

GIOVANNI MARCO SALADINO

Master Thesis Engineering Physics Stockholm, Sweden 2019

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KTH School of Engineering Sciences SE-100 44 Stockholm

TRITA-SCI-GRU 2019:056 SWEDEN

Supervisor: Dr. Gunaratna Kuttuva Rajarao

Co-supervisors: Dr. Carmen Vogt and Bejan Hamawandi Examiner: Professor Muhammet Toprak

Superparamagnetiska Hybrida Mikrosfärer som en Pålitlig Plattform för Bio-funktionalisering

Cover Picture: Micrograph of three superparamagnetic hybrid microspheres on a graphite sheet, obtained by SEM imaging and, artificially, coloured.

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iii

Abstract

Biofunctionalized magnetic nanomaterials have been identified as promising separation tools for various applications. Magnetic nanoparticle-based materials have been demonstrated to be feasible and reliable platforms as an alternative to centrifugation, gravitational separation, separation in columns, filtration and precipitation processes.

The present research was aimed at designing and fabricating an inexpensive, reusable and easy-to-use biocompatible platform, which comprises of inorganic nanoparticles and amino acids with a natural protein tagged on the external surface.

Citrate-coated superparamagnetic iron oxide nanoparticles (SPIONs) have been synthesized and transformed into microspheres via self-assembly with a polyamine.

Nanoparticles with a diameter < 10 nm were synthesized via a novel microwave-assisted hydrothermal method, which allowed to obtain uniform and negatively-charged nanoparticles within 30 min. These were then effectively coupled with Poly-L-lysine to form micrometer-sized spherical entities via coacervation process. Mechanical stability of the coacervate assembly has been achieved via cross-linking amine groups on the polyamino acid with glutaraldehyde, allowing to permanently embed the SPIONs in the microspheres.

The active bio-functionality was made possible by introducing a protein grafting methodology, using m-maleimidobenzoyl-N-hydroxysulfosuccinimide ester; hence, it was possible to cross-link amine groups of the Poly-L-lysine with the sulfhydryl groups present in protein residues. The protein used was the Moringa Oleifera Coagulant Pro- tein from a seed extract, functional for its characteristic coagulation activity. Further- more, models and simulations were built up in order to reveal and study the protein morphology, obtaining 99.9% of confidence for the predicted structure via homology modelling. Thus, it permitted to highlight the three α-helices and the charge distributions along its structure. Finally, the research work allowed to get insights into the magnetic properties of the nanoparticles, as well as the morphological and functional characteristics of the microspheres, thus, obtaining a saturation magnetization of 72 emu/g for the citrate-coated SPIONs, without any relevant coercivity. The successful functionalization was confirmed by the highly-positive ζ-Potential of the microspheres, with a value over +30 mV. The performance of biofunctionalized material was evaluated as a function of turbidity removal from polluted water via magnetic separation, obtaining over 80% of activity within 15 minutes. The advantages of a strong and tunable magnetic response within the biofunctionalized materials make the process extremely time-efficient and user-friendly.

Keywords: biofunctionalization, superparamagnetic microspheres, hybrid platform, protein grafting, coacervation, SPIONs, turbidity removal, protein structure

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Sammanfattning

Biofunktionaliserade magnetiska nanomaterial har identifierats som ett lovande separa- tionsverktyg för en rad olika tillämpningar. Magnetiska nanopartikelbaserade material har visats vara tillämpbara som tillförlitliga alternativ till centrifugering, gravitations- separation, separation i kolumner, filtrering och utfällningsprocesser.

Detta arbete syftade till att designa och tillverka en billig, återanvändbar och lättan- vänd biokompatibel plattform bestående av oorganiska nanopartiklar och aminosyror ytmärkt med ett naturligt protein.

Citratbelagda superparamagnetiska järnoxidnanopartiklar (SPION) har syntetiserats och vidare omformats till mikrosfärer via självihopsättning av en polyamin.

Nanopartiklar med diameter < 10 nm syntetiserades via en ny, effektiv mikrovågsas- sisterad hydrotermisk metod som resulterade i likformiga och negativt laddade nanopartiklar inom 30 min. Dessa kombinerades sedan effektivt med poly-L-lysin för att bilda mikrometerstorlek sfärer via en koacervationsprocess. Mekanisk stabilitet hos mikro- sfärerna har uppnåtts via tvärbindning mellan amingrupper på polyaminosyran och glu- taraldehyd, vilket möjliggör en permanent inbäddning av de superparamagnetiska nanopartiklarna i mikrosfärerna.

Den aktiva biofunktionaliteten infördes genom proteinympning och användandet av en tvärbindare, m-maleimidobenzoyl-N-hydroxysulfosuccinimid ester. Där med möjlig- gjordes tvärbindning av amingrupper hos poly-L-lysin med sulfhydryl grupper i protei- net. Moringa Oleifera Coagulant proteinet användes och är utvunnet från ett fröextrakt som kännetecknas för sinkarakteristiska koagulationsaktivitet. Vidare har modeller och simuleringar tagits fram för att kunna studera proteinmorfologi, för vilka en konfidens- grad om 99.9% för de förutspådda strukturerna uppnåddes med användning av homo- logi modellering. Därmed kunde de tre α-helixarna och laddningsfördelningen genom strukturerna presenteras. Slutligen ingav forskningsarbetet en inblick i de magnetiska egenskaperna hos nanopartiklarna och mikrosfärerna samt deras morfologiska och funk- tionella egenskaper. Däribland uppmättes en mättad magnetisering till 72 emu/g för de citrat belagda SPION, utan någon framträdande koercivitet. Den lyckade funktionalise- ringen bekräftades genom uppmätning av den särdeles positiva ζ-potential hos mikro- sfärerna, till ett värde över +30 mV. Utförandet av de biofunktionaliserade enheterna har utvärderades som en funktion utav avlägsnandet av grumlighet från förorenat vat- ten genom magnetisk separation, där en aktivitet över 80% uppnåddes inom 15 minuter.

Fördelarna med en stark och avstämbar magnetisk respons hos de biofunktionaliserade enheterna gör avlägsningsprocessen mycket tidseffektiv och användarvänlig.

Nyckelord: biofunktionalisering, superparamagnetiska mikrosfärer, hybridplattform, pro- teintransplantation, koacervation, SPION, grumlighetsavlägsnande, proteinstruktur

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Acknowledgments

I would like to thank Dr. Gunaratna K. Rajarao and Prof. Muhammet Toprak for being enlightening guides, constantly and readily available all along this path.

Thanks to the whole Nanochemistry group, which has made me feel like home since the very beginning, enthusiastically welcoming me with a familiar environment.

Deep gratitude to Bejan Hamawandi, who has always been ready to suggest, and willing to support my ideas, with a lot of patience. Special thanks to Dr. Carmen Vogt for her observations and suggestions, helping me to deal with the lab instruments and making me aware of all the possible risks.

Very grateful to Dr. Erik Holmgren and Dr. Dmytro M. Polishchuk from Nanos- tructure Physics for their considerable support in the magnetic characterization. And thankful to Prof. Foivos Perakis, from Stockholm University, for his enthusiastic col- laboration in protein characterization with X-ray diffraction techniques.

Huge acknowledgement to my family, who supported and supports me in all my life choices, with a constant but discreet presence. Thanks to all my old friends around the world, with whom I can feel close despite being thousands of kilometres far apart. And, last but not least, to my new friends, who have made Sweden a warmer place.

Giovanni Marco Saladino Stockholm, June 2019

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List of Figures

2.1 Magnetic response of a paramagnet, superparamagnet and ferromagnet. 4

2.2 Crystal Structures of hematite, magnetite and maghemite. . . 5

2.3 Scheme for Coacervation process. . . 8

2.4 Scheme for coagulation phenomenon. . . 9

2.5 Sequence of MO2.1Protein. . . 10

3.1 Scheme for the SPIONs synthesis. . . 11

3.2 flexiWAVE Microwave and Reaction Temperature Profile. . . 13

4.1 SPfit interface. . . 22

4.2 Secondary Structure Analysis of MO2.1. . . 23

4.3 MO2.1 Ribbon Structure and Protein Surface Morphology. . . 24

4.4 MO2.1 Ribbon Structure highlighting specific residues. . . 24

4.5 Sample-Detector Distance as a function of the maximum Q value. . . . 26

4.6 Simulated 2D X-ray Scattering Pattern of MO2.1. . . 27

4.7 Simulated Powder Pattern of MO2.1 Protein. . . 28

5.1 Magnetization Curve, PDF and CDF for sample CP2. . . 31

5.2 Magnetization Curve, PDF and CDF for sample MW1. . . 32

5.3 SEM Micrograph for sample MW2. . . 33

5.4 AFM Mapping for sample MW2. . . 33

5.5 Magnetization Curve, PDF and CDF for sample MW2. . . 34

5.6 FTIR Analysis on Sample MW2 and TSC Powder. . . 37

5.7 Scheme showing the monodentate and bidentate citrate complexation. . 38

5.8 TGA thermogram of MW2 under atmosphere. . . 39

5.9 XRD Spectrum for sample MW2 and Magnetite. . . 40

5.10 Molecular structure of Glutaraldehyde and scheme for cross-linking. . . 44

5.11 FTIR Analysis on samples of SAPES and MW2. . . 45

5.12 SEM micrograph of a self-assembled coacervate. . . 45

5.13 Size distribution of cross-linked SAPES. . . 47

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LIST OF FIGURES ix

5.14 Scheme for SAPES. . . 47

5.15 Calibration Curve for Protein Detection with Bradford Assay. . . 50

5.16 Fluorescent emission spectrum of MOCP. . . 50

5.17 Calibration Curve for Protein Detection with Fluorescence emission. . . 51

5.18 Molecular Structure of SMBS. . . 53

5.19 Conjugation mechanism between PLL and MOCP. . . 54

5.20 Hydrodynamic Size Distribution for SAPES and MO-SAPES1. . . 55

5.21 SEM micrograph of a protein-grafted coacervate (MO-SAPES1). . . 56

5.22 Scheme for MO-SAPES. . . 57

5.23 FTIR Analysis on SAPES, MOCP and MO-SAPES. . . 57

5.24 UV-vis spectra of SAPES and MO-SAPES1. . . 58

5.25 UV-vis Absorption Intensities of Kaolinite. . . 59

5.26 SEM Micrograph of a microsphere (MO-SAPES2) covered with clay . . 61

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List of Tables

2.1 Iron oxide crystal structures and characteristics. . . 5

3.1 Sample list of the synthesised iron oxide nanoparticles. . . 13

3.2 Quantities used for the coacervation process. . . 15

3.3 Concentrations in the protein-grafting process, for amine binding. . . . 16

3.4 Concentrations for the protein cross-linking process. . . 16

5.1 Magnetization Parameters obtained via VSM data with SPfit. . . 35

5.2 ζ-Potentials for as-washed (single-step) and post-grafted SPIONs. . . . 36

5.3 List of observed vibrational modes for MW1, MW2 and TSC. . . 37

5.4 Crystalline properties of Magnetite. . . 40

5.5 Diffraction peaks for sample MW2. . . 41

5.6 ICP Results for sample MW2, using three diluted samples. . . 42

5.7 List of Vibrational Modes for Cross-linked SAPES. . . 44

5.8 Fitted parameters for log-normal size distribution of SAPES. . . 46

5.9 Results from DLS Analysis for SAPES. . . 48

5.10 Concentrations of BSA for Protein Detection with Bradford Assay. . . 49

5.11 Results from DLS Analysis for MO-SAPES1. . . 55

5.12 Turbidity Removal Activities after 15 minutes. . . 60

x

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Chapter 1 Introduction

Today, the recent increasing and successful developments of nanoparticles have resulted in continuous and hectic research for designing and employing these in the most dis- parate fields and applications. The possibility to functionalize nanoparticle surfaces opens the door to practical and powerful interactions with entities of different nature.

Considerable importance and emphasis are given to the advancements of nanoparticle bio-functionalization, in order to unfold a wide spectrum of biomedical applications.

In particular, coupling the magnetic properties of superparamagnetic nanoparticles with biofunctional molecules, such as antibodies and ligands, has led to the optimization of several hybrid tools, obtaining selective interactions with the chosen targets, in a var- iegated biological environment; from pathogen detection [1, 2] and protein separation [3, 4] to toxin decontamination from bodies [5] and nanoprobe development for non- invasive imaging [6] and cancer therapy [7].

Furthermore, the possibility to assemble magnetic nanoparticles into more robust, stable and isotropic magnetic microspheres allowed to keep having the superparamagnetic property of nanoparticles [8], but able to constitute a firmer solid platform for bio-functionalization. Several aggregation methods have been proposed employing polymerization, in the last decades, such as emulsion [9] and dispersion [10], but a remarkable self-assembly method consists of coacervation formation via polyelectrolyte complexation, followed by a cross-linking procedure [11]. The as-formed microspheres present high porosity and stability [12], thus constituting an optimal platform for grafting bio-molecules, such as proteins.

Nowadays, the need for drinkable and clean water is getting higher and higher. The excessive consumption of water by industrialized countries is leading to serious issues for water providers. Furthermore, the developing countries still directly face the lack of clean water. According to the World Health Organization (WHO), 844 million people do not have access to a basic drinking-water service, and even more people – 2 billion

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2 CHAPTER 1. INTRODUCTION

in 2015 – use contaminated water as an everyday drinking source. It was foreseen that, by 2025, half of the world’s population will face difficulties in employing potable water in everyday uses. The cause can be found in several aspects: from the rapid population growth, with subsequent deforestation and urbanization, to the warming global climate change [13].

Contaminated waters can easily become a means of disease transmissions, such as cholera, diarrhoea, and polio, which are the cause of several deaths each year. The long exposure to heavy metals, commonly present in surface water, can lead to high health risks, from strongly acute to chronic effects [14]. Even in the most industrialized countries, where the massive usage of pesticides and fertilizers provoked the contamination of a large quantity of groundwater [15], the lack or incompleteness of water purification treatments can generate huge risks to people’s health [16].

The involvement of chemical coagulants, substances able to bind suspended materials and remove them, allows to obtain quite relevant results but, at the same time, these chemicals are responsible for some leftovers in the treated water, thus being themselves a sort of contaminant, called disinfectant by-products (DBPs). One of the most common coagulants for water purification is the aluminium sulfate, Al2(SO4)₃, whose residues in treated water, together with the naturally occurring aluminium in water, constitute a causative agent of neurological disorders, like Alzheimer’s disease [17].

In this context, the current work will focus on the functionalization of superparam- agnetic microspheres with a protein, the Moringa Oleifera Coagulant Protein, having coagulation and flocculation properties [18].

This coupling can lead to the formation of a stable bio-functionalized hybrid platform for water treatment via magnetic separation, whose firmness and bio-friendly characteristic grant an environmentally friendly and ready-to-use tool for turbidity removal, very promising for both individual and industrial aims. The proposed coupling methodology does not imply a loss of generality in terms of possible target proteins, highlighting the wide-ranging characteristic of the followed path.

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Chapter 2 Background

The aim of this chapter is to present and highlight the key concepts which allowed to make the route followed in this work, and to draw crucial conclusions from the characterization data, for a successful outcome and for an optimal understanding of the results.

2.1 Superparamagnetism

The crucial characteristic of the iron oxide nanoparticles is their superparamagnetic behaviour, exhibited only at the nanoscale level. This attractive feature has significant relevance in many biomedical applications. In the case of sufficiently small ferro- and ferri-magnetic particles, these exhibit a single magnetic domain constituted by all the singular magnetic moment of the atoms being aligned along the same direction and, thus, behaving as a single giant magnetic moment. At non-null temperature, there is a non-zero probability for the magnetization to randomly change direction due to the thermal fluctuations. Hence, the Néel time τN is defined as the time between two subsequent spin variations, following an exponential law:

τ_N = τ₀exp KV k_bT

where K is the magnetic anisotropy energy, V is the nanoparticle volume, τ0 is the attempt period, material dependent, and kb is the Boltzmann constant.

Whilst, the blocking temperature Tbis the temperature at which the measuring time τ_mequals the Néel time, and given by the following relation:

T_b = KV k_bln

τN

τ0

3

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4 CHAPTER 2. BACKGROUND

Magnetic Field

Magnetization

Paramagnet Superparamagnet Ferromagnet

Figure 2.1: Magnetic response of a paramagnet (blue), superparamagnet (red) and ferromagnet (black).

If the temperature is high enough (T Tb), the measuring time will be much higher than the Néel time: the superparamagnetic behaviour is in action [19].

The essential characteristics of superparamagnetism can be described by analysing two extreme cases. The former is depicted by the absence of an external magnetic field:

in this situation, the averaged total magnetization M is equal to zero. The latter case is in play when a strong magnetic flux B is applied, the spins of the nanoparticle will tend to align with it, eventually overcoming the thermal fluctuations and anisotropies. The magnetic response will lead to a saturation magnetization MS, where the spins with unit magnetization miare all aligned.

The two above-mentioned cases represent the key concepts of superparamagnetic nanoparticles: no net effect at zero-field and a linear response when an external field is applied, stressing out that the response to the magnetic field strongly depends upon the size of the nanoparticles. These two characteristics can be appreciated in figure 2.1, where a comparison with paramagnetic and ferromagnetic behaviours is shown.

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2.2. IRON OXIDE NANOPARTICLES 5

2.2 Iron Oxide Nanoparticles

This class of nanoparticles is characterized by polymorphism, i.e. the oxide can have different crystal structure conformations. Iron atoms can exhibit different oxidation states (+2 and +3), by which they form various structure. The most common classes are the hematite (α-Fe₂O₃), maghemite (γ-Fe₂O₃) and magnetite (Fe₃O₄), whose crystalline characteristics are shown in table 2.1.

The hematite is characterized by a hexagonal lattice and weak magnetization properties, with its high coercivity and small saturation magnetization [20].

The efficient synthesis of iron oxide nanoparticles involves the production of two classes of materials: magnetite and maghemite, having similar magnetic behaviour, with their low coercivities and high saturation magnetization values. They are both characterized by an inverse spinel crystal structure, with small deviations represented by the interstitial sites. In magnetite, these are filled with Fe²⁺and Fe³⁺(molar ratio of 1/2), re- sulting in an inverse spinel structure [21]. On the other hand, in maghemite only Fe³⁺is present and some interstitial sites are left vacant in the cation sublattice [22]. Given their polymorphic characteristic, they can exhibit temperature-induced phase transitions. A scheme for the three different crystal structures can be observed in figure 2.2.

Table 2.1: Iron oxide crystal structures and characteristics [23].

Property Hematite Maghemite Magnetite Crystal System Hexagonal Cubic Cubic Lattice Parameter(s) a =5.03Å

a = 8.35Å a = 8.40Å c =13.75Å

Figure 2.2: Crystal Structures of hematite, magnetite and maghemite (Fe²⁺ in black, Fe³⁺in green and red balls for O²⁻) [24].

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2.3 X-ray Diffraction

One of the most interesting properties of X-rays is their characteristic wavelength on the order of the atom size, which makes possible the study of the interactions between light and matter on the atomic scale. Being electromagnetic waves, their wavelength (λ) can be associated with the energy (E) of the constituting photons, as follows:

λ[Å] = hc

E = 12.398 E[keV]

While going through a material, photons can be absorbed or scattered. The scattering events can be both elastic and inelastic, respectively preserving or not the photon mo- mentum ¯hk. In order to lead to a positive interference of the scattered light, the incident and scattered wavevectors, respectively k and k’ must follow the following relation:

Q = k − k’ (2.1)

where Q is called scattering vector.

Each atom of a molecule contributes to generating scattered light, whose intensity be- comes proportional to f(Q), known as atomic form factor, and dependent on the electron distribution of the correspondent atom. A parametric function as a sum of Gaussians allows to obtain f(Q) for all the atoms:

f (Q) =

4

X

i=1

aiexp −bi

Q 4π

2!

+ c (2.2)

where ai, bi and c are atom-dependent table-valued parameters [25].

The contributions of the single atoms in a molecule are summed, considering a phase factor, yielding:

F_mol(Q) =

atom

X

j

f_j(Q)e^iQ·r^j (2.3)

where Fmol(Q)is the molecular form factor with rj the atomic position of the j-atom with respect to a reference point. The scattered intensity from a molecule Imol will be given by the following relation:

I_mol = |F_mol|² (2.4)

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2.3. X-RAY DIFFRACTION 7

An analogous conclusion can be obtained for a periodical lattice of a single unit (molecule or atom), allowing to obtain a crystal form factor Fcrys, as follows:

F_crys(Q) =

atom

X

j

f_j(Q)e^iQ·r^j·

cell

X

k

e^iQ·R^k

where Rkare the lattice vectors. It can be demonstrated that the condition Q = G, with Gthe reciprocal lattice vector, must be fulfilled in order to get a constructive interference and, thus, a detectable intensity (Laue condition). This condition is equivalent to the Bragg’s law, which defines a direct relationship between the inter-planar distance d and the photon incident angle ϑ:

nλ = 2d sin ϑ

where n is an integer. Hence, by studying the scattered x-ray light, it is possible to deduce the crystal properties of a material [26].

In the case of a powder, several nano-crystals of the same materials are oriented in random angles. This characteristic broadens the intensity in the proximity of a peak, depending on the size of the single crystal. Thus, it is possible to relate the broadening of the peaks to the crystalline size DC, via the Scherrer equation:

DC = Kλ

β cos (2ϑ)

where β is the full width at half maximum (FWHM) of the peak at the angular position (2ϑ). Finally, K is a shape factor, commonly set to 0.9 [27, 28].

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2.4 Polyelectrolyte Self-assembly

Macromolecules having charges distributed all over the surface when dissolved in a polar solvent are defined with the term polyelectrolytes. Their characteristic is in fact shown in polar solvents, such as water, where they dissociate in macroion and counterions.

Thanks to the low activity of the released counterions, the macroion can exert strong electrostatic interactions towards other entities dissolved in the solvent [29].

The polyelectrolyte complexes are entities of various sizes characterized by their origin, i.e. strong electrostatic interactions. A key factor for the successful formation of these complexes is the ratio between the negative charges of one ionic species from the positive charges of the other one.

Figure 2.3: Scheme for Coacervation process; negative entities (red) are wrapped and neutralized by positively-charged electrolytes (green).

The presence of electrolytes in solution together with oppositely-charged entities leads to the agglomeration and neutralization of the species, yielding a phenomenon called polyelectrolyte self-assembly; the size of the as-formed agglomerates, even called coacervates, is strongly dependent on the hydrophilic characteristics of the species, together with temperature and solvent characteristics [30].

This phenomenon can thus lead to the possibility to form hybrid entities, starting from two species with opposite net charges. The agglomerates can assume a spherical morphology if the above-mentioned parameters are carefully adjusted, as shown in previous papers [11, 31].

In figure 2.3, a schematic image of the coacervation process is shown: negative entities, such as functionalized nanoparticles, are wrapped by positive polyelectrolytes, forming a spherical, self-assembled, complex.

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2.5. COAGULATION PROPERTY 9

2.5 Coagulation Property

In water treatments, the term coagulation refers to the phenomenon that occurs when charged ions dissolved in water are neutralized by oppositely-charged particles. The charge neutralization alters the ion stability in water: by reducing their charges, the ions lose the self-provided repulsion among them and affinity towards water, which is indeed polar. Lacking the intrinsic charging characteristic, the neutralized ions tend to sediment and, subsequently, lead to a reduction of the dissolved quantity in solution.

This coulombic interaction between positively and negatively charged particles can, thus, be employed for water purification, even called turbidity removal. A scheme illus- trating the turbidity removal is shown in figure 2.4, where negatively-charged entities are neutralized by the addition of positive ones (coagulants), subsequently causing their sedimentation.

Figure 2.4: Scheme for coagulation phenomenon: positive entities (green) coagulate negatively-charged pollutants (red).

In addition to this phenomenon, flocculation constitutes the second main molecular property for water filtration: molecules presenting high molecular weight have the abil- ity to bridge and merge together particles present in solution, generating an amorphous structure, characterized by high porosity and by rapid sedimentation [32].

These two phenomena powerfully contribute to water purification systems, combin- ing the intrinsic properties of some polymers and proteins with subsequent water filtration mechanisms [33]. Furthermore, the existence of coagulants extracted from plants is able to make the process eco-friendly and avoid the introduction of toxic entities in water [34, 35].

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2.6 Moringa Oleifera

The properties of coagulation and flocculation have been long searched on plant extracts, in order to find an economic and accessible method for domestic water treatment;

among others, the extracts of Moringa Oleifera plant seeds were found to be good co- agulants and flocculants [18]. The possibility to obtain these extracts without following any sophisticated methodology constitutes a noticeable advantage, thus recommended for domestic water purification, especially in areas where conventional water treatments cannot be afforded by society. Although the crude extract of Moringa Oleifera seed al- ready possesses the coagulation property for turbidity removal in water, it is the cause of an increase in organic load in solution, which could become a source for bacterial proliferation [36]. It is not suggested, indeed, to use the crude extract for long-term stored purified water, but can still be safe to make use of it before 24 hours [37].

The coagulation and flocculation properties were also identified in MO2.1, a re- combinant protein from the Moringa Oleifera Coagulant Protein (MOCP). The protein MOCP, extracted from plant seeds, can also act as disinfectant, possessing antimicro- bial properties, mainly attributable to the fusion of bacterial membranes and, thus, being able to cause their damage [38]. In particular, studies on the sequence of MO2.1 were attained [39], yielding the sequence in figure 2.5.

Figure 2.5: Sequence of MO2.1Protein (UniProtKB - P24303).

It is constituted by a sequence of 60 amino acids, forming three α-helices. The study of the residues in the coagulant molecules highlighted the key role of arginine and glu- tamine for the coagulation and flocculation properties [40]; these, in fact, are the main contributors of positive charges, which would lead to strong electrostatic interactions between the peptide and the negative ions constituting the turbid waters.

Recently, the use of inorganic iron oxide nanoparticles has allowed the purification of the Moringa Oleifera seed extract, proving the successful binder role of nanoparticles [41]. Furthermore, the combination of the coagulant properties of the MOCP with the easiness of the magnetic filtration provided by magnetic nanoparticles has led to very promising results [42]. The Van der Waals interactions occurring between positively- charged residues in MOCP and negatively-charged nanoparticles represented the main feature for some previous works. Although, the non-covalent characteristics of these interactions could not grant that some peptides remained in solution after magnetic separation [43].

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Chapter 3 Materials & Methods

3.1 Synthesis of Nanoparticles

The synthesis of SPIONs was attained by following two different routes; coprecipitation and microwave-assisted methods. Four samples were obtained and their characteristics were analyzed in detail, in order to identify the best alternative amidst the candidates. For the synthesis, ferric chloride hexahydrate (FeCl₃ ·6H₂O), ferrous sulfate heptahydrate (FeSO4·7H2O), sodium hydroxide (NaOH) and sodium citrate dihydrate (Na3C6H5O7 ·2H2O, TSC) were all purchased from Sigma Aldrich. Stock solutions were stored for use: 3.622 g of ferric chloride were dissolved in 130 mL of DI H2O, while 1.825 g of ferrous sulfate in 130 mL of DI H₂O, in order to get a concentration of 0.1 M and 0.05 M, respectively. Furthermore, stock solutions of TSC (0.5 M) and sodium hydroxide (1 M) were prepared.

Figure 3.1: Scheme for the synthesis of Superparamagnetic Iron Oxide Nanoparticles.

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12 CHAPTER 3. MATERIALS & METHODS

3.1.1 Coprecipitation

As regards the coprecipitation method, two samples were prepared in 60 mL vessels.

Shortly, 20 mL of ferric chloride and 20 mL of ferrous sulfate were mixed in the vessels so that a 2 : 1 ratio was obtained, granting optimal conditions for magnetite formation.

While magnetically stirring, sodium hydroxide was fast added in solution, triggering the reaction. A scheme is presented in figure 3.1. One sample, named CP1, was attained following the as-described procedure.

A second sample CP2 was obtained following the following method: to 16 mL of ferric chloride and 16 mL of ferrous sulfate, 6.8 mL of NaOH were added, followed by the dissolution of 16 mL of TSC, in order to get negatively-charged iron oxide nanoparticles. The sample was sonicated for 15 minutes at 85°C.

Both the two samples were washed three times, via centrifugation, in order to remove the residuals of the reactions.

Citrate-enriched samples were actualized by following a post-grafting procedure, to ensure the saturation of negative charges on the surface of the magnetic nanoparticles.

For 1 mL sample of CP1 and CP2, 2 mL of TSC were added, followed by 15-minute sonication at 85°C. The as-formed samples were stored in the fridge for further charac- terizations.

3.1.2 Microwave-assisted Synthesis

The microwave-assisted hydrothermal synthesis was made possible by the use of a flexi- WAVE (Milestone SRL), leading to high reproducibility conditions. The tunable temperature, duration and power permit to attain high customization, whilst the volume capacity per vessel (100 mL) together with the possibility to simultaneously use up to 15 high-pressure vessels for parallel synthesis grant the high reproducibility condition (see figure 3.2.a). One sample, named MW1, was obtained by following an already- known recipe [44], with some modifications. In order to mimic sample CP1, obtained via the coprecipitation method, the same ratios and amounts for iron salts were used.

A second sample, named MW2, was prepared with the same characteristics of sample CP2, as shown in table 3.1.

The two prepared samples were treated under microwave irradiation according to the following recipe: a temperature of 150°C was reached with a 5-minute ramp, and kept constant for a duration of 25 minutes, shown in figure 3.2.2. A frequency of 2.45 GHz was employed, under continuous magnetic stirring (70% mode). A power limit of 1200W was set for safety reasons, despite never reached during the procedure.

After washing three times with DI water, the two samples were post-grafted following the above-mentioned procedure.

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3.1. SYNTHESIS OF NANOPARTICLES 13

Table 3.1: Sample list of the synthesised iron oxide nanoparticles.

Sample Volume [mL]

FeCl₃ FeSO₄ NaOH TSC

CP1 20 20 10 0

CP2 16 16 6.8 16

MW1 20 20 10 0

MW2 16 16 6.8 16

(a) (b)

Figure 3.2: FlexiWAVE Microwave (a) and Reaction Temperature Profile for Microwave-assisted Synthesis (b).

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3.1.3 Synthesis Reaction

Making the hypothesis to be able to convert all the iron in solution into magnetite (Fe₃O₄), the following net reaction occurs:

Fe²⁺_(aq)+ 2Fe³⁺_(aq)+ 8OH_(aq)^- →Fe3O4 (s)+ 4H2O(l)

Ideally, the same molar quantity n of magnetite as the ferrous sulfate precursor is obtained:

n (Fe3O4) = n (FeSO4)

Being [FeSO₄]the ferrous sulfate molarity, the predicted molality concentration for magnetite [Fe3O4]_gis:

[Fe₃O₄]_g= [FeSO₄] × M_W(Fe₃O₄) (3.1) where MW (Fe3O4) = 231.533^g/molis the molecular weight of magnetite. Hence:

[Fe₃O₄]^{CP1, MW1}_g = 4.63^g/L

[Fe₃O₄]^{CP2, MW2}_g = 3.38^g/L

respectively for samples CP1 and MW1 and for samples CP2 and MW2.

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3.2. COACERVATION AND STABILIZATION PROCESS 15

3.2 Coacervation and Stabilization Process

For the coacervation process and subsequent crosslinking procedure, the following chemicals were purchased from Sigma Aldrich: Poly-L-lysine hydrobromide (70 − 150 kDa, PLL), Glutaraldehyde solution (25% in H₂O, GA), Glycine (Gly). Stock solutions were then prepared: 20 mg of PLL were dissolved in 10 mL of DI water, while a 2.5 M solution was made for Gly; finally a 2.5 % GA solution was stocked.

From the washed sample MW2, 375 µL were diluted in DI water, with a total volume of 15mL. To this sample, 165 µL of 0.5 M TSC were added in order to generate a citrate- enriched environment, followed by 3s-pulsed sonication for 30 min at the maximum power. The pH of the prepared sample (C-MW2) was ∼ 7.5, confirming the possibility to get a working condition already compatible with most of the possible biomedical environments.

The procedure consisted of mixing C-MW2 with PLL, and incubating for 10 minutes. Then, GA was added (vortex for 15 s) and let it act for 5 minutes in order to ac- complish the crosslinking of the amine groups from different PLL molecules, via Schiff base formation [45]. Finally, the extra GA was quenched by adding Gly [11]. In table 3.2, we provide the list of the quantities used for the coacervation process.

Table 3.2: Quantities used for the coacervation process.

Volume [µL]

C-MW2 PLL GA Gly

120 20 120 40

For the washing procedure, 10 samples were prepared in parallel and collected together in a 4 mL cuvette after quenching. The as-prepared sample was washed three times using magnetic separation in order to remove all the non-magnetic entities present in solution.

Finally, the sample, called Self-Assembled Poly-Electrolytic Spheres (SAPES), was filled with 2 mL of DI water and stored for further uses.

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3.3 Protein Cross-linking

The Moringa Oleifera Coagulant Protein (MOCP) was crosslinked to the surface of the SAPES, by exploiting the free amine groups present on the surface of the latter and two thiol groups in the protein structure. For this purpose, m-maleimidobenzoyl-N- hydroxysulfosuccinimide ester (Sulfo-MBS) was bought from Thermo Fisher; its characteristic short spacer arm and the presence of two reactive groups at the two ends, NHS-ester and maleimide, make it the best candidate to obtain covalent bondings with the coacervate and the MOCP, respectively. A standard Phosphate-buffered saline (PBS) solution was prepared using the tablets from Sigma Aldrich, allowing to obtain a buffer solution with pH = 7.4.

Table 3.3: Concentrations in the protein-grafting process, for amine binding.

Molality [^µ^g/mL]

SAPES SMBS

SPIONs PLL

50 100 1000

A standard sample was made by using 3 mL dispersion of SAPES, where DI water was substituted by PBS via magnetic separation. Thus, 3 mg of Sulfo-MBS were added to the sample, obtaining the concentrations reported in table 3.3, and followed by mixing for 5 seconds and an incubation time of 30 minutes. After washing the sample to remove the excess cross-linker, the sample was refilled with 3 mL of PBS and 300 µL of MOCP (3 mg/mL) were quickly added, mixing the sample on vortex for 5 seconds and letting the thiol groups be crosslinked for 60 minutes. The concentrations for protein binding are presented in table 3.4. Finally, the as-obtained sample MO-SAPES1 was washed and refilled with 3 mL of DI water, storing it at 4^◦C for further uses. A second sample (MO-SAPES2) was prepared following the same methodology but keeping the excess cross-linking in solution when adding the protein. The term MO-SAPES was used to identify both the candidates, since they share most of the morphological and structural characteristics.

Table 3.4: Concentrations for the protein cross-linking process.

Molality [^µ^g/mL] SAPES

SPIONs PLL MOCP

46 91 243

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3.4. CHARACTERIZATION TOOLS 17

3.4 Characterization Tools

Dynamic light scattering (DLS)

Hydrodynamic size and ζ-potential distributions were measured by the Zetasizer Nano ZS90 with an incident angle of 90°. For the analysis, a neutral pH was always kept in order to mimic a physiological environment in view of possible biomedical applications.

The characterization was attained in DI H2O diluted samples at room temperature. At least three measurements were made for each sample and the results were averaged for the final values.

Thermal gravimetric analysis (TGA)

For this characterization technique, a TGA 55 (TA Instruments) was used. A dried sample with a weight between 3 and 10 mg was processed. Thus, by linearly increasing the temperature, this instrument allowed to get the weight percentage of a solid sample as a function of temperature. Among others, organic decomposition reactions could be detected.

Fourier-transform infrared spectroscopy (FTIR)

Infrared spectra in transmission mode (KBr Mini-Pellet Press, Specac) were collected by using a Thermo Scientific Nicolet iS20 FTIR spectrometer, ranging the wavenumber from 4000 to 450 cm⁻¹and allowing the detection of significative vibrational modes: the instrument is constituted by an interferometer, which allows the scansion of the above- mentioned range of the spectrum. Post-processing with the Fourier transform permits to obtain the intensity as a function of the frequency or, equivalently, the wavenumber.

Vibrating-sample magnetometry (VSM)

It allows to characterize a magnetic sample, obtaining the magnetization curve from a sample of about 10 mg via the application of a strong magnetic field. For our analysis, the field intensity maximum was fixed to 5 kOe and it scanned the range [−5; 5] kOe twice, in order to highlight the hysteretic behaviour, if present. A Lake Shore 7300- series VSM was provided by the Nanostructure Physics division (Department of Applied Physics, KTH), courtesy of Prof. Korenivski. The noise of the instrument is about 1.5 · 10⁻⁴emu.

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X-ray Powder Diffraction (XRD)

This analytical technique was used to identify the crystalline phase of the nanoparticles, allowing to obtain the peak positions and correspondent Full Width at Half Maximum (FWHM). These two parameters were useful to calculate the crystalline size in SPIONs via the Scherrer equation. The spectra are scanned in the range 2ϑ = [10^◦; 80^◦], with the Powder diffractometer PANalytical X’Pert PRO Alpha-1, which is equipped with a Copper anode (Cu-Kα1 radiation). The step size was set to 0.24^◦ in continuous mode, getting a scan speed of 0.04^◦/swhich led to a total time of about 30 minutes.

Ultraviolet–visible spectroscopy (UV-Vis)

The Ultraviolet absorption of water samples with clay was analysed via the Nanopho- tometer NP80 (IMPLEN) in order to test the effectiveness in turbidity removal of the SAPES and the bio-functionalized ones (MO-SAPES). Moreover, UV absorptions from aromatic rings can be detected. Both 200 µL (1 mm path length, virtual dilution factor 10) and 2 mL (1 cm path length) cuvettes were used for the detection.

Scanning Electron Microscopy (SEM)

This microscopy technique was extensively used to provide fast and high-resolution imaging of the different synthesised SPIONs, as well for checking the various steps that led to the formation of the final product, the bio-functionalized microspheres. The samples were prepared on a graphite-coated holder, by dropping from 10 to 20 µL of dispersion, spread all over the holder and let it spontaneously dry. The typically used voltage was 10 keV, whilst the working distance (WD) was set to about 5 mm. The instrument used for imaging was an FEI Nova 200, in the Albanova Nanolab (KTH).

Inductively Coupled Plasma Atomic Emission Spectroscopy (ICP-AES)

The quantification of the iron concentration in the SPIONs sample was attained by the use of the Thermo Scientific ICAP 6500; the data was collected and provided by the Applied Physical Chemistry subdivision (Department of Chemistry, KTH). Handling samples with known concentration ensured a high level of reproducibility and allowed to optimize several steps of the synthesis (i.e. protein grafting).

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3.4. CHARACTERIZATION TOOLS 19

Photoluminescence Spectrometry (PL)

By the use of an FP-8300 Spectrofluorometer (JASCO), the luminescence properties of MOCP were studied, allowing to obtain quantitative analyses thanks to the relation between fluorescent emission and its concentration. A 2 mL quartz cuvette was used for this purpose and emission spectra in the UV-visible range were collected.

Atomic Force Microscopy (AFM)

This technique makes use of a microscope, constituted by a cantilever with a tiny tip. The Van der Waals interactions between the tip and a specific point of the sample establish the distance between them, allowing to obtain a 3D map of the sample. 10µL of sample were dropped on a silica wafer and let dry at room temperature, before carrying out the scansion. The instrument used for this purpose was the AFM Bruker Dimension FastScan Bio, in the Albanova Nanolab (KTH). A scan rate of 1 Hz and a tip velocity of 0.303 µm/s were used for the mapping.

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Chapter 4 Models & Simulations

4.1 Magnetic Properties

Since magnetic nanoparticles exhibit superparamagnetism, thus behaving like several paramagnetic macrospins, it is possible to treat the magnetization property in a similar route as for paramagnets. Their magnetic response is described by the Langevin equation L (x) which is given by the following formula:

L = coth x − 1

x (4.1)

where the variable x is:

x = M_S⁰V B kT

with MS⁰ the bulk saturation magnetization, V the volume of the nanoparticle, B the magnetic flux, k the Boltzmann factor and T the temperature. In the general case in which the nanoparticles are characterized by a size distribution f(y), the total magnetization of the powder of nanoparticles can be written as:

M = M_S ˆ ∞

0

L f (y) dy (4.2)

where y = ^D/DM is the reduced diameter, with DM being the median diameter of the distribution and D the nanoparticle diameter [46].

According to previous studies [47], the size distribution of the nanoparticles, i.e. the Probability Density Function (PDF), can be described by a lognormal distribution:

f (y) = 1 yσ√

2π exp

"

−(ln y)² 2σ²

#

(4.3)

20

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4.1. MAGNETIC PROPERTIES 21

Hence, the probability of finding a nanoparticle with a reduced diameter in the range [0, Y ]can be found via the Cumulative Distribution Function (CDF), with the following relation:

F (Y ) = ˆ Y

0

f (y)dy (4.4)

For a specific interval, centred in y = 1 (D = DM)and defined as [1 − ε, 1 + ε], we obtain:

F (ε) = F (1 + ε) − F (1 − ε) = ˆ _1+ε

1−ε

f (y)dy

In order to model the above-mentioned nanoparticle characteristics (eq. 4.2, 4.3 and 4.4), we define the units of the main quantities used for this section: MS[emu/g], M_S⁰ [emu/cc] and H [Oe]. The other quantities, unless otherwise stated, will be ex- pressed in SI units. It is crucial to note that it was necessary to convert the above mentioned quantities into SI units in order to match the energy unit given by the thermal energy. For this purpose, the conversion equation is provided by the following relation:

B[T] · M [^A/m] = 0.1 · H[Oe] · M [^emu/cc] (4.5) In order to fit the data about the magnetization behaviour of nanoparticle powders, we substitute eqs. 4.1, 4.3 into eq. 4.2, defining three parameters p (i):

M = p (1) ˆ ∞

0

cothH³y³p (2) − 1 [H³y³p (2)]

1 y exp

"

−(ln y)² p(3)

#

dy (4.6) Comparing eq.4.6 with eq.4.2 and using the conversion equation (eq. 4.5), we find the physical quantities in relation to the chosen parameters:

M_S = p (1) pπp (3) D_M =q³

30kT p(2)

πM_S⁰ σ_M =

qp(3) 2

The parameters were found for each magnetization curve, by fitting eq. 4.6 to the experimental data. In order to automatize the procedure, a Matlab Application was developed using Matlab App Designer, and called SPfit. Its strong point lies in the possibility to install and use it, although Matlab is not installed on the computer. It is provided with an installation setup (figure 4.1.a) and customized banner (figure 4.1.b).

Moreover, its user-friendly graphic interface allows to load the data (M vs. H) and instantaneously show the comparison between the fitted magnetization curve and the experimental data, other than the calculated PDF and CDF, as shown in figure 4.1.c.

Furthermore, parameters like temperature, bulk magnetization, weight and more can easily be set in the main interface. All the useful data is highlighted in a Results window just after the fitting is complete (figure 4.1.d). Moreover, all the plots can be opened in a new window for editing with Matlab or directly saved in multiple formats. The fitted parameters can be saved as a text file. Other details can be found in the integrated guide of the program.

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22 CHAPTER 4. MODELS & SIMULATIONS

(a) (b)

(c) (d)

Figure 4.1: SPfit interface, with the install window (a), launcher (b), main window (c) and Results message (d).

Finally, the core function scripts are reported in Appendix A: magnfit() returns the fit magnetization together with the three parameters p (i) and the physical quantities MS, D_M and σM; SizeProb() and SizeDistr() provide the CDF and PDF, respectively, and plot them.

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4.2. PROTEIN STRUCTURE 23

4.2 Protein Structure

In this section, the structure of the recombinant protein MO2.1 was analysed. The sequence presented in the background (see figure 2.5) was used for homology modelling of the polypeptide. For this purpose, an online suite of tools, Phyre2, was employed, allowing to predict and analyse protein structure, function and mutations, based on a homology/analogy recognition engine. In particular, the suite protocol is able to inter- pret the protein sequence and resolve the secondary and tertiary structure of the protein, as well as their domain composition and model quality [48].

The platform provided the results with a confidence in the model of 99.9%, where 53residues, constituting the 88% of the protein sequence, were modelled by the sweet protein mabinlin-2 chain b.

The confidence value represents the probability that the protein sequence truly forms the same structure as the reported template. The generated PDB file was analysed via the software Chimera. In figure 4.3.a, the protein structure is presented, with a colour scale from blue (N-terminus) to red (C-terminus). The structure presents three α-helices, in accordance with previous studies [49, 50]. In figure 4.3.b, the protein external surface is highlighted, presenting its characteristic shell structure, which can contribute to its coagulation property.

Figure 4.2: Secondary Structure Analysis of MO2.1.

In figure 4.2, the secondary structure analysis is presented; the disordered residues constitute the 32% of the sequence, whilst the 68% of the residues arranges to form three helices. Starting from the N-terminus, the first α-helix is constituted by 12 residues (from Pro7 to Asn18), the second is the most extended with its 17 residues (from Pro26 to Val42) and the third along 13 residues, from Pro44 to Asn56.

In figure 4.4.a, the two cysteine residues, Cys12 and Cys25 are shown and highlighted with the ball-and-stick structures: each of them presents a sulfhydryl group, which allowed the covalent binding with SMBS to form the MO-SAPES. In particular, from figure 4.3.b, the residue Cys12 results quite internal to the structure and difficult to be reached by the cross-linker. Thus, in the case of MO-SAPES1, the most probable interaction between the protein and the cross-linker is due to the covalent bonding with Cys25. On the contrary, the protein presents several positively-charged spots, shown in figure 4.4.b, distributed quite uniformly along the three α-helices. These are seven arginine residues (in positions 5, 11, 17, 24, 29, 48 and 52) and one histidine residue (His36). The large amounts of amines in the protein thus contributes to the origins for

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(a) (b)

Figure 4.3: MO2.1Ribbon Structure (a) and Protein Surface Morphology (b).

the protein coagulation activity. Some of these were used for covalent bonding with the SAPES via SMBS, keeping the cross-linker even during the addition of MOCP in solution (sample MO-SAPES2), hence increasing the bonding probability. The covalent bond would essentially quench a positively-charged centre, thus inhibiting the local coagulation activity, which could have led to a decrease of the performances.

Furthermore, the residual cross-linker would also act as a bridge for two polypeptides, cross-linking them via the sulfhydryl group of one and amine group of another.

Magnetic separation can grant that only the polypeptides agglomerates with at least one covalent bond with the SAPES can remain in solution.

(a) (b)

Figure 4.4: MO2.1 Ribbon Structure highlighting cysteine residues (1) and positively- charged residues (2).

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Moreover, the residue Asp8, close to the N-terminus, could constitute a possible source for electrostatic interactions with the positively-charged surface of the SAPES.

This possibility is, though, considered quite remote, given the large amounts of positive centres surrounding the residue and the total net positive charge of the polypeptide.

These considerations allow to infer with enough confidence that no residual peptides would be released in solution by a protein-grafted coacervate during a magnetic separation process, thus establishing a stable bio-functionalized platform.

Furthermore, a simulation of a powder x-ray diffraction was attained by the use of a Matlab script, presented in Appendix B. From the previously obtained PDB file, the position and the element symbol of the atoms constituting a single protein were collected with the Matlab function readprotein(). These positions were defined with respect to a unique reference frame, corresponding to the protein centroid rc, defined as follows:

r_c= 1 N

N

X

j

r_j

where N is the number of atoms in the protein and rj the position of the j-th atom.

The scattering vector Q and its norm Q were defined from a given wavelength, num- ber of pixels in the detector, sample-detector distance and incident wavevector, with the function DefQ(). After defining the incident wavevector k and scattered wavevector k’, it is possible to use eq. 2.1 to determine the scattering vector. Let us consider a specific case, where the scattered wavevector has contributions only on the x and z directions, such that:

k’ = 2π λ

h_N

pix

2 0 D_sdi

qN_pix²

4 + D²_sd

thus, corresponding to the highest detectable value of the scattering vector on the longitudinal direction, Q^maxx . Considering an incident wavevector along the z direction,

k = 2π

λ [0 0 1]

Q^max_x = |k − k’|

whence, the sample-detector distance can be obtained as a function of Q^maxx , as follows:

D_sd = N_pix 2

1 − A

√2A − A²

where A is a term depending upon the emission wavelength λ and Q^maxx , that is:

A = (Q^max_x λ)² 8π²

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Furthermore, the function relating the sample-detector distance to Q^maxx is plotted in figure 4.5, where the Kα emission wavelength of Molybdenum (λ = 0.709 Å) and a square detector of 200 × 200 pixels (Npix = 200) was used. In this respect, this function could easily be employed to correctly set Dsd, depending on which Q range is relevant for the specific analysis. In order to relate the experimental distance D^exp_sd to the simulated one, it is necessary to know the physical detector size Ld, yielding:

D_sd = N_pixD^exp_sd Ld

From eq. 2.3, it was possible to calculate the molecular form factor of a single pro- tein – function ProtFac() – and, thus, the intensity produced from the scattered light (eq. 2.4). In this respect, a simplified formalism was used: according to previous studies [51], a significant behaviour can be obtained by computing the unweighted sum of phases from the protein atoms, as follows:

F_mol(Q) =

atom

X

j

e^iQ·r^j

This simplification allowed to speed the simulations up, and highlight the effect of the phase interference. In figure 4.6.a, the two-dimensional x-ray diffraction pattern of a single protein is shown, setting a specific sample-detector distance, Dsd = 170.

Figure 4.5: Sample-Detector Distance as a function of the maximum scattering vector value on the longitudinal axis, when an emission wavelength λ = 0.709Å and a number of pixels Npix = 200are employed.

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(a) (b)

Figure 4.6: Simulated 2D X-ray Scattering Pattern of MO2.1, for a single protein (a) and for independent random rotations (b).

This result, despite highly characteristic, can hardly be obtained experimentally. In fact, in order to detect and extrapolate the exact structure of a protein from X-ray diffraction analysis, a crystallized protein sample is required.

This step is not always attainable, especially for small proteins, such as MO2.1, which is, indeed, constituted by only 60 residues. On the contrary, powder X-ray diffraction experiments are relatively easy to be performed; freeze-dried protein samples can, directly, be used for the experimental data collection. By using specific holders, both Single-crystal and powder X-ray Diffractometers can, thus, be employed. The former would provide a 2D X-ray Diffraction pattern of the powder, whilst the latter could directly furnish the integrated powder pattern, although high quantities are usually needed.

In order to mimic the experimental conditions of a protein powder, measured via XRC, the modelled protein molecule was rotated at random angles, by applying the rotation matrix R, defined as follows:

R = R_z(α)R_y(β)R_x(γ) where:

R_x(γ) =





1 0 0

0 cos γ − sin γ 0 sin γ cos γ



 R_y(β) =





cos β 0 sin β

0 1 0

− sin β 0 cos β





R_z(α) =





cos α − sin α 0 sin α cos α 0

0 0 1





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with α, β and γ being the Tait–Bryan angles about axes z, y and x, respectively. These angles were randomly generated and the rotation matrix was applied to all the atoms constituting the protein, via rotprot(); the data related to various rotations was saved by using GenerateRotations(). Hence, the form factor of a rotated protein Fmol,kis provided by the following equation:

F_mol,k(Q) =

atom

X

j

exp (iR_k· r_j· Q)

The contributions of the rotated proteins were summed as non-interfering entities, in order to prevent any possible long-range interactions; the total intensity, thus, resulted:

|F (Q)|² =

protein

X

k

|F_mol,k(Q)|²

The 2D diffraction pattern obtained by summing over 100 rotations is plotted in figure 4.6.b, where the same parameters of the single-protein pattern were used. In order to further mirroring the experimental conditions, the temperature dependence was considered: the Debye-Waller factor of the j-th atom (DWFj) takes into account the displace- ment of a scattering atom in a molecule u²_j

, due to thermal-induced vibrations. This contribution exhibits with an exponential factor [52], viz:

DWFj = exp −Q²u²_j 3

5 Å

Figure 4.7: Simulated Powder Pattern of MO2.1 Protein.

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For the model, a generalized factor B will be employed, which represents the sum of all the single atom contributions in the protein causing displacements. The integrated intensity of the powder pattern at a specific temperature T will, hence, result:

I(Q, T ) = ˆ 2ϑ

0

|F (Q, ϑ)|² e^−BQ²dϑ

In figure 4.7, the integrated powder pattern for MO2.1 protein is shown, highlighting two characteristic peaks, at 1.3 Å⁻¹ and 2.9 Å⁻¹. A qualitative analysis was made possible by relating the Q-values to physical characteristic distances D in the protein molecule, viz:

D = 2π Q

The former peak can, indeed, be associated with the typical distance between two atoms from consecutive turns of the α-helix, about 5 Å, whilst the latter peak is in the range of intra-residue distances, on the order of 2.2 Å, precisely corresponding to the carbon-nitrogen distance in the side chain of the most abundant residue in MO2.1, Glu- tamine. The B factor was set to 0.05 Å², easily tunable by comparing the simulated pattern with experimental data.

In conclusion, this model could constitute an easy but powerful tool to identify modifications or perturbations in the protein structure, comparing the simulated pattern with experimental data from dried or dissolved protein samples. The evidence of peak shifts or long-range interactions would then constitute the proof of phenomenological changes, such as structure relaxations or assembling phenomena, like protein dimerization.

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Chapter 5 Results & Discussion

In this chapter, the experimental methods were applied in a bottom-up approach: following the synthesis routes for the superparamagnetic iron oxide nanoparticles, these were characterized by employing the characterization tools described in Chapter 4.

Thus, a deep characterization of the cross-linked coacervates was attained, aiming at highlighting their stability and functional properties.

Finally, a wide variety of instruments allowed to establish the successful crosslinking with a protein, ending up with a suggestion and related results of a possible biological and promising application in water treatment.

30

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5.1. NANOPARTICLES 31

5.1 Nanoparticles

The superparamagnetic iron oxide nanoparticles (SPIONs), synthesized according to the methodologies described in the experimental procedures, were characterized aiming at establishing the best alternative among the presented ones. The characterization techniques permitted to obtain data from different perspectives, from the magnetic properties and size distribution, to crystal structure and surface functionalization.

For the magnetic characterization, the purpose was to show the response of the SPI- ONs to an external magnetic field. The data was collected via the VSM and elaborated via the software SPfit, whose functionality was documented in Chapter 4. The magnetic behaviour allows to compute the average magnetic diameter of the nanoparticles, and study their size distribution and their uniformity. The analysed samples were the ones obtained from three different synthetic routes.

(a) (b)

(c) (d)

Figure 5.1: Magnetization Curve (a, b), PDF (c) and CDF (d) for sample CP2.

Platform for Bio-functionalization

Superparamagnetic Hybrid Microspheres as a Reliable

Platform for Bio-functionalization

GIOVANNI MARCO SALADINO

Superparamagnetic Hybrid

Microspheres as a Reliable Platform for Bio-functionalization

GIOVANNI MARCO SALADINO

Abstract

Sammanfattning

Contents

Acknowledgments

List of Figures

List of Tables

Chapter 1 Introduction

Chapter 2 Background

2.1 Superparamagnetism

2.2 Iron Oxide Nanoparticles

2.3 X-ray Diffraction

2.4 Polyelectrolyte Self-assembly

2.5 Coagulation Property

2.6 Moringa Oleifera

Chapter 3

Materials & Methods

3.1 Synthesis of Nanoparticles

3.1.1 Coprecipitation

3.1.2 Microwave-assisted Synthesis

3.1.3 Synthesis Reaction

3.2 Coacervation and Stabilization Process

3.3 Protein Cross-linking

3.4 Characterization Tools

Chapter 4

Models & Simulations

4.1 Magnetic Properties

4.2 Protein Structure

5 Å

Chapter 5

Results & Discussion

5.1 Nanoparticles