Establishing and Manipulating the Dimeric Interface Of

Home , Formyl peptide receptor, Melanopsin, OPN1LW, OPN1MW, OPN1SW, Opsin

ESTABLISHING AND MANIPULATING THE DIMERIC INTERFACE OF

VISUAL/NON-VISUAL OPSINS

A Dissertation

Presented to

The Graduate Faculty of The University of Akron

In Partial Fulfilment

Of the Requirements for the Degree

Doctor of Philosophy

William D. Comar

May, 2018

ESTABLISHING AND MANIPULATING THE DIMERIC INTERFACE OF

VISUAL/NON-VISUAL OPSINS

William D. Comar

Dissertation

Approved: Accepted:

Advisor Department Chair Dr. Adam W. Smith Dr. Christopher J. Ziegler

Committee Member Dean of the College Dr. Leah Shriver Dr. John C. Green

Committee Member Executive Dean of the Graduate School

Dr. Sailaja Paruchuri Dr. Chand Midha

Committee Member Date Dr. Michael Konopka

Committee Member Dr. Jordan Renna ii

ABSTRACT

G protein-coupled receptors (GPCRs) make up the largest family of cell surface protein receptors and are involved in a number of diverse biological processes. The association of GPCRs, whether they be monomeric, dimeric, or oligomeric, is hypothesized to alter their signaling. Attaining crystallographic evidence of the dimeric or oligomeric associations of Class A GPCRs, specifically (non)visual opsins, remains a difficulty, as does establishing the stability of these associations. The purpose of this research was to quantify the association of (non)visual opsins, in situ, in the plasma membrane of live cells.

We used a time-resolved fluorescence approach to accomplish this purpose. Pulsed- interleaved excitation fluorescence cross-correlation spectroscopy (PIE-FCCS) offered a way in which the dynamic interactions of (non)visual opsins could be quantified.

Throughout this dissertation, three projects will be presented. The first project focused on the dimeric association of rhodopsin, the light sensitive protein involved in scotopic vision. By transfecting low concentrations of rhodopsin into mammalian cells, we found a modest affinity for dimerization. The second project focused on the proteins involved in trichromatic photopic vision, cone opsins. Two of the three human cone opsins,

OPN1LW (red) and OPN1MW (green) share a 95% sequence homology. Despite having such a homology, red and green cone opsin showed different affinities for dimerization.

iii Red cone opsin was observed to have the highest affinity for dimeric association among the GPCRs studied. Green cone opsin was shown to primarily exist as a monomer.

Mutagenesis was performed on both red and green cone opsin in an attempt to decrease red cone opsin dimerization affinity and increase green cone opsin dimerization affinity. The third project focused on melanopsin, a non-visual human opsin. Melanopsin is expressed in the ganglion cell layer (GCL) of the retina and plays a role in both circadian rhythm and the pupillary light response. The experiments in Chapter 5 demonstrate that melanopsin has a low dimerization affinity. The affinity is higher than our monomeric controls, but lower than that of both rhodopsin and red cone opsin. Establishing the native association of these visual and non-visual opsins in the retina is a key step in determining how the spatial organization of these proteins regulates their biological function. Experiments in chapters 3, 4, and 5 begin to connect dimerization to function, but more work is needed to quantify these relationships. This work also creates a paradigm in which GPCR dimerization can be quantified and contextualized, which is critical for developing new pharmaceutical treatments for this important class of proteins.

DEDICATION

My middle school teacher once told 13 year old me that I’d never do anything with my life and I almost proved her right. I took the most unconventional route to get to this point. Those of you that never gave up on me along the way, this is for you! My amazing parents, William P. and Jacqueline Comar, thank y’all for the physical and mental support!

Through my bouts with depression and ostracism, y’all were always readily available to offer advice and I love y’all for that! My two beautiful older sisters, Kartika and Kiana, y’all are stronger than y’all could ever imagine! Constantly competing with each other growing up, y’all both became amazing mothers to healthy beautiful boys at almost the same time. So, it’s a tie… Keep believing in yourselves and know that I’ll never stop believing in each of you! My little brother, Waquiem, I’ve watched your maturation into manhood mostly from afar. Know that I’ve been in awe of you at every step and have even found myself looking up to you, at certain times. Keep grinding, keep pushing, and never let them see you sweat. My precious nephews, Quintas (Poseidon) and Isaiah (Zeus), your makua loves you both so very much! No matter where I’m at, I’m always there for y’all!

Finally, to the rest of my family and family-like friends, each one of you helped mold me into the man I am today. We may not have talked much or often through the years, but when I leaned on you, you kept me upright.

“As iron sharpens iron, so one person sharpens another” -Proverbs 27:17 NIV- v

ACKNOWLEDGEMENTS

I would like to thank my advisor, Dr. Adam Smith, for initially taking a chance with me during my undergrad. I would like to thank my fellow Smith Lab members (former and current) as I’ve had the pleasure of working with each of you in some form or fashion:

Dr. Xiaojun (Roger) Shi, Dr. Megan (Megatron) Klufas, Xiaosi Li, Shaun Christie, Paul

Mallory, Soyeon (Stephanie) Kim, and Grant Gilmore. I would like to thank all the former and current undergrads that have helped me over the years: Rachel Neugebauer, Tony

Esway, Kevin Skinner, Christie Klinginsmith, Morgan (1.0) Marita, Morgan (2.0)

Torcasio, Margaret Pinkevitch, and Ryan Lingerak. I would like to thank my committee members: Dr. Leah Shriver, Dr. Sailaja Paruchuri, Dr. Michael Konopka and Dr. Jordan

Renna. I would like to thank my collaborators: Dr. Beata Jastrzebska and Dr. Krzysztof

Palczewski.

I am grateful for the amazing Chem Dept. staff: Nancy Homa, Jean Gracia and Dr.

Bart Hamilton. I appreciate all the work you do! Finally, I’m especially grateful for the best group of friends and fellow Spring ’18 Ph.D. graduates anybody could ask for in: Dr.

Marie Southerland, Dr. Allen Osinski, Dr. Dan Morris, and Dr. Lucas McDonald! It was an absolute pleasure working through this process with each and every one of you!

TABLE OF CONTENTS

Page

LIST OF FIGURES ...... x

LIST OF SUPPLEMENTAL FIGURES ...... xiii

CHAPTER

I. INTRODUCTION ...... 1

II. MATERIALS AND METHODS ...... 13

INTRODUCTION ...... 14

PCMV6 VECTOR ...... 14

RESTRICTION ENZYME INSERTION ...... 14

MELANOPSIN DNA SEQUENCE ...... 17

MELANOPSIN MUTATIONS ...... 18

CELL CULTURE ...... 18

IMAGING ...... 19

PULSED-INTERLEAVED EXCITATION FLUORESCENCE CROSS- CORRELATION (PIE-FCCS) ...... 21

III. TIME-RESOLVED FLUORESECENCE SPECTROSCOPY MEASURES CLUSTERING AND MOBILITYOF A G PROTEIN-COUPLED RECEPTOR OPSIN IN LIVE CELL MEMBRANES ...... 22

INTRODUCTION...... 23

RESULTS AND DISCUSSION… ...... 27

vii CONCLUSIONS ...... 44

EXPERIMENTAL SECTION...... 46

PIE-FCCS INSTRUMENT ...... 46

CELL CULTURE AND TRANSFECTION...... 47

PLASMIDS ...... 48

DATA COLLECTION AND ANALYSIS ...... 49

IV. A G PROTEIN-COUPLED RECEPTOR DIMERIZATION INTERFACE IN HUMAN CONE OPSINS ...... 52

INTRODUCTION...... 53

MATERIALS AND METHODS...... 57

DNA CONSTRUCTS AND PRIMERS ...... 57

COS-7 CELL CULTURES AND DATA COLLECTION...... 58

FLUORESCENCE CORRELATION SPECTROSCOPY (FCS) ...... 59

PULSED-INTERLEAVED EXCITATION FLUORESCENCE CROSS- CORRELATION SPECTROSCOPY (PIE-FCCS) ...... 59

LIFTIME FITTING ...... 60

EXPRESSION OF CONE OPSINS IN HEK-293 CELLS; PIGMENT RECONSTITUTION AND PURIFICATION...... 60

UV-VIS SPECTROSCOPY OF CONE OPSIN PIGMENTS ...... 61

CROSS-LINKING OF CONE OPSINS IN MEMBRANES ...... 62

RESULTS...... 63

FLUORESCENCE CORRELATION SPECTROSCOPY OF HUMAN CONE OPSINS ...... 63

PIE-FCCS DATA SHOW THAT HUMAN RED CONE OPSIN, BUT NOT BLUE OR GREEN CONE OPSIN, IS SEGREGATED INTO DIMERIC STRUCTURES IN THE PLASMA MEMBRANE ………………………………………………………………….………. 66 viii LIFETIME FRET DATA OF CONE OPSINS ...... 76

A TRIPLE-POINT SWAP MUTANT DISRUPTS DIMERIZATION OF RED CONE OPSIN AND INCREASES DIMERIZATION OF GREEN CONE OPSIN ...... 79

CROSS-LINKING OF CONE OPSINS AND THE EFFECT OF A TRIPLE MUTATION ON DIMER FORMATION ...... 90

ROLE OF A TRIPLE MUTANT IN SPECTRAL TUNING ...... 94

CONCLUSIONS ...... 101

V. MEASURING G PROTEIN-COUPLED RECEPTOR DIMERIZATION IN HUMAN MELANOPSIN ...... 104

INTRODUCTION...... 105

RESULTS...... 108

PIE-FCCS OF HUMAN MELANOPSIN IN TRPC3-HEK293 CELLS ...... 108

A TRIPLE POINT MUTATION IN HUMAN MELANOPSIN ...... 115

CONCLUSIONS ...... 119

VI. CONCLUSIONS...... 120

REFERENCES ...... 125

LIST OF FIGURES

Figure Page

1.1 Sample FCCS Data for a Green Cone Opsin Mutant ...... 9

2.1 Restriction Enzyme Insertion… ...... 16

2.2 TRPC3-HEK293 Cell Expressing Melanopsin… ...... 20

3.1 PIE-FCCS Schematic… ...... 25

(a) Opsin-Expressing Cell ...... 25

(b) Schematic of Possible Diffusion Events ...... 25

(d) Photon Counting Events...... 25

(e) Fluorescence Fluctuations ...... 25

(f) Fluorescence Lifetime Histogram ...... 25

3.2 Representative FCCS Data...... 28

3.3 Summary of Cross-Correlation Data ...... 31

(a) Scatter Plot ...... 31

(b) Box and Whisker Plot ...... 31

3.4 Mobility…...... 35

3.5 Molecular Brightness ...... 37

3.6 FRET Analysis ...... 40

(a) Fluorescence Lifetime (ns)...... 40

x (b) FRET Efficiency (%) ...... 40

3.7 Dimerization Equilibrium Constants ...... 42

(a) Opsin… ...... 42

(b) Src16 ...... 42

4.1 Schematic of FCS Data Collection and Analysis ...... 64

(a) Membrane Diffusion Schematic ...... 64

(b) Fluorescence Fluctuations ...... 64

(d) Molecular Brightness ...... 64

(e) Diffusion Coefficient ...... 64

4.2 PIE-FCCS Data Collection and Analysis ...... 73

(a) Two Color Membrane Diffusion Schematic ...... 73

(b) Diagram of Single-Photon Events ...... 73

(d) Scatter Plot with Box and Whisker Plot Overlay ...... 73

4.3 Triple-Point Red/Green Cone Opsin Mutants ...... 81

(a) Homology Model of Red and Green Cone Opsin with Mutant Highlight ...... 81

(b) Scatter Plot with Box and Whisker Plot Overlay ...... 81

(d) Molecular Brightness ...... 81

4.4 Effect of Triple Mutations on Opsin Cross-Linking… ...... 92

(a) Effects of Mutations on the Formation of DSG-Cross-Linked Opsin

Dimers ...... 92

xi (b) Quantification of DSG-Cross-Linked Dimers...... 92

4.5 Biochemical Characterization of Green, Red and Mutant Cone Opsins ...... 99

(a) Immunoblots Indicating Expression Levels in HEK-293 cells ...... 99

(b) Immunoblots with 11-cis-retinal Purified by Chromatography… ...... 99

5.1 TRPC3-HEK293 Cell Expressing Mel WT ...... 109

5.2 Representative FCCS Data for Mel WT ...... 111

5.3 Summary of Cross-Correlation Data for Mel WT ...... 113

(a) Scatter Plot ...... 113

(b) Box and Whisker Plot ...... 113

5.4 Summary of Cross-Correlation Data for Mel WT and the Mel_LLI_A3

Mutant ...... 116

(a) Scatter Plot ...... 116

(b) Box and Whisker Plot ...... 116

5.5 Average Diffusion Coefficient ...... 118

6.1 Summary of Cross-Correlation Data for Visual and Non-Visual Opsins ...... 122

(a) Scatter Plot ...... 122

(b) Box and Whisker Plot ...... 122

xii

LIST OF SUPPLEMENTAL FIGURES

Figures Page

S4.1 FCCS Data for Red Cone Opsin ...... 69

S4.2 FCCS Data for Green Cone Opsin ...... 70

S4.3 FCCS Data for Blue Cone Opsin ...... 71

S4.4 Density Dependent Dimerization ...... 75

S4.5 FRET Analyses ...... 77

(a) Beeswarm Plot of Single Cos-7 Cell FRET Efficiency… ...... 77

(b) FRET Efficiency for Red/Green WT and Mutants ...... 77

S4.6 Density Dependence of FRET Efficiency ...... 78

S4.7 A Sequence Alignment of Red and Green Cone Opsins ...... 80

S4.8 FCCS Data for Red-TSV ...... 84

S4.9 FCCS Data for Green-IAM ...... 85

S4.10 Comparison of Red Cone Opsin Homodimerization with Heterodimerization of WT Red Cone Opsin and Red-TSV ...... 87

S4.11 Comparison of Dimerization for Green Cone Opsin, Green-IVM and Green-IAM ………………………………………………………………………………….. 89

S4.12 Biochemical Characterization and Spectral Tuning of EGFP Constructs ...... 96

(a) Immunoblots ...... 96

xiii (b) Membrane Localization ...... 96

(d) Absorption Spectra ...... 96

xiv

CHAPTER 1

INTRODUCTION

With about 800+ members, G protein-coupled receptors (GPCRs) make up the largest family of cell surface protein receptors. GPCRs are composed of 7 transmembrane

α-helices.1-3 These receptors are responsible for the transmission of a wide variety of biological signals across the plasma membrane. Biological signals such as neuronal, sensory and hormonal signals.4 Thus, making them a very popular target for pharmaceutical companies as an estimated 35% of approved drugs target GPCRs.5 With six different classes of GPCRs, this research focused on the Class A or Rhodopsin-like class of receptors.

The typical GPCR follows the following cycle for activation: 1) The receptor, with the bound heterotrimeric G protein, sits inactive in the plasma membrane. 2) A ligand binds to the N-terminus of the receptor, causing a conformational change in the receptor, and the

Gα subunit of the heterotrimeric G protein undergoes a guanine nucleotide exchange.

Exchanging GDP for GTP. 3) The Gα subunit dissociates from the Gβγ subunit. Both the

Gα and the Gβγ subunits move downstream to different effector cells and begin the signaling cascade. 4) Activation of GTPase causes GTP hydrolysis on the Gα subunit. 5) The ligand

6 on the receptor dissociates and the heterotrimeric G protein returns to the inactive state.

Opsin activation differs from that of the typical GPCR. The opsins have a covalently bound ligand, retinal, and unlike other GPCRs, they are activated via light.7-10

15 The activation cycle of rhodopsin begins with single photon absorption leading to isomerization of 11-cis retinal to all-trans retinal (ATR). ATR causes a conformational change in the inactive opsin receptor to the active opsin receptor. This conformational change allows for the binding of a heterotrimeric G protein, either transducin (Gt) for the visual opsins or Gq for melanopsin. The Gα subunits still undergo a guanine nucleotide exchange, upon binding the activated opsins, and dissociate from the Gβγ subunits to different effector cells for signaling.

For visual and non-visual opsins, the GTP on the Gα subunit is hydrolyzed to GDP allowing the inactive Gα subunit to rejoin the Gβγ subunit. In that time ATR must either continue through the retinoid cycle (visual opsins) or be photoisomerized, at a different wavelength than the initial phototransduction (melanopsin) to recreate 11-cis retinal.

Arrestin, a protein which stops the activation of GPCRs, is phosphorylated by a G protein receptor kinase (GRK) and terminates rhodopsin activity.11-12 ATR is reduced to all-trans retinol via all-trans retinol dehydrogenase (RDH) and is removed from the apoprotein opsin to enter the retinoid cycle.

The inter-photoreceptor retinol binding protein (IRBP) transports all-trans retinol out of the outer segment (OS) across the inter-photoreceptor matrix (IPM) and into the retinal pigment epithelium (RPE).13 A cellular retinol binding protein (CRBP) takes all- trans retinol to be esterified by lecithin retinol acyl transferase (LRAT) making all-trans retinyl ester (trans ester). Another soluble chaperone protein, RPE65, transports the trans ester to be isomerized by retinyl ester isomerohydrolase making 11-cis retinol.14-15 The alcohol is then oxidized back to 11-cis retinal by 11-cis retinol dehydrogenase and a

16 cellular retinal binding protein (CRALBP) transports it from the RPE across the IPM and back into the OS. An IRBP ushers 11-cis retinal to an opsin where it, non-covalently, binds making opsin-cis retinal. A Schiff base then forms between the opsin and 11-cis retinal recreating the complete visual opsin.

In recent years, a major concern of the GPCR community has been about how

GPCRs are arranged in the plasma membrane and how the arrangement affects cell signaling. Back in the late 70s early 80s, studies involving solubilized rhodopsin from rod outer segment (ROS) regions showed that a single rhodopsin molecule was able to activate the heterotrimeric G protein, transducin.16-18 These findings led to the belief that rhodopsin existed as a monomer. In 2000 the rhodopsin monomer narrative was questioned when a crystal structure (2.8 Å) of the GPCR was published showing a pair of rhodopsin molecules aligned parallel in a unit cell.8 A few years later Fotiadis et al. (2003), using atomic-force microscopy (AFM), showed that murine rhodopsin formed paracrystalline arrays or dimers

19 in native membranes.

The concept of rhodopsin dimerization was met with some opposition when a communication, Chabre et al. (2003), was published which directly questioned the validity of the AFM findings previously mentioned.20 Chabre et al. not only questioned the density of rhodopsin in the native disks but also whether the observed dimers were indeed just equally spaced proteins aligned in long double rows. In the same communication, Fotiadis et al. retorted that the results they observed via AFM, also accompanied by electron microscopy (EM), showed distinct rows of rhodopsin dimers.19, 21 Chabre and Maire (2005) went on to publish a review in which, again, rhodopsin dimerization was questioned on the basis that the original studies of detergent solubilized rhodopsin, in the 70s and 80s, was

17 4 extensively studied and characterized as a monomer.

A debate over rhodopsin dimerization still persists, though dimerization is more widely accepted, to date.22-23 When one considers the debate, why does dimerization matter? Why is dimerization important? With the observation of dimers, what is the functionality of dimerization? Does dimerization cause some sort of allosteric modulation or attenuation of signaling? Allosteric modulation occurs when a molecule interacting at a location on a protein alters the function or binding of a second molecule at a different spot on the protein.24 Allosteric modulation is not only an important regulator of GPCR function but is also critical in the development of compounds that target GPCR signaling.24-25

Kenakin and Miller (2010) discussed the two types of allostery resulting from dimerization of receptors: 1) The dimeric species can act as a combined conduit for signaling; 2) One of

24 the receptors pushes the other to function as a conduit for signaling.

When considering the dimeric interface, what is the driving force, chemically, behind these interactions? Studies like the biased molecular dynamics (MD) simulations performed by Johnston et al. (2012) showed a comparison between two proposed dimeric interfaces of β1- and β2-adrenergic receptors in an attempt to measure the strength of

GPCR dimerization under physiological conditions.26 Johnston et al. reported that the suggested interface between transmembrane helix one (TM1) and helix 8 (H8), under physiological conditions, was more stable and longer lasting (minutes) than that of TM4/3

(milliseconds). As for the driving force behind dimeric interactions, a review by Mondal et al. (2014) looked at protein-membrane interaction and how these interactions possibly influence protein-protein interactions.27 While studying rhodopsin, β1- and β2-adrenergic

18 receptors via MD, Mondal et al. took into consideration hydrophobic mismatch (HM), a mismatch occurring between an unperturbed membrane and the hydrophobic thickness of a protein embedded in that membrane. These studies and reviews show that there are numerous variables to consider while investigating the whys behind dimerization. Moving forward from simulations, the next steps would be to observe dimerization in live cells, quantify it, and determine the functionality of dimerization.

Class A GPCR dimerization has been observed with a number of techniques like x- ray crystallography,8, 28-29 AFM,19, 21, 30-32, Förster resonance energy transfer (FRET),33 and bioluminescence resonance energy transfer (BRET).34-35 These techniques have all contributed to the characterization of dimerization but each has their own advantages and drawbacks. X-ray crystallography is a powerful tool for atomic resolution structural analysis but requires the use of detergent solubilized membrane proteins.36 Though AFM can be performed on live cells, it can neither resolve the monomer-dimer equilibria nor can it distinguish between proteins in a heterologous system.37 FRET/BRET can also be measured in live cells but all conditions must be met. The fluorophores would need to be within 10 nanometers and the donor fluorophore would need to transfer energy to the acceptor fluorophore.38 FRET/BRET could also be measured from dynamic collisions or

“touch-and-go” interactions, giving rise to false positives of dimeric activity.

The current need in the field is to quantify dimerization with high and reproducible accuracy in such a way that dynamic (ie non-dimer forming) collisions are disregarded during the measurement of stable dimeric complexes. To address this/these needs, my approach was to use a time-resolved fluorescence technique capable of being performed in live cells. Using pulsed-interleaved excitation fluorescence cross-correlation spectroscopy 19 (PIE-FCCS), we were able to quantify the dimeric affinity of human opsins. PIE-FCCS is a technique that quantifies the number of co-diffusing species, whether homo- or heterooligomers, while simultaneously quantifying the total population of the diffusing species.

This helps eliminate the false positives for dimerization previously mentioned.

During PIE-FCCS, a pulsed white light source is used to create blue and green beams which pass through fibers of varying sizes. The blue and green beams are pulsed at

100 ns and interleaved at 50 ns with respect to each other. The blue and green beams pass through a 488 nm and 561 nm filter, respectively, and are then sent through a dichroic beam splitter to the sample. The sample, for these studies, a set of cells transiently co-transfected with visual or non-visual receptors containing a fluorescent tag of either mCherry or EGFP.

The signals returning from the sample pass through a 50 μm confocal pinhole and are split with a long-pass filter before then being sent to wavelength specific detectors (i.e. green and red detectors). The wavelength specific detectors pick up any signal, within a 50 ns pulse, from any species expressing the proper fluorescent tag. For example, during the 488 nm laser pulse, the green detector picks up any signal from the sample showing the expression of EGFP.

From the data produced, during the live cell measurements, there are a few parameters created that are used to determine dimerization and the degree to which a species dimerizes. First molecular brightness (η,cpsm), determined by average number of molecules (Ni) divided by the photon count rate or counts per second (cpsi).

20 The molecular brightness shows that a dimer is, ideally, twice as bright as a monomeric

species. Before considering the diffusion coefficient (D), determined by the square root of 2 the radius of the lasers ( ) divided by the decay time of the auto-correlation curve (4 ), 0

2 = � 0

the plot of the data from the created FCCS curves are examined.

In Figure 1.1, the green and red colored dots are the measured data points for the

individual auto-correlation curves (ACCs) from the data for the EGFP and mCherry,

respectively, fused species. The amplitude of the green ( ()) or red ( ()) ACC is

inversely proportional to the number of diffusing species expressing EGFP or mCherry,

respectively. The blue dots are the measured data points from co-diffusing species for

FCCS where the amplitude of the curve ( ()) is proportional to the total number of co-

diffusing species. The black lines represent the fitted functions and the horizontal dotted

line is the zero value. The diffusion coefficient tells us that a dimeric species should be

slower to diffuse through the plasma membrane and confocal area than a monomeric

species due to the size of the species. The same should apply to an oligomeric species in

comparison to a dimeric species with the bulkier oligomer diffusing much slower than the

dimer. The final consideration for dimerization is based on the relative cross-correlation

(fc) where the amplitude the co-diffusing species ( (0)) is divided by the zero-time value

of the max ACC ( (0)).

(0) C = (0)

Figure 1.1. Sample FCCS Data for a Green Cone Opsin Mutant. Green and red colored

dots are the measured data points for the individual auto-correlation curves (ACCs). The

green and red colors correspond to cells expressing EGFP and mCherry, respectively, with

the amplitude of the green ( ()) or red ( ()) ACC inversely proportional to the

number of diffusing species. The blue dots are the measured data points from co-diffusing species for FCCS with the amplitude of the curve ( ()) proportional to the total number

of co-diffusing species. The black lines represent the fitted functions and the horizontal

dotted line is the zero value.

22 In the work described in this thesis, PIE-FCCS was used to quantify dimerization of human opsins. The work begins with a focus on rhodopsin because it was historically at the center of the GPCR dimerization debate. Rhodopsin is contained in stacks of discs in the outer segment of rod photoreceptors in the retina. Rhodopsin is comprised of the protein opsin and a covalently bound ligand, 11-cis retinal, and is the primary GPCR in the visual signaling cascade of rod photoreceptors.39 Of the three modes of vision, rhodopsin is involved with scotopic vision which takes place during low lit conditions or night vision.8

Chapter 3, “Time-resolved fluorescence spectroscopy measures clustering and mobility of a G protein-coupled receptor opsin in live cell membranes”, describes how, using PIE-

FCCS, we were able to establish the concentration dependence of dimeric rhodopsin in live cells. Using those results, we were also able to quantify the diffusion, molecular brightness, and the equilibrium constant (Keq) for dimerized rhodopsin. The Keq had not been previously reported.

There are two other modes of vision, aside from scotopic vision, that evolved to deal with different levels of light. Photopic vision (well lit conditions or daytime vision), involves cone opsins. Mesopic vision is a mixture of both rods and cones.39 Three cone opsins make up the trichromatic daytime vision; red, green and blue.40 Cone opsins are structurally similar to rhodopsin but have different spectral sensitivities. Light stimulates red cone opsin around 560 nm (long wavelengths), green cone opsin is stimulated at medium wavelengths (530 nm) and blue cone opsin (short wavelengths) around 430nm.41

Chapter 3, “A G protein-coupled receptor dimerization interface in human cone opsins”, describes how we were able to quantify the diffusion and molecular brightness of cone opsins, again using PIE-FCCS. More importantly, we were able to identify a dimeric

23 interface for cone opsins and identify a few residues partially responsible for the spectral tuning of red cone opsin.

A few layers away from rods and cones, in the ganglion cell layer (GCL), resides a third opsin; melanopsin. Melanopsin is responsible for circadian clock regulation, which roughly follows a 24 hour clock.42 In regards to inner-retinal photosensitivity, melanopsin is thought to be essential. Melanopsin itself can also give rise to photo responsiveness in mammalian cells.43 In Chapter 4, much like Chapters 2 and 3, we discuss how we were able to quantify the dimeric association of melanopsin using PIE-FCCS. Site- directed mutagenesis was also carried out on melanopsin in an attempt to manipulate the dimeric interface of the GPCR. As with all of these opsins, there is further work to be done.

Establishing and manipulating the dimeric interface of these GPCRs is just a start.

These studies open up different avenues of research for potential pharmacological targets.

Studies like the one by Orru et al. (2011) looked at how different heterodimers could affect

44 the binding affinities for antagonists of the GPCR adenosine A2A receptors (A2AR).

Chinese hamster ovary (CHO) cells were co-transfected with the GPCR(s) A2AR and either

A1AR, dopamine D2 receptors (D2R), or neither of the two. The cells were treated with one of six different antagonists. A decrease in binding affinity for the antagonist SCH442416 was observed for cells expressing D2R as compared to cells expressing just A2AR or also expressing A1AR. The antagonist KW-6002 actually showed a higher binding affinity for the A2AR-D2R heterodimer. These results show that allosteric modulation plays a major

24 role in the binding affinity for agonists/antagonists. Establishing an understanding of the dimeric activity of GPCRs could offer insight into potential allosteric modulations.

Manipulating these interactions would potentially be useful for diseases like Huntington’s and or Parkinson’s.

CHAPTER 2

MATERIALS AND METHODS

INTRODUCTION

In this chapter I describe the vectors used and mutations made to plasmids in unpublished portions of this research. The raw DNA sequence of melanopsin is listed as well as any primers used. Also described are the techniques used for cell culture, imaging and PIE-FCCS.

PLASMIDS AND PRIMERS

PCMV6 VECTOR

Human melanopsin, purchased from Origene (Rockville, MD), was obtained with melanopsin flanked on either side by the restriction enzymes SgfI (GCGATCGC) and MluI

(ACGCGT) at the 5’ and 3’ ends, respectively, in a pCMV6 vector. Vectors pmCherry-N1

(Clonetech, Mountain View, CA) and mEGFP-N1 (Addgene, Cambridge, MA) were purchased along with the restriction enzymes AsiSI (SgfI) and MluI-HF (New England Bio

Labs, Ipswich, MA).

RESTRICTION ENZYME INSERTION

The restriction enzymes, AsiSI (SgfI) and MluI-HF, were inserted into the multi cloning sites (MCS) of the pmCherry-N1 and mEGFP-N1 vectors using the following primers: AsiSI, forward primer 5’- CGA TCG CTA CCG GAC TCA GAT CTC G -3’ and reverse primer 5’- CGC TAG CGG ATC TGA CGG -3’; MluI forward primer 5’- ACG

26 CGT TTC TGC AGT CGA CGG TAC -3’ and reverse primer 5’- TTC GAA GCT TGA

GCT CGA G -3’. The restriction enzymes were inserted using the protocols supplied from a Q5® site-directed mutagenesis kit (New England Bio Labs). The pCMV6 vector underwent gene synthesis to remove the full-length human melanopsin sequence, which was then cloned into the custom fluorescently tagged vectors. The melanopsin plasmids were made by Genewiz (South Plainfield, NJ). All insertions and sequences are also verified by Genewiz.

Figure 2.1. Restriction Enzyme Insertion. Restriction enzymes AsiSI (SgfI, GCGATCGC) and MluI-HF (ACGCGT) were inserted into the MCS of both a pmCherry-N1 vector

(shown) and a mEGFP-N1 vector.

27 MELANOPSIN DNA SEQUENCE

Listed beneath is the raw DNA sequence of the GPCR melanopsin:

ATGAACCCTCCTTCGGGGCCAAGAGTCCTGCCCAGCCCAACCCAAGAGCCCA

GCTGCATGGCCACCCCAGCACCACCCAGCTGGTGGGACAGCTCCCAGAGCAG

CATCTCCAGCCTGGGCCGGCTTCCATCCATCAGTCCCACAGCACCTGGGACTT

GGGCTGCTGCCTGGGTCCCCCTCCCCACGGTTGATGTTCCAGACCATGCCCAC

TATACCCTGGGCACAGTGATCTTGCTGGTGGGACTCACGGGGATGCTGGGCA

ACCTGACGGTCATCTATACCTTCTGCAGGAGCAGAAGCCTCCGGACACCTGC

CAACATGTTCATTATCAACCTCGCGGTCAGCGACTTCCTCATGTCCTTCACCC

AGGCCCCTGTCTTCTTCACCAGTAGCCTCTATAAGCAGTGGCTCTTTGGGGAG

ACAGGCTGCGAGTTCTATGCCTTCTGTGGAGCTCTCTTTGGCATTTCCTCCAT

GATCACCCTGACGGCCATCGCCCTGGACCGCTACCTGGTAATCACACGCCCG

CTGGCCACCTTTGGTGTGGCGTCCAAGAGGCGTGCGGCATTTGTCCTGCTGGG

CGTTTGGCTCTATGCCCTGGCCTGGAGTCTGCCACCCTTCTTCGGCTGGAGCG

CCTACGTGCCCGAGGGGTTGCTGACATCCTGCTCCTGGGACTACATGAGCTTC

ACGCCGGCCGTGCGTGCCTACACCATGCTTCTCTGCTGCTTCGTGTTCTTCCTC

CCTCTGCTTATCATCATCTACTGCTACATCTTCATCTTCAGGGCCATCCGGGA

GACAGGACGGGCTCTCCAGACCTTCGGGGCCTGCAAGGGCAATGGCGAGTCC

CTGTGGCAGCGGCAGCGGCTGCAGAGCGAGTGCAAGATGGCCAAGATCATG

CTGCTGGTCATCCTCCTCTTCGTGCTCTCCTGGGCTCCCTATTCCGCTGTGGCC

CTGGTGGCCTTTGCTGGGTACGCACACGTCCTGACACCCTACATGAGCTCGGT

GCCAGCCGTCATCGCCAAGGCCTCTGCAATCCACAACCCCATCATTTACGCC

ATCACCCACCCCAAGTACAGGGTGGCCATTGCCCAGCACCTGCCCTGCCTGG 28 GGGTGCTGCTGGGTGTATCACGCCGGCACAGTCGCCCCTACCCCAGCTACCG

CTCCACCCACCGCTCCACGCTGACCAGCCACACCTCCAACCTCAGCTGGATCT

CCATACGGAGGCGCCAGGAGTCCCTGGGCTCGGAGAGTGAGGTGGGCTGGA

CACACATGGAGGCAGCAGCTGTGTGGGGAGCTGCCCAGCAAGCAAATGGGC

GGTCCCTCTACGGTCAGGGTCTGGAGGACTTGGAAGCCAAGGCACCCCCCAG

ACCCCAGGGACACGAAGCAGAGACTCCAGGGAAGACCAAGGGGCTGATCCC

CAGCCAGGACCCCAGGATG

MELANOPSIN MUTATIONS

To create the melanopsin L246A, L249A, I252A triple point mutants, the melanopsin wild types underwent site-directed mutagenesis using a Q5® site-directed mutagenesis kit (New England Bio Labs) and the following primers: forward primer 5’-

TAT CAT CGC CTA CTG CTA CAT CTT CAT CTT C -3’ and the reverse primer 5’-

GCC AGA GGG GCG AAG AAC ACG AAG CAG CAG -3’. The above mentioned plasmids were then used for PIE-FCCS experiments.

CELL CULTURE

TRPC3-HEK293 cells (BPS Bioscience, San Diego, CA) are seeded at 10+6 cells/mL on 100 mm X 20 mm tissue culture plates (Celltreat Scientific, Pepperell, MA) with 10 mL of Dulbecco’s modified Eagle’s medium (High glucose and L-Alanyl-L-

Glutamine, Caisson Labs, Smithfield, UT). The DMEM is supplemented with 10% FBS

(Seradigm, VWR, Radnor, PA), 1% NEAA (Gibco, Life Technologies, Grand Island, NY),

1% Sodium pyruvate (Gibco, Life Technologies), and 400 mg/mL Geneticin (Caisson

Labs). Cells are grown at 37ºC and split when the confluency reaches ~75-90%. Three days

29 prior to imaging, cells are split onto Poly-L-lysine (Sigma-Aldrich, St. Louis, MO) treated

22 mm X 22 mm cover slides (Fisher Scientific, Thermo Fisher Scientific, Waltham, MA) in six well plates (Argos Technologies, Elgin, IL) with 2.5 ml of complete media. Cells are then transiently transfected 16 hours prior to imaging using Opti-MEM I reduced serum medium and Lipofectamine (Thermo Fisher Scientific) according to the protocols provided. On the day of imaging, at least 30 minutes prior to, media is removed from the six well plate and replaced with Opti-MEM I reduced serum medium (no phenol red,

Thermo Fisher Scientific).

IMAGING

Individual cover slides are transferred from the six well plates to a 35mm chamlide

CMS magnetic chamber (Live Cell Instrument, Nowon-gu, Seoul, Korea) and 1 mL of

Opti-MEM I reduced serum medium is gently added to the chamber. The chamber is placed in a stage incubator on a custom-modified Eclipse Ti inverted microscope (Nikon

Instruments, Tokyo, Japan) for imaging. The cover slide is searched via raster scan for fluorescent cells. A laser is focused on the membranous portion of fluorescent cells and five 15-second acquisitions are taken for each cell.

30 Laser illumination

Figure 2.2. TRPC3-HEK293 Cell Expressing Melanopsin. Shown, is a stack image from the red and green channel of a TRPC3-HEK293 cell co-expressing Mel-mCherry and Mel-

EGFP.

PULSED-INTERLEAVED EXCITATION FLUORESCENCE CROSS-CORRELATION

SPECTROSCOPY (PIE-FCCS)

A white light source (SuperK NKT Photonics, Birkerod, Denmark) was used to create laser excitation. The laser is pulsed at 9.7 MHz and has an internal pulse picker. Blue and green beams pass through 488 nm and 561 nm filters, respectively. The 488 nm filter and 561 nm filter have a 1.9 nm and 2.1 full half max (fwhm) bandwidth, respectively

(LL01-488-12.5, LL02-561-12.5, Semrock, Rochester, NY). Each beam pulses at 100 ns and are interleaved at 50 ns with respect to each other. A dichroic beam splitter

(zt488/561rpc, Chroma Technology Corp., Bellows Falls, VT) directs each beam to the sample on the stage. The fluorescent signals pass through a laser-blocking filter

(zet488/561m, Chroma technology Corp.), used to remove scattered laser light. The signals passing through a 50 μm confocal pinhole (Thorlabs, Newton, NJ) are split with a long- pass filter (FF560-FDi01-25x36, Semrock) and filtered into two, wavelength specific, bandpass-filtered (FF01-621/69-25, Semrock) SPAD detectors (Micro Photon Devices, 31 Bolzano, Italy). At a timing resolution of 32 ps, time-correlated single-photon data is recorded with a four-channel routed time-correlated single-photon counting (TCSPC) device (Picoharp 300, PicoQuant, Berlin, Germany). FCCS data is constructed from the

TCSPC files. The photons arriving to the “green” and “red” detectors within 50 ns of 488 nm and 561 nm pulses, respectively, are used to make time-dependent fluorescence signals

(FG(t) and FR(t), respectively). Correlation spectra is calculated, fit, and analyzed as

45-47 previously reported.

CHAPTER 3

TIME-RESOLVED FLUORESECENCE SPECTROSCOPY MEASURES

CLUSTERING AND MOBILITYOF A G PROTEIN-COUPLED RECEPTOR OPSIN

IN LIVE CELL MEMBRANES

INTRODUCTION

Membrane receptor dimerization and assembly is essential in many cell-signaling pathways, but remains controversial for many others. The reason for the controversy is the complex nature of the plasma membrane and the lack of tools to probe these structures in situ. G protein-coupled receptor (GPCR) oligomerization, for example, remains controversial despite numerous investigations.48-50 The prevalence and physiological role of GPCR oligomers is of central concern because GPCRs comprise the largest family of membrane proteins in the mammalian genome and a large fraction of drugs target these

51 receptors.

Here we describe our work with a time-resolved fluorescence technique, pulsed- interleaved excitation fluorescence cross-correlation spectroscopy (PIE-FCCS), to study opsin oligomerization in a live cell membrane. PIE-FCCS translates fluctuations in fluorescence signal (arising mainly from diffusion) into information about a protein’s mobility and concentration. With PIE-FCCS it is possible to measure correlated movements of proteins such that the population of stable complexes can be quantified with high accuracy. Here we observed that opsin, a prototypical GPCR, is organized into dimers.

33 At low concentrations we found a linear increase of the dimer population with the square of monomer concentration from which we obtained an equilibrium constant for the dimerization reaction.

Rhodopsin (opsin + 11-cis-retinal) is the light sensitive protein at the heart of scotopic vision and the first GPCR to be crystallized and structurally resolved.52-53 In retina, rhodopsin is highly concentrated in rod cell outer segment (ROS) membranes (~24,000 molecules/μm2).54 Early experiments indicated that it was rotationally and translationally mobile in those membranes,55-56 which led to the conclusion that rhodopsin is monomeric.

In support of this conclusion, single protein activity assays showed that monomeric rhodopsin could enable signal transduction.57-58 Alternatively, there is a large body of biophysical work showing that rhodopsin is dimerized in native membranes. Evidence for rhodopsin dimers ranges from detergent-stabilized complexes to optical imaging and atomic force microscopy of isolated ROS membranes.7, 59-60 Still lacking from this work is a full characterization of the thermodynamics of opsin dimerization in native membranes.

Our solution to this problem is a time-resolved fluorescence technique, PIE-

FCCS,61 which quantifies the population of receptors that co-diffuse as homo-oligomers, while simultaneously quantifying the total population of receptors. This live-cell compatible technique has been used to resolve the mechanism of epidermal growth factor activation and inhibition,62 as well as the organizational principles affecting lipid-anchored proteins.63 One advantage of PIE-FCCS is that it relies on receptors diffusing in and out of a small area defined by a laser focus. This makes it possible to measure the mobility of the receptors at higher densities and with a sampling rate superior to single molecule tracking.

34 It also serves as a spatiotemporal filter, which excludes large immobile aggregates and internal organelles from the analysis. This removes some of the artifacts that can result in over-estimation of the dimer fraction by methods based on resonant energy transfer.

Figure 3.1. PIE-FCCS Schematic. (A) An epi-fluorescence image of an opsin-eGFP- expressing Cos-7 cell is merged with an image of fluorescence excited by the laser used for PIE-FCCS (scale bar = 5 μm). The arrow is points to the laser illumination area shown in green, which has a radius of ~220 nm. (B) Several possible diffusing species are diagrammed to show their respective contributions to the total fluorescence signal. The red/green dimer diffusing through the laser focus leads to a spike of intensity in the 520 and 612 nm detector channels. Green monomers or dimers show a spike of intensity in the

35 green channel proportional to the number of receptors, as well as some intensity in the red channel. This spectral bleed-through is removed with PIE using the time gating shown in panels D and F. Red monomers and dimers display essentially no bleed-through to the 520 nm detector. (C) Schematic showing that the laser excites fluorescence in the basal and apical membranes of Cos-7 cells, and that on average there are many receptors diffusing in and out of the laser focus. (D) Pulse diagram showing the interleaving of the 488 and 561 nm lasers. Each photon detection event is time-tagged to a sync pulse (from laser system), which allows for the assignment of that photon to either 488 nm or 561 nm excitation. (E)

For a sample with more than one fluorescent species, multiple overlapping diffusion events cause the fluctuations, but the correlation analysis described in the Experimental Section can quantify the concentration and mobility of the molecules in the signal. (F) A lifetime histogram shows the number of photon detection events occurring at each value of δτ. This information is used to select the time gates for the red and green species (Gates A and B), and rejects photons arising from spectral bleed-through or cross-talk from the correlation analysis.

RESULTS AND DISCUSSION

In this study we measured opsin oligomerization in a live cell membrane under physiological conditions. Because of the high density of opsin in native ROS membranes, we expressed the receptor in cultured COS-7 cells. This cellular environment served as a native-like membrane system, where the density of the receptor can be passively varied through transient transfection. For data shown here we observed opsin at expression densities ranging from 100-2000 molecules/μm2.

36 The apparatus used for PIE-FCCS experiments is described in detail in the experimental section. It essentially consisted of dual-laser point excitation and dual-band confocal detection with single photon avalanche photodiodes. The laser system was a white-light picosecond-pulsed fiber laser, from which two narrow bands were selected (488

± 2 nm and 561 ± 2 nm) and temporally separated by a fixed fiber delay. The temporal offset interleaves the two pulse trains in time so that any fluorophore excited by one pulse

(e.g. 488 nm) decays before the next pulse arrives (e.g. 561 nm). This strategy sorts the photons into four data channels: the product of two time gates and two color channels (See

Figure 3.1).

Figure 3.2. Representative FCCS Data. FCCS data are shown for (A) Src16-GCN4, (B)

Src16, and (C) opsin expressed in Cos-7 cells. In each plot, colored dots are the measured data points, whereas the solid black lines indicate the fitted functions (defined in the

Experimental Section). Red dots are the FCS data for the mCherry fusion protein, (), green dots are the FCS data for the eGFP fusion, (), and blues dots are the FCCS data, 37 (). Amplitude data reports directly on the concentration of diffusing species through

the relationship: (0) = 1⁄〈〉, and is used to calculate fc as shown in equation 1. In each

plot, a horizontal dashed line marks the zero value for comparison with the cross- correlation amplitude, (0).

In PIE-FCCS, photons arriving during the 488 nm pulse time gate and the green

(520/44 nm) color channel were used to calculate the green (eGFP) autocorrelation curve,

whereas photons arriving during the 561 nm pulse time gate and the red (612/69 nm) color

channel were used to calculate the red (mCherry) autocorrelation curve. The same data

were used to calculate the cross-correlation spectrum, resulting in freedom from cross-talk

(488 nm light exciting mCherry) and spectral bleed-through (eGFP emission in the red

62 channel).

Example PIE-FCCS data is shown for three dual-expression constructs. The first

(Figure 3.2 A) is a lipid-anchored peptide derived from cSrc fused to the GCN4 α-helical

64 dimerization motif and a C-terminal eGFP or mCherry fluorescent protein, Src16-GCN4-

eGFP/mCherry). The second (Figure 3.2 B) is the cSrc derived peptide fused directly to

65 the fluorescent protein, Src16-eGFP/mCherry. The Src16 and Src16-GCN4 constructs were

identical to those used in a previous publication where they served as a negative and

positive control, respectively, for cross-correlation in the experiment (named Myr-FP and

62 Myr-GCN4-ICM in reference 30). The fact that we found zero cross-correlation for Src16

demonstrates that PIE effectively removed artifacts that would have led to false-positive

cross-correlation and that the fluorescent proteins themselves did not drive dimerization.

The Src16-GCN4 data show the upper limit for a strongly dimerized system due to protein

dark states66 and the presence of dimers with identical fluorescent protein tags (see Fig 3.1

38 B). Finally, Figure 3.2 C shows example PIE-FCCS data for opsin with C-terminal eGFP or mCherry.

To quantify the mobility and clustering of opsin compared to the control proteins,

PIE-FCCS data were fit to a simple 2D diffusion model (see Experimental Section).

Autocorrelation spectra were fit to a single component diffusion model with triplet relaxation. Cross-correlation spectra were fit to a single diffusing species model without triplet relaxation. Meaningful parameters obtained from these fits were (i) the number of diffusing species in the laser focus, (ii) the fraction of molecules diffusing as a complex, and (iii) the mobility of the receptors. Each of these parameters is discussed below.

Fluorescence correlation spectra at early time points are inversely proportional to the number of diffusing species in the laser focus (() = 1⁄〈〉). The fraction of receptors incorporated into clusters, , was calculated by taking the ratio of the number of red or

62, 67-68 green diffusing species and the number of co-diffusing species :

Calculated in this way, fc represents the fraction of receptors labeled with eGFP that co- diffuse with receptors labeled with mCherry (or vice versa).

Figure 3.3. Summary of Cross-Correlation Data. (A) The fc value for each individual cell is plotted on the vertical axis and grouped by protein type. The spread in the horizontal dimension is proportional to the number of cells within 0.05 intervals of fc. Numbers in parentheses at the top of the graph are the total number of data points or unique cells measured for each construct. The red line indicates the mean value of the distribution. (B)

Box and whisker plots are shown for the identical data points in panel A. The red line is the median value. The blue boxes enclose the 25-75% percentile values and the notches indicate the range over which two distributions are different to the 5% confidence level.

Whiskers enclose the most extreme points not considered outliers and outliers are marked in red.

40 To characterize the extent of oligomerization for each construct, we measured

multiple cells in four (or more) independent experiments. Figure 3.2 summarizes the results

of these measurements by plotting fc values along the vertical axis and spreading the values

along the x-axis in vertical bin values of 0.05. The Src16-GCN4 data showed a median fc

value of 0.23 and a mean of 0.25 ± 0.10. The spread in fc values reflects cell-to cell

variability and weak density dependence at low concentrations. The mean fc of 0.25 is the

maximum correlation one would expect based on the large dark state population of

mCherry66 and the statistics of dimerization between eGFP and mCherry labeled proteins,

62, 66 eGFP/eGFP : eGFP/mCherry : mCherry/mCherry (1:2:1). The Src16 data showed fc

values that were tightly clustered near 0, with a median value of 0.016 and a mean of 0.025

62 ± 0.022, consistent with previous measurements.

For the opsin protein, 79 individual cells were measured and the resulting fc values

are shown in Figure 3.2. Over 90% of the cells displayed non-zero cross-correlation ( >

0.05), indicating that opsin is significantly distributed into oligomers. The values of fc were spread over a wide range with a median value of 0.10 and a mean/standard deviation (� ±

) of 0.12 ± 0.08. The mean fc value was half that of the positive control indicating

significant yet incomplete oligomerization. The spread in fc values for opsin reflects cell-

to cell variability as well as a density dependence that will be addressed below.

We also measured the cross-correlation of opsin with another class-A GPCR, the

dopamine D2 receptor (D2R). Opsin and dopamine receptors play disparate physiological

roles, but share structural similarities that could potentially lead to clustering in the plasma

membrane. Testing for specificity is one way to determine if opsin oligomerization is

41 specific for homo-oligomerization or if it is a non-specific property of GPCR’s. The distribution of cross-correlation for the opsin-D2R expressing cells in Figure 3.3 indicated that opsin-D2R oligomers were much less prevalent than opsin-opsin oligomers. The distribution of fc values was similar to the Src16 monomer, but with a median value of 0.035 and a mean/standard deviation of 0.054 ± 0.054. This provides evidence that opsin homodimerization is specific and suggests that opsin oligomers are not passively formed by structural features shared with other Class A GPCRs.

The time decay of the correlation spectra reports directly on the mobility of the receptors and is sensitive to protein cluster size. Mobility alone cannot unambiguously distinguish oligomer size due to the unresolved relationship between protein size, oligomer state, and mobility in plasma membranes.69-72 However, the diffusion coefficient can be extracted from the data for comparison among the proteins studied here and with previous literature values. To quantify mobility, we related the diffusion coefficient to the decay time of the FCS curves, , and the radius, 0, of the lasers at the focus through the following equation.

2 � 0 = 4

Because there are likely to be other contributions to protein mobility besides pure

Brownian motion, we refer to this as the effective diffusion coefficient, . In Figure

3.4, was calculated from the green autocorrelation data. The Src16 diffusion coefficient was nearly as high as that for free lipids in the plasma membrane,73 consistent with a protein anchored to the membrane by a single acyl chain. The Src16-GCN4 construct

42 showed a much smaller diffusion coefficient, consistent with a dimer complex with a large effective radius in the membrane. Opsin diffusion was similar to the positive control and

74-75 comparable to that of other GPCRs, and the average = 0.38 ± 0.15 for opsin is consistent with monomer and small oligomer diffusion.

Figure 3.4. Mobility. The effective diffusion coefficient, , is shown for each of the indicated GFP-labeled protein species. The diffusion coefficients were calculated from the fit as indicated in the text. The column height is the mean value averaged over the same cell data as in Figure 3.3. Error bars indicate standard deviations. The means and standard deviations are also printed above each of the columns for clarity.

43 One method to estimate the size of the opsin oligomers observed in the PIE-FCCS data is molecular brightness analysis. Molecular brightness quantifies the average number of photons emitted by each species as it enters and exits the laser focus. A similar method is the photon counting histogram, which has been used to estimate the size of other

GPCRs.74 FCS data encode this information as the ratio of the average number of molecules, , divided by the photon count rate, or counts per second (). We refer to this ratio as the molecular brightness, indicated by the symbol .

We conducted brightness experiments in GFP-only expressing cells. Cells were otherwise treated and measured identically to the PIE-FCCS experiments discussed above.

The FCS data is calculated and fit as described for the dual color experiments and the molecular brightness is calculated using the ratio above. In Figure 3.5 we see that the molecular brightness of Src16-eGFP proteins is slightly more than half of the brightness of the Src16-GCN4-eGFP proteins. The molecular brightness of opsin-eGFP is nearly identical to the monomer control, but with a larger spread in values indicative of a range of clustering. This is consistent with the distribution of fc values shown in Figure 3.3 and indicates that the opsin is found may be found as monomers and dimers, but higher order oligomers are not likely to be present.

Figure 3.5. Molecular Brightness. The molecular brightness for cells expressing Src16- eGFP, Src16-GCN4-eGFP, or Opsin-eGFP was calculated from single color FCS data as described in the text. Error bars indicate the standard deviation.

Another metric for determining the degree of opsin clustering is Förster resonance energy transfer (FRET). This has been used to quantify opsin dimerization in the past, and could potentially be a factor in the present experiments.60, 76 The data collected for the PIE-

FCCS analysis was recorded in a time-correlated single photon counting mode, so we could also construct lifetime histograms as described in Figure 3.1. In this way we experimentally measure the fluorescent lifetime of each protein construct. Fluorescent lifetimes are sensitive to the probe environment and are good indicators of resonant energy transfer, i.e.

FRET. The eGFP and mCherry fluorophore labels in this study are not an ideal FRET pair, but have been used in for past FRET analyses.77 Moreover, the lifetime FRET data serves as a as quality control test for the PIE-FCCS results. This is because strong FRET could

61 bias the FCCS data and the resulting fc values.

For the lifetime FRET analysis, we used the same photon data employed to calculate the PIE-FCCS data summarized in Figure 3.3. The lifetime histograms were

45 binned at 32 ps intervals and fit to a single exponential curve convolved with the instrument response function. The lifetime fit results are shown in Figure 3.6 A, where lifetime fit for each of the five, 15 s measurements made per cell is displayed. The average lifetime of eGFP in cells expressing only Src16-eGFP was used as the 0 value in the following equation to estimate the FRET efficiency, .

= 1 − 0

Here, is the lifetime of the donor in the presence of the acceptor. Figure 3.6 B shows the average FRET efficiency for each of the constructs. The Src16 data shows a very low FRET efficiency, while the dimer shows only a small relative increase. This small

46 FRET value for Src16-GCN4 is likely due to the distance and orientation of the fluorophores in the dimer complex. This is because the fluorescent proteins are fused to the C-terminal tails of the EGFR kinase domain, which dimerize in a way that keeps the C-terminal labels several nanometers apart.62, 78 The opsin construct shows a modest FRET efficiency of 4.2

± 0.1%. (Here and in Figure 3.6, the error is reported as the standard error of the mean).

The low value of FRET efficiency for each of the constructs shows that resonant energy

61 transfer is not strongly influencing the PIE-FCCS data.

Figure 3.6. FRET Analysis. (A) Scatter plot of fluorescence lifetimes fit as described in the

text. Each data point is a 15 s measurement and each cell was measured five times. (B) Bar

graph of average FRET efficiency calculated from the lifetimes as described in the text.

Error bars indicate the standard errors of the mean.

47 The mobility, molecular brightness, and lifetime FRET data are consistent with opsin existing as monomers or small oligomers. From this, we hypothesize that under the conditions of these experiments, opsin in the plasma membrane is in a monomer-dimer equilibrium, with no resolvable population of higher order oligomers. To further test this hypothesis we returned to the cross-correlation data, where the distribution of fc values provides a statistical overview of the extent of opsin dimerization in the plasma membrane.

Buried in this analysis is the fact that for each cell measured, PIE-FCCS quantifies fc and the total number of diffusing species. If we posit a monomer-dimer equilibrium then the

PIE-FCCS data can be used to determine the concentration of monomer and dimer species in the membrane. The chemical reaction for dimerization can be written as:

+ ↔ ∙

The equilibrium constant for this reaction is then given by:

[ ∙ ] = []2

To determine Keq, we plotted the individual cell data as the product of the eGFP- and mCherry-labeled monomer concentrations versus the concentration of dimers (Figure

3.7). At sufficiently low receptor concentrations, each of the scatter plots showed a linear

68 trend, consistent with a monomer-dimer equilibrium.

Figure 3.7. Dimerization Equilibrium Constants. Protein concentrations, Ci, were obtained from the model fits to the FCS data and the area of the laser focus (see SI). At low concentrations, plots reveal a linear increase in the dimeric species concentration, CX, versus the product of the monomer species, CR and CG. The slope provides the equilibrium coefficient for each dimerization reaction.

49 As seen in Figure 3.7, the dimer concentrations of opsin and Src16 increased linearly up to 40,000 molecules2/μm4 or 200 molecules/μm2. This linear relationship is consistent with our model and is evidence that opsin clustering is dominated by dimerization and not higher order clustering in this range of concentrations. At higher concentrations the data were more scattered, indicative of either more complex diffusional behavior or larger noise in the FCCS measurements. For opsin, a linear fit to the data in Figure 3.7 gave a slope of

9.94 ± 0.53 x 10-4 (molecules/μm2)-1. Under the assumptions of the simple model above, the slope is equal to Keq for the dimerization reaction. The Keq value for opsin then could be compared to that of the monomer control, Src16. Over the same range, the Src16 data were fit to a line with a slope of 1.08 ± 0.19 x 10-4 (molecules/μm2)-1, approximately one order of magnitude lower than that of opsin.

The Keq for dimerization to our knowledge has only been reported for one other

GPCR, the N-formyl peptide receptor (FPR). Using single molecule imaging at low receptor concentrations (< 2.6 molecules/μm2), the authors report a 2-dimensional dimer dissociation constant of 3.6 molecules/μm2.79 This is more than 250 times smaller than the

2 dissociation constant we measure for opsin (2D-KD = 1/Keq = 1,010 molecules/μm ). This likely indicates a substantially different affinity for dimerization of these two receptors, but further work is needed to directly compare the two methods.

50 CONCLUSIONS

To understand the implications of the Keq obtained from this analysis, it is useful to consider the fraction of proteins found in dimers at various concentrations in the membrane. First, based on the fit Keq value above, the fraction of opsin proteins found in dimeric complexes would be 50% at a total opsin concentration of 1,006 molecules/μm2.

This is consistent with the opsin fc distribution in Figure 3.3, which had a mean value half that of the positive control and was taken at a concentration range centered at 1,000 molecules/μm2. At much higher concentrations, similar to those of rhodopsin found in ROS membrane disks (~24,000 molecules/μm2), 87% of the total protein population would be found in a dimeric complex.

Within ROS membranes it is possible that further oligomerization of rhodopsin dimers could occur.59, 80 There is also the possibility that the intradiscal domains of two rhodopsin molecules located on two facing layers of membrane on the same ROS disc could provide an additional stabilizing force, leading to further immobilization and self- aggregation of this receptor.54 These organizational features could be essential for development of ROS structure. At the other end of this multi-stage equilibrium, a modest dimerization Keq would allow the rhodopsin monomer to also be present in appreciable amounts.

We have shown that PIE-FCCS can resolve the concentration of dimeric opsin in the plasma membranes of live cells. From these results we calculated the equilibrium constant for opsin dimerization, which to date has not been reported. Our results show that

PIE-FCCS provides a powerful platform to quantify membrane protein mobility and

51 clustering. The method could greatly impact future studies of membrane receptor clustering, which is increasingly thought to influence cell communication.

EXPERIMENTAL SECTION

PIE-FCCS INSTRUMENT

Fluorescence imaging and spectroscopy measurements were made with a customized inverted microscope (Nikon Eclipse Ti, Toyko, Japan). For laser excitation we used the output of a continuum white light laser (SuperK NKT Photonics, Birkerod,

Denmark) operating at 9.7 MHz with an internal pulse picker. Two excitation beams were selected from the parent continuum beam with bandpass filters and then cleaned up with narrowband filters. The blue beam passed through a 488 nm filter with a 1.9 nm full width half max (FWHM) bandwidth (LL01-488-12.5, Semrock, Rochester, NY) whereas the green beam passed through a 561 nm filter with a 2.1 FWHM bandwidth (LL02-561-12.5,

Semrock, Rochester, NY). For optimal mode overlap each beam was coupled to an identical core single mode optical fiber (QPMJ-3AF3U-488-3.5/125-3AS-18-1-SP and

QPMJ-3AF3U-488-3.5/125-3AS-3-1-SP, OZ Optics, Ottawa, Ontario). The beams passed through fibers of different lengths (18 m for α488 and 3 m for α561), to introduce a 50 ns delay between the two pulse trains for pulsed interleaved excitation (PIE). The two beams exited their respective fibers with identical coupling lenses and were overlapped with a 503 nm cut-off dichroic beam splitter (LM01-503-25, Semrock, Rochester, NY). The combined beam was then fed into the microscope using a laser filter cube (91032, Chroma

Technology Corp. Bellows Falls, VT) with a two-color dichroic mirror and laser blocking filter (zt488/561rpc and zet488/561m, Chroma Technology Corp. Bellows Falls, VT). A

52 100X TIRF objective, NA 1.49, (Nikon Corp., Tokyo, Japan) was used to focus the excitation light on the sample and collect the emitted fluorescence.

For time-correlated single photon counting, we employed a custom-built confocal detection unit with a 50 μm confocal pinhole (Thorlabs, Newton, NJ) placed at one of the output ports of the microscope. Light passing through the pinhole was collimated and then split with a 560 nm long-pass beam splitter (FF560-FDi01-25x36, Semrock, Rochester,

NY). Each beam then was focused to a single photon avalanche diode (SPAD) with a 50

μm active area, 30 ps timing resolution and 25 dark counts per second (Micro Photon

Devices, Bolzano, Italy). The red beam passed through a 612/69 nm filter (FF01-621/69-

25, Semrock, Rochester, NY) and the green beam passed through a 520/44 nm filter (FF01-

520/44-25, Semrock, Rochester, NY). The data were recorded with a four-channel-routed time-correlated single photon counting (TCSPC) device. (Picoharp 300, PicoQuant, Berlin,

Germany).

To ensure maximal overlap between the 520 and 612 nm detection volumes, we regularly measured the cross-correlation of a 41 base pair DNA oligonucleotide with a

TAMRA dye on the 5’ end and a 6-FAM dye on the 3’ end. With this control we measured an fc of 0.80.

CELL CULTURE AND TRANSFECTION

Mammalian cell culture and transfection was carried out with standard protocols.

COS-7 cells were cultured in Dulbecco’s Modified Eagle Medium (DMEM 1X +

GlutaMAX, Life Technologies, Grand Island, NY ) supplemented with 10% fetal bovine serum (FBS, Life Technologies) and 1% penicillin/streptomycin (BioReagent, Sigma

53 Aldrich). Cells were grown in 100 x 20 mm petri dishes and split when they reached ~95% confluency. Cells were passaged up to 7 times. Two to three days prior to imaging, cells were seeded into 35 x 10 mm uncoated glass bottom dishes with #1 coverslips (MatTek) and grown to 70-90% confluency before transfection. Cells were transfected 1 day prior to imaging with the Lipofectamine 2000 transfection reagent (Life Technologies) following the supplier’s protocols. Media for transfected cells was changed from DMEM to Opti-MEM I media without phenol red (Life Technologies) prior to imaging.

PLASMIDS

The Src16-eGFP/mCherry and Src16-GCN4-eGFP/mCherry plasmids provided by

Jay T. Groves (UC Berkeley) have been described previously.62-63 The plasmid for the dopamine D2R measurements, pcDNA-D2s-L-Venus, was obtained from Addgene

(Cambridge, MA) and used without modification. For construction of opsin-EGFP and opsin-mCherry, mouse opsin cDNA was amplified by PCR and EcoR1 and BamH1 restriction sites were introduced at the 5’- and 3’-ends, respectively, by using the following primers: for the opsin-EGFP construct, forward primer:

GTGGGGAATTCGCCATGAACGGCACAGAGGG and reverse primer:

TCTGGGGATCCGGCTGGAGCCACCTGG; for opsin-mCherry construct: forward primer: GTGGGGAATTCGCCATGAACGGCACAGAGGG and reverse primer:

TCTGGGGATCCCGGGCTGGAGCCACCTGG. Amplified DNA was cloned into pEGFP-N3 and pmCherry-N1 original vectors (Clontech, Mountain View, CA), respectively. The functional relevance of these fluorescent protein fusion constructs was

60, 76 demonstrated in previous work.

54 DATA COLLECTION AND ANALYSIS

Measurements were made on live cells maintained at 37 ˚C in a stage-top incubator

(Chamlide IC, Quorum Technologies, Guelph, Ontario). For each measurement, laser powers were set to 800 nW (488 nm) and 1 nW (561 nm), measured before the light entered the microscope light path. During imaging, cells with similar expression levels of mCherry and eGFP fluorescence were selected and TCSPC data were collected at 5 x 15 s intervals for each cell.

The TCSPC data were processed by constructing a fluorescence intensity plot that contained the number of photons detected in sequential 10 ns bins. Data were time-gated to include only photons collected within 0.2 ns before and 70 ns after the 488 nm laser pulse arrival time for () and 0.2 ns before and 30 ns after the 561 nm laser pulse arrival time for (). The autocorrelation curves were then calculated with a multiple tau algorithm used in previous publications,62-63 that is numerically equivalent to the following expression: 〈() ∙ ( + )〉

() = 2 〈 ()〉

where, is the fluctuation of away from the average value, and i is either G or R. The cross-correlation curve was calculated in a similar way, namely:

〈 () ∙ ( + )〉 () = 〈 ()〉 ∙ 〈 ()〉

Prior to fitting the FCS data, individual 15 s autocorrelation curves were averaged together. Any curves showing large amplitude decays with decay times longer than 1 s

55 were assumed to reflect large vesicles or other immobile aggregates and thus were excluded from the data fitting calculation.

The autocorrelation curves were fit to a single component two-dimensional diffusion model with triplet relaxation:

1 1 − + −⁄ 1 () = ∙ ∙ 〈 〉 1 − 1 + �

where represents the number of diffusing species with fluorophore i (monomers + dimers), F is the fraction of molecules in the triplet state, is the triplet relaxation time, and is the dwell time of molecules in the laser focus. The gamma factor typically used to account for the Gaussian shape of the detection volume is assumed to be 1. This cancels out in for the calculation of fc values, but may lead to a slightly lower Keq. The cross- correlation curve showed no sign of triplet relaxation and thus was fit to the following equation:

1 (0) ∙ () = 1 + �

To calculate the concentration of red-labeled monomers (CR), green-labeled monomers (CG), and red/green-labeled dimers (CX), we used parameters from the fit functions and the area of the laser focus in the membrane. The number of red/green-labeled

81 dimers was calculated from :

(0) = (0) ∙ (0)

56 The number of red- and green-labeled monomers, and , was obtained by subtracting from or , respectively. Concentrations were calculated by dividing

the number of monomers or dimers by the corresponding area of the laser focus (0.332 μm2

2 for CR and 0.304 μm for CG and CX).

CHAPTER 4

A G PROTEIN-COUPLED RECEPTOR DIMERIZATION INTERFACE IN HUMAN

CONE OPSINS

INTRODUCTION

The spatial organization of cell surface receptors plays a major role in biological function. Organization can occur over a range of length scales, from the ligand-activated dimerization of growth factor receptors to micron-scale clusters of T-cell receptors during an immune response.82-83 G protein-coupled receptors (GPCRs) are a large family of membrane proteins for which the general rules governing spatial organization have remained elusive. Long considered to act as monomers during activation, class A GPCRs have recently been investigated for their potential to form dimers or oligomers. However, answers to this line of inquiry have remained elusive because of the difficulty in identifying dimeric complexes in the heterogeneous environment of the plasma membrane,48-50 as well as linking dimerization to functional outcomes. Thus, more information is needed about the structure, stability, and function of GPCR dimerization.

Efforts have been made to characterize the dimerization interface for class A

GPCR’s. Many of these studies are based on crystal packing geometries84-88 and structural modeling,89-92 whereas others have included methods such as peptide disruption93-98 and

Cys residue cross-linking.76, 99-102 But only a limited number of studies have reported site- specific mutagenesis that disrupted hypothetical dimer contact regions in human

58 GPCRs,103-108 all of which relied on FRET or BRET (Förster or bioluminescence resonance energy transfer) as the principle probe for dimerization. For instance, the 5-HT1A serotonin receptor was investigated with FRET, where it was shown that the wild type (WT) receptor is dimeric and that mutations in transmembrane (TM) helices 4 and 5 (TM4/5) disrupted dimerization.104 The M3 muscarinic receptor was probed with a BRET saturation assay after introducing successive point mutations into seventy lipid-facing amino acids.105 Many of these mutants decreased the BRET signal, and TM5 was found to be particularly important. However, in many of these studies, the point mutants did not eliminate energy transfer completely, which was interpreted as evidence for higher order oligomers and multiple dimerization interfaces.103-107 The difficulty with BRET and FRET studies is that they can be overly sensitive to weak and transient interactions, and potentially overestimate the extent of dimerization. This interpretation was supported by data from several assays that are sensitive to dimer lifetimes.109-111 For example, FRAP microscopy of the β1 adrenergic receptor indicated that it forms only transient interactions.109 Single molecule tracking of the M1 muscarinic receptor revealed that dimers are relatively short-lived.110

An in situ affinity assay showed that the dopamine receptor D2 is not co-recruited as a homo-oligomer, despite reports of high FRET that were originally posited as evidence for dimerization.111 Such conflicting observations have severely complicated the field of

GPCR dimerization, leading to multiple reports for and against the significance of this

112-115 process even for the same receptor.

This lack of clarity from previous work on GPCR dimerization can be resolved by combining methods that are both sensitive to receptor dimerization and that distinguish

59 transient collisions from stable dimeric complexes. Here we investigated the dimerization of visual cone opsins with time-resolved fluorescence assays, an approach that allowed us to simultaneously measure receptor concentration, mobility, and dimerization. We used two related techniques to quantify these properties: fluorescence correlation spectroscopy

(FCS) and pulsed-interleaved excitation fluorescence cross-correlation spectroscopy (PIE-

FCCS). Data were collected within small regions of a live cell plasma membrane; where the proteins are translationally mobile. Dimerization was measured in several ways. (i) By molecular brightness, defined as the average rate that photons are emitted from diffusing complexes. For receptors labeled with a fluorescent protein, dimeric species contain two fluorescent proteins (one fused to each receptor) and thus emit twice as many photons as monomeric receptors. (ii) Dimeric complexes also exhibit reduced mobility relative to monomeric receptors, revealed as a decrease in their effective diffusion coefficients. (iii)

In two-color experiments, the lifetime of the donor fluorescent protein (eGFP) is sensitive to acceptor (mCherry)-labeled receptors in close proximity. Thus, fluorescence lifetimes were used to calculate FRET efficiencies, indicative of dimerization. (iv) PIE-FCCS can also be used to measure the population of receptors that undergo co-diffusion, a signature of stable dimerization. PIE-FCCS is exquisitely sensitive to pairs of receptors (one with eGFP and one with mCherry) stably diffusing together.

Here we investigated the dimerization of human visual cone opsins, which we refer to as red, green, and blue (corresponding to genes OPN1LW, OPN1MW, and OPN1SW, respectively). Cone opsins endow humans with trichromatic vision and comprise the basis of daytime image formation. They share a high degree of sequence similarity with rhodopsin (~40%),116 the most abundant photoreceptor pigment responsible for night and

60 peripheral vision. Rhodopsin has long served as a prototype for GPCR studies, and was the first GPCR to be structurally resolved with X-ray crystallography.52 Evidence for rhodopsin dimerization includes atomic force microscopy (AFM) of isolated outer membrane disks,59 association assays in reconstituted liposomes,60 purification of dimeric rhodopsin imaged by transmission electron microscopy,80 and cryoelectron tomography of sectioned rod cells.117 Recently, we reported a live-cell PIE-FCCS study in which dimerization of retinal-free rod opsin was found to be density-dependent at 10-100 times lower concentrations than in retinal membranes.45 This result suggests that though the affinity is relatively modest, it leads to a dominantly dimeric receptor at high densities.

Although no point mutations have been reported that disrupt rhodopsin dimerization, recent work indicates that synthetic TM peptides mimicking TM4/5 and TM1/2 can disrupt dimerization.93 This finding is also consistent with crystal packing analysis and modeling

118 of the AFM data indicating two dimerization interfaces for rhodopsin.

Here we sought to elucidate dimerization in human cone opsins, which share ~40% sequence homology with rhodopsin.119 No quantitative biophysical study of human cone opsin dimerization has yet been reported. A recent study of murine S-opsin reported co- trafficking with R-opsin, suggesting that it dimerizes with rhodopsin in a mouse model.120

Another study noted blue cone opsin aggregation due to a Phe-rich region in this receptor,121 but the aggregated protein was located in the ER and trans-Golgi network instead of the plasma membrane. Using the approach outlined above, we found that red cone opsin was significantly dimerized, and that the average cross-correlation was higher than that of rhodopsin. Neither blue nor green cone opsin showed significant homodimerization in the plasma membrane. Using site-directed mutagenesis, we identified

61 amino acid residues in TM5 that disrupted dimerization of red cone opsin, but induced dimerization of green cone opsin. The same mutations also were responsible for the spectral shift between these two opsins, suggesting their possible functional role in cone opsin dimerization.

MATERIALS AND METHODS

DNA CONSTRUCTS AND PRIMERS

Human blue, green and red cone opsin cDNAs cloned into the pUC57 vector were synthesized and obtained from Genentech (San Francisco, CA). The last 14 amino acids in blue cone opsin and the last 12 amino acids in green and red cone opsins were replaced by a 1D4 tag, a TETSQVAPA amino acid sequence comprising the last 9 amino acids of rod opsin. For construction of cone opsin-eGFP and cone opsin-mCherry, cDNAs of human blue, green and red cone opsins were amplified by PCR. EcoR1 and Sac2 restriction sites were then introduced at the 5′- and 3′- ends, with the following primers: for the cone opsin- eGFP construct, forward primer GTGGGGAATTCGCCATGAAGACCATCATCGCCCT and reverse primer TCTGGCCGCGGTGGCTGGAGCGACCTGA; for the cone opsin- mCherry construct, forward primer

GTGGGGAATTCGCCATGAAGACCATCATCGCCCT and reverse primer

TCTGGCCGCGGGGCTGGAGCGACCTGA. The resulting amplified DNA was then cloned into the peGFP-N3 and pmCherry-N1 original vectors (Clontech, Mountain View,

CA).

Green cone opsin T230I, S233A, V236M (green-IAM) and red cone opsin I230T,

A233S, M236V (red-TSV) were constructed with Phusion high-fidelity DNA polymerase

(New England Biolabs, Ipswich, MA) using a standard protocol.122 These constructs were 62 then used for PIE-FCCS experiments.

Additionally, a 1D4 tag was added at the C-terminus of eGFP in the cone opsin- eGFP constructs. These constructs then were used to test the expression levels of cone opsins following their transfection into HEK-293 cells, as well as for protein purification and ultraviolet-visible (UV-Vis) spectroscopy experiments.

WT green, red, green-IAM, and red-TSV were also subcloned into a pcDNA3.1(+) vector following a standard protocol,122 and the resulting constructs were used for protein purification and UV-Vis spectroscopy experiments. The composition of each construct was confirmed by DNA sequencing.

COS-7 CELL CULTURES AND DATA COLLECTION

Cos-7 cells were cultured in Dulbecco’s modified Eagle’s medium (DMEM 1X +

GlutaMAX, Life Technologies, Carlsbad, CA) at ~106 cells/ml and 37 °C. Both 10% fetal bovine serum (FBS, Life Technologies) and 1% penicillin/streptomycin (BioReagent,

Sigma-Aldrich, St. Louis, MO) were added to the media. Cells grown on 100 X 20 mm tissue culture plates (Falcon, Corning Inc., Corning NY) at 37 °C were split when their confluency reached ~80-90%. Two to three days prior to imaging, cells were removed from the 100 X 20 mm plates and transferred to 35 X 10 mm gamma-irradiated glass bottom culture dishes (MatTek, Ashland, MA). Cells then were transfected 24 h prior to imaging by using Opti-MEM I media with reduced phenol red and Lipofectamine 2000 transfection reagent (Life Technologies) according to the supplied protocols. On the day of imaging, the media was changed from DMEM to Opti-MEM I media without phenol red (Life

Technologies) at least 30 min prior to imaging.

63 FLUORESCENCE CORRELATION SPECTROSCOPY (FCS)

FCS was conducted with a custom-modified Eclipse Ti inverted microscope (Nikon

Instruments, Tokyo, Japan) described in previous publications.45-47 The 488 nm laser was selected and filtered (LL01-488-12.5, Semrock, Rochester, NY) from a supercontinuum fiber laser with 5 ps pulse duration and 10 MHz repetition rate (SuperK NKT Photonics,

Birkerød, Denmark). At the microscope, a dichroic beam splitter directed the 488 nm beam to the sample (zt488/561rpc, Chroma Technology Corp. Bellows Falls, VT). The fluorescence signal collected by the objective passed through a laser-blocking filter to remove scattered laser light (zet488/561m, Chroma Technology Corp.). The signal was then directed to a camera port at the side of the microscope where it was focused through a 50 μm confocal pinhole onto a bandpass-filtered SPAD detector (Micro Photon Devices,

Bolzano, Italy). The time-correlated single photon data was recorded with a four-channeled routed time-correlated single-photon counting (TCSPC) device (Picoharp 300, PicoQuant,

Berlin, Germany) at a timing resolution of 32 ps. TCSPC files were processed as described previously to produce the fluorescence correlation curves and fluorescence lifetime

45-46 histograms.

PULSED-INTERLEAVED EXCITATION FLUORESCENCE CROSS-CORRELATION

SPECTROSCOPY (PIE-FCCS)

PIE-FCCS was carried out on the same instrument as above, with a 561 nm laser excitation beam selected from the supercontinuum laser and delayed ~50 ns with respect to the 488 nm pulses (LL02-561-12.5, Semrock, Rochester, NY). The same dichroic and laser blocking filter was used for two-color excitation. The fluorescence signal emitting from eGFP and mCherry was split with a long-pass filter (FF560-FDi01-25x36, Semrock) 64 after passing through a confocal pinhole. A second SPAD detector collected the long wavelength portion of the signal after passing through a bandpass filter (FF01-621/69-25,

Semrock). The TCSPC files were used to construct FCS and FCCS data after time-gating the fluorescence signal. Only photons arriving within 50 ns after the 488 pulse in the

‘green’ detector, and within 50 ns after the 561 nm pulse in the ‘red’ detector were used to construct the time-dependent fluorescence signals ( () and (), respectively). The

45-47 correlation spectra were calculated, fit, and analyzed as previously described.

LIFTETIME FITTING

To measure the fluorescence lifetimes of the various eGFP fusion constructs, we constructed lifetime histograms from the time-correlated single photon counting data collected in the FCS and PIE-FCCS studies. Thus, we only report lifetime measurements for the same cells for which FCS or PIE-FCCS data are also provided. Photons were binned at 64 ps according to their arrival time relative to a synchronized pulse from the excitation laser. The lifetime was fit with a nonlinear least squares routine in MatLab after deconvolution with an instrument response function collected from a scattering sample taken on the same microscope under an identical optical setup. Data were then fit to a single component exponential decay function.

EXPRESSION OF CONE OPSINS IN HEK-293CELLS; PIGMENT

RECONSTITUTION AND PURIFICATION

HEK-293 cells were cultured in Dulbecco's modified Eagle medium (DMEM) with

10% FBS (Hyclone, Logan, UT), 5 µg/ml plasmocin (InvivoGen, San Diego, CA) and 1 unit/ml penicillin and 1 µg/ml streptomycin (Life Technologies) at 37 °C under 5% CO2.

65 Transient cell transfections were performed with polyethylenimine.123-124 Twenty-four hours post-transfection, cone opsins were reconstituted with either 11-cis-retinal or 9-cis- retinal. Retinal was delivered to the cell culture from a DMSO stock solution to a final concentration of 10 or 20 µM, for 11-cis-retinal and 9-cis-retinal, respectively, and then cells were incubated in the dark for 24 h at 37 °C with 5% CO2. Cells from fifteen 10 cm plates were harvested, centrifuged at 800 g and the pellet was suspended in 50 mM HEPES,

150 mM NaCl, 20 mM n-dodecyl-β-D-maltopyranoside (DDM), and protease inhibitor cocktail, pH 7.0, before being incubated for 1 h at 4 °C on a rotating platform. The lysate was centrifuged at 100,000 g for 1 h at 4 °C and cone opsins were purified from the supernatant with an anti-rhodopsin C-terminal 1D4 antibody immobilized on CNBr- activated agarose. Two hundred µl of 2 mg 1D4/ml agarose beads were added to the supernatant and incubated for 1 h at room temperature. The resin was then transferred to a column and washed with 10 ml of 50 mM HEPES, 150 mM NaCl, 2 mM DDM, pH 7.0.

Cone opsins were eluted with 150 mM HEPES, 150 mM NaCl, 2 mM DDM, pH 7.0, supplemented with 0.6 mg/ml of the TETSQVAPA peptide.

UV-VIS SPECTROSCOPY OF CONE OPSIN PIGMENTS

UV-visible spectra were recorded from freshly purified cone pigment samples. The absorption spectrum between 260 nm and 700 nm was initially recorded in the dark to calculate the concentrations of purified cone opsins. To obtain difference spectra of purified cone pigments, a baseline was recorded first on the sample in the dark and then measured following sample exposure to white light delivered from a Fiber-Light illuminator (150 W lamp) (Dolan-Jenner, Boxborough, MA) at a distance of 10 cm for 3 min. 66 CROSS-LINKING OF CONE OPSINS IN MEMBRANES

HEK-293 cells were transiently transfected with WT green, red, green-IAM, and red-TSV constructs cloned into the pcDNA3.1(+) vector. Forty-eight hours after transfection, cells from two 10 cm plates were harvested, washed with PBS and suspended in 200 µl of 20 mM Bis-Tris-propane, 100 mM NaCl buffer, pH 7.5, containing a protease inhibitor cocktail. After gentle trituration with syringe and needle, the membranous fraction was pelleted by centrifugation at 16,000 g for 10 min at 4 °C. The pellet was suspended in

200 µl of the Bis-Tris-propane buffer and half of the resulting solution was used for cross- linking. Two mM of disuccinimidyl glutarate (DSG) cross-linker (Thermo Scientific,

Waltham, MA) was added to membranous samples and the cross-linking reaction was allowed to proceed for 2 h on ice. The reaction was terminated with 1 M Tris-HCl, pH 8.0, added to a final concentration of 50 mM and the samples were incubated for 15 min followed by membrane solubilization with 20 mM DDM. Cross-linked opsins (50 µg of total protein extract) were separated on a 10% SDS-PAGE gel and then transferred to polyvinyl difluoride (PVDF) membranes. Proteins were detected with an anti-rhodopsin

C-terminal 1D4 antibody, an HRP-conjugated anti-immunoglobulin and a chemiluminescence assay (Thermo Scientific). The amount of opsin dimer was quantified by densitometry using ImageJ Software.

67 RESULTS

FLUORESCENCE CORRELATION SPECTROSCOPY OF HUMAN CONE OPSINS

We first created fluorescent protein (eGFP) fusions to the C-termini of three cone opsins, referred to here as red (OPN1LW), green (OPN1MW), and blue (OPN1SW). These fusions were then inserted into a vector plasmid for mammalian expression and transiently transfected into Cos-7 cells. Cos-7 cells, an immortalized cell line derived from African green monkey kidneys, were chosen mainly for their optimized geometry for optical imaging experiments. They express no endogenous visual opsins and are an ideal model system for investigating protein interactions in a native plasma membrane. We interrogated opsin-eGFP-expressing cells with FCS. In our instrument (Fig. 4.1 A), a focused laser is positioned near the edge of a live cell maintained at 37 °C. Single photons are recorded as they were emitted from fluorescent molecules diffusing in and out of a fixed region in space, defined by the excitation laser focus and confocal detection optics. The time- dependent intensity of the photon counts displays relatively large fluctuations that are indicative of single molecules diffusing in and out of the detection area (Fig. 4.1 B). These fluctuations have a characteristic size and time scale, which can be quantified by a time- time autocorrelation function (Fig. 4.1 C). Two key features of this correlation function are the decay time, , and the early-time amplitude, (0).

Figure 4.1. Schematic of FCS Data Collection and Analysis. (A) eGFP labeled GPCRs

diffuse in and out of the confocal area (radius = 210 nm) illuminated by a 488 nm laser.

Emission from the fluorescent proteins is collected by the objective and directed to a single

photon detector. (B) Photon counts are binned into evenly spaced time segments to produce

the time-varying fluorescence signal, F(t). (C) Fluctuations in the fluorescence intensity,

() = () − 〈()〉, are used to calculate a time-time autocorrelation function, () =

〈() ∙ ( + )〉⁄〈()〉2. The early time amplitude of G(τ) is used to obtain the

average population of diffusing particles, whereas the decay time is proportional to the

average dwell time of the particles in the confocal area. (D-E) Parameters extrapolated

from the fitted data are used to quantify the average molecular brightness (η) and effective

diffusion coefficient (Deff) for each cell (error bars are standard errors of the means).

69 The amplitude of the correlation function, (0), is proportional to the size of the intensity fluctuations and thus is inversely proportional to the average number of molecules in the laser focus, 〈〉. We obtained the local concentration by dividing 〈〉 by the diffraction-limited area (2), where is the beam radius. For the opsin-eGFP experiments, we observed cells with concentrations ranging from 80 to 2000 molecules/μm2. The concentration in this case refers to the number of diffusing species, not necessarily the number of opsin-eGFP proteins. To determine the dimerization state of the diffusing species, we took the average photon counts from a cell measurement and divided it by the average number of diffusing species, 〈〉. The result is referred to as molecular brightness (symbolized by η) and has units of photon counts per second per molecule (cpsm). Molecular brightness is proportional to the number of protomers in a diffusing species, i.e., a dimer is ideally twice as bright as a monomer. Average molecular brightness values for green and blue cone opsins were 451 ± 19 and 461 ± 25 cpsm (Fig.

4.1 D), consistent with monomeric lipid-anchored eGFP measured on the same instrument under similar conditions (errors reported here and below are standard errors of the mean).45-

46 For red cone opsin, the average molecular brightness was 738 ± 51 cpsm (Fig. 4.1 D), a value similar to that obtained from a dimer control protein consisting of a fluorescent protein fused to a leucine zipper dimerization motif and a lipid anchored peptide.45-46 Our brightness data indicate that red cone opsin is dimeric in the plasma membrane. The molecular brightness is not quite double the monomer brightness, which could indicate that the protein is distributed into a mixture of monomer, dimer, and oligomer states. The observed brightness is also affected by fluorescent proteins in the dark state, which are

125 reported to be over 20% in single particle counting studies of eGFP.

70 To further characterize the dimerization state of the cone opsins, we analyzed their mobility using the FCS data. The decay time of the FCS correlation function, is the average dwell time of a molecule in the detection area. The dwell time was converted to a

2 diffusion coefficient through the following equation: = ⁄4 , where is the calibrated radius of the detection area, 210 nm in our instrument. There have been reports of transmembrane proteins displaying complex diffusion behavior the cell plasma membrane.126-127 Nevertheless, our data fit well to the two-dimensional diffusion model, so we used this relationship and acknowledge that it is better thought of as an effective diffusion coefficient, . Diffusion coefficients are dependent on the size of the protein or protein complex, although the scaling laws for TM proteins are still under debate.71, 128

Single cell FCS measurements of red cone opsin displayed an average diffusion coefficient of 0.37 ± 0.03 μm2/s, whereas those of green and blue cone opsins were significantly larger,

0.56 ± 0.05 and 0.62 ± 0.04 μm2/s, respectively (Fig. 4.1 E). The lower diffusion coefficient of red cone opsin indicates a dimeric complex, consistent with conclusions drawn from the molecular brightness data.

PIE-FCCS DATA SHOW THAT HUMAN RED CONE OPSIN, BUT NOT BLUE OR

GREEN CONE OPSIN, IS SEGREGATED INTO DIMERIC STRUCTURES IN THE

PLASMA MEMBRANE

Both the mobility and brightness data from FCS measurements are consistent with red cone opsin diffusing as a dimer, and green and blue cone opsins diffusing as monomers.

We next turned to PIE-FCCS to further investigate the dimerization state of the visual cone opsins. PIE-FCCS is a variation of FCCS, which has been a powerful approach to

71 measuring molecular associations in live cells.81 The unique advantage of PIE-FCCS is that it separates individual excitation events in time such that each photon collected can be assigned to an excitation source (i.e., 488 nm light or 561 nm light).61 In this way, photons emitted by eGFP that pass to the red detector (i.e., spectral cross-talk) are eliminated from the calculation of the cross-correlation function. Fluorescent proteins have broad emission spectra, and spectral cross-talk leads to an uncorrectable overestimation of the cross- correlation function.62 This effect is especially true for membrane proteins, which diffuse more slowly and in a more complicated matrix than water soluble cytosolic proteins.

To conduct these experiments, we co-transfected Cos-7 cells to express cone opsin- eGFP and cone opsin-mCherry, and then measured them with a custom-built PIE-FCCS instrument (Fig. 4.2 A).45-46 In this instrument, 488 and 561 nm laser light was selected from a pulsed white light source and directed through fibers of different lengths before being focused at the same point within the sample. This configuration introduced a delay of ~50 ns such that individual photons arriving at the detectors could be assigned to an excitation source. Only photons arriving at the green detector within 50 ns of a 488 nm pulse and at the red detector within 50 ns of the 561 nm pulse were included in the time- dependent intensity traces (Fig. 4.2 B). Autocorrelation functions for the red and green channel were then calculated and fit to reveal the number of diffusing species labeled with an mCherry and an eGFP probe, respectively (Fig. 4.2 C, red and green dots). The autocorrelation functions for the eGFP and mCherry-labeled proteins showed a fast (~500

μs) and a slow (~40 ms) time component, which we ascribed to photophysical dynamics and 2D diffusion, respectively, as described in our previous publications.45-46 Variations in amplitude between the red and green autocorrelation functions reflect slight variations in

72 expression level (more single cell measurements are shown in Figs. S4.1-S4.3). A cross- correlation function was also calculated (Fig. 4.2 C, blue dots). The amplitude of the cross- correlation function is proportional to the number of diffusing species containing at least one mCherry and one eGFP probe. The cross-correlation function rigorously identifies the degree to which proteins are associated into stable dimeric complexes. Sample FCCS data sets are shown in the Supporting Information section, Fig. S4.1 (red cone opsin), Fig. S4.2

(green cone opsin), and Fig. S4.3 (blue cone opsin). The receptor densities in single cell measurements ranged from 65 to 2000 molecules/μm2.

Figure S4.1. FCCS Data for Red Cone Opsin. FCCS data are shown for nine representative single Cos-7 cells expressing human red cone opsin fusions to eGFP and mCherry. In each plot, the colored dots are the measured data points, whereas the solid black lines indicate the fitted functions (defined in the Material and Methods). Red dots are the FCS data for the mCherry fusion protein, GR (τ); green dots are the FCS data for the eGFP fusion, GG

73 (τ); and blue dots are the FCCS data, GX (τ). A horizontal dotted line marks the zero value in each plot. Amplitude data report directly on the concentration of diffusing species through the relationship: (0) = 1⁄〈〉 = 1⁄〈〉. The fraction correlated is calculated by comparing the relative amplitudes of the cross-correlation function and autocorrelation functions as described in the Materials and Methods.

Figure S4.2. FCCS Data for Green Cone Opsin. FCCS data are shown for nine representative single Cos-7 cells expressing human green cone opsin fusions to eGFP and mCherry. In each plot, the colored dots are the measured data points, whereas the solid black lines indicate the fitted functions (defined in the Material and Methods). Red dots are the FCS data for the mCherry fusion protein, GR (τ); green dots are the FCS data for the eGFP fusion, GG (τ); and blue dots are the FCCS data, GX (τ). A horizontal dotted line marks the zero value in each plot. Amplitude data report directly on the concentration of diffusing species through the relationship: (0) = 1⁄〈〉 = 1⁄〈〉. The fraction correlated is calculated by comparing the relative amplitude of the cross-correlation function and autocorrelation functions as described in the Material and Methods.

Figure S4.3. FCCS Data for Blue Cone Opsin. FCCS data are shown for nine representative single Cos-7 cells expressing human blue cone opsin fusions to eGFP and mCherry. In each plot, the colored dots are the measured data points, whereas the solid black lines indicate the fitted functions (defined in the Material and Methods). Red dots are the FCS data for the mCherry fusion protein, GR (τ); green dots are the FCS data for the eGFP fusion, GG (τ); and blue dots are the FCCS data, GX (τ). A horizontal dotted line marks the zero value in each plot. Amplitude data report directly on the concentration of diffusing species through the relationship: (0) = 1⁄〈〉 = 1⁄〈〉. The fraction correlated is calculated by comparing the relative amplitudes of the cross-correlation function and autocorrelation functions as described in the main text.

76 The relative cross-correlation, , was calculated for each cell by taking the

amplitude of the cross-correlation function and dividing it by the zero-time value of the autocorrelation function with the highest amplitude: = (0)⁄ (0). For

eGFP/mCherry labeled systems, we expect a median value of 0.167 for fully dimerized

46 proteins. In Fig. 4.2 D, the fc distributions of rod opsin and the red, blue and green cone

opsins are shown as bee-swarm plots with a boxplot overlay for statistical comparison. The

median C value of rod opsin was comparable to the expected value for a dimeric protein

as reported previously.45 The data for red cone opsin displayed a wide distribution of

values, with a median = 0.19 (Fig. 4.2 D). This result was higher than that of rod opsin

(P < 0.001), suggesting that red cone opsin forms dimers and possibly higher order

oligomers. The cross-correlation of green and blue cone opsins clustered near zero with

median C values of 0.028 and 0.032, respectively (Fig. 4.2 D), indicating that blue and

green cone opsins are overwhelmingly monomeric in the plasma membrane.

In contrast to what was reported previously for rod opsin,45 red, blue and green cone

opsins did not show any significant trend between fc and receptor density. This can be

visualized by plotting the dimer concentration as function of the monomer concentrations

(Fig. S4.4). A correlated trend, as seen for rod opsin, suggests a modest driving force for

dimerization. If the population is either dominantly monomeric or dominantly dimeric over

the measured concentrations, there will not be a significant correlation. For green and blue

cone opsins, a lack of correlation between monomer and dimer concentrations is consistent

with a lack of significant dimerization. For red cone opsin, this data suggest that either the

dimerization affinity is very high or that red cone opsin forms higher order oligomers.

Figure 4.2. PIE-FCCS Data Collection and Analysis. (A) Two-color excitation is used to illuminate the sample. Pulsed interleaved excitation is achieved by increasing the optical path of the 488 nm light relative to the 561 nm light with single mode optical fibers of different lengths. Fluorescence emission is spectrally separated and detected by two single photon counting modules. (B) Diagram of single photon events. Only photons collected in detector B after excitation by a 488 nm pulse were included in FG(t) and photons collected by detector A after excitation by a 561 nm pulse were included in FR(t). This strategy eliminates cross-talk from spectral leak-through and direct excitation. (C) Correlation functions and model fits (GG(τ), GR(τ), and GX(τ)) are shown for a representative single cell measurement. The cross-correlation function is fit with a 2D Brownian model whereas the autocorrelation functions are fit with an additional triplet term to account for the 78 photophysics of the fluorescent protein. The amplitude of the CCF is related to the fraction of dimers through the fc parameter. (D) Single cell values (gray squares) are shown for rod opsin and the three cone opsins. The total number of cells is shown in parentheses above the distributions. Boxplots are overlaid to indicate the median (red line) and percentiles (box – 25 to 75%, whiskers – 0 to 100%, red plus signs – outliers).

Figure S4.4. Density Dependent Dimerization. For each data set shown in Fig. 4.2 D and

Fig. 4.3 B of the main text, we plotted the single cell values of the dimer concentration as a function of the product of the monomer concentrations. The rhodopsin data and their fits were published previously129. Plots for the other receptors indicate low correlations in a linear regression analysis: all R2 values were less than 0.5 except for green-IAM.

80 LIFETIME FRET DATA OF CONE OPSINS

The time-correlated single photon counting approach used for PIE-FCCS also allowed us to construct lifetime histograms for each cell measured in Fig. 4.2. The eGFP fluorescence lifetime is sensitive to resonance energy transfer, i.e. FRET, and thus can be used as a probe for molecular associations. Our eGFP/mCherry system was not as efficient a FRET pair as, for example, cyan and yellow fluorescent proteins, but we did observe a significant decrease in the fluorescence lifetime of red cone opsin fused to eGFP in dual expression experiments. Using the acceptor-free lifetime, 0, from the eGFP-only experiments above, we calculated the FRET efficiency for each cell measurement (Fig.

S4.5 A). For red cone opsin, the FRET efficiencies reached as high as 12%, with an average of 3.6 ± 0.9. The green and blue cone opsin FRET efficiencies never exceeded 3.5%, and their averages were near zero (-0.12 ± 0.01% and -0.06 ± 0.02% respectively). These data provide further evidence that red opsin forms dimeric complexes, whereas blue and green cone opsins are mostly monomeric. The FRET efficiencies for each of the cone opsins did not show any significant trend with density over the range measured here (Fig. S4.6).

Figure S4.5. FRET Analyses. The efficiency of FRET was determined by donor lifetime

analysis, = �1 − �, using the lifetime of the donor fluorophore in the 0 presence () and absence (0) of the acceptor. A higher FRET efficiency indicates an increase in dimerization. (A) Beeswarm plot of single Cos-7 cell FRET efficiency data is shown with box and whisker plots for rod opsin and the three human cone opsins. (B)

FRET data for WT red and green cone opsins are compared with data from their mutants

(described in the main text).

Figure S4.6. Density Dependence of FRET Efficiency. FRET values from Fig. S4.5 are plotted against the receptor density calculated from the FCS data.

83 A TRIPLE-POINT SWAP MUTANT DISRUPTS DIMERIZATION OF RED CONE

OPSIN AND INCREASES DIMERIZATION OF GREEN CONE OPSIN

Human red and green cone opsins differ by only 15 residues,130 as seen in the amino acid sequence alignment of human red cone opsin with human green cone opsin in Fig.

S4.7. Based on the data above, we found that among cone opsins, only red cone opsin forms dimers. Therefore, we determined which of the unique amino acids were located at the receptor surface and thus could be involved in receptor-receptor interactions. Three of those residues (230, 233 and 236; TSV in green and IAM in red cone opsin, Fig. 4.3 A) were located on TM5, implicated in the formation of the dimer interface in other GPCRs.93

To test if these specific amino acids are responsible for red cone opsin dimerization, we constructed two triple point swap mutants: a red I230T, A233S, M236V (red-TSV) to abolish receptor dimerization and a green T230I, S233A, V236M (green-IAM) to induce receptor dimerization.

Figure S4.7. A Sequence Alignment of Red and Green Cone Opsins. Produced with

Clustal2.1. Conserved residues are highlighted in grey. The symbols below the sequences indicate: conserved sequences (*), conserved mutations (:) and semi-conserved mutations

(.).

Figure 4.3. Triple Point Red/Green Cone Opsin Mutants. (A) 3D homology model of red and green cone opsins highlighting the location of the three point mutations. (B) Summary of cross-correlation, , for WT cone opsins and triple-point mutants. A significant change in dimerization is caused by the triple point mutation. The cross-correlation of red-TSV decreased compared to WT red cone opsin, whereas the cross-correlation of green-IAM increased relative to WT green cone opsin. This observation is consistent with the mutation disrupting dimerization in red-TSV and inducing dimerization in green-IAM. (C) Effective diffusion coefficients for eGFP-labeled opsins. These data indicate that the mobility of red-

TSV increases relative to WT, consistent with the loss of dimerization, whereas the mobility of green-IAM decreases relative to WT, consistent with an increase in dimerization. (D) Molecular brightness of eGFP-labeled opsins. The average molecular

86 brightness of red-TSV decreased significantly compared to WT indicating a mostly monomeric population. The molecular brightness of green-IAM increased relative to WT indicating a significant increase in dimeric species. For C and D, the error bars are the standard errors of the means.

We then repeated the FCS and PIE-FCCS experiments described above with the triple-point swap mutants, and the findings are summarized in Fig. 4.3 (Sample PIE-FCCS data are shown in Fig. S4.8 and S4.9). The PIE-FCCS measurements of red-TSV displayed significantly reduced cross-correlation compared with those of WT red cone opsin (Fig.

4.3 B, P < 0.001). Moreover, the green-IAM cross-correlation increased relative to the WT protein indicating an increased dimerization (Fig. 4.3 B, P < 0.001). The median value of green-IAM was 0.10, which is greater than the median C of WT green cone opsin (0.03), but less than the median for red cone opsin (0.19). The single-color FCS data for red-

TSV and green-IAM are consistent with the conclusions drawn from the PIE-FCCS results:

The diffusion coefficient of the red-TSV mutant increased and its molecular brightness decreased, indicating a higher mobility and lower clustering relative to the WT protein

(Fig. 4.3 C, D). Conversely, the diffusion coefficient of the green-IAM mutant decreased and the molecular brightness increased relative to the WT protein denoting a lower mobility and increased clustering (Fig. 4.3 C, D).

Figure S4.8. FCCS Data for Red-TSV. FCCS data are shown for nine representative single

Cos-7 cells expressing red-TSV fusions to eGFP and mCherry. In each plot, colored dots are the measured data points, whereas the solid black lines indicate the fitted functions

(defined in the Material and Methods). Red dots are the FCS data for the mCherry fusion protein, GR (τ); green dots are the FCS data for the eGFP fusion, GG (τ); and blue dots are the FCCS data, GX (τ). A horizontal dotted line marks the zero value in each plot.

Amplitude data report directly on the concentration of diffusing species through the relationship: (0) = 1⁄〈〉 = 1⁄〈〉. The fraction correlated is calculated by comparing the relative amplitudes of the cross-correlation function and autocorrelation functions as described in the Material and Methods.

Figure S4.9. FCCS Data for Green-IAM. FCCS data are shown for nine representative single Cos-7 cells expressing green-IAM fusions to eGFP and mCherry. In each plot, colored dots are the measured data points, whereas the solid black lines indicate the fitted functions (defined in the Material and Methods). Red dots are the FCS data for the mCherry fusion protein, GR (τ); green dots are the FCS data for the eGFP fusion, GG (τ); and blue dots are the FCCS data, GX (τ). The horizontal dotted line marks the zero value in each plot. Amplitude data report directly on the concentration of diffusing species through the relationship: (0) = 1⁄〈〉 = 1⁄〈〉. The fraction correlated is calculated by comparing the relative amplitudes of the cross-correlation function and autocorrelation functions as described in the Material and Methods.

89 Blue cone opsin shares about 40% of sequences homology with red and green cone opsins. According to our results obtained from FCS experiments, both green and blue cone opsins do not form dimers in the cell membrane. V211 S214, and C217 are three residues in blue cone opsin that are homologous to I230, A233, and M236 in red cone opsin and

T230, S233, and V236 in green cone opsin (see sequence alignment in Fig. 4.3 A).

Interestingly, both green and blue cone opsins have an identical serine residue in the middle of this ‘triple amino acid motif’. Moreover, both green and blue cone opsins contain a valine residue, although this is located on the opposite ends of this motif. V211 and C217 in blue cone opsin correspond to T230 and V236 in green cone opsin, respectively. All these four residues are comparable in size and smaller than the isoleucine and methionine present in red cone opsin.

Our data are consistent with the triple-point mutation increasing the dimerization of green cone opsin, but not to the level observed for WT red cone opsin. This comparison suggests that there could be higher order oligomerization in red cone opsin involving more than just TM5. To test this idea, we also conducted PIE-FCCS measurements of cells co- transfected with red-TSV and WT red cone opsins. If there is a TM5-TMX interface, we would expect there to be significant cross-correlation for the combination of a wild-type with TM5 mutants. Instead, we observed a significant drop in the values, similar to the red-TSV only experiments. (Fig. S4.10). Although this finding does not exclude possible combined interfaces with TM5 (i.e., TM4/5 or TM5/6), it does indicate that TM5 is part of a dimerization interface.

Figure S4.10. Comparison of Red Cone Opsin Homodimerization with

Heterodimerization of WT Red Cone Opsin and Red-TSV. The PIE-FCCS data show

that co-expression of WT red-mCherry and red-TSV-eGFP results in a significant

decrease in dimerization (P < 0.001). This result is consistent with the conclusion that

TM5 is part of the dimerization interface, and that other interfaces likely play only

minor roles.

The ability of triple point mutations to significantly modulate cone opsin dimerization affinity opens up new avenues to investigate the chemical interface between

GPCRs in a dimeric complex. One possibility for future work is to probe of the side chain dependence of the cross-correlation to resolve the local interactions that drive dimerization.

As an initial experiment, we mutated the Ala residue to Val at position 230 in the green swap mutant to compare green-IAM with green-IVM. Dimerization of green-IVM was slightly lower than in green-IAM (Fig. S4.11), suggesting that the steric bulk of the Val residue relative to Ala contributes to the dimerization affinity. More work will be needed to fully understand the chemical forces driving cone opsin dimerization.

Figure S4.11. Comparison of Dimerization for Green Cone Opsin, Green-IVM and Green-

IAM. The plot contains a summary of cross-correlation values, , for green cone opsin, green-IAM, (T230I, S233A, V236M) and green-IVM (T230I, S233V, V236M). The median of the C distribution for green-IVM is between those of WT green and green-IAM.

This indicates that the Val substitution at position 233 weakens the dimerization affinity relative to the Ala residue at the same position.

92 CROSS-LINKING OF CONE OPSINS AND THE EFFECT OF A TRIPLE MUTATION

ON DIMER FORMATION

PIE-FCCS experiments indicated that red cone opsin has a higher propensity than green cone opsin to self-associate. This affinity was alleviated by introducing three mutations into the amino acids located at the potential dimer interface, which matched the sequence in green cone opsin. In contrast, changing the same amino acids in green cone opsin to those present in red cone opsin enhanced self-association. To confirm these results, we performed cross-linking of red, green, and mutated cone opsins expressed in HEK-293 cell membranes with a short (7.7 Å spacer arm) disuccinimidyl glutarate (DSG) cross- linker. This homobifunctional N-hydroxysuccinimide ester (NHS-ester) cross-linker reacts with primary amines on the N-termini of the ε-amine of Lys residues forming a stable covalent amide bond connecting the two protein molecules, but only if such molecules are in close proximity. Thus, only those receptors self-associating in the lipid bilayer (not freely diffusing monomers) are likely to be captured by the cross-linker to form stable dimers/oligomers. Before cross-linking, a dimer population of about 40-60% was found for the green and red WT and mutant cone opsin samples. This relatively high dimer content in all samples could result from nonspecific aggregation in the presence of SDS, commonly noted for many integral membrane proteins.131-133 These properties however, could change after surface modification of the receptors by a bound cross-linker.

Nevertheless, after incubation with a DSG cross-linker, an increased level of receptor

DSG-chemical dimers and a decrease of monomers were observed for red cone opsin but not for green cone opsin (Fig. 4.4 A, B). The higher-order oligomers overlapped with a smear, possibly resulting from various extents of receptor N-glycosylation. The smear also

93 could lead to an overestimation of their content, so we quantified only band intensities of monomers and dimers, finding 79 ± 9% of DSG-dimers for red cone opsin, but only ~21 ±

14% of DSG-dimers for green cone opsin after cross-linking. Consistent with the fluorescence microscopy measurements above, less dimer formation was found for red-

TSV (48 ± 12% versus 79 ± 9% for WT) and enhanced dimerization was seen for green-

IAM (43 ± 2% versus 21 ± 14% for WT) (Fig. 4.4 A, B, arrows).

Figure 4.4. Effect of Triple Mutations on Opsin Cross-Linking. (A) Effects of mutations on the formation of DSG-cross-linked opsin dimers. Membranes isolated from HEK-293 cells containing cone opsins were cross-linked with DSG (see dark lines above panels A and B). Fifty µg of the total protein extracts were loaded on each lane of the SDS-PAGE.

(B) Quantification of DSG-cross-linked dimers. The amount of DSG-cross-linked opsin dimers was calculated from densitometric analyses of protein bands corresponding to the opsin monomer and dimer from 3 independent experiments. Results are presented as means

95 ± SDs. Arrows indicate an increase of dimer formation in green-IAM opsin relative to green cone opsin and a decrease of dimer formation in red-TSV opsin compared to red cone opsin.

ROLE OF A TRIPLE MUTANT IN SPECTRAL TUNING

Because of the high degree of sequence similarity between red and green cone opsins, there has been significant interest in understanding the shift in their spectral sensitivities.116 The wavelength of maximum absorbance of red cone opsin is 564 nm, just

30 nm longer than the 534 nm maximum absorbance wavelength of green cone opsin.116

Moreover, red and green cone opsin amino acid sequences are identical except for 15 residues. Based on functional mutagenesis work, the spectral distinction between red and green cone opsins distributed over precisely seven of those amino acid residues.134 The majority (~70%) of the spectral shift can be assigned to positions 277, 285, and 309.

However, positions 116, 180, 230, and 233 are required to fully recapitulate the native absorbance profile.135 Of these seven amino acids, two (230 and 233) are part of the dimeric interface we identified above, and also account for 4 nm of the spectral shift between red

134-135 and green cone opsin.

We performed absorbance measurements of the cone opsin constructs used in our study to verify their function and spectral sensitivity. We also sought to confirm that the triple-point mutant used in this work shows the expected spectral shift seen in previous studies. To purify the cone opsin-eGFP fusion proteins, a 1D4 tag was added at the C- terminus following the eGFP sequence. Expression levels of WT and mutant cone opsin- eGFP-1D4 constructs in transiently transfected HEK-293 cells were similar and their membrane localization was unaffected by the tag (Fig. S4.12). Transiently expressed cone 96 opsins instead of native 11-cis-retinal were regenerated with the isochromophore 9-cis- retinal, purified by 1D4-immunoaffinity chromatography, after which their UV-Vis absorption spectra were measured (Fig. S4.12 C, D). Absorption maxima of retinal- regenerated cone pigments were difficult to discriminate due to the high absorbance of eGFP, with an absorption maximum at 488 nm. Therefore, to extract the absorption spectra of cone opsins, we recorded difference spectra. As shown in Fig. S4.12, the absorption maximum of 9-cis-retinal bound green opsin was ~493 nm and ~525 nm for 9-cis-retinal bound red opsin, in agreement with previous observations.136 A spectral shift of 6 nm towards shorter wavelengths was observed for red-TSV as compared to WT red cone opsin.

However, no spectral shift was found for green-IAM compared to WT green cone opsin

(Fig. S4.12 D). One explanation for this finding could be that an exchange of the native chromophore 11-cis-retinal to the 9-cis isochromophore avoided the spectral shift in the green-IAM mutant due to specific structural changes possibly occurring in iso-opsins.

Alternatively, the inability to detect a spectral shift could result from the overlap in the absorption maxima between 9-cis-green opsin (493 nm) and eGFP (488 nm).

Figure S4.12. Biochemical Characterization and Spectral Tuning of EGFP Constructs. (A)

Immunoblots indicating expression levels of green cone opsin, green-IAM, red cone opsin

98 and red-TSV, each with an eGFP-1D4 fusion tag and transiently expressed in HEK-293 cells. Measurements were made with an anti-rhodopsin C-terminal 1D4 tagged antibody on 50 µg of total protein cell lysate 48 h after transfection. GAPDH was the protein loading control. (B) Membrane localization of opsins was determined by detecting eGFP fluorescence in live cells. (C) Immunoblots of green cone opsin, green-IAM, red cone opsin and red-TSV regenerated with 9-cis-retinal and purified by immunoaffinity chromatography and detected with the anti-rhodopsin C-terminal 1D4 tagged antibody. Ex

– extract (total lysate), FT – flow through, W – last wash, El – elution. (D), Difference absorption spectra of green cone opsin, green-IAM, red cone opsin and red-TSV regenerated with 9-cis-retinal and purified by immunoaffinity chromatography. The spectrum of red-TSV shows a 6 nm spectral shift, whereas the green-IAM mutant opsin does not.

To validate the red cone opsin observations and eliminate spectral interference from the eGFP tag, we re-cloned the green and red cone opsins and their respective mutants into a pcDNA3.1(+) vector without the eGFP fusion. Measured expression levels of WT and mutant cone opsins in transiently transfected HEK-293 cells were similar (Fig. 4.5 A). UV-

Vis absorption spectra were then recorded for purified cone pigments regenerated with 11- cis-retinal chromophore (Fig. 4.5 B, C). Here, spectral shifts were found for both mutants: a 4 nm shift towards longer wavelengths for green-IAM opsin (530 nm  534 nm) and a

5 nm shift towards shorter wavelengths for red-TSV opsin (560 nm  555 nm) (Fig. 4.5

C). These results are consistent with those of an earlier study that linked residues I230 and

A233 in exon 4 to the spectral sensitivity of red cone opsin.134 A direct connection between the two effects (dimerization and color tuning) remains to be established. The first step

99 needed is to probe dimerization in the chromophore-bound state and then to determine the mechanism of how the above residues drive spectral sensitivity.

Figure 4.5. Biochemical Characterization of Green, Red and Mutant Cone Opsins. (A)

Immunoblots indicating expression levels of green cone opsin, green-IAM, red cone opsin and red-TSV transiently expressed in HEK-293 cells are shown. Fifty µg of total protein cell lysate obtained 48 h after transfection were used for detection with an anti-rhodopsin

C-terminal 1D4 tag antibody. GAPDH was the protein loading control. (B) Shown are immunoblots of green cone opsin, green-IAM, red cone opsin and red-TSV regenerated with 11-cis-retinal and purified by immunoaffinity chromatography. Proteins were detected with an anti-rhodopsin C-terminal 1D4 tag antibody. Ex – extract (total lysate),

FT – flow through, W – last wash, El – elution. (C) Illustrated are difference absorption

100 spectra of green cone opsin, green-IAM, red cone opsin and red-TSV regenerated with 11- cis-retinal and purified by immunoaffinity chromatography. Spectra of green-IAM and red-

TSV reveal shifts of 4-5 nm.

CONCLUSIONS

Evidence presented in this paper is consistent with human red cone opsin, but not green or blue cone opsin, forming a stable dimer in the live cell plasma membrane. This result was particularly surprising because of the high sequence similarity (>95%) between the red and green cone opsins. From the limited number of lipid-facing residues that differ between red and green cone opsins, we identified three amino acids in TM5 that are required for dimerization. By swapping these three amino acids from green cone opsin into red cone opsin, we observed a significant decrease in dimerization. Conversely, the analogous green cone swap mutant showed a significant increase in dimerization. All of our fluorescence methods: molecular brightness, mobility, FRET, and cross-correlation, yielded results consistent with this conclusion. Moreover, these microscopic observations were confirmed by membrane receptor cross-linking. This study is the first to show disruption of an opsin dimer with point mutations. It also is the first to identify a set of

GPCRs for which receptor dimerization can be both eliminated and induced with point mutations.

Translating these results into to the physiology of vision will require future investigation. For example, the lipid content of rod and cone membrane disks differs notably from the plasma membrane of Cos-7 cells,137 and the density range studied here is two to three orders of magnitude lower than the actual physiological densities.116 So, what physiological relevance could there be for red cone opsin dimerization? One possibility 101 could be to stabilize the protein by reducing the effect of thermal fluctuations on receptor activation. For rhodopsin, the stable dimeric form is likely to prevent spontaneous activation and thus permits single photon detection.138-139 Point mutations in TM5 of rhodopsin can increase dark noise and cause stationary night blindness before degenerative retinitis pigmentosa becomes evident.140-141 For green cone opsin, with an absorption spectrum similar to that of rhodopsin, dimerization could be less critical because it operates under high lighting conditions wherein low levels of spontaneous activation are less problematic. Red cone opsin also operates under high light conditions, but its increased sensitivity to longer wavelengths makes it more susceptible to activation by thermal fluctuations. Red cone opsin does in fact have a significantly higher rate of thermal activation,142 and this likely needs to be suppressed for effective daytime vision.

Consequenty, stabilization in the dimeric conformation could be important for red cone opsin to prevent self-activation at body temperature.

Another potential physiological role for dimerization of red cone opsin is to modulate its spectral sensitivity. Our results show that the amino acids in TM5 responsible for dimerization also shift the maximum absorbance wavelength of the opsin-retinal complex. This finding suggests that dimerization could, through allosteric modulation of the protein structure, shift the transition energy of 11-cis-retinal-bound opsin.

Alternatively, the dimeric forms of rhodopsin and red cone opsin could be essential for transport to the outer segment membranes, or for development and stabilization of the photoreceptor cellular structure. Or possibliy the dimeric form of cone opsin is a byproduct of the other evolutionary pressures that drove the spectral shift away from green cone opsin.

Regardless of the answers to these questions, our results establish an essential link between

102 the amino acid sequence of a functional GPCR and its propensity to form dimeric structures. They also provide a unique opportunity to investigate the chemical forces responsible for the lateral association of GPCRs and to further resolve the physiological role of dimerization.

103

CHAPTER 5

MEASURING G PROTEIN-COUPLED RECEPTOR DIMERIZATION IN HUMAN

MELANOPSIN

INTRODUCTION

The most commonly studied Class A GPCR is rhodopsin (OPN2). Hence the class’

secondary title of “Rhodopsin-like GPCRs”. Rhodopsin, stacked away in rod cells in the

retina, is responsible for scotopic vision. Responsible for photopic vision are the

trichromatic cone opsins in red (OPN1LW), green (OPN1MW), and blue (OPN1SW). Also

in the retina, a few layers away, is a third type of opsin; melanopsin. Melanopsin was first

isolated from the dermal melanophore cells of frogs.143 Part of the non-image forming

pathway; melanopsin was identified as an intrinsically photosensitive Retinal Ganglion

Cell (ipRGC).144 Melanopsin is ~10,000-fold less sensitive to light than visual opsins.145-

146 Melanopsin shares a 27%, 28%, and 28% sequence homology with red, green, and blue

cone opsins, respectively. Melanopsin also shares a 29% sequence homology with the

prototypical GPCR, rhodopsin. For many years rhodopsin stood as the “go to” GPCR,

8 especially with being the first GPCR to be crystalized.

Over the past decade, many studies have shown support in regards to the dimeric

nature of rhodopsin. Dimerization has been observed in isolated rod outer segment (ROS)

7, disks via atomic force microscopy (AFM) and transmission electron microscopy (TEM).

31 We previously reported on the dimeric association of retinal-free rhodopsin, and also 104 that of the cone opsins, at low concentrations via live-cell PIE-FCCS measurements. A triple point mutation on the fifth transmembrane helix (TM5) of red and green cone opsin was determined to contribute to the reduction and increase, respectively, of dimeric association. Those same amino acids were shown to contribute to a spectral shift of 4 nm towards longer wavelengths for the green cone opsin mutant and 5 nm towards shorter wavelengths for the red cone opsin mutant.

Here we investigated the dimerization of human melanopsin, otherwise known as

OPN4. Clyde E. Keeler was the first to study melanopsin, though he had no idea about what he stumbled across, while studying “normal and ‘rodless’ retinae” of mice.147

Decades later, efforts in understanding circadian photoreception in animal models via the pupillary light reflex (PLR) would offer us a another glimpse into melanopsin.148 One constant in melanopsin studies is the testing of the PLR. Studies like those done by Mure, et.al. showed that human melanopsin is unique in the sense that it is considered bistable, unlike human rhodopsin and cone opsins.149-150 In this context, bistability means melanopsin does not need a retinoid cycle in order to regenerate 11-cis retinal from all- trans retinal (ATR) like its visual counterparts. Melanopsin has an intrinsic light-induced regeneration process by which 11-cis retinal is regenerated from all-trans retinal. All of these studies have been useful but there is still more to be done in regards to the continual characterization of melanopsin.

To date, there have been no studies in which an attempt to quantify the dimeric association of human melanopsin was reported. Based on our rhodopsin and cone opsin studies there is reason to believe that melanopsin will dimerize. To further the

105 characterization of melanopsin, we used a time-resolved fluorescence technique; pulsed- interleaved excitation fluorescence cross-correlation spectroscopy (PIE-FCCS). Using

PIE-FCCS, we were able to quantify the population of co-diffusing melanopsin receptors while simultaneously quantifying the total population of melanopsin receptors. PIE-FCCS offers the ability to take live cell measurements of a species, receptors in this case, diffusing through a laser focus. This technique allows us to measure the mobility and diffusion of receptors transiently transfected into live cells. The data produced from measurements allows us to determine to what degree a receptor has an affinity for forming a dimeric, or higher order oligomeric, species.

Using PIE-FCCS we determined that retinal-free human melanopsin shows a weak affinity for dimerization, slightly lower than that of previously tested murine rhodopsin. In an attempt to disrupt dimerization, a triple point mutation was introduced along TM5. The specific amino acids were chosen to mimic our previous study on red and green cone opsins. Instead of disrupting dimerization there was actually a slight increase but considered not significant after an ANOVA test.

RESULTS

PIE-FCCS OF HUMAN MELANOPSIN IN TRPC3-HEK293 CELLS

Full length melanopsin (OPN4) was first cloned into empty pmCherry-N1 and mEGFP-N1 mammalian expression vectors. The fluorescent tags are located at the C- terminal end of melanopsin. The plasmids are then transiently transfected into human embryonic kidney cells (HEK293) cells that stably express transient receptor potential 3

(TRPC3) channels. TRPC3-HEK293 cells were primarily chosen as they show significant

106 Ca2+ permeability and result in a functional cascade when co-expressed with melanopsin.151 These are the ideal cells for future electrophysiology experiments. They express no endogenous melanopsin. The cells are co-transfected in an attempt to both express Mel-mCherry and Mel-EGFP. The co-transfected cells have a laser focused on the membranous portions (Figure 5.1).

Figure 5.1. TRPC3-HEK293 Cell Expressing Mel WT. A dual channel epi-fluorescence image of co-transfected Mel WT being expressed in a TRPC3-HEK-293 cell with the laser illumination spot shown by the arrow. The red channel (on the left) showing mCherry being expressed. The green channel (on the right) showing EGFP being expressed. The center image is a stack of the two outside images. Scale bar = 10 μm.

During the acquisitions, 488 nm and 561 nm laser lights are shone onto the cell from a pulsed white light source. The lights pass through fibers of a varying size creating

~50 ns delay between lights as they reach the sample. As fluorescent molecules pass in and out of the confocal and laser defined area, individual photons are emitted and counted by specified detectors. Any photon emitted by pmCherry detected by the green detector will be removed from cross-correlation calculations. This eliminates the threat of spectral cross-

107 talk which would lead to an exaggerated calculation of cross-correlation. Autocorrelation curves, red and green curves on the plots, are created from the red and green channels and are inversely proportional to the number of diffusing molecules tagged with either mCherry or EGFP, respectively (Figure 5.2). The varying amplitudes of the autocorrelation curves are inversely proportional to the differences in expression. Cross-correlation (shown in blue, Figure 5.2) was also calculated and the amplitude is proportional to the total number of co-diffusing species that have at least one mCherry and one EGFP tag. The degree to which a species stably dimerizes is shown by cross-correlation.

Figure 5.2. Representative FCCS Data for Mel WT. Mel WT was expressed in TRPC3-

HEK293 cells. The green (GG(τ)) and red (GR(τ)) autocorrelation curves in each plot are inversely proportional to the number of diffusing species expressing either EGFP or mCherry, respectively. The blue FCCS curve (GX(τ)) is directly proportional to the number of co-diffusing species. The black lines show the lines of best for for each curve and a horizontal dashed line shows the zero value for comparison with the cross-correlation amplitude, GX(0).

108 The fraction correlated species or relative cross-correlation (fc), represented by a scatter plot (Figure 5.3 A) and a box and whiskers plot (Figure 5.3 B), is calculated by dividing the time zero value of the cross-correlation by the time zero value of the autocorrelation curve with the highest amplitude.

GX(0) = GR or G(0)

According to the data for Mel WT, the median fc is reported at 0.07. This result lies between that of the positive control (myr-GCN4-EGFR) and the negative control (Src16).

There is no significant difference between Mel WT and rhodopsin (previously reported45,

P 0.9993). This indicates that melanopsin has a weak affinity for dimerization.

109

Figure 5.3. Summary of Cross-Correlation Data for Mel WT. (A) The scatter plot shows the distribution of individual fc values grouped by protein type. The black lines in the scatter plots mark the median for the data sets. (B) The box and whisker plot was created from the same set of data as the scatter plot. The boxes encompass the 25-75% percentile values and the bars show the range of values. The horizontal line inside the boxes marks the median of the data sets. The individual points outside of the bars show the outliers. The black bars

110 indicate the confidence intervals Numbers in parenthesis show the total number of cells measured.

A TRIPLE POINT MUTATION IN HUMAN MELANOPSIN

Melanopsin shares a 27% and 28% sequence homology with red and green cone opsins, respectively. In a previous study152, three amino acids on TM5 of red and green cone opsins were identified as unique to the fact that, when mutated, they disrupted dimerization of red cone opsin and increased dimerization of green cone opsin. Based on this, we identified the corresponding amino acids in melanopsin (L246, L249, and I252).

Using site-directed mutagenesis, we mutated these amino acids to the smallest of the hydrophobic side chains, alanine, making the mutant Mel_L246A_L249A_I252A

(Mel_LLI_A3).

111

Figure 5.4. Summary of Cross-Correlation Data for Mel WT and the Mel_LLI_A3

Mutant. (A) The scatter plot shows no significant difference between the Mel WT and triple point mutant although the mutant shows a narrower distribution. The black lines in the scatter plots mark the median for the data sets. (B) The box and whisker plot was created from the same set of data as the scatter plot. The boxes encompass the 25-75% percentile values and the bars show the range of values. The horizontal line inside the boxes marks the median of the data sets. The individual points outside of the bars show the outliers. Numbers in parenthesis show the total number of cells measured. 112 PIE-FCCS was used to measure the dimerization of Mel_LLI_A3 and the results are summarized in Figure 5.4. The scatter plot (Figure 5.4 A) shows a narrower distribution of fc values for the mutant as compared to the Mel WT. There is no significant difference in the fc of Mel_LLI_A3 as compared to that of Mel WT (P 0.8134). There is no major difference between the effective diffusion coefficients (Deff) of Mel WT and Mel_LLI_A3

(P 0.0173). The Deff of Mel WT is reported to be 0.40 ± 0.15 for mCherry and 0.46 ± 0.23 for EGFP with Mel_LLI_A3 reported to be 0.47 ± 0.18 for mCherry and 0.50 ± 0.20 for

EGFP (Figure 5.5). These values lie between the previously reported values for red and green cone opsin152. This comparison shows that both Mel WT and Mel_LLI_A3 have a weak affinity for dimerization.

There were no experiments done to see if a co-transfection with Mel WT and

Mel_LLI_A3 would have an effect on dimerization. Seemingly, the mutation itself had no effect on dimerization. Future works could potentially include the mutation of other amino acids along TM5 or mutants involved in phenomena like seasonal affective disorder

(SAD)153. There is still more work needed to characterize the dimerization of melanopsin.

113

Figure 5.5. Average Diffusion Coefficient. The average diffusion coefficients show the mobility of Mel WT as compared to Mel_LLI_A3 per their fluorescent species. There is a slight increase in effective diffusion from the WT to the mutant (P 0.0173).

114 CONCLUSIONS

The results described in this paper are consistent with melanopsin showing a weak affinity for dimerization. The results are fitting considering only a 29% sequence homology with rhodopsin. We hypothesized that removing some of the surface area of the dimeric interface would cause a decrease in dimerization but the triple point mutation made showed to have little effect on the affinity for dimerization for melanopsin. The amino acids chosen for mutation corresponded to the amino chosen for the red and green cone opsin swap mutants. The mutants for the red and green cone opsin swap mutants had a profound effect on their affinities for dimerization. More studies are needed to probe what affects the mutations in melanopsin might have on the PLR. All of the fluorescence methods utilized are consistent with our conclusion. This is the first study to report on the dimerization of melanopsin.

With melanopsin binding a Gq heterotrimeric G protein instead of transducin, like the visual opsins, it could take on a slightly different morphology lowering the affinity for dimerization. This study was performed at much lower concentrations of melanopsin than that natively found in the GCL. It could be, that melanopsin dimerization is concentration dependent. Regardless, we have shown that PIE-FCCS is a powerful method able to elucidate the affinity for dimerization for melanopsin in live cells showing that melanopsin exists in a monomer-dimer type flux. Determining how dimerization plays a role in the non-visual pathway will take more work.

115

CHAPTER 6

CONCLUSIONS

G protein-coupled receptors (GPCRs) detect a wide variety of physical and chemical signals and transmit that information across the cellular plasma membrane.

Determining membrane protein quaternary structure of these receptors is extremely challenging, especially in of live cell membranes. In Chapter 3, we measured the oligomerization of opsin, a prototypical G protein-coupled receptor with pulsed- interleaved excitation fluorescence cross-correlation spectroscopy (PIE-FCCS). Individual cell measurements revealed that opsin is predominantly organized into dimeric clusters (fc of 0.10). At low concentrations, we observed that the population of oligomers increased linearly with the square of the individual monomer populations. We reported a Keq of 9.94

± 0.53 X 10-4, which had not been previously reported. This finding supports a monomer- dimer equilibrium and provides an experimental measurement of the equilibrium constant.

In Chapter 4, we investigated the dimerization affinity and binding interface of human cone opsins, which initiate and sustain daytime color vision. Using PIE-FCCS, we found that human red cone opsin exhibits a high propensity for dimerization (fc of 0.19), whereas the green and blue cone opsins do not. Through mutagenesis experiments, we identified a dimerization interface in the fifth transmembrane helix of human red cone opsin involving amino acids I230, A233, and M236. Insights into this dimerization interface of red cone opsin should aid ongoing investigations of the structure and function

116 of GPCR quaternary interactions in cell signaling. Finally, we demonstrated that the same residues needed for dimerization are also partially responsible for the spectral tuning of red cone opsin. This last observation has the potential to open up new lines of inquiry regarding the functional role of dimerization for red cone opsin.

117 Figure 6.1. Summary of Cross-Correlation Data for Visual and Non-Visual Opsins. (A)

The scatter plot shows the complete distribution of individual fc values among visual and non-visual opsins. The black bars indicate the median values. (B) the box and whisker plot was created from the same data set as the scatter plot. Among the visual/non-visual opsins,

RCO has the highest affinity for dimerization. The boxes encompass the 25-75% percentile values and the total number of cells measured are in parenthesis. The bars show the total range of each data set and individual points outside of the bars are outliers.

In Chapter 5, we investigated the dimeric association of human melanopsin, which plays a role in both circadian rhythm regulation and the pupillary light response. Using

PIE-FCCS, we found that human melanopsin has a weak dimerization affinity (fc of 0.07).

Through site-directed mutagenesis, a melanopsin mutant was designed under the premise of disrupting dimerization based on the previous human cone opsin experiments. The triple point mutation in melanopsin, L246A, L249A, and I252A, showed to have no significant difference on dimerization affinity. More probing is needed to see what, if anything, could the triple point mutation in melanopsin be effecting.

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