Soft and hard interactions between polystyrene nanoplastics and

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Soft and hard interactions between polystyrene nanoplastics and human serum albumin protein corona Shinji Kihara, Nadine J van der Heijden, Chris Kinglsey Seal, Jitendra Mata, Andrew Whitten, Ingo Köper, and Duncan J. McGillivray Bioconjugate Chem., Just Accepted Manuscript • DOI: 10.1021/acs.bioconjchem.9b00015 • Publication Date (Web): 01 Mar 2019 Downloaded from http://pubs.acs.org on March 3, 2019

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Bioconjugate Chemistry

Soft and Hard Interactions between Polystyrene Nanoplastics and Human Serum Albumin Protein Corona Shinji Kihara1, 2, Nadine J. van der Heijden1, 2, Chris K. Seal1, 2, Jitendra P. Mata3, Andrew E. Whitten3, Ingo Köper4, and Duncan J. McGillivray*1, 2

1

School of Chemical Sciences, The University of Auckland, Auckland 1010, New Zealand

2 The

3

MacDiarmid Institute for Advanced Materials and Nanotechnology, Wellington 6140, New Zealand

Australian Centre for Neutron Scattering, Australian Nuclear Science and Technology Organisation, Lucas

Heights, NSW 2234, Australia 4

Institute for Nanoscale Science and Technology, College for Science and Engineering, Flinders

University, Adelaide, SA 5042, Australia KEYWORDS: nanoplastics, protein corona, soft corona, hard corona, human serum albumin, nanotoxicology

ACS Paragon Plus Environment

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Bioconjugate Chemistry 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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ABSTRACT

Upon contact with biological fluids, the surface of nanoparticles is surrounded by many types of proteins, forming a so-called “protein corona”. The physicochemical properties of the nanoparticle/corona complex depend predominantly on the nature of the protein corona. An understanding of the structure of the corona and the resulting complex provides insight into the structure-activity relationship. Here, we structurally evaluate the soft and hard components of protein corona, formed from polystyrene (PS) nanoplastics and human serum albumin (HSA). Using circular dichroism (CD) spectroscopy to elucidate the structure of HSA within the complex, we establish the effect of nanoparticle size and pH on the nature of the protein corona formed- whether hard, or soft. Despite the weak interaction between PS and the HSA corona, small angle neutron scattering (SANS) revealed the formation of complex structure that enhance the intermolecular interactions between HSA proteins, PS particles and the HS/PSA complexes. Fractal formation occurred under conditions where the interaction between PS and HSA was strong; and, increasing HSA concentrations suppressed the degree of aggregation. The size of the nanoparticles directly influenced the nature of the protein corona, with larger particles favouring the formation of a soft corona, due to the decreased PS-HSA attraction.


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INTRODUCTION With the significant amount of plastic waste in the environment, there is concern that the environmental concentration of polymeric nanoparticles (nanoplastics) will increase considerably in the future, due to the natural weathering1-2 and biodegradation3 of bulk plastic. A recent study4 also demonstrated that microplastics can fragment into nanoplastics when ingested by Antarctic krill (Euphausia superba). The toxicity of nanoplastics is known to be highly dependent on their physical and chemical properties. Nanoparticles that are intended to be taken up into biological systems (particularly nanoparticles used for biomedical applications) are carefully designed in order to ensure they are not toxic. Unlike these engineered nanoparticles, nanoplastics present in the environment have a mixture of sizes, elemental compositions, geometries, and surface functional groups because of uncontrolled manner in which they form. This uncontrolled nature of environmental nanoplastics contrasts with the highly controlled nature of engineered nanoparticles5-6. Engineered nanoparticles are designed to minimise the risk to health for intentional uses in humans. The random nature of environmental nanoplastics lack this design of protection. Toxicological studies conducted on marine organisms have demonstrated the potential adverse effects resulting from nanoplastics2, 5-8. Nanoplastics are also known to propagate up to higher ranks in food chains15, which may cause successively hazardous effects to


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humans. Despite these established physiological effects, the mechanisms behind their toxic actions has been studied infrequently. Much attention has been paid to interactions between nanoparticles (in general) and cellular membranes9-12 in an attempt to elucidate the membrane disruption and penetration mechanisms. However, the research is still far away from identifying the origin of these adverse effects, on a molecular level. It is well established that the surfaces of nanoparticles are covered by various kinds of proteins and other biological molecules when in contact with a biological system13-17. As a result, the nanoparticles now exist as a new entity, a complex of nanoparticles with layers of proteins (so called protein corona13-14, 18), whose surface characteristics alter depending on its composition. The nature of protein coronae is also dependent on the intrinsic properties of the nanoparticles, their chemical compositions14, 19, shape20, and surface chemistry14, 19, 21. Proteins within coronae are divided into two groups: “hard” and “soft” coronae. Those that are adsorbed tightly on the surface are referred to as “hard” and are thought to have a more significant impact on the surface properties of the nanoparticles. Loosely bound nanoparticle/proteins complexes are called “soft” coronae. Although the biological relevance of the protein coronae is not fully understood, the proteins within hard coronae are known to partially lose their biochemical activities, resulting from modification to the secondary structure of proteins22. Intriguingly, proteins that interact softly with nanoparticle surfaces have also been reported to show decreasing enzymatic activities, despite the lack of conformational changes23. The


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biological relevance of the hard interaction has been frequently investigated22, 24-25 due to the their distinctive stability on nanoparticle surfaces18, 26. While the modified protein functionality in hard coronae can be explained by the disruption of protein structure, the same association cannot be made for soft coronae. Further assessment of protein interactions with nanoparticles is essential to elucidate the origin of modified protein functionality in soft coronae, and importantly the role of corona interactions with biological molecules. The present work investigates the structure of soft and hard protein coronae that form around nanoplastics which could shed light on different roles that each plays. This scientific question has been laid out in the past27-28, although to the best of our knowledge is yet to be studied in detail. Particularly, we investigate soft and hard protein coronae, which form from human serum albumin (HSA) on polystyrene (PS) colloids with a particular focus on the geometry of each corona, PS/HSA complex, and interaction between complexes. HSA was chosen as it has previously been found to be a component in both soft and hard corona19. This is, in part, due to its relative abundance in blood plasma19. PS colloids were chosen as the model nanoplastic, as the particle size can be changed without modifying the surface functional groups. Using PS allows to develop a controlled nanoparticle (NP), varying both surface chemistry and size. PS nanoparticles of two different sizes were used in order to assess the influence of size on the formation of protein coronae. In addition, the relative abundance of PS in the environment and its reported adverse


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physiological effects make the results acquired from this model system biologically relevant29-30. CD spectroscopy was used to probe the secondary structure of HSA before and after the interaction with PS nanoplastics and to distinguish the formation soft corona from hard corona. The protein adsorption behaviour and resulting geometries of the PS/HSA complexes were characterised by DLS and SANS. In SANS the H2O/D2O ratio of solvent was adjusted to match the neutron scattering length density (SLDn) of the solvent with the PS particles (Table S1) to highlight the geometry of HSA component of the PS/HSA complexes for both the soft and the hard coronae.

RESULTS AND DISCUSSION Circular Dichroism (CD) Spectroscopy The secondary structure of HSA before and after the introduction of HSA was evaluated by CD spectroscopy. A distinction between soft and hard coronae is made by looking at the preservation of the secondary structure of the protein after introducing nanoparticles. If the secondary structure is preserved, then we define the corona as soft; if it is lost then we define the corona as hard. Irrespective of the PS nanoparticle size, the secondary structure of HSA was unaffected at pH 7.4 (Figure 1 left), making the interaction between PS particles and HSA soft. However, the CD spectrum observed for PS-s/HSA complex at pH 5.0 showed a partial unfolding of 𝛼 helices, 51% ( ± 2%) to 46% ( ± 2%) (Figure 1


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right), leading to a hard interaction. This conformational change is attributed to the direct adsorption of HSA onto the PS-s surface and the free energy minimisation within this newly formed complex31. The absence of the change in the CD spectra, before and after the introduction of PS-L at pH 5.0, confirmed the presence of soft interaction (Figure 1 right). The summary of secondary structure content of all the samples is found in Table S2 and S3.

Figure 1. CD spectra of HSA, before and after the introduction of PS-s and PS-L at pH 7.4 (left) and pH 5.0 (right).

Dynamic Light Scattering (DLS) and zeta potential measurements


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Figure 2. Z-average distributions obtained by DLS for HSA with PS-s in pH 7.4 (a), in situ Z-average study of PS-s/HSA at pH 7.4 (b), PS-s/HSA at a higher concentration of HSA (c), PS-s/HSA complex at pH 5.0 (d), PS-L/HSA complex at pH 7.4 and 5.0 (e-f). The final concentration of PS and HSA used was 1.0 mg mL-1, unless otherwise, stated.

DLS is a frequently used technique to characterise the adsorbed layer thickness of colloidal suspension and resulting aggregates23, 32-33. Steady-state DLS experiments were conducted for the HSA (1.0 mg mL-1) and small PS-s (1.0 mg mL-1) prior to mixing, and the hydrodynamic diameter (Z) of the HSA/PS-s was measured after 1.0 h when the system was equilibrated (Figure 2a). A small increase of the average Z (~4.0 nm) was observed when the PS-s particles were mixed with HSA. This was followed by an in situ


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DLS experiment (Figure 2b) under the same conditions which revealed that the incorporation process took approximately 30 min to reach an increase in approximately 4.0 nm. The size distribution of PS-s/HSA complex at pH 5.0, acquired by multimodal analyses, is presented in Figure 2d. An increasing Z-average from 33 nm to 120 nm was confirmed as well as the formation of large aggregates (< 5 𝜇m). Consistent with the subtle increase of Z-average for PS-s/HSA soft corona complex at pH 7.4 (Figure 2), the PS-L/HSA soft corona complexes showed a small increase in the Z-average regardless of the pH, without larger aggregate formation.

Additionally, zeta potentials of these single components and complexes were measured to elucidate the nature of interactions that PS and HSA undertake. PS-s and PS-L both showed negative surface charges at each pH (Table S4), whereas, the zeta potential of HSA significantly became neutral as the pH was changed from 7.4 to 5.0 (-12.2 ± 3.2 mV to -4.4 ± 4.5 mV). The neutralisation of the HSA is caused by two factors: protonation of aspartic acid and glutamic acid, and protonation of histidine. Based on the calculation using Equation S1-2, 5% of aspartic acid (~2 molecules) and 17% of glutamic acid (~10 molecules) are protonated at pH 5.0, resulting in the suppression of net negative charge. Additionally, 90% of histidine undergo protonation (~14 molecules), and so the net charge becomes more positive. The zeta potentials of PS-s/HSA complex were -15.5 mV (


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± 3.0 mV) and -15.8 mV ( ± 9.8 mV) at pH 7.4 and 5.0, respectively, both of which showed a similar extent of charge suppression in comparison with the free PS-s particles. Intriguingly, the zeta potential of PS-L/HSA at pH 7.4 was -43.4 mV ( ± 7.1 mV), showing a smaller degree of interaction between PS-L and HSA at pH 7.4, while at pH 5.0, the zeta potential value of -9.0 mV ( ± 6.8 mV) was observed. SANS characterisation of single components The diameters of the PS-s and PS-L were found to be 230 Å (with a polydispersity of 17%) and 2374 Å (with a polydispersity of 2%) based on the sphere model (Figure S1 and S2, and Table S5 and S6). The fitted diameters were smaller than the average size determined in the DLS study, which was expected due to the fact that the size resolved by DLS also takes into account of the movement of the particles34. The neutron scattering data for PSL

(9.0 mg mL-1) was collected in 25% d-buffer to ensure that the PS particles are contrast

matched, and no significant scattering feature was observed (Figure S3). The dimensions of HSA estimated by the fit of an ellipsoid to the neutron scattering data were 15.6 × 43.7 Å, which is in a reasonable agreement with previously reported values from the literature35 (Figure S4 and Table S7). SANS characterisation of PS/HSA complex system


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Figure 3. SANS profiles of PS-s/HSA complexes at pH 7.4 (left) and pH 5.0 (right, andd their corresponding individual components). The inset in both plots show the residual between the scattering intensities from the PS-s/HSA complex and the sum of individual components. The concentration of the PS-s used in the complex was fixed at 9.0 mg mL-1.

Figure 4. SANS profiles of PS-s/HSA complex at pH 7.4 in 100% d-buffer (left) and in 25% d-buffer with HSA (3.0 mg mL-1) collected in 100% d-buffer as a comparison (right). The SANS profile was fitted with sphere model with a structure factor (sticky hard sphere).


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Table 1. Fitting parameters of sphere model with structure factor (sticky hard sphere) for PS-s/HSA complex in pH 7.4. The radius and the SLD contrast fitted here takes into account of both PS and HSA.

100% d-buffer at

Radius / Å

perturb

Stickiness

∆SLDn / 10-6 Å-2

135a ± 0.4

0.100 ±

0.0856 ±

4.45

0.003

0.0008

pH 7.4 PS-s/HSA

aThe

optimised polydispersity was 17%.

SANS profiles of HSA/PS complexes were divided into two distinctive q ranges for the convenience of describing two distinctive structural features at different length scales (Figure 3). The q range I encodes information relating to the structural features from individual PS-s and HSA, while q-range II encodes information relating to the geometry of PS-s/HSA complexes. The insets of Figure 3 show the residual scattering intensity after subtracting the sum of scattering from PS-s and HSA from PS-s/HSA complex. The small residual at q-range I at pH 7.4 reflects the absence or small portion of PS-s and HSA experiencing a direct interaction. The resulting scattering at q range I is best described by a sum of a sphere model and an ellipsoid model for q range I (Figure S5 and Table S8). Nevertheless, the q range II could not be described, suggesting that these models do not capture the geometrical arrangement of the complexes and/or its interparticle interaction. Hence, a combination of a sphere model and a structure factor (hard sticky sphere) was


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used to describe the q range II (Figure 4) with “stickiness” and “perturb” as a measure of the strength of interparticle interaction (PS-s/HSA – PS-s/HSA). To provide further insight, a SANS experiment was carried out in 25% d-buffer, which contrast matches the PS-s particles (Figure 4 right and Figure 5). Rg of the HSA/PS-s complex in 25% d-buffer resolved by Guinier analysis was approximately 134 Å which compares with 116 Å and 400 Å for the PS-s and PS-s/HSA complexes in 100% d-buffer, respectively (Figure S6). The resulting neutron scattering reflects that HSA participated in the formation of complexes, and likely that the HSA is decorated on the surface of PS-s spheres.

Figure 5. Proposed structural model of PS-s/HSA complexes in pH 7.4 (top) and pH 5.0 (bottom). The background of the figures on the right are coloured to portray the neutron scattering data collected using 25% d-buffer.


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Figure 6. SANS profiles of PS-s/HSA complex in 100% and 0% d-buffer at pH 5.0, fitted with a fractal model. Table 2. Fitting parameters of fractal moodel for PS-s/HSA complex in pH 5.0.

PS-s/HSA at pH

Radius / Å

5.0

Fractal

Correlation length

dimension

/Å

∆SLDn / 10-6 Å-2

100% d-buffer

135 ± 0.23

2.3 ± 0.041

1556 ± 0.2

5.0

0% d-buffer

135 ± 0.35

2.3 ± 0.064

1556 ± 0.23

1.8

aOptimised

value of PD was 2%.


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Figure 7. SANS profiles of PS-s/HSA complex in 100% d-buffer at pH 5.0 with various HSA concentrations (left) and PS-s/HSA complex in 25% d-buffer at pH 5.0 with various HSA concentrations.

The SANS profiles of PS/HSA complex at pH 5.0 (Figure 3 inset right) shows that the scattering from PS-s/HSA complex can no longer be explained by the summation of scattering from individual components. This change in the q range I can be attributed to the change in the PS-HSA interface via direct adsorption. Fitting the q-range I at pH 5.0 with a core shell model supports the direct adsorption model with a partial coverage (Figure S7 and Table S9). Unlike pH 7.4, the upturn in q range II cannot be accommodated by a sphere model with structure factor (sticky hard sphere) with a given volume fraction. The aggregation of the colloidal system is better described by a fractal model, where both primary particles (PS-s/HSA complex) and aggregates (geometric arrangements of PSs/HSA

complexes) can be considered in q range I and q range II, respectively. Global

fitting was used to fit the scattering curves obtained in 100% d-buffer and 0% d-buffer in


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Figure 6 (fitted parameters in Table 2). In particular, the SLDn of the solvent was fixed according to the D2O content in each, and the fractal dimension (Dm) and correlation length were fitted with appropriate constraints. The radius obtained for the model was 135 Å ( ± 0.4 Å) which took into account of the radius of primary particles (PS-s and HSA). For mass fractals, the power law I(q) ∝ q-Dm relationship holds, as opposed to the power law relationship for surface fractal36, described as I(q) ∝ q-6+Dm. Here, the power law fit for PS-s/HSA (with HSA concentration of 3.0 mg mL-1, presented in ) complex shows a relationship I(q) ∝ q-2.3. The observation that this characteristic upturn in the low q region lasts more than one decade in q and given the fractal dimension of 2.5 ( ± 0.04) for the power law fit, supports a mass fractal formation. SANS curves with various concentrations of HSA (0 – 15 mg mL-1) and a fixed concentration of PS-s (9.0 mg mL-1) are presented in Figure 7. The increasing scattering intensity in q region I is attributed to the scattering from individual HSA. The change in the steepness of the upturn in q region II, however, shows a modification to the geometry of the PS-s/HSA complex, which depends on the HSA concentration. Power law fitting in q region II showed a decreasing coefficient from q-2.3 to q-1.8, as the HSA concentration increased from 3.0 mg mL-1 to 15.0 mg mL-1. If the assumption that the power law relationship I(q) ∝ q-Dm holds for the PS-s/HSA complexes at all the HSA concentrations, the power law coefficients, q-P, are interchangeable with mass fractal coefficients. The mass fractal dimension describes the “compactness” of the fractal aggregates36-38, with


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more compact aggregates, with a higher local concentration, having a higher dimension, Dm (cartoon shown in Figure S8). The decrease of fractal dimension with an increasing HSA concentration can be explained by charge screening of the PS-s by HSA bound to the surface. With an increasing concentration of HSA on the PS-s surface, additional HSA is more likely to experience electrostatic repulsion from HSA bound to other PS/HSA complexes, leaving a spatially limited adsorption site on PS. This results in a less branched fractal aggregate (low Dm), suggesting that minimal aggregation would be observed with an excess HSA concentration. Further evidence of this structural model can be found in SANS curves for PS-s/HSA with two HSA concentrations (3.0 and 9.0 mg mL-1) contrast matched in 25% d-buffer. The increase from q-1.6 to q-2.1 in these SANS curves (Figure 7 right) reflects a local aggregation of HSA on PS-s surfaces. The SANS profile of PS-L/HSA complexes at pH 7.4 shows that the interaction between the PS-L and HSA is minimal (Figure 8 left and that a combination of spherical and ellipsoid model could accommodate the scattering profiles over the entire q range (Figure 8, Table S10). For pH 5.0, structure factor (sticky hard sphere) was added to the model to describe the upturn at a low q range (Fitting parameters shown in table S11).


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Figure 8. SANS profiles of PS-L/HSA complexes at pH 7.4 (left) and pH 5.0 (right). The scattering profiles of PS-L is fitted with sphere model. The scattering profile of PS-L/HSA (3.0 mg mL-1) complex at pH 5.0 is fitted with a combined model of sphere, ellipsoid, and structure factor (sticky hard sphere), else the scattering profiles are fitted with a combination of sphere and ellipsoid models.

Figure 9. Crystal structure (1AO6)39 of HSA from two different angles with colour codes (red for positively chargeable amino acids and blue for negatively chargeable amino acids), portraying the potential sites for PS particles to experience an electrostatic interaction.


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Soft and hard HSA corona around PS nanoplastics The origin of the interaction between the HSA soft corona with PS surface is maintained by a subtle balance of the electrostatic interaction. Despite having an overall negative charge, the HSA surface is a mixture of negatively and positively charged amino acids as shown in Figure 9. This weak interaction observed in HSA soft corona is attributed to an attractive interaction between the positively charged residues and the PS surface, while negatively charged residues, particularly those in the vicinity of the positively charged residues, inhibit a strong interaction. When the pH was lowered down to 5.0, protonated histidine (providing positive charge), aspartic acid and glutamic acid (losing negative charges) enhanced the electrostatic attraction. As a result, HSA experienced a strong attraction to PS particles, forming larger aggregates. However, greater HSA concentrations led to a lesser degree of aggregation. The finding suggested that an excessive HSA concentration would result in an extensive coverage of HSA, and that protein molecules on nanoparticle surface mitigate interactions with other PS particles. We expect that a real biological system follows such case. When compared with the smaller analogue, PS-L exhibited a weaker attraction to HSA. In the literature, the binding affinities of proteins increase as the binding site becomes less curved due to the reduced free energy22-23, 40. However, the opposite effect was reported


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for TiO2 nanoparticles with pepsin, where smaller size facilitated more proteins on the surface than its larger analogue41. Our finding for PS/HSA complexes follows such an example. Many of the protein-protein interactions are known to be transient, yet significant in their functions42-44. For soft corona, despite the absence of conformational change, the interparticle interaction between the PS/HSA – PS/HSA and HSA/HSA, could alter the way native proteins interact with other proteins. However, to correlate the observed interparticle interaction between soft coronae to their biological relevance, an assessment of protein functionality, such as enzymatic activities, is required. Nevertheless, the presence of interparticle interactions would be an important parameter to add to the current understanding of soft coronae.

CONCLUSION We studied the interaction between negatively charged PS nanoparticles and HSA, with a particular focus on the structure of soft and hard protein coronae. CD spectroscopy was first used as a diagnostic tool to identify the nature of protein corona at each condition. A hard interaction was observed for PS-s/HSA complex at pH 5.0, though only soft interaction was observed with PS-L/HSA at pH 5.0. DLS revealed differences in this


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interaction, based on size distributions and kinetic studies, highlighting a subtle increase in the Z-average for soft interactions and aggregate formation for hard interactions. Specific geometries of HSA soft and hard corona within PS/HSA complexes were evaluated by SANS. The SANS profiles of the complex system strongly supported the presence of interparticle interaction between PS/HSA-PS/HSA complexes. The proposed structural model of a soft corona provides additional information to the existent understanding of the soft corona. At pH 5.0, the formation of larger aggregates for PSs/HSA

complexes was confirmed both by DLS and SANS. The resulting aggregates were

described by fractal model. Furthermore, we found that an increasing HSA concentration lessens the degree of aggregation by charge screening. The finding suggested that with excess HSA, the aggregation caused by hard corona could be minimised. Although the soft and hard components of has corona around PS nanoplastics were characterised in this work, it should be noted that these structures may change when soft and hard components co-exist, and the types of nanoplastics and proteins in the corona should also play an important role. In parallel to structural analyses, protein functionality and their effect on other biological molecules would be crucial to illustrate the biological relevance of protein coronae. METHODS AND MATERIALS


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Carboxylic-terminated polystyrene nanoplastics (PS-s) were purchased from SigmaAldrich (CML Latex beads, 0.02 𝜇m). Larger polystyrene nanoplastics functionalised with carboxylic acid (PS-L) were synthesised via an emulsion-free polymerisation method described elsewhere45. The synthesised PS-L was dialysed extensively against ultrapure water (Milli-Q, resistivity = 18.2 M𝛺 cm) prior to further characterisation. NaCl (ECP, 99.5%), KCl (99.5%, ECP), Na2HPO4 (99%, Sigma Aldrich), KH2PO4 (99.5%), and citric acid (99.5%, Sigma Aldrich) were used to prepare buffer solutions. For neutron experiments, both PS-s and PS-L were dialysed twice, over a period of 24 h, against D2O (provided by the Australian Nuclear Science and Technology Organisation (ANSTO)). Unless stated, all the reagents were used without further purification.

Circular Dichroism (CD) spectroscopy Circular dichroism (CD) experiments were performed on a Chirascan spectrometer (Applied Photophysics, UK) over the range of 180 nm to 360 nm, at 0.5 nm intervals, using a quartz cuvette of 1.0 mm path length (Hellma cells Pacific, Singapore). The spectra were recorded for the samples (400 µL) at a scan rate of 0.5 s per point and 1.0 nm bandwidth. A minimum of five scans were averaged prior to the data conversion to absolute CD values. HSA and PS nanoplastics were dispersed in 10 mM sodium phosphate buffer


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without saline at pH 7.4. The raw CD signal (𝜃) was, then, converted to mean residual ellipticity ([𝜃]MRE) using the equation below:

[𝜃]𝑀𝑅𝐸 =

𝜃 𝐶𝑟𝑙

where, Cr is protein concentration and 𝑙 is the cuvette path length (1.0 mm). Spectral deconvolution was performed using CONTIN algorithm46 with a reference set of SP17547 available on DICHROWEB46.

Dynamic Light Scattering (DLS) and zeta potential measurements Particle size distribution and zeta potential analyses were carried out on a Malvern Instruments Nanozetasizer ZS equipped with a 633 nm laser. The size distribution of PS nanoplastics and HSA in PBS buffer (pH 7.4) was measured in non-invasive back scatter (NIBS) mode, with the photomultiplier detector placed at 173° relative to the incident beam, a measurement path length of 3.00 mm and an attenuation factor of 9. The temperature of the samples was maintained at 23 °C with 120 s of temperature equilibration time. The measurements comprised of 14 runs and with three repeats combined to provide average results. For the time resolved experiments, each run comprised of 10 s data acquisition with six repeats, making the time interval at each point 60 s. For zeta potential determination, the Smoluchowski approximation was used.


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Small-angle Neutron Scattering (SANS) measurements and data analysis SANS measurements were carried out on BILBY, the time-of-flight small-angle neutron scattering (SANS) instrument, at ANSTO, Lucas Heights, Australia48. Samples were suspended in three different deuterated buffers (d-buffer) at the following H2O:D2O ratios- 0%, 25%, and 100%. The 25% d-buffer was used to mask the neutron signals from PS particles. The samples were placed in a 1.0 mm path-length quartz Hellma cell. The buffer solutions at pH 7.4 contained Na2HPO4 (10 mM), KH2PO4 (3 mM), NaCl (132 mM) and KCl (2.7 mM), and the pH was adjusted with NaOH dissolved in D2O (50 𝜇M). For the acidic buffers, citric acid (10 mM) and NaCl (132 mM) was used with NaOH dissolved in D2O to make pH 5.0 solution. Scattering data were radially averaged (under the assumption of isotropic scattering) and placed on an absolute scale using the direct beam intensity. The value of q was defined as

𝑞=

4𝜋𝑠𝑖𝑛𝜃 𝜆

where 𝜆 is the wavelength of the incident neutron beam and 2𝜃 is the angle of scattering. For the PS-s and HSA, neutrons with wavelengths between 2–20 Å were collected on 2dimensional detector panels positioned at 7.000 (rear), 4.500 (horizontal curtains) and 3.500 m (vertical curtains) from the sample (q-range = ~0.002 – 0.340 Å-1, 𝛥𝜆/𝜆 = 12.4-


24

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14.3%). For PS-L and PS/HSA complexes, the rear detector was moved to 17.000 m from the sample (q-range = ~0.001 – 0.340 Å-1, 𝛥𝜆/𝜆 = 9.0 - 14.3%). Neutron

scattering

curves

were

fitted

using

the

SasView

software

(http://www.sasview.org/). The scattering intensity from bare PS particles were fitted with a sphere model 49, and that of HSA was fitted with a ellipsoid model50. For a PS/HSA complex system, a sphere model with a structure factor (sticky hard sphere)51, and a fractal model37 were used. The radius of gyration (Rg) was resolved using the AutoRg function in the ATSAS package (2.8.2)52.


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ACKNOWLEDGEMENT S. Kihara thanks The University of Auckland for the doctoral scholarship and would also like to thank AINSE Limited for providing financial assistance (Award - PGRA) to enable work on the research. We would also like to thank ANSTO for the provision of neutron beamtime (P6925 & P6766). Prof. John W. White (Australian National University) is also acknowledged for valuable discussions.

SUPPORTING INFORMATION Supporting information is available. CORRESPONDING AUTHOR Duncan J. McGillivray Email: [email protected]

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