Characterization of ATP-dependent protein dynamics under native-like conditions

Harsha Ravishankar

Department of Chemistry Umeå 2020

This work is protected by the Swedish Copyright Legislation (Act 1960:729) Dissertation for PhD ISBN: 978-91-7855-302-0 (print) ISBN: 978-91-7855-303-7 (pdf) Information about cover design / cover photo / composition Electronic version available at: http://umu.diva-portal.org/ Parts of this thesis have been published previously in: 978-91-7729-775-8 (print) Printed by: VMC-KBC, Umeå University Umeå, Sweden 2020

To Amma and Appa…

“The great secret is this: it is not enough to have intuitions; we must act on them; we must live them.”

- - Patanjali, The Yoga Sutras

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Table of Contents Abstract ............................................................................................... vi

Populärvetenskaplig sammanfattning ............................................. viii

Abbreviations ....................................................................................... x

List of publications ............................................................................. xii

Contribution report .......................................................................... xiii

1. Introduction ...................................................................................... 1

1.1 General protein structures ............................................................ 1

1.2 Protein structural dynamics ......................................................... 1

1.3 Adenylate kinase ........................................................................... 3

1.4 Biological membrane environment ............................................... 5

1.5 Membrane proteins ...................................................................... 5

1.6 Protein transport of ions across membranes ................................ 6

1.7 P-type ATPases .............................................................................. 7

1.8 Ca2+-transporting P-type ATPases (SERCA) .................................. 9

1.9 Zn2+-transporting transmembrane protein (ZntA) ...................... 11

2. Methods .......................................................................................... 13

2.1 Infrared (IR) spectroscopy ......................................................... 13

2.2 Fourier Transform Infrared (FTIR) spectroscopy ...................... 13

2.3 FTIR spectroscopy of proteins .................................................... 14

2.4 Applications of FTIR spectroscopy ............................................. 15 2.4.1 Reaction-induced difference FTIR spectroscopy ...................................... 15 2.4.3 Attenuated total reflectance (ATR) FTIR spectroscopy ........................... 16

2.5 X-ray scattering .......................................................................... 17 2.5.1 Scattering by atoms .................................................................................... 17 2.5.2 Scattering by protein solutions ................................................................. 19

2.6 Time-resolved X-ray solution scattering (TR-XSS) .................... 20 2.6.1 Synchrotron radiation ............................................................................... 20 2.6.2 Pump-and-probe experiments ................................................................. 20 2.6.3 Difference X-ray scattering analysis ........................................................ 21 2.6.4 Spectral decomposition ............................................................................ 22 2.6.5 Structural analysis .................................................................................... 23

2.7 Molecular dynamics simulations ................................................ 23

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2.7.1 Theory ........................................................................................................ 23 2.7.2 Targeted MD simulations ......................................................................... 24 2.7.3 Membrane simulations ............................................................................. 25

3. Scope of the thesis ........................................................................... 26

4. Results and Discussion – Paper I .................................................... 27

4.1 Structural dynamics of P-type ATPases ....................................... 27

4.2 Production of a Shigella sonnei Zn2+ transporting P-type ATPase27

4.3 Measurement of protein activity using a biochemical colorimetric assay ................................................................................................ 28

4.4 Infra-red spectral signature of ssZntA activity ........................... 32

4.5 Triggered time-resolved measurements of ssZntA activity ......... 33

4.5 Summary of paper I ................................................................... 40

5. Results and Discussion – Paper II ................................................... 41

5.1 Structural dynamics of the sarcoplasmic reticulum Ca2+

transporting pump (SERCA). ........................................................... 41

5.2 Sample preparation .................................................................... 42

5.3 Time-resolved X-ray solution scattering (TR-XSS) data collection42

5.5 Kinetic modelling of the TR-XSS data ......................................... 43

5.6 Comparison to X-ray crystallography data ................................. 45

5.7 Simulating transition dynamics .................................................. 46

5.8 Membrane MD simulations ........................................................ 47

5.9 Structural interpretation ........................................................... 48

5.10 Summary of Paper II ................................................................ 50

6. Results and Discussion – Paper III ................................................. 51

6.1 Lipid interactions and structural stability of SERCA transient intermediate states. ......................................................................... 51

6.2 Simulated systems ...................................................................... 52

6.3 Structural dynamics in the TR-XSS pre-pulse state .................... 52

6.2 Intermediate (1.5 ms) state structural dynamics and stability .... 53

6.3 Late (13 ms) state structural dynamics and stability ................... 55

6.4 Lipid environment ..................................................................... 56

6.5 Summary of Paper III ................................................................. 58

7. Results and Discussion – Paper IV .................................................. 59

7.1 Introduction and outlay of the AK studies ................................... 59

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7.2 TR-XSS results ........................................................................... 60

7.3 AK TR-XSS data structural refinement ....................................... 61

7.4 Summary of Paper IV ................................................................. 62

8. Concluding remarks and future directions ..................................... 63

9. Acknowledgements ......................................................................... 64

10. References ..................................................................................... 66

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Abstract Proteins are biological macromolecules capable of accelerating biochemical reactions. To accomplish this, proteins undergo changes in their molecular structure. Advances in structural biology have resulted in ever-increasing numbers of high-resolution protein structures. However, the majority of transient intermediate states will not amendable with traditional structural determination methods. Therefore, understanding how protein structural changes are correlated with the biological function necessitates development of methods that characterize the reaction in the native environment. P-type ATPase membrane transporters and the adenylate kinase (AK) are two ATP-dependent proteins that undergo extensive conformational change in their reaction cycles. While P-type ATPases maintain concentration gradients of ions across the cellular membranes, AK regulates cellular energy homeostasis by catalyzing interconversion of nucleotides. Resolving P-type ATPase and AK temporal and spatial structural dynamics is crucial to understand how these proteins are triggered by ATP for functionality. To pave way for time-resolved X-ray characterization of ATP-dependent conformational changes, it was necessary to identify optimal conditions for triggering protein reactions. Therefore, time-dependent Fourier-Transform Infra-Red (FTIR) spectroscopy of a recombinant Zn2+-transporting ATPase was used to optimize activation by photolysis of caged ATP. These conditions were then used to track structural dynamics of the Ca2+-transporting sarcoplasmic reticulum ATPase (SERCA) in skeletal muscle native membranes. Fast single-cycle dynamics were registered with the formation of an intermediate state at 1.5 ms followed by steady-state accumulation at 13 ms. The molecular dynamic (MD)-based structural refinement procedure showed that the 13-ms transient intermediate represented an ADP-sensitive, phosphorylated Ca2+-bound E1 state (Ca2E1P), with a domain arrangement that has so far eluded structural characterization. MD simulations of the identified SERCA transient intermediates further finetuned their positions in the reaction cycle. The 1.5-ms state was assigned to an ATP-bound state prior to phosphorylation, while the 13-ms state was stable in its Ca2E1P conformation. Because the simulations were performed in multicomponent lipid bilayers mimicking the native membrane, specific state-dependent lipid interactions were also identified. Finally, the wider applicability of the time-resolved X-ray method to study ATP-dependent protein dynamics was demonstrated by tracking AK structural dynamics. A transient intermediate at 5 ms was identified that showed closing of the ATP-binding domain prior to the NMP-binding domain, in the presence of both ATP and AMP substrates. This study provided conclusive experimental proof of the relative ordering

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of domain closure that had been predicted by several computational studies. In summary, the work presented in this thesis has contributed to developing the time-resolved X-ray method to study the structural dynamics of ATP-dependent proteins.

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Populärvetenskaplig sammanfattning Proteiner är biologiska makromolekyler vars arbetsuppgifter i cellen möjliggör liv. För att kunna utföra sina tillordnade funktioner måste proteinets struktur i många fall förändras. Denna inneboende dynamik är inkodad i proteinets aminosyrasekvens och har optimerats genom evolutionsprocessen. I många fall finns det molekyler som kan starta igång ett visst proteins funktion. En sådan molekyl är adenosintrifosfat (ATP) som är en organisk förening som tillhandahåller energi till ATP-beroende proteiner. Ett exempel är P-typs ATPaser som är proteiner insprängda i cellens membran som transporterar olika joner. Denna transport möjliggörs av proteinets strukturella förändringar som sätts igång av energi tillförd av ATP molekylen. Även proteinet som reglerar tillgången av ATP i cellen genomgår stora konformationsförändringar. Detta protein är adenylatkinas (AK) och katalyserar interkonversion av nukleotider. För att förstå hur dessa proteiner kan startas igång av ATP molekylen är det därför viktigt att bestämma hur deras strukturer förändras över tid till följd av tillgång på ATP. För P-typs ATPaser har ett stort antal strukturer av olika intermediära tillstånd bestämts främst genom röntgenkristallografi. Dock så kommer det finnas instabila tillstånd som aldrig kommer att kunna fångas av traditionella strukturbestämningsmetoder. Utöver detta så är det möjligt att proteinet inte kan genomgå sina naturliga strukturförändringar i en proteinkristall. För ett membranprotein är dessutom funktionen beroende av dess omgivande lipidmembran. För att bättre förstå proteinets funktion är det därför viktigt att försöka studera den aktuella processen under förhållanden så nära som möjligt till de fysiologiska förhållandena som råder i cellen. Denna avhandling syftade till att vidareutveckla en existerande tidsupplöst röntgenspridningsteknik (TR-XSS) för att karakterisera ATP-beroende proteindynamik i lösning. För att erhålla en tillräckligt stark signal i dessa experiment måste en stor del av proteinerna i provet utföra sin funktion samtidigt. Detta kan uppnås genom laseraktivering. Vi använde laseraktivering av en burförening av inaktiv ATP för att starta transportreaktionen för en zinktransportör från den patogena bakterien Shigella sonnei. Genom att följa signalen från ATP hydrolys med infraröd spektroskopi hittades lämpliga betingelser för TR-XSS synkrotronexperiment. Förutom att bana vägen för tidsupplösta röntgenförsök är kinetiken och strukturdynamiken av intresse eftersom denna zinktransportör är vanligt förekommande hos patogena bakterier men inte hos människor och därför utgör ett potentiellt målprotein för utveckling av nya antibiotika. Vid utvecklingen av TR-XSS-metoden användes laseraktivering av en ATP burförening för att studera en strukturellt väl-karakteriserad kalciumtransportör (SERCA) i dess naturliga membranmiljö istället för i proteinkristaller. Experimenten identifierade ett intermediärt tillstånd vid 1.5 millisekunder och ackumuleringen av ett annat

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hastighetsbegränsande intermediärt tillstånd vid 13 millisekunder. Med hjälp av molekyldynamikdatorsimuleringar (MD) bestämdes sedan strukturen av det hastighetsbegränsande tillståndet i en konformation som ännu inte hade observerats med traditionella strukturbestämningsmetoder. MD-simulering av strukturmodellerna erhållna från TR-XSS-metoden i membranmodeller som imiterade den naturliga lipidsammansättningen finjusterade placeringen av de bestämda tillstånden i SERCA-reaktionscykeln samt karakteriserade deras interaktion med de omgivande lipiderna. Den utvecklade TR-XSS-metoden användes sedan för att studera ATP-beroende proteindynamik för AK. Resultaten visade experimentellt den relativa ordningen på de strukturella förändringar som proteinet genomgår som respons på ATP tillgång. Detta visar på bredden hos den utvecklade röntgenmetoden. Dessutom finns flera olika typer av burföreningar tillgängliga, såsom metaboliter, joner, och signalsubstanser, vilket ytterligare öppnar upp för möjliga målproteiner.

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Abbreviations A list and short explanation of the different abbreviations and terms commonly used in this thesis.

ESRF European Synchrotron Research Facility (Synchrotron facility in Grenoble, France)

MD Molecular Dynamics (computer simulations of protein motions)

TR-XSS Time-Resolved X-ray Solution scattering (Solution scattering technique)

XFEL X-ray Free Electron Laser (X-ray source)

ATP Adenosine Tri-Phosphate

P-type ATPase ATP dependent enzyme with phosphorylated intermediate

SERCA Sarcoplasmic Reticulum Calcium transporter (Ca2+ transporting P-type ATPase)

ZnTA Zinc Transporting P-type ATPase

AK Adenylate Kinase (enzyme involved in interconversion of nucleotides)

A domain Actuator domain of P-type ATPase

N domain Nucleotide-binding domain of P-type ATPase

P domain Phosphorylation domain of P-type ATPase

M domain Trans-membrane domain of P-type ATPase

CORE domain Central domain of Adenylate Kinase

LID domain ATP binding domain of Adenylate Kinase

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NMP domain ADP binding domain of Adenylate Kinase

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List of publications

Paper 1. H. Ravishankar, A. Barth, M. Andersson. (2017) Probing the activity of a recombinant Zn2+-transporting P-type ATPase. Biopolymers, Volume 109, Issue 2, e23087. Paper 2. H. Ravishankar, M.N. Pedersen, M. Eklund, A. Sitsel, C. Li, A. Duelli, M. Levantino, M. Wulff, A. Barth, C. Olesen, P. Nissen, M. Andersson – Tracking Ca2+ ATPase intermediates in real-time by X-ray solution scattering - Science Advances, Volume 6, Issue 12, eaaz0981. Paper 3. H. Ravishankar, D.R. Mahato, M. Andersson. Stability and lipid-interaction in transient Ca2+ P-type ATPase (SERCA1a) intermediates (Manuscript). Paper 4. H. Ravishankar., J. Goodman, A. Duelli, M.N Pedersen, M.Levantino, M. Wulff, M. Wolf-Watz, M. Andersson. Tracking ATP-binding conformational change in adenylate kinase using time-resolved X-ray solution scattering (Manuscript).

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Contribution report

Paper 1. I performed expression and purification of the protein samples, executed the FTIR experiments, performed data analysis, and contributed to the writing of the paper. Paper 2. I contributed to the design and execution of the X-ray scattering experiments, analysed the data, performed simulations and structural analysis, and took a major part of writing the paper. Paper 3. I designed the research together with my supervisor. I performed the simulations and data analysis. I took a major part in writing the paper. Paper 4. I was involved in the design of the experiment along with my supervisor and collaborators. I contributed to the design and execution of the X-ray scattering experiments, analysed the data, performed simulations and structural analysis and took a major part of writing the paper.

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1. Introduction 1.1 General protein structures Proteins are complex macromolecules made up from polymers of amino acids. The amino acid building blocks are composed of an amide group (-NH2), a carboxyl group (-COOH), along with a side chain that is distinctive for each amino acid. There are 20 amino acids with a variety of side chains that can be hydrophobic, hydrophilic, aromatic, polar, positively or negatively charged, which therefore confer different properties to the protein polypeptide sequence. The amino acids are encoded in sequences of DNA, which are then transcribed to strands of RNA and then translated to polypeptide sequences that fold into proteins. Amino acids form polypeptide chains via peptide bonds (-CO-NH-) and the single chain of amino acids in a specific sequence constitutes the primary structure of a protein molecule2. Backbone atomic interactions of amino acids in the polypeptide chain stabilize the protein molecule by forming stable patterns such as alpha helices and beta sheets, which are the secondary structures of the protein. An alpha helix is a conformation where backbone –NH groups form hydrogen bonds to C=O groups located four residues away in the sequence. In contrast, in a beta sheet, the –NH group is hydrogen bonded with the C=O group from an adjacent strand3. The arrangement of secondary structural elements in three dimensions in a monomeric protein is referred to as tertiary structure, whereas the quaternary structure describes multimeric proteins (Fig.1).

1.2 Protein structural dynamics Proteins undergo large-scale conformational changes in the arrangement of protein secondary structures in order to carry out their designated functions. These structural rearrangements are well coordinated in time in order to carry out the protein function. Therefore, monitoring protein structural dynamics and their relative timing is essential to understand protein functionality.

Figure 1. Hierarchy of structural organization in proteins. (A) Primary, (B) secondary, (C) tertiary and (D) quaternary structures.

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There are three widely used methods for studying the three-dimensional structure of proteins; X-ray crystallography, nucleo-magnetic resonance (NMR) and cryo-electron microscopy (Cryo-EM). Cryo-EM is a powerful method for studying protein structures that in principle can be used to probe structural intermediates, but cannot capture the dynamics in real time. X-ray crystallography has provided several tens of thousands of three-dimensional protein structures, deposited into the Protein Data Bank (PDB) database4. However, a major shortcoming of X-ray crystallography is that it is dependent on the protein being able to form good quality, repeating crystal lattices. This is problematic when characterizing proteins with intrinsically disordered regions or sections that are flexible, as these might not be amenable to crystallization. In addition, most crystal structures of proteins have been limited to the ground state. However, despite these difficulties, X-ray based methods for studying the dynamics of proteins in crystal lattices have been developed. In kinetic crystallography, the crystallized protein is triggered externally and the resulting structural intermediate is trapped within the crystal lattice. A common method for intermediate trapping (given that the transition rate is low enough) is by flash-freezing the crystal following triggering the reaction by soaking the crystal in a chemical inducer or by photo-activation using a light source 5-8. Another method is to use Laue diffraction subsequent to laser activation of a single crystal of a light-sensitive protein9, 10. In addition, X-ray free electron lasers (XFELs) have enabled new venues for visualizing protein dynamics. Time-resolved serial femtosecond crystallography is a pump-and-probe methodology that track the reaction in a stream of microcrystals11. Such studies have produced detailed structural information on e.g. the structural rearrangements in bacteriorhodopsin across a broad temporal regime from pico-to-milliseconds12. For all methods based on protein crystals, it is not clear to what extent the protein molecules are restricted by the crystal lattice and therefore the observed structural changes might not exactly resemble those under native conditions13. Also, conformational dynamics might be hindered by non-physiological conditions required for crystallization14. Therefore, there is a need to develop methods that can directly measure conformational changes occurring in proteins in solution under conditions which are close to the physiological. X-ray solution scattering (XSS) is a technique that has been developed to study proteins in solution. Small-angle X-ray scattering (SAXS) and wide-angle X-ray scattering (WAXS) are two variants of the XSS method. These X-ray scattering methods register the scattering from protein atoms in solution to generate a one-dimensional scattering profile from which low-resolution structural information can be gathered. The advantages are that the protein is free in solution and not constrained by a crystal lattice. In addition, the protein can be studied under conditions that are close to its natural environment. The disadvantage is that the high-resolution structural information is lost. While SAXS enables collection of information at small scattering angles giving information about the size and shape of the protein15, 16, WAXS

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emphasizes the wider scattering angles and hence gives structural information on the secondary structural elements of the protein17. Advances in synchrotron radiation sources and sample delivery systems have enabled collection of time-resolved structural data from protein molecules in solution. The advantage of Time-Resolved XSS (TR-XSS) is that it registers only the signal arising from the changes in molecular structure and hence reduces the complexity of the XSS scattering signal. The TR-XSS methodology was developed by studying the formation of transient intermediates of small photo-activated compounds18-20 These studies were later extended to characterize transient intermediates of protein molecules. The first studies in this direction were aimed at conformational changes of haemoglobin that were probed in the nanosecond to millisecond time range after dissociation of carbon monoxide triggered by a laser flash21. The observed changes were comparable to the crystal structures of haemoglobin intermediates. The TR-XSS technique was predicted to be amendable to membrane protein dynamics22. Indeed, the kinetics and structural rearrangements of different intermediates of rhodopsin membrane proteins were later measured13, 23, 24. The established results provided new knowledge of the structural changes that occur in these proteins during the reaction cycle. Another example is the TR-XSS characterization of the structural dynamics of photosensitive phytochrome proteins25. 1.3 Adenylate kinase Adenylate kinase (AK) is an enzyme that undergoes large-scale conformational changes and therefore constitutes a possible target for TR-XSS characterization. The AK enzyme catalyzes reversible phosphoryl transfer between the nucleotides adenoside mono-, di- and tri-phosphates (AMP, ADP and ATP, respectively), in the presence of magnesium (Eq.1).

AMP + ATP'()*+⎯⎯- 2ADP (1)

As such, AK has a primary role in maintaining energy homeostasis in cells. The importance of the protein is reflected in its ubiquitous presence in a wide variety of organisms and cells26. The protein comprises of three domains which are defined as the ATP binding (LID) domain, AMP binding (NMP) domain, and the central CORE domain27. The AK enzyme from E. coli has been crystallized in two conformations, one apo state where both the LID and the NMP domains are open (PDB ID: 4AKE)27 and one inhibitor-bound state with both domains in a closed configuration (PDB ID: 1AKE)28 (Fig.2). From the crystal structures, it is clear that AK is capable of large conformational changes. Binding of ATP and AMP to the respective domains, leading to closure of the protein structure, is directly linked with enzyme catalysis29. Therefore, laser-induced release of ATP from inactive caged ATP could possibly be used to trigger the AK reaction in TR-XSS experiments.

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How the AK enzyme respond to the presence of its substrates have been subjected to intense research efforts. In nuclear magnetic resonance (NMR) and single-molecule Förster resonance energy transfer studies (sm-FRET), the ligand-binding domains were measured to close in millisecond time-scales30-33 but also fast µs closures have been observed34. However, neither the NMR or the sm-FRET experiments could resolve the relative ordering of domain closure that occurred during the reaction cycle. Moreover, the attachment of molecular probes in the sm-FRET experiments also carry the risk of affecting the normal protein dynamics. Computational methods can track atomistic-level changes in protein structure and resolve correlative motion between different AK domains. Therefore, several simulation studies – all starting from the open state crystal structure – have aimed to determine the relative order of domain closing in AK35, 36. However, the results from the computational studies so far have not been conclusive with some studies indicating that the LID domain closes before the NMP domain upon substrate binding36-40 while others indicating the opposite41, 42. These discrepancies might be explained by atomistic molecular dynamics (MD) simulations not yet being able to match the biological time-scales and inaccuracies in the coarse-grained models. Therefore, the relative order of the domain closure in AK upon presentation of the substrates remains elusive.

Figure 2. The adenylate kinase structure. (A) The substrate-free (apo) open crystal structure (PDB ID: 4AKE) and (B) the inhibitor-bound closed crystal structure (PDB ID: 1AKE). The CORE, LID and NMP domains are marked in the figure.

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1.4 Biological membrane environment Biological membranes compartmentalize living cells and cell organelles and separate them from their environment. Proteins inserted into biological membranes carry out e.g. transfer of energy and nutrients. In addition, these proteins also play an important role in cell signaling. The membrane consists of a bilayer of lipid molecules, which are composed of a polar head group and a hydrophobic tail (Fig.3A). The lipid molecules are organized into a bilayer with the polar head groups facing towards the aqueous surrounding and their hydrophobic tails forming a hydrophobic core (Fig.3B). This arrangement shields the hydrophobic tails from the surrounding aqueous environment and thereby makes the cell membrane impermeable to ions43. The structure and function of proteins associated with membranes are influenced by their surrounding lipid environment44. Such proteins are regulated by both the general properties of the lipid membrane, such as thickness and fluidity, and also by specific protein-lipid interactions where lipid molecules directly interact with specific lipid binding sites in the protein45. Hence, the membrane lipids can act as allosteric regulators of membrane protein function.

1.5 Membrane proteins Membrane proteins interact with biological membranes and are broadly classified as peripheral or integral membrane proteins. Peripheral membrane proteins are loosely associated at the surface of membranes while the integral membrane proteins are embedded in the membrane lipid bilayer. Integral membrane proteins have two types of membrane-spanning structures; alpha-helical bundles have transmembrane helices spanning the membrane bilayer while beta barrels consist of anti-parallel beta sheets

Figure 3. Composition of the lipid bilayer. (A) Structure of a single phosphatidylcholine lipid molecule and (B) arrangement in a lipid bilayer with polar head groups facing water and hydrophobic tails arranged inwards.

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that are cylindrical in shape. Integral membrane proteins carry out a variety of roles in the cell such as transport of ions and other compounds in and out of the cell as well as signaling between cells46. Membrane proteins are divided into three major classes, receptors, channels and transporters (Fig.4)47. Receptors are specialized proteins to which external molecules such as hormones and neurotransmitters can attach and trigger a wide range of intra-cellular responses. Channels, when activated are simultaneously open to both the extra- and intra-cellular environments, while transporters are selectively open to only one side at a time. Also, transporters have a limited number of binding sites. The transporter binding sites recognize and selectively bind substrates and allow only a limited number of molecules to pass, unlike channels that allow thousands or millions of molecules to pass through when open.

1.6 Protein transport of ions across membranes Active transport is the facilitated movement of a substance, such as an ion, across a membrane barrier, against its concentration gradient. This is carried out in living cells by membrane protein transporters. These proteins are either primary active transporters that use free energy released from enzymatic hydrolysis of ATP or secondary active transporters that instead exploit existing electrochemical gradients to drive the uphill transport48. In both transport modes, the transported ion binds to the protein from one side of the membrane and causes a conformational change in the protein which then exposes the internal ion-binding site to the opposite side of the membrane where it is released (Fig.5)49. Hence, the transport protein alternates between extra- and intra-cellular open states in which the substrate-binding site is

Figure 4. Classes of membrane proteins – receptor, transporter and ion channel. The ions undergoing transport across the membrane are shown as circles, and the receptor ligand is shown as a triangle.

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accessible to only one side at a time, according to the so called alternating access model50.

1.7 P-type ATPases P-type ATPase transporters are membrane transporter proteins where the transport process is powered by ATP hydrolysis. The name “P-type” comes from the formation of phosphorylated enzyme intermediate through the transfer of the gamma-phosphate of ATP to a conserved aspartate residue in the protein. The breakdown of ATP gives rise to ADP and Pi (inorganic phosphate) and causes conformational changes in the protein structure that lead to transport of ions (or lipids) across the membrane51. These transport proteins carry out vital functions in the cell. Examples are the sodium-potassium exchanger (Na+/K+) ATPase, which helps maintain the cellular membrane potential52, the hydrogen-potassium (H+/K+) ATPase that acidifies the vertebrate stomach53 and the sarcoplasmic reticulum Ca2+ transporter (SERCA), which triggers muscle relaxation54.

Figure 5. Schematic of the alternating access mechanism of a membrane protein transporter in action. The proteins are situated in a schematic lipid bilayer and the circles are the translocated ions.

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Out of the several subtypes of P-type ATPases (Fig.6), the Type-II and Type-III ATPases are the best studied. The Type-IIA ATPases contain the SERCA transporter that transport Ca2+ across the SR membrane54, while Type-IIB are plasma membrane Ca2+- pumps1. The Type-IIC ATPases contain the renal Na+/K+-ATPases and gastric H+/K+-ATPases55, 56 Type-IIIA H+-ATPases are found exclusively in plasma membranes of plants and fungi57, while the Type-IIIB proteins are a small family of bacterial Mg2+ pumps58. In contrast, proteins in the Type-I subfamily are relatively less

well characterized. Type IB-ATPases regulate cellular levels of Cu+, Zn+, and Pb+ to support critical enzymes with metal ions while avoiding high concentrations that induce toxic effects59, 60. These transporters are mostly bacterial proteins although homologues have been found in yeast, plants and animals61.

Figure 6. Phylogenetic tree showing the diversity of P-type ATPases. The subtypes are grouped according to their substrate specificities. Adopted from Ref 1.

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The Post-Albers scheme for membrane transport describes the general mechanism of action for the P-Type ATPase proteins (Fig.7)62, 63. In this scheme, the ion binds from inside the cell to the protein in a high-affinity E1 or enzymatic ‘ground’ state, which upon phosphorylation of an aspartic acid residue undergoes conformational changes that leads to an E1P state. The E1-to-E1P conformational changes induce piston-like movement of helices in the membrane domains that forms an E2P state with low affinity for the bound ion, hence causing release of the ion across the membrane.

Dephosphorylation and binding of counter ions (for some subtypes) cause conformational changes that results in reformation of a high-affinity E1 state facing into the cytosol (Fig.7)1. 1.8 Ca2+-transporting P-type ATPases (SERCA) In muscle cells, free Ca2+ ions are stored in mM concentrations in a specialized cellular organelle called the sarcoplasmic reticulum (SR)64. The main function of the SR Ca2+

ATPase membrane protein (SERCA) is to pump Ca2+ ions that are released in the cytosol during muscle contraction back against its gradient into the SR lumen so that the muscle can relax. Since SERCA is highly abundant in the SR membrane, Ca2+

uptake takes only milliseconds, allowing for fast relaxation. The SERCA paralog SERCA1a is expressed in fast-twitch muscle cells in adult animals65, 66. SERCA1a is composed of a single polypeptide chain that comprises 994 amino acids and has a molecular mass of 110 kDa. The crystal structure of SERCA1a shows a 10-helix membrane (M) domain and three globular domains in the cytoplasm, namely the N domain (nucleotide binding) which binds ATP, the P domain (phosphorylation) where the phosphorylation of Asp 351 takes place and the A domain (actuator) domain that alters the Ca2+ affinity of the protein through structural changes (Fig.8)67. In the reaction cycle, SERCA1a transitions through the high-affinity E1 and low-affinity E2 states (Fig.9). In the E1 state, the ion-binding sites are accessible from the cytoplasmic side resulting in binding of two Ca2+ ions before the enzyme becomes phosphorylated. ATP binding and phosphorylation is followed by a series of conformational changes

Figure 7. Post-Albers cycle: the general ion-translocation cycle for P-type ATPases.

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leading to the formation of the low Ca2+ affinity state that is open to the lumenal side of the membrane. In this E2P state, Ca2+ ions are released to the lumen and 2-3 H+ counter ions can now bind. The cycle is completed when the enzyme undergoes dephosphorylation and returns to the high-affinity E1 state.

Crystal structures have trapped the SERCA in several intermediate states that structurally describe the protein as it performs the membrane transport68-74. In Ca2E1 state crystal structures, which is the state formed after binding of two Ca2+ ions, the three globular cytoplasmic domains adopt an ‘open’ arrangement75, 76. The internal ion-binding Ca2+ sites bind two ions near the middle of the membrane bilayer75. To mimic the ATP- and Ca2+-bound state Ca2E1ATP, ATP analogues such as 5’-β,γ- methylene-triphosphate (AMPPCP) and adenosine 5’-β,γ-imido-triphosphate (AMPPNP) were used to trap the protein in that specific state of enzymatic action77, 78. This caused large-scale conformational changes in the global protein structure bringing the N and P domains closer together. These conformational changes pull transmembrane helices M1 and M2 together and close the cytosolic entrance for the Ca2+ ion, thereby preventing its backflow78, 79. In the enzymatic transition from the E1P to E2P states, the transmembrane helices undergo significant rearrangement, revealing an open, funnel-shaped Ca2+ exit pathway, with the Ca2+ binding residues now facing the SR lumen. Exposing the metal ion-binding residues to the lumen reduces their ion-binding affinity leading to dissociation of the Ca2+ ions80. Since SERCA is unstable in the absence of Ca2+, all E2 state crystal structures in the absence of Ca2+ have been co-crystallized with stabilizing inhibitors80. Hence, structures of intermediate states directly involved in the E1-E2 transition, such as the Ca2E1P state where ADP had been released and the Ca2E1P state before calcium release, are still missing (Fig.9). Such states, that do not seem to be amendable with traditional structure determination methods, might be possible TR-XSS targets.

Figure 8. SERCA structure. The N, P, A, and M domains are marked in the figure.

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Subsequently in the SERCA reaction cycle, upon formation of E2 states, the three cytoplasmic domains gather together to form a single headpiece, with a conformational arrangement different from that of phosphorylated E1 states. The transition from E1 to E2 induces a change moving the M1-M4 helices away from M5-M6, that the distorts the geometry of the Ca2+ binding residues, exposing them to the luminal environment through the funnel shaped exit pathway81. From the dephosphorylated E2 state, the enzyme shifts to the E1 conformation, Ca2+ ions can bind again, and the cycle can be restarted1.

1.9 Zn2+-transporting transmembrane protein (ZntA) The zinc transporter A (ZntA) is a Type-IB ATPase that transports primarily Zn2+, but also Pb2+ and Cd2+ out of the cell82. It plays an important role in mediating zinc ion toxicity by actively transporting heavy metal ions across the cytoplasmic membrane. It is predominantly found in microbes and plants83, but is absent in animals. Its absence in animals (especially humans) makes it an attractive target from a pharmacological

Figure 9. SERCA crystal structures of different intermediate states in the reaction cycle shown along with the corresponding PDB IDs.

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perspective, with respect to finding new antibiotics to fight multidrug-resistant pathogens. Similar to other P-type ATPases, ZntA comprises of the structurally conserved intracellular domains (Fig.10); A (actuator), P (phosphorylation), N (nucleotide-binding) as well as the M (membrane) domain through which ion efflux takes place84. In addition, the ZntA contains a regulatory N-terminal metal-binding domain with multiple copies of the conserved metal-binding motif, GXXCXXC85, which were not resolved in the crystal structures. The ZntA transporter have only been trapped in the E2-P and E2.Pi states84. An intracellular electronegative funnel was observed that can potentially bind free-floating Zn2+ with high affinity. The metal ion-binding membrane domain contains a lysine residue that might act as a built-in counter ion in the transport mechanism. The extracellular Zn2+-release pathway showed structural similarity to the Type-II ATPases SERCA and the Na+/K+ ATPase84. In contrast, another Type-I ATPase (a Cu+-transporter) was shown to exhibit quite different ion-release dynamics 86. Such subtle differences could potentially be caused by the limitations of a crystal lattice87. Therefore, characterizing the conformational changes in a lipid environment could possibly discriminate Type-I and Type-II reaction cycle dynamics and also provide structural information on elusive Type-I E1-states. Structural information on E1 states will be critical to understanding ion uptake. Such E1 states and ion uptake was recently modeled in Cu+ ATPases88, but direct experimental information is still missing. Adding to the structural information on the ZntA transporter could potentially be used to find inhibitors and hence contribute to development of new antibiotics.

Figure 10. Crystal structure of ZnTA in the E2P state (PDB ID: 4UMV). The A, P, N and M domains are marked in the figure.84

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2. Methods 2.1 Infrared (IR) spectroscopy Spectroscopy is the study of the wavelength-dependent interaction of electromagnetic radiation with atoms and molecules. The energy of photons is dependent on the wavelength of the electromagnetic radiation, which is described by the Bohr equation E = h ∗ υ, where h is the Planck’s constant and υ is the frequency of the radiation.

Photons in the UV and visible wavelength range are capable of inducing transitions in the electrons of the atoms they interact with. However, photons in the infrared (IR) range can only induce changes in molecular vibrations or rotations. The wavelength range of IR radiation is between 0.75 and 250 µm and is divided into the near-IR region (0.75 to 2.5 µm), the-mid IR region (2.5 to 25 µm) and the far-IR (25 to 250 µm). In a molecule consisting of several atoms, different types of vibrations are present, such as stretching vibrations over chemical bonds and bending vibrations over bond angles. Because vibrations from neighbouring groups are coupled if the frequencies are similar, IR spectroscopy can probe molecular structure. 2.2 Fourier Transform Infrared (FTIR) spectroscopy In traditional dispersive IR measurements, a diffraction grating is used to separate a single wavelength of light and direct it onto the sample and detector. Because the wavelengths are measured one at the time covering a wide range, each measurement is time-consuming. A major breakthrough was achieved in the introduction of FTIR spectrometers, which measure the entire wavelength range simultaneously leading to

Figure 11. The electromagnetic spectrum showing the range of wavelengths and frequencies of electromagnetic radiation.

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faster data collection. Other advantages are enhanced signal-to-noise ratios due to more energy reaching the detector and frequency precision89. A typical FTIR spectrophotometer consists of an IR light source, an interferometer and a detector (Fig.12)90. The interferometer in turn consists of a beam splitter and two mirrors, one of which is fixed at a specific distance from the beam splitter and another which is moving. The beam from the IR source is split into two by the beam splitter and deflected onto the mirrors. The reflected beams are recombined at the beam splitter and passed through the sample and finally to the detector. Because the reflected beams have travelled different distances, recombining them at the beam splitter gives rise to constructive and destructive interference. The interferogram is

Fourier transformed into an IR spectrum. The most common detectors for infrared spectroscopy are deuterated triglycine sulfate (DTGS) and mercury cadmium telluride (MCT) detectors91. DTGS detectors are stable at room temperature (with the drawback of slow response time), unlike MCT detectors that require cooling with liquid nitrogen. The MCT detectors offer better sensitivity and have ten-fold faster response time compared to DTGS detectors, thereby enabling fast recording of the spectra required for time-resolved studies. 2.3 FTIR spectroscopy of proteins FTIR spectroscopy has been extensively used to study biological molecules, including a diverse array of proteins and polypeptides90, 92, 93. FTIR measurements provide information about the protein structure, environment of the protein backbone and side chains, and also its structural dynamics94. The vibrational spectrum of biomolecules is usually plotted against the wavenumber (υ = 1/λ), which is the inverse of the wavelength (λ) with units of cm-1. When a peptide bond absorbs IR radiation, it gives rise to nine characteristic wavenumber bands. These are named amide A, B and amide I through VII90. The

Figure 12. General scheme of an FTIR spectrometer.

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amide I and II bands are closely related to absorption of the protein backbone structure. The amide I band arises primarily due to the changes in absorption caused by the C=O bond stretching vibration with minor contributions from the C-N bond’s stretching vibration and gives rise to distinct bands with high amplitudes and are therefore frequently used to study protein structural changes95. The amide I band covers the 1600-1700 cm-1 region and the exact position of peaks within this region is determined by the geometry of the protein backbone and changes in the hydrogen bond pattern. The amide II band, on the other hand, is present in the 1580-1510 cm-1 region and arises due to the coupling of N-H bending and C-N stretching vibrations. Because these band regions are not directly linked to the protein structural dynamics the amide II region is less frequently used for structural analysis of protein molecules96. Amide I bands are connected to protein secondary structures93, 97. The spectral signature of alpha helices is found at 1654 cm-1, while the amplitude of the signal and the exact wavenumber are dependent on the number of residues in the alpha helix and the extent of the structural changes. The beta sheet structure bands appear at 1630 cm-

1 with antiparallel beta sheet movements having an additional signature in the 1684 cm-1 region. As with the case of alpha helices, the exact wavenumbers vary with strand lengths, number of strands and the strand orientation. A problem with measuring signals in the amide I region is overlap with the O-H bending vibration in water molecules. Therefore, IR measurements require high protein concentrations to overcome the water background. Another approach to increase the protein signal is to equilibrate the sample in D2O, which shifts the water bending vibration away from the amide I region98, 99. An important aspect of FTIR spectroscopy is that the IR spectral signature of the biological material can be obtained in a wide range of sample conditions100. Hence, protein molecules can be studied in aqueous solutions, organic solvents, crystals and even in detergent micelles and lipid membranes101. 2.4 Applications of FTIR spectroscopy 2.4.1 Reaction-induced difference FTIR spectroscopy To avoid overlapping absorbance in the mid-range IR region, CaF2 sample cuvettes with fixed path-lengths are commonly used. For protein samples in solution, path lengths of 5 µm are typically used. The short path length limits the absorption of water and therefore enhances the signal resulting from the protein dynamics. The short path length cuvettes also require low sample volume, typically between 1-2 µL102, 103. Proteins give rise to complex absorption signals when perturbed by IR radiation. Reaction-induced difference spectroscopy can be used to reduce this complexity. In this IR method, the absorption spectrum of a protein in a specific state is recorded as the “blank reference”. The reaction is then initiated by perturbing the system, e.g. by increasing the substrate concentration followed by absorbance spectra measurements

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over time. In this way, the difference between the absorption spectrum of the ground and perturbed states will depend only on the components of the protein sample that have participated in the structural change and the rest of signal from the inactive components will cancel out. Hence, reaction-induced difference spectroscopy can reveal details of the reaction mechanism despite a large background absorption. In the difference spectra, negative bands are characteristic of a component decreasing over time while positive bands indicate an increase.

ATP-dependent proteins can be studied by activation of N-phenyl-ethyl ester (NPE) caged ATP (Fig.13)104, 105. Caged compounds can be included with the protein in the sample cuvette and then be triggered externally by a laser pulse, thereby inducing the protein reaction. The caged compounds are usually 2-nitrobenzyl derivatives97, 106-108. Upon illumination in the near-UV spectral range (300-350 nm), the compound of interest is released, thereby increasing the substrate concentration available to the protein under study. The binding of a substrate to the protein and subsequent protein conformational changes can then be monitored in the resulting IR spectra over time. The obtained signals can be difficult to interpret since they originate from a myriad of groups. Assignment of peaks in the IR spectra can be accomplished by identifying the parts of the protein they originate from. This is done by methods such as isotopic labelling and site-directed mutagenesis of the protein90. Isotopic labelling increases the mass of the active groups and therefore enhances the signal or causes shifts in the wavenumber of the bands. Thus, the conformational changes happening in the protein molecule create a specific spectral signature. Similarly, site-directed mutagenesis gives rise to wavenumber shifts. 2.4.3 Attenuated total reflectance (ATR) FTIR spectroscopy An alternative to transmission FTIR spectroscopy is attenuated total reflectance (ATR) FTIR spectroscopy. In this method, the sample is placed on top of a crystal that has a higher refraction index than the solution. The crystal material can be diamond, ZnSe or Germanium. As the IR beam passes through the crystal it is reflected at the interface between the sample and the crystal. Upon reflection at the interface, an evanescent wave is formed and penetrates into the sample, carrying information about the various absorbing components in the sample. The IR beam is thus reflected several times

Figure 13. N-phenyl-ethyl ester (NPE) caged Adenosine Tri-Phosphate (caged ATP) molecule. Caged ATP undergoes photolytic cleavage when flashed with UV light at 300 nm wavelength, which releases ATP which can then be hydrolysed by ATP-dependent proteins.

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within the crystal before reaching the detector (Fig.14). In ATR FTIR spectroscopy, sample conditions can be easily manipulated since the sample surface on top of the crystal is exposed. For example, ligands can be directly added or the pH of the sample changed relatively easily. When studying proteins, a high concentration can be achieved by drying the sample on the surface of the crystal, thereby maximizing the amount of protein at the interface of the crystal. This results in an enhanced signal-to-noise ratio, as there is no competing interference due to water absorption109.

2.5 X-ray scattering 2.5.1 Scattering by atoms X-rays are electromagnetic radiation with wavelengths of 0.1 to 1 Å. Since these wavelengths approximately correspond to the lengths of a chemical bond, X-rays are ideal to study molecular structure. When an X-ray photon strikes the electron cloud of an atom, radiation with the same wavelength as the X-ray is emitted. This phenomenon is called X-ray scattering. The combined scattering from all the electrons of the atom produces a spherical wave. The larger the electron cloud, the higher the amplitude of the scattered X-rays. The atomic scattering amplitude of an atom as a function of the scattering angle is described by the form factor (f), which decreases as a function of the scattering angles. Consequently, lighter elements have a lower form factor than heavier elements.

Figure 14. Scheme of a typical ATR FTIR spectrometer setup.

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Consider a system consisting of two points, A and B separated by the distance AB interacting with an incident wave (S0) (Fig.15). The incident wave has a wave-front of BC when it reaches points A and B and scatters at an angle of 2q The resulting wave-front has a wave-front of BD. The phase difference d in radians between S0 and S1 is expressed as a function of the path difference D travelled by the two waves such that,

∆= 𝐀𝐃 − 𝐀𝐂 = 𝐫 ∗ (𝐒𝟏 − 𝐒𝟎) (2)

δ = 2 D∆

E= 2π𝐫 ∗ 𝐒𝟏G𝐒𝟎

E(3)

where r defines the vector AB, S0 and S1 being the unit vectors and l is the wavelength of the incident X-ray beam. The scattering vector q can therefore be calculated as the difference between the wave vectors k1 and k0 according to

𝐪 = 𝐤𝟏 − 𝐤𝟎 = JKDEL 𝐒𝟏 − 𝐒𝟎 (4)

and the corresponding magnitude of the scattering vector can be derived as, q= MNOPq

E (5)

and the phase difference can now be expressed as,

δ = 𝐫 ∗ (𝐤𝟏 − 𝐤𝟎) = 𝐫 ∗ 𝐪 (6)

Figure 15. (A) X-ray scattering by two points in space. (B) The scattering vector, q is the difference between the normalized wave vectors k1 and k2.

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If the two points represent two atoms with the form factor f, the amplitude of the scattered wave (F) at point B with respect to A can be written as a function of the scattering vector,

F(𝐪) = feOT = feO𝐪.V (7) The reciprocal relationship described by q (reciprocal space) and r (real space) provides information about the resolution that is achieved in a scattering experiment. Therefore, to resolve shorter scattering distances, we need to go to higher q values. This can be accomplished by increasing the observation angle or reducing the wavelength. The resolution attained in a scattering experiment is therefore 2p/qmax, where qmax is the maximum q-value for which the scattering is observed. 2.5.2 Scattering by protein solutions In X-ray scattering experiments, the protein is suspended in an aqueous buffer solution. Apart from the waves scattered by the protein molecule there is also scattering from the bulk solvent and the so-called hydration layer, which corresponds to water molecules in close proximity to the protein that has a higher density than bulk water. This gives the sum of the scattering contributions as, F(𝐪) = ΣXYfX − ρNυX[eOV.𝐪(8) , where uj is the volume of the atom j and the termfX − ρNυX represents the contrast amplitude between the atom j in the protein and the bulk solvent. In a protein solution with N identical protein molecules with no inter-particle interference, the intensity of the scattered waves S(q) is found by the summation of the intensities over all the molecules, hence phase information is lost. S(𝐪) = ΣP][FP(𝐪)]K (9) Also, since molecules in solution exhibit different orientations, the scattering intensity can be obtained from the Debye formula, which accounts for the rotational averages:

S(𝐪) = N[absF(𝐪)]K = N dedeYfeGghij[(fkGghil)NOP𝐪Vek𝐪Vek

(10)

, where rjk is the distance between the atoms j and k. Therefore, in order to calculate the expected scattering intensity from a protein solution, we would need to know N – the number of molecules in the solution, the form factor f and the atomic volume u of all protein atoms and also the density of the solvent rs.

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2.6 Time-resolved X-ray solution scattering (TR-XSS) 2.6.1 Synchrotron radiation Synchrotron radiation is the radiation emitted when an accelerated charge moving at relativistic speed follows a curved trajectory. Such radiation can be generated in cyclic particle accelerators called synchrotrons where electrons are accelerated at relativistic speeds. During acceleration, the applied magnetic field is increased enabling synchronization to the increasing kinetic energy of the particle. Auxiliary devices such as wigglers, undulators and bending magnets which apply strong magnetic fields perpendicular to the accelerated electron beam cause the relativistic electrons to emit radiation, which is termed as synchrotron radiation.110 Synchrotrons produce high intensity, pulsed beams that can be used to measure transient molecular events at time resolution from 100 picoseconds to several hundreds of milliseconds111. 2.6.2 Pump-and-probe experiments Biomolecular phenomena span a wide range of time scales from the ultrafast femto-pico-nanosecond dynamics to the slower micro-millisecond conformational changes in proteins. While X-ray free-electron lasers (XFELs) can probe the ultrafast dynamics regime, time-resolved X-ray solution scattering (TR-XSS) is particularly suited for studies in the slower temporal regime. Such dynamics are crucial to understand protein function. The TR-XSS method can be performed using rapid read-out detectors23. In these experiments, the sample is exposed to a continuous train of X-ray pulses before and after laser activation leading to two sets of detector images. The difference scattering data is obtained by subtracting images before and after laser excitation. The time resolution of such experiments is determined by the detector frequency. For example, the Pilatus detector has a readout time of 5 ms, while Eiger detectors have three orders of magnitude faster readout112. To circumvent the limitations of detectors, an alternative time-resolved approach was developed. This pump-and-probe method monitors a molecular process by first triggering the system with an activating laser pulse and then probing with short X-ray pulses isolated from the synchrotron pulse train using a rotating, mechanical chopper113, 114. Time delays spread across several orders of magnitude can be recorded and the TR-XSS method applies to a large number of chemical reactions. For this thesis, the time-resolved XSS experiments reported in Papers II and IV were carried out at the dedicated time-resolved ID09B beamline at European Synchrotron Radiation Facility (ESRF), France. This experimental station produces intense X-rays using a narrow-bandwidth undulator optimal for solution scattering (Fig.16A). A chopper system consisting of a water-cooled heat-load chopper, a high-speed chopper

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and a millisecond shutter has been installed at ID09B to provide short X-ray pulses and works in synchronization with a nanosecond pulse laser (Fig.16B)113, 114.

In the experiments, a mixture of the protein solutions and photoactive NPE-caged ATP was pumped through a capillary. The laser focal spot was focused to the X-ray spot on the capillary to trigger and probe the reaction at specific time delays. Between each pump-and-probe experiment the sample in the capillary was continuously replenished by a peristaltic pump. This was necessary since the reaction was triggered by the release of caged ATP and was hence irreversible. To prevent X-ray scattering from air, a helium-filled cone was placed between the sample capillary and the detector. The 2-D images from each time delay were recorded by the detector. 2.6.3 Difference X-ray scattering analysis The scattering data was recorded onto a 2-D detector and transformed into a 1-D curve by radial integration. Since X-rays are scattered by all atoms in the solution sample, the resulting 1-D scattering intensity profile is the sum of the scattering from the protein, but also the solvent and protein-solvent cross terms. Because protein concentration is low compared to the solvent, the scattering profile is dominated by solvent contributions. Therefore, to increase the sensitivity of the scattering profile to the protein structure, difference scattering spectra were calculated by subtracting the scattering curve (recorded at a particular time point) from the negative reference time delay (scattering recorded before the laser excitation). The raw scattering curves were first aligned in an angular region q0 where little scattering changes are expected to occur. SPmVn(𝐪, t) = q(𝐪,r)

dstq(𝐪,r) (11)

Figure 16. The polychromatic beam consists of the first harmonic of the undulator spectrum (A) and the pump-probe experimental set up (B) showing the high-speed rotating mechanical chopper, sample capillary, laser and detector.

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The difference scattering was then calculated by subtracting the scattering curve from a negative reference time delay from those of the positive time delays, ΔS(𝐪, Δt) = SPmVn(𝐪, Δt) − SPmVn(𝐪, Δt < 0) (12)

To compensate for drift, it is advantageous to record two blank references flanking each time point and then calculate the difference spectra by subtracting an average of the two blank measurements. Before any structural analysis of the scattering curves can be performed, the thermal response from the solvent (due to laser and X-ray induced heating) needs to be removed. The scattering profile of a dye solution was recorded using a similar protocol as for the sample and then subtracted after normalizing it in the region where the water scattering dominates (q > 1.5 Å-1 ) (Fig.17).

2.6.4 Spectral decomposition Following the collection of TR-XSS data, the first step was to reduce the complexity to enable kinetic and structural refinement. This can be achieved by decomposing the TR-XSS difference scattering data into a set of time-independent basis spectra, which are capable of reproducing the experimental data through linear combination of their respective intensities, at the time points of the experiment. In this thesis, the kinetic modelling relied on integrated rate equations as well as singular value decomposition (SVD) analysis of the time-resolved data. The kinetic models assumed irreversible steps and the rate constants calculated correspond to the rise-times of formation of the transient states. The rate constants were optimized against the time-resolved data using a global least-squares refinement method.

Figure 17. Correction of the TR-XSS data by removal of the heating signal. Experimentally measured heating signal (black) was subtracted from the measured difference scattering curve at 5 ms (red). The heating induced curve was scaled to fit the experimental difference data in the q-range between 1.5-1.7 Å-1.

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2.6.5 Structural analysis Structural refinement can be accomplished by comparing theoretically predicted XSS difference curves with the experimental TR-XSS data115. Theoretical curves can be calculated from crystal structures or simulated structures of transient protein conformations using software, such as CRYSOL116, FoXS117, or WAXSiS118. For this thesis, CRYSOL was used to calculate spherically averaged scattering patterns from protein coordinates with an implicit solvent model to account for the surrounding solvent. The average scattering intensity is given by the equation, S(𝐪) = [Fx(𝐪) −ρNFN(𝐪) +∆ρFy(𝐪)]K (13) Here, Fa(q) is the scattering amplitude from the protein in vacuum, Fs(q) is the scattering amplitude from the excluded volume, ρNis the density of the solvent, Fb(q) is the scattering from the border layer of water molecules and ∆ρ is the density contrast between the bulk and the border layer. For wider angles, the scattering from the border layer is relatively small and can thus be omitted119. The scattering intensity from proteins embedded in membranes or micelles in solution contains additional scattering contributions from the membranes/micelles and the corresponding cross-terms to the protein. To account for this, protein-membrane complexes were constructed in silico and the scattering intensity calculated for the entire protein-membrane complex. The theoretical scattering was then fitted to the TR-XSS difference scattering data. An internal R-factor (normalized root mean square difference) was devised to allow comparison to the experimental data. The R-factor was defined as,

R = d√Y∆q|}~t�~|����G∆q~��~���~�|��[)

d√Y∆q~��~���~�|��[) (14)

Here, Sr��mV�rO�x� represents the theoretical difference scattering curve between a ground/resting/pre-pulse state and a transient intermediate and S����VOn�Prx� is the experimentally measured difference scattering curve. 2.7 Molecular dynamics simulations 2.7.1 Theory Molecular dynamics (MD) simulation is a computational method to determine the movements of individual atoms in a dynamic system. The trajectories of individual

24

atoms are calculated by solving Newton’s laws of motion in a system of interacting particles using forcefields, which are a set of parameterized equations that are used to calculate the potential energy (Vff) of interacting atoms. Force fields describe interactions of all types atoms in a system, such as a protein. The potential energy described by a forcefield includes bonded and non-bonded interaction terms. The bonded interactions are bonds, angles and dihedrals whereas the non-bonded terms comprise long-range interactions, such as electrostatic and van der Waal’s interactions. Therefore, from the forces (F) governing the atomistic interactions (provided by forcefield), and the atomic positions in space (r) and mass (m), it is possible to simulate the evolution of the system by obtaining updated positions (ri) and velocities (vi), with respect to time using Newton’s second laws of motion,

𝐅O = −�����𝐫 (15)

𝐅O = m(dK𝐫/dtK) (16)

Therefore, combining equations 15 and 16, we get

− �����𝐫

= m(dK𝐫/dtK) (17) The system is simulated over time by updating atomic positions at successive small time-steps (in the order of femtoseconds). The trajectory of the system is represented by the change in coordinates over time and this information can be used to determine macroscopic properties of the system. The method of MD simulation was originally developed in the 1950s120 and the simulation time has been increased from few picoseconds121 to several micro or even milliseconds at present122, 123. 2.7.2 Targeted MD simulations In Targeted MD simulations (TMD), a defined set of atoms in the simulation is guided towards a final target structure through the means of steering forces. At each timestep, the RMSD between the current coordinates and those of the target structure is computed. The force applied to each atom is calculated by the gradient U��� =

�[��q|�G��q|)])

K] (18)

Here RMSt1 is the best fit RMSD of the current atomic coordinates to that of the target, while RMSt2 is calculated by a linear fit of the RMS values from the first TMD step to the final RMSD at the last step.

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TMD simulations is an enhanced sampling method to e.g. induce conformational changes in protein structures that would be impossible to probe using unbiased MD simulations. Hence, the transition of the protein is independent of the height of energy barriers. Therefore, the TMD approach can be used to sample conformational transitions between known structures in a reaction cycle. 2.7.3 Membrane simulations The lipid environment is crucial to the functioning of membrane proteins44. Properties of the lipid bilayers, such as thickness, curvature and specific interactions with the protein are key in maintaining the structural integrity and proper functioning of membrane proteins. Therefore, MD simulations of membrane proteins need to be inserted into membrane systems that as close as realistically possible model the native environment. To simulate membrane proteins in lipids, an atomistic in silico model of the system (proteins and lipids) can be created by tools such as the CHARMM-GUI124. The size, composition, and the symmetry of the lipid bilayer are aspects that define membrane systems. Environmental components such as solvent molecules (water) and ions can also be added to the system. In papers II and III, a model of the SR membrane in skeletal muscle cells was constructed using CHARMM-GUI and used for the simulations. The model contained the lipid types phosphatidylcholine, phosphatidylethanolamine, phosphatidylserine, phosphatidylinositol and phosphosphingomyelin in the ratio of 61:24:8:2:5, same ratio as in skeletal muscle SR membrane125. Since MD simulations can model structural dynamics at atomistic resolution126-133, specific interactions to lipids134-136 and ligands137, 138, the method is ideal for structural refinement of low-resolution methods such as TR-XSS115, 139-142 In the thesis, MD simulations were used for structural refinement of the TR-XSS data in Papers II and IV and for characterizing TR-XSS model stability and identifying lipid interactions in Paper III.

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3. Scope of the thesis The aim of this thesis was to develop a time-resolved X-ray scattering methodology to study the kinetics and structural rearrangements associated with the functioning of ATP-dependent proteins in solution. The obtained structural information could potentially complement traditional structural biology approaches and determine the structures of elusive transient intermediate states. Prior to performing the X-ray scattering experiments, it was necessary to develop an optimal triggering protocol for caged ATP at high protein concentrations. For this purpose, we used a combination of FTIR and biochemical colorimetric assays (Paper I). From this work, we identified optimal protein and caged ATP concentrations, as well as pH and temperature conditions at which the ZntA protein could be triggered in order to give the maximum activity. The next step was to develop a structural refinement procedure to obtain structural information from the time-resolved X-ray solution scattering (TR-XSS) experiments. For this purpose, the Ca2+ P-type ATPase (SERCA) protein was chosen as proof-of-principle system since it is well-characterized with several intermediate states resolved by X-ray crystallography. The synchrotron experiments monitored SERCA conformational changes, and the developed molecular dynamics (MD)-based structural refinement protocol revealed novel domain arrangements compared to existing crystal structures. The results shed new light into the structural dynamics of the SERCA transporter (Paper II). Following this in Paper III, MD simulations were used to finetune the structural assignment of the TR-XSS models from Paper II, as well as identifying state-dependent lipid-protein interactions. Finally, the combined TR-XSS and MD simulations methodology developed in Paper II was used on a soluble, but ATP-dependent, protein, adenylate kinase. The results summarized in Paper IV shed new light on the order of domain rearrangements, which provide direct experimental proof supporting the predictions made previously by computational studies.

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4. Results and Discussion – Paper I 4.1 Structural dynamics of P-type ATPases The crystal structure of a Zn2+-transporting Type-I ATPase from the pathogenic bacteria Shigella sonnei has sparked an interest in Type-I structural dynamics84. Because P-type ATPase function is dependent on the surrounding lipid bilayer, it is important to characterize protein structural dynamics under conditions that resemble the native environment. A few members of the P-type ATPase family exist in high enough concentrations in their native membranes, such as the Na+/K+ ATPase, H+ ATPase and Ca2+ ATPase, that enable their characterization in a native environment. However, this is not the case for the majority of P-type ATPases, which necessitates purification and characterization from recombinant sources. Time-resolved methods, such as TR-XSS, could in principle resolve single-cycle structural dynamics of membrane proteins. However, such methods necessitate high concentrations of protein and an efficient reaction trigger to generate satisfactory signal-to-noise. Caged ATP is an ideal trigger for use in time-resolved measurements of P-type ATPase structural dynamics. Therefore, Paper I aims at optimizing triggering conditions for the activation of Shigella sonnei Zn2+-transporting P-type ATPase (ssZntA) by a combination of biochemical activity measurements, ATR spectroscopy and time-dependent FTIR spectroscopy. Hence, the work establishes a protocol for structural characterization of recombinant, detergent-solubilized P-type ATPases and was published in the scientific journal Biopolymers143. 4.2 Production of a Shigella sonnei Zn2+ transporting P-type ATPase Shigella sonnei ZntA (ssZntA) DNA was cloned into a pET expression vector with a C-terminal His-tag and transformed into a BL21 (DE3) Escherichia coli expression strain. The cells were grown in an LB medium at 310 K until the absorbance measured at a wavelength of 600 nanometers reached 0.6. The cells were then induced with 1 mM isopropyl-beta-D-thiogalactoside (IPTG) and further incubated at 293 K for 20 hours. The cell culture was subsequently pelleted by centrifugation and lysed after resuspension in buffer by means of a high-pressure cell homogenizer. The resulting cell lysate was used for the purification of the expressed ssZntA by high-performance liquid chromatography (HPLC) using affinity and size-exclusion columns. The affinity column consists of Nickel-Nitrilo-Triacetictic-Acid (Ni-NTA) coated agarose beads and binds selectively to the poly-histidine terminal tag of the ssZnTA protein. The lysate was loaded onto the affinity column equilibrated with Tris-HCl buffer at pH 7.5 containing 20% glycerol and 50 mM imidazole and washed until a steady baseline was observed. The ssZntA protein was eluted by increasing the imidazole concentration to 500 mM (Fig.18A). Samples containing ssZntA protein were identified using SDS-PAGE and concentrated to approximately 10 mg/mL. The concentrated protein sample

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was then injected into a size-exclusion column equilibrated with MOPS-KOH buffer containing 20% glycerol and run at a flow rate of 0.4 mL/min. The protein eluted at 100 mL (Fig.18B) and the protein was concentrated using centrifugal concentration tubes to a final concentration of 13 mg/mL. For use in experiments requiring higher than 13 mg/mL concentrations of protein, the protein was purified at a lower concentration of glycerol to enable increasing the protein concentration by drying under a stream of N2 gas. Resuspension in lower volumes increased the protein concentration > 13 mg/mL while maintaining the glycerol concentration constant at 20%.

4.3 Measurement of protein activity using a biochemical colorimetric assay The Baginsky’s assay, which is a colorimetric assay that measures inorganic phosphate production, was used to measure the activity of the recombinant ssZntA protein. To

Figure 18. Chromatograms recorded at 280 nm. (A) Affinity column and (B) from size-exclusion column HPLC purification.

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evaluate the concentration dependence of protein activity, activities were measured at proteins concentrations of 0.13, 0.65, 1.3, 2.5 mg/mL in a MOPS-KOH (pH 7.0) reaction buffer containing 3.0 mg/mL C12E8, 1.2 mg/mL soybean lipids, 20 mM cysteine and 1 mM ZnCl2 at 310 K in a total reaction volume of 50 µL. The C12E8 detergent solubilized the membrane protein while the lipids are necessary for the protein function.144 The samples were incubated with 1 mM ATP (pH 7.0) at 310 K for 150 minutes with shaking. After the incubation step, 50 µL of stop solution containing 2.86 % w/v ascorbic acid, 1 M HCl, 0.48 % w/v (NH4)2MoO4, 2.86 % SDS was added and the mixture incubated on ice for 8 min. The stop solution inhibits the protein and brings the reaction to a halt. Following which, 75 µL colorimetric solution (3.5 % w/v Bismuth citrate, 1 M HCl and 3.5 % w/v sodium citrate) was added and further incubated for ~30 min at room temperature (293 K). The color development is caused by formation of a complex between phosphate and molybdate. The absorbance of the sample was measured in a UV-visible spectrophotometer at 710 nm. The specific activities were calculated as nanomoles of inorganic phosphate produced per mg of ssZntA per minute of the incubation (reaction) time. Triplicates of each set of experiments were performed and the specific activity was taken as their average.

The observed specific activities were constant for protein concentrations from 0.13 to 2.5 mg/mL (Fig.17). Because the specific activity was constant also at 2.5 mg/mL, this concentration was used as a standard when probing effects varied concentrations of ATP, reaction temperature and pH (Fig.19).

Figure 19. Specific activity of ssZntA in nanomoles of inorganic phosphate molecules produced per min, per mg of the protein, for different concentrations of protein.

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When testing the temperature dependence of enzyme activity, it was observed that the activity drops by 50% at 293 K (Fig.20A). This is probably due to the fact that the Shigella sonnei host organism naturally thrives at temperatures close to 310 K145. The protein activity at 2.5 mg/mL ssZntA was at its maximum at 1.0 mM ATP, while increasing the ATP concentration to 2.0 mM resulted in a 50% drop (Fig.20B). A similar effect was observed when the reaction sample buffer pH was increased to 8.0, slightly more alkaline compared to the neutral pH of 7.0 (Fig.20C). Time-resolved experiments are typically performed at high concentrations of proteins, in order increase the signal-to-noise ratio. One way to increase protein concentration is by drying the sample and resuspending it in a lower volume of buffer. To proceed with experiments at higher protein concentration we first tested the feasibility using the biochemical activity assay. To achieve a protein concentration of 25 mg/mL, the purification procedure was performed with 10% glycerol in the size exclusion buffer. This was done in order to ensure constant level of glycerol to allow comparison between experiments.

Figure 20. Specific activity at 2.5 mg/mL concentration of ssZntA at (A) different sample temperatures, (B) concentrations of ATP and (C) pH.

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Drying the protein to achieve a protein concentration of 25 mg/mL caused a 50% drop in the activity, compared to the activity measured at 2.5 mg/mL (without drying) (Fig.21). This likely originated from drying the protein at a lower quantity of glycerol (10%). Since it was previously demonstrated that caged ATP has an inhibitory effect on P-type ATPase activity146, 147, we tested if the presence of caged ATP had an inhibitory effect on the ssZnTA protein. This was because caged ATP was to be used as a trigger in the time-resolved FTIR experiments. Adding 10 mM caged ATP to the 25 mg/mL ssZntA sample did not produce a significant difference in its specific activity (Fig.22A). Since lipids have been shown to be essential for P-type ATPase activity,84 we tested if increasing the concentration of lipids in the sample could increase the protein activity. However, increasing the lipid concentration did not change the specific activity significantly (Fig. 22B). Therefore, samples with 25 mg/mL ssZntA and 10 mM ATP with 1.2 mg/mL added lipids were selected for used to scale up in time-resolved FTIR experiments.

Figure 21. Rate of ATP hydrolysis measured the colorimetric assay at protein concentrations of 2.5 and 25 mg/mL, respectively.

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4.4 Infra-red spectral signature of ssZntA activity To enable time-resolved FTIR experiments using caged-ATP activation it was first necessary to identify wavenumbers associated with the product formation of the ATP hydrolysis. For this purpose, ATR spectroscopy was used. The samples were prepared with purified, recombinant ssZntA protein at a final concentration of 1.3 mg/mL and 5 mM ATP in a MOPS-KOH pH 7.0 buffer with 1mM ZnCl2. From this sample mixture, aliquots were pipetted onto the crystal surface of a DuraSampllR II ATR spectrophotometer equipped with an MCT detector. The absorbance spectra were measured every minute, starting from the zero-minute spectrum recorded immediately after the sample was pipetted onto the ATR crystal surface. The OPUS Bruker software was then used to subtract each time-dependent spectrum from the initial absorbance spectrum at zero-minutes. The difference spectra at 5 min, 10 min, 15 min spectra show significant differences in absorbance in the region spanning 1400-900 cm-1 (Fig.23). The negative bands at 1235 cm-1 increased over time and showed similarity to bands observed at 1238 cm-1 that were attributed to the loss of phosphate groups from hydrolysis of ATP148, 149, whereas bands at 1192,1076, 941 cm-1 increased over time. Its known that the peak at 1076 cm-1

Figure 22. ATP hydrolytic activity measured at 25 mg/mL protein concentration of ssZntA for different concentrations of (A) caged ATP and (B) lipids.

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arises from stretching vibrations of PO32- molecules in the ADP and inorganic phosphate generated from ATP hydrolysis150. These results establish that ssZntA produces a distinct spectral signature arising from enzymatic hydrolysis of ATP over time.

4.5 Triggered time-resolved measurements of ssZntA activity For time-resolved measurements of ssZntA activity using FTIR spectroscopy, samples with protein concentrations of 13 mg/mL and below were prepared by drying 1 µl of 10 mM NPE-caged ATP under a stream of N2 gas on a CaF2 glass window with a 5 µm trough. This was followed by drying 1 µl of reaction buffer and resuspension with the protein sample (in 20% glycerol) for a particular protein concentration at constant lipid concentration. Formation of a gel-like phase in the centrifugal concentration made it difficult to reach protein concentrations above 13 mg/mL in 20% glycerol, which necessitated a different sample preparation method. Therefore, to prepare 25 mg/mL and 50 mg/mL samples, the protein was purified at lower concentrations of glycerol (10% and 5% respectively, instead of 20%). Here, 2 and 4 µl of the protein solution was dried upon the surface of the CaF2 window followed by resuspension with 1 µl of the reaction buffer and caged ATP. Hence, the glycerol concentration was kept constant in all samples of protein. The time-resolved measurements were carried out using a Bruker IFS 66 rapid-scan FTIR spectrophotometer with an MCT detector. A Xenon lamp was used to flash the

Figure 23. Difference spectra of ATR-FTIR measurements of ssZntA activity at a sample concentration of 1.3 mg/mL protein (in 20% glycerol) and 5 mM ATP at 310 K at 5 min (black), 10 min (red), and 15 min (blue). The decreasing band at 1235 cm-1 corresponds to the consumption of ATP in the sample while bands at 1192, 1076 and 941 cm-1 respectively correspond to the production of ADP and inorganic phosphate.

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sample at 120 mJ in the near UV-range. The arrangement of the lamp was directed along the focal line of an elliptical mirror, which helped focus the light directly to the center of the sample window. The spectral resolution of the data was 4 cm-1. Bruker OPUS software was used to record all time-resolved spectra of the ssZntA samples in 4 separate time bins; 0-12 s (10 spectra composed of 20 scans each), 13-82 s (10 spectra composed of 100 scans each), 83-287 s (10 spectra of 300 scans each), 288-492 s (5 spectra composed of 600 scans each), and 493-697 s (5 spectra composed of 600 scans each). The difference spectra were calculated with reference to a dark measurement of 2000 scans recorded immediately before the flash. Flash-induced release of caged ATP resulted in a number of bands in the 1200-900 cm-1 region of the difference spectra of ssZnTA (Fig.24A). The first were the bands at 1192, 1087, and 941 cm-1, which were the same as those assigned to ATP hydrolysis in the ATR-FTIR experiments (Fig.23). The bands at 1110, 1041, and 990 cm-1 could potentially arise from a subtle variation in glycerol concentration over time in the part of the sample probed by the IR beam. However, since, the 1245 cm-1 spectral region of the control spectra was completely unaffected by the glycerol bands, this region was chosen to evaluate ZntA ATPase activity under different conditions in the subsequent time-dependent FTIR characterization. The negative bands at 1345 cm-1 and 1527 cm-1

are indicative of the release of the ATP from its cage by UV light.150 The band at 1245 cm-1 decreases over the measured time intervals and has been previously assigned to ATP depletion due to enzymatic hydrolysis.151 Therefore, to quantify the protein activity, the rate of depletion of ATP was determined by tracking the reduction in the band area in the 1250-1240 cm-1 region. This was done by drawing a baseline between 1290 and 1190 cm-1 using the integration method E provided by OPUS software and calculating the change in band area over time. The averaged initial slope was calculated by fitting the traces in Fig.24B using the exponential expression y = A + B * EXP (-C*x), using the MATLAB curve fitting tool. The rate of the integrated absorbance change at 1245 cm-1 for 25 mg/mL ssZnTA and 10 mM NPE-caged ATP at pH 7.0 and 310 K was calculated to 5.9*10-5 cm-1/s.

35

Additionally, control experiments were performed in order to ensure that the bands at 1245 cm-1 arose only as a result of the ATP being hydrolyzed by the protein.

Figure 24. FTIR difference spectra of ssZnTA (prepared in 10% glycerol) at 25 mg/mL concentration and 10 mM ATP. (A) The three difference spectra represent the averages from time intervals 0-12 seconds (black), 83-287 seconds (red), 288-492 seconds (blue) and 493-697 (magenta), respectively. All of the spectra are aligned at the 1527 cm-1 band. (B) Kinetics of ATP hydrolysis calculated using the rate of decrease of the band at 1245 cm-1 over time. The three lines correspond to triplicate measurements.

36

The control experiment with caged ADP (Fig.25A) showed photolysis bands at the same positions as the ones seen in the experiment with 25 mg/mL ssZntA and 10 mM ATP, but did not show changes at the 1245 cm-1 region where ATP hydrolysis would be expected. Additionally, no further bands were observed at 1192, 1087, 941 cm-1 which are the bands corresponding to ADP and Pi production. However, changes in absorbance were observed at 1110 and 1041 cm-1 developing over time for the caged ADP controls (Fig.25B), which could possibly be assigned to minor variations in the glycerol concentration.152

Figure 25. Control experiments of photolysis triggered ATPase activity measured using FTIR, at 25 mg/mL protein and 10 mM ADP (A). The difference spectra correspond to averages from 0-12 s, 83-287 s, 288-492 s and 493-687 s respectively. The double difference spectra in (B) were calculated by subtracting the early 0-12 s time interval from the later 83-287 s (black), 228-492 s (red) and 493-687 s (blue) time intervals.

37

The control experiment with no protein (Fig.26A) showed photolysis bands at the same positions as the ones seen in the experiment with 25 mg/mL ssZntA and 10 mM ATP (Fig.26A) and also showed a band at 1245 cm-1 (Fig.26B), which was present in the first double difference spectrum and then remains largely constant. The band at 1245 cm-1 appeared in the first averaged block of time-dependent spectra and is coupled with the formation of other bands at 1449 and about 1650 cm-1 (not shown in the figure). These bands represent the formation of an intermediate in the reaction of the reducing agent dithiothreitol with the byproduct from the photolysis reaction97 and are therefore tentatively attributed to a reaction of the photolysis byproduct with the reductant (cysteine) in the sample.

Figure 26. FTIR control experiment with no protein and 10 mM ATP (A). The difference spectra correspond to averages from 0-12 s, 83-287 s, 288-492 s and 493-687 s respectively. The double difference spectra in (B) were calculated by subtracting the early 0-12 s time interval from the later 83-287 s (black), 228-492 s (red) and 493-687 s (blue) time intervals.

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Because glycerol is used to provide stability to membrane proteins, all experiments included 20 % (v/v) glycerol. To test the necessity of glycerol as stabilizing agent we performed time-dependent FTIR measurements in the absence of glycerol, but were unable to observe the difference bands associated with ATP hydrolysis (Fig.27). Time-resolved FTIR experiments were performed to study protein concentration-dependency of caged ATP-triggered ATPase activity. Since we were unable to spin-concentrate proteins above 13 mg/mL, we instead dried and resuspended the protein samples to obtain higher concentrations of 25 mg/mL and 50 mg/mL. The samples prepared this way had the same concentration of glycerol (20%), to permit comparison to other samples. The concentration of caged ATP and reaction temperature were kept constant at 10 mM and 310 K, respectively.

Figure 27. Control experiment of ssZntA protein prepared in absence of glycerol in the gel filtration buffer and 10 mM ATP. The difference (A) and double difference (B) spectra were calculated as described in the legends for Figures 23 and 24.

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The rate of ATP hydrolysis increased with protein concentration from 1.3 to 50 mg/mL (Fig.28). The observed rate of hydrolysis did not increase in a linear fashion. For instance, the hydrolysis rate observed at 13 mg/mL was not twice of that observed at 6.5 mg/mL, as was expected, even though both samples were prepared without drying. This effect could arise from an unknown concentration effect. Also, the activities at 25 and 50 mg/mL ssZntA concentration were not linear and we attribute this decrease to drying the protein in 10% and 5% glycerol respectively (instead of 20% glycerol). This is reminiscent of the same effect observed in the biochemical colorimetric activity assay (Fig.20).

Since the protein showed maximum activity at 25 mg/mL, this concentration was chosen to study the effect of pH, reaction temperature and caged ATP substrate concentration on ATPase activity. From the results shown in Fig.29, it is seen that the Zn2+ transporting P-type ATPase showed a maximum activity with 10 mM caged ATP at a reaction temperature of 310 K and at pH of 7.0.

Figure 28. Zn2+ ATPase activity resulting from spectroscopic measurements of NPE-caged ATP activation at varying concentrations of ssZntA protein.

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4.5 Summary of paper I In Paper I, we studied the triggering conditions of a recombinant full-length Zn2+ ATPase from Shigella sonnei (ssZntA) in a lipid-detergent solubilized mixture. First, the enzyme activity was measured using a biochemical activity assay at different protein concentrations, temperature, pH, ATP and caged ATP. We observed that the presence of caged compounds does not inhibit protein activity significantly. These conditions were then utilized for IR spectroscopic studies of the protein. ATR-FTIR was used to identify the IR fingerprint associated with ATP hydrolysis. This was then utilized in time-resolved FTIR spectroscopy to probe hydrolysis of ATP at different sample conditions such as protein, caged ATP concentrations, temperature and buffer pH. We recorded the highest total activity at a protein concentration of 25 mg/mL, at 310 K, and pH 7 triggered by 10 mM caged ATP. We also established that glycerol was necessary for protein activity and that protein prepared in the presence of 20% glycerol showed the maximum activity. These conditions were optimized to enable future time-resolved X-ray scattering studies to probe structural dynamics in the reaction cycle. Optimization using time-dependent FTIR was necessary because access to synchrotrons is severely limited. Therefore, our findings present an important step towards determining the structural dynamics of recombinant P-type ATPases.

Figure 29. Zn2+ ATPase activity resulting from spectroscopic measurements of NPE-caged ATP activation. The rates of ATP hydrolysis are shown for (A) varying concentrations of NPE-caged ATP, (B) reaction temperatures, and (C) pH. All the experiments were performed in triplicates (error bars).

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5. Results and Discussion – Paper II 5.1 Structural dynamics of the sarcoplasmic reticulum Ca2+

transporting pump (SERCA). The membrane transporter Ca2+ -ATPase (SERCA) is abundantly found in the sarcoplasmic reticulum (SR) membrane where it controls relaxation of skeletal muscle by pumping two Ca2+ ions from the cytosol to the SR lumen in exchange for 2-3 H+

ions.64 At a structural level, SERCA is the most well-characterized protein in the P-type ATPase family. The SERCA protein consists of four domains, which are named according to their functions: the phosphorylation (P), nucleotide-binding (N), actuator (A), and membrane (M) domains. One intriguing aspect of SERCA structure and function is that the domains undergo large-scale conformational changes throughout the reaction cycle to significantly change the inter-domain distances. Additionally, the phosphorylation site in the P domain is separated 36 Å from the ion binding sites in the M domain. Using phosphate analogues, several transient SERCA states have been trapped and crystallized to reveal detailed 3-D information on structural movements during the reaction cycle68, 72. The structures corresponding to the Ca2+-bound E1 state (Ca2E1) and subsequent Ca2+-occluded phosphorylated E1 states differ in the arrangements of the cytoplasmic domains resulting from ATP binding and hydrolysis to phosphorylate the protein (Fig.9). The ATP hydrolysis induces conformational changes leading to formation of an E2 state characterized by piston-like movements of the transmembrane helices that result in alternate access to the internal ion-binding sites.

Following Ca2+ release, the protein becomes dephosphorylated and binds H+ counterions to reform an E1 state facing the cytosol. While a majority of the intermediate steps have been crystallized, the crucial transient states associated with the Ca2+-bound, phosphorylated E1 and E2 states (Ca2E1P and Ca2E2P) remain elusive.

Figure 30. SERCA [Ca2]E1 (PDB ID: 2C9M) and E2P (PDB ID: 3N5K) SERCA crystal structures embedded into sarcoplasmic reticulum membrane mimics.

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An additional motivation for studying the SERCA reaction cycle is that crystallographic studies trap the protein in a crystal lattice that limits the displayed conformational changes13, 87. As a result, there are unresolved questions regarding the exact structural nature of Ca2+ transport in particular the transient states which are involved in the inward-to-outward switch, which necessitates studying protein conformational dynamics in solution under conditions that closely resemble its natural environment. Therefore, in Paper II, we used the TR-XSS methodology to track SERCA structural dynamics in real time on the µs-ms timescale. 5.2 Sample preparation SR membranes from rabbit, containing high concentrations of SERCA protein were centrifuged at 140,000*g followed by resuspension in MOPS buffer containing 100 mM KCl, 100 mM MgCl2 and 75 µM CaCl2. The final concentration of SR membranes was 25 mg/mL. Prior to the experiment, the protein sample was mixed with caged ATP to a final concentration of 10 mM. 5.3 Time-resolved X-ray solution scattering (TR-XSS) data collection Time-resolved pump-probe X-ray solution scattering data were collected of SERCA-containing SR membranes in solution at the dedicated time-resolved beamline ID09B at the European Synchrotron Radiation Facility (ESRF), Grenoble, France. The samples were pumped through a quartz capillary using a peristaltic pump at a constant flow rate. The reaction was initiated using a laser pulse focused at a spot on the capillary that was probed by the X-ray beam. The experimental time delay (Dt) between the laser flash and X-ray pulse generated time-resolved data for nine different time delays ranging from 20 µs to 200 ms (Fig.31A). The intensity of the scattered X-rays was recorded on a CCD camera and were collected over ~1,100 pump probe cycles per time delay to achieve satisfactory signal-to-noise. For each time delay, a so-called ‘dark reference’ representing a negative time delay was also recorded. The recorded TR-XSS images were integrated to obtain radial intensity curves as a function of the magnitude of the scattering vector. The difference scattering intensities were calculated by aligning scattering profiles at 2.0-2.1 Å-1 followed by subtraction of each time point from its respective flanking ‘dark reference’ images (obtained from the negative time points). To filter excessive noise, individual difference scattering profiles that diverged by more than 3.5 times the standard deviations were excluded. The signal resulting from heating of the sample due to the laser was removed by subtracting each difference scattering curve from a normalized heating curve obtained from a dye solution (Fig.31B).

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The resulting difference scattering curves thus arise solely from structural changes in the protein and surrounding lipids in the membrane. The experimental data show major features up to q = 0.25 Å-1, which corresponds to secondary and tertiary structural elements. Specifically, negative and positive features were observed at 0.04 Å-1 and 0.09 Å-1 and two positive features appeared at 0.16 Å-1 and 0.22 Å-1, respectively. The data does not change significantly after the 50 ms time delay (Fig. 31), which coincides with the reaction cycle under similar condition153, 154. This indicates that a rate-limiting state accumulated at t > 50 ms. 5.5 Kinetic modelling of the TR-XSS data The SERCA difference scattering data were spectrally decomposed according to the following sequential models:

Earlyk1→ Late

Early k1→ Intermediate

k2→ Late The rate constants between the transition from early to intermediate and intermediate to late states were k1 and k2, respectively. The rate constants were derived from least-squares refinement of the data according to:

Figure 31. The TR-XSS difference scattering data for SERCA. (A)The time delays range from 20 µs to 200 ms. The negative point of -50 µs was used as the ‘dark’ reference from which the difference scattering of other time points were calculated. To enhance visualization of low-q features all scattering curves were multiplied by q. (B) Removal of heating signal from the TR-WAXS data. Experimentally measured heating signal (black) is subtracted from the measured difference scattering curve at 5 ms (red). The heating induced curve was scaled to fit the experimental difference data in the q range between 1.5-1.7 Å-1

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∆S(q,∆t)theory = Ured(q)C(∆t) (19)

, where 𝑈�� (𝑞)is a m x k matrix containing the first k significant components and 𝐶(∆𝑡) is a k x n matrix with the kinetic profiles for k-number of different transitions. The latter is calculated by the integrated rate equations describing the kinetic transitions:

[early] = e-k1t (20)

[intermediate] = k1k2-k1

(e-k1t-e-k2t) (21)

[late] = 1+[(k1*e-k2t )-(k2*e-k1t)]/(k2-k1) (22)

The spectral decomposition that showed best agreement with the experimental data was a three-state model with a fast decay of the early component and an intermediate component with a rise time of 1.5 ms followed by formation of the late component at 13 ms. The kinetic components are described by their corresponding time-independent basis spectra (Fig.32A).The observed reaction rate of the late state corresponds to earlier observed rates of phosphorylation of the SERCA protein155, 156. To evaluate the agreement between the proposed kinetic model and the difference scattering data, reconstituted data from linear combinations of the basis spectra were fitted to the experimental data, resulting in a satisfactory match to the TR-XSS data (Fig.32B). The resulting global least squares fit of S=1.9 x 10-6 was significantly lower than transition between two states (S=2.9 x 10-6) or a single state decay (S=1.2 x 10-5). Adding a thapsigarin inhibitor, which traps the protein in an E2 state, eliminated the TR-XSS signal (Fig.32C).

Figure 32. Spectral decomposition and control. (A) Basis spectra obtained from spectral decomposition of the SERCA TR-XSS data. The black line represents the formation of an early state, the red and blue lines indicate the formation of intermediate and late states. (B) The data obtained from linear combination of the decomposed basis spectra and population densities (red) aligned to the experimental difference scattering curves (black). (C) TR-XSS data in the presence of thapsigargin, a SERCA inhibitor.

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5.6 Comparison to X-ray crystallography data To interpret the TR-XSS data structurally, the experimental basis spectra were compared to theoretical difference scattering curves calculated from structural models of putative SERCA transient states with respect to a common ground state, which in this case was taken to be the fully open Ca2+ bound E1 state (Ca2E1, PDB ID: 2C9M). We first calculated scattering profiles from atomic coordinates from crystal structures representing different transient states in the SERCA reaction cycle using the software CRYSOL116. Difference scattering profiles were then obtained by subtracting scattering from the ground state model from each intermediate state. The resulting difference scattering curves were corrected for use of polychromatic radiation by convolution using the undulator spectrum157. An R-factor was defined to quantify the agreement between the calculated scattering profiles and the experimental data,

R =¤Y¥~��|G�∗¥|}~t�¦[

)

√Y¥~��|[) (23)

Here 𝐼�¨©ªand 𝐼ª«�¬�­are the difference scattering intensities from the experiment and theory, respectively, and c is a scaling parameter. Overall, the calculated difference scattering profiles agreed better with the intermediate basis spectrum (lowest R-factor = 0.73) than the late basis spectrum (lowest R-factor = 0.89) (Fig.33). However, given that thermal fluctuation at room temperature results in R = 0.1, which can be considered an optimal fit, the available crystal structures did not generate satisfactory agreement with the TR-XSS data, in particular for the late state.

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Figure 33. Theoretical scattering from existing crystal structures. Difference scattering profiles generated from different E1 and E2 crystal structures with respect to the Ca2E1 ground state and comparison to the experimental intermediate basis spectrum (A) and experimental late basis spectrum (B). 5.7 Simulating transition dynamics Because the crystal structures did not satisfactorily explain the TR-XSS data, we explored structural dynamics beyond the crystal lattices. We first simulated transition dynamics between crystal structures using targeted MD (TMD) simulations in the absence of membrane lipids. A set of 100 structures was extracted along trajectories starting from the [Ca2]E1 state (PDB ID 2C9M) to each of the seven principal states with existing crystal structures and their difference scattering was calculated with respect to the starting state. Simulated transition structures towards the E1 crystal structures showed significant R-factor drops when compared to the intermediate basis spectrum at RMSDs < 5 Å close to the target E1 structure (Fig.34). However, comparison to the late basis spectrum resulted in significantly higher R-factors, indicating that the intermediate state but not the late state is explained by a coming together of the cytosolic domains which is expected to be the first major structural transition of SERCA following the binding of the photolytically released ATP. Instead, the late basis spectrum agreed better with transitions towards E2 states. The simulated structure that resulted in the lowest R-factor emerged mid-way in the transition towards the target E2P structure (Fig.34). Hence the experimental late state could best be explained by domain re-arrangements occurring in the E1 to E2 transition step.

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Figure 34. Structural refinement with simulated transition dynamics. R-factor and RMSD for the transition dynamics trajectories resulting in the lowest R-factors with respect to the (A) intermediate and (B) late basis spectra. The lowest R-factor difference spectra from X-ray crystallography, transition dynamics simulation, and membrane simulations with respect to the (C) intermediate and (D) late basis spectra. 5.8 Membrane MD simulations Since SERCA functionality is dependent on its lipid environment54 we inserted the structures that resulted in the lowest R-factors with respect to the intermediate and late basis spectra, as well as the Ca2E1 crystal structure (PDB ID 2C9M) into a model of the SR membrane. The membrane model contained experimentally derived proportions of phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylserine (PS), phosphotidyl inositol (PI), and sphingomyelin (SM) lipids125. All systems were then simulated for 300 ns without restraints. From each trajectory, 200 simulated structures were extracted for the structural refinement and the difference scattering was calculated between all 40,000 possible combinations of ground and excited state structures. The intermediate and late state pairs with the pre-pulse state that matched best with their corresponding TR-XSS experimental data were then identified. R-factor minimal values from different segments of the trajectories corresponded to similar structural solutions, which showed the robustness of the structural refinement. This did not significantly change even upon the addition of a scattering contribution from the surrounding solvent and lipids. This can be explained by the fact that large domain re-arrangements of the protruding soluble domains

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dominate the difference scattering compared to that of transient changes in the lipid positions. The best difference scattering pairs for the pre-pulse/intermediate state had a slightly improved R-factor compared to the crystal and transition structure difference scattering when matched against the experimental basis spectrum (Fig.34C). The effect was more pronounced in the pre-pulse/late state pairs (Fig.34D) when compared to the late basis spectrum, where a large R-value drop from 0.58 to 0.30 was observed. 5.9 Structural interpretation

To understand the TR-XSS modeling in structural terms, the simulated protein pairs that resulted in the best fit to the experimental data were superimposed upon the corresponding crystal structures (Fig.35).

Difference spectra of simulated intermediate and late states showed better agreement to the TR-XSS data when generated by subtraction of the simulated Ca2E1 structure, rather than the crystal structure. When the simulated pre-pulse states generated by the refinement process were compared to the Ca2E1 (PDB ID 2C9M) crystal structures, the pre-pulse states showed a more compact conformation of the cytosolic domains, in particular domains A and N (Fig.35). Previous single molecule fluorescence resonance energy transfer (FRET) microscopy performed on Listeria monocytogenes Ca2+ ATPase also had shown similar result158. The 1.5 ms intermediate state model showed similar positions of the M and P domains when compared to the Ca2E1ATP (PDB ID 3N8G) crystal structure, while the N and A domains showed slight shifts (Fig.35). Hence, the intermediate basis spectrum represents an early calcium-bound E1 state where the cytosolic domains have closed around the ATP molecule with some flexibility in the positions of the N and A domains compared to the available E1 crystal structures.

Figure 35. Structural rearrangements in the pre-pulse, intermediate and late state in the TR-XSS models (N, A, M and P domains colored) compared to the corresponding crystal structures (white) and formation rise times. The protein structures were superimposed on the M7-M10 helices, which display minimal movements in the reaction cycle.

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In the 13 ms late state model, the A domain occupied a position not observed in any crystal structure, while the N domain had an orientation close to E1 conformations. The late state therefore represented a state where the A domain had not yet fully moved to an E2 position, with the N domain still in an E1 position. The domain re-arrangements observed in the late state were significantly more pronounced compared to the intermediate state, which explained for the difference in magnitude between the two states (Fig. 34). Upon comparison of these states to the known crystal structures, the A-domain was observed to be in the rotating axis between the Ca2E1P:ADP and E2P crystal structures (Fig.36A). The ADP binding site was exposed in the late state model (compare panels Fig.36B,C), and the TGES motif was halfway from the phosphorylation site Asp351 when compared to the E2P crystal structure (Fig.36D). The TM1-3 helices were moving towards the E2P positions, but with the calcium binding residues and the M domain locked in a closed conformation (Fig.36E). Hence the late state TR-XSS model likely represents an intermediate state of the Ca2E1P:ADP to E2P transition, which is assumed to be an ADP-sensitive, calcium-occluded Ca2E1P state.

Figure 36. Real-time dynamics compared to known structural rearrangements. (A) Structural differences in the A domain between the late TR-XSS model (yellow), the [Ca2]E1:ADP (PDB ID: 3BA6) (blue), and E2P (PDB ID: 3B9B) (magenta) states. The N domain is colored red. (B) The [Ca2]E1:ADP state crystal structure (PDB ID: 3BA6) displays a closed A-N interface, while in the late state TR-XSS model, in (C), the A-domain (yellow) has moved relative the N-domain (red) to expose the ADP-binding pocket (encircled). The truncated rest of the ATPase is shown in gray. (D) TGES motif and Asp351 dynamics in [Ca2]E1:ADP (PDB ID: 3BA6, cyan) and E2P (PDB ID: 3B9B, pink) (upper), and [Ca2]E1:ADP (PDB ID: 3BA6, cyan) and late TR-XSS state (magenta) (lower). (E), TM1-3 helices and A domains from [Ca2]E1:ADP (PDB ID: 3BA6), E2P (PDBID: 3B9B), and late state with color coding as in a and ion-binding residues from the late state.

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5.10 Summary of Paper II In Paper II, we used laser activation of caged ATP to trigger the SERCA reaction and obtained TR-XSS structural data from the transport cycle of the protein in its native membrane. We further identified the temporal evolution of difference signals and rise times associated with the formation of transient intermediate states. The observed data were consistent with the observed rates of phosphorylation and enzyme turnover. We developed a structural refinement method that identified a pre-pulse state that showed significant structural differences in the cytosolic domains compared to the more open Ca2E1 crystal structures (PDB IDs 2C9M and 1SU4). Hence, the crystallized Ca2E1 structure might be one out of several possible protein conformations and might not necessarily represent the dominant structure in the Ca2+ bound E1 state. Using saturing Ca2+ conditions we observed accumulation of a 13 ms transient state in which the A-domain had moved to a position in-between that of crystal structures, but with N and P domains still in their E1 orientations. The refined TR-XSS state might therefore represent the as of yet structurally elusive ADP-sensitive Ca2E1P state (Fig.37).Finally, from a technical point of view the work in Paper II demonstrates that the TR-XSS methodology can be extended to proteins undergoing irreversible reactions and is not limited to light-sensitive proteins. This significantly increases the number of potential biological targets that can be studied with the TR-XSS method.

Figure 37. Schematic comparison of the principal structural rearrangements in-between crystal structures and TR-XSS models. The pre-pulse state shows reduced opening of the cytoplasmic domains, the intermediate TR-XSS model is similar to a [Ca2]E1ATP state, and displacement of the A domain in the late TR-XSS model exposes the ADP site, but with the N-domain not yet in a E2 position. The ATP and ADP displayed as four and three purple pentagons, the TGES motif is represented by a green rectangle, and phosphorylated aspartic acid in yellow and the calcium ions are depicted as green circles.

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6. Results and Discussion – Paper III 6.1 Lipid interactions and structural stability of SERCA transient intermediate states. Membrane protein function is dependent on lipids in the surrounding membrane and specific protein-lipid interactions regulate protein function44. Of the P-type ATPases, in particular the Na+,K+ ATPase have proven to be dependent on specific lipid interactions for optimal functionality45. The SERCA transporting activity also depends on lipid composition, especially thickness of the membrane159, but crystal structures have also resolved lipids that could potentially act as specific regulators70, 71. From E1 and E2 crystal structures, a total of four (A-D) lipid-interaction sites have been identified, which partially overlap with binding sites of regulatory transmembrane polypeptides like phospholamban and sarcolipin, as well as the inhibitor thapsigargin. While such experimental characterization of lipid-protein interactions can be painstakingly difficult, MD simulations are optimally suited for exploring structural dynamics in complex systems such as membrane proteins in lipid bilayers160. Using MD simulations in combination with low-resolution X-ray data, SERCA was shown to adopt its structure to the surrounding membrane and the lipids also reorganized around the protein to avoid hydrophobic mismatches161. Such in silico characterization requires structural data, such as crystal structures, as a starting point. Membrane protein crystal structures are crystallized in detergent micelles, which constitute a quite different surrounding compared to native membranes. Therefore, the SERCA TR-XSS models that have been identified in native SR membranes are ideal starting points to explore lipid interaction. Such MD simulation also pose an opportunity to characterize stability of the transient SERCA intermediates. The identified 1.5 ms TR-XSS intermediate represents a SERCA state where the cytosolic headpiece has closed to occlude the released ATP molecule141. However, the low-resolution data could not distinguish between phosphorylated and nonphosphorylated states, which means that the exact location of the 1.5 ms state in the SERCA reaction cycle is presently unknown. Upon examination of the known crystal structures, the full E1 to E2 transition is defined as a rotational movement of the A domain to expose the ADP binding site and opening of the transmembrane helices to release Ca2+ ions. TR-XSS experiments identified a putative Ca2E1P structure with a rise time of 13 ms in the reaction cycle, which had an intermediate A domain orientation with an exposed ADP site, thus primed for ADP release141.The rate of formation of the Ca2E1P state coincided with the rate-limiting step in the SERCA reaction cycle and was therefore involved in the crossing of a free energy barrier. Since such transient states are inherently unstable it is therefore important to analyse the stability of the TR-XSS 13 ms state. Would it fall back into an E1 state or take a more E2 like conformation?

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In addition, the TR-XSS studies also presented an equilibrium SERCA structure representing the protein before laser-induced release of ATP, referred to as a pre-pulse state141. The extent to which the protein is open towards the cytoplasm has been debated. Previous studies using FRET indicate that the wide-open conformation observed in Ca2E1 crystal structures (PDB IDs 2C9M,1SU4) probably constitute one out of several possible ensembles of states, where the vast majority showing a considerably more closed configuration. The TR-XSS pre-pulse model also showed a more closed configuration of the cytosolic domains. The stability of this SERCA state can also be addressed using extended MD simulations. Thus, the TR-XSS models from Paper II provide a unique opportunity to characterize transient state stability and domain dynamics, as well as lipid-protein interactions in Paper III. 6.2 Simulated systems Six variants of the TR-XSS models from the previous study (Paper II) were used, namely, the pre-pulse state, the 1.5 ms state (with no Ca2+ ions or ligands), the 1.5 ms state with Ca2+ and ATP, the 1.5 ms state with Ca2+ and phosphorylated Asp351 and ADP, 13 ms state (with no Ca2+ ions or ligands) and the 13 ms with phosphorylated Asp351 and Ca2+ ions. Each model was inserted into a model membrane mimicking the SR membrane composition125, which was built using CHARMM-GUI124 with symmetric lipid distribution in upper and lower leaflets. After energy minimization and six rounds of equilibration, each system was produced in an unrestrained 300 ns simulation using GROMACS 2019122. 6.3 Structural dynamics in the TR-XSS pre-pulse state The distances between the A, P and N domains were measured along the pre-pulse

simulation trajectory and were found to be stable for the P domain interaction with the A and N, which reflects upon the central location of the P domain (Fig.38A). The

Figure 38. Stability of the pre-pulse TR-XSS model. (A) Interdomain distances between A and P (black), A and N (red) and P and N (blue) domains. RMSDs of the the A, P and N domains in the pre-pulse state simulation with respect to (B) the fully open crystal structures and (C) principal E1 and E2 state crystal structures.

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distance between the A and N domains, on the other hand, increased dramatically to more than twice its starting distance and remained at this distance for a large part of the 300 ns simulation. Upon comparison to Ca2E1 crystal structures (Fig.38B), it was found the domain RMSDs decreased significantly indicating that the TR-XSS pre-pulse model opens up along the same conformation as the open crystal structures, but not to the same extent. This was further confirmed upon comparison to E1 and E2 state crystal structures, where the A and N domain RMSDs were considerably higher (Fig.38C). This indicates that the equilibrium state before accessing the ATP has a significant degree of freedom in the N-domain conformational space. 6.2 Intermediate (1.5 ms) state structural dynamics and stability In the simulation of the 1.5 ms TR-XSS state without any ligands or Ca2+, the distances between the cytosolic domains changed very little and were more favourably compared to the E1 state as compared to the E2 state (Fig.39A,B), indicating that this state was more stable than the pre-pulse model. Since the TR-XSS models are of low resolution, it was not possible to determine if the 1.5 ms model was phosphorylated or not. So, the 1.5 ms state was additionally simulated with phosphorylated Asp351, calcium ions and ligands (ATP and ADP, respectively in two independent simulations). We observed slightly increased dynamics in the A-N domain interaction in the simulation of the 1.5 ms state with ATP simulation, which stabilized after ~150 ns (Fig.39C). The E1 and E2 RMSDs showed a pronounced E1 character that increased throughout the simulation (Fig.39D). In the simulation of the phosphorylated 1.5 ms model (with ADP), it was observed that the A-N domain distance changed considerably In addition to the A-P domain distance (Fig.39E), while showing a more E1 state like conformation (Fig.39F), though not as much as the non-phosphorylated, ATP bound state.

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In addition, the distance between the TGES motif, which is involved in de-phosphorylation, and the phosphorylation site Asp351 was kept relatively constant in the ATP-bound 1.5 ms state simulation, when compared to the ADP-bound state simulation (Fig. 40A). Further, the ATP molecule showed increased RMSD compared to the ADP, which remained in a more fixed location bound to the N-domain (Fig. 40B). From these observations, it was concluded that the 1.5 ms TR-XSS model likely corresponds to a Ca2E1ATP state where the cytosolic domains have closed to bind ATP, but the protein has not yet become phosphorylated. In addition, the TGES motif which de-phosphorylates Asp351 maintained a steady distance in the ATP bound 1.5 ms simulation, when compared to the ADP bound one (Fig.40A). Further, the ATP molecule had increased RMSD than the ADP which remains in a more fixed location bound to the N-domain (Fig.40B). From these observations, it was concluded that the

Figure 39. Stability of the 1.5 ms TR-XSS model. (A) Interdomain distances between A and P (black), A and N (red) and P and N (blue) domains for the 1.5 ms TR-XSS state with no Ca2+ or ATP/ADP bound. (B) RMSDs of the 1.5 ms state simulation of A, P and N domains with respect to principal E1 and E2 state crystal structures. Similar analysis for the (C,D) non-phosphorylated, ATP bound and (E,F) phosphorylated, ADP bound 1.5 ms TR-XSS state.

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1.5 ms TR-XSS model corresponds to a Ca2E1ATP state where the cytosolic domains come together to bind ATP, but the protein has not yet become phosphorylated.

6.3 Late (13 ms) state structural dynamics and stability In the analysis of the non-phosphorylated 13-ms TR-XSS simulation, the cytosolic domains showed very stable positions and their RMSDs being stable when compared to E1 and E2 structures (Fig. 41A,B). This indicates that the TR-XSS model’s unique cytosolic domain arrangements were stable and did not undergo shifts towards either E1 or E2 conformations during the simulation period. Phosphorylation of the 13-ms model induced an increased A-N interdomain distance (Fig. 41C). The A and P domain RMSDs were relatively stable (Fig. 41D) and the increased A-N interdomain distance likely originated from the N domain. However, no tendencies to move towards E1 or E2 structures were observed (Fig. 41D).

Figure 40. 1.5 ms model dynamics. (A) Distances between the centers of masses of the TGES motif and Asp351 for the non-phosphorylated (black) and phosphorylated (red) states. (B) RMSDs of the ATP and ADP molecules in the non-phosphorylated (black) and phosphorylated (red) simulations.

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6.4 Lipid environment To characterize protein-lipid interactions we analysed all six simulations for enhanced sampling. The membrane thickness was assessed by measuring the distances between the averaged lipid densities for both the upper and lower leaflets. The overall membrane thickness was on average 5% thinner close to the protein. To determine the reason for the deformation effects in the vicinity of the protein, a depletion enrichment (DE) index of lipids was calculated. An increase in the lipid type would give rise to a DE > 1 while a decrease would give a DE < 1. In all simulations sampled, the dominating lipid types POPC and POPE showed a DE index of around 1, while POPS and PSM lipids were somewhat lesser (Fig.42A). However, in all simulations except for the non-phosphorylated 13 ms state, the POPI lipids showed a big increase in DE indices, indicating that anionic lipids are attracted towards the SERCA M domain. Anionic lipids have been observed to induce inhibitory effects on SERCA activity141. To further characterize the lipid environment around the SERCA M domain, the lipids with a high occupancy of >0.9 within 0.5 nm of the protein were counted and the proportion of high-occupancy lipid types matched the overall lipid proportions in the lipid-bilayer (Fig.42B). In particular, the high DE index POPI lipids were observed to

Figure 41. 13 ms model dynamics. (A) Interdomain distances between A and P (black), A and N (red) and P and N (blue) domains in the simulation with no Ca2+ or phosphorylation. (B) RMSDs of the A, P and N domains with respect to important E1 and E2 state crystal structures. Similar analysis for the (C,D) phosphorylated, Ca2+-bound 13 ms model.

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interact with the cytoplasmic end of helix M10 and the center-to-extracellular side of helices M1 to M2 (Fig.42C).

On comparing the high-occupancy lipid types and locations to the four principal lipid interaction sites identified from X-ray crystallography for the simulations of the 1.5 and 13 ms TR-XSS structures, no high occupancy lipids were found binding to the E2 specific site A in either of the simulations (Fig.43A,C), confirming that the TR-XSS models indeed were E1 states. A similar absence of lipid interactions was observed for the neighboring site C. Along with an enrichment of POPI lipids near site B, we also found high-occupancy POPC lipids in close contact to this part of the cytoplasmic interface. At Site D, which corresponds to the thapsigargin regulatory site, POPC and POPE lipids were found in both 1.5- and 13-millisecond TR-XSS simulations, respectively. Significant differences in the lipid interactions were observed in simulations of the 1.5 and 13 ms states. More high-occupancy lipids in the deep hydrophobic core of the M domain in the 13-millisecond state might indicate that the M domain in this state is involved in the E1-to-E2 transition. Hence, the M domain structure and local chemistry at this particular point in time is such that specific lipid-protein interactions are preferred and that these interactions in turn could help drive conformational change in transmembrane region.

Figure 42. Lipid dynamics in SERCA interface. (A) Depletion-Enrichment (DE) indices and (B) high-occupancy SR membrane lipid types in simulations of the 1.5-millisecond state (black), the 13-millisecond state (red), the pre-pulse state (blue), 1.5-millisecond state with bound ATP (magenta), phosphorylated 1.5-millisecond state with bound ADP (green), phosphorylated 13-millisecond state (brown). (C) Iso-density surface of the POPI lipids from the phosphorylated 13-millisecond state simulation (blue) mapped onto the SERCA membrane section (white).

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6.5 Summary of Paper III In Paper III, we simulated transient intermediate structures of SERCA in sarcoplasmic reticulum mimics. A 1.5 ms state that was previously characterized from TR-XSS studies was assigned an ATP bound state prior to phosphorylation and a 13 ms state retained its domain conformation stably corresponding to a phosphorylated calcium-bound state. In addition, we observed that the lipid interactions were typical of E1 states and we predicted the regulatory site in-between the transmembrane helices M3, M5 and M7 near their cytoplasmic site (site D) was involved in the E1-to-E2 transition. Therefore, simulations have helped finetune characterization of the time-resolved X-ray structures and to predict regulatory lipid-binding sites.

Figure 43. Lipid dynamics at the SERCA M domain interface to the surrounding lipids. Lipids sites A and B (magenta) and C and D (blue) displayed in a surface representation on the TM section (white) for two side-views for the (A,B) 1.5- and (C,D) 13-millisecond TR-XSS structures. Iso-density surfaces corresponding to the simulated positions at 0.6 occupancy for POPC (green), POPE (orange), POPI (cyan), and POPS (red) lipids.

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7. Results and Discussion – Paper IV 7.1 Introduction and outlay of the AK studies Adenylate kinase (AK) is a phosphotransferase enzyme that regulates cellular energy homeostasis by interconversion of adenine nucleotides162. The protein comprises of a central domain (CORE) linked to two flexible ATP-binding (LID) and AMP-binding (NMP) domains which undergo large-scale conformational changes in order to perform catalysis (Fig. 39). Crystal structures of E. coli AK have trapped the protein in substrate-free open (PDB ID 4AKE)29 and closed (PDB ID 1AKE)163 conformations, where the closed conformation was trapped usning a non-hydrolysable inhibitor. Because of its relatively small size (214 amino acids) and capability of undergoing large conformational change, AK has become a principal model system to study the relationship between protein structure, conformational dynamics and catalysis. A fundamental dynamic feature that has not yet been demonstrated experimentally is the ordering of domain closure. A range of computational studies have predicted closure of the LID domain to precede NMP domain closure36, 38-40, while studies indicating the opposite also exist41, 42. While NMR30, 32, 33 and single-molecule FRET31, 32, 34 experiments have monitored domain closing events, determination of the relative ordering of the domain movements cannot be obtained in such measurements. In our study, we activated the AK reaction by laser-induced release of caged ATP and tracked domain movements in real time using TR-XSS. The advantage of this method being that it is not only a non-intrusive method, but it allows tracking of all interatomic distances simultaneously and can therefore resolve ordering of structural even

Figure 44. Adenylate kinase structural information. Open (A) and closed (B) crystal structures of E. coli AK.

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7.2 TR-XSS results The TR-XSS experiments were performed at the dedicated time-resolved ID09 beamline at the ESRF synchrotron. The AK samples were pumped at a constant flow in a quartz capillary and difference scattering data were recorded in a time series of 20 µs, 80 µs, 350 µs, 1.4 ms, 6 ms, and 25 ms (Fig.45A). A three-state kinetic model was found to best describe the experimental data and identified two states which showed rise times of 0.3 ms and 5 ms respectively (Fig.45B). The structural refinement focused on the late basis spectrum since the rise times of the early and intermediate coincided with caged ATP release (Fig.45C). The SVD analysis identified two major components

with the slower component growing on the millisecond time scale (Fig.45D), which further confirmed the decision to proceed with refinement of the late basis spectrum.

Figure 45. TR-XSS data and kinetic modeling. (A) Difference X-ray scattering data (black) obtained by subtracting -50 µs ‘dark’ references (i.e. X-rays before laser) from each positive time delay (i.e. X-rays after laser). Reconstituted data (red) resulting from linear combinations of (B) the population densities and (C) time-independent basis spectra evaluates the kinetic modeling. The intermediate and late basis spectra showed rise times of 0.3 ms and 5 ms, respectively. (D) Independent singular value decomposition (SVD) also identified two major components.

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7.3 AK TR-XSS data structural refinement To interpret the 5-ms late state in structural terms, we first calculated theoretical difference scattering profiles from the open and close crystal structures (Fig. 46A).

While the overall shape agreed with the experimental data, substantial differences were present (Fig. 46B). In order to find a common structural feature in the ensemble dynamics, we extracted the hundred best-scoring structural pairs and calculated an average C-alpha distance difference matrix. The change in distances showed that the ATP-binding LID domain mostly initiated an inward rotational movement, while the AMP domain remained largely in a relatively open conformation (Fig.47C). Performing the same analysis on the hundred worst-fitting pairs showed both the LID and NMP domains to remain relatively open. Thus, the time-resolved structural data identified a dominating transient intermediate state at 5 ms that was best described by an initiation of the ATP-binding LID domain closing movement upon the laser triggered release of caged ATP, but before closing of the AMP binding domain, even though AMP was present in the solution.

Figure 46. Structural refinement of the 5-ms TR-XSS basis spectrum. Theoretical difference scattering profiles from (A) open (blue) and closed (red) crystal structures were calculated using the CRYSOL software, (B) which did not generate a satisfactory fit to experimental data as judged by a 0.94 crystallographic R-factor. To account for structural dynamics, (C) both crystal structures were simulated and difference scattering profiles for all possible combinations were calculated, (D) which drastically improved the fit to experimental data.

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7.4 Summary of Paper IV Continuing from our work in Paper II, we used time-resolved X-ray scattering to study the laser-activated reaction cycle of AK. Caged ATP releases on the millisecond time-scale164 and our characterization was therefore limited to the 5-ms transient intermediate. The X-ray scattering data revealed that the LID domain of AK initiated closing movement at 5 ms prior to the NMP domain in the presence of ATP and AMP substrates. Thus, Paper IV concludes a decade worth of simulation papers predicting the LID domain to initiate the closing mechanism.

Figure 47. Simulated AK dynamics and relation to the 5-ms TR-XSS data. (A) Sampling of domain movements in simulations starting from crystal structures of the open (red) and closed (green) states. C-alpha distance difference matrices of the (B) open and closed crystal structures (PDB ID: 4AKE and 1AKE, respectively), structural pairs from the simulations corresponding to the 100 (C) lowest or (D) highest R-factors with respect to the late basis spectrum.

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8. Concluding remarks and future directions The ever-increasing number of high-resolution protein structures resulting from advances in cryo-EM and X-ray crystallography techniques is accompanied by an increasing need to understand how these proteins rearrange their structures to perform function in their native environments. The extent of the conformational changes range from sub-Ångström to nanometer scale and the time ranges from nanoseconds to several hundreds of milliseconds, which makes such studies extremely challenging. The TR-XSS technique is ideally suited to study ATP-dependent protein structural dynamics because it is a direct probe, sensitive to all atomic positions, triggers the reaction externally (by activating caged ATP), and can track the reaction for several milliseconds. As a first step, since access to synchrotron facilities were limited, it was necessary to optimize the conditions for triggering ATP-dependent reactions. Therefore, FTIR spectroscopic studies of a recombinant bacterial Zn2+-transporting ATPase were performed (Paper I). The results pave way for the future characterization of membrane proteins that are not found in high concentrations in their native environments (i.e. the vast majority) and hence, need to be produced recombinantly and characterized in detergent-solubilized conditions. A drawback of the TR-XSS method is that the data is of low resolution, necessitating structural refinement methods. In Papers II and IV, it was achieved by MD simulations starting from known enzyme intermediate crystal structures. In Paper III, MD simulations were used to finetune the structural characterization of models obtained in Paper II. MD simulations provide valuable information on the atomistic scale and given developments of sampling algorithms and enhanced supercomputing capabilities is likely to be a major part of TR-XSS data analysis in the future. The work in this thesis, paves way for further TR-XSS studies of ATP-dependent proteins, such as the Na+/K+ ATPase and ABC transporters. Though ATP-dependent proteins constitute a relatively small part of the proteome, the developed TR-XSS methodology can also be used to pursue structural characterization of a wide range of proteins through similar means of triggering such as using caged neurotransmitters, ions, and other substrates. The work presented in this thesis establishes TR-XSS as a method to study ATP-dependent protein dynamics in solution in real time and paves way for characterization of a broader range of protein targets.

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9. Acknowledgements Pursuing doctorate studies in Sweden has a been a fantastic experience with so many wonderful people helping me along the way both professionally and personally. I would like to start by thanking my supervisor Magnus Andersson for believing in me and taking me on as a student. I could always come to you with questions and you gave me freedom to manage my own projects. As a newcomer to biophysics especially computational methods, I was able to learn a lot. This would not have been possible without your patience and understanding. I have always found you very generous with your time, always motivating me to try again when I have failed. I have learnt not just scientific techniques from you but also how to write and present my work in a good way. Once again, I would like to thank you for providing me the opportunities over the years to not just pursue new and exciting scientific research, but also to present my work to different audiences. I am also deeply grateful to my co-supervisor at Umeå, Magnus-Wolf Watz for his constant encouragement and support. It was a pleasure working in the same place as you, with your enthusiasm motivating me a lot. You had given me a nice introduction to the beautiful environment and culture of Northern Sweden when I first moved in here, which will stay with me for life. I would also like to thank my former co-supervisor Erik Lindahl at Scilifelab, Stockholm university for his encouragement and guidance. Like many others I too have been inspired by your enthusiasm for research and knowledge of science. I am lucky to have been able to work in proximity to you. I wish many other students would get the same privilege in the years to come. I have been very fortunate to collaborate with collaborators who put in a significant amount of work to help me conduct my research. First, I thank Andreas Barth of Stockholm university for kindly allowing me to use his equipment to pursue research that lead to my first publication. Without your explanations and critical inputs, it would not have been possible. I would also like to thank the members of your lab, past and present, who taught me the techniques of infra-red spectroscopy. Since a lot of the work in the thesis was carried out at the ESRF synchrotron at Grenoble, France I am very thankful to our collaborators there (past and present) like Martin, Michael and Matteo. I would also like to thank our collaborator in Denmark, Poul Nissen for supplying the sample used in our second publication and also Annette, Chenge and Mattias for helping me out at the synchrotron. I would like to thank my colleague Ram who has been a good friend and co-worker, thank you for all of your friendship and support, both inside the lab and outside of it. I would also like to thank another colleague Fredrik, who has also been a good friend. It was fun to attend and teach classes together. I wish the both of you all the very best

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for your future. It was also fun working with our “next-door” colleagues from the Wolf-Watz lab, namely Per, Jorgen, Jack, Ameeq, Apoorv and Chanrith. It made my work experience in Umeå very memorable. I wish them the very best for their future endeavours. It was a fun experience to teach students alongside with my other colleagues at the department Piotr, Khorshed and Martin. Even though it involved a lot of work, the experience was made fun thanks to you guys. I hope you continue to have a great life. I would also like to thank my other friends at KBC , Lakshmi, Amit, Pusan, Aparna, Rajesh and Naresh for making life in Umeå all the more enjoyable. I would also like to thank my colleagues and friends at Stockholm, who are too numerous to list here. My colleagues at the Science for life laboratory were great friends and made all those years in Stockholm all the more interesting and fun. In addition, I have a deep gratitude to Umeå university and KTH, Stockholm and to funding agencies Stifelsen Olle Engkvist and Vetenskapsrådet of Sweden who made my PhD studies possible. I am also deeply indebted to the people of Sweden who made me feel welcome and provided me with a memorable life experience. Last but not the least I would also like to thank Harish, Appa, Amma, Uma aunty and Ajji for all their love and support they have given me over the years. I am truly blessed to have them in my life. Finally, to Neha, my wife, I have no words to express all that you mean to me. I love you.

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