A Novel Class of Liposomal Contrast Agents for Molecular MRI

LisNRs: A Novel Class of Liposomal Contrast Agents for Molecular MRI

Jacob Cyert Simon

B.A., Physics B.A. (Hons.), Molecular and Cell Biology University of California, Berkeley, 2012

Submitted to the Department of Biological Engineering in partial fulfillment of the requirements for the degree of

Doctor of Philosophy in Biological Engineering at the Massachusetts Institute of Technology

February 2021

Signature of Author: Department of Biological Engineering January 12th, 2021

Certified by: Alan Jasanoff Professor of Biological Engineering, Brain and Cognitive Sciences, Nuclear Science and Engineering Thesis Supervisor

Accepted by: Katharina Ribbeck Hyman Career Development Professor of Biological Engineering Graduate Program Committee Chair

Thesis Committee

Accepted by:

K. Dane Wittrup C.P. Dubbs Professor of Chemical Engineering and Biological Engineering Thesis Committee Chairman

Accepted by:

Alan Jasanoff Professor of Biological Engineering Thesis Supervisor

Accepted by:

Barbara Imperiali Class of 1922 Professor of Biology and Chemistry Thesis Committee Member

Accepted by:

Peter Caravan Professor of Radiology, Harvard Medical School Co-director, Institute for Innovation in Imaging, Massachusetts General Hospital Thesis Committee Member

LisNRs: A Novel Class of Liposomal Contrast Agents for Molecular MRI

Jacob Cyert Simon

Submitted to the Department of Biological Engineering On 1/12/2020 in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Biological Engineering

ABSTRACT

Biological systems depend on numerous molecular messengers that transduce information across large distances. Understanding the spatial and temporal dynamics of molecular signaling networks is crucial for the construction of systems- and organism-level models of biological function. Molecular imaging, a technique that employs chemical probes to relay molecular events into spatially-resolved signal changes, is a promising strategy for studying complex molecular signaling networks in situ. Magnetic resonance imaging (MRI) is a leading noninvasive imaging modality that allows for imaging of large volumes of deep tissue with high spatiotemporal resolution. Paramagnetic molecular sensors enable detection of molecular phenomena with MRI (molecular MRI). The scope of molecular MRI experiments thus far, however, has been limited by the modest sensitivity and signal changes provided by existing probes. In this dissertation, I introduce Liposomal Nanoparticle Reporters (LisNRs), a novel class of MRI-detectible sensor that utilizes an innovative contrast mechanism in which reversible modulation of the water permeability of liposomal bilayers simultaneously modulates water access to a large, concentrated pool of conventional T1-weighted MRI contrast agents. This architecture gives rise to significant signal amplification with respect to first-generation MRI probes that rely on stoichiometric sensing mechanisms in which binding of one analyte molecule modulates water access to a single paramagnetic metal ion. I employ two strategies for the signal-dependent modulation of liposomal water permeability. The first approach uses reversible modulation of lipid bilayer fluidity to induce changes in passive bilayer water permeability. To demonstrate this concept, I build Light- LisNR, a photosensitive MRI contrast agent, which I use to map light distribution in the rat brain. The second approach utilizes ligand-gated water-permeable channels to modulate bilayer water permeability. I demonstrate the potential of this strategy for molecular sensing using biotin/streptavidin as a model system. Together, this work introduces and demonstrates a novel platform for sensing with MRI that addresses longstanding challenges of low sensitivity and signal change with existing MRI-detectible probes.

Thesis Supervisor: Alan Jasanoff Title: Professor of Biological Engineering

Acknowledgements

To my advisor, Alan Jasanoff

For your kindness, mentorship, and the confidence you showed in me by giving me the freedom to create my own thesis project.

To my collaborators,

For everything you have contributed to the work presented here. Thanks to Miriam Schwalm for taking Light-LisNR in vivo. Thanks to Nina Hartrampf and Mackenzie Poskus of the Pentelute group for synthesizing Alamethicin. Thanks to Johannes Morstein of the Trauner group for synthesizing azoPC.

To the Jasanoff lab,

For making the lab such a supportive environment and a great place to work. I feel fortunate to have made so many lasting relationships during my time at MIT. I especially want to recognize Peter Harvey, Ali Barandov, and Greg Thiabaud for teaching me everything I know about chemistry.

To my friends, For making my time in Cambridge special.

To my family, For everything you have done to help me along the way. I am looking forward to the day we can celebrate this accomplishment together.

Most of all, Thanks to my partner, Josephine Dybe, for everything you have done to support me throughout.

Table of Contents

Background and Introduction ...... 6 Modalities for Molecular Imaging ...... 7 Optical Imaging ...... 7 Radiotracer Imaging ...... 9 Magnetic Resonance Imaging (MRI) ...... 10 Light-LisNR: Sensing Light in Deep Tissue with MRI ...... 20 Abstract ...... 20 Introduction ...... 21 Results ...... 24 Discussion ...... 30 Materials and Methods ...... 32 Ligand-Responsive LisNRs for Molecular MRI ...... 51 Abstract ...... 51 Introduction ...... 51 Results ...... 54 Discussion ...... 57 Materials and Methods ...... 60 Engineering Binding Proteins for Competitive Sensing ...... 67 Abstract ...... 67 Introduction ...... 67 Results ...... 70 Discussion ...... 72 Materials and Methods ...... 74 Conclusions and Future Directions ...... 82 Synopsis, Significance, and Impact ...... 82 Limitations ...... 82 Future Work ...... 84 References ...... 87

Background and Introduction

Molecular biology seeks to understand the mechanistic basis of biological function at the molecular level with the eventual goal of integrating this detailed information into complete models of biological function from the bottom up. This approach has led to a wealth of accumulated knowledge about the specific function of isolated molecules in simplified experimental conditions, but the integration of such knowledge into models of higher-order biological function, and dysfunction, at organ and organism scales remains a major challenge. Nowhere in modern biology is the difficulty of integrating molecular mechanisms into large-scale models more obvious than in neuroscience. The human brain consists of approximately 100 billion neurons1, each making on average 7000 synaptic connections2, not to mention the important roles of a multitude of supporting cell types like astrocytes, microglia, and oligodendrocytes3.

Beyond the sheer complexity of such massive cellular and molecular networks, the brain provides a major physical challenge for observation with classical methods that have been applied successfully for the study of individual, isolated neurons.

One approach towards the study of integrated biological systems is to build more complex and complete model systems of higher-order function that are more accessible to experimental inquiry; for example, tissue engineering of organoids and organs-on- chips4,5. Molecular imaging6, on the other hand, is a holistic approach for the study of intact biological systems in situ, most often through the use of contrast agents that recognize and translate specific molecular events into changes in image signal, localized in time and space.

Modalities for Molecular Imaging

In order to realize the goals of molecular imaging, it is first necessary to develop suitable imaging probes, delivery methods, and noninvasive imaging modalities.

Extensive engineering efforts have been made towards this goal. Thus far, these efforts have focused primarily on a few major imaging modalities: optical imaging, radiotracer- based methods, and magnetic resonance imaging (MRI). Here I outline the principles, probes, and specific applications of these methods and discuss their respective strengths and limitations.

Optical Imaging

Optical imaging has been one of the most influential technologies for the study of biology, despite some major limitations. Fluorescence microscopy, in which an excitation photon is absorbed by a fluorophore, resulting in emission of a lower energy photon, has become ubiquitous in biology due in large part to low barriers to entry as well as the wide array of compatible molecular probes now widely available, including genetically encoded fluorophores for protein labeling and visualization7,8 as well as protein- and small molecule-based molecular sensors9,10. While fluorescence microscopy offers subcellular and subsecond spatiotemporal resolution and is applicable for the study of cells in culture and thin tissue samples, noninvasive in vivo applications are limited by the rapid scattering and absorption of light in tissue. Multi- photon imaging addresses this limitation by exciting fluorophores through the near simultaneous absorption of multiple photons11. This technique allows for excitation with longer wavelength photons that interact less severely with tissue. In addition, the

7 spectral separation of emitted light from scattered excitation light is much easier, reducing noise levels, and the distribution of excited fluorophores is more concentrated at the focal spot, increasing resolution. Still, this advanced method requires invasive procedures, like removal of a portion of skull, which attenuates optical signals significantly, and is limited to depths on the order of 1 mm, far too shallow to study more than superficial cortical layers of even small rodent brains without more invasive interventions for localized deep tissue delivery and collection of light. In addition, heating is more problematic12, compared to single-photon excitation, due to a requirement for higher intensity illumination. Luminescence-based imaging methods offer another approach towards optical imaging that relies on light emission through chemical modification of a substrate molecule by a class of naturally-occurring enzymes called luciferases13,14. While luminescent probes emit fewer photons compared to fluorophores under normal imaging conditions, this method has the advantage of extremely low background signal, as no excitation light is necessary. Luminescence imaging also eliminates the risk of excitation-induced heating and photodamage.

Photoacoustic tomography (PAT) is an emerging optical technique in which high frequency light pulses are used to elicit pressure waves that are detected by an array of acoustic sensors15,16. Computed tomography methods are then used to localize the sources of these ultrasonic waves. While this approach does allow for increased imaging depths, on the order of 1 cm, there is still a significant tradeoff between imaging depth and resolution and imaging agents for this technique are still relatively undeveloped compared to more established optical microscopy methods. In addition, invasive procedures are generally required, like removal of a portion of skull, which

8 interacts strongly with both optical and acoustic signals. Currently, PAT is mostly often used for hemodynamic imaging as blood is readily visible with this method.

Radiotracer Imaging

Positron emission tomography (PET) and single-photon emission computed tomography (SPECT), are well-established noninvasive imaging modalities for the detection of molecular probes in intact animals and have been widely used in humans.

Both methods detect high-energy photons emitted during radioactive probe decay and are sensitive to extremely low probe concentrations with limits of detection in the picomolar range17. PET utilizes radioactive probes that result in the simultaneous emission of two positrons and resolution is ultimately limited to ~ 1 mm by non- collinearities of positron emission18. SPECT relies on radioactive probes that result in single particle emission and this imaging modality resolution is ultimately limited by collimation during detection making submillimeter resolution possible if decreases in sensitivity19 are acceptable.

PET/SPECT approaches for biological imaging generally consist of the use of affinity probes that bind to target molecules, affecting radiotracer pharmacokinetic distribution, which limits temporal resolution to the order of minutes20. This approach has been used, for example, for quantitative mapping of neurotransmitter receptors within the brain21. Other functional imaging approaches that measure glucose metabolism22,23 using fluorodeoxyglucose (18F-FDG) and cerebral blood flow24 using

15 H2 O. Importantly, these approaches do not give readouts of specific molecular activity, but rather of neurotransmitter receptor distribution or metabolic activity.

Because molecular probes for PET/SPECT are ‘always on’ and cannot be biochemically modulated, dynamic ligand sensing is not possible.

Magnetic Resonance Imaging (MRI)

MRI is a powerful noninvasive imaging modality that offers an attractive combination of broad spatial coverage, almost unlimited tissue penetration, and relatively high spatiotemporal resolution on the order of seconds and hundreds of microns. MRI signal results from the net magnetization of unpaired nuclear spins of particular isotopic species, usually protons, which are most abundant in tissue in the form of water, in the presence of a strong magnetic field (B0). A simplified semi- classical description of a standard imaging sequence is as follows: a resonant radiofrequency (RF) pulse perturbs the net magnetic moment, aligned with the main magnetic field at equilibrium, tipping it into the transverse plane (normal to the main magnetic field). The magnetic moment precesses at a frequency proportional to B0 (the

Larmor frequency) resulting in an induced oscillatory current in a receiving coil when the magnetic moment is nonzero in the transverse plane. Two relevant relaxation processes occur as the system returns to equilibrium after such perturbation. The first is transverse relaxation, an exponential process described by the rate constant R2 or its reciprocal, the time constant T2. Because precession frequency is proportional to B0, small inhomogeneities over the field of view give rise to a distribution of precession frequencies, which leads to dephasing of the transverse magnetization so that the magnitude of the net transverse magnetization eventually goes to zero. The second process is longitudinal relaxation, the recovery of net magnetization parallel to B0. This exponential process is described by the rate constant R1 or its reciprocal, the time

10 constant T1. Samples, biological or otherwise, can vary in proton density, R1, and R2, resulting in inherent differences in image signal (contrast) based on local differences in water concentration and mobility.

Contrast agents generally operate through interactions with water protons that generate changes in R1 and R2. The effectiveness of these agents is specified in terms of longitudinal or transverse relaxivity (r1 or r2) defined as the change in R1 and R2 per contrast agent molecule (expressed in units of s-1 mM-1). Sensors based on this mode of action are typically defined by a change in relaxivity, Δr1 or Δr2, induced upon sensor actuation. Spin echo imaging sequences, a commonly used image acquisition scheme, are characterized by a repetition time, TR, between RF excitation pulses and an echo time, TE, between RF excitation and signal readout. The signal in this image sequence is determined by the following equation.

(1.1) �� (1 − �−�1 ∗ ��) ∗ �−�2 ∗ ��

In this scenario, as R1 increases (relative to TR), signal increases and as R2 increases

(relative to TE), signal decreases. T1-weighted scans (short TR, short TE) emphasize contrast due to differences in R1 while T2-weighted scans (long TR, long TE) highlight contrast due to differences in R2.

Single-metal agents

Contrast. Paramagnetic metal chelates constitute a large family of MRI contrast agents that operate mainly by enhancing R1 relaxation rates through interactions with coordinated water molecules25. Gadolinium (Gd) is the most commonly used metal in these small molecule complexes as Gd3+ has a high magnetic moment, with a quantum spin number of 7/2 that describes the intrinsic angular

11 momentum of a particle. The result of addition of such paramagnetic chelates to

26 aqueous solutions is a concentration-dependent increase in T1-weighted signal . The earliest clinically applied agent27, Gd-DTPA (gadolinium diethylenetriamine pentaacetic acid), was approved for use in humans by the United States Food and Drug

Administration (FDA) in 1988 under the name Magnevist. Nephrogenic systemic fibrosis (NSF) has been observed with gadolinium-based agents in a small number of patients, especially in those with impaired renal function28,29, and has been associated with systemic metal accumulation30–32. Macrocyclic chelators, like Gd-DOTA

(gadolinium 1,4,7,10-tetraazacyclododecane-N,N',N'',N'''-tetraacetate) have reduced these issues32,33 and use of these agents is increasing relative to linear gadolinium chelates34. In general, these agents are not cell-permeable in order to reduce metal accumulation. Manganese chelates represent an alternative to gadolinium-based contrast agents35 with reduced toxicity and cell-permeable manganese-based agents have also been developed36.

Sensing. A number of T1-weighted sensors have been developed using small molecule and protein metal chelators to sense many different physiological stimuli including calcium37, dopamine38–40, serotonin41, light42–44, reactive oxygen species45,46,

47–49 and enzymatic activity . These sensors generate changes in R1 through changes in water access upon ligand binding or other induced structural changes. While this contrast mechanism is well developed and has worked reliably in many contexts, these stoichiometric single-metal sensors, where one analyte interacts with one metal complex, are inherently insensitive, as the change in R1 induced by a single analyte molecule is small. Therefore, these first-generation sensors need to be employed at

12 concentrations ~ 10 - 100 µM in order to generate appreciable signal changes. This requirement represents a significant limitation for biological sensing as most molecules are present at physiological concentrations well below even 1 µM, and delivery of high contrast agent concentrations in tissue can be challenging. Therefore, there is a significant need for the development of next-generation molecular MRI contrast agents capable of generating readily detectible signal changes with nanomolar analyte sensitivity.

Mineralized Nanoparticles

Contrast. Superparamagnetic iron oxide nanoparticles (SPIOs)50, each composed of hundreds to thousands of mineralized iron atoms, represent another class of MRI contrast agent that most often operates by a T2-weighted mechanism where magnetic field inhomogeneities increase R2, decreasing T2-weighted signal, however small nanoparticles also exhibit longitudinal relaxivities similar to gadolinium chelates51.

Ferumoxytol is currently the only SPIO agent available for clinical use; however, it is approved as a treatment for anemia and not for imaging applications, though it is used off-label for angiography in patients who cannot be given gadolinium-based contrast agents due to renal failure. SPIO particles typically have diameters on the order of 20 -

100 nm, but more recently exceedingly small particles have been synthesized with diameter ~ 4 nm to improve particle spread in tissue and improve T1 relaxation properties51. While SPIO particles are inherently insoluble in aqueous solutions, biocompatible surface coatings can be employed to improve solubility significantly52.

Genetically encoded paramagnetic nanoparticles, like the iron-binding protein complex ferritin53, have been explored as an alternative to both circumvent the difficulty of

13 delivering nanoparticles as well as to allow sensor access to the intracellular space, as compared to exogenously applied nanoparticles that are not cell-permeable. Ferritin nanoparticles, however, produce much weaker contrast effects compared to SPIOs due to the fact that they incorporate a less magnetic form of mineralized iron oxide. In addition, to generate any visible contrast due to ferritin expression in vitro, supplementary iron complexes must be supplied, providing an additional challenge for in vivo applications.

Sensors. Molecular sensors based on this class of contrast agent operate through selective aggregation/disaggregation in response to a physiological signal of interest, for example neurotransmitters54, calcium55,56, and enzymatic activity57. R2 effects are generally enhanced upon aggregation, though precise changes depend on the size of the nanoparticles, the relative interparticle distance, and the overall size of aggregates58. While the use of small nanoparticles < 5 nm aids in agent spread upon injection, these smaller nanoparticles also generate reduced signal changes upon aggregation. A typical molecular sensor consists of either two distinct species of nanoparticles, where one species is functionalized with a tethered analyte and the other is functionalized with a corresponding binding protein54, or the use of a multivalent crosslinker55. While this mechanism is capable of generating substantial changes in signal, it is not well-suited for fast reversible sensing, as the kinetics of disaggregation are especially slow due to the large number of molecular interactions that hold aggregates together54. In addition, this mechanism depends strongly on nanoparticle concentrations, a potential problem for in vivo applications.

Engineered Hemodynamics and the BOLD effect

Contrast. A unique source of endogenous contrast is available in form of iron- rich blood, the basis for contrast changes observed in functional MRI (fMRI) as well as in other hemodynamic imaging modalities. Deoxygenated, but not oxygenated hemoglobin is paramagnetic, and the difference in magnetic susceptibility between partially deoxygenated blood and surrounding tissue therefore results in T2* contrast, where T2* is the observed T2 when imaging sequences that do not correct for static magnetic field inhomogeneities are used, like gradient echo imaging. Functional MRI

(fMRI) of brain activity depends on the ability of active neurons to elicit transient increases in local blood flow, through neurovascular coupling, resulting in vasodilation and increased blood oxygenation, together resulting in increases in MRI signal known as the blood oxygenation level dependent (BOLD) effect59. The main advantage of this method for functional brain imaging is the lack of any need for exogenous contrast agent making it a completely noninvasive approach applicable in humans60, however the molecular insight gained from this approach is limited, as the mapping of molecular activity onto changes in blood flow is not well-determined61,62.

Sensors. While hemodynamic imaging is not inherently a molecular imaging approach, several innovative strategies have been employed to take advantage of the endogenous blood contrast for molecular imaging by artificially introducing engineered neurovascular coupling mechanisms activated by specific molecular events.

Successfully implemented strategies include an intracellular calcium-dependent nitric oxide synthase enzyme63 and vasoactive peptides, modulated by ligand binding64 or protease activity65, that activate receptors on vascular smooth muscle cells (VSMCs) at

15 nanomolar concentrations, decreasing vascular muscle tone and inducing vasodilation66. The main advantages of this approach are its sensitivity and the comparative ease of noninvasive probe delivery, given the low sensor concentrations required compared to paramagnetic contrast agents. However, this technique also comes with a number of key limitations. While the nanoparticle and paramagnetic complex contrast mechanisms presented here are applicable to many different biological systems, engineered hemodynamics is not necessarily applicable to other organs beyond the brain. Saturation of the hemodynamic response limits maximum possible signal changes, possibly on the order of ~10-20% reported during strong stimulation in a few examples67,68, though typically BOLD fMRI studies69 report signal changes of approximately 1 – 3% . For comparison, intracranial injection of 10 µl of

100 nM calcitonin gene-related peptide65 over ten minutes led to a BOLD signal change of approximately 6%. Hemodynamic responses are also relatively broad70, limiting spatiotemporal resolution to ~ 1 mm and ~ 4 – 5 seconds, respectively, and are highly variable depending on the physiological state of the animal including strong dependence on the anesthetic agent used71–73, and the depth of anesthesia. In addition, endogenous hemodynamic fluctuations represent a significant confounding source of background signal that must be accounted for. While hemodynamic fluctuations can be reduced through the systemic application of nitric oxide synthase

74 inhibotors , this approach is only partially effective. Additionally, T2* imaging sequences are much more prone to image artifacts to due magnetic field inhomogeneities as compared to spin echo-based imaging sequences typically used with T1- and T2-weighted sensors. Finally, because vasoprobes interact with

16 corresponding receptors with low nanomolar affinity75, a necessary feature to achieve high sensitivity, they will likely exhibit non-ideal kinetics for sensing biological activity in applications that require high temporal resolution, for example, for visualization of neurotransmitter signaling in the brain as sensor off rates will be limited by slow vasoprobe unbinding or receptor internalization.

Future developments

Despite a number of promising developments towards next-generation imaging agents, based on novel contrast mechanisms designed to address key limitations of single-metal sensors, the potential of molecular MRI for the interrogation of biological systems is still substantially limited by the capabilities of existing probes and sensing approaches. Ideally, MRI probes should be readily deliverable through noninvasive methods, detectible at low sensor concentrations, and responsive to physiologically relevant signals. Engineered hemodynamics represents a unique approach towards realizing these goals, but the reliance of this approach on underlying physiology to generate contrast changes represents a major source of variability and likely will suffer from background hemodynamic fluctuations even with the application of drugs. In addition, attempts to adapt this sensing strategy to the measurement of specific biological signals of interest is still in early stages of development. Therefore, there remains a need for novel sensors and contrast mechanisms that offer improved sensitivity and signal change over stoichiometric single-metal sensors capable of generating contrast independent of underlying physiology allowing for a much wider range of applications including imaging in biological systems beyond mammalian brains.

Figure 1-1: MRI sensor mechanisms

All images reproduced with permission.

37 A) Reproduced from Barandov et al. Representative diagram of a single-metal T1- weighted MRI sensor. Calcium binding to the sensor generates changes in water (blue spheres) access to a chelated manganese ion (pink sphere). Inset shows MRI signal.

B) Reproduced from Barandov et al.37 Measure calcium response of the sensor shown in A, in HEK 293F cells partially permeabilized with thapsogargin, to calcium

18 concentrations modulated by adding calcium ionophore calcimycin and varying media calcium concentrations.

C) Reproduced from Okada et al.54 Representative diagram showing a dopamine- sensitive nanoparticle aggregation sensor.

D) Reproduced from Okada et al.54 Chemical structures of dopamine and a tethered dopamine analog used in the sensor for C.

E) Reproduced from Okada et al.54 Response to addition of free dopamine to sensor in C (DaReNa), or control nanoparticles with tethered ligand alone (Tyr-PEG-SH), or binding protein alone (9D7*). While 9D7* binds free dopamine with an affinity ~ 1 µM, DaReNa responds to free dopamine concentrations approaching 100 uM.

F) Reproduced from Ohlendorf et al.64 Representative diagram showing action of vadodilatory peptide PACAP on vascular smooth muscle cells and resulting MRI signal.

G) Reproduced from Ohlendorf et al.64 Representative diagram showing a ligand- sensing mechanism using PACAP, along with a tethered analyte analog (black), and analyte-binding domain (green).

H) Reproduced from Ohlendorf et al.64 Observed BOLD signal response after intracranial implantation of biotin-functionalized cells and delivery of biotin-responsive PACAP sensor.

Light-LisNR: Sensing Light in Deep Tissue with MRI

Abstract

Molecular magnetic resonance imaging (molecular MRI), a technique that uses contrast agents to relay molecular and cellular events into MRI signal changes, is a promising approach for the study of biology that leverages the broad spatial coverage, high spatiotemporal resolution, and noninvasiveness of MRI. This approach is currently limited, however, by a lack of sufficiently bright and sensitive contrast agents. Here we introduce Liposomal Nanoparticle Reporters (LisNRs), a novel class of MRI contrast agent that operates by an unprecedented mechanism in which analyte-dependent regulation of liposomal membrane water permeability determines water access to a large, concentrated pool of encapsulated paramagnetic complexes. This design allows for the modulation of water access to many contrast agent molecules simultaneously, resulting in dramatically improved signal changes compared to existing T1-weighted MRI sensors. Using this concept, we build Light-LisNR, which transduces light into MRI signal changes. Light-LisNR enables three-dimensional light mapping by MRI, a capability useful for the experimental determination of light delivery profiles in vivo in a number of experimental applications, for example for the characterization and development of novel techniques for noninvasive light delivery techniques for optogenetics. Light mapping with MRI will also generate necessary experimental data for the refinement of models of light spread within complex structures like the brain. We show that Light-LisNR is capable of generating large, reversible T1-weighted MRI signal

20 changes in response to light both in vitro and in live animals, and we use Light-LisNR to map light delivered to the brain through an LED-coupled optical fiber.

Introduction

In recent decades, there have been major advances in the development of molecular imaging agents—chemical probes that alter image contrast in response to molecular and cellular phenomena. These agents, combined with noninvasive imaging methods, offer unique potential for large-scale mapping of cellular and molecular events and could be valuable for applications ranging from basic biological investigations to clinical evaluations of disease. Perhaps the largest strides have been made in the development of agents for optical imaging modalities and notable achievements include spectrally resolved, genetically encoded agents8; fluorescent and luminescent proteins that can report on gene expression, important signaling molecules, sub-cellular localization, and other biomolecular interactions. Applications of optical molecular imaging in vivo, however, are limited substantially by the rapid scattering and absorption of light in tissue. There is need, therefore, for the development of alternative molecular imaging modalities better suited for large scale noninvasive in vivo imaging.

MRI is a leading noninvasive imaging modality that offers almost unlimited imaging depth, whole-organ coverage, and relatively high spatiotemporal resolution.

First-generation molecular sensors for MRI have been developed for a number of biological targets40,41,46 that function through a common mechanism; a signal of interest interacts stoichiometrically with a single paramagnetic complex giving a change in water coordination of the paramagnetic metal ion resulting in a T1-weighted MRI signal

21 change. This mechanism, however, is inherently insensitive as the signal change generated by a single paramagnetic metal complex is small, necessitating the use of 10

– 100 µM sensor concentrations to generate appreciable signal changes. Delivery of such high contrast agent concentrations can be difficult to achieve by noninvasive means, and this is especially true in the brain due to the blood brain barrier (BBB). In addition, many biological molecules of interest are present at concentrations well below

1 µM making molecular imaging impossible with single-metal sensors. A notable exception is free intracellular calcium, which is present at nanomolar to micromolar concentrations but is heavily buffered in cells allowing for the use of micromolar probe concentrations.

To address these limitations in signal change and sensitivity, several innovative contrast agent strategies are being developed. Mineralized iron oxide nanoparticles generate strong magnetic field inhomogeneities that result T2-weighted MRI signal and a number of sensors have been constructed that rely on reversible nanoparticle aggregation54,55,76. However, this approach suffers from several key limitations. Iron oxide nanoparticles are hard to deliver, do not spread easily in tissue, and can have significant iron toxicity at high concentrations. In addition, because nanoparticle aggregates are held together by a large number of binding interactions that need to be reversed through competitive free analyte binding, these sensors suffer from poor sensitivity and slow kinetics. For example, a recently reported dopamine-sensitive nanoparticle aggregation sensor showed sensitivity of approximately 100 µM54 even though the dopamine-binding domain used, BM3h-9D739, binds dopamine with an affinity of 1 µM. Many sensors based on the mechanism also require the use of two

22 distinct species of nanoparticles that must be present at specific relative ratios offering another challenge for in vivo applications.

Engineered hemodynamics is a promising and creative approach that bypasses the need for traditional exogenous metallic contrast agents by instead regulating hemodynamic responses using blood as an endogenous source of contrast. This mechanism has been used for sensing intracellular calcium, with calcium-dependent nitric oxide synthase enzymes (NOSTICs)63, and for protease65 and biotin64 sensing using modified vasoactive peptides that exhibit changes in affinity for receptors on vascular smooth cells in response to a signal of interest. Vasopeptide-based approaches offer the potential for improved sensitivity as they are capable of generating contrast changes at nanomolar analyte concentrations, however, this contrast mechanism has some key limitations. First, hemodynamic responses are broadened, reducing spatiotemporal resolution, and are also highly variable depending heavily on the physiological state of the animal, for example the anesthetic agent used and the depth of anesthesia71–73. There is also a limit on maximal achievable signal changes as hemodynamic responses saturate. Furthermore, background changes in blood flow result in signal fluctuations that are not easily distinguishable from sensor-induced signal changes. Drugs can be used to suppress background hemodynamic signals, however they are only partially effective74. In addition, hemodynamic contrast is most visible with T2*-weighted MRI, an imaging protocol that is especially sensitive to magnetic field inhomogeneities, making it prone to artifacts. Finally, because the binding affinity of modified peptides for VSMC receptors is in the nanomolar range likely resulting in poor off kinetics due to slow receptor unbinding making this approach less

23 suitable for measuring signals that vary with high frequency, like neurotransmitter concentrations.

Therefore, there remains a major need for new MRI contrast mechanisms with improved sensitivity that function independently of hemodynamics. Here we introduce

LisNRs, a novel class of liposomal MRI contrast agent that offers improved sensitivity and signal change by simultaneously modulating water access to a large, concentrated pool of paramagnetic complexes. We demonstrate this promising sensor platform in vitro and in vivo to sense light with MRI.

Results

Liposomes are a versatile class of biologically compatible nanoparticle that have been used to enhance circulation time and tissue accumulation of drugs and contrast agent that can, conveniently, be encapsulated within either the hydrophobic bilayer or the hydrophilic lumen. It has long been appreciated that liposome encapsulation of

MRI-visible paramagnetic complexes decreases their efficacy77. To circumvent this issue, metal-chelating lipids have been used to label liposomes for MRI78–80.

Paramagnetic liposomes have also been made sensitive to a variety of inputs including both endogenous signals, like pH81 and lipase82 activity, as well as exogenous inputs like heat80, ultrasonic energy83,84, and light85 in order to trigger content release in a targeted manner. In all of these examples, liposomes are permeabilized irreversibly.

Here we introduce a novel concept, the reversible modulation of MRI signal from paramagnetic liposomes through changes in bilayer water permeability, for molecular sensing. We first used an established theoretical framework77,86 to evaluate the

24 feasibility of LisNRs quantitatively. We estimated maximal R1 changes possible using paramagnetic liposomes at realistic volume fractions (f), the fraction of all water molecules that are intraliposomal, of 0.1% and 0.01%, which correspond to concentrations of ~ 3 and 0.3 nM for liposomes of diameter 100 nm and final gadolinium concentrations of 220 µM and 22 µM, respectively (Fig. 2-1). Liposome synthesis usually resulted in volume fractions of 2 – 3% without further concentration, allowing for in vivo volume fractions as high as 0.5% after dilution, however it may be desirable to use liposomes at lower volume fractions that may be more easily achievable with noninvasive delivery methods. To evaluate whether the water permeability of liposomal membranes could be made sufficiently low to effectively quench encapsulated contrast agent, we calculated values of τ, the average liposomal water residence time, for liposomes with diameters of 30 nm and 100 nm whose bilayers are made up of low fluidity, fully saturated phospholipids (Fig. 2-1). Our results indicate that even small unilamellar liposomes (~30 nm diameter), which have higher surface area to volume ratios, are sufficiently impermeable to efficiently quench MRI signal from encapsulated contrast agent when made up of low fluidity phospholipids.

To confirm experimentally the possibility for modulation of the longitudinal relaxation rate (R1) through changes in liposomal bilayer fluidity and water permeability, we constructed a series of liposomes made up of different mixtures of the fully saturated lipid 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC), and the fluidizing phospholipid 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC), which contains a single carbon-carbon double bond in one fatty acid chain (Fig. 2-1). As expected, we find that, at constant liposome concentrations, R1 increases dramatically with increasing

POPC composition. These differences in R1 are not due to differences in free contrast agent levels resulting from incomplete purification or contrast agent leakage after purification as demonstrated by further size-exclusion column chromatography of purified liposome samples (Fig. 2-1).

Having established, experimentally, a basis for the LisNR contrast mechanism, we next set out to construct a reversible sensor based on this principle. For this demonstration we chose light as an input signal as light can controlled more easily in vitro and in vivo than chemical concentrations as it can be turned on and off easily.

Several moieties are capable of reversible photoisomerization making light an ideal signal to demonstrate the reversibility of this contrast mechanism87. In addition, there are a number of interesting applications for light mapping in vivo, including characterization of light delivery methods for optogenetics. Several light-sensitive MRI contrast agents have been reported43,44, including small-molecule chelates that operates by a single-metal contrast mechanism in which a light-induced conformational change generates a change in the number of water protons interacting directly with a chelated paramagnetic ion. A light-induced nanoparticle aggregation strategy has also been developed42, however, it relies non-specific hydrophobic interactions making translation in vivo unlikely. The novel contrast mechanism described here has the potential to increase both the magnitude of signal changes and sensitivity to light.

To generate light-induced changes in membrane fluidity and water permeability, we incorporated azoPC88, a photoisomerizable azobenzene-containing phospholipid, into paramagnetic liposomes (Fig. 2-2). Unsaturated lipids increase membrane fluidity because fatty acid carbon-carbon double bonds hinder lipid-lipid packing by introducing

26 a region with increased local stiffness89. We expect that azoPC in the bent cis conformation, as compared to the linear trans conformation, will differentially perturb lipid packing and increase membrane fluidity in a manner similar to differences observed for liposomes composed of as compared to DPPC (Fig. 2-1). We made liposomes containing different relative amounts of azoPC and used blue and UV LEDs to measure R1 changes resulting from azobenzene photoisomerization. We observed reversible, light-dependent R1 changes in liposomes containing up to 10% azoPC, while higher azoPC concentrations resulted in only partially reversible responses (Fig. 2-2).

The relative instability of paramagnetic liposomes with high azoPC concentrations is not entirely surprising given a previous report of transient increases in small molecule permeability during isomerization from cis to trans, and trans to cis, of liposomes composed of 100% azoPC90. However, even liposomes containing low amounts of azoPC leaked contrast agent when incubated at 38 °C for 10 minutes, a problem for in vivo applications (Fig. 2-2). To address heat stability, we added cholesterol and found that incorporating 40% cholesterol was sufficient to eliminate heat-induced leakage.

After the addition of cholesterol to lipid mixes, we also observed dramatic increases in light-dependent R1 changes, and increased stability at higher azoPC concentrations

(Fig. 2-2).

We quantitatively characterized the light responsiveness of Light-LisNR by measuring sensitivity to UV and blue light in buffer (Fig. 2-2). We used LEDs in combination with neutral density filters and varied light exposure times to deliver light doses from 1014 - 1017 incident photons to liposome samples. We were able to generate

16 ~ 20% changes in R1 with 10 photons at a liposome concentration of 3 nM, and up to

~70% changes in R1 with saturating illumination. This liposome concentration corresponds to a final gadolinium concentration of 220 µM. By comparison, a single-

43 metal light-sensitive T1-weighted sensor, spiropyran-do3a-gadolinium , showed less

16 than a 2% change estimated change in R1 after illumination with ~1.8 * 10 photons at contrast agent concentrations of almost 160 µM in buffer, and only an estimated 6% change in R1 with saturating illumination. A nickel-based T1-weighted light sensitive contrast agent44 generated much larger relative changes in relaxivity, on the order of

80%, however this agent exhibits low relaxivity even in the active conformation (r1 ~

0.15 mM-1 s-1, approximately 25 times lower than gadoteridol), and is not very soluble in water making it difficult to achieve sufficient concentrations in vivo.

We next sought to demonstrate the use of Light-LisNR in live animals as a number of useful applications could be enabled by light mapping in vivo. Optogenetics, the use of light-activated ion channels to modulate neural activity, has revolutionized neuroscience but requires the delivery of high intensity light (> 1 mW/mm2). This is most often accomplished using an implanted optical fiber; however, the precise placement of the fiber can vary significantly between experiments. Observed positive functional responses are often cited as proof that sufficient light intensities have been achieved, however, this approach is incomplete as it does not account for the possibility of false negative findings, due to insufficient light intensity or animal-to-animal variability in the tissue activation volume. Noninvasive illumination technologies, like mechanoluminescent ZnS nanoparticles that emit blue light in response to ultrasonic perturbation, represent innovative approaches towards solving the challenge of light delivery in vivo and have the potential to expand optogenetic capabilities considerably.

For both of these examples, mapping of illumination patterns with Light-LisNR would provide valuable data for the characterization and validation of light intensities achieved in vivo which currently can only be accomplished through implantation of an optical fiber for light collection which provides only a single, highly-directional measure of light intensity.

We performed bilateral intracranial injections of Light-LisNR, or control liposomes lacking azoPC, in rats and implanted an optical fiber to deliver light unilaterally using blue or UV fiber-coupled LEDs (Fig. 2-3). Initial blue light exposure did not lead to any response, implying that liposomes were initially in the trans conformation. Subsequent

UV and blue light exposure led to robust T1-weighted signal changes of up to 30-40% that were completely reversible over multiple cycles of light exposure. No light-induced signal changes were observed from azoPC liposomes contralateral to fiber implantation, or from control liposomes (Fig. 2-3, S2-2). We varied light exposure times from 10 minutes to 30 seconds to explore light sensitivity in vivo and found that we were reliably able to detect light exposures as short as 2 minutes, corresponding to approximately 2 *

1016 incident photons, in all animals with mean signal change ~ 10% (Fig. 2-5).

Notably, we were able to map both blue and UV light over relatively large volumes of ~

10-15 mm3 made up of hundreds of voxels (Fig. 2-4). Light mapping was limited by the spread of light from the implanted optical fiber rather than the spread of contrast agent, which generally covered volumes > 30 mm3. This is a clear demonstration that Light-

LisNR is sufficiently sensitive to map light at relevant intensities used for optogenetics as the LED light sources used here are much lower intensity (~ 0.3mW) at the fiber tip than is typical for in vivo optogenetic excitation (> 100 mW).

Discussion

Here, we demonstrate for the first time a potent new class of MRI sensor,

LisNRs, capable of generating large MRI signal changes at nanomolar sensor concentrations addressing major limitations of stoichiometric single-metal T1-weighted

MRI sensors. Signal amplification is accomplished by regulating water access to a large number of paramagnetic complexes simultaneously through modulation of water transport across the lipid bilayer of paramagnetic liposomes. We evaluate the basic viability of this concept both theoretically, using a simple two-compartment model, and experimentally, by modulating liposomal membrane permeability with the fluidizing lipid

POPC. Using a similar strategy, we incorporate azoPC into paramagnetic liposomes to generate reversible light-induced changes in bilayer fluidity and water permeability through fatty acid isomerization in order to sense light by MRI deep in the brain, where we observed large in vivo T1-weighted signal changes of 30 to 40% and we were able to map light-induced signal changes over large volumes (Fig. 2-5). In vitro, we observed approximately an order of magnitude improvement in sensitivity over an existing light-sensitive paramagnetic complex, spiropyran-do3a-gadolinium43 at similar metal concentrations.

In addition to the unique sensing mechanism of LisNRs, these liposome-based nanoparticles exhibit excellent biocompatibility; the sensor scaffold is constructed mainly of naturally-occurring phospholipids and the encapsulated gadolinium chelate contrast agent has been clinically approved for use in humans. In this instance, liposomes were delivered by intracranial injection, a well-tolerated if invasive procedure that precludes whole-brain imaging, however, LisNRs are potentially compatible with

30 non-invasive delivery methods due to the low sensor concentrations required. We are also encouraged by the ease with which even the relatively large (100 nm diameter) liposomes used here spread within the brain. In future studies, the use of smaller liposomes will likely be beneficial for both noninvasive delivery and spread and unilamellar liposomes are generally stable for diameters as small as 20-30 nm.

A long-term goal for light-sensitive MRI contrast agents involves the use of genetic techniques for conditional luciferase enzyme expression, whose activity is visualized by MRI, allowing the study of gene expression in the brain. For example, with this technology MRI could be used to detect spatial changes in expression of genes involved in neural plasticity after a behavioral task. However, large improvements in sensitivity would be necessary as we estimate strong expression of Gaussia luciferase, could generate only on the order of 3*1013 photons/s/cm2. Ideas for improving Light-

LisNR sensitivity and signal change include loading higher contrast agent concentrations into liposomes, for example using multivalent polymeric MRI contrast agents which would also allow the use of higher azoPC concentrations without contrast agent leakage, increasing efficiency of light capture. Light-gated water-permeable channels represent another approach to modulating membrane water permeability that may improve sensitivity to light, depending on the sensitivity and water-permeability of the channel used. A strategy for actuating LisNRs using light-sensitive proteins, for example LOV domains91, that capture light with much higher efficiency compared to small molecules, could improve sensitivity substantially. Finally, protein engineering approaches are also being applied to luciferase enzymes to produce brighter luciferase enzymes and molecular sensors92.

It is important to note that the LisNR contrast mechanism present here can be readily adapted to sense any signal that can be relayed into a change in membrane water permeability, done in this case through lipid photoisomerization. An exciting possibility for implementing changes in water permeability is the use of ligand-gated water-permeable channels. By engineering gating mechanisms into such channels, we anticipate increasing the scope of signals detectible with LisNRs including for molecular sensing.

Materials and Methods

Animal procedures

All animal procedures were conducted in accordance with National Institutes of

Health guidelines and with the approval of the MIT Committee on Animal Care.

Experiments were performed on 9 male Sprague Dawley rats weighing between 350 and

450 g.

Modeling

To model the relationship between R1, MRI signal, and bilayer water permeability for paramagnetic liposomes, we used a two compartment model77. This model is valid for relatively small volume fractions (f ≤ 10%) as it neglects the signal contribution of intra-liposomal water protons. This assumption is valid for all experimental conditions tested as liposomes were used at f ~ 0.1 - 1%. This model also assumes that water exchange is not diffusion-limited, a valid assumption in all cases as the time it takes for a water molecule to diffuse a characteristic distance of 100 nm is approximately 4 microseconds. The following equations, derived from the model, relate R1 values to the 32 average lifetime of water molecules within liposomes (τ) and the lipid bilayer water permeability (P). Related variables include liposome diameter (d), volume (V), surface area (S), and volume fraction (f); background R1 (R1b), the paramagnetic metal complex contribution to R1 (R1para), the relaxivity (r1para) and intraliposomal concentration (Cpara) of the paramagnetic metal complex, and the intraliposomal T1

(T1ves).

� � (2.1) � = �� = �6� 1 1 (2.2) �1�� = �(�1para ∗ �para) + ��1b

� ( ) 2.3 �1�� ≡ �1 − �1b = �(�1ves + (�⁄6 ∗ �))

To estimate MRI signal changes, we used the signal equation for spin echo pulse sequences, assuming the echo time is sufficiently short to make T2-weighted signal contributions negligible.

(2.4) �� ∝ (1 − �−�1∗��)

Light sensitivity required to sense luciferase activity

We focus on Gaussia luciferases (GLuc), which are particularly bright and are spectrally-compatible with azobenzene photoisomerization (peak emission ~ 480 nm).

Light output from existing GLuc variants is reported to be 7 – 30 photons/s/molecule93.

We approximate the illumination intensity by considering a cubic volume element and estimating the total photon output as the photon flux through one face of the cube (1/6 of the total light output). In a 1 µL volume (face area 0.01 cm2), assuming an effective luciferase concentration of 100 nM, GLuc could generate ~ 3e13 photons/s/cm2.

Liposome synthesis and purification

In brief, unilamellar paramagnetic liposomes (LUVETs) were made using the thin film rehydration and extrusion method and were purified by size exclusion column chromatography. Liposome concentrations were determined by ICP-MS.

Unless otherwise stated, lipids were purchased from Avanti Polar Lipids

(Alabaster, AL). AzoPC was kindly synthesized and provided by Johannes Morstein and Dirk Trauner (NYU). Lipids (1.65e-6 mol total) were co-dissolved in chloroform, with the exception of phosphotidyl glycerol which was dissolved in 97/2/1 (v/v) chloroform/methanol/water, and dried overnight under high vacuum. For long term storage, the resulting lipid films were kept at -20 °C in sealed vials (PTFE septum with parafilm) in a sealed secondary container with calcium sulfate. ProHance (Gadoteridol) was purchased from MIT Pharmacies and diluted to 220mM gadolinium with distilled water. Gadoteridol solution (1.1 ml, 220 mM gadolinium) was added to a lipid film aliquot and the resulting solution was incubated at 58 °C using a water bath for at least

2 hours with brief vortexing every ~10-20 minutes. The solution was then subjected to three freeze-thaw cycles with liquid nitrogen. To extrude liposomes, we used a liposome extrusion kit from Avanti Polar Lipids (Alabaster, AL) which uses 1 ml syringes to force the aqueous lipid solution through polycarbonate filters of defined pore size (≤ 200 nm for predominantly unilamellar liposomes). The lipid solution was forced through double- stacked filters 21 times while maintaining temperatures above the highest phase transition temperature of the individual lipid constituents (typically 60 °C) a heating block. The resulting liposome solution was purified by gravity flow size exclusion column chromatography using resin Sepharose CL-4B purchased from Cytiva

(Marlborough, MA) and buffer (10mM HEPES (pH 7.4 with HCl), 139mM NaCl) to remove unencapsulated gadoteridol. The resulting purified liposome solutions were quantified using an Agilent ICP-MS instrument (MIT CEHS Core Facility) using standards from 0 – 1000 ppb gadolinium with 10 ppb erbium as an internal standard.

Liposome size were characterized by dynamic light scattering. The fraction of free contrast agent remaining after purification (or after heating for heat-stability tests), typically ~3-5%, was determined by further size exclusion chromatography and ICP-MS of liposome-associated (early) and free contrast agent (late) fractions. Liposome solutions were stored in the dark at 4 °C (never frozen) for up to several months.

Light sources

Light was delivered in vitro using UV (365 nm, ~ 8 mW/cm2) and blue (460 nm,

~24 mW/cm2) LED flashlights (Amazon). Light intensity was determined using a digital optical power meter, UV-compatible sensor, and neutral density filters to decrease intensity, all purchased from Thorlabs (Newton, NH).

Light for in vivo experiments was delivered by a multimode optic fiber with a diameter of 200 µm and a 0.48 numerical aperture from Thorlabs (Newton, NJ). After removing the cladding from the tip, the fiber delivering either ultraviolet or blue light for liposome activation/inactivation was inserted via a craniotomy and glued to the skull with biocompatible UV glue. The amount of glue for holding the fiber in place was kept at a necessary minimum for the fMRI experiments to reduce MR image distortions.

During the MRI experiment the fiber was then connected to the respective light source, either a UV, 365 nm, LED from Thorlabs (Newton, NJ) or a blue, 470 nm, LED from NPI

(Tamm, Germany) via a SMA connector.

In Vitro Imaging

MRI was performed on a 9.4 T BioSpec small animal scanner (Bruker, Billerica,

MA) using a 70 cm inner diameter linear volume coil (Bruker). Scanner operation was controlled using the ParaVision 5.1 software (Bruker). T1-mapping experiments were performed using a series of MSME spin echo scans with echo time (TE) = 11ms, matrix size = 256 by 256, field of view (FOV) = 5 cm by 5 cm, slice thickness = 2 mm and excitation angle = 90° with repetitions times (TR) from 30 ms to 5 seconds. The number of scan averages was set such that total scan time at each TR was at least 7 minutes.

Raw FID data was reconstructed and analyzed using a custom Matlab Mathworks (Natick,

MA) script.

In Vivo Imaging

Adult male Sprague–Dawley rats (350–450 g) were purchased from Charles

River Laboratories (Wilmington, MA). After arrival, animals were housed and maintained on a 12 hour light/dark cycle and permitted ad libitum access to food and water. All procedures were carried out in strict compliance with National Institutes of Health guidelines, under oversight of the Committee on Animal Care at the Massachusetts

Institute of Technology. Animals were anesthetized with isoflurane (3% for induction,

2% for maintenance) and placed on a water heating pad from Braintree Scientific

(Braintree, MA) to keep body temperature at 37 °C. Animals were then fixed in a stereotaxic frame, and topical lidocaine was applied before a 3 cm lateral incision extending from bregma to lambda was made, exposing the skull. Craniotomies (0.5

36 mm) were drilled bilaterally over the caudate Putamen (CPu), 0.5 mm posterior and 3.0 mm lateral to bregma. 28-gauge infusion cannulae were lowered to 6.5 mm below the surface of the skull through each craniotomy and were held in place by the stereotactic arms. 15 μL of liposomes (f = 2%), light-responsive (20% azoPC, 30% distearoylphosphatidylcholine, 40% cholesterol, 20% dipalmitoylphosphatidylglycerol) or non-responsive (20% 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine, 30% disteroylphosphatidylcholine, 40% cholesterol, 20% dipalmitoylphosphatidylglycerol) for control experiments, were infused over the course of 2 hours. Ten minutes after the injection, infusion cannulae were slowly removed from the brain, and the craniotomies were closed with bone wax (CP Medical, Inc. Portland, OR). The fiber was lowered through a third craniotomy (3.0 mm posterior and +3.00 mm lateral to bregma), with an angle of 21° in anterior-posterior direction until 7.5 mm below the surface of the skull, to reach the location of where liposomes were previously infused. Animals were then transferred into a custom rat imaging cradle, fixed with ear bars and bite bar, maintained under 2% isoflurane anesthesia, and kept warm using a recirculating water heating pad for the duration of imaging.

MRI was performed on a Bruker 9.4 T BioSpec small animal scanner (Billerica,

MA) using a transmit-only 70 cm inner diameter linear volume coil made by Bruker

(Billerica, MA) and a receive-only 3x1 array-coil with openings through which the fiber was led through to then be connected to the respective light sources outside of the scanner room. Scanner operation was controlled using the ParaVision 6.01 software from

Bruker (Billerica, MA).

T1-mapping was carried out using a series of MSME spin echo scans with echo time (TE) = 5 ms, matrix size = 128 by 64, field of view (FOV) = 30 by 18 mm, slice thickness = 1 mm, with repetition times (TR) from 200 ms to 3 seconds. The number of scan averages was set such that total scan time at each TR was at least 2 minutes. Raw

FID data was reconstructed and analyzed using a custom Matlab Mathworks (Natick, MA) script.

Multislice T1-weighted fast low-angle-shot MRI images were acquired to evaluate the spread of liposomes in the CPu with TE = 4 ms, TR = 200 ms, field of view (FOV) =

30 × 18 mm, in-plane resolution 200 × 200 μm, and four coronal slices with slice thickness

= 1 mm. Sagittal T2-weighted TurboRARE images with TE = 30 ms, TR = 1000 ms, Rare

Factor 8, Matrix size 256 x 256, FOV = 25.6 x 25.6 and in-plane resolution of 100 x 100

µm were used to evaluate the position of the fiber.

Rapid acquisition with refocused echoes (RARE) pulse sequences were used for functional scans with the following parameters: FOV = 30 × 18 mm, slice thickness = 1 mm, matrix size = 128 x 64, and RARE factor = 4 (with 5 ms echo spacing). Functional scans of different lengths with different ON and OFF periods of either blue or UV LED light were performed and their signal change and functional maps were assessed.

All quantitative data analyses were performed using MATLAB by Mathworks (Natick,

MA). Statistical comparisons were performed using Student’s t-test, unless otherwise specified.

Figure 2-1: Adding unsaturated lipids increases membrane fluidity and R1.

A) Modeling results show the estimated ΔR1 for two liposomes concentrations, volume fraction (f) = 0.1%, or 0.01%, as a function of τ, the average water residence time in liposomes. Dotted lines show estimated τ for liposomes with diameter, d, of 30 nm and 100 nm based on a literature report86 of the permeability of liposomes made of 95% (DPPC) and 5% DSPE-PEG2000. B) Molecular structures for DPPC, DSPE-PEG2000, and POPC.

C) Experimentally-determined R1 for liposomes made of 5% DSPE-PEG2000 and a mixture of DPPC and POPC. Incorporation of fluidizing lipid POPC increased R1 (n = 2 independent experiments, error bars indicate standard deviation). D) Percent of total contrast agent leaked from liposomes in C measured by size exclusion chromatography and detected by ICP-MS (n=2 independent ICP-MS measurements, error bars indicate standard deviation).

Figure 2-2: AzoPC-containing liposomes are sensitized to UV and blue light.

A) Molecular structure of azoPC in the cis conformation, favored by UV light (360-380 nm), and the trans conformation, favored by thermal relaxation or blue light (450 – 470 nm). Figure adapted from Morstein et al.88

B) Schematic showing azoPC in the cis and trans conformations in lipid bilayers and resulting effects on water exchange across the liposomal membrane and R1.

C) Response of liposomes, at volume fraction (f) = 1%, containing 5% or 25% azoPC, to UV (365 nm) and blue (460 nm) light. Lipid mixes contain 5% DSPE-PEG2000, with the remaining portion made up of DPPC and azoPC. Inset shows MRI signal.

D) Mean R1 of 5% azoPC liposomes from C in the cis and trans conformations (n = 5 light cycles, error bars show standard deviation).

E) Response of liposomes (f = 1%) containing 20% azoPC, 40% cholesterol, 30% DPPC, and 10% DPPG over 3 light cycles of UV (365 nm) and blue (460 nm) light. Inset shows MRI signal.

F) Mean R1 of 5% azoPC liposomes from E in the cis and trans conformations (n = 3 light cycles, error bars show standard deviation).

G) R1 of liposomes in response to heating at 38 ºC for 10 minutes. Increased R1 is indicative of contrast agent leakage. Liposomes mixes are as follows: a – 85% DPPC, 10% azoPC, 5% DSPE-PEG2000 b – 65% DPPC, 20% POPC, 10% azoPC, 5% DSPE-PEG2000 c – 80% DPPC, 10% azoPC, 10% DPPG d – 70% DPPC, 10% azoPC, 20% DPPG e – 60% DPPC, 20% cholesterol, 10% azoPC, 10% DPPG f – 40% DPPC, 40% cholesterol, 10% azoPC, 10% DPPG g – 30% DPPC, 40% cholesterol, 20% azoPC, 10% DPPG

H) Sensitivity of liposome mix f to UV light at concentrations of 30 nM (f = 1%), shown in blue, and 3 nM (f = 0.1%) shown in orange.

I) Same as H but with blue light.

Figure 2-3: In vivo light sensing with Light-LisNR

The lipid mix used contains 30% DSPC, 40% Cholesterol, 20% azoPC, and 10% DPPG. Shaded regions indicate standard error.

A) Diagram showing liposome injections and subsequent optical fiber implantation into the rat striatum.

B) Typical spread of liposomes in a sagittal slice (T1-weighted RARE image, 1mm slice thickness)

C) Liposome spread in coronal section (1mm slice thickness) and positioning of ROIs used to determine percent signal change (% SC). Initial illumination with blue light did not result in any response indicating that liposomes were initially in the trans (off) conformation upon injection (not shown).

D) Mean response in ROI of fiber-implanted side (blue) versus control side (red) upon 10 minutes of UV light exposure (n=6 animals, 9 scans).

E) Same as in D, but for blue light exposure (n=2 animals, 5 scans).

F) Average percent signal change in fiber ROI (blue) and control ROI (red) during on-off cycling of 6 minutes of either UV (purple shading) or blue (blue shading) repetitive light exposure (n=2 animals, 2 scans).

Figure 2-4: Example response maps to UV and blue light exposure.

A) Percent signal change (%SC) over time in ROI drawn around area of liposome injection during one scan with 10-minute UV light exposure (purple shaded area).

B) T1-weighted signal change maps of liposome responses to UV light (+1.5 to - v0.5 from bregma), corresponding to experiment shown in A. Inset shows close-ups of area marked by the white box.

C) Percent signal change in a scan with 10 minutes of blue light exposure (blue shaded area; same animal as in A.)

D) Same as in C for blue light exposure, corresponding to the experiment shown in B.

Figure 2-5: In vivo light titration.

A) Peak percent signal change (% SC) resulting from different UV light exposure times for the fiber (blue) or control (red) side (n = 6 rats, 9 scans for 10 minutes of UV light exposure, other exposure times are 2 animals, 2 scans each). T1 RARE images show activation maps from a single slice for different illumination times for a representative animal. Error bars indicate standard error.

B) Same as A, but for blue light exposure.

Figure S2-1: Example of in vivo liposome spread and fiber positioning.

A) T1 RARE slices (coronal sections) as used for functional scans (bregma coordinates are shown). The implanted optic fiber appears dark and is visible in the left hemisphere of slice ‘AP +0.5’.

B) T2 TurboRARE (sagittal view) to confirm fiber positioning and orientation. The optical fiber appears dark and is visible in slice ‘ML 2.8’.

C) T1 RARE scan (sagittal view) to assess spread in medio-lateral direction.

Figure S2-2: Control liposomes show no response to light.

Control liposomes contain 30% DSPC, 40% cholesterol, 20% POPC, and 10% DPPG.

A) Example of T1 RARE slices with control, non-light reactive liposome infusion (one slice in the center of liposome infusion is depicted for animal C1 (left) and C2 (right), respectively.

B) Percent signal change (%SC) over time in ROI drawn around area of control liposome injection during a scan with 10 minutes of blue light exposure (blue shaded area) in the hemisphere where the optic fiber was implanted (blue) versus the hemisphere without a fiber (red), continuous line is mean response, shaded area is sem (n=2 animals, 2 scans).

C) same as in B but for UV light (n=2 animals, 2 scans). D) Percent signal change (% SC) over 30 minutes without light exposure in fiber-implanted (blue) versus non-fiber implanted (red).

Figure S2-3: Various azoPC liposomes respond reversibly to light.

Liposomes compositions used in panels A-D:

a = 40/40/10/10 (DPPC/Cholesterol/DPPG/AzoPC) b = 30/40/10/20 (DPPC/Cholesterol/DPPG/AzoPC) c = 20/60/10/10 (DPPC/Cholesterol/DPPG/AzoPC) d = 40/40/10/10 (DSPC/Cholesterol/DPPG/AzoPC)

A, B) Reversible switching was observed at 3 nM and 30 nM liposome concentrations for all liposome mixes containing at least 40% cholesterol in response to UV and blue light (indicated by purple and blue horizontal bars, respectively) over multiple light cycles.

C, D) R1 in the trans (blue) and cis (purple) state from samples in panels A and B. (n = 3 light cycles, error bars indicate standard deviation).

Figure S2-4: Liposomes are stable over weeks/months.

A) Liposomes made from 5% DSPE-PEG2000 and varying amounts of DPPC/POPC showed stable R1 values almost 300 days after synthesis during which liposomes were stored in sealed vials at 4 ºC.

B) R1 values for liposomes (30/40/20/10 DPPC/Cholesterol/AzoPC/DPPG) at 3 nM in the trans (blue) and cis (purple) conformations both 1 day and 29 days after liposome synthesis. (n = 3 light cycles, error bars indicate standard deviation).

C) Relative levels of free contrast agent for a wide range of liposome compositions. Free contrast agent was separated from liposomes (at least one day after liposome synthesis) by size exclusion chromatography and quantified by ICP-MS. Corresponding lipid mixes are listed below: a – 90/10/0 (DPPC/DPPG/POPC) b – 80/10/10 (DPPC/DPPG/POPC) b10 – 70/10/10/10 (DPPC/DPPG/POPC/Chol) b20 – 60/10/10/20 (DPPC/DPPG/POPC/Chol) c – 70/10/20 (DPPC/DPPG/POPC) c10 – 60/10/20/10 (DPPC/DPPG/POPC/Chol) c20 – 50/10/20/20 (DPPC/DPPG/POPC/Chol)

49 d – 80/20/0 (DPPC/DPPG/POPC) e – 70/20/10 (DPPC/DPPG/POPC) e10 – 60/20/10/10 (DPPC/DPPG/POPC/Chol) e20 – 50/20/10/20 (DPPC/DPPG/POPC/Chol) f – 60/20/20 (DPPC/DPPG/POPC) f10 – 50/20/20/10 (DPPC/DPPG/POPC/Chol) f20 – 40/20/20/20 (DPPC/DPPG/POPC/Chol) g – 95/5/0 (DPPC/DSPE-PEG2000/POPC) h – 85/5/10 (DPPC/DSPE-PEG2000/POPC) i – 75/5/20 (DPPC/DSPE-PEG2000/POPC) j – 85/5/10 (DPPC/DSPE-PEG2000/AzoPC) k – 65/5/10/20 (DPPC/DSPE-PEG2000/AzoPC/POPC) l – 90/5/5 (DPPC/DSPE-PEG2000/AzoPC) m – 85/5/10 (DPPC/DSPE-PEG2000/AzoPC)

Ligand-Responsive LisNRs for Molecular MRI

Abstract

Molecular magnetic resonance imaging (Molecular MRI) is a promising approach for molecular imaging that utilizes contrast agents to relay molecular events into MRI signal changes – leveraging the almost unlimited imaging depths possible with MRI for in vivo imaging of large-scale biological structures, with molecular specificity while maintaining high spatiotemporal. However, the development of contrast agents for the specific detection of molecules at physiological concentrations represents a major challenge. Here we develop the Liposomal Nanoparticle Reporter (LisNR) contrast agent platform for molecular sensing by introducing gated water-permeable channels for analyte-dependent regulation of water access to a large pool of encapsulated paramagnetic complexes. We demonstrate the potential of this approach theoretically, through quantitative modeling, and experimentally, using streptavidin (SA) and a biotinylated derivative of the pore-forming peptide gramicidin A (gA-Bio). We report signal changes in excess of 20% at low nanomolar liposome concentrations and low micromolar peptide concentrations. To achieve comparable signal changes, approximately 100 µM of a previously reported T1-weighted MRI sensor would be required39.

Introduction

Our understanding of biological systems at the molecular level has expanded dramatically with the application of new technologies, like the ability to clone and

51 express proteins exogenously, allowing for mechanistic studies of individual biological components in simplified experimental systems. One of the major themes that has emerged from the study of biology at the molecular level is the importance of messengers, signaling molecules that mediate functional interactions between spatially- separated molecular species. Small molecule messengers are implicated in a wide variety of biological processes. While we have learned much about the mechanisms through which these molecules are released and detected in biological systems, integrating this mechanistic detail into tissue- and organism-level models remains a major challenge. Molecular imaging, the use of chemical probes to transduce molecular events into image contrast, is a holistic approach that allows for the study of specific molecular events in situ with spatiotemporal discrimination. Applying this technique to study biological systems over large length scales, however, is challenging and requires sensors with high molecular specificity as well as compatible imaging modalities with fine spatiotemporal resolution, deep tissue penetration depth, and wide fields of view.

Fluorescence microscopy is a leading molecular imaging modality that uses light to excite fluorophores stimulating spectrally-shifted photon emission. A wide array of tools have been developed for molecular imaging with fluorescence microscopy, including molecular sensors for calcium94, glutamate95,96, and cyclic adenosine monophosphate (cAMP)97. Despite the variety of optical agents available to researchers and the high spatiotemporal resolution of fluorescence microscopy, noninvasive optical approaches are still significantly limited for in vivo imaging by the rapid scattering and absorption of light in tissue which limits imaging depth to less than approximately 1 mm even with advanced techniques like two-photon microscopy.

Because of the fundamental limitations of light-mediated imaging in the brain, significant efforts have been made to develop alternative noninvasive imaging modalities for molecular neuroimaging; however, these imaging modalities are generally limited by a lack of available molecular sensors. Radiotracer probes, in combination with computed tomography methods (PET/SPECT), can be detected with high sensitivity, but cannot be regulated making the reversible imaging of molecular and cellular phenomena impossible. In addition, these imaging modalities suffer from poor spatial and temporal resolution, approximately millimeters and minutes, respectively.

MRI is a promising modality for molecular imaging that offers a unique combination of broad spatial coverage, almost unlimited imaging depth, and spatiotemporal resolution on the order of ~ 100 microns and ~ 1 second, respectively. MRI-based functional imaging methods that use intrinsic contrast changes, such as the BOLD effect, have been widely used in rodents, primates, and even humans, however, these methods offer only limited insight into the underlying molecular or cellular bases of biological phenomena. A number of reversible MRI-detectable sensors for signaling molecules like calcium37,55,56, dopamine40, and serotonin41, some of which have even been employed in vivo. These protein and small molecule agents typically function by linking analyte binding to a change in water access to a paramagnetic metal ion that results in a change in R1 and T1-weighted MRI signal. This contrast mechanism suffers unilaterally from low sensitivity as the stoichiometric interaction between one analyte molecule and one paramagnetic metal ion generates only a small change in MRI signal.

This lack of sensitivity is problematic as required contrast agent (> 10 µM) are well

53 above physiological concentrations of many biological species. In addition, micromolar sensor concentrations can also be challenging to achieve in tissue.

To address these limitations, we are developing sensors based on novel contrast mechanisms designed to generate large MRI signal changes at lower sensor and analyte concentrations. Iron oxide nanoparticle aggregation is a contrast mechanism capable of generating large signal changes, however it suffers from poor sensitivity and kinetics due to the large number of molecular binding interactions that hold aggregates together. Engineered hemodynamics64,65 with vasoactive peptides is another general contrast agent mechanism for small molecule sensing that potentially offers high sensitivity. However, this approach also has a number of limitations including decreased spatiotemporal resolution, slow kinetics, variable hemodynamic responses, an upper limit on signal changes of ~ 5 – 10%, and background hemodynamic fluctuations.

Here we show the potential for molecular sensing with LisNRs, a new class of

MRI sensors that operates by an unprecedented contrast mechanism in which ligand- gated water-permeable channels modulate water access to a large, concentrated pool of liposome-encapsulated paramagnetic metal complexes simultaneously.

Results

To evaluate the feasibility of LisNRs incorporating water-permeable channels

(Fig. 2-1), we used a previously described two-compartment model (Ch. 2, Materials and Methods) and introduced a term representing pore-mediated water transport. While

54 this model is generalizable for any water-permeable channel, to generate quantitative estimates of the effect of channels on MRI signal, we used the estimated single channel diffusive hydraulic permeability (1.82 × 10–15 cm3/s) of the well-studied pore-forming peptide gramicidin A (gA)98. Our modeling results confirm that, even at low liposome concentrations of 3 nM, corresponding to liposome a volume fraction (f) of 0.1%, pore modulation in LisNRs should be capable of generating R1 changes of 10% with gA concentrations as low as 100 nM, corresponding to 333 gA monomers per liposome

(Fig 2-1). Importantly, the predicted R1 changes here are limited only by channel activity and much larger R1 changes are possible for channels with higher water- permeability. These results clearly demonstrate the theoretical potential of pore-based

LisNRs for nanomolar analyte sensing by MRI. The signal amplification (A) achieved with LisNRs can be defined as follows;

� ∗ � (3.1) � = � where � represents the efficiency of liposomal contrast modulation (0 ≤ � ≤ 1), Y represents the number of contrast agents encapsulated per liposome, and X represents the number of channels per liposome.

We next set out to test experimentally channel-mediated modulation of liposomal water permeability using gA and alamethicin (Alm). Both peptides are available commercially, purified from natural sources, and addition to paramagnetic liposomes resulted in concentration-dependent increases in R1. We next sought to explore the potential for engineering ligand-gated channels based on these peptides to enable molecular sensing with LisNRs. There have been multiple efforts to develop modified peptidic channels for sensing applications, including for light-99 and ligand-sensing100–

103. We utilize a previously reported ligand-gating strategy that was developed to make electrical sensors of molecular activity. It has been shown that, by fusing a tethered ligand analog to the peptides in the proper orientation based on the known channel conformation, the electrical conductance of these channels can be modulated by protein binding to the modified channel. This system represents a simple competitive channel gating mechanism that we suspected will also modulate water permeability in addition to ion conductivity, though that has not been shown. Naturally-occurring forms of both peptides have modified C-termini making them unsuitable for chemical modification so we instead employed solid phase peptide synthesis methods. While gA-Bio was synthesized using standard solid phase methods (MIT Koch Biopolymers Core), Alm-

Bio proved to be synthetically challenging due to the presence of multiple sterically- hindered α-aminoisobutyric acid (2-methylalanine) residues. To overcome this issue, we turned to a new flow-based high-throughput solid phase peptide synthesis approach that allows for increased reaction temperatures which allowed for synthesis of Alm using standard commercially-available reagents104. We then added gA-Bio and Alm-Bio to paramagnetic liposomes with varying lipid compositions (Fig. 2-2). Incorporating relatively low amounts of POPC (10 – 20%) into liposomal bilayers substantially increased the activity of both Alm-Bio and gA-Bio while only contributing relatively minor increases in baseline liposome water permeability and signal (Fig. 2-2). This finding is consistent with reports that these channels are sensitive to mechanical properties of lipid bilayers including fluidity105. We used size exclusion chromatography to separate leaked paramagnetic complexes from liposomes after peptide addition to confirm whether the R1 changes observed are due to channel-induced increases in water

56 permeability or peptide-induced contrast agent leakage. We found that Alm-Bio, but not gA-Bio, induces substantial contrast agent leakage that explains peptide-dependent increases in R1 making Alm-Bio unsuitable for LisNRs as currently constructed (Fig. 2-

2).

We next sought to demonstrate experimentally the potential for molecular sensing with LisNRs using gA-Bio and SA. We performed T1-weighted MSME scans after peptide addition to paramagnetic liposome solutions and found that MRI signal plateaus after approximately ~ 30 - 60 minutes, indicating peptide incorporation. We then diluted liposomes with buffer or SA and performed a series of T1-weighted MSME scans followed by a series of R1-mapping scans. Addition of SA, at liposome concentrations of 3 nM and 30 nM, gave robust signal changes and equilibrium R1 decreases of 27% and 75% with final gA-Bio concentrations of 2 µM and 20 µM,

-1 -1 respectively. We observed a large relaxivity change, Δr1 ~ 58 s mM gA , compared to relaxivity changes of ~1, and 1.5 s-1 mM-1 for two existing T1-weighted MRI sensors37,40.

Notably, most of the quenching effect of SA has already occurred within the ~ 10 - 15 minutes necessary to set up the MRI experiment indicating LisNRs are capable of responding with temporal resolution on the order of minutes or faster. A modified experiment allowing for quick setup would be necessary to more accurately estimate maximal sensor response kinetics.

Discussion

Here, we have demonstrated the potential for molecular MRI with LisNRs utilizing analyte-gated water channels. The innovative contrast mechanism described is

57 capable of generating large signal changes with sensitivity on the order of 100 nM - 1

µM, a major advance relative to existing T1-weighted contrast agent technology. Our experimental results represent an improvement of over an order of magnitude in longitudinal relaxivity changes, Δr1, compared to existing MRI sensors with significant potential for further development. Based on the data presented here, we estimate an amplification factor, A, ~ 14 for a liposome concentration of 3 nM with 667 gA molecules per liposome (X), and 69,000 contrast agent molecules per 100 nm diameter liposome

(Y).

A key determinant of LisNR potency is the time-averaged single channel water permeability, which takes into account single channel water permeability and duty cycle.

Increasing average single channel permeability in this sensing strategy, through introduction of new channels or engineering of gA channels, would allow for more efficient contrast agent modulation (e) at lower channel concentrations (X). For example, a covalent dimer of gA has been reported to have greatly increased open channel lifetime, likely resulting in increased average single channel permeability106.

The gA pore opening is narrow allowing only single-file water transport98. Channels with wider pores, like Alm107 which has a roughly 2 nm diameter pore as compared to 0.4 nm for gA108, are likely to exhibit increased water permeability, however, the potential for contrast agent leakage also increases with pore diameter. Replacing gadoteridol, the ~

559 Da paramagnetic complex used in this study, with a large multivalent contrast agent, like a dendrimer-based gadolinium chelator, could solve the issue of leakage allowing for the use channels with wider pores, like Alm. This strategy could also improve LisNR performance by increasing the number of paramagnetic complexes

58 encapsulated (Y), without increasing osmolarity of the intraliposomal solution beyond physiological osmolarity (~ 310 mOsm for cerebrospinal fluid).

Modularity is another significant advantage of the competitive sensing mechanism described here as the biotin/SA interaction used in this demonstration could be replaced with other analyte/protein pairs to target additional analytes. For example, we have shown that the dopamine-binding protein BM3h-9D7 binds both dopamine and tethered tyramine, a dopamine analog, making it potentially suitable for use in a dopamine-sensitive LisNR. Competitive sensing, however, will also reduce analyte sensitivity compared to, for example, direct pore blocking by analyte binding. An intriguing approach for increasing sensitivity with LisNRs is the use of liposome- conjugated protein targeting domains that would preferentially localize sensors to sites of analyte release and increase effective analyte concentrations. In the brain, for example, millimolar neurotransmitter levels within synaptic clefts rapidly fall off with distance due to both diffusion and active clearance. In this case, antibodies against extracellular synapse-associated proteins, like dopamine transporter (DAT), could serve as targeting domains. This approach is only possible for contrast agents that generate detectible signal changes at concentrations lower than the concentration of the extracellular protein targets, typically present at nanomolar concentrations. Antibody- directed targeting has been demonstrated previously for other liposomal imaging agents80,109 demonstrating the feasibility of this approach.

Materials and Methods

Modeling

We modified the model described in Chapter 2 to account for increased liposomal water permeability due to incorporation of water-permeable channels as a function of the number of channels per liposome (n), channel duty cycle (β), and the single channel hydraulic permeability (α);

� ∗ � ∗ � (3.2) � = � + 0 4 ∗ � ∗ (�⁄2)2

where P0 is the baseline liposomal membrane water permeability and d is the liposome diameter.

Liposome synthesis and purification

Liposomes were synthesized and purified as described in Ch. 2. gA-Bio

gA-Bio (Fig. S3-1) was purchased from the MIT Koch Biopolymers Core Facility

(Cambridge, MA). Peptide was synthesized using standard FMOC solid phase peptide synthesis methods. Pre-biotinylated ‘FMOC-PEG Biotin’ resin was purchased from

Millipore Sigma (Burlington, MA). Manual formylation was performed before peptide cleavage. Stock solutions of gA-Bio were made in DMSO and stored at 4 ºC in sealed vials or at -20 ºC for long term storage. gA-Bio concentration was determined by absorbance at 280 nm with a Thermo Scientific Nanodrop UV-Vis Spectrophotometer

(Waltham, MA) using the reported extinction coefficient for gA (20700 M-1 cm-1).

Peptide was verified by matrix-assisted laser desorption time of flight mass spectrometry (MALDI-TOF). Crude peptide was used without further purification.

Alm-Bio

Alm-Bio was synthesized and provided by Nina Hartrampf and Mackenzie

Poskus of the Pentelute group using a fully automated flow-based solid phase synthesis approach104 with RINK amide resin (Fig. S3-2). Alm-Bio purity was verified by HPLC and LCMS (M/3 = 778 Da). Biotin was attached through addition of C-terminal biotinylated lysine. Alm-Bio concentrations were measured by NMR proton peak integration110 of phenylalanine residues and a 3-(Trimethylsilyl)propionic-2,2,3,3-d4 standard purchased from MilliporeSigma (Burlington, MA). Alm-Bio stock solutions were made in DMSO and stored at 4 ºC in sealed vials.

Magnetic Resonance Imaging (MRI)

MRI was performed on a Bruker 7T Avance III small animal scanner (Billerica, MA) using a Bruker Biospin MRI coil. Scanner operation was controlled using the Bruker

ParaVision 5.1 software. T1-mapping experiments were performed using a series of

MSME spin echo scans with echo time (TE) = 8ms, matrix size = 256 by 256, field of view

(FOV) = 5 cm by 5 cm, slice thickness = 2 mm and excitation angle = 90° with repetitions times (TR) from 30 ms to 5 seconds. The number of scan averages was set such that total scan time at each TR was at least 7 minutes. Raw FID data was reconstructed and analyzed using a custom Mathworks Matlab (Natick, MA) script.

Figure 3-1: Molecular LisNRs have the potential for high analyte sensitivity. A) Conceptual diagram showing effect of LisNR contrast mechanism. Black shading shows low MRI signal while white shading shows high MRI signal. Insets show voxel- averaged signal.

B) Estimated R1para and percent change in R1 in buffer of LisNR, at 3 nM liposome concentration, from modeling. Curves are shown for gA duty cycles of 100%, 50% 20% 10%, and 5% (from dark to light, respectively). C) Conceptual diagram showing proposed gA competitive sensing mechanism where binding protein (white) binds ligand-functionalized gA channels and free analyte (orange triangle) competes for the same binding site.

-1 -1 D) r1 [s (mM gA) ] and R1para shown from B at 100 nM gA.

Figure 3-2: gA permeabilizes liposomes to water but not contrast agent.

A) Effect on R1 of gA-Bio addition to liposomes containing 20% DPPG with the remaining lipids a mix of DPPC and POPC. POPC composition was 0, 10, or 20% (from light orange to dark orange). Inset shows MRI signal.

B) Effect on R1 of Alm-Bio addition to liposomes containing 20% DPPG with the remaining lipids a mix of DPPC and POPC. POPC composition was 0, 10, 20, 47.5 or 95% (from light purple to dark purple). Alm-Bio shows enhanced R1 increases at lower peptide concentrations when added to liposomes as compared to gA-Bio (A).

C) R1 after vehicle (DMSO) or peptide addition as well as the expected R1 due to contrast agent leakage alone. gA-Bio addition causes R1 increases explained by increased membrane water permeability, not contrast agent leakage, while effects of Alm-Bio are explained entirely by contrast agent leakage. Contrast agent leakage was measured independently using size exclusion chromatography to separate free contrast agent from liposomes and measured by ICP-MS, shown in D.

Figure 3-3: Streptavidin addition blocks gA-Bio. Liposome composition is 60% DPPC, 20% POPC, 20% DPPG. Shaded regions and error bars show standard deviation (n = 2 independent experiments).

A) T1 RARE sequence (repetition time 300 ms) shows signal increase from gA-Bio addition plateaus after ~ 30 min indicating peptide incorporation. Shaded regions show standard deviation. B) Samples from A were diluted with either buffer or SA. Final concentrations were 3 nM liposomes/ 4 µM SA (left) or 30 nM liposomes/ 33.3 µM SA (right). Addition of SA, but not buffer, causes rapid decrease in T1 RARE MRI signal. Shaded regions show standard deviation.

C) R1 values measured for samples from A and B after equilibration with SA. Further investigation is necessary to determine whether SA inactivates channels by removing them from the membrane, direct pore blockage, or through induced changes in peptide conformation upon binding.

D) Relaxivities (r1) were calculated in the presence and absence of SA based on C and are expressed per mM gA-Bio.

E) Percent change in R1 for buffer addition, relative to SA addition, for liposomes containing gA-Bio or vehicle is shown for samples from C. 64

Figure S3-1: gA-Bio structure and characterization. The structure and sequence of gA-Bio is shown as well as characterization by MALDI.

Figure S3-2: Alamethicin-bio structure and characterization The structure and sequence of Alm-Bio is shown as well as characterization by LCMS as well as synthesis conditions on the ‘Amidator’ automated peptide synthesizer104.

Engineering Binding Proteins for Competitive Sensing

Abstract

Molecular imaging is a powerful approach for the visualization of molecular signaling networks that rely on biomolecular sensors that rely molecular events into image contrast. Contrast mechanisms that rely on competition between free analyte and tethered analyte analogs for protein binding sites in order to generate analyte- dependent signal changes represent generalizable platforms into which new protein/ligand pairs can be substituted to alter molecular specificity. Sensors based on this principle have been reported for multiple imaging modalities including fluorescence microscopy and magnetic resonance imaging (MRI). The development of suitable protein domains, however, remains a significant bottleneck. Here we describe a general high-throughput protein engineering approach, utilizing yeast surface display, that is adapted for the selection of free and tethered small molecule binding proteins. We use this approach to select for dopamine-binding antibody single chain variable fragment

(scFv) domains from naïve yeast display libraries.

Introduction

Over the last several decades, beginning with the advent of phage display in

1985111, directed evolution has become a powerful method for engineering proteins with novel functions, from binding40,112 to complex enzymatic activities113,114. Yeast surface display115,116 is a well-established platform that has been widely used to engineer protein-protein interactions in conjunction with high-throughput fluorescence activated

67 cell sorting (FACS). However this method has less often been used to engineer small molecule-protein interactions112,117 and never, to our knowledge, for the engineering of a novel small-protein interaction from a naïve library. This application is challenging due to the relatively small number of potential binding interactions offered by small molecules when compared to proteins, often with masses two orders of magnitude greater, however it is clearly feasible as several examples of extremely tight protein/ligand interactions, including two antibodies matured with yeast surface display112,118.

On potential use of directed evolution and high-throughput protein screening is for the rapid development of biosensors for molecular imaging that convert molecular events into localized signals, effected through binding of the molecular target.

Molecular MRI is an especially promising noninvasive molecular imaging modality with the capability for whole-organ imaging while retaining relatively high spatiotemporal resolution. However, first-generation single-metal MRI sensors that operate through stoichiometric interactions between an analyte molecule and a paramagnetic metal ion are inherently insensitive, requiring sensor concentrations on the order of 10-100 µM to see realize appreciable signal changes. Several promising next-generation MRI sensor platforms, like activatable vasoprobes for analyte targeting (AVATars)64, and liposomal nanoparticle reporters (LisNRs), offer the potential for nanomolar sensitivity necessary for many physiological molecules like neurotransmitters. However, both sensor designs rely on a competitive mechanism where increasing analyte concentrations compete with a tethered analyte analog for protein binding. The modularity of this competitive sensing mechanism is a major advantage as different ligand/protein pairs should be

68 interchangeable, however the engineering of binding proteins responsive to both free and tethered analyte remains the limiting step for the application of these sensor platforms. Additionally, fine tuning of the relative protein binding affinity for free and tethered analyte binding is predicted to have a large impact on sensitivity, with lower affinity for the tethered ligand being favorable due to increases in local effective concentrations due to tethering. Yeast surface display offers an attractive engineering approach for the development of analyte binding proteins compatible with these promising new sensors. Here we focus on engineering antibodies, a well-established and versatile binding scaffold, for competitive sensing applications. We use single chain antibody fragments (scFv), a minimal antibody architecture made by direct fusion of light and heavy chain variable domains that generally retains the ligand-binding capability of full-length antibodies while offering the additional simplicity of a single polypeptide chain119. We chose dopamine, a neurotransmitter known for its role in motor control and reward circuits in mammals that is implicated in addiction, as a small molecule target, however, the general strategy described here is adaptable to other small molecules. Besides its functional importance in the brain, dopamine represents a reasonable target for the validation of this approach as commercial polyclonal antibodies have been raised against dopamine, though binding affinities are not reported.

Results

We employed yeast surface display using two previously characterized scFv libraries120,121, ‘H3’ and ‘G’, each with diversity ~ 109. Because these libraries have diversity substantially larger than can be screened even with high-throughput FACS selections (~ 3 – 4 million cells per hour of sorting), pre-selections are typically carried out using magnetic beads to reduce library diversity. Beads coated with streptavidin are often used in order to easily immobilize biotinylated target ligands. Because dopamine is approximately 100 times smaller than more typical protein target ligands, we anticipated that secondary binders that interact with SA were more likely to arise in our selections. While negative selections using SA-coated beads without the addition of the target ligand can be used to reduce the prevalence of SA binders, this process is likely not very efficient due to the low number of beads relative to the total number of yeast cells used during these selections. Therefore, we opted instead to chemically conjugate dopamine to beads. We synthesized a tethered dopamine analog, DA-PEG-NH2, which contains a free amine for peptide coupling to carboxyl-functionalized beads, as well as a hydrophilic polyethylene glycol (PEG) linker.

After two rounds of pre-selections, we then proceeded to FACS selections. To maximize our ability to capture weak binders with affinities in the range of 1 – 10 µM, we employed a multivalent ligand complex made by mixing fluorescently-labeled SA with a biotinylated tethered dopamine analog, DA-PEG-Bio (Fig. 4-1) at a ratio of 4:1 to reduce unbinding rates. Normally, a wash step is performed to remove any ligand not bound to yeast cells before addition of fluorescent SA (secondary staining). Because our multivalent ligand complex is already fluorescent, we were able to proceed to flow

70 cytometry immediately after removal of excess ligand, minimizing the time between the wash and the start of FACS. Samples were kept on ice from the time excess ligand was removed in order to further decrease unbinding. In addition, we used a high ligand complex concentration of 5 µM, corresponding to a DA-PEG-Bio concentration of 20

µM. In order to avoid enriching for binders specific to the SA/DA-PEG-Bio complex, we incorporated multiple selection steps where neutravidin (NA), an alternative tetravalent biotin-binding protein, was substituted for SA. To ensure enriched protein domains retain the ability to bind free dopamine, in addition to DA-PEG-Bio, we incorporated competitive negative selections in which we added free dopamine in solution along with

SA/DA-PEG-Bio and selected for binders that showed low binding (Fig 4-1). Following multiple rounds of selection, no appreciable binding was observed from library H3, not entirely surprising as tryptophan was removed from the H3 CDR of this library to reduce nonspecific sticking and the stacking of aromatic rings is a common binding mode for aromatic molecules like dopamine122. Strong, dopamine-dependent binding was observed for populations from library G, and these populations were sequenced to identify highly-enriched individual clones (Fig, 4-2). Interestingly, the H3 complementarity-determining region (CDR), which was highly diverse in the initial library design121, was identical in all highly-enriched clones.

The most highly-enriched clones were then chosen for further validation using on cell FACS-based binding titrations (Fig. 4-3), similar to standard FACS selections only with isogenic yeast samples rather than mixed populations. For these experiments, DA-

PEG-Bio was mixed with SA or NA at a ratio of 0.9:1 in order to minimize the effects of multivalency when quantifying binding affinity. Multiple clones from libraries G showed

71 low micromolar binding affinity for DA-PEG-Bio/SA, DA-PEG4-Bio/NA, and free dopamine. We were encouraged to also see substantial selectivity over serotonin, a related monoamine neurotransmitter.

Clones 11H1, 9M1, and 9M2, were then expressed, as scFv-Fc fusions for added stability, in HEK 293F cells for further validation using biolayer interferometry (BLI).

Clones 11H1 and 9M1 showed significant binding to SA-coated BLI tips loaded with DA-

PEG-Bio (Fig. 4-4), though they also showed some binding to SA-coated tips even in the absence of DA-PEG4-Bio which will likely need to be addressed in future work.

Discussion

The approach taken here to engineer binding domains for biosensor applications that rely on competitive mechanisms is general and can be applied for the development of sensing domains for a wide range of applications. To adapt traditional yeast display methods for the selection of small molecule binders from naïve libraries, we took a few simple steps, including the use of a fluorescently-labeled multivalent ligand complex using tetravalent biotin binders SA and NA. In anticipation of additional complications from off-target interactions due to the small relative size of dopamine, we implemented strategies to reduce secondary binding, like alternating the use of SA and NA, as well as chemical conjugation, rather than biotin/SA complexation, to tether a dopamine analog to magnetic beads during library pre-selection. However, despite these steps, we still see interaction between free protein domains and SA-coated BLI tips in the absence of DA-PEG-Bio.

One possible explanation of this finding is that the selected proteins still bind weakly to SA, in the absence of DA-PEG4, in spite of the additional steps taken to mitigate this possibility. Interestingly, this explanation raises the question of whether weak interactions with SA might actually be necessary or beneficial to further boost binding low affinity dopamine-binding proteins in naïve libraries. An alternative explanation is that the proteins selected simply show some nonspecific binding. One way to explore this hypothesis would be to test for nonspecific binding more directly, either using a polyspecificity reagent (PSR)123 or simply by using a BLI tip loaded with a control protein other than SA, though commercially available options are somewhat limited. In practice, affinity maturation to increase affinity for DA-PEG-Bio, circumventing the need for such high protein concentrations (> 10 µM), will likely address both these issues. Despite these complications, the proteins selected here represent an important step towards the engineering of dopamine-binding domains and the strong selectivity observed for free dopamine over serotonin, as well as high sequence identity among selected clones in the highly variable H3 CDR, are clear signs that these proteins do exhibit the desired binding activity. Future steps include affinity maturation of these domains for increased dopamine affinity, ideally in the 100 nM to 1

µM range, and the extension of this strategy to other biological small molecule targets of interest.

Materials and Methods

Yeast Display Reagents

Primary antibodies chicken anti-cymc and mouse anti-HA (clone 16b12) were purchased from Exalpha Biologics (Shirley, MA) and BioLegend (San Diego, CA), respectively. Goat anti-chicken AF488/647, goat anti-mouse AF488/647, streptavidin-

AF647, neutravidin-OG488, 293 Freestyle media, and OptiMEM I were purchased from

Thermo Fisher Scientific (Waltham, MA).

Yeast Display

Yeast display experiments were carried out mostly as described115,116 with a few differences. DA-PEG4-NH2 was covalently conjugated to M-270 carboxylic acid beads, from Thermo Fisher Scientific (Waltham, MA), using NHS coupling according to the manufacturer’s protocol. For FACS sorts, DA-PEG4-Bio was premixed (4:1) with SA or

NA for at least 45 min to allow for equilibration, during which cells were stained with a primary antibody against cmyc. For on cell titrations, a (0.9:1) mix of DA-PEG-

Bio/protein was used to give, on average, monovalent ligands for more accurate determination of affinity. DA-PEG4-Bio complex was added along with the secondary antibody against the cmyc primary antibody. After equilibration, cells were washed and taken immediately for FACS on ice to reduce unbinding. Initial DA-PEG-Bio concentrations during sorting were 20 uM in order to capture low affinity binders. NA and SA were alternated to prevent enrichment of secondary-specific dopamine binders.

In addition, negative selection steps as well as competitive binding negative seletions steps (where dopamine was added to cells at the same time as DA-PEG4-Bio complex)

74 in order to minimize secondary binding and to ensure selected clones would not be specific for DA-PEG-Bio complexes. All sorts were done on BD Biosciences (San Jose,

CA) FACS Aria sorters at the MIT Koch Flow Cytometry Core Facility (Cambridge, MA).

Dopamine stocks were made fresh for each experiment to prevent oxidation.

Protein production

Selected clones were expressed as Fc fusions in HEK 293-Freestyle cells using a gWiz expression plasmid, Genlantis (San Diego, CA). Transfections were performed using PEI, at a ratio of 3:1 (w/w) PEI to DNA in OptiMEM I. Supernatant from transfected cultures was collected by centrifugation after 7 days and protein was purified using rProtein A Sepharose FastFlow resin, Cytiva Lifesciences (Marlborough,

MA).

Biolayer Interferometry (BLI)

BLI was performed on a ForteBio Octet system at the MIT Biology

Instrumentation Facility (Cambridge, MA) using SA-coated tips.

Chemical Synthesis

DA-PEG4-Bio was synthesized using NHS coupling with reagent NHS-PEG4-

Biotin from BroadPharm (San Diego, CA) with a slight excess (~ 1.1:1) of dopamine in

PBS (degassed and bubbled with argon prior to use) at room temperature for 30 minutes followed by HPLC purification and characterization by LCMS and NMR. DA-

PEG4-Bio was quantified using an exctinction coefficient at 280 nm measured for dopamine by mass (2.75 mM-1 cm-1). Product was aliquoted, lyophilized, and stored dry in sealed vials at -20 ºC for long term storage, or as a stock solution in water at -80 ºC for short term storage.

DA-PEG4-NH2 was synthesized using NHS coupling with reagent t-boc-N-amido-

PEG4-NHS from BroadPharm (San Diego, CA) with a slight excess (~ 1.1:1) of dopamine in PBS (degassed and bubbled with argon prior to use) at room temperature for 30 minutes followed by HPLC purification. Product was then lyophilized and boc was deprotected in dichloromethane + 20% TFA overnight. Solvent and TFA was removed by rotary evaporation and the resulting solid was characterized by LCMS and

NMR. DA-PEG4-NH2 was quantified using an extinction coefficient measured at 280 nm by weight for dopamine (2.75 mM-1 cm-1). Product was aliquoted and stored in sealed vials at -20 ºC, for long term storage, or as a stock solution in water at -80 ºC for short term storage (several weeks).

Figure 4-1: Yeast surface display.

A) Representation of yeast surface display system (adapted from Chao et al.115)

B) Tethered dopamine analogs DA-PEG-NH2 (top), and DA-PEG-Biotin (bottom)

C) Crystal structure of a fluorescein-binding scFv 4m5.3 (PDB 1x9q124). CDR loops are shown in orange and a bound fluorescein molecule is shown in green.

D) General description and sequence of the steps for the selection of dopamine-binding scFvs with yeast display.

Figure 4-2: Sequence Analysis of populations 0.11H and 0.9M from library G.

A) Sequence alignments of the most highly enriched clones from approximately 90 sequenced colonies per population. Population 0.11H underwent several addition selections at DA-PEG-Bio concentrations as low as 0.2 µM as compared to population 0.9M which was sorted with DA-PEG4-Bio concentrations as low as 2 µM. Remarkably, all top clones from both populations had the exact same H3 CDR sequence, CDR loop with the highest diversity in the initial library G design121.

B) Distribution on clone frequencies from sequencing of the populations from A.

Figure 4-3: On cell binding titrations.

A) Left column shows on cell binding titrations with DA-PEG4-Bio mixed 0.9:1 with either NA-OG488 or SA-AF647. Middle and right columns show competitive titrations where dopamine (DA) or serotonin (HT) was added at a range of concentrations with [DA-PEG4-Bio] = 1µM, using either NA-OG488 or SA-AF647. Fluorescence was measured from approximately 10,000 cells per data point.

B) Binding affinities (µM) for titrations in A.

Figure 4-4: BLI titrations with purified scFv-Fc domains.

BLI was carried out using SA-coated tips preloaded using 150 nM DA-PEG-Bio or unloaded as a negative control. Clones 9M1 and 11H1 both show clear binding signals, though there is also some binding to SA control tips. Protein concentrations used were 0, 1.25, 2.5, 5, 10, 20, and 40 µM (from light to dark).

Conclusions and Future Directions

Synopsis, Significance, and Impact

In this dissertation, I have introduced a novel liposome-based MRI contrast agent platform in which water access to a large number of paramagnetic metal complexes can be modulated simultaneously. This principle for analyte sensing can be thought of as an extension of the well-established contrast mechanism employed in single-metal sensors, generalized to the macromolecular scale, where water access is modulated at the liposomal membrane rather than at coordination sites on individual paramagnetic complexes.

While the development of this contrast agent architecture is still in early stages, the theoretical and experimental results presented here demonstrate the potential of this contrast agent platform for molecular imaging with increased sensitivity and signal change, addressing the major limitations of existing paramagnetic MRI probes.

Limitations

The use of LisNRs still requires the delivery of exogenous paramagnetic contrast agent, which can be challenging especially in vivo, and especially in the brain due to the impermeability of the blood brain barrier. LisNRs ultimately still rely on T1-weighted signal from paramagnetic metal complexes, so the requirement for micromolar metal complex concentrations in order to generate readily detectible signal changes is still applicable, despite the low nanomolar particle concentrations used. For instance, the

100 nm diameter liposomes used here, a particle concentration of 3 nM (volume

82 fraction, f = 0.1%) still corresponds to a high metal concentration of 220 µM. Such concentrations were achieved in the brain through intracranial infusion, in the case of

Light-LisNR. While this delivery method is well-tolerated and can be used for basic research and preclinical studies in rodents without further modification, it precludes the possibility of whole-brain imaging. Liposomes did, however, spread over large brain volumes (> 30 mm3) sufficient for systems-level neuroscience applications. It remains to be seen whether low nanomolar liposome concentrations can be achieved through noninvasive blood brain barrier (BBB) delivery methods like receptor-mediated transcytosis125 (RMT), or transient BBB opening using mechanical126 (ultrasound sonication with gas microbubbles) or chemical methods127 (lysophosphatidic acid).

Delivery of liposome cargo to the brain has been observed through a RMT approach, but it is not demonstrated whether intact liposomes can also permeate the BBB128.

The development of LisNRs for molecular sensing with MRI, a major scientific objective, is limited at this point not by the contrast mechanism itself, but rather by available channels and gating mechanisms. We demonstrate that gA is capable of generating large relaxivity changes when added to paramagnetic liposomes and showed that a previously reported competitive gating mechanism of the ion conductivity of this channel in electrical sensors was generalizable for modulation of channel water permeability, offering a path towards expanding the range of sensing applications accessible with LisNRs.

Future Work

To improve upon the contrast agent platform described here, there are a number of straightforward steps that can be taken to address the limitations of LisNRs as currently constructed.

First and foremost, the development and implementation of more permeable water channels will be a crucial step in extending LisNR sensitivity, as demonstrated by our model of LisNR activity. A covalent dimer of gA has been reported to have a much longer channel lifetime106 which could result in substantial gains in time-averaged water permeability. In addition, there are a number of pore-forming proteins reported in the literature that could be tested for compatibility with LisNRs129. Other candidates include protein-based channels, like aquaporin Z or even ligand-gated ion channels, likely permeable to water in addition to ions based on estimated pore size, which can be incorporated into liposomes through detergent solubilization and dialysis130.

In order to extend the range of channels compatible with LisNRs, the synthesis and encapsulation of multivalent paramagnetic complexes, for example dendrimer- based gadolinium chelates, should allow the use of channels with larger pore diameter and higher water-permeability. This strategy may also enable encapsulation of higher metal concentrations without exceeding physiological osmolarity, further boosting LisNR performance.

The incorporation of targeting domains represents a unique strategy for improving analyte sensitivity by localizing sensors to sites of analyte release, for example, near synapses. As analyte-binding proteins with improved affinities are developed to increase sensitivity, slower unbinding rates will inevitably reduce sensor

84 kinetics. Increasing local analyte concentrations by localizing sensors to synapses, in the case of neurotransmitter sensing, would improve analyte responses without compromising sensor kinetics. In fact, fast chemical neurotransmission relies on exactly this concept and is only possible due to the low affinity and fast kinetics of neurotransmitter receptors which necessitates the co-localization of sites of neurotransmitter release and detection to achieve sufficiently high local neurotransmitter concentrations. Protein targeting has been demonstrated previously128 and a number of common surface conjugation chemistries have been shown to be applicable for liposomes surface conjugation, including copper-free click chemistry and maleimide- sulfhydryl coupling131.

We have demonstrated a protein engineering approach for the selection of protein domains for competitive sensors, including LisNRs and AVATars64 as well as fluorescence-based molecular sensors132. While the dopamine-binding domains identified here are not yet sufficient for use in functional applications, the positive initial results presented nonetheless serve as a proof-of concept for this approach. Extending this strategy to other analytes would dramatically expand potential applications of existing molecular sensors including, but not limited to, LisNRs.

Further improvement of Light-LisNR sensitivity to enable molecular MRI mediated by light with luciferase-based molecular sensors would allow for investigators to take advantage of the benefits of MRI as compared to optical imaging while still taking advantage of the array of luminescent molecular tools already developed. One potential approach towards improved light-sensitivity is the use of light-gated water channels, as opposed to the mechanism employed here which uses photoisomerization

85 of azoPC to effect changes in membrane fluidity and passive permeability, which may boost sensitivity depending, of course, on the functionality specific light-gated channels.

There is an example of a light-sensitive peptide channel based on gA reported in the literature99 that could be used in Light-LisNRs and other light-gating mechanisms are possible including strategies analogous to those taken for chemical optogenetics, for example, for the engineering of light-switchable potassium channels133. The current fluidity-based mechanism for light sensing could also be improved substantially with the addition of polymeric gadolinium complexes, or other large molecular weight contrast agents like nanoparticles, allowing for the use of higher azoPC concentrations, that resulted in leakage of the small paramagnetic complex used here, and would increase the efficiency of light absorption.

In the future, nanomolar molecular sensing with LisNRs would enable a number of important biological applications. Mapping neurotransmitters at physiological concentrations could have a tremendous impact on our understanding of the basic function of the central nervous system with implications for the study and treatment of disorders like depression, anxiety, and addiction. Light-LisNRs could enable detection of luciferase activity in vivo, which would allow investigators to study gene regulation in the brain with a wide range of implications from developmental biology to the study of the genetic basis of behavior.

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