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2017 Neuromodulation of Mitral Cells by Serotonin and GLP-1 Neurons in the Olfactory Bulb and the Consequences of Gene Deletion of Kv1.3 Zhenbo Huang
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COLLEGE OF ARTS AND SCIENCES
NEUROMODULATION OF MITRAL CELLS BY SEROTONIN AND GLP-1 NEURONS IN
THE OLFACTORY BULB AND THE CONSEQUENCES OF GENE DELETION OF KV1.3
By
ZHENBO HUANG
A Dissertation submitted to the Department of Biological Science in partial fulfillment of the requirements for the degree of Doctor of Philosophy
2017
Zhenbo Huang defended this dissertation on November 16, 2017. The members of the supervisory committee were:
Debra Ann Fadool Professor Directing Dissertation
Timothy M. Logan University Representative
David M. Gilbert Committee Member
Lisa C. Lyons Committee Member
Zuoxin Wang Committee Member
The Graduate School has verified and approved the above-named committee members, and certifies that the dissertation has been approved in accordance with university requirements.
ii
This work is dedicated to my parents, Shengding Huang and Heyin Tang, for their unconditional support throughout my life. Without them, I could not have achieved this.
iii ACKNOWLEDGMENTS
First, I would love to thank my mentor, Dr. Debra Ann Fadool, for her attention and guidance to various aspects of my Ph.D. training. With her hands-on teaching, I acquired solid patch-clamp technique. Her rigorous writing style has helped me to become a better writer. Her scientific think enabled me to do thorough science. She also serves as a role model for me in life. Her kindness and patience to everyone inspires me to do the same.
I would also like to thank my Graduate Committee, Drs. David Gilbert, Lisa Lyons, Timothy Logan, and Zuoxin Wang for their insightful comments and suggestions to my research. I learned a lot from them.
Thanks to post-docs, Dr. Nicolas Thiebaud and Dr. Erminia Fardone, and my fellow graduate students, Austin Schwartz, Brandon Chelette, Daniel Landi Conde, Dolly Al Koborssy, Genevieve Bell, and Kassandra Ferguson, and Louis Colling in the lab. They helped me both in scientific experiments and in daily life. With their help I made a relative easy and pleasant transition to live in a foreign country.
Dr. James M. Fadool and his laboratory crew were also very helpful during my Ph.D. study.
Last, but not least, I would like to thank all the faculty and staff in the Program in Neuroscience and in the Biological Science Department who helped me along the way. Their help made me feel at home and contributed to my achievements here at Florida State University.
iv TABLE OF CONTENTS
List of Tables ...... vii List of Figures ...... viii List of Abbreviations ...... x Abstract ...... xii
1. INTRODUCTION ...... 1
1.1 Origin of Neuro-electricity and the Development Patch-clamp Technology ...... 1 1.2 Introduction of Ion Channels and their Function ...... 5 1.3 Neuromodulation in the Olfactory Bulb ...... 9
2. DIFFERENTIAL SEROTONERGIC MODULATION ACROSS THE MAIN AND ACCESSORY OLFACTORY BULBS ...... 14
2.1 Introduction ...... 14 2.2 Materials and Methods……………………………………………………………………16 2.3 Results...... 21 2.4 Discussion ...... 36
3. THE MODULATION OF GLP-1 NEURONS IN THE OLFACTORY BULB ...... 41
3.1 Introduction ...... 41 3.2 Materials and Methods……………………………………………………………………43 3.3 Results...... 49 3.4 Discussion ...... 55
4. OLFACTION AND ANXIETY IN KV1.3 KNOCK-OUT MICE: POSSIBLE APPLICATION IN ADHD...... 60
4.1 Introduction ...... 60 4.2 Materials and Methods……………………………………………………………………62 4.3 Results...... 69 4.4 Discussion ...... 77
5. SUMMARY ...... 84
APPENDICES ...... 87
A. KV1.3 AND MITOCHONDRIA ...... 87 B. TESTING QUANTUM DOT-CONJUGATED DRUG ON BRAIN SLICE ...... 95 C. THE EFFECTS OF SHORT-TERM PRENATAL HIGH-FAT DIET ON OFFSPRINGS AND DAMS THEMSELVES ...... 96 D. ACUC APPROVAL LETTER ...... 99
v REFERENCES ...... 100
BIOGRAPHIC SKETCH...... 127
vi LIST OF TABLES
2.1 A comparison of intrinsic properties of mitral cells (MCs) in the main olfactory bulb (MOB) versus those in the accessory olfactory bulb (AOB) ...... 21
3.1 Basic intrinsic properties of GLP-1 neurons in the olfactory bulb ...... 50
C.1 Litter statistics comparing dams maintained on control- and high-fat diets ...... 98
vii LIST OF FIGURES
1.1 Basic model of the olfactory bulb neural network...... 11
2.1 Mitral cells in the main olfactory bulb (MOB MCs) largely exhibit an increase in action potential (AP) firing frequency in response to serotonin (5-HT) ...... 23
2.2 Quantitative analysis of the excitatory response of MOB MCs...... 24
2.3 Serotonin (5-HT) elicits direct excitation of MOB MCs...... 26
2.4 5-HT-evoked excitation in MOB MCs is inhibited by 5-HT receptor antagonists that have subtype specificity...... 27
2.5 Mitral cells in the accessory olfactory bulb (AOB MCs) predominantly exhibit a decrease in AP firing frequency in response to 5-HT ...... 28
2.6 AOB MCs are differentially inhibited by 5-HT, regardless of onset kinetics of the modulation...... 31
2.7 5-HT-evoked inhibition in AOB MCs responds differentially to gabazine...... 32
2.8 Slow-onset 5-HT modulation is sensitive to 5-HT2 receptor antagonists while rapid-onset is sensitive to 5-HT1 receptor antagonist in AOB MCs...... 34
2.9 Model of serotonergic modulation in two parallel processing pathways of the olfactory system...... 40
3.1 Representative current-clamp recording of a GLP-1 neuron...... 50
3.2 Acetylcholine shows inhibitory effects on GLP-1 neurons...... 51
3.3 Acetylcholine shows excitatory effects on GLP-1 neurons...... 52
3.4 Cholecystokinin modulates the activity of GLP-1 neurons...... 53
3.5 A subgroup of GLP-1 neurons responds to changes of glucose concentration...... 54
3.6 Enzyme-linked immunosorbent assay (ELISA) measurements of GLP-1 content ...... 55
3.7 Habituation-dishabituation tests after delivering Exendin-4...... 56
4.1 Kv1.3-/- mice exhibit increased anxiety in the light-dark box (LDB) and elevated-plus maze (EPM) apparatus ...... 71
viii 4.2 Anxiety disorder in male Kv1.3-/- mice can be alleviated by methylphenidate (MPH) treatment...... 72
4.3 Object-based attentional deficits of male Kv1.3-/- can be ameliorated by MPH treatment. ...73
4.4 Locomotor activity is not significantly altered by MPH treatment...... 75
4.5 Dopaminergic signaling differences in WT vs. Kv1.3-/- mice...... 76
A.1 Kv1.3-/- mice have smaller mitochondria in the mitral cell layer of the OB, which do not exhibit an increase in volume when challenged with moderately-high fat diet (MHF)...... 91
A.2 Schematic diagram showing cell signaling interactions of plasma membrane Kv1.3 (Kv1.3) and potential interplay with mitochondrial Kv1.3 (mKv1.3)...... 93
B.1 Mitral cell (MC) action potential firing frequency in response to margatoxin-conjugated quantum dots (QD-MgTx) ...... 95
C.1 Behavioral tests of the offspring of dams maintained on control- and high-fat diet...... 97
ix LIST OF ABBREVIATIONS
5-HT: serotonin ACh: acetylcholine ACSF: artificial cerebrospinal fluid ADHD: attention-deficit/hyperactivity disorder ANOVA: analysis of variance AOB: accessory olfactory bulb AP: action potential APV: D-(-)-2-Amino-5-phosphonopentanoic acid
CB1: cannabinoid type-1 CCK: cholecystokinin CNS: central nervous system D2DR: dopamine receptor type II DA: dopaminergic DAT: dopamine transporter DOPAC: 3:4-dihydroxyphenylacetic acid dSACs: deep short-axon cells EPL: external plexiform layer EPM: elevated-plus maze ERK: extracellular signal-related kinase ETC: external tufted cell Ex-4: Exendin-4 GC: granule cell GCL: granule cell layer GL: glomerular layer GLP-1: glucagon-like peptide-1 GPCRs: G-protein-coupled receptors HCN: cyclic nucleotide-gated HDB: the horizontal limb of the diagonal band of Broca IPI: interpulse interval IPL: internal plexiform layer x ISI: interspike interval Kv1.3: voltage-dependent potassium channel, Shaker family 1.3 Kv1.3-/-: Kv1.3 knockout mice LDB: light-dark box mAChR: muscarinic acetylcholine receptor MB: marble burying MCL: mitral cell layer MCs: mitral cells Min: minute MOB: main olfactory bulb MOE: main olfactory epithelium MPH: methylphenidate ms: millisecond nAChR: nicotinic acetylcholine receptors NBQX: 2:3-dihydroxy-6-nitro-7-sulfamoyl-benzo[f]quinoxaline NS: not significantly-different means NTS: the nucleus of the solitary tract OB: olfactory bulb OCD: obsessive-compulsive disorder ONL: olfactory nerve layer OSNs: olfactory sensory neurons PBS: phosphate buffered saline PG: periglomerular RMP: resting membrane potential s: second SAC: short-axon cell sSA: superficial short-axon T2DM: type 2 diabetes mellitus TH: tyrosine hydroxylase VNO: vomeronasal organ. WT: wild-type
xi ABSTRACT
Neuromodulation plays important roles in adjusting our nervous system to produce behaviors. The same neuromodulator could have different effects on different targets, or the same target could be modulated by multiple neuromodulators. In the first project of my dissertation I investigated differential modulation of mitral cells (MCs) contained in the main (MOB) and accessory (AOB) olfactory bulb by serotonin (5-HT) using an in vitro, brain slice approach in postnatal (P15-30) day mice. In the MOB, 5-HT elicited three types of responses in 94% of 158 cells tested. Cells were either directly excited (73%, n = 115), inhibited (9%, n = 15), or showed a mixed response −first inhibition followed by excitation (12%, n = 19). In the AOB, 83% of 115 cells were inhibited with 17% of cells showing no response. Albeit located in parallel partitions of the olfactory system, 5-HT largely elicited excitation of MOB MCs while it evoked two different kinetic rates of inhibition in MCs of the AOB. Using a combination of pharmacological agents, I found that the excitatory responses in MOB MCs were mediated by 5-
HT2A receptors through a direct activation. In comparison, 5-HT-evoked inhibitory responses in the AOB arose due to a polysynaptic, slow-onset inhibition attributed to 5-HT2 receptor activation exciting GABAergic interneurons. The second type of inhibition had a rapid onset as a result of direct inhibition mediated by the 5-HT1 class of receptors. The distinct serotonergic modulation of MCs between the MOB and AOB could provide a molecular basis for differential chemosensory behaviors driven by the brainstem raphe nuclei into these parallel systems.
In the second project of my dissertation, I explored the modulation of glucagon-like peptide-1 (GLP-1) neurons in the olfactory bulb (OB). A population of GLP-1 neurons was recently discovered in the OB. The functions of these neurons remain incompletely understood. Herein, I used an in vitro, brain slice approach to investigate the modulations of GLP-1 neurons. Juvenile mice (P20 to P45) of both sexes were used to examine the involvement of centrifugal projections from higher brain areas including serotonergic, cholinergic, and noradrenergic afferents. Bath application of serotonin (40 µM, n = 4) and norepinephrine (100 µM, n = 4) had no effect on the evoked firing frequency. Acetylcholine (ACh; 100 µM), however, led to either inhibition or excitation of GLP-1 neurons. For inhibition, ACh induced a small outward current (5.1 ± 1.8 pA, n = 9) recorded by voltage-clamp when neurons were held at −70 mV. When
xii recorded in current-clamp mode, ACh delayed the latency to first spike (control: 253 ± 30 ms, ACh: 396 ± 4 ms; n = 2). For excitation, bath application of ACh resulted in 1.9 ± 0.6-fold increase in firing frequency (n = 21). Previous evidence showed that GLP-1 neurons in the brainstem could be modulated by metabolic-related hormones such as leptin and cholecystokinin (CCK). I found that GLP-1 neurons could be modulated by CCK, but not by leptin. Bath application of CCK (0.8 µM) led to either cessation of firing (n = 10) or an increase in firing of 1.7 ± 0.4-fold (n = 11). Lastly, mice were injected intraperitoneally with the GLP-1 analogue Exendin-4 (0.4 µM /kg) or control saline and tested 30 minutes post injection in a habituation- dishabituation odor test. Mice receiving Exendin-4 failed to show significant dishabituation, demonstrating impaired ability to discriminate a novel odor from a familiar odor.
One primary target of neuromodulation is ion channels. Depending on which group of neurons and in which brain region it is expressed, the same type of ion channel can contribute to multiple functions. In the third project of my dissertation I examined the consequences of loss of function of voltage-gated potassium channel Kv1.3. It has long been recognized that olfaction and emotion are linked. My study aimed to investigate the roles of olfaction in modulating anxiety. Kv1.3 knockout mice (Kv1.3-/-), which have heightened olfaction, and wild-type (WT) mice were examined for anxiety-like behaviors. Because Kv1.3-/- mice have also been observed to show increased locomotor activity, which is one behavior reported in animal models of attention-deficit/hyperactivity disorder (ADHD), inattentive behavior was quantified for both genotypes. Kv1.3-/- mice showed increased anxiety levels compared to their WT counterparts and administration of methylphenidate (MPH) via oral gavage alleviated their increased anxiety. Object-based attention testing indicated Kv1.3-/- mice had attention deficits and treatment with MPH also ameliorated this condition. My data suggest that heightened olfaction does not necessarily lead to decreased anxiety levels, and that Kv1.3-/- mice may be used as a behavioral model of the inattentive subtype of ADHD.
xiii CHAPTER 1
INTRODUCTION
1.1 Origin of Neuro-electricity and the Development Patch-clamp Technology
The concept of bioelectricity can be traced back to the ancient science era. In his book Sir Isaac Newton wrote “electric bodies operate to greater distances…and all sensation is excited, and the members of animal bodies move at the command of the will, namely, by the vibrations of this spirit, mutually propagated along the solid filaments of the nerves, from the outward organs of sense to the brain, and from the brain into the muscles. But these are things that cannot be explained in few words, nor are we furnished with that sufficiency of experiments which is required to an accurate determination and demonstration of the laws by which this electric and elastic spirit operates.” (Newton, 1713). Other scientists during the early 18th century also suggested the electric nature of nerve signals (Hales, 1733). By the middle of 18th century the theory on neuro-electricity had begun to form. The first experiments demonstrating bioelectricity came from the electric eel and the electric ray. John Walsh observed electric activity such as electric shocks generated by these live animals in late 18th century (Piccolino & Bresadola, 2002). These experiments did not address neuro-electricity directly. However, they played an important role in propagating the concept of bioelectricity and promoted the study of neuro- electricity. Not long after that, Italy anatomist Luigi Galvani began to perform his electrophysiological experiments using a frog neuro-muscular preparation developed by the Dutch natural scientist, Jan Swammerdam (Cobb, 2002). When an electric stimulus was delivered to the frog preparation, it triggered vigorous muscle contractions (Galvani, 1791). Galvani even tested this phenomenon outside the laboratory. He connected a long wire to the neuro-muscular preparation and pointed the wire toward the sky during a thunderstorm. He observed that the contraction of limb muscles corresponded well with the occurrence of lightning before the thunder. Galvani was most likely the first to demonstrate the propagation of bioelectricity by attaching the sciatic nerve of the first frog leg to the nerve or the muscle of the second leg. By doing this, he observed contractions in both preparations (Galvani, 1841).
1 From then on scientists were trying to measure this bioelectricity with more advanced instruments. The first measurement of electrical activity from the neuro-muscular preparation was made by Leopoldo Nobili in 1828 using an electromagnetic galvanometer (Nobili, 1828). He observed a current associated with muscle contraction that he called frog’s current. However, Nobili believed that the current he measured was a thermoelectrical current rather than a bioelectricity. Until a decade later another scientist Carlo Matteucci demonstrated the biological nature of frog’s currents. Matteucci built up a pile of frog thigh muscles in series and measured the current with a galvanometer. He observed when more thighs were added to the circuit, the current became bigger (Matteucci, 1844). The first indirect measurement of action potential was performed by Emil Heinrich du Bois-Reymond in Berlin (du Bois-Reymond, 1884). By measuring the potential difference between the intact surface and the cut portion of the tissue he observed that excitatory electrical response decreases the potential difference or even reduces it to zero difference. The first measurement of the speed of neuro-electricity propagation was done by Herman Ludwig Ferdinand von Helmholtz by measuring the delay between the application of an electrical stimulus and muscle contraction (Helmholtz, 1850; 1852). Another advance in the instrumental measurement of bioelectricity came from the invention of the rheotome by Julius Bernstein. The rheotome can record very fast electrical signals in the range of microseconds. Using this instrument Bernstein recorded the resting membrane potential and action potential in the neuro-muscle preparation. He found that during the action potential the potential difference not only reached a zero point, but it also went into opposite direction—the discovery of the action potential overshoot (Bernstein, 1868; 1871).
Although a lot of progress of measurement of neuro-electricity has been made in the 18th century, there were still no direct measurements of current in neurons. The reason for that is obvious—neurons are too small to be measured with the instruments available at that time. However, the situation was changed with the discovery of the giant squid axon by John Z. Young in early 19th century (Young, 1936). The diameter of the giant squid axon can reach up to 1 mm. Its manipulable size quickly allowed it to become a model system to study neurophysiology. Another instrumental improvement that made direct measurement of current inside a neuron was the fabrication of mini-electrodes that could be inserted into the squid giant axon. Using mini- electrodes Alan L. Hodgkin and Andrew F. Huxley (Hodgkin & Huxley, 1939) and
2 independently, Kenneth S. Cole and Howard J. Curtis (Curtis & Cole, 1940) directly measured the resting and action potentials in the giant squid axon. The next improvement in the measurement of neuro-electricity came from the voltage-clamp technique developed by Kenneth S. Cole (Cole, 1949) and by George Marmont (Marmont, 1949). This technique enabled scientists to measure ionic currents under certain voltage, which was achieved by inserting two electrodes into the membrane. One was called the “voltage electrode” which measured transmembrane voltage relative to ground. The other was called the “current electrode” which injected currents into the membrane. The experimenter could set a “holding voltage” through an external command. Voltage-clamp received this command voltage (Vc), compared it to the transmembrane voltage (Vm) it measured, and calculated the difference between the two voltages. Then through current injection voltage-clamp brought the Vm to the Vc. If there was any ionic current passing through the membrane that deviated the Vm from the Vc, voltage- clamp circuits would inject an opposite current trying to bring the Vm back to Vc. So voltage- clamp produced a current equal and opposite to the ionic current. Voltage-clamp is a powerful tool for scientists to study voltage-dependent ionic currents. However because of the size limit of mini-electrodes the early voltage-clamp experiments were conducted mostly using the giant squid axon. The situation was changed with the introduction of glass microelectrodes by Gilbert N. Ling and Ralf W. Gerard in 1949 (Ling & Gerard, 1949), which started an era of single-cell electrophysiology. These microelectrodes were fabricated from glass capillary tubes that were heated and then stretched out to form very thin tips. The diameters of microelectrode tips were usually less than a micron, which were much smaller than the cell body of most neurons. So it became practical to insert these microelectrodes into neurons and most types of neurons were able to endure the penetration trauma by the microelectrodes for a reasonable length of time. Soon after the introduction of glass microelectrodes they were adapted for a variety of cell types in electrophysiological experiments (Purves, 1981).
However, there were some disadvantages with this traditional electrophysiological recording method. The main problem was that penetration of the membrane by microelectrodes causes large leak currents, which prevents low-noise recordings. Since the introduction of glass microelectrodes scientists started to use them for extracellular recording. In the 1960s, several scientists used these glass microelectrodes for focal stimulation and even monitoring membrane
3 currents (Strickholm, 1961; 1962; Neher & Lux, 1969). By pressing the tip of a glass microelectrode against the cell membrane it bestowed upon the membrane patch underneath some degree of electrical isolation. In 1976, using similar extracellular recording technique, Ervin Neher and Bert Sakmann recorded the first single ion currents in nicotinic acetylcholine receptors within native muscular membranes (Neher & Sakmann, 1976). They constructed glass microelectrodes with relative small tip (1-2 micrometers in diameter) and pressed the tip to the cell membrane to electrically isolate a small patch of the membrane to record the currents going through it. This is where the name “patch-clamp” came from. However, the measurement was not flawless. There still was high background noise because of the not so tight seal between microelectrode and membrane. The next major improvement of the patch-clamp technique resulted from an accidental observation. After many efforts (including polishing or coating microelectrode tips, cleaning membrane surfaces, etc.) to improve the seal between microelectrode and membrane with little success, Erwin Neher et al. observed by chance that when they applied a slight suction to the lumen of microelectrode, the seal increased dramatically by more than two orders of magnitude reaching the gigaohm range (Hamill et al., 1981; Sakmann & Neher, 1984). This is where the name “Gigaseal” came from. The improved seal greatly reduced the background noise for single ion channel recording. Unexpectedly, this Gigaseal also provided other benefits for electrophysiological recordings. Soon scientists realized that the Gigaseal not only provided an excellent electrical isolation but also formed a tight mechanical connection between the microelectrode tip and the membrane. By simply withdrawing the microelectrode scientists could acquire an excised membrane with tight seal for electrophysiological experiments. Alternatively, a short pulse of quick suction or voltage could be delivered to the microelectrode to rupture the membrane underneath it while still maintaining Gigaseal. In that way, the microelectrode now had electrical access to the whole cell, which today is called the whole-cell patch-clamp mode.
From then on the patch clamp technique reached its full-fledged application and caused a revolution in the field of electrophysiology. It has been applied not only to study single ion channels but also to investigate electrical activity of different types of neurons both in vitro and in vivo. Because of their contributions to the patch-clamp technique and fundamental studies of ion channels Erwin Neher and Bert Sakmann shared the Nobel Prize in Physiology or Medicine
4 in 1991. The patch-clamp technique opened the door to the investigation of single ion channels. Next, I will briefly introduce the history of the discovery of ion channels and their important functions in human physiology.
1.2 Introduction of Ion Channels and their Functions
When Galvani performed his classical electrophysiological experiments using the frog neuro-muscular preparation, he also developed a theory of animal electricity (Galvani, 1794; Piccolino, 1997). He believed there was a non-conductive sheath between conductive external medium and internal space of the muscle or the nerve fiber, and that the electricity was the result of the accumulation of charges across the non-conductive sheath. Galvani predicted that there would be a pathway through the non-conductive sheath, which might allow flow of charges across the external and internal surfaces. He imagined these water-filled channels distributed on the surface of the muscle or the nerve fiber that would allow the electrical current to flow, hence underlying neuro-excitation. It turned out that the non-conductive sheath was the cell membrane and the water-filled channels were ion channels that we are talking about today. In fact, the word ion means "wanderer" in Greek. When you place ions in an electric field, they will move according to the strength and direction of the electric field.
The next theory breakthrough about ion channels came from Julius Bernstein who used the rheotome device to record the resting membrane potential and action potential in a neuro- muscular preparation. Bernstein developed some concepts that are important for modern electrophysiology such as the ionic theory, the Nernst Equation, and the semi-permeable membrane. He postulated that there is a selective potassium ion (K+) permeability of the membrane that could account for the presence of resting membrane potential (Bernstein, 1912). Another scientist who made important contributions to the excitable membrane concept is Charles Ernst Overton. He observed that certain lipid-soluble dyes could enter cells much easier than the dyes that are only soluble to water and proposed a “lipoidal membrane” model for cell membranes (Overton, 1899). Overton also identified that sodium ions (Na+) were responsible for the action potential overshoot and suggested that the action potential resulted from the exchange
5 of Na+ and K+ (Overton, 1902). Using another model system—frog heart Sidney Ringer discovered the importance of different ions for maintaining the beating of the heart (Ringer, 1882a; 1882b; 1883). Specifically, he found that calcium, sodium, and potassium were needed for heart contraction.
Due to the introduction of the giant squid axon model it had become possible to study ionic currents directly. Using extracellular electrodes, Kenneth S. Cole and Howard J. Curtis measured the membrane conductance of squid axons. They observed the rapid increase of the membrane conductance when the action potential occurred, which indicated transmembrane current generation (Curtis & Cole, 1940). A milestone of studying ion channels came from Hodgkin and Huxley’s research on action potentials in the squid axon. In 1952, deploying voltage-clamp and ion substitution techniques, Hodgkin and Huxley systematically studied the ionic mechanisms underlying the initiation and propagation of action potentials (Hodgkin et al., 1952; Hodgkin & Huxley, 1952b; 1952c; 1952d; 1952e; 1952f) and came up with a mathematical model describing the production of action potentials (Hodgkin & Huxley, 1952a). The Hodgkin-Huxley model proposes that the action potential is produced by ion fluxes across different ion channels, mainly voltage-dependent sodium and potassium channels, voltage- independent leakage channel, according to their electrochemical gradients. In their ion theory Hodgkin and Huxley also suggested different cell types could have different ion channel composition allowing for specific membrane permeabilities to ions to define the electrical characteristics of the cell. The Hodgkin-Huxley model demonstrates how scientists can apply mathematics to model complex biological processes. It is one of the most successful mathematical models in neuroscience and is applied to study bioelectricity from simple single- celled organisms to complex neurons in animals’ brain. Because of their contribution to the research of ion channels, Hodgkin and Huxley received the Nobel Prize in Physiology or Medicine in 1963.
Most fascinating, the Hodgkin-Huxley model was proposed well before any detailed knowledge of ion channels and cell membrane structure were available. Theoretically, it was suggested that nerve cells could change their permeability to an ion through the opening and closing of the pores of ion channels. One way to test this theory was to record the current changes discontinuously when pores open and close at the single ion channel level. The main 6 obstacle in recording single channel currents was to resolve extremely low pico-ampere currents flowing through a single ion channel distinguished from background electrical noise. The background electrical noise is always proportional to the clamped membrane area. For traditional voltage-clamp experiments with microelectrodes the background electrical noise can be as high as hundreds of pico-amperes because the membrane of the whole cell is clamped. If a small membrane area is isolated, for example a few square micrometers, then the background electrical noise is reduced quite low that pico-ampere currents can now be detected. With the invention of the patch-clamp technique it is possible to measure single channel currents. Early attempts to record single ion channel current changes were performed in artificial membranes with pore- forming materials such as antibiotic gramicidin (Haydon & Hladky, 1972). In 1976, using microelectrodes with small tip diameters (about 1-2 micrometer) to isolate a small patch of membrane (less than 10 square micrometers), Ervin Neher and Bert Sakmann successfully recorded the first single ion currents of nicotinic acetylcholine receptors (nAChR) in the native muscular membrane (Neher & Sakmann, 1976).
With the advance of the patch-clamp technique more and more single ion channel currents were measured. But scientists still had little knowledge about the structure of ion channels. With the development of recombinant DNA technology (Cohen et al., 1972) in the 1970s combined with advances in DNA sequencing, scientists began to have a glance at what an ion channel looked like. The nAChR was the first ion channel expressed in the Xenopus oocytes using recombinant DNA technology (Barnard et al., 1982). With the known DNA sequence scientists could then predict the amino acid sequence of the nAChR protein. Five similar subunits were seen from the primary amino acid sequence. From the primary structure scientists could predict what the ion channel should look like in its 3D-structure. Another insight learned through molecular genetics was the great variety of ion channels. It is believed that there are over three hundreds human genes encoding ion channel subunits (Ashcroft, 2006). Further diversity of ion channels comes from alternative splicing of subunit genes and distinct combinations of different subunits. The ion channels can be classified based on their gating mechanisms to voltage-gated channels, ligand-gated channels, and other gating mechanisms such as light-gated channels, mechanosensitive ion channels, cyclic nucleotide-gated channels, and temperature- gated channels. Based upon the ion passing through the ion channel selectivity filter ion channels
7 can be divided into sodium, potassium, chloride, calcium channels, protons channels, non- selective cation channels and so on.
Molecular genetics provides tools for scientists to have a peek at ion channels. However, it was not until the application of another ground-breaking technology—X-ray crystallography, that scientists began to observe the structure of ion channels directly. X-rays was discovered by German scientist Wilhelm Röntgen in 1895 (Underwood, 1946). In 1912, the X-ray was first used to study crystals structure by Max von Laue and his colleagues and X-ray diffraction patterns were observed (Eckert, 2012). In 1912–1913, William Lawrence Bragg developed methodology to decode X-ray diffraction pattern to solve a crystal’s atomic structure (Bragg & Trinity College, 1912; Bragg, 1913). Collaborating with his Father, William Henry Bragg, the Braggs revolutionized the era of X-ray crystallography. During the early age of X-ray crystallography the structural studies were mainly focused on simple inorganic crystals and minerals. Later on, X-ray crystallography was expanded to organic compounds and small biological molecules. A representative work during this period was done by Dorothy Crowfoot Hodgkin (see obituary by Glusker, 1994). She and her team solved the structures of cholesterol, penicillin, vitamin B12, insulin, and so on. In the 1950s, crystal structures of complex biological molecules such DNA (Watson & Crick, 1953) and protein myoglobin (Kendrew et al., 1958) began to be solved by X-ray crystallography. In 1998, the first crystal structure of a voltage- gated ion channel, the bacteria potassium channel KscA , was solved (Doyle et al., 1998). This meant that scientists could determine the exact positions of each atom of the ion channel in 3- dimensional space. Following that, a few other ion channel structures were solved (Zhou et al., 2001; Kuo et al., 2003; Unwin, 2005). However, because most ion channels are membrane- related complex proteins with multiple membrane-crossing domains and intricate charging patterns, it continues to be challenging to get crystals of ion channels. So there are a lot more ion channel structures yet to be solved. Furthermore, in order to know how an ion channel functions, a series of ion channel crystal structures in different operational states must be determined. Determination of crystal structure remains one of the most exciting and challenging active areas in modern ion channel research.
Apart from progresses in ion channel structure, scientists are also gaining insight concerning ion channels function. With advances in molecular genetics such as site-directed 8 mutagenesis, scientists are able to study how defects in ion channel genes affect organisms. One example is the discovery of “Shaker” ion channel. It was found that a mutation in the fly Drosophila melanogaster led to trembling of appendages under anesthesia (Catsch, 1944). Later this mutation was located to a gene that codes for a voltage-gated potassium channel (Salkoff & Wyman, 1981; Kamb et al., 1987; Tempel et al., 1987; Papazian et al., 1987). Since then, more and more ion channels have been functionally characterized. It turns out that ion channels have diverse functions in physiology and are involved in various processes such as sensory transduction, locomotion, learning and memory, and development (Jentsch et al., 2004). The dysfunction of ion channels has been linked to more than 60 diseases in humans. These diseases are collectively referred to as “channelopathies” (Jentsch et al., 2004; Ashcroft, 2006). Because of their significant impact on human diseases ion channels have become important therapeutic targets for drug discovery (Bagal et al., 2013). Most recently, with the rapid development of gene-editing technologies such as the CRISPR-Cas9 system it seems promising to utilize these technologies to treat the congenital diseases caused by mutations in ion channels (Mali et al., 2013; Ran et al., 2015; Yin et al., 2016). Given the essential roles of ion channels in human physiology, continuing efforts should be made in ion channel research.
1.3 Neuromodulation in the Olfactory Bulb
Our nervous system is an intricate information processing machine. It receives different types of information through sensing organs, processes them internally, and produces output signals to regulate behavior. The nervous system utilizes a variety of signal molecules called neurotransmitters including numerous amines, neuropeptides, gases, and other molecules for information transmission (Lodish et al., 2000). Simply put, the information flow in the nervous system can be divided into two categories: neurotransmission and neuromodulation. Neurotransmission is usually referred to as fast synaptic transmission mediated by classical neurotransmitters such as glutamate and GABA. Unlike neurotransmission, which basically excites or inhibits the target neuron, neuromodulation rather leads to the modification of other events occurring at the target neuron. Through other neurons or substances released by other neurons, neuromodulation usually results in the alteration of cellular and/or synaptic properties
9 of the target neuron. Another distinction between neurotransmission and neuromodulation lies in the different nature of the two processes. For neurotransmission it is typically transitory without involving intracellular events, and usually limited to the sub-synaptic regions. For neuromodulation it can have prolonged effects on distant locations other than synaptic regions, and often involves intracellular events (Florey, 1967). Neurotransmission is like a high-way system keeping information flowing in the nervous system, while neuromodulation acts like controlling stations and managing instructions to make adaptations in order for the nervous system to function properly.
Neuromodulation is carried out through a variety of mechanisms. One of the main mechanisms is activation of G-protein-coupled receptors (GPCRs) by neuromodulators. Through GPCRs and their related intracellular events, neuromodulators can exert effects at the single neuron level by altering ion channel function and expression, the synaptic level by changing the strength of synapses, and eventually on the circuit level (Levitan, 1988; Marder & Thirumalai, 2002; Bargmann, 2012; Marder, 2012). Neuromodulation of neural circuits is known to influence brain states and ultimately alter behaviors (Harris-Warrick & Marder, 1991; Beverly et al., 2011; Lee & Dan, 2012; Liu et al., 2012a). Neuromodulation has been shown to play important roles in multiple processes such as sensory adaptation (Prabhakar et al., 2009), reward (Giardino & de, 2014), addiction (Bari et al., 2014), learning and memory (Puig et al., 2014), aggression (Alekseyenko et al., 2014) and so on. Research on the sources, time course, functions, and mechanisms of neuromodulation is critical for understanding how the nervous system produces behavior. A big portion of my thesis focuses on neuromodulation in the olfactory bulb (OB). Next I will introduce some background on that region of the brain.
The OB is a relay station connecting olfactory sensory neurons in the olfactory epithelium to higher brain areas. It has diverse neuron cell types in a nicely organized laminar structure (see Figure 1.1 from Nagayama et al., 2014) and receives multiple centrifugal projections from cortical regions, which makes it a good model system to study neuromodulation. In the OB, there are multiple types of neurons forming sophisticated circuits to process information before transmitting it further to the olfactory cortex (Nagayama et al., 2014). Histologically, the OB can be divided into different layers. By using Golgi-staining in the 1970s
10 researchers were successful in visualizing multiple layers in the OB. They showed that different layers were composed of morphologically distinct cells (Price & Powell, 1970a; 1970b; 1971).
Figure 1.1, Basic model of the olfactory bulb neural network. Abbreviation: ONL, olfactory nerve layer; GL, glomerular layer; EPL, external plexiform layer; MCL, mitral cell layer; IPL, internal plexiform layer; GCL, granule cell layer; PG cell, periglomerular cell; sSA cell, superficial short-axon cell.
As shown in Figure 1.1, from outer to inner space, the OB is divided into the olfactory nerve layer (ONL), glomerular layer (GL), external plexiform layer (EPL), mitral cell layer (MCL), internal plexiform layer (IPL), and granule cell layer (GCL). Conventionally, the neurons in the OB have been categorized based on the layers in which their cell bodies are located. For example, in the GL there are three morphologically distinct cell types: periglomerular (PG) cells, external 11 tufted cells (ETC, not shown in the figure), and superficial short-axon (sSA) cells. In the EPL, tufted cells are one type of projection neurons that are scattered throughout the layer. Mitral cells are the other type of projection neurons whose somata are located in the MCL. Both mitral and tufted cells send a single primary dendrite into a defined glomerulus, where they receive synaptic inputs from olfactory sensory neurons (OSNs) and make reciprocal synapses with PG cells. Their secondary dendrites are elongated in the EPL, where reciprocal synapses are formed with granule cell dendrites. The axons from mitral cells and axon collaterals of tufted cells run through the IPL and project to the olfactory cortex. The GCL is largely composed of granule cells that send dendrites apically into the EPL.
Olfactory information reaches the OB through OSNs and is conveyed to higher brain regions. However, the OB is not just a simple relay station. It is heavily modulated by local circuits and multiple centrifugal inputs. Within the OB the local lateral inhibition that involves reciprocal dendrodendritic synapses has been extensively studied (Jahr & Nicoll, 1980; Isaacson & Strowbridge, 1998; Urban, 2002; Isaacson & Vitten, 2003; Dietz et al., 2011). The centrifugal inputs have also been shown to play important roles in modulating the activity of olfactory neurons and the output of the OB. First, there are dense feedback fibers from cortical and subcortical areas. The piriform cortex sends projections back to the ipsilateral OB. The anterior olfactory nucleus also projects back to both the ipsilateral and contralateral OB. These feedback axons synapse with granule cells, PG cells, and sSA cells. By exciting these inhibitory interneurons the feedback axons can inhibit the activity of mitral/tufted cells, thereby modulating the output of the OB (Yan et al., 2008; Boyd et al., 2012; Markopoulos et al., 2012). The other centrifugal inputs come from brain’s diffuse modulatory systems, including cholinergic, noradrenergic, and serotonergic systems. The OB receives cholinergic and GABAergic inputs from the horizontal limb of the diagonal band of Broca (HDB) of the basal forebrain (Zaborszky et al., 1986; Kasa et al., 1995). This cholinergic input has been shown to have an important influence in olfactory processing (Devore & Linster, 2012). More specifically, odor response tuning of mitral/tufted cells is sharpened by the cholinergic input, thereby facilitating contrast enhancement (Castillo et al., 1999; Ma & Luo, 2012). The GABAergic input, which directly inhibits granule cells, has also been shown to be important for olfactory discrimination (Nunez- Parra et al., 2013). The noradrenergic input comes from the locus coeruleus (Shipley et al., 1985).
12 In adult rats noradrenergic modulation was reported to influence odor discrimination, but not the formation of odor habituation memory (Mandairon et al., 2008). In neonatal animals, increased noradrenaline induced by somatosensory stimulation has been shown to result in neural changes at both the main and accessory olfactory bulbs to affect a range of olfactory behaviors including odor discrimination and more complex behaviors such as memory formation during mating (Brennan & Kendrick, 2006). The OB also receives a serotonergic projection from the brainstem raphe nuclei (Cairncross et al., 1979; McLean & Shipley, 1987a; McLean & Shipley, 1987b). It has been shown that this serotonergic projection can modulate olfactory information flow to the OB and that this modulation may depend upon the animal’s behavioral state (Petzold et al., 2009). In this study, the authors electrically stimulated the dorsal raphe nuclei and recorded odor- evoked glomerular responses at the same time. Endogenous serotonin released by the electrical stimulation attenuated odor-evoked responses without detectable bias in glomerular position or odor identity. But weaker glomerular responses were less sensitive to the raphe nuclei stimulation than strong responses.
In summary, the OB is a good model to study neuromodulation because of its anatomically distinct organization and accessibility for in vivo electrophysiology and imaging. However, due to its complex lamination and diverse cell types there remain many questions. For example, there are seven types of non-GCs including deep short-axon cells (dSACs) in the GCL (Ramon y Cajal, 1911; Price & Powell, 1970a; Schneider & Macrides, 1978). While dSACs can be further divided into three subtypes: GL-dSACs, EPL-dSACs, GCL-dSACs (Nagayama et al., 2014). Understanding the cell type specific modulation is still an ongoing task. Another important question is how centrifugal projections modulate multiple targets in the OB. What’s the difference among the modulations of multiple targets by the same centrifugal projection? How do they coordinate with each other to modulate olfactory output?
13 CHAPTER 2
DIFFERENTIAL SEROTONERGIC MODULATION ACROSS THE MAIN AND ACCESSORY OLFACTORY BULBS
2.1 Introduction
Monoamine 5-hydroxytryptamine (serotonin, 5-HT) is an important signaling molecule for a diverse number of behavioral and physiological functions (Berger et al., 2009), whereby at least 14 different 5-HT receptors have been identified and grouped into seven major subfamilies based upon structure, pharmacology, and downstream signal transduction mechanisms (Millan et al., 2008). In the central nervous system (CNS), serotonin and its various receptors regulate a breadth of neuropsychological processes including mood, reward, aggression, appetite, and memory (Roth, 1994; Roth & Xia, 2004; Mittal et al., 2016). The CNS serotonin system mainly originates from the brainstem raphe nuclei and projects to almost every part of the brain (Jacobs & Azmitia, 1992). As such, all major brain areas express specific subfamilies of 5-HT receptors (Roth, 2007). Many receptor subfamilies are important therapeutic targets for anti-psychotic drug development and are of broad physiological importance for thermoregulation, pain, sleep, and smooth muscle contraction (Reynolds et al., 2005; Pithadia & Jain, 2009; Palacios, 2016).
The olfactory bulb (OB) makes an amenable model to investigate serotonin neuromodulation due to its distinct anatomical organization that facilitates electrophysiological studies and its known receipt of serotonergic projections from the brainstem raphe nuclei (Broadwell & Jacobowitz, 1976; de Olmos et al., 1978; Araneda et al., 1980; McLean & Shipley, 1987a; Suzuki et al., 2015). The OB is composed of two distinct structures: the main (MOB) and accessory olfactory bulb (AOB). Albeit sharing some common cytological organization with similarly named neurolamina –nomenclature that was carried forward from the
This Chapter was published as, “Differential serotonergic modulation across main and accessory olfactory bulbs”. The Journal of Physiology. 2017. 595: 3515-3533. By Zhenbo Huang, Nicolas Thiebaud, Debra Ann Fadool. ZH was responsible for the collection of all electrophysiological data and preparing the first draft of the manuscript. All authors designed the experiments, assembled and interpreted the data, aided in spike analysis, and wrote the manuscript.
14 MOB to the AOB by Ramon y Cajal (Figueres-Onate et al., 2014) −there are several noteworthy differences in the organization of AOB cell types whose biophysical properties are largely incompletely characterized. A prominent difference lies in the principle output neurons, called mitral cells (MCs) in both systems. In fact, Larriva-Sahd (2008) suggested that in the AOB, they should not actually be referenced as ‘mitral’ per se because their somata are not mitre in shape as they are in the MOB. AOB MCs are largely arranged as a scattered array, as opposed to a highly linear lamina, and have a multi-tufted morphology that terminates in 3-8 glomeruli rather than a single apical dendritic tuft leading to a single glomerulus (Ramon y Cajal, 1911; Takami & Graziadei, 1990; Jia et al., 1999; Urban & Castro, 2005). Hovis et al. (2012) examined the development of the unique circuit in the AOB to show that MC dendrites target glomeruli containing vomeronasal sensory neurons expressing the same receptor and that connectivity is both precise and activity modulated. As such, MOB and AOB MCs have distinct passive and active intrinsic properties to permit differential information processing (Zibman et al., 2011). Noguichi et al. (2014) support a computational model whereby dual informational processing might exist between the MOB and AOB. Shpak et al. (2012) and earlier in vivo work by Luo et al. (2003) demonstrate that AOB MCs, unlike those in the MOB, respond with strong, persistent excitation in response to transitory stimulation.
Despite initial explorations of basal biophysical differences across MOB and AOB MCs, the degree of neuromodulation across these systems has not been widely explored. One recent study has shown opposing effects of cholinergic-modulation in the AOB vs. the MOB and suggests that these circuits utilize different physiological solutions for processing odor information (Smith et al., 2015). While there is strong structural and biophysical characterization of the role of serotonergic signaling in the MOB (Hardy et al., 2005; Petzold et al., 2009; Liu et al., 2012b; Schmidt & Strowbridge, 2014; Suzuki et al., 2015; Brill et al., 2016), there are no biophysical studies in the AOB involving serotonin modulation despite anatomical evidence that suggests the existence of serotonergic fibers (Broadwell & Jacobowitz, 1976; Takeuchi et al., 1982). Early reports indicate the importance of serotonergic pathways in the regulation of innate behaviors such as aggression (Vergnes et al., 1974; Diuzhikova et al., 1987). Given the important roles of the accessory olfactory system in social and reproductive behaviors,
15 serotonergic modulation of the AOB may be an important factor, however, studies are needed to test this notion.
Given the diversity and wide-spread distribution of serotonin signaling in the CNS, noteworthy circuitry differences between the two partitions of the OB, differential expression of serotonin receptors across the MOB and AOB (McLean et al., 1995), and distinct firing properties of MCs across these structures, we undertook an exploration of serotonin neuromodulation using an in vitro slice preparation of the AOB vs. MOB. Utilizing a pharmacological approach across a large sampled population, 5-HT2A receptors appear to mediate a direct excitation of MOB MCs whereas two different serotonin receptor types appear to mediate an inhibition of AOB MCs. AOB MCs are indirectly inhibited through activation of
GABAergic interneurons via 5-HT2 receptors or are directly inhibited through 5-HT1 receptors expressed on MCs. Economical utilization of the same molecule across two different parallel olfactory systems could serve to modulate distinct behaviors regulated by these olfactory sensory divisions.
2.2 Materials and Methods
2.2.1 Ethical approval
All animal experiments were approved by the Florida State University (FSU) Institutional Animal Care and Use Committee (IACUC) under protocol #1427 and were conducted in accordance with the American Veterinary Medicine Association (AVMA) and the National Institutes of Health (NIH). In preparation for OB slice electrophysiology, mice were anaesthetized with isoflurane (Aerrane; Baxter, Deerfield, IL, USA) using the IACUC-approved drop method and were then sacrificed by decapitation (AVMA Guidelines on Euthanasia, June 2007). All authors understood the ethical principles that The Journal of Physiology operates under and the work complied with the animal ethics checklist reported by Grundy (2015).
16 2.2.2 Animal care
All mice (Mus musculus, C57BL/6J strain; The Jackson Laboratory, Bar Harbor, ME, USA) were housed at the FSU vivarium on a standard 12 h/12 h light/dark cycle and were allowed ad libitum access to 5001 Purina Chow (Purina, Richmond, VA, USA) and water. Mice of both sexes at postnatal day 15-30 were used for the slice electrophysiology experiments, and had a body weight ranging from 5.7 g to 17.5 g [mean (SD): 9.2 (3.5) g]. A total of 85 mice were used in the present study.
2.2.3 Solutions and reagents
Artificial cerebral spinal fluid (ACSF) contained (in mM): 119 NaCl, 26.2 NaHCO3, 2.5
KCl, 1 NaH2PO4, 1.3 MgCl2, 2.5 CaCl2, 22 glucose; 305-310 mOsm, pH 7.3-7.4. Sucrose-modified artificial cerebral spinal fluid (sucrose ACSF) contained (in mM): 83 NaCl,
26.2 NaHCO3, 1 NaH2PO4, 3.3 MgCl2, 0.5 CaCl2, 72 sucrose, 22 glucose; 315-325 mOsm, pH 7.3-7.4. The intracellular pipette solution contained (in mM): 135 K gluconate, 10 KCl, 10
HEPES, 10 MgCl2, 2 Na-ATP, 0.4 Na-GTP; 280-290 mOsm, pH 7.3-7.4. All salts and sugars were purchased from Sigma-Aldrich (St. Louis, MO, USA) or Fisher Scientific (Pittsburgh, PA, USA). The synaptic blockers 2,3-dihydroxy-6-nitro-7-sulfamoyl-benzo[f]quinoxaline (NBQX), D-(-)-2-Amino-5-phosphonopentanoic acid (APV), and 2-(3-Carboxypropyl)-3-amino-6-(4 methoxyphenyl) pyridazinium bromide (Gabazine) were purchased from Ascent Scientific (Princeton, NJ, USA). All synaptic blockers were prepared as stock solutions (NBQX 5 mM, APV 25 mM, Gabazine 6 mM) in Milli-Q water and stored at −20°C. They were diluted to working concentrations (NBQX 5 µM, APV 50 µM, Gabazine 6 µM) in ACSF on the day of use.
The serotonin hydrochloride (5-HT) and serotonin receptor blockers methysergide maleate salt (methysergide), mianserin hydrochloride (mianserin), spiperone, and pindolol were purchased from Sigma-Aldrich. Methysergide stock solution (2 mM) was prepared in Milli-Q water and stored at −20°C. All other pharmacological agents were prepared at stock concentrations in ACSF (5-HT 0.8 mM, mianserin 80 µM, spiperone 80 µM, pindolol 2 mM with 1% acetic acid) and were diluted to working concentrations (5-HT typically 20, 40, 80 µM, mianserin 20 µM, spiperone 20 µM, pindolol 20 µM with 0.1% acetic acid) in ACSF on the day
17 of use. Previous reports have used a working range of 20 – 50 M to explore 5-HT modulation in the MOB (Hardy et al., 2005; Brill et al., 2016). In our studies, 20 M of 5-HT was used for MOB MC recordings whereas 40 µM was used for AOB MC recordings. We elected to use a higher concentration in the AOB to accurately sample the modulation effect knowing there were less serotonergic projections to the AOB (Broadwell & Jacobowitz, 1976; Takeuchi et al., 1982). All pharmacological agents were introduced to OB slices through the bath chamber. Controls consisted of bath ACSF or vehicle control (ACSF plus 0.1% acetic acid) depending upon the pharmacological agent employed.
2.2.4 Olfactory bulb (OB) slice electrophysiology
Mice were anesthetized by inhalation of isoflurane (see Ethics Section), quickly decapitated. The OBs were exposed by removing the dorsal and lateral portions of the skull between the lambda suture and the cribriform plate. The OBs were harvested and prepared for slice electrophysiology as described previously (Fadool et al., 2011). Briefly, after removing the dura, a portion of forebrain attached with the OBs was cut and quickly glued to a sectioning block with Superglue (Lowe’s Home Improvement, USA), and submerged in oxygenated
(95%O2 / 5%CO2), ice-cold, sucrose-modified ACSF for approximately two minutes (min) prior to vibratome sectioning (Vibratome/Leica Model 1000, Wetzlar, Germany). Coronal sections were made at a thickness of 300 µM and then allowed to recover in an interface chamber (Krimer & Goldman-Rakic, 1997) for 20-30 min at 33°C containing oxygenated ACSF. The interface chamber was then maintained at room temperature (23°C) for about 60 min before recording. OB slices were recorded in a continuously-perfused (Ismatec; 1-2 ml/min), submerged-slice recording chamber (RC-26, Warner Instruments, Hamden, CT, USA) with ACSF at room temperature. Slices were visualized at 10× and 40× using an Axioskop 2FS Plus microscope (Carl Zeiss Microimaging, Inc., Thornwood, NY, USA) equipped with infrared detection capability (Dage MTI, CCD100, Michigan, IN, USA). MCs in the MOB were identified as previously (Fadool et al., 2011) , while AOB lamination and MCs were identified based on previous reports (Salazar et al., 2001; Larriva-Sahd, 2008). Electrodes were fabricated from borosilicate glass (Hilgenberg #1405002, Malsfeld, Germany) to a pipette resistance ranging from 4 to 7 MΩ. Positive pressure was retained while navigating through the OB laminae until a slight increase in the pipette resistance (typically 0.1 - 0.2 MΩ) was observed; 18 indicating that the pipette tip had made contact with the cell. A giga-ohm seal (Re = 2.0 - 16.4 GΩ) was achieved by releasing positive pressure and simultaneously applying a light suction. The whole-cell configuration was established by applying a rapid but strong suction to the lumen of the pipette while monitoring resistance.
After establishing a whole-cell configuration, MCs were first sampled for adequate resting potential (less than −55 mV) and proper series resistance (less than 40 MΩ) prior to initiating a series of current-clamp recordings. Perithreshold current levels were determined by incrementally injecting 1000 milliseconds (ms)-long, 25 pA steps of current every 10 seconds (s), starting at −50 pA. Following the determination of spike threshold, cells were then stimulated with a long, perithreshold current step of 5000 ms duration (typically ranging from 5 to 100 pA) every 10 s to acquire spike frequency data for MOB MCs. For some AOB MCs, an interpulse interval (IPI) of 10 s led to hyperpolarization of the cell. Thus the IPI was increased to 18-22 s for some AOB MCs in order to adequately sample basal firing activity. The basal firing frequency was determined in control ACSF conditions for a minimum interval of 5 minutes by computing the mean firing frequency at the perithreshold step determined for an individual cell. The latency for the onset of suppression in AOB MCs was then measured as the time interval between the application of 5-HT and the time the firing frequency fell below this mean baseline frequency recorded for that cell. Because spike firing frequency was calculated across the duration of an applied current step (5 s) with a 10 s IPI, the resolution of the minimum onset latency for suppression was at least 15 s.
2.2.5 Data acquisition and statistical analysis
Current-evoked changes in membrane voltage were measured using a Multiclamp 700B amplifier (Axon Instruments, Molecular Devices, Sunnyvale, CA, USA). The analog signal was filtered at 10 kHz and minimally digitally sampled every 100 µs. The signals were digitized with a Digidata 1440A digitizer (Axon Instruments, Molecular Devices). The pipette capacitance was electrically compensated through the capacitance neutralization circuit of the Multiclamp 700B amplifier. Resting membrane potentials were corrected for a calculated −14 mV junction potential offset. Membrane capacitance and input resistance were acquired from the membrane test function of Clampex 10.3 (Axon Instruments). Data were analyzed using Clampfit 10.3
19 (Axon CNS), in combination with the analysis packages Origin 8.0 (MicroCal Software, Northampton, MA, USA), and Igor Pro 6.0.2 (Wavemetrics Inc., Portland, OR, USA) with the NeuroMatics 2.02 plugin (written by Jason Rothman). MOB MCs usually exhibit an intermittent firing pattern and are characterized by variable spike clusters. A cluster was therefore defined as three or more consecutive spikes with an inter-spike interval (ISI) of 100 ms or less (Balu et al., 2004). Spike frequency (calculated throughout pulse depolarization), ISI (calculated within a spike cluster) and action potential cluster duration were measured as previously described (Balu et al., 2004; Fadool et al., 2011). Changes in the spike frequency, ISI, or cluster duration were plotted as the mean percentage change compared to the control condition prior to bath application of the modulator. Baseline, treatment, and washout values were calculated from the mean of at least 10 consecutive traces.
Statistical significance was determined between baseline biophysical property and that following the modulator using a two-tailed, paired t-test or a one-way repeated measures analysis of variance (ANOVA) at the 95% confidence level (α = 0.05). Comparison of independent means was alternatively examined using a Student’s t-test. Spike firing frequency data were graphed by normalizing to the percent of the control condition, but non-normalized data were applied in the statistical analyses. All sampled populations were analyzed using Prism 6 (GraphPad Software Inc., CA, USA). For all applied t-tests and ANOVA tests, the assumptions of random sampling, normal distribution, and equal variances were examined (Steel R.G.D. & Torrie J.H., 1980). Data were tested for equal variance using the Variance Ratio Test (two sample) or the Fmax test (ANOVA; variance within group) to ensure they did not violate the homogeneity of variance (Steel R.G.D. & Torrie J.H., 1980). Data were tested within the Prism software for normality using a D’Agostino-Pearson omnibus normality test. If any of the assumptions for a parametric design were violated or the sample size was small, corresponding non-parametric tests such as the Wilcoxon matched-pairs signed rank test (non-parametric equivalent to paired t test) or Friedman test (non-parametric equivalent to repeated-measures ANOVA) were used. All reported values are mean (standard deviation, SD).
20 2.3 Results
2.3.1 Electrophysiological properties of MOB and AOB mitral cells
A total of 85 mice were used to acquire 328 recordings across our entire study for all electrophysiological measurements. Of the 180 MCs sampled from the MOB, 108 (60%) were spontaneously active; for AOB MCs, 70 out of 148 (47%) were spontaneously active under our recording conditions. For MOB MCs, more than half showed either spike clustering in spontaneously active neurons, or evoked spike clustering if they were initially silent, but were activated by injecting current. Here, a cluster was defined as three or more consecutive spikes with an interspike interval (ISI) of 100 ms or less (Balu et al., 2004). In contrast, sampled AOB MCs were rarely observed to have spike clusters. The intrinsic properties of our sampled MOB and AOB MCs are reported in Table 2.1. The membrane capacitance of MCs in the MOB was significantly greater than that in the AOB (Student’s t-test, p < 0.01) while the input resistance was significantly less than that measured from the AOB (Student’s t-test, p < 0.01). The mean resting membrane potential for MCs was more hyperpolarized in the AOB over that in the MOB (Student’s t-test, p < 0.01). These distinct intrinsic properties of MOB and AOB MCs may reflect differences in the capacity for extrinsic modulation.
Table 2.1 A comparison of intrinsic properties of mitral cells (MCs) in the main olfactory bulb (MOB) versus those in the accessory olfactory bulb (AOB)
MOB AOB
Membrane potential (mV) −58.5 ( 3.3) −67.6 (2.5)**
Membrane capacitance (pF) 117.1 (24.2) 84.3 (29.9)**
Input resistance (MΩ) 80.6 (21.7) 162.4 (67.2)**
Data are presented as mean (SD); n = 24 for MOB MCs, n = 21 for AOB MCs. **Significantly different mean values compared with MOB, Student’s t-test, p < 0.01.
21 2.3.2 The effects of 5-HT on MOB mitral cells
To study 5-HT modulation across the sampled MOB MC population, action potential (AP) threshold was initially determined using a brief current-step protocol (See Methods), and then cells were injected with the empirically-defined perithreshold current (typically ranging from 5 to 100 pA) using a 5000 ms pulse duration every 10 s (interpulse interval, IPI). Such spike firing frequency data were typically acquired for 30 min. A majority of the MOB MCs (126 of 180 examined; 70%) exhibited an increase in the evoked AP firing frequency in response to bath application of 5-HT (Fig. 2.1A, a). As shown in the comparative spike frequency plots, some cells (18/180; 10%) were inhibited by 5-HT (Fig. 2.1A, b). Another population of cells (23/180; 13%) exhibited a mixed response −first inhibition followed by excitation (Fig. 2.1A, c). A small portion of the cells (13/180; 7%) did not respond to 5-HT. Because the majority of MCs were excited by 5-HT, we chose to only examine the biophysical details of this subtype of cells for the remainder of our study and did not explore inhibition or mixed-response cells. It was also possible to elicit increased AP firing frequency in cells held at rest without injected current in response to bath application of 5-HT (Fig. 2.1B). 5-HT bath application typically led to a small amplitude depolarization of 2.9 (1.6) mV after a delay of 18 (11) s [mean (SD), n = 15]. The depolarization was accompanied by an increased AP firing frequency. For both evoked and spontaneous activity, the latency to increase firing frequency in response to 5-HT was likely attributed to permeation time into the slice, rather than the time course for a transduction event. Unless specified otherwise, all our subsequent reported recordings were from evoked responses where spikes were quantified during the depolarizing pulse.
To systematically quantify the magnitude of the modulation by 5-HT, AP firing frequency of the evoked activity was averaged for 20 traces (5 min) in control ACSF solution (Fig. 2.2A, ‘a’). Following bath introduction of 5-HT, the mean firing frequency was acquired for 20 traces (5 min) once the spike frequency was greater than the highest recorded value (in Hz) of the baseline, control activity (defined as an excitatory response) (Fig. 2.2A, ‘b’). For washout measurements, AP firing frequency was determined, again for a mean of 20 traces once firing frequency reached original pre-modulation firing rates (Fig. 2.2A, ‘c’). As shown in the bar graph of Fig. 2.2A, bath application of 5-HT resulted in a 6.8 (3.6)-fold (n = 15) increase in firing frequency of MOB MCs over that of the control condition (significantly-different, one-way 22
Figure 2.1 Mitral cells in the main olfactory bulb (MOB MCs) largely exhibit an increase in action potential (AP) firing frequency in response to serotonin (5-HT). A, a-c, Line graph summary of the changes in evoked, AP firing frequency in response to bath applied 5-HT indicated by the horizontal line for three representative MCs. Demonstrated is one representative cell from each type of response from the 180 cells sampled, where cells were either a, excited (126/180; 70%); b, inhibited (18/180; 10%); or c, demonstrated a mixed response to 5-HT (23/180; 13%) of first inhibition followed by excitation. A small portion of the cells (13/180; 7%) did not respond to 5-HT (data not shown). B, A representative current- clamp recording of a MC at resting state in a whole-cell configuration. Bath application of 20 µM 5-HT at the line; resting membrane potential (RMP) = −62 mV.
repeated-measures ANOVA, F(2, 28) = 166.4, p < 0.0001, with Bonferoni’s post-hoc test, p < 0.01). In this, and subsequent repeated-measures ANOVA tests, the three treatment groups were control, modulator (5HT), wash, yielding a degree of freedom of 2. The number of cells recorded across the three treatment groups is reported on the bar graphs, whereby the degree of freedom error was computed as degree of freedom within – degree of freedom subjects. The post-hoc analyses sought the location of the variance between the treatment groups and is indicated by an asterisk at the given probability level (p). MOB MCs usually exhibit an intermittent firing pattern that is characterized by variable length spike clusters. 5-HT significantly increased the number of spike clusters recorded within a recording window of ten, 5000 ms traces [Fig. 2.2B, d; 15.4 (14.7) = Control vs. 53.2 (28.9) = 5-HT, significantly-different by paired t-test, p < 0.01, n = 17] and increased the cluster duration [Fig. 2.2B, e; 153.3 (80.6) ms = Control vs. 241.7 (124.8) ms = 5-HT, paired t-test, p < 0.01], but did not significantly change the ISI [Fig. 2.2B, f; 43.0 (9.7) ms = Control vs. 40.7 (8.7) ms = 5-HT, paired t-test, p = 0.07].
23
Figure 2.2 Quantitative analysis of the excitatory response of MOB MCs. A, (Left) Raster plot showing evoked spike firing events binned in 5000 ms pulse duration (Event time) and recorded with an IPI of 10 s over a 25-30 min recording period, and the associated line graph of spike firing frequency under control ACSF, 5-HT, and then wash ACSF conditions. Each vertical bar corresponds to the duration of the applied bath condition. RMP = −64 mV, 50 pA perithreshold current injection. (Middle) Representative current-clamp recordings for the cell on the left at time points a, b, c indicated at the arrows. (Right) Bar graph of a population of cells recorded as on the left (n = 15). **Significantly- different from control, one-way repeated-measures analysis of variance (ANOVA), Bonferoni’s post-hoc test, p < 0.01. B, Spike cluster analysis. a, Representative recording in control ACSF condition where two spike clusters (Cluster) and the inter-spike interval (ISI) are indicated. Raster plot collected for a cell as in A, under b, control ACSF and then c, 5-HT bath application. d-f, Bar graphs indicating the mean number of AP clusters, cluster duration, and ISI for a paired recording in control ACSF and then following 5-HT bath application. **Significantly-different from control, paired t-test, n = 17, p < 0.01. 24 To determine if modulation altered AP shape in addition to firing frequency, similar within cell recordings were made as in Fig. 2.2 but applying an increased sampling frequency (20 kHz) of the data to determine shape properties. As anticipated for a depolarized membrane, 5-HT significantly decreased the mean spike amplitude [68.9 (4.3) mV = Control; 67.1 (4.4) mV = 5-HT] while it increased AP half-width [1.4 (0.2) ms = Control; 1.5 (0.3) ms = 5-HT] and 10- 90% rise time [0.7 (0.01) ms = Control; 0.8 (0.02) ms = 5-HT] (each significantly-different by paired t-tests, n = 15, p < 0.01). To examine whether 5-HT modulation depended upon synaptic processes or was intrinsic to MOB MCs, we tested for retention of 5-HT modulation for cells pre-incubated with fast glutamatergic and GABAergic synaptic blockers, namely a cocktail of NBQX, APV, and gabazine. As shown in Fig. 2.3A, MOB MCs retained a strong increased firing frequency [7.8 (4.5)-fold increase] in response to 5-HT in the presence of synaptic blockers (n = 14) that was significantly different [Fig. 2.3B; one-way repeated-measures ANOVA, F(2, 26) = 26.03, p < 0.001, with Bonferoni’s post-hoc test, p < 0.01]. Although the excitatory effect of 5-HT in the presence of synaptic blockers (Fig. 2.3B) appeared larger than that in the absence of blockers (Fig. 2.2A), this differential did not reach statistical significance, suggesting that 5-HT modulation was not significantly influenced by additional circuits (Student’s t-test, n = 29, p = 0.5211). These collective data suggest that the excitatory effect of 5-HT on MOB MCs is probably direct or intrinsic, without the requirement of synaptic transmission.
2.3.3 Pharmacological identification of serotonergic receptor type involved in the direct excitation of MOB mitral cells
Because our results indicated that 5-HT could directly depolarize the MOB MCs, we performed pharmacological tests to determine which 5-HT receptor might be involved in this action. For this series of pharmacological experiments, the non-selective 5-HT2,7 receptor antagonist methysergide (Hoyer et al., 1994), was introduced into the bath following acquisition of firing frequency under control ACSF conditions (Fig. 2.4A). Subsequent co-presentation of 5-HT and methysergide failed to increase firing frequency in 6 of 6 cells tested [Fig. 2,4A, right, 0.4 (0.1) Hz = methysergide vs. 0.4 (0.3) Hz = methysergide plus 5-HT, not significantly- different, paired t-test, p > 0.05]. Because a small percentage of MOB MCs were not excited by 5-HT, we completed a wash of the antagonist and then application of 5-HT to insure the recorded 25
Figure 2.3 Serotonin (5-HT) elicits direct excitation of MOB MCs. A, Raster plot as in Fig. 2 but where evoked responses were recorded in the presence of NBQX (5 µM), APV (50 µM), and Gabazine (6 µM). RMP = −61 mV; 75 pA perithreshold current injection. B, Bar graph of the mean spike frequency expressed as percent of the basal firing of the control. Same statistical analysis and notations as in Fig. 2.2A, n = 14.
neuron was indeed excitatory for the modulator (see Fig. 2.4A, left). Next, we tested mianserin, a more specific 5-HT2 receptor antagonist (Hoyer et al., 1994). Here, MOB MCs were prescreened for 5-HT excitatory responses, washed, and then pre-incubated with mianserin prior to co-presentation with mianserin and 5-HT (Fig. 2.4B, left). As shown in Fig. 2.4B, right, 5-HT excitation was also blocked by mianserin [1.0 (1.2) Hz = mianserin vs. 1.1 (1.5) Hz = mianserin plus 5-HT, not significantly-different, Wilcoxon signed-rank test, p > 0.99, n =5]. Spiperone, a more selective 5-HT2A receptor antagonist (Hoyer et al., 1994), similarly prevented the excitatory effect of 5-HT in 7 of 8 cells tested using an identical protocol as that previously [Fig. 2.4C, 0.9 (0.7) Hz = spiperone vs. 0.5 (0.4) Hz = spiperone plus 5-HT, not significantly- different, paired t-test, p > 0.05]. Finally, to confirm that the results of the receptor subtype pharmacology were the result of a direct effect on MCs, we extended these experiments to include the synaptic blockers, gabazine, NBQX, and APV, as similarly applied in Fig. 2.3.
26
Figure 2.4 5-HT-evoked excitation in MOB MCs is inhibited by 5-HT receptor antagonists that have subtype specificity. Representative raster plots and associated spike frequency line graphs acquired and constructed for evoked activity as in Fig. 2.2A. A, (Left) Representative recording whereby the MC was preincubated with the non-selective 5-HT2,7 receptor antagonist, methysergide, prior to co- presentation of the inhibitor plus 5-HT. Note that following a wash, application of 5-HT confirmed the neuron was excited by the modulator. (Right) Bar graph of the mean spike frequency expressed as percent of the basal firing of the control for six such recordings. B, (Left) Same as in A, but applying the 5-HT2 receptor antagonist mianserin. (Right) Bar graph of the mean spike frequency expressed as percent of the basal firing of the control for five such recordings. C, (Left) Same as in A, but applying a more selective 5-HT2A receptor antagonist, spiperone. (Right) Bar graph of the mean spike frequency expressed as percent of the basal firing of the control for seven such recordings. AC, NS = not significantly-different, paired t-test, p > 0.05. B, NS = not significantly-different, Wilcoxon signed-rank test, p > 0.05.
27
Figure 2.4 - continued
Figure 2.5 Mitral cells in the accessory olfactory bulb (AOB MCs) predominantly exhibit a decrease in AP firing frequency in response to 5-HT. A, a-c, Line graph summary of the changes in evoked, AP firing frequency in response to bath applied 5-HT indicated by the horizontal line for three representative MCs. Demonstrated is one representative cell from each type of response from the 148 cells sampled, where either a, slow-onset (74/148; 50%); or b, rapid-onset (48/148; 32%) inhibition was recorded. A population of cells (c, 26/148; 18%) did not respond to 5-HT. B, Histogram distribution plot of the onset latency times for inhibition by 5-HT. Two separate distributions, a slow-onset inhibition (right Gaussian) and a rapid-onset inhibition (left Gaussian) were fit from the sampled population. C, A representative current-clamp recording of a spontaneously active MC in a whole-cell configuration. Bath application of 40 µM 5-HT at the line; RMP = −65 mV. 28 In retesting cells for lack of serotonin excitation in the presence of the antagonists mianserin (n = 3) and spiperone (n = 3) using the synaptic blocker cocktail, both sets of experiments similarly prevented an increased firing frequency of MCs by 5-HT [0.2 (0.1) Hz = mianserin vs. 0.2 (0.2) Hz = mianserin plus 5-HT, not significantly-different, Wilcoxon signed-rank test, p > 0.99 and 0.2 (0.01) Hz = spiperone vs. 0.1 (0.01) Hz = spiperone plus 5-HT, not significantly-different, Wilcoxon signed-rank test, p = 0.25]. These collective data indicate that 5-HT direct modulation of MOB MCs occurs through a 5-HT2A receptor-mediated process.
2.3.4 The effects of 5-HT on AOB mitral cells
In contrast to what was discovered for MOB MCs, the majority of AOB MCs (122/148; 82%) exhibited an inhibitory response to 5-HT rather than excitation (Fig. 2.5A, a,b). The remainder of the sampled AOB population (26/148; 18%) did not respond to 5-HT (Fig. 2.5A, c). In plotting a frequency distribution histogram for the onset times of all inhibitory responses (Fig. 2.5B), we found that there were two distinct populations, which we will refer to as slow-onset inhibition (as in Fig. 2.5A, a) and rapid-onset inhibition (as in Fig. 2.5A, b) types, respectively (significantly-different means, Student’s t-test with Welch’s correction, p < 0.0001). Seventy- four out of 122 cells had onset times that fell within the Gaussian fit of the slow-onset inhibition type [mean (SD), 166 (47.3) s] in response to 5-HT modulation; while 48 out of 122 cells had much quicker onset times for inhibition by 5-HT [27 (4.8) s] and fell within the fit for the rapid- onset inhibition. Similar to that found with MOB MCs, spontaneous activity of AOB MCs could also be modulated by bath applied 5-HT (Fig. 2.5C).
When we quantified the magnitude of the modulation by 5-HT systematically, we found there were two different magnitudes of inhibition, regardless of onset kinetics. The first was a weak inhibition, in which the spike frequency was modestly, but significantly, reduced by 5-HT compared with the control condition (Fig. 2.6A, Friedman’s test, p = 0.0002, with Dunn’s post- hoc test, p < 0.01, n = 9). The second group exhibited strong inhibition to 5-HT. Here, 5-HT bath application gradually delayed the latency of the first evoked spike of the cell until it stopped firing compared with the control condition (Fig. 2.6B, Friedman’s test, p < 0.0001, with Dunn’s post-hoc test, p < 0.01, n = 9). Correspondingly opposite to what we found for excitatory MOB MCs, the AP shape for AOB MCs exhibited an increase in peak amplitude [83.4 (7.0) mV =
29 Control; 86.3 (7.5) mV = 5-HT], a reduction in the half-width [2.6 (0.4) mV = Control; 2.3 (0.4) mV = 5-HT] and 10-90% rise time [0.9 (0.1) mV = Control; 0.8 (0.2) mV = 5-HT] (each significantly-different, paired t-test, p < 0.01, n = 10). These data were pooled from both weakly and strongly inhibited cells regardless of onset of modulation, because all types of inhibited AOB MCs demonstrated the same change in AP shape. In order to identify whether synaptic transmission was required for 5-HT inhibitory responses for either slow-onset inhibition or rapid-onset inhibition in AOB MCs, experiments were performed in the presence of gabazine
(GABAA receptor antagonist) in ACSF. Two different types of responses were observed −slow-onset inhibition responding to gabazine application and rapid-onset inhibition that was insensitive to gabazine application. Five sampled cells that were found to be the slow- onset inhibition type, failed to be modulated by 5-HT following gabazine pre-incubation. For these recordings (Fig. 2.7A), baseline AP firing frequency was first determined in control ACSF and then 5-HT was introduced to determine that the cell was slowly inhibited by the modulator. Gabazine was then introduced to the bath followed by a co-presentation of gabazine plus 5-HT. Finally, following wash out of both agents, 5-HT was re-applied to confirm continued inhibitory response to the modulator. As determined for the population of sampled AOB MCs, slow-onset inhibition appeared to be mediated by GABA transmission because adding gabazine prevented the inhibitory effect of 5-HT [Fig. 2.7A, 2.2 (1.0) Hz = gabazine vs. 2.3 (1.2) Hz = gabazine plus 5-HT, not significantly-different, Wilcoxon signed-rank test, p > 0.81, n = 5]. To confirm that 5- HT in the AOB was exciting GABAergic neurons that could inhibit MCs via GABA release and not causing an excitation of glutamatergic neurons that could in turn excite GABAergic neurons to inhibit MCs, it was important to delineate between these alternatives by preventing synaptic transmission of glutamate. Therefore, in the presence of APV/NBQX, we report that 4 of 4 cells still exhibited slow-onset inhibition [Fig. 2.7B, 1.9 (0.6) Hz = APV/NBQX vs. 1.0 (0.6) Hz = APV/NBQX plus 5-HT, significantly-different, Wilcoxon signed-rank test, p < 0.04, n = 4]. For these recordings (Fig. 2.7B), cells were first confirmed to be slowly inhibited by 5-HT and following a wash, 5-HT was reintroduced, but in the presence of APV/NBQX (Fig. 2.7B).
Among these four cells, we examined three with the 5-HT2 receptor antagonist mianserin in the continued presence of APV/NBQX. Mianserin co-presented with 5-HT blocked the slow-onset inhibition [2.8 (0.8) Hz = APV/NBQX plus mianserin vs. 2.8 (0.9) Hz = APV/NBQX plus mianserin and 5-HT, Wilcoxon signed-rank test, p = 0.99, n= 3] (Fig. 2.7B). To our surprise, six
30
Figure 2.6 AOB MCs are differentially inhibited by 5-HT, regardless of onset kinetics of the modulation. Current-clamp recordings and associated raster plots for a representative MC that was A-a, weakly inhibited (RMP = −67 mV; 25 pA perithreshold current injection) vs. one that was B-a, strongly inhibited by 5-HT (RMP = −69 mV; 30 pA perithreshold current injection). For cells responding to 5-HT with the latter type of inhibition, 5-HT progressively delayed the latency to first spike until the cell stopped firing in latter trace numbers. A-B, parts a, Note that AP firing in AOB MCs does not exhibit cluster behavior as demonstrated in the raster plots. A-B, parts b, Line graphs showing the spike frequencies for individual cells under the control, 5-HT, and wash conditions. A-B, parts c, Bar graphs of the mean spike frequency expressed as percent of the basal firing of the control. ** Significantly-different from control, Friedman’s test with Dunn’s post-hoc test, p < 0.01.
31
Figure 2.7 5-HT-evoked inhibition in AOB MCs responds differentially to gabazine. Representative raster plot and spike frequency line graphs generated as in Figure 3 for a MC that was inhibited by 5-HT with A,B slow-onset vs. C, rapid-onset modulation. A, (Left) Note that the slow-onset 5-HT modulation was blocked by pre-incubation with Gabazine after which co-presentation of Gabazine plus 5-HT failed to inhibit firing frequency. This could be recovered following a wash (time break bar) and inhibited again via 5-HT application alone. B, (Left) Note that the slow-onset 5-HT modulation was not blocked by pre- incubation and then co-presentation with synaptic blockers (APV/NBQX). Using a continual background of synaptic blockers, the 5-HT2 receptor antagonist, mianserin, blocked the slow-onset inhibition. C, (Left) Note that the rapid-onset 5-HT modulation was not blocked by pre-incubation with Gabazine after which co-presentation of Gabazine plus 5-HT continued to elicit rapid inhibition by 5-HT. This was repeatable within the same cell. A-C, (Right) Bar graphs of the mean spike frequency expressed as percent of the basal firing of the control for both kinetic types of inhibitory responses. A, (Right), NS = not significantly-different, Wilcoxon signed-rank test, n = 5, p > 0.05. B, (Right), *Significantly-different, Wilcoxon signed-rank test, n = 4, p < 0.04. C, (Right), ** Significantly-different, paired t-test, n = 6, p < 0.01. 32
Figure 2.7 – continued
sampled AOB MCs, demonstrated that 5-HT rapid-onset inhibition could not be blocked by gabazine (Fig. 2.7C). Here, 5-HT was confirmed to rapidly inhibit evoked AP firing frequency, but when washed and pre-incubated with gabazine as in the first sampled population, co- presentation of gabazine and 5-HT continued to elicit an inhibition of firing frequency, like that of 5-HT alone [Fig. 2.7C, 1.3 (0.5) Hz = gabazine vs. 0.2 (0.2) Hz = gabazine plus 5-HT, significantly-different, paired t-test, p < 0.01, n = 6]. This was repeatable within the same cell. Additionally, following an extended wash of these agents, pre-incubation with broad spectrum antagonist methysergide and then co-presentation of methysergide and 5-HT did prevent the inhibitory effect of 5-HT (data not shown). We therefore speculated that the rapid-onset inhibition could be a direct effect of 5-HT on MCs. To confirm our conjecture, we performed further pharmacological tests as described below.
2.3.5 Pharmacological identification of receptor types involved in 5-HT actions on AOB mitral cells
Because our results suggested there were two types of 5-HT inhibition of AOB MCs –a slow-onset inhibition and rapid-onset inhibition –we hypothesized that the slower onset inhibition might use a polysynaptic mechanism. As such, 5-HT would be expected to initially excite GABAergic interneurons that, in turn, could release GABA onto MCs to inhibit them.
33
Figure 2.8 Slow-onset 5-HT modulation is sensitive to 5-HT2 receptor antagonists while rapid-onset is sensitive to 5-HT1 receptor antagonist in AOB MCs. Representative raster plot and associated spike frequency line graph for a MC that exhibited slow-onset 5-HT inhibition that was inhibited by either A, (Left) a non-selective 5-HT2,7 receptor antagonist methysergide or B, (Left) a more specific 5-HT2 receptor antagonist mianserin. C, (Left) Raster plot and associated spike frequency for a MC that exhibited rapid- onset 5-HT inhibition that was blocked by the 5-HT1 receptor antagonist pindolol. A-C, (Right) Bar graphs of the mean spike frequency expressed as percent of the basal firing of the control. Because the application of methysergide (noted as Methysergide-1) and mianserin (noted as Mianserin-1) elicited strong inhibitions, current injections were increased to elevate spike firing frequencies (noted as Methysergide-2 and Mianserin-2) prior to the co-application of 5-HT and the antagonists. Same statistical analyses and notations as in Fig. 2.4. A, n = 4; B, n = 5; C, n = 4.
34
Figure 2.8 - continued
We confirmed that the slow-onset inhibition could be blocked by the non-selective 5-HT2,7 receptor antagonist methysergide [Fig. 2.8A, 1.0 (0.7) Hz = methysergide vs. 1.2 (0.8) Hz = methysergide plus 5-HT, not significantly-different, Wilcoxon signed-rank test, p = 0.13, n = 4] and 5-HT2 receptor antagonist mianserin [Fig. 2.8B, 1.3 (0.3) Hz = mianserin vs. 1.4 (0.4) Hz = mianserin plus 5-HT, not significantly-different, Wilcoxon signed-rank test, p = 0.44, n = 5]. Here, 5-HT was first applied to confirm slow inhibition, followed by a wash and then application of the antagonist (noted as Methysergide-1 or Mianserin-1). Because the antagonist elicited strong inhibition, current injection was increased to elevate spike firing frequency (noted as Methysergide-2 or Mianserin-2) prior to co-presentation of 5-HT and the antagonist. Because mianserin prevented slow-onset inhibition (Fig. 2.7B and 2.8B) but not rapid-onset inhibition (data not shown), this may suggest that the subtype of 5-HT receptors mediating the two kinetically-distinct types of inhibition may be different. 5-HT1 receptors, including 5-HT1A/B, have been shown to mediate both pre- and post-synaptic inhibitory effects of 5-HT (Blier et al.,
1998; Morikawa et al., 2000; Ogren et al., 2008) . We therefore examined whether 5-HT1A/B receptor antagonist, pindolol (Hoyer et al., 1994), could prevent the rapid-onset inhibition by 5- HT. As shown in Fig. 2.8C, the rapid-onset 5-HT inhibition that is independent of GABAergic transmission (not blocked by gabazine) could be blocked by pindolol in 4 of 5 tested cells [1.0 (0.1) Hz = pindolol vs. 1.1 (0.3) Hz = pindolol plus 5-HT, not significantly-different, Wilcoxon signed-rank test, p = 0.38]. Finally, block by pindolol in the presence of gabazine was
35 additionally examined, which similarly demonstrated a block of the rapid-onset inhibition by 5- HT [1.1 (0.8) Hz = gabazine and pindolol vs. 1.0 (0.6) Hz = gabazine and pindolol plus 5-HT, not significantly-different, Wilcoxon signed-rank test, p = 0.25, n = 4].
2.4 Discussion
Despite the conserved circuitry of 5-HT arriving from centrifugal projections of the CNS (Devore & Linster, 2012; Smith et al., 2015), our electrophysiological results demonstrate striking differences in serotoninergic modulation. 5-HT was predominantly excitatory for MCs of the MOB, although both inhibition and mixed excitation/inhibition were observed to a lesser frequency, while modulation was strictly inhibitory for those in the AOB. AOB inhibitory responses were classified by two different kinetic rates of inhibition – slow-onset inhibition and rapid-onset inhibition, respectively – and were found to be governed by two different subfamilies of 5-HT receptors. The diversity of responses to 5-HT in the MOB could contribute to general plasticity in the olfactory system that is important for olfactory discrimination and learning. Alternatively, the uniform inhibitory response to 5-HT in the AOB could be preserved as an important mechanism to regulate hard-wired innate behaviors such as aggression.
Although our study of 5-HT modulation in the MOB pharmacologically focused on those MCs exhibiting excitation, we did observe a heterogeneous response to 5-HT similar to the earlier study by Hardy et al., 2005, and most recent studies by Kapoor et al., 2016 and Brunert et al., 2016. It is likely that 5-HT release from the raphe nuclei into the MOB modulates olfactory synaptic physiology both with a heterogeneous response of MCs as well as across multiple OB neuron targets (Brunert et al., 2016).
Our data demonstrating that MCs of the MOB are modulated rapidly and directly by 5-
HT2A receptor activation to yield an increase in action potential (AP) firing frequency is consistent with other reports that have explored activation of the raphe nuclei, ensemble modulation of MOB MCs, and changes in synaptic activity and the glomerular network in response to serotonin (Hardy et al., 2005; Schmidt & Strowbridge, 2014; Brill et al., 2016; Kapoor et al., 2016). The majority of our sampled MCs in the MOB (70%) were excited 36 following bath application of 5-HT while a small population of MCs was found to be either inhibited or received a dual inhibition/excitation following 5-HT application, which could be attributed to an indirect mechanism involving lateral inhibition from other MCs receiving a stronger excitation by 5-HT (Urban & Sakmann, 2002). Additionally, recent studies demonstrate that 5-HT, delivered locally at the glomerular level that receives most of the serotoninergic projections in the OB, also increases the spiking frequency of inhibitory interneurons such as PG cells and short-axon cells (SACs) through the activation of the 5-HT2C receptor, promoting interglomerular inhibition and hence decreasing the activity of some MCs (Petzold et al., 2009; Brill et al., 2016).
Since the discovery of the heterogeneity of the brain 5-HT receptor in the 1980s, and then subsequent heterogeneity of the receptor subtypes soon thereafter, subtype-specific ligands for serotonin receptors have been sought to regulate their different down-stream signaling cascades (Hoyer et al., 1994; Barnes & Sharp, 1999; Pithadia & Jain, 2009). As a whole, the agonists and antagonists for 5-HT receptors are deemed ‘semi-selective agents’ that can support subtype identity along with other parallel methods such as cloning, in situ hybridization, and structural approaches. Our pharmacologic data that demonstrate 5-HT-evoked excitation in MOB MCs is blocked by three different competitive ligands (mianserin, methysergide, and spiperone) that antagonize 5-HT2A receptors (among others) corroborates earlier in situ and immunocytochemical studies of the distribution of this receptor subtype on the soma and dendrites of MOB MCs (McLean et al., 1995; Yuan et al., 2003). Recently Brill et al. (2016) electrophysiologically applied a different cadre of antagonists to model the dense serotonergic innervation of the MOB to synaptic contacts on MCs (5-HT2A subtype), ETCs (5-HT2A subtype), and SACs (5HT2C subtype) to suggest an increased excitatory drive onto glomerular interneurons due to 5HT2A subtype activation on MCs. Although there is no reported expression of subtype- specific receptors in the AOB, save from the reported lack of 5-HT2A mRNA by McLean et al.
(1995), we suspect expression of 5HT2C subtype of receptors on GCs and 5HT1A/B on MCs as modeled in Figure 2.9 based solely upon our pharmacological results and deduction of cross comparison of these ‘semi-selective agents’. For example, mianserin has been reported to have much higher affinity at 5-HT2A and 5-HT2C receptors compared to other 5-HT receptor subtypes (Brunello et al., 1982; Hoyer, 1988). Because spiperone failed to block the 5-HT-evoked
37 slow-onset inhibition in the AOB MCs (data not shown), combined with a reported lack of 5-
HT2A mRNA (McLean et al., 1995), our AOB MC sensitivity to mianserin (Fig. 2.7B and 2.8B) infers the activation of 5-HT2C receptor. Our data demonstrating the block of the 5-HT-evoked rapid-onset inhibition in the AOB by a preferred 5-HT1A/1B receptor antagonist (pindolol, Fig.
2.8C) and a broad 5-HT1A and 5-HT2A receptor antagonist (spiperone, data not shown) (Sundaram et al., 1992; Newman-Tancredi et al., 1997) infers the presence of direct activation of a 5-HT1A/1B receptor subtype. This is also consistent with an earlier study that reported the expression of 5-HT1A receptor mRNA in the OB, but the study did not localize it to the main or the accessory bulb (Pompeiano et al., 1992). There appear to be two sources of inhibition in MCs of the AOB following bath application of 5-HT that we initially distinguished based upon kinetics of onset of the inhibition −a rapid- or a slow-onset inhibition. The slow-onset inhibition was suppressed by GABAA and 5-HT2C receptor antagonists, suggesting a di-synaptic mechanism involving the activation of GABAergic interneurons expressing 5-HT2C receptor. Conversely, rapid-onset inhibition by 5-HT observed in some AOB MCs was found to not respond to gabazine, but was suppressed by the ligands pindolol and spiperone that antagonize the 5-HT1A receptor. This is consistent with its observed direct inhibition in the rapid-onset class of modulation, given that the 5-HT1A receptor is coupled to Gi/Go proteins and mediates inhibitory neurotransmission (Palacios, 2016).
Beyond our discovery of a differential modulation by serotonin between the MOB and AOB, others have reported opposing effects in such parallel odor processing pathways for neuromodulators such as noradrenaline (Nai et al., 2009) or acetylcholine (Smith et al., 2015). The opposing responses are underlined by a difference of receptor subtype expression between the MOB and the AOB and also the sensitivity of the different inhibitory interneurons to these neuromodulators in both circuits. For example, Smith and collaborators demonstrate that MCs of both systems are regulated in opposing fashion by acetylcholine resulting in an inhibition in the MOB, and conversely an excitation in the AOB. This difference relied on the expression of the muscarinic acetylcholine receptor (mAChR) M2 in the MOB inhibiting MCs, whereas M1- mAChR expressed in the AOB directly exciting MCs. Similarly, GCs present in the AOB and MOB were found to respond differently to acetylcholine due to a different distribution of M1- and M2-mAChRs (Smith et al., 2015). It has to be noted that inhibition of MC output does not
38 necessary correlate with a loss of function. Many studies have demonstrated that for both the MOB and the AOB, the response to a specific chemical stimulus triggers both activation and inhibition of MCs (Luo et al., 2003; Olsen & Wilson, 2008). Inhibition is essential to reduce the signal-to-noise ratio and increase the contrast of MC responses, in order to generate distinct temporal and spatial patterns of activation (Economo et al., 2016).
Differential neuromodulation in these parallel olfactory pathways might be inherent to their respective primary function. The main olfactory system is subject to plasticity and learning (Wilson, 2002; Luo et al., 2003; Mouly & Sullivan, 2010; Lepousez et al., 2014) while the accessory system is linked with the amygdala and hypothalamus and is specialized in the integration of semiochemical signals arising from mates or predators, triggering stereotyped innate behaviors including social interaction or danger avoidance (Dulac & Torello, 2003; Trotier, 2011; Takahashi, 2014). In the MOB, it has been suggested that 5-HT modulates the odor input by reducing the odor-evoked synaptic activity and reducing the gain of sensitivity (Petzold et al., 2009). However, 5-HT depletion in the OB reduces odor discrimination in rats (Moriizumi et al., 1994) and also impairs the olfactory learning ability of neonatal rats through a
5-HT2 receptor-dependent mechanism (McLean et al., 1993; McLean et al., 1996). Interestingly, 5-HT acts in collaboration with the noradrenaline in olfactory learning (Price et al., 1998; Yuan et al., 2000). It has been shown that 5-HT (through 5-HT2A receptor) and noradrenaline (through β1-adrenoceptor) work together by co-regulating a cAMP signaling pathway in MCs in the MOB (Yuan et al., 2003). To our knowledge, no studies have directly explored the effect of 5-HT in the mammalian AOB. In the moth, 5-HT modulates the activity of neurons in the central lobes that receive input from olfactory sensory neurons (Kloppenburg & Mercer, 2008). Interestingly, some behavioral effects resulting from bulbectomy (increase aggression and reduced sexual behaviors; Kelly et al., 1997) can be mimicked by injection of selective serotonergic neurotoxin
5,6- or 5,7-dihydroxytryptamine into the OB (Cairncross et al., 1979). Moreover, the 5-HT1 receptor has been implicated in aggressive behaviors through pharmacological studies (Olivier & van, 2005; de Boer & Koolhaas, 2005). In particular, when 5-HT1A receptor is activated by agonists, animals show decreased aggressive behavior (de Boer et al., 1999; de Boer et al., 2000). Similarly, in teleost fish, serotonin plays a primary inhibitory role in aggressive behavior (Munro, 1986; Winberg et al., 2001; Perreault et al., 2003).
39 Further functional studies are necessary to explore whether the biophysical differences we observed in serotonergic modulation across the MOB and AOB may correlate to each system’s respective primary function. Having a greater knowledge base on 5-HT receptor pharmacology and changes in AP firing frequency of the major output neuron in each system provides a strong set point to design the dimensions of such behavioral studies.
Figure 2.9 Model of serotonergic modulation in two parallel processing pathways of the olfactory system. Serotonergic (5-HT) projections from the Raphe nuclei extend to interneurons and primary projection neurons of the main (MOB) and accessory (AOB) olfactory bulbs. In the primary output neurons of each system, mitral cells can respond to 5-HT via the 5-HT2A and 5-HT1A/B receptors, respectively. Activation of 5-HT2A elicits direct excitation of MCs in the MOB and as coupled to Go/Gi signaling, activation of 5-HT1A/B evokes inhibition of MCs in the AOB. The same subclass of serotonergic receptor, 5-HT2C, is found on interneurons in both systems, but associated with different interneurons −PG/SAC in the MOB versus GC in the AOB. Note circuit differences allowing input from MOE and VNO respectively that could coordinate different behavioral outputs in response to 5-HT availability in each system. MOB = main olfactory bulb, MOE = main olfactory epithelium, AOB = accessory olfactory bulb, VNO = vomeronasal organ, GL = glomerular layer, MCL = mitral cell layer, GCL = granule cell layer, PG/SAC = periglomerular/short-axon cells, GC = granule cell, CNS = central nervous system. 40 CHAPTER 3
THE MODULATION OF GLP-1 NEURONS IN THE OLFACTORY BULB
3.1 Introduction
Obesity and type 2 diabetes mellitus (T2DM) have become prevailing modern health problems worldwide. Over the past decades, researchers have tried to identify suitable targets to treat T2DM. One of the promising candidates is the glucagon-like peptide-1 (GLP-1) (Campbell & Drucker, 2013). Glucagon, which has hyperglycemic effect, was discovered in pancreas extracts (Murlin et al., 1923). Subsequent research showed that glucagon was a peptide fragment cleaved from the proglucagon protein (Rouille et al., 1995; Rouille et al., 1997). Proglucagon gene sequence studies further identified two glucagon-like sequences (Bell et al., 1983a; Bell et al., 1983b), known as glucagon-like peptide 1 (GLP-1) and glucagon-like peptide 2 (GLP-2). The cleavage of proglucagon is tissue specific depending on posttranslational modification by prohormone convertases (PC). In the pancreas, the proglucagon is predominantly cleaved to glucagon, glicentin-related pancreatic polypeptide (GRPP), intervening peptide 1 (IP1), and a proglucagon fragment by enzyme PC2; in the gut and brain, proglucagon is predominantly cleaved to GLP-1, GLP-2, oxyntomodulin, glicentin, and IP2 by enzyme PC1/3 (Sandoval & D'Alessio, 2015). GLP-1 is the most studied fragment of proglucagon because of its insulinotropic action and clinical applications in type 2 diabetes (Campbell & Drucker, 2013).
GLP-1 is found both in the peripheral tissues and the central nervous system (CNS). In the peripheral tissues, GLP-1 is mainly synthesized and secreted from epithelial endocrine L cells in the intestinal tract (Holst, 2007). Moreover, GLP-1 secretion is rapidly increased by meal intake (Orskov et al., 1996). It has been shown that an elevated glucose concentration induces increased GLP-1 secretion from L cells (Reimann & Gribble, 2002; Gribble et al., 2003). The function of GLP-1 in the pancreas is well established. GLP-1 binds to the GLP-1 receptor on beta cells in the pancreas, which releases the stimulus G protein, following the activation of cAMP-PKA signaling pathway to increase the synthesis and release of insulin (MacDonald et al., 2002; Holz, 2004). Apart from stimulating insulin signaling, GLP-1 also strongly inhibits glucagon secretion (Orskov et al., 1988). Other important functions of peripheral GLP-1 include
41 the inhibition of gastrointestinal secretion and gastric emptying (Wettergren et al., 1993; Nauck et al., 1997). Recently, increasing research has focused on the role of GLP-1 in the CNS (Trapp & Cork, 2015). GLP-1 has a very short half-life in plasma of 1- 2 minutes (Kieffer et al., 1995) predicting any crossing of systemic GLP-1 to the CNS through blood brain barrier to be minimal. It has been suggested that peripheral GLP-1 could exert its effect on the brain through the vagal afferent nerve (Waget et al., 2011). The expression of GLP-1 in the nucleus of the solitary tract (NTS) neurons and their long-range projections to different parts of the brain, however, suggests a local action of GLP-1 in the CNS (Trapp & Cork, 2015). The roles of GLP-1 have been implicated in food intake (Tang-Christensen et al., 1996; Turton et al., 1996), thermogenesis (Lockie et al., 2012), blood glucose control (Knauf et al., 2005), cardiovascular control (Yamamoto et al., 2002), and neuroprotection (During et al., 2003) in the brain. The central effects of GLP-1 could come from three different sources: (1) GLP-1 produced within the CNS, (2) peripheral GLP-1 crossing the blood-brain barrier, and (3) GLP-1 signaling via sensory afferent vagal neurons. It’s a challenge to dissect out the relative contribution of different sources of the central effects of GLP-1.
A population of GLP-1 neurons was identified anatomically in the olfactory bulb (OB) (Merchenthaler et al., 1999), and was functionally explored recently (Thiebaud et al., 2016). These neurons are located mainly in the granule cell layer (GCL) of the OB. The functional significance of these neurons remains incompletely understood. Previous research on GLP-1 neurons in the NTS showed that these neurons could be modulated by metabolic-related hormones such as cholecystokinin (CCK) (Hisadome et al., 2011) and leptin (Hisadome et al., 2010). These NTS GLP-1 neurons had been suggested as a link between energy state and stress response (Maniscalco et al., 2015). In this study the authors showed that negative energy balance induced by overnight fasting could block neural and behavioral responses to acute stress by inhibiting the activity of the NTS GLP-1 neurons (Maniscalco et al., 2015). By comparison, GLP-1 neurons in the OB could act as a link between metabolic state and olfactory response. Increasing evidence indicates that apart from the OB’s primary role in odor detection, it could serve as an internal metabolic sensor (Palouzier-Paulignan et al., 2012). The expression of a variety of metabolic hormones such as ghrelin, orexins, leptin, insulin, CCK and their receptors
42 (Palouzier-Paulignan et al., 2012) would allow the OB to detect metabolic state while simultaneously modulate olfactory information processing.
The GCL of the OB receives multiple centrifugal projections from higher brain areas including serotonergic, noradrenergic, cholinergic, and cortical feedback fibers. These centrifugal projections are believed to modulate olfactory information processing depending upon an animals’ metabolic state. It has been shown that the regulation of granule cells through cortical feedback projections links the stronger odor processing to the hunger state (Soria-Gomez et al., 2014b). Our previous data showed that GLP-1 neurons in the GCL are deep short-axon cells (dSACs) (Thiebaud et al., 2016) that can modulate the activity of mitral/tufted cells (Burton et al., 2017), the major output neurons of the OB. It is possible that GLP-1 neurons in the GCL could be the link between the weaker olfactory response and the satiation state.
A series of experiments were performed in this chapter to test the potential functions of GLP-1 neurons in the OB. First, whole-cell patch-clamp experiments were carried out to electrophysiologically characterize these GLP-1 neurons, and to identify the possible regulations of these neurons. These experiments would test the hypothesis that the OB GLP-1 neurons could also detect the metabolic-related hormones such as leptin or CCK. To examine whether changing GLP-1 signaling can modulate animals’ olfactory behavior, I tested animals in an odor habituation-dishabituation behavioral paradigm after delivering a GLP-1 analogue Exendin-4. These data would provide foundation for future experiments to address the functional role of GLP-1 neurons in modulating olfactory responses according to metabolic states in the OB.
3.2 Materials and Methods
3.2.1 Ethical approval
All animal experiments were approved by the Florida State University (FSU) Institutional Animal Care and Use Committee (IACUC) under protocol #1427 and were conducted in accordance with the American Veterinary Medicine Association (AVMA) and the National Institutes of Health (NIH). In preparation for OB slice electrophysiology, mice were anaesthetized with isoflurane (Aerrane; Baxter, Deerfield, IL, USA) using the IACUC-approved 43 drop method and were then sacrificed by decapitation (AVMA Guidelines on Euthanasia, June 2007).
3.2.2 Animal care
Detection of preproglucagon (PPG) neurons expressing a red fluorescent protein (RFP) was achieved by crossing Rosa26-tandem-dimer red fluorescent protein (tdRFP) reporter mice (Luche et al., 2007) with mice expressing Cre recombinase under the control of the preproglucagon promoter (GLU-Cre12 mice) (Parker et al., 2012). For simplification, homozygous progeny resulting of the breeding of GLU-Cre12 and Rosa26 tdRFP mice will be referred as PPG-Cre-RFP. Since proglucagon is cleaved to GLP-1 in the brain (Sandoval & D'Alessio, 2015), these RFP labeled PPG neurons will be referred to as GLP-1 neurons in this manuscript. Channelrhodopsin-2 was expressed in GLP-1 neurons by crossing to heterozygosity PPG-Cre-RFP mice with the Ai32 line (Stock # 007908, Jackson Laboratories, Bar Harbor, ME, USA) that contains a Floxed allele expressing the fusion protein ChR2(H134R)-EYFP in the presence of the CRE recombinase in PPG-neurons (Madisen et al., 2012). All mice were housed at the FSU vivarium on a standard 12 h/12 h light/dark cycle and were allowed ad libitum access to 5001 Purina Chow (Purina, Richmond, VA, USA) and water. Mice of both sexes at postnatal day 20-45 were used for slice electrophysiology experiments. Two to three months old wild-type mice (Mus musculus, C57BL/6J strain; The Jackson Laboratory, Bar Harbor, ME, USA) were used for the biochemistry and behavioral experiments.
3.2.3 Solutions and reagents
Artificial cerebral spinal fluid (ACSF) contained (in mM): 119 NaCl, 26.2 NaHCO3, 2.5
KCl, 1 NaH2PO4, 1.3 MgCl2, 2.5 CaCl2, 22 glucose; 305-310 mOsm, pH 7.3-7.4. Sucrose-modified artificial cerebral spinal fluid (sucrose ACSF) contained (in mM): 83 NaCl,
26.2 NaHCO3, 1 NaH2PO4, 3.3 MgCl2, 0.5 CaCl2, 72 sucrose, 22 glucose, 5 sodium ascorbate, 2 thiourea, 3 sodium pyruvate; 315-325 mOsm, pH 7.3-7.4. The intracellular pipette solution contained (in mM): 135 K gluconate, 10 KCl, 10 HEPES, 10 MgCl2, 2 Na-ATP, 0.4 Na-GTP; 280-290 mOsm, pH 7.3-7.4. All salts and sugars were purchased from Sigma-Aldrich (St. Louis, MO, USA) or Fisher Scientific (Pittsburgh, PA, USA). The synaptic blockers 2,3-dihydroxy-6-
44 nitro-7-sulfamoyl-benzo[f]quinoxaline (NBQX), D-(-)-2-amino-5-phosphonopentanoic acid (APV), and 2-(3-carboxypropyl)-3-amino-6-(4 methoxyphenyl) pyridazinium bromide (Gabazine) were purchased from Ascent Scientific (Princeton, NJ, USA). All synaptic blockers were prepared as stock solutions (NBQX 5 mM, APV 25 mM, Gabazine 6 mM) in Milli-Q water and stored at −20°C. They were diluted to working concentrations (NBQX 5 µM, APV 50 µM, Gabazine 6 µM) in ACSF on the day of use. All pharmacological agents were introduced to OB slices through the bath chamber. Controls consisted of bath ACSF.
The serotonin hydrochloride (5-HT, H9523-100 mg, Sigma) was prepared at stock concentration (0.8 mM) in ACSF and was diluted to working concentrations (40 µM) in ACSF on the day of use. Stock solutions were prepared in Milli-Q water for the following drugs: 0.1 mM norepinephrine (A7257-500 mg, Sigma), 5 mM acetylcholine chloride (ACh, A6625-10 mg, Sigma), 0.2 mM cholecystokinin octapeptide (sulfated) ammonium salt (CCK, H2080-1 mg, Bachem), 0.1 mM leptin (116-130) amide (mouse) trifluoroacetate salt (Leptin, H3966-1 mg, Bachem). Exendin-4 (AS-24464, 1 mg, AnaSpec) was prepared at stock concentration (100 µM) in PBS. All ordarants: ethyl hexanoate (C6) / ethyl octanoate (C8), ethyl heptanoate (C7) / isopropyl tiglate (Iso-t) were purchased from Sigma-Aldrich (St. Louis, MO, USA).
3.2.4 Olfactory bulb (OB) slice electrophysiology
Mice were anesthetized by inhalation of isoflurane (see Ethics Section), quickly decapitated, and then the OBs were exposed by removing the dorsal and lateral portions of the skull between the lambda suture and the cribriform plate. The OBs were harvested and prepared for slice electrophysiology as described previously (Fadool et al., 2011). Briefly, after removing the dura, a portion of forebrain attached with the OBs was cut and quickly glued to a sectioning block with Superglue (Lowe’s Home Improvement, USA), and submerged in oxygenated
(95%O2 / 5%CO2), ice-cold, sucrose-modified ACSF for approximately two minutes (min) prior to vibratome sectioning (Vibratome/Leica Model 1000, Wetzlar, Germany). Coronal sections were made at a thickness of 300 µM and then allowed to recover in an interface chamber (Krimer & Goldman-Rakic, 1997) for 20-30 min at 33°C containing oxygenated ACSF. The slices were then maintained at room temperature (23°C) for about 60 min before recording. OB slices were recorded in a continuously-perfused (Ismatec; 1-2 ml/min), submerged-slice
45 recording chamber (RC-26, Warner Instruments, Hamden, CT, USA) with ACSF at room temperature. Slices were visualized at 10× and 40× using an Axioskop 2FS Plus microscope (Carl Zeiss Microimaging, Inc., Thornwood, NY, USA) equipped with infrared detection capability (Dage MTI, CCD100, Michigan, IN, USA). Electrodes were fabricated from borosilicate glass (Hilgenberg #1405002, Malsfeld, Germany) to a pipette resistance ranging from 9 to 15 MΩ. Positive pressure was retained while navigating through the OB laminae until a slight increase in the pipette resistance (typically 0.1 - 0.2 MΩ) was observed; indicating that the pipette tip had made contact with the cell. A giga-ohm seal (Re = 2.0 - 16.4 GΩ) was achieved by releasing positive pressure and simultaneously applying a light suction. The whole- cell configuration was established by applying a rapid but strong suction to the lumen of the pipette while monitoring resistance.
After establishing a whole-cell configuration, GLP-1 neurons were first sampled for adequate resting potential (less than −70 mV) and proper series resistance (less than 60 MΩ) prior to initiating a series of current-clamp recordings. Perithreshold current levels were determined by incrementally injecting 1200 milliseconds (ms)-long, 25 pA steps of current every 10 seconds (s), starting at −100 pA. Following the determination of spike threshold, cells were then stimulated with a long, perithreshold current step of 5000 ms duration (typically ranging from 5 to 50 pA) every 18 s to acquire spike frequency data.
3.2.5 Habituation-dishabituation olfactory test
Odor discrimination was tested using the habituation/dishabituation paradigm as previously described (Smith et al., 2015). Briefly, mice were routinely handled for 3 days before behavioral experiments. Behavioral tests were performed at the beginning of animal’s dark phase under dim red light. Mice were firstly tested for their baseline odor discrimination as following: mice were placed in a clean cage (27 cm [L] × 16 cm [W] × 12 cm [H]) covered with a filter top in the presence of an unscented wooden cube (100 µl mineral oil on the top) for 30 min. The wooden cube (3/4 Inch, sold by Craftparts Direct from Amazon) was taped in the center of the bottom of the cage. Following this familiarization period, mice were tested for their ability to discriminate between the following odor pairs: ethyl hexanoate (C6) / ethyl octanoate (C8), ethyl heptanoate (C7) / isopropyl tiglate (Iso-t). During the habituation phase, each mouse was
46 exposed during four or five consecutive trials to a wooden block scented with 100 µl of the first odor (1:5000 dilution in mineral oil). The last exposure trial (dishabituation) consisted of the new odor (1:5000 dilution in mineral oil). Each exposure lasted 2 min, with a 1 min intertrial interval. The investigation time was defined as the total time when the mouse’s nose was within 2 cm radius of the wooden block. The time when mice jump over or stand on the top of the wooden block was not included as investigation time. Odor discrimination was considered successful when mice showed a significant increase in investigation time during the presentation of the new odor compared with the last trial of the first odor. Only mice showed successful odor discrimination were used for the subsequent drug testing experiments. One week following the initial baseline odor discrimination, mice were given either PBS or Exendin-4 (0.4 µM/kg) intraperitoneally (10 µl/g), or Exendin-4 (10 µM, 20 µl) intranasally. Then mice were tested as described above. The odor discrimination index (DI) was calculated as the investigation time of the new odor (Tn) minus the investigation time of the last trial of the first odor (To), then divided by the investigation time of the first trail of the first odor (T1). DI = (Tn – To) / T1. If the mouse did not show increased investigation time of the new odor compared with the last trial of the first odor, the odor discrimination index was zero. A higher discrimination index reflected better odor discrimination ability for the mouse.
3.2.6 Tissue harvest for ELISA measurement of GLP-1
For measurement of GLP-1, wild-type mice were divided into three groups: (1) ad- libitum group had access to food all the time, (2) fasted group was deprived of food for 24 hours, and (3) re-fed group was deprived of food for 22 hours then was provide food for 2 hours. At the time of harvest, mice were anaesthetized with isoflurane (Aerrane; Baxter, Deerfield, IL, USA) using the IACUC-approved drop method and were then sacrificed by decapitation (AVMA Guidelines on Euthanasia, June 2007). First, trunk blood was collected and serum was prepared according to the GLP-1 (7-36) Active ELISA kit (Cat# EGLP-35K, EMD Millipore) sample preparation manual. The OBs were quickly harvested after decapitation. Tissues were immediately frozen in dry ice/100% ethanol. OBs were homogenized in homogenization buffer that contained (mM): 320 sucrose, 10 Tris base, 50 KCl and 1 EDTA (pH 7.8) plus DPP-IV enzyme inhibitor (Cat# DPP4, EMD Millipore) and protease / phosphatase inhibitors: 1mM phenylmethylsulphonyl fluoride (PMSF), 10 μg ml−1 aprotinin, 1 μg ml−1 leupeptin and 0.5 47 mM sodium orthovanadate on ice. Homogenized samples were centrifuged 14000 rpm at 4°C for 30 minutes, and supernatants were collected for GLP-1 measurement.
3.2.7 Data acquisition and statistical analysis
Current- and voltage-clamp experiments were performed using a Multiclamp 700B amplifier (Axon Instruments, Molecular Devices, Sunnyvale, CA, USA). The analog signal was filtered at 10 kHz and minimally digitally sampled every 100 µs. The signals were digitalized with a Digidata 1440A digitizer (Axon Instruments, Molecular Devices). The pipette capacitance was electrically compensated through the capacitance neutralization circuit of the Multiclamp 700B amplifier. Resting membrane potentials were corrected for a calculated −14 mV junction potential offset. Membrane capacitance and input resistance were acquired from the membrane test function of Clampex 10.3 (Axon Instruments). Data were analyzed using Clampfit 10.3 (Axon CNS), in combination with the analysis packages Origin 8.0 (MicroCal Software, Northampton, MA, USA), and Igor Pro 6.0.2 (Wavemetrics Inc., Portland, OR, USA) with the NeuroMatics 2.02 plugin (written by Jason Rothman). Baseline, treatment, and washout values were calculated from the mean of at least 10 consecutive traces. Both PPG-Cre-RFP mice and PPG-Cre-RFP-ChR2 mice were used for electrophysiological recordings. Because there was no strain difference in terms of electrophysiological properties of GLP-1 neurons, data collected from all GLP-1 neurons recordings were pooled together. Statistical significance was determined between baseline biophysical property and that following the modulator using a two-tailed, paired t-test or a one-way repeated measures analysis of variance (ANOVA) at the 95% confidence level (α = 0.05). Comparison of independent means was alternatively examined using a Student’s t-test. All sampled populations were analyzed using Prism 6 (GraphPad Software Inc., CA, USA). All reported values are mean (standard deviation -SD) unless otherwise noted.
48 3.3 Results
3.3.1 Electrophysiological properties of GLP-1 neurons
Under our recording condition nearly all GLP-1 neurons lacked spontaneous firing at resting. Once an adequate resting membrane potential (< −70 mV) was sampled, perithreshold current levels were determined by incrementally injecting 1200 milliseconds (ms)-long, 25 pA steps of current every 10 seconds (s), starting at −100 pA (see Figure 3.1). All GLP-1 neurons showed a ‘sag’ potential at a hyperpolarized state. The ‘sag’ potential is associated with hyperpolarization-activated, cyclic nucleotide-gated (HCN) channels (He et al., 2014), and is defined as the membrane potential difference between the peak potential and the tail potential (Figure 3.1). Basic electrophysiological properties of GLP-1 neurons in the OB are reported in Table 3.1.
3.3.2 The regulation of GLP-1 neurons by centrifugal projections
Because the OB receives multiple centrifugal projections from higher brain areas including serotonergic, cholinergic, and noradrenergic afferents, we first examined the possible top-down regulation of GLP-1 neurons by these centrifugal projections. Bath application of serotonin (40 µM, n = 4) and norepinephrine (100 µM, n = 4) had no effect on the evoked firing frequency. Acetylcholine (ACh; 100 µM), however, led to either inhibition or excitation of GLP- 1 neurons. For inhibition, ACh induced a small outward current (5.1 ± 1.8 pA, n = 9, Figure 3.2 C) recorded by voltage-clamp when GLP-1 neurons were held at −70 mV. When injecting a small current in current-clamp mode, ACh delayed the latency to first spike (control: 253 ± 30 ms, ACh: 396 ± 4 ms; Figure 3.2 A, B). This delay of first spike by ACh was observed only in two cells. For excitation, bath application of ACh resulted in 1.9 ± 0.6-fold increase in firing frequency (n = 21, Figure 3.3).
49 Table 3.1 Basic intrinsic properties of GLP-1 neurons in the olfactory bulb
Parameters Values Membrane potential (mV) −77.5 ± 3.6 Membrane capacitance (pF) 18.2 ± 3.6 Input resistance (MΩ) 980.9 ± 333.2 Hyperpolarization-evoked sag potential (mV) 26.2 ± 8.3
Data are presented as mean ± SD; n = 21. Hyperpolarization was induced by injecting -100 pA current.
Figure 3.1 Representative current-clamp recording of a GLP-1 neuron. Perithreshold current levels were determined by incrementally injecting 1200 ms-long, 25 pA steps of current every 10 s, starting at −100 pA. Notice the rebound firing after hyperpolarization. Also action potential (AP) firing shows adaptation.
50 Figure 3.2 Acetylcholine shows inhibitory effects on GLP-1 neurons. (A) Raster plot showing evoked spike firing events binned in 5000 ms pulse duration (Event time) and recorded with an inter pulse interval of 18 s over a 12-min recording period. Arrows indicate the times when ACh was introduced or washed from the bath, respectively. (B) Bar graph of time delay to first spike for each pulse. (C) Representative voltage-clamp trace when the neuron was held at −70 mV. Arrow indicates the time when ACh was introduced from the bath.
3.3.3 The regulation of GLP-1 neurons by metabolic-related signals
Previous evidence has shown that GLP-1 neurons in the NTS can be modulated by metabolic-related hormones such as cholecystokinin (CCK) and leptin (Hisadome et al., 2010; Hisadome et al., 2011). I found that leptin did not modulate the activity of GLP-1 neurons in the OB. Bath application of CCK (0.8 µM), however, led to either cessation of firing (n = 10, Figure 3.4 B, D, F) or an increase in firing of 1.7 ± 0.4-fold (n = 11, Figure 3.4 A, C, E). It seemed that the OB GLP-1 neurons responded to satiety-related hormones. After meal ingestion, another altered nutrient signal is the glucose concentration. Next, I tested whether GLP-1 neurons responded to glucose concentration changings. When I switched the bath glucose concentration from 22 mM to 1 mM, a subset of GLP-1 neurons (6 of 16 tested cells) demonstrated a 1.2 ± 0.4- fold increase (Figure 3.5) in firing frequency that was accompanied by a 1-2 mV depolarization.
51
Figure 3.3 Acetylcholine shows excitatory effects on GLP-1 neurons. Representative current-clamp recordings of a GLP-1 neuron under either (A) control ACSF or (B) ACh condition. (C) Raster plot showing evoked spike firing events binned in 5000 ms pulse duration (Event time) and recorded with an inter pulse interval of 18 s over a 12-min recording period. Arrows indicate the times when ACh was introduced or washed from the bath, respectively. (D) Line graph showing the spike frequencies for individual cells under the control, ACh, and wash conditions. (E) Bar graph of the mean spike frequency. *** Significantly-different from control, one-way repeated measure ANOVA with Tukey’s post-hoc test, p < 0.001.
52
Figure 3.4 Cholecystokinin modulates the activity of GLP-1 neurons. (A, B) Line graphs of the changes in evoked, AP firing frequency in response to bath applied CCK for two representative GLP-1 neurons (A) excitation and (B) inhibition. (C, D) Line graphs showing either (C) enhanced or (D) suppressed spike frequencies for individual cells under control, CCK, and wash conditions. (E, F) Bar graphs of the mean spike frequency in the sampled population of GLP-1 neurons that were either (E) excited or (F) inhibited by CCK, respectively. ** Significantly-different from control, one-way repeated measure ANOVA with Tukey’s post-hoc test, p < 0.01.
53 Figure 3.5 A subgroup of GLP-1 neurons responds to changes of glucose concentration. (A) Line graph of the changes in evoked, AP firing frequency under different glucose concentrations for a representative GLP-1 neuron. (B) Bar graph of the mean spike frequency for six GLP-1 neurons that responded to glucose concentration changes among 16 recorded neurons, paired t-test, p = 0.13, n = 6.
3.3.4 Enzyme-linked immunosorbent assay (ELISA) measurements of GLP-1
It seemed that the OB GLP-1 responded to metabolic-related signals. Next, we wanted to examine whether different metabolic states change the contents of GLP-1 in the OB. Three groups of animals were used in the experiment. (1) ad-libitum group had access to food all the time, (2) fasted group was deprived of food for 24 hours, and (3) re-fed group was deprived of food for 22 hours then was provide food for 2 hours. At the time of harvest, blood samples and OB tissues were collected for GLP-1 measurements. We found that fasting significantly decreased the GLP-1 level in the OB compared with ad-libitum group, while re-feeding did not significantly change the GLP-1 level compared to fasted group (Figure 3.6A). In the blood, re- feeding increased GLP-1 level compared with ad-libitum group and fasted group, while there was no significant difference between ad-libitum group and fasted group (Figure 3.6B).
3.3.5 The effects of systemic modulation of GLP-1 signaling on olfactory behavior
Lastly, we sought to investigate whether the alteration of GLP-1 signaling could change animals’ olfactory behavior. Mice were injected intraperitoneally (0.4 µM/kg) with the GLP-1 analogue Exendin-4 or control saline and tested 30 minutes post injection in an odor habituation-
54 dishabituation paradigm. Mice receiving Exendin-4 failed to show significant dishabituation, demonstrating impaired ability to discriminate the novel odor from old odor (Figure 3.7 C, D). However, when the Exendin-4 (10 µM, 20 µL) was delivered intranasally, mice showed normal odor discrimination compared with vehicles treated animals (Figure 3.7 E, F).
Figure 3.6 Enzyme-linked immunosorbent assay (ELISA) measurements of GLP-1 content. Bar graph of GLP-1 levels in the (A) OB and in (B) serum. One-way ANOVA with Tukey’s post-hoc test; different lower case letters indicate significantly-different means in the post-hoc analyses. Number of mice per treatment group as indicated.
3.4 Discussion
In the present study, we explored the basic electrophysiological properties of GLP-1 neurons in the OB. We showed that ACh could modulate the activity of the OB GLP-1 neurons. We also found that these GLP-1 neurons could be modulated by metabolic-related hormone CCK, and a subset of these neurons responded to glucose concentration changing. Lastly, we showed that systemic injection of a GLP-1 analogue Exendin-4 impaired animal’s odor discrimination ability.
All GLP-1 neurons exhibited hyperpolarization induced ‘sag’ potential. The ‘sag’ potential is associated with hyperpolarization-activated, cyclic nucleotide-gated (HCN) channel (He et al., 2014). Activation of HCN channel led to permeability of potassium and sodium ions,
55
Figure 3.7 Habituation-dishabituation tests after delivering Exendin-4. (A) Photograph of the apparatus for habituation-dishabituation test. (B) A representative data for a mouse going through the test. Repeated exposure to odor 1 led to habituation indicated by gradually decreased exploratory time. When present with odor 2, the mouse showed dishabituation indicated by dramatically increased exploratory time. (C) Habituation-dishabituation test for ethyl hexanoate (C6) / ethyl octanoate (C8) after intraperitoneal injection of PBS or Exendin-4. (D) Habituation-dishabituation test for ethyl heptanoate (C7) / isopropyl tiglate (Iso-t) after intraperitoneal injection of PBS or Exendin-4 (Ex-4). (E) Habituation- dishabituation test for ethyl hexanoate (C6) / ethyl octanoate (C8) after intranasal delivery of PBS or Exendin-4. (F) Habituation-dishabituation test for ethyl heptanoate (C7) / isopropyl tiglate (Iso-t) after intranasal delivery of PBS or Exendin-4. *Significantly-different, p < 0.05, ** Significantly-different, p < 0.01, Mann-Whitney U test.
56 and produced the inward so called Ih current (Biel et al., 2009). Ih current plays important roles in stabilizing the resting membrane potential (Llinas & Jahnsen, 1982; Lupica et al., 2001) and integrating the synaptic inputs (Magee, 1998). Ih current has been implicated in a variety of physiological processes including learning and memory, sleep and wakefulness, sensation and perception (Robinson & Siegelbaum, 2003). It has been shown that Ih current is involved in adjusting sensory signal transduction and perceiving environmental stimuli (Orio et al., 2009;
Zhou et al., 2010). For the vision, Ih current was characterized in the photoreceptor cells and was contributed to visual adaptation to bright light (Bader et al., 1979; Attwell & Wilson, 1980). In the taste system, HCN channels were also thought to generate the sensory receptor potential to mediate the sour taste response (Stevens et al., 2001). The dysregulation of HCN channels has been shown to involve multiple pathological conditions such as epilepsy, neuropathic pain, parkinsonian disease (He et al., 2014). HCN channels are regulated by wide-ranging cellular signals. Acetylcholine can both inhibit (Heys et al., 2010) and upregulates (Pian et al., 2007). It will be interesting to examine whether the modulation of GLP-1 neurons by acetylcholine in the
OB involves Ih current, which may adjust olfactory signal transduction and eventually lead to change in the olfactory perception.
The important role of cholinergic modulation in the OB for olfactory acuity has been long established (Fletcher & Wilson, 2002; Wilson et al., 2004; Chaudhury et al., 2009). More specifically, odor response tuning of mitral/tufted cells is sharpened by the cholinergic input, thereby facilitating contrast enhancement (Castillo et al., 1999; Ma & Luo, 2012). The OB receives cholinergic input from the horizontal limb of the diagonal band of Broca (HDB) of the basal forebrain (Zaborszky et al., 1986; Kasa et al., 1995). Interesting, this basal forebrain cholinergic system also projects to hypothalamus and has been shown to modulate appetite- related synapses in lateral hypothalamic slice (Jo et al., 2005). A recent study further showed that the basal forebrain to hypothalamus cholinergic circuit plays an important role in regulating feeding behavior (Herman et al., 2016). When the cholinergic signaling was impaired by either ablating cholinergic neurons or knockdown choline acetyltransferase expression, animals showed increased food intake leading to severe obesity. On the other hand, enhanced cholinergic signaling led to decreased food intake. The authors concluded that this cholinergic basal forebrain feeding circuit modulates appetite suppression. Based on this knowledge a link
57 between satiation/positive energy state and altered olfactory process could be constructed. Through unknown mechanisms feeding activates the basal fore brain cholinergic neurons (Herman et al., 2016), which, in turn, will act on hypothalamic targets to exert their appetite suppression effect, and at the same time modulate the activity of GLP-1 neurons in the OB to alter olfactory processes. It has been shown that exogenous GLP-1 can modulate the activity of mitral cells in the OB (Thiebaud et al., 2016). We have further evidence showing that optogenetic activation of GLP-1 neurons can also have direct and indirect effects on the activity of mitral cell (Thiebaud et al., submitted), which, in turn, can alter the olfactory process.
It is well known that a person’s nutritional status could affect the person’s olfaction. During a fasting state people showed an enhanced ability to detect odors including some food- related odors, while at satiety state people exhibited reduced ability to detect the food odor (O'Doherty et al., 2000; Mulligan et al., 2002). Accumulating evidence shows that the OB not only serves as a sensory organ detecting olfactory information from external environment, but also could function as a sensor for internal metabolic states (Palouzier-Paulignan et al., 2012). In the OB the expression of a variety of metabolic hormones such as ghrelin, orexins, leptin, insulin, CCK and their receptors (Palouzier-Paulignan et al., 2012) makes it capable of detecting animal’s metabolic states. In capable of detecting metabolic states places the OB in a critical position to connect metabolism with olfaction. Indeed, it has been shown that the cannabinoid type-1 (CB1) receptor in the OB is a link between hunger state and stronger odor processing in mice (Soria-Gomez et al., 2014b). Fasting increased the levels of the endocannabinoid anandamide (AEA) in the OB, AEA activates the CB1 receptor, which reduced the glutamatergic transmission leading to decreased activation of neurons in the granule cell layer of the OB, through which and unknown mechanisms animals showed stronger odor processing and increased food intake (Soria-Gomez et al., 2014b). The endocannabinoid system in the OB seems to link hunger state with stronger odor sensing to promote food intake.
Substantial evidence has demonstrated both the central and peripheral effects of GLP-1 on reducing food intake (Williams, 2009). Since GLP-1 is secreted after meal ingestion, it’s possible that the GLP-1 system in the OB could link weaker odor sensing to satiety state to inhibit food intake. When we increased GLP-1 signal through systemic injection of Exendin-4, animals showed weaker odor sensing indicated by impaired odor discrimination. This result 58 could be attributed to central effects of Exendin-4 in the OB and other brain regions. Because Exendin-4 has a much longer half-life (Parkes et al., 2001), it can cross blood brain barrier and reach to several areas of the brain (Kastin & Akerstrom, 2003). Our previous data showed that when fluorescent Exendin-4 was injected subcutaneously, it can reach to the mitral cells in the OB (Thiebaud et al., 2016). When Exendin-4 was delivered intranasally, we did not detect the Exendin-4 in the OB (unpublished data). Whereas under physiological condition, the cross of GLP-1 secreted after meals through blood brain barrier, if any, should be minimal because of its short half-life of 1-2 min (Kieffer et al., 1995). Our result also supports this. When fasted animals were re-fed for 2 hours, there was increased GLP-1 level in the blood. However, the level of GLP-1 in the OB did not show significant change after re-feeding (Figure 3.6). Our ELISA data showed that re-feeding did not increase GLP-1 in the OB. However, even though the total GLP-1 content did not change, the release of GLP-1 could increase if the GLP-1 neurons are activated by re-feeding. One possible way to activate GLP-1 neurons by re-feeding is through the satiety-related hormones such as leptin, CCK. We did find that the activity of GLP-1 neurons was modulated by CCK. However, CCK induced both excitation and inhibition of GLP-1 neurons. So the mechanisms are more complicated than just CCK activating GLP-1 neurons. Further experiments are needed to examine whether there is heterogeneity among the GLP-1 neuron population in the OB, what are their specific inputs, what are their downstream targets?
In summary, using in vitro electrophysiology and behavioral testing we provide evidence that GLP-1 neurons in the OB connect metabolic state with olfaction. We demonstrated that the OB GLP-1 neurons could respond to metabolic-related signals such as CCK, glucose. Moreover, when we activated GLP-1 signaling, animals showed impaired odor discrimination ability. Of course, further experiments using optical or genetic tools to monitor or modulate the activity of the OB GLP-1 neurons in vivo during different metabolic states are needed to directly address our hypothesis. Lastly, our olfactory behavioral testing data suggests that the GLP-1 related drugs may cause side effect on patient’s olfaction. In our animal behavioral experiments acute administration of Exendin-4 caused temporal detrimental effect on animal’s ability to distinguish odors. Once the drug was cleared, the animals regained their olfactory ability. For patients, however, long-term use of GLP-1 related drug may induce impairments of their olfactory function.
59 CHAPTER 4
OLFACTION AND ANXIETY IN KV1.3 KNOCK-OUT MICE: POSSIBLE APPLICATION IN ADHD
4.1 Introduction
Olfaction is phylogenetically the most ancient sense and has a close association with emotion; it has been well studied that the perception of an odor cue can be altered depending upon reward, threat, or homeostatic state (Hamann, 2003; Krusemark et al., 2013; Nunez-Parra et al., 2014). Unlike other senses, the olfactory system has extensive reciprocal connections with primary emotion areas in the brain such as the amygdala, the hippocampus, and the orbitofrontal cortex (Astic et al., 1993; Carmichael et al., 1994; Haberly, 2001). Not surprisingly, a modification in olfactory function may affect emotion. While olfactory function can be disturbed via disease or nutritional state (Rugarli, 1999; Aime et al., 2007; Thiebaud et al., 2014), olfactory function can also be altered experimentally through surgical (Meredith et al., 1983) or chemical lesions (Slotnick et al., 2007; DiBenedictis et al., 2014), or via genetic engineering (Fadool et al., 2004; Glinka et al., 2012). Interestingly, surgical removal of the olfactory bulb is classically known to result in anxiety- and depression-like behaviors (for review, see Brunjes, 1992). In fact, bulbectomized rodents show behavioral changes that simulate many of those seen in patients with major depression and most of these behaviors can be reversed by chronic antidepressant treatment (Song & Leonard, 2005; Roche et al., 2012; Amigo et al., 2016). As a result, olfactory bulbectomy models have frequently been used to screen for antidepressant drugs (Cairncross et al., 1977; Kelly et al., 1997; Song & Leonard, 2005).
This Chapter was submitted to Physiology & behavior as, “Olfaction and anxiety in Kv1.3 knock-out mice: possible application in ADHD”. By Zhenbo Huang, Carlie A. Hoffman, Brandon M. Chelette, Nicolas Thiebaud, Debra Ann Fadool. ZH was responsible for data collection of Figure 1, 2, 5, configuration of all figures, analysis of all data, and preparing the first draft of the manuscript.
60 Genetic engineering can also be used to produce either a loss or an accentuation of olfactory ability. For example, Glinka et al. (Glinka et al., 2012) showed that Cnga-2-null mice that lack the cyclic nucleotide-gated ion channel mediating transduction of olfactory signals via the main olfactory epithelium are anosmic, and possess increased anxiety levels compared to mice of normal olfactory ability (Zhang & Firestein, 2002) . The authors suggest that anosmia might lead to chronic stress as indicated by measurable elevations in plasma corticosterone levels. Fadool et al., 2004 showed that mice containing a deletion of a predominant voltage- gated potassium channel expressed in mitral cells of the olfactory bulb (Kv1.3-/- mice) have a ‘Super-smeller’ phenotype (Fadool et al., 2004). These mice have heightened olfactory function as measured by olfactory threshold and odor discrimination. If olfactory function and anxiety level are inversely related, we hypothesized that mice with an enhanced olfactory ability might evoke an anxiolytic state or reduction in anxiety. This would be congruent with our previous findings that insulin-induced phosphorylation of Kv1.3 (Fadool et al., 2000; Marks et al., 2009; Fadool et al., 2011) and resultant decrease in channel open probability (Fadool et al., 2000) evokes a reduction in anxiety behaviors when intranasally administered to the olfactory bulb (Marks et al., 2009). Whether the Kv1.3 ion channel could be a pharmacological target to reduce anxiety is also an intriguing possibility.
Increased anxiety is often co-morbid with other psychiatric conditions such as attention deficit/hyperactivity disorder (ADHD), a disorder characterized by excessive levels of impulsivity, inattention, and hyperactivity (Biederman et al., 2013; Yuce et al., 2013; Pineiro- Dieguez et al., 2014). In phenotyping Kv1.3-/- mice for olfactory-related behaviors, we qualitatively observed hyperactivity-like behaviors and quantified increased locomotor activity during the dark cycle as well as irregular ingestive and metabolic activities (Fadool et al., 2004; Tucker et al., 2010). We and others described a thin body type and resistance to diet-induced obesity in the Kv1.3-/- mice that was linked to the conductance of the channel (Xu et al., 2003; Fadool et al., 2004; Fadool et al., 2011). Thus, we became curious as to whether olfaction, metabolism, ADHD, and anxiety were interrelated (Palouzier-Paulignan et al., 2012; Krusemark et al., 2013; Kovach et al., 2016).
ADHD has a complex symptomatology due to the heterogeneous nature of the genetic and environmental factors contributing to the disorder – and suitable animal models are largely 61 lacking. Because many individuals carry this disorder into adulthood (Pineiro-Dieguez et al., 2014), research currently focuses on finding long-term treatment options that could benefit from a greater variety of new animal models. The ADHD diagnosis is often subdivided into three categories: 1) the predominantly inattentive subtype, characterized primarily by inattentiveness in the absence of hyperactivity; 2) the predominantly hyperactive/impulsive subtype, characterized by impulsiveness; and 3) the combined subtype, which exhibits both inattentiveness and impulsiveness (Taylor, 1998; Sagvolden et al., 2005). Thus far, the most widely studied and best accepted animal model of ADHD is the spontaneously hypertensive rat (SHR), which has been found to exhibit face validity, construct validity, and predictive validity for ADHD (Sagvolden et al., 2005; Hill et al., 2012). Other models, such as the prenatal nicotine exposure mouse, have also been used to study treatment options and neural effects of ADHD (Zhu et al., 2012).
The present study explores the possibility that Kv1.3-/- mice may serve as an advantageous animal model of ADHD whereby inattentiveness could be reversed through treatment with methylphenidate. In parallel, we investigate the interrelationship of anxiety, which can be co-morbid with ADHD, with that of olfactory ability to interrogate whether accentuation of olfactory acuity can reduce anxiety behaviors.
4.2 Materials and Methods
4.2.1 Animals
All animal experiments were approved by the FSU Institutional Animal Care and Use Committee (IACUC) under protocol #1427 and were conducted in accordance with the American Veterinary Medicine Association (AVMA) and the National Institutes of Health (NIH Publications No. 8023, revised 1978). For tissue collection, mice were anaesthetized with isoflurane (Aerrane; Baxter, Deerfield, IL, USA) using the IACUC-approved drop method and were then sacrificed by decapitation (AVMA Guidelines on Euthanasia, June 2007). Use of the ARRIVE guidelines for reporting animal research was followed in the design of the manuscript (Kilkenny et al., 2010).
62 All mice (WT = wildtype; C57BL/6J background strain, The Jackson Laboratory, Bar Harbor, ME) were singly-housed in conventional style open cages at the Florida State University (FSU) vivarium in accordance with institutional requirements for animal care. Mice were maintained on a standard control diet (Purina 5001, New Brunswick, NJ). Mice had access to food and water ad libitum and experienced a standard 12/12-hour light/dark cycle with 7:00 AM lights and 7:00 PM lights off. Behavioral testing was performed 2 hours (h) prior to the dark cycle. Both male and female mice were examined for anxiety phenotyping. Because sex-related differences were largely unobserved in the anxiety tests, subsequent experiments only utilized male mice. Kv1.3-/- mice were generated by excision of the Kv1.3 promoter region and one third of the 5’ coding region of C57BL6/J mice (Xu et al., 2003). In accordance with institutional and National Institutes of Health (NIH) guidelines, cages were cleaned weekly and rooms housing mice were examined daily for suitable living conditions. The majority of mice used in this study were two to five months of age. For attention and locomotor testing experiments, young mice were defined as 2-5 months of age and older mice were defined as 8-12 months of age.
4.2.2 Anxiety testing
4.2.2.1 Marble-burying test
Based on the procedure described in Marks et al., 2009, the marble burying (MB) test involved taking mice from their home cage and allowing them to acclimate in an empty rat cage (45 cm [L] × 23 cm [W] × 20 cm [H]) filled with 5 cm of bedding for 15 minutes. The cage was kept in a small, dark room and was covered with a wire lid for the duration of the MB experiment. The mice also did not have access to food or water during testing. After the acclimation period, the mice were returned to their home cage while an evenly-spaced grid of black marbles possessing a light metallic sheen was arranged in the testing cage (Figure 4.1A). The mice were then placed into the center of the grid of marbles and were free to move around the cage for a 30-minute period. After the testing period, the mice were removed and returned to their home cages while the number of buried marbles was counted. Buried marbles were defined as being at least 2/3 covered by bedding.
63 4.2.2.2 Light-dark box test
As described in Marks et al., 2009, the light-dark box (LDB) was constructed from a rat cage (45 cm [L] × 23 cm [W] × 20 cm [H]) that was painted half white and half black. A black lid and removable divider were constructed out of hard, black cardboard. The black divider was positioned at the intersection between the white and black regions to create separate dark and light boxes. The divider also contained a square opening (7 cm [L] × 7 cm [W]) at its base to enable the mouse to easily enter and exit the dark and light boxes. The black lid was placed over the black-painted portion of the box, while a 60-watt light bulb was suspended and positioned over the white-painted portion of the box (Figure 4.1C). Mice were removed from their home cage and placed directly into the dark box of the testing apparatus. The lid was positioned over the dark box and a small square of hard, black cardboard was held over the opening in the divider for the first five seconds of the testing period. After this time, the square was removed and the mouse was free to move between the boxes for a five minute testing period. The mouse did not have access to food or water for the duration of the experiment. A video camera (Sony Handycam camcorder; San Diego, CA) was suspended from a ceiling tile and used to record each testing period. Once the testing period had concluded, the mouse was removed from the testing apparatus and returned to its home cage. After recording, Sony Picture Motion Browser software was utilized to digitize the videos and the amount of time the mouse spent in the dark and light boxes was determined.
4.2.2.3 Elevated-plus maze test
Mice were removed from their home cage and placed directly into the center of an elevated-plus maze (EPM, Columbus Instruments, Columbus, Ohio). The maze was elevated 45 cm off the ground and possessed four arms, two of which contained barriers (35 cm [L] × 5 cm [W] × 15 cm [H]), while two were open (35 cm [L] × 6.5 cm [W]) (Marks et al., 2009) (Figure 4.1G). The mouse was placed at the intersection of the closed and open arms and was able to move freely between the arms for a five minute testing period. The mouse did not have access to food or water for the duration of the experiment. The video camera and the software described above were used to determine the amount of time the mouse spent in the open arms, closed arms, and the intersection point.
64 4.2.3 ADHD behavioral testing
4.2.3.1 Oral gavage
For drug administration, mice were given methylphenidate hydrochloride (MPH, Sigma- Aldrich, St. Louis, MO) or a phosphate buffered saline (PBS) vehicle via oral gavage 60 minutes prior to testing. The dose of MPH (0.75 mg/kg) was used as described previously (Balcioglu et al., 2009). A dose of 0.75 mg/kg in mice appears to be therapeutically relevant given that this oral dose achieves plasma levels within 15 minutes as that obtained and valid occupancy level of the dopamine transporter in patients (is comparable to 6-10 ng/ml; Balcioglu et al., 2009). Also in accordance with Balcioglu et al., 2009, we used a blunt metal feeding needle (Fisher Scientific, catalog #1020887; Pittsburg, PA) that was lubricated with water prior to insertion of the needle through the mouth and into the stomach of the mouse. MPH or saline was then administered directly into the stomach via the feeding needle and the gavage volume was kept constant at 10 µL/g body weight.
4.2.3.2 Object-based attention test
According to the procedures detailed by Alkam et al., 2011 and Ishisaka et al., 2012, an opaque, plexiglas black chamber was manufactured for use in the object-based attention test. The apparatus consisted of two chambers separated by a removable, sliding divider (acquisition chamber: 40 cm [L] x 40 cm [W] x 22 cm [H]; retention chamber: 40 cm [L] x 20 cm [W] x 22 cm [H]), and the floors of the chambers were covered with a thin layer of standard bedding (Figure 4.3A). The mice were administered MPH or saline vehicle via oral gavage 30 minutes prior to beginning the acclimation period. The mouse was then removed from its home cage and placed into the empty, full testing apparatus for 10 minutes (Figure 4.3B). The sliding divider was removed during this time to allow the mouse access to both the acquisition (large) and retention (small) chambers. The sliding divider was then reinserted and the mouse was free to explore the large acquisition chamber for 10 minutes. The sliding divider was finally raised and, using gentle guidance, the mouse was moved into the small retention chamber and was allowed to explore only this area for 10 minutes. After this final acclimation time, the mouse was removed from the testing apparatus and placed in its home cage while five wooden toys
65 (Imaginarium Wooden Block Set, Wayne, NJ) of various shapes (semi-circle, circle, bridge, rectangle, and square) were randomly placed an even distance apart in the acquisition chamber. Two wooden toys, one unique in shape (triangle) and one replicate shape (square) from the five toys placed in the acquisition chamber were also evenly spaced in the retention chamber. The chambers were separated by the sliding divider for the duration of the testing period and the toys used were of similar size, color, and smell to prevent undesired bias toward a single shape. The mouse was then placed into the center of the acquisition chamber and was free to explore the five unfamiliar toys for a three-minute timespan. The sliding divider was then raised and the mouse was gently guided into the small retention chamber, where it was free to explore one familiar toy (square) and one unfamiliar toy (triangle) for a three-minute period. The mouse did not have access to food or water for the duration of the experiment. The basis behind this test assumes that if the mouse is able to appropriately divide its attention among the five toys in the acquisition chamber, then it will spend more time attending to the novel toy in the retention chamber. However, if the mouse spends equal or less time on the novel object compared to the familiar object in the retention chamber, then the animal did not properly allocate its attention in the acquisition chamber. All testing was recorded using the Handycam camcorder and associated software as described previously. The time spent on each toy in the acquisition chamber as well as time spent on each toy in the retention chamber were measured from the digitized records. A mouse was considered to be attending to a toy when its body was oriented toward it and it was within one nose-length of the object. The amount of time spent on the unfamiliar toy compared to the amount of time spent on both toys in the retention chamber was defined as the recognition index (Alkam et al., 2011).
4.2.3.3 Locomotor test
Metabolic chamber analysis involved removing mice from their home cage and placing them into sealed chambers that recorded total locomotor movement and water, food, and air consumption over a 24-hour period (Williams et al., 2000; Tucker et al., 2008). While in the chambers, the mice had unlimited access to food, water, and one enrichment item. The metabolic chambers were built by the FSU machine shop and were derived from standard rat cages (Figure 4.4A). Eight cages were stored in two recycled deep freezers to enable the air levels and temperature of the cages to be controlled. A computer program was used to record the 66 pressure, oxygen, and carbon dioxide levels as well as the temperature of the chambers and the total distance moved by each mouse over the 24-h day. Only data from the dark cycle were analyzed for these experiments. Each day at 6:00 PM, the mice were weighed and the food and water from each chamber were removed and weighed to determine how much the mice had consumed over the previous 24-h period. The food and water were then disposed of and fresh equivalents were weighed and presented to the mice. The food utilized was standard mouse chow (Purina 5001) that had been ground into a fine powder. The mice were kept in the chambers for a minimum of six days total and experienced a standard 12/12-h light/dark cycle during this time from 7:00 AM light on to 7:00 PM light off. The cages were not changed or cleaned for the duration of the six-day acclimation, but were only cleaned before a new mouse was placed in the chamber. After acclimation, mice were weighed at 6:00 PM and gavaged with either saline or MPH at 9:00 PM. There was a two hours’ time lapse between initiating the dark cycle (7:00 PM) and initiating gavaging (9:00 PM) to enable the mice time to acclimate to the dark cycle before beginning testing. After gavaging, the total distance traveled from 9:00 PM to 7:00 AM (10 hours block) was recorded. The total distance traveled per mouse for each of the three nights of testing was averaged to yield one mean distance value per mouse.
4.2.3.4 Tissue harvest for HPLC and SDS PAGE/Western analyses
Mice were anaesthetized with isoflurane (Aerrane; Baxter, Deerfield, IL, USA) using the IACUC-approved drop method and were then sacrificed by decapitation (AVMA Guidelines on Euthanasia, June 2007). Olfactory bulbs (OBs) were quickly harvested after decapitation. Tissues were immediately frozen in dry ice/100% ethanol. The HPLC measurements of dopamine and 3,4-dihydroxyphenylacetic acid (DOPAC) were performed by the Vanderbilt Neurochemistry core at Vanderbilt University (Nashville, TN). For SDS PAGE analysis, OBs were homogenized in NP40 PPI for fifty strokes with a Kontes tissue grinder (size 20) on ice, and cytosolic proteins were extracted as previously described (Tucker & Fadool, 2002). The cytosolic proteins (25 µg/lane) were separated on 8%–10% acrylamide gels by SDS-PAGE and electrotransferred to nitrocellulose blots. Nitrocellulose was incubated overnight at 4 °C with the primary antibodies: anti-tyrosine hydroxylase (TH), anti-dopamine receptor type II (D2DR), and extracellular signal- related kinase (ERK). The anti-TH (applied at 1:500 dilution) was acquired from Cell Signaling Technology (Danvers, MA, cat# 2792) and is a polyclonal antibody produced by injecting 67 rabbits with a synthetic peptide that corresponds to the amino-terminal sequence of human TH. The anti-D2DR (applied at 1:500) is from Millipore (Temecula, CA, cat# AB5084P) and is a polyclonal antibody produced by injecting rabbits with a 28 amino acid peptide sequence within cytoplasmic loop #3 of the human D2 receptor. The anti-D2DR recognizes both the long and short form of the receptor. The anti-ERK (applied at 1:2000) was acquired from Cell Signaling Technology (cat# 9102) and is a polyclonal antibody produced by injecting rabbits with a synthetic peptide derivative of the C-terminus of rat ERK1. The anti-ERK recognizes both ERK1 and ERK2. Enhanced chemiluminescence (ECL; Amersham-Pharmacia) exposure on Fugi Rx film (Fisher) was used to visualize labeled proteins. The film autoradiographs were analyzed by quantitative densitometry using a Hewlett-Packard Photo Smart Scanner (model 106–816, Hewlett Packard, San Diego, CA) in conjunction with Quantiscan software (Biosoft, Cambridge, England). Immunodensity ratios (Kv1.3-/- over wild-type) were calculated, normalized, and analyzed as described previously (Tucker & Fadool, 2002).
4.2.4 Statistical analyses
GraphPad Prism 6.0 (GraphPad Software, Inc., La Jolla, CA) was utilized for statistical analyses. For each analysis, data were first confirmed to be normally distributed using the D'Agostino & Pearson omnibus normality test. For anxiety tests comparing genotyping differences, a two-way randomized analysis of variance (ANOVA) was applied with sex and genotype as factors. For anxiety, attention, and locomotor tests involving MPH treatment, a two- way, repeated measures ANOVA was applied using drug and genotype as factors. Post-hoc tests for multiple comparisons were performed with a Tukey’s correction. Student’s t-test and non- parametric Mann-Whitney test were applied for two-sample population studies for the HPLC and SDS PAGE experiments. Statistical significance was determined at the 95% confidence level (α ≤ 0.05) unless otherwise noted. Values are reported as the mean ± standard error of the mean (SEM). Data were graphed using Origin 8.0 (MicroCal Software, Northampton, MA) or Photoshop CS7 (Adobe, San Jose, CA).
68 4.3 Results
4.3.1 Kv1.3-/- mice exhibit increased anxiety in the LDB and EPM apparatus
We initiated anxiety testing in the Kv1.3-/- mice due to the reported comorbidity of ADHD and anxiety disorders (Biederman et al., 2013; Yuce et al., 2013; Pineiro-Dieguez et al., 2014). We used three different paradigms to assess anxiety-like behaviors in the Kv1.3-/- mice – the marble-burying (MB) test, the light-dark box (LDB) test, and the elevated-plus maze (EPM) test (Figure 4.1). Species-typical behaviors such as burrowing and digging have been employed as sensitive measures to screen the effects of suspected anxiolytic drugs but there are still debates in the literature as to whether this test detects anxiety, depression, or obsessive-compulsive behavior in rodent models (Deacon, 2006). Only male mice were available during our MB tests, but the other two tests used mice of both sexes. The number of marbles buried is correlated to an increase in anxiety or related disorder. Using a 30-minute testing interval (see methods), the number of marbles buried was not significantly different across genotypes (Kv1.3-/- mice = 1.8 ± 0.3 (n = 26) vs. WT = 2.3 ± 0.5 (n = 17); Student’s t-test, p = 0.4202Figure 4.1B). In the light- dark box (LDB) test, the latency for the Kv1.3-/- mice to make the first move to the light box was significantly delayed (Figure 4.1D; sex: NS, p = 0.294; genotype: p = 0.005) and the total time spent in the light box was significantly reduced compared with that of WT mice (Figure 4.1E; sex: p = 0.013; genotype: p < 0.001) when applying a two-way analysis of variance (ANOVA) using genotype and sex as factors; Tukey’s post-hoc test. While these metrics implicated an increased anxiety level in the Kv1.3-/- mice, there was not a significant difference in exploratory behavior as assessed by total number of transitions between boxes (Figure 4.1F; 2- way ANOVA, sex: p = 0.057; genotype: p = 0.138) although there was a trend that the Kv1.3-/- moved less in this assay and particularly for that of females. The third and final anxiety test represented one of threatening or real danger for the mouse given that the apparatus has open arms that are 42 cm off the floor in the EPM. The number of transitions to the open arms of the maze was less than 10% of the total transitions for Kv1.3-/- mice (Figure 4.1H vs. J; 2-way ANOVA, sex: p = 0.025; genotype: p < 0.001) that spent a significantly shorter duration of their testing time in the open arms (Figure 4.1I; 2-way ANOVA, sex: p = 0.183; genotype p < 0.001). In fact, we observed that approximately 20% of the Kv1.3-/- mice sometimes exhibited a
69 freezing like behavior in the open arms. If the animals immobilized in the open arms for over 15 s, the data were excluded and recorded as a freezing event.
4.3.2 MPH treatment ameliorates Kv1.3 anxiety and attention deficit
Next we examined whether the significant genotypic difference we observed for the anxiety-like behavior in the LDB could be alleviated for mice following methylphenidate (MPH) treatment. First, both WT and Kv1.3-/- male mice were administered saline via oral gavage to determine their basal anxiety levels. As shown in Fig. 2, Kv1.3-/- mice showed increased latency to the light box (Figure 4.2A), and spent less time in the light box (Figure 4.2B), which indicated increased anxiety, similar to what we demonstrated previously (Figure 4.1). This suggested that the oral gavage route of administration did not perturb this behavior. After four days, the same mice were administered MPH by oral gavage, and anxiety levels were retested. As shown in Figure 4.2B, MPH treatment alleviated the anxiety of the Kv1.3-/- that now spent time in the light box, which was not significantly different than that of WT mice (two-way repeated ANOVA, drug p = 0.076, genotype p = 0.039). The most marked effect was the first latency to the light box that was 8x as long in the Kv1.3-/- vs. WT mice prior to MPH treatment, which after MPH treatment, fell to less than 5 s and was similar to latency times recorded for WT mice (Figure 4.2A; two-way repeated ANOVA, drug p = 0.005, genotype p = 0.003).
Because one of the prominent behavioral symptoms of ADHD exhibited by children and adults is an attention deficit, we were eager to examine the attention levels of young (two to five months) vs. older (eight to twelve months) mice using a relatively new object-based attention testing paradigm (Figure 4.3A). Both WT and Kv1.3-/- mice were initially administered saline via oral gavage to determine their basal attention levels, again under an oral route of administration. The test animal’s attention was indicated by a calculated recognition index (see methods). Mice with better attention abilities will be able to spend less time with the familiar object and a greater amount of time with the unfamiliar object, yielding a higher recognition index. After two weeks, the same mice were administered MPH via oral gavage and their recognition index was recomputed. While in the acquisition phase (Figure 4.3B), the mice spent approximately equal amounts of time exploring each of the five toys (data not shown), thus indicating there was no bias towards a particular shape. Older Kv1.3-/- mice had a significantly
70
Figure 4.1 Kv1.3-/- mice exhibit increased anxiety in the light-dark box (LDB) and elevated-plus maze (EPM) apparatus. (A) Photograph of the buried marble (MB) test apparatus. (B) Bar graph of the number of marbles buried by male wild-type (WT) vs. Kv1.3-/- (Kv1.3-/-) mice. Student’s t-test. (C) Photograph of the light-dark box (LDB) test apparatus. (D-F) Bar graphs of the latency to movement to the light box (D), the time spent in the light box (E), and the number of transitions between boxes (F) comparing WT vs. Kv1.3-/- mice. Two-way analysis of variance, Tukey’s post-hoc test. (G) Photograph of the elevated-plus maze (EPM) test apparatus. (H-J) Bar graphs of the number of transitions to the open arms (H), the time spent in the open arms (I), the total number of transitions (J) comparing WT vs. Kv1.3-/- mice. Two-way analysis of variance, Tukey’s post-hoc test. (B, D-F, H-J): Significantly- different means, * p < 0.05, ** p < 0.001. NS = not-significantly different. Different lower case letters indicate significantly- different means in the Tukey’s post-hoc analysis with genotype and sex as factors. Number of mice per treatment group as indicated. Data represent mean plus or minus the standard error of the mean (s.e.m.).
71
Figure 4.1- continued
Figure 4.2 Anxiety disorder in male Kv1.3-/- mice can be alleviated by methylphenidate (MPH) treatment. (A) Bar graph of latency of first movement to the light box of the LDB, or (B) the time spend in the light box of the LDB comparing WT vs. Kv1.3-/- mice treated first with saline (baseline) and then with MPH. Two-way repeated measure (RM) ANOVA, Tukey’s post-hoc analysis with drug and genotype as factors. Same notations as in Fig. 4.1. 72 reduced recognition index that was elevated to that of WT mice following MPH treatment (Figure 4.3D; two-way repeated ANOVA; drug p = 0.037, genotype p = 0.045). This pattern of behavior was also observed for the young mice but did not reach statistical significance (Figure 4.3C; two-way repeated ANOVA; drug p = 0.112, genotype p = 0.569).
Figure 4.3 Object-based attentional deficits of male Kv1.3-/- can be ameliorated by MPH treatment. (A) Schematic diagram of the object-based attention test apparatus whereby mice are permitted a 3- minute interval in the acquisition chamber followed by a 3-minute testing interval in the retention chamber. (B) Schematic time line of the experiment. Preceding habituation, each mouse was orally gavaged (start oral gavage) with saline or MPH and was returned to its home cage for 30 minutes. After this period, habituation began and occurred in three stages, each 10 minutes in duration. For the first 10 minutes, the mouse was free to explore the entire empty apparatus. A removable divider was then placed within the apparatus, dividing the cage into a large acquisition chamber and a small retention chamber. The mouse was free to explore the large acquisition chamber for 10 minutes, then the small retention chamber for 10 minutes. After habituation, the mouse was placed in the center of the acquisition chamber that now included the shape objects and was permitted to roam the chamber for 3 minutes (the acquisition phase). After this time, the removable divider was raised and the mouse was gently guided into the retention chamber. Once the mouse was in the smaller chamber, the divider was slid back into place and the mouse was permitted to roam the retention chamber for 3 minutes (the retention phase). Bar graph of the recognition index for (C) young vs. (D) older mice. (C-D) young = two to five months, older = eight to twelve months of age. Same statistical analyses and notations as in Fig. 4.2.
73 4.3.3 Locomotor testing
In addition to attention deficits, another core symptom of ADHD is hyperactivity. Metabolic chamber analysis (Figure 4.4A, B) was performed on mice of both genotypes to measure locomotor activity, and thus indirectly measure hyperactivity. Mice were gavaged two hours into the dark cycle. The amount of locomotor activity within the first 60 minutes following the gavage was recorded as well as the total number of meters moved for the remaining 10 h of the dark cycle. Within the first hour following oral gavage, older mice treated with MPH trended to have an elevated activity over that of saline-treated mice, regardless of genotype (Figure 4.4C; young mice; two-way ANOVA, genotype p = 0.53, drug p = 0.27 and Figure 4.4D; older mice; two-way ANOVA, genotype p = 0.25, drug p = 0.15). It was also evident that the gavage treatment itself elicited a general increase in locomotor activity because post-gavage activity levels were 5-6X greater than that of pre-gavage activity levels and then decreased after roughly 90 minutes following administration of saline or drug. In tabulating cumulative activity over the 10 h dark cycle, the young Kv1.3-/- mice trended to have greater locomotor activity compared to that of WT mice, and MPH treatment increased activity for both Kv1.3-/- and WT mice, though there were no statistical significant differences (two-way ANOVA, genotype p = 0.151, drug p = 0.122, Figure 4.4E). For older animals, Kv1.3-/- mice also trended towards higher locomotor activity when calculated over the 10 h dark cycle, however, MPH treatment had no effect on activity for either genotype (two-way ANOVA, genotype p = 0.103, drug p = 0.890, Figure 4.4F).
4.3.4 Dopamine measure and expression of down-stream signaling proteins
Because dopaminergic signaling may be involved in modulating anxiety-like behaviors (Sullivan et al., 2014b), we explored whether there were differences in basal dopamine (DA) or MPH treatment effects on dopamine signaling in WT vs. Kv1.3-/- mice. An HPLC analysis of the olfactory bulb of untreated animals demonstrated that Kv1.3-/- mice had significantly higher dopamine levels, while they contained less of the dopamine metabolite DOPAC (Figure 4.5A, B; Student’s t-test, p < 0.05). Western blot analysis of saline- vs. MPH-treated mice demonstrated no significant changes in tyrosine hydroxylase (TH), dopamine receptor 2 (D2DR) protein levels, or extracellular-signal-regulated kinase (ERK) within the olfactory bulb (Figure 4.5C, left) or the
74 prefrontal cortex (Figure 4.5C, right), therefore analyses were pooled to compare immunodensity ratios across Kv1.3-/- vs. WT mice for each protein within (Figure 4.5D) the OB and (Figure 4.5E) the PFC ( not significantly different, Student’s t-test, p > 0.05).
Figure 4.4 Locomotor activity is not significantly altered by MPH treatment. (A-B) Photograph of a custom-made metabolic chamber (A) and individual home cage that is sealed to perform indirect calorimetry as well as positioned on a platform to detect movement in a 50-mm unidirectional movement (B). (C-D) Line graph of the mean locomotor activity following an oral gavage of saline or MPH (arrow) initiated 2 hours (h) into the dark cycle for young (C) and older mice (D). (E-F) Bar graph of the mean locomotor activity for 10 h following oral gavage for young (E) and older mice (F). Same statistical analyses and notations as in Fig. 4.1.
75
Figure 4.5 Dopaminergic signaling differences in WT vs. Kv1.3-/- mice. (A) Bar graph of the HPLC determination of dopamine (DA) and (B) DOPAC in the olfactory bulb. (C-E) Western blot analysis (C) and associated quantitative densitometry (bottom) for dopaminergic signaling proteins expressed in (D) the olfactory bulb (OB) and in (E) the prefrontal cortex (PFC). Mice were gavaged with saline control (S) or MPH (M) 30-minute prior to tissue collection. Western blot analysis of saline- vs. MPH-treated mice demonstrated no significant changes; therefore analyses were pooled to compare immunodensity ratios across Kv1.3-/- vs. WT mice. Pixel immunodensity values were determined for each protein band and then expressed as a ratio (dashed line = no expression difference, or 1.0). WT/S = wild-type with saline, WT/M = wild-type with MPH, Kv/S = Kv1.3-/- with saline, Kv/M = Kv1.3-/- with MPH, TH = tyrosine hydroxylase, D2 = dopamine receptor 2, and ERK = extracellular signal-related kinase. (A, B) Student’s t-test, p < 0.05, (D, E) Mann-Whitney test, p > 0.05, sample size represents the number of mice.
76 4.4 Discussion
By behavioral phenotyping mice with a deletion of the Kv1.3 potassium ion channel we discovered that the “Super-smeller” mice (Fadool et al., 2004) had an increased level of anxiety that was ameliorated by treatment with methylphenidate (MPH). While younger Kv1.3-/- mice trended to exhibit reduced attention to an object-based attention task, older Kv1.3-/- mice performed with a significant deficit, which also was ameliorated by MPH treatment. Because enhanced locomotor activity of Kv1.3-/- mice was unchanged by MPH treatment, this transgenic mouse line might be a favorable model of the inattentive element of the ADHD disorder, but would lack utility for the hyperactivity element of the disorder. While elevated anxiety may present as co-morbid with ADHD, our results suggest that anxiety and olfactory function may not necessarily be inversely related in all instances of change in olfactory perception.
Contrary to our hypothesis, the Kv1.3-/- mice largely exhibited behaviors consistent with an elevated anxiety in two of the three behavioral tests we performed. We initially surmised that the “Super-smeller” phenotype of the Kv1.3-/- mice would predict a reduction in anxiety due to the reported enhancement in stress and anxiety in mouse models of anosmia, such as that of the Cnga2-null lines (Glinka et al., 2012). However, given our findings that the Kv1.3-/- mice with an enhanced olfactory ability for both odor discrimination and threshold (Fadool et al., 2004) have increased anxiety, we must conclude that olfactory function and anxiety have a relationship that is not strictly inversely related. We cannot exclude that targeted deletion of Kv1.3 outside the olfactory system could also evoke a change in emotion that is not linked to olfactory perception. Alternatively, a change in olfactory perception, either enhanced or dampened, may reflect an altered or stressed state to increase anxiety. It seems that aberrant olfaction could be associated with anxiety. In fact, in humans, emotion has been linked with altered olfaction in both directions. It has been shown that a negative emotional state reduces olfactory sensitivity (Pollatos et al., 2007), while enhanced olfactory sensory perception with anxiety has also been reported (Krusemark & Li, 2012).
Consistent with this idea are another genetically-engineered line of mice in which greater than 95% of all sensory neurons express the same odorant receptor, or the M71 monoclonal nose model (Fleischmann et al., 2008). These mice are not anosmic, although they lack detection of
77 their preferred ligand, acetophenone, and they can detect other odorants, despite impairments in associative odor learning tasks and reduced discrimination. Nonetheless monoclonal nose mice have increased stress and heightened anxiety (Glinka et al., 2012). Because olfaction is the rodent’s primary sensory modality and source of major interaction with its external environment, it is not unexpected that a change in any direction of its olfactory function and processing of odor information could modify behavior to produce stress or anxiety.
Prior to our investigation, few animal studies had been performed concerning the relationship between heightened olfactory function and anxiety. In rodents, it has been demonstrated that associative learning (fear – foot shock) can facilitate olfactory nerve synaptic output to glomerular activity to change the neural representation of what become predictive threat odorants (Kass et al., 2013). In human subjects, Krusemark et al., 2013 interestingly were able to drive changes in anxiety levels to the extent that previously neutral or innocuous odorants became unpleasant and took longer to detect. Using fMRI they were able to discern that these now aversive odorants induced augmented responses in higher olfactory cortices and the anterior cingulate cortex (Krusemark et al., 2013). Our mouse studies utilized three different types of anxiety paradigms including MB, LDB, and EPM. MB and LDB tests examine basal level of anxiety in non-threatening environments, whereas the EPM introduces a threatening or actual danger of being 42 cm off the ground. The MB task has been demonstrated to be an effective assessment of anxiety (Borsini et al., 2002) but is also utilized to measure the degree of repetitive compulsivity or obsessive-compulsive disorder (OCD), for example, when transgenic mice are devoid of producing serotonin (Angoa-Perez et al., 2013). Alternatively, supplementing with serotonin-active compounds or a variety of anxiolytics that act to reduce anxiety, depression, or OCD, will oppositely reduce burying or digging behaviors (Borsini et al., 2002; Deacon, 2006). Because Kv1.3-/- mice did not bury significantly greater number of marbles than that of WT mice, they do not appear to be a model for repetitive compulsivity, although the other two paradigms, LDB and EPM, indicated a significant difference in anxiety-like behaviors, and ones that could be ameliorated by MPH treatment. The LDB can predict basal anxiolytic- or anxiogenic-like activity in mice, whereby transitions have been reported to be an index of activity-exploration over that of time spent in each compartment, which might habituate over time, but is a reflection of aversion (Bourin & Hascoet, 2003). In LDB, mice with targeted
78 deletion of Kv1.3 channel spent less time in the light chamber and had a greater latency to move to the light chamber, indicating anxiogenic behaviors. The level of transitions between chambers trended to be less for female Kv1.3-/- mice that perhaps additionally had reduced activity- exploration behaviors. In the EPM, Kv1.3-/- mice not only spent less time in the open arms, they transitioned to them less frequently and their total transitions between compartments were less independent of sex. In comparison to treatments in which insulin is intranasally delivered to phosphorylate its Kv1.3 substrate, which is known to decrease mean open time of the channel (Fadool et al., 2011), mice with reduced Kv1.3 activity but not targeted deletion have anxiolytic- like behaviors or reduced anxiety in terms of more time in the light chamber of the LDB as well as increased time in open arms of the EPM (Marks et al., 2009). Even though posttranslational modification of the channel and targeted deletion both disrupt channel function, phosphorylation of Kv1.3 channel can serve as a signalplex for a variety of protein-protein interactions (Cook & Fadool, 2002; Marks & Fadool, 2007; Colley et al., 2009; Marks et al., 2009) and may not necessarily correlate to a complete absence of the ion channel protein.
While our MB tests were limited to male mice, those of the LDB and EPM did not reflect any sex-related differences in the increased anxiety demonstrated in the Kv1.3-/- mice. We also did not observe many sex differences in the behaviors tested in our WT C57BL/6J strains. Although human studies clearly indicate that females have a greater frequency of emotion disorders (Feingold, 1994), until recently there has been less reporting of sex-related differences in rodent anxiety behaviors (Johnston & File, 1991; Palanza, 2001; An et al., 2011). The reports concerning sex-dependent rodent anxiety behaviors are conflicting. Some report that female rodents are more anxious and others indicate male rodents are more anxious (Donner & Lowry, 2013), whereas our data indicate no sex differences in behavior. There appear to be a variety of factors influencing the design of anxiety behavioral phenotyping including individual/group housing, circadian time point, period of estrous, or dominance stature of the male, to name a few. Our data are contrary, for example, to reports that find that female C57BL/6J mice spend less time in the open arms of an EPM (An et al., 2011) or less time in the light chamber of a LDB apparatus (Palanza, 2001) than that of male mice. Unlike these reports, our study did not restrain the use of females to only diestrous, it did not utilize only males that lost dominance
79 trials, and were performed in a 2-3 h window prior to lights out, for which we have observed increased activity in our colony environment in anticipation of the light change.
ADHD is often treated with stimulant medications, the most prevalent of which being methylphenidate (MPH) (Rothenberger & Rothenberger, 2012; Somkuwar et al., 2013). MPH has been found to reduce hyperactivity and impulsivity in children, but has not been demonstrated to improve attention-related cognitive deficits, including working memory, processing speed, or attention skills (Hellwig-Brida et al., 2011). Because anxiety induced by stimulant treatment has been noted in clinical populations or by individuals seeking purported cognitive enhancement under anxiety-saturated conditions (i.e. projects/exams) but without ADHD, studies have begun to examine the effect of MPH on anxiety in control vs. disorder populations. In our investigation of the ability for MPH to mitigate the anxiety behaviors noted in the Kv1.3-/- mice, the time spent in the light chamber of the LDB was significantly reduced in Kv1.3-/- mice and increased compared with that of WT animals following MPH administration. The Kv1.3-/- mice had a delayed latency to enter the light chamber that was 4x as long as that exhibited by WT mice – which again was completely ameliorated following MPH administration to the short 10s latency observed for that of WT mice. MPH had no effect on anxiety in the WT cohort. Interestingly, in comparing our data to that of a human subjects study, Segev et al., 2016 also found that MPH was ineffective in reducing anxiety across a control group or elicited mild enhancement in anxiety, but significantly decreased anxiety in individuals with subclinical or state-anxiety (Segev et al., 2016). Golubchik et al., 2017 similarly report changes in anxiety for Asperger/and ADHD co-morbid patients as opposed to unafflicted individuals (Golubchik et al., 2017). Complementary to these types of studies, data by Coughlin et al., 2015 suggest that improved anxiety symptoms with MPH in ADHD-affected individuals, is a secondary result of targeting ADHD symptoms (Coughlin et al., 2015).
The object-based attention test employed for this study was a relatively new paradigm for testing animal behaviors (Alkam et al., 2011; Ishisaka et al., 2012), but provided an advantage in terms of the absence of training required to perform the task and the reduced amount of time involved in completing the task. Although our object-based attention test had the limitation that it could not fully examine ADHD characteristics by utilizing typical multiple fixed- interval/extinction schedules of reinforcement (FI/Ext schedules) to allow sustained 80 attentiveness, impulsivity, or hyperactivity to be measured (Sagvolden et al., 2005), it could potentially be used for large-scale preclinical screening of drug candidates, for example.
While young Kv1.3-/- mice trended to have a reduced recognition index compared to that of WT mice, older mice exhibited a significantly reduced index that was restored following MPH treatment. It is likely that the attention deficit present in the Kv1.3-/- mice is not strongly age- dependent because the reduced attention deficit observed in the young animals is similarly restored following MPH treatment and may be the result of lesser sample size. The fact that MPH treatment could ameliorate a reduced recognition index in both age groups implicates that Kv1.3-/- mice are suitable models of the inattentive element of the ADHD behavioral phenotype. The amount of MPH presented to each mouse was equivalent to the clinical dose given to human subjects diagnosed with ADHD (Balcioglu et al., 2009); however, only a single dose was utilized for this study, while some studies have included several dosages for comparison (Balcioglu et al., 2009; Zhu et al., 2012). A stronger effect on the attention levels of either Kv1.3-/- or WT mice may have been observed with the use of a higher dose or with the use of repeated or chronic administration of MPH.
In addition to attention deficits, another core symptom of ADHD is hyperactivity. Our use of a metabolic chamber to measure locomotor activity was an indirect method to assess hyperactivity, nonetheless we found that the Kv1.3-/- mice did not have significantly elevated, sustained hyperactivity levels. Previous studies involving metabolic chamber testing have indicated that Kv1.3-/- mice had significantly greater locomotor activity than WT mice (Fadool et al., 2004); whereas here we noted the same trend although it did not reach statistical significance. Additionally, treating young mice with MPH resulted in increased locomotor activity, regardless of genotype. Because MPH is a stimulant, its administration to normally functioning individuals typically results in increased activity levels while its administration to individuals with ADHD typically results in reduced activity. Both young WT and Kv1.3-/- mice exhibited a trend toward greater activity with MPH treatment, which is a typical response to stimulant treatment instead of an ADHD-type response to treatment. Whereas possibly due to age factor, older mice lacked locomotor response to MPH treatment. Overall, these results indicate that Kv1.3-/- mice are not a suitable model of the hyperactivity component of ADHD.
81 Stimulants exert their effectiveness by acting on both the dopaminergic (DA) and norepinephrine systems in the brain (Biederman & Faraone, 2005; Hellwig-Brida et al., 2011). MPH, in particular, is a dopamine transporter (DAT) inhibitor, thus resulting in an increase in extracellular DA concentrations through the release of DA from intracellular storage (Carey et al., 1998; Biederman & Faraone, 2005). While we did not explore direct MPH induction of DA, others have found it to increase DA release from the prefrontal cortex, nucleus acumens, and caudate-putamen (Carey et al., 1998) and also found that it increases frontal cortex and striatal activation (Hellwig-Brida et al., 2011). Stress can increase DA release in the prefrontal cortex (Deutch & Roth, 1990; Finlay et al., 1995) and elevated D2DR availability in the orbitofrontal cortex has been linked in humans with social anxiety disorder symptoms (Plaven-Sigray et al., 2017).
We found that Kv1.3-/- mice have an elevated, basal level of DA in the OB and a reduction in one of its metabolites, 3,4 dihydroxyphenylacetic acid (DOPAC). While we don’t know its comparative level in the prefrontal cortex, the level of TH, ERK, and D2DR were all unchanged in the prefrontal cortex, suggesting that dopaminergic signaling in this region is likely not responsible for anxiety-like behaviors of the Kv1.3-/- mice. While vesicular release of DA is typically cleared by DAT in most brain regions, the OB predominantly uses catechol-O-methyl- transferase (COMT) over that of DAT (el-Etri et al., 1992; Cockerham et al., 2016), so it is not inconceivable that MPH would have no real targeted effect in the OB. The fact that DA is elevated in the OB of Kv1.3-/- mice, however, might suggest a differential degree of dopaminergic modulation in the Kv1.3-/- mice, leading to a change in olfactory sensitivity. For example, olfactory gain control driven by local juxtaglomerular interneurons via traditional lateral inhibition is regulated by co-release of DA and GABA from deep short axon cells to change firing frequency of the major output neurons, namely mitral/tufted cells (Vaaga et al., 2017).
Face validity of an animal model requires that the animal be similar to the human disease in terms of etiology and also it must mimic the behavioral characteristics of the disorder (Davids et al., 2003; Sagvolden et al., 2005). While Kv1.3-/- mice are suitable models of attention- deficits, deletion of the Kv1.3 channel in humans has not, as of yet, been linked to ADHD-type behaviors, indicating the etiology of Kv1.3-/- inattentiveness may not mimic the etiology of such 82 symptoms in humans. The Kv1.3-/- mice thus may be useful in terms of the attention-deficit aspect of the disorder to design experiments exploring attentional problems. Because ADHD is characterized by a cluster of behavioral symptoms, the Kv1.3-/- mice cannot be considered models of the disorder until they are proven to exhibit attention deficits, hyperactivity, and impulsivity. Some researchers even consider impulsiveness to be the most important criteria for ADHD (Taylor, 1998; Sagvolden et al., 2005); however, this behavioral characteristic was not examined in the current study beyond that of the MB test. Moreover, inattention and hyperactivity are elements of many other mental disorders; therefore the Kv1.3-/- mice should only be considered as a model of inattentive subtype of ADHD.
83 CHAPTER 5
SUMMARY
Neuromodulation plays an important role in determining how we responding to external stimuli. The nervous system is like the hardware of a computer system. Neuromodulation is like the software that keeps the computer system functioning properly. The main neuromodulation in the mammalian brain comes from diffuse modulatory systems, including the cholinergic, noradrenergic, and serotonergic systems. The cholinergic system principally originates from the basal forebrain area, noradrenergic axons arise from the locus coeruleus, and serotonergic fibers originate from the raphe nuclei in the brainstem. It is believed that almost every part of the brain receives some serotonergic input. Here in Chapter 2, I investigated serotonergic modulation of mitral cells in the MOB and AOB. I found that serotonin was largely excitatory for MOB mitral cells while predominantly inhibitory for AOB mitral cells. The distinct serotonergic modulation of MCs between the MOB and AOB could provide a molecular basis for differential chemosensory behaviors driven by the raphe nuclei into these parallel systems. I also found the cholinergic modulation of GLP-1 neurons in Chapter 3. Another resource of neuromodulation comes from peptides. Here, I found GLP-1 neurons were modulated by CCK. The basic unit of neuromodulation usually comes down to ion channels. By modification of ion channel function and expression neuromodulators can exert nonlinear and complex effects on properties of a neuron.
Each neuron has a different combination of ion channel expression and compartmentalization, which immensely increases the information processing ability of our nervous system. Ion channels can be divided into multiple groups based on different category criteria. For example, based on gating mechanisms ion channels can be divided into voltage- gated channels, ligand-gated channels, and other gating such as light-gated channels, mechanosensitive ion channels, cyclic nucleotide-gated channels, temperature-gated channels, while based on ion selectivity they can be classified as sodium, potassium, chloride, calcium channels, protons channels, non-selective cation channels and so on. Diversity of ion channels also extends into the genome. In the genome there is a large portion of genes encoding ion channel proteins. For example, there are over 180 ion channel genes in the genome of the Caenorhabditis elegans (Bargmann, 1998). Another level of complexity comes from the 84 alternative splicing of RNA expressing different isoforms of ion channel subunits, and different combinations of multiple units. Why do we have such diversity of ion channels? Imagine we only had two types of ion channels: one, a positive ion channel that excites neurons; the other, a negative ion channel that inhibits neurons. With this kind of architecture we can only have two kinds of responses: excitation and inhibition. We would not be able to sense different light/color conditions, different sound intensities, different temperatures etc. So one important reason why we have such diversity of ion channels is to meet the information processing capacity we need to respond to a variety of external stimuli. Depending on which group of neurons and which brain region it expressing, the same type of ion channel can contribute to multiple functions. This can be seen in Chapter 4 of my dissertation. Here in Chapter 4 of my dissertation I further expanded the possible functions of voltage-gated potassium channel Kv1.3 by showing that Kv1.3 knockout mice have heightened anxiety levels and attention deficits. It had been previously shown that loss function of Kv1.3 in mice resulted in heightened olfactory ability indicated by decreased odor detection threshold and improved odor discrimination ability (Fadool et al., 2004), changed metabolism and exhibited resistance to high-fat induced obesity (Xu et al., 2003; Tucker et al., 2012), and increased locomotion activity (Fadool et al., 2004). Further researches are needed to investigate through what mechanisms Kv1.3 contributes to these functions.
Bioelectricity plays an essential role in human physiology. Electricity in cardiovascular system and nervous system is critical for maintaining normal physiology and adjusting physiological functions. Since the discovery of bioelectricity more and more researches have been conducted to study its mechanisms and functional significance. A milestone in bioelectricity research is the discovery of ion channels. The research on ion channel functions has reached a new level due to the development of experimental techniques such as gene technology, X-ray crystallography, and patch-clamp electrophysiology. Their important functions in numerous behaviors (Jentsch et al., 2004) and their involvements in many human diseases (Jentsch et al., 2004; Ashcroft, 2006) make ion channels important targets to investigate. For future work, identifying ion channel targets of the neuromodulators found in my dissertation should be a priority. For example, what are the ion channel targets of serotonergic modulation for the excitation of mitral cells in the MOB and the inhibition of mitral cells in the AOB? Through modulating which ion channels ACh and CCK exert their effects on the activity
85 of GLP-1 neurons in the OB? Through ion channels, neuromodulation could change neuronal properties and thereby modulating neural circuits to produce different behavioral outputs depending upon changing external stimuli. It would be interesting to see whether the neuromodulations found here could alter animal behavior. For example, one could deliver serotonergic drugs specifically into the MOB or AOB, and examine their effects on animals behavior. For the serotonergic modulation in the MOB, it is possible to see its effects on general olfactory function such odor threshold detection. The serotonergic modulation in the AOB is more likely to affect some innate behaviors such as aggression. When we can modulate the activity of GLP-1 neurons through in vivo optogenetics or chemogenetics method, animals’ olfactory response and feeding behavior should be examined. Neuromodulation enables neural circuits with great flexibility. However, dysfunctional neuromodulations could cause many neurological problems such as chronic pain, Parkinson’s disease (Kumar & Rizvi, 2014; Da et al., 2015). On the other hand, neuromodulation has been used as a tool to treat various neurological diseases (McDonald, 2016; Lewis et al., 2016). I predict that neuromodulation will be at the forefront of neuroscience research in the future.
86 APPENDIX A
KV1.3 AND MITOCHONDRIA
A.1 Introduction
There are multifarious roles for potassium channels beyond drivers of the resting potential (Kaczmarek, 2006), although classically one envisions potassium channels as dampeners of excitability through timing of the interspike interval and shape of the action potential (AP) (Jan & Jan, 1994; Yellen, 2002). Among the non-conductive functions of potassium channels lies their ability to detect, be regulated, or be modulated by energy substrates or metabolites, namely glucose, ATP, or NADPH (Pan et al., 2011; Tucker et al., 2013; Tinker et al., 2014). This original research article will present a review of metabolic sensing by brain region outside the traditional endocrine axis controlling food intake and energy balance—the olfactory bulb (OB). We highlight the role of a particular potassium channel, Kv1.3, which is highly expressed in the OB and may serve as the molecular sensor of metabolism. We hypothesize that the olfactory system has a dual function, to transduce external chemical signals, or odorants, into an internal representation, and simultaneously to detect internal chemistry, namely metabolically important molecules, such as glucose and insulin (Fadool et al., 2000; Fadool et al., 2011; Tucker et al., 2013). Thus, the OB is a detector of metabolic state; the biophysical properties of Kv1.3 are modulated by energy availability and the disruption of energy homeostasis can modify olfactory sensory coding (Palouzier-Paulignan et al., 2012). Such metabolic sensing could change food intake given the intimate relationship of olfactory perception to satiety and food choice (Aime et al., 2007; Tong et al., 2011; Badonnel et al., 2014; Soria-Gomez et al., 2014a; Lacroix et al., 2015).
While Kv1.3 channels do not exist in isolation in the plasma membrane – they are part of a well-characterized scaffold of proteins and adaptor proteins that act to interface signaling
Appendix A are excerpts from the previously published article “Mitochondrial ultrastructure and glucose signaling pathways attributed to the Kv1.3 ion channel”. Frontiers in Physiology 7:178. doi: 10.3389/fphys.2016.00178. eCollection 2016 by C.P. Kovach, D. Al Koborssy, Z. Huang, B.M. Chelette, J.M. Fadool, D.A. Fadool. ZH contributed to graphing and analysis of Figure A.1 and text content on Kv1.3 and mitochondria.
87 cascades with the channel (Cook & Fadool, 2002; Marks & Fadool, 2007; Colley et al., 2009) – the channels are not solely restricted to this organelle. The channel is additionally highly expressed in the inner mitochondrial membrane (IMM) of several cell types including lymphocytes (Szabo et al., 2005), cancer cells (Leanza et al., 2012), and hippocampal neurons (Bednarczyk et al., 2010). It is for this reason, given the metabolic and olfactory phenotypes of Kv1.3-/- mice, that we undertook an ultrastructural analysis of mitochondria in the OB. The IMM is home to many types of ion channels and exchangers for a variety of cations and anions (Bernardi, 1999), which maintain a negative membrane potential of the organelle. The tightly controlled IMM permeability is critical for efficient ATP production and a dysregulation of IMM permeability often leads to cell death (Kim et al., 2003). It has been proposed that potassium ion channels play an important role in the control of the integrity of the IMM (Szewczyk et al., 2009) whereby substantial evidence has shown cardio- and neuro-protective effects of targeting mitochondrial potassium channels (Szewczyk & Marban, 1999; Busija et al., 2004; O'Rourke, 2004). The mechanism of these b effects has been linked to the mitochondrial production of reactive oxygen species or ROS (Malinska et al., 2010). Interestingly, it has been shown that oxygen/glucose deprivation of microglia results in suppression of Kv1.3 currents in a tyrosine phosphorylation signaling cascade, which can be significantly attenuated by ROS scavengers (Cayabyab et al., 2000). It is possible that mitochondrial Kv1.3 functions could go beyond cryoprotection and involve ROS-dependent energy metabolism. ROS signaling is usually considered to be detrimental and damage-promoting, however, ROS can act as signaling molecules regulating organismal homeostasis, stress responsiveness, health, and longevity (Shadel & Horvath, 2015). ROS production is linked to the central control of whole body metabolism (Shadel & Horvath, 2015). In fact, there is considerable evidence showing that ROS can enhance insulin sensitivity by oxidizing multiple signaling molecules (Mahadev et al., 2001; Mahadev et al., 2004; Loh et al., 2009; Cheng et al., 2010), while long-term excessive ROS may cause insulin resistance (Szendroedi et al., 2012).
Metabolic imbalance attributed to diet-induced obesity (DIO) has been shown to disrupt the structure and function of the olfactory system. When mice were challenged with high-fat or high-fat, high-carbohydrate diets, the excess energy imbalance resulted in marked loss of olfactory sensory neurons (OSNs), loss of axonal projections to defined glomerular targets,
88 reduced electro-olfactogram amplitude, irregular AP firing frequency in mitral cells of the OB, reduced olfactory discrimination ability, slowed reward-reinforced behaviors, and disrupted reversal learning (Fadool et al., 2011; Thiebaud et al., 2014). Insulin-induced Kv1.3 phosphorylation in the OB (Fadool & Levitan, 1998; Fadool et al., 2000) was lost in DIO mice (Marks et al., 2009) and slices from these mice exhibited loss of insulin modulation of mitral cell excitability, exemplifying a degree of insulin resistance for mitral cell function in the obese state (Fadool et al., 2011). Obesity-resistant Kv1.3-/- mice exhibited similar loss of OSNs as that of WT mice while challenged with high-fat, high-carbohydrate diet, but not when fed a high-fat diet. The Kv1.3-/- mice showed a concomitant loss of olfactory discrimination and slowed reward-reinforced behaviors in only the high-fat, high-carbohydrate diet. Kv1.3-/- mice oddly showed improved olfactory discrimination with the high-fat diet and showed a reversal learning capacity that was slowed regardless of diet.
Herein, in an effort to further elucidate the mechanism of the metabolic phenotype of Kv1.3-/- mice, we report the presence of GLUT4 in the same neurolamina as the Kv1.3 channel and explore the ultrastructure of mitochondria in the Kv1.3-/- mice.
A.2 Results and Discussion
Elevated plasma glucose after a meal activates mitochondrial oxidative phosphorylation in pancreatic cells to increase ATP release and insulin secretion. A chronic rise in glucose such as in diabetic or obese patients has caused mitochondrial atrophy, which suggests an important connection between mitochondria and metabolic imbalance (Gerbitz et al., 1996). Several potassium channels contribute to mitochondrial function including Kv1.3 (Bednarczyk, 2009). We decided to investigate the change in mitochondrial morphology in the OB of WT and Kv1.3- /- mice that have been challenged with a moderately high-fat diet (MHF; Research Diets D12266B; 16.8% kcal protein, 51.4% kcal carbohydrate, and 31.8% kcal fat; New Brunswick, NJ, USA) vs. control diet (CF; Purina 5001 Rodent Chow; 28.05% kcal protein, 59.81% kcal carbohydrate, and 13.5% kcal fat; Richmond, VA, USA).
89 Electron micrographs showing the abundance and size of mitochondria examined within the cell bodies of mitral cells are found in Figure A.1 A, B, respectively (low and higher magnification). The number, cross-sectional area, and circularity index of mitochondria from 40 fields of view were quantified from three mice in each of the four conditions (Figure A.1 C-E). For control fed mice, there was no significant change in the number of mitochondria across the genotypes [number: one-way ANOVA, F (3, 161) = 4.925, p = 0.0027, Student Newman Keuls’s (snk) post-hoc test CF +/+ vs. CF -/-, p > 0.05), however the cross-sectional area was larger and circularity index was less in the WT mice compared with that of the Kv1.3-/- mice [area: one- way ANOVA, F (3, 305) = 51.36, p < 0.0001, snk post-hoc test CF +/+ vs. CF -/- significantly different, p < 0.0001; circularity index: one-way ANOVA, F (3, 302) = 8.178, p < 0.0001, snk post-hoc test CF +/+ vs. CF -/- significantly different, p < 0.05). When WT mice were challenged with a MHF diet, the mitochondrial cross-sectional area but not the circularity index became enlarged [area: one-way ANOVA, F (3, 305) = 51.36, p < 0.0001, snk post-hoc test CF +/+ vs. MHF +/+ significantly different, p < 0.0001; circularity index: one-way ANOVA, F (3, 302) = 8.178, snk post-hoc test CF +/+ vs. MHF +/+, p > 0.05) and the abundance of mitochondria decreased, [number: one-way ANOVA, F (3, 161) = 4.925, p = 0.0027, snk post- hoc test CF +/+ vs. MHF +/+ significantly different, p < 0.05). In contrast, a MHF-diet challenge did not affect mitochondria number, area, or circularity in the Kv1.3-/- mice (one-way ANOVA, snk post-hoc test, p > 0.05). These data provide evidence that diet high in fat changes the morphology of mitochondria in the OB, and that gene-targeted deletion of Kv1.3 precludes these effects.
Because Kv1.3-/- mice have an increased locomotor activity and metabolism, a change in mitochondrial shape might be anticipated. Our ultrastructural data demonstrate that control fed Kv1.3-/- mice have an altered circularity shape compared with similarly fed WT mice. Additionally, the cross-sectional area of the mitochondria is smaller in the Kv1.3-/- regardless of dietary treatment. Neuronal mitochondria typically have cristae that form a network of anastomosing tubes and the number of cristae is correlated with the level of aerobic activity and associated ATP production (Lehninger, 1982). While our analysis did not quantify this sub- organelle structure, qualitatively the cristae from the WT mice appeared to be more longitudinally arranged. During high rates of metabolism, the mitochondrial membranes can become condensed due to structural changes of the IMM and matrix, as opposed to orthodox or 90
Figure A.1 Kv1.3-/- mice have smaller mitochondria in the mitral cell layer of the OB, which do not exhibit an increase in volume when challenged with moderately-high fat diet (MHF). Photomicrographs acquired from the mitral cell layer of the OB of wildtype (+/+) and Kv1.3-null mice (- /-) maintained on MHF vs. CF for 4 months. (A) Low and (B) higher magnification. Bar graph or box blot representing (C) mean number, (D) cross-sectional area, and (E) circularity index of mitochondria collected across 40 fields of view for 3 mice. Data represent mean ± s.d. for the bar graph, or mean (line), 25/75% quartile (box) and 5/95% range (whiskers) for the box plot. Significantly different, one-way ANOVA, Student Newman Keuls’s (snk) post-hoc test, ****p < 0.0001; ***p < 0.001, **p < 0.01; *p < 0.05.
91 ‘idling’ mitochondria that are not actively respiring (Lehninger, 1982). This type of shrinking does not appear to be the cause of smaller mitochondria in the Kv1.3-/- because the out mitochondria membrane (OMM) is observed closely juxtaposed to the IMM and cristae. Future functional studying of mitochondria from Kv1.3-/- mice is needed to test the idea that the more condensed mitochondrial volume might contribute to increased total energy expenditure (TEE). Interestingly in the rat OB, the respiratory control ratio that measures mitochondrial activity is 2x higher that in the hypothalamus (Benani et al., 2009) and is in accordance with the high energy demand of the glomeruli (Nawroth et al., 2007). What is also of interest for mitochondria in the OB is the high expression of GLUT4 in this region and the total energy budget for olfactory discrimination. Odor-evoked oxidative metabolism of OB synaptic transmission is energetically demanding and is tightly correlated to capillary density (Lecoq et al., 2009).
The challenge of a MHF-diet did not decrease the number or increase cross-sectional area of mitochondria in the Kv1.3-/- mice as it did in the WT mice. This is very intriguing given that mitochondria are highly dynamic in morphology and abundance. In liver, short-term challenge (21 day) with a high-fat diet causes a decrease in proteins of the electron transport chain and transporters/ exchangers of the IMM, but does not cause a change in mitochondrial volume (Kahle et al., 2015). The influx of potassium across the IMM (Figure A.2) through both mKv1.3 and mKATP could cause an increase in volume changes of the mitochondria if not tightly counterbalanced by the H+/K+ antiport exchanger (Garlid, 1996). One role of the H+/K+ antiport exchanger is to counterbalance the influx of K+ that allows the high membrane gradient required for oxidative phosphorylation and thereby acts to provide volume homeostasis (Garlid & Paucek, 2003). In the absence of Kv1.3, there may be less K+ influx, leading to smaller mitochondria. In the condition of long-term (4 month) MHF-diet and precipitated DIO, the WT mice could have dysfunction in IMM ion transport resulting in increased volume or swelling. Such ionic imbalance could lead to unhealthy mitochondria, which might undergo mitophagy and lead to a loss in mitochondrial density or abundance such as we observed. The subsequent lack of volume change or loss of number in the fat-fed Kv1.3-/- mice could be either attributed to less initial K+ influx or changed fatty-acid metabolism that is also linked to organelle volume (Garlid, 1996) and would be anticipated to be reduced in the thin, obesity resistant mice. Whether mitochondrial dysfunction is linked to glucose intolerance and insulin resistance is a topic of intensive research
92 and current debate (see review, Montgomery & Turner, 2015), but certainly a greater number of mitochondria permit greater ATP production and a reduced number of mitochondria are found during periods of quiescence. Typical to what we observed in the DIO wildtype mice, a reduced number of mitochondria was associated with larger individual organelles. Although our ultrastructural data do not allow us to discern if the larger mitochondria had impaired function, by deduction, the fatty diet either decreased mitochondrial biogenesis or increased mitophagy to yield a decreased mitochondrial density in the obese mice. The fact that loss of Kv1.3 channel alters mitochondria shape and prevents increased volume of mitochondria when challenged with MHF suggests an
Figure A.2 Schematic diagram showing cell signaling interactions of plasma membrane Kv1.3 (Kv1.3) and potential interplay with mitochondrial Kv1.3 (mKv1.3). Glycogen-like peptide (GLP-1) and insulin are two signaling hormones that block Kv1.3 current. The channel (red) is known to be a substrate for insulin receptor (IR) kinase (blue) on the N- and C-terminal aspects of the channel protein (Y111-113, Y137, Y479). Insulin-induced phosphorylation (P) of Kv1.3 (blue line) decreases Kv1.3 current amplitude by decreasing Propen of the channel. GLUT4 is typically translocated to the membrane upon insulin activation (blue dashed line) but upon block of Kv1.3 conductance, can also be translocated (red dashed line). Metabolism of glucose establishes the H+ gradient and the production of ATP via the electron transport chain (ETC). Maintenance of the ionic environment is dependent upon influx of K+ through mKv1.3 and mKATP and the balance provided by efflux via the K+/H+ exchanger. The ATP energy source could be used for the GLP-1R triggered conversion of ATP to cAMP through adenylase cyclase to increase potential PKA activity (?). Metabolic factors that decrease Kv1.3 ion channel activity increase the AP firing frequency in mitral cells that is thought to provide odor quality coding of olfactory information. OMM, outer mitochondria membrane; IMM, inner mitochondria membrane; IMS, inter membrane space.
93 alteration of normal dynamics of the organelle and associated fission and fusion proteins. Similar effects of high-fat diet on mitochondrial function have been observed in the central nervous system (Petrov et al., 2015). For example, Parton et al. (2007) attributed loss of glucose sensing by pro-opiomelanocortin (POMC) neurons of the hypothalamus in DIO mice to the mitochondrial uncoupling protein 2 (UCP2). Genetic deletion or pharmacological inhibition of UCP2 was able to restore glucose sensing in the obese mice, underscoring the role of mitochondrial dysfunction and altered ATP production in DIO.
One of the earliest changes in the development of insulin resistance attributed to DIO is ectopic lipid accumulation (Turner et al., 2013). In response to excess lipid availability in the wildtype DIO mice, increase reactive oxygen species (ROS) such as superoxides, hydroxyl radicals, and hydrogen peroxide could have been elevated (i.e. Paglialunga et al., 2015). Interestingly, Kv1.3 can be regulated by these types of second messengers. Phosphorylation of Kv1.3 on four serine residues by PKA and PKC is known to increase Kv1.3 activity to maintain a negative membrane potential (Chung & Schlichter, 1997a; Chung & Schlichter, 1997b). As ATP is depleted below basal intracellular levels, the channel exhibits reduced peak current amplitude and a shift in voltage dependence. Application of ROS scavengers alleviates Kv1.3 phosphorylation to decrease the membrane potential (Cayabyab et al., 2000).
Plasma membrane bound Kv1.3 and mitochondrial Kv1.3 could influence or detect metabolic state at the level of the OB through channel neuromodulation and down-stream signaling cascades that could modify excitability. Insulin and the incretin hormone, GLP-1, can phosphorylate Kv1.3 at the plasma membrane, decrease Kv1.3 current and upregulate GLUT4 translocation to the membrane to facilitate glucose metabolism. In turn, the activity of mitochondrial Kv1.3 is linked to ROS and ATP production that regulate channel phosphorylation and conductance. Future targeted regulation of Kv1.3 in the OB could reveal the ability of this brain region to detect and regulate metabolic state by changing membrane excitability based on nutritional needs. The extent by which the mitral cell plasma and mitochondrial membrane activity interplays in detecting the chemistry of metabolism and olfactory coding utilizing Kv1.3 is a novel future trajectory in understanding brain energy sensing and dysfunction following obesity.
94 APPENDIX B
TESTING QUANTUM DOT-CONJUGATED DRUG ON BRAIN SLICE
Appendix B is a figure from previously published article “Margatoxin-bound quantum dots as a novel inhibitor of the voltage-gated ion channel Kv1.3”. J Neurochem. 140(3):404-420. doi: 10.1111/jnc.13891. by A.B. Schwartz, A. Kapur, W. Wang, Z. Huang, E. Fardone, G. Palui, H. Mattoussi, D.A. Fadool, 2017. The idea is to conjugate drugs to fluorescent quantum dots. So the drugs can be traced by fluorescence. I tested the efficacy of margatoxin-bound quantum dots on brain slice.
Figure B.1 Mitral cell (MC) action potential firing frequency in response to margatoxin- conjugated quantum dots (QD-MgTx). (a) Representative action potentials (APs) recorded in the whole-cell configuration in a mouse olfactory bulb (OB) slice preparation. The cell was current clamped and APs were elicited by small current injection of 25 pA. Vm = −65 mV. Spike firing frequency was first recorded under bath application of control artificial cerebral spinal fluid solution (ACSF Control), followed by unconjugated quantum dots (QD Control), and then margatoxin-conjugated quantum dots (QD-MgTx). (b) Photomicrograph of OB slice showing pipette position in the mitral cell neurolamina (MCL). EPL, external plexiform layer; GCL, granule cell layer. Scale bar = 100 μm. (c) Bar graph of the normalized firing frequency for a population of MCs. One-way repeated measures ANOVA, Bonferroni's post hoc test, **p ≤ 0.001. Sample size = number of cell recordings. 95 APPENDIX C
THE EFFECTS OF SHORT-TERM PRENATAL HIGH-FAT DIET ON OFFSPRINGS AND DAMS THEMSELVES
In the first experiment I wanted to examine what would happen to offspring if we put dams on a high-fat diet for the duration of pregnancy. The wild-type dam 877F was maintained on a standard chow diet (28.05% kcal protein, 59.81% kcal carbohydrate, and 13.5% kcal fat) as a control. The wild-type dams 879F and 878F were switched from standard chow diet to a high- fat diet (20% kcal protein, 20% kcal carbohydrate, and 60% kcal fat), and at the same day each of them was crossed with a male. Dam 879F gave two births. However, there were no offspring that survived from these two births. Dam 878F was put on high-fat diet on 1-15-2013, and gave birth to 7 pups on 2-6-2013. Six of the pups died the next day. The remaining one died the day after. Dam 878F gave a second birth to 8 pups on 3-3-2013. One of the pups died on the day of birth. Seven remaining pups were surrogated to dam 877F and all survived (three males and four females). These pups were weaned on 4-1-2013 and tested in different behavioral paradigms at 2-month of age. The 4 male pups of dam 877F from another birth were also tested in the same behavioral paradigms at 2-month of age as control. The results were shown in Figure C.1.
Previous research has shown that maternal high-fat during pregnancy and lactation results in metabolic syndrome of the offspring, and increased anxiety in adulthood (Sullivan et al., 2014a). Here it seems that high-fat diet during pregnancy did not affect the offspring’s anxiety levels and memory function, at least the ones I tested (Figure C.1). The reasons for this discrepancy may be because the maternal diet during the lactation period could be crucial, because significant maturation occurs early in life. In my experiments, because of the poor pup survival of these two dams maintained on high-fat diet, the pups were surrogated to the dam maintained on control diet. So these pups were not exposed to high-fat diet during the lactation period. However, it seems that high-fat diet had detrimental effects on maternal behaviors indicated by the poor survival of offspring of the dams maintained on high-fat diet. So I set up second experiment to test whether high-fat diet had detrimental effects on maternal behavior. The experimental design was the same as the first experiment. The second experiment included more female dams, and also another genotype Kv1.3 knock-out mouse besides WT mouse.
96
Figure C.1 Behavioral tests of the offspring of dams maintained on control- and high-fat diet. Four male pups from the dam maintained on control diet, and three male pups and four females pups from the dam maintained on high-fat diet during pregnancy were tested in (A) light/dark box, (B) elevated plus maze, and (C, D) novel object recognition test. CF = control diet, HF = high-fat diet. (A), (B) one-way ANOVA, no significant differences were found. (C), (D) paired t-test for each pups group, *p < 0.05.
As shown in Table C.1, dams maintained on high-fat diet showed normal maternal behaviors indicated by the survival of most of their pups. I also tested pups retrieval behavior of dams. In brief, I first removed the dam from the cage and placed three pups to three corners of the cage. Then I introduced the dam back to the cage and observed whether the dam retrieved the pups back to the nest. If the dam does retrieve the pups, how long does it take for the dam to retrieve three pups? Both WT and Kv1.3-/- dams maintained on high-fat diet showed normal pups retrieval behavior. We tested two WT dams maintained on high-fat diet (32 s and 110 s), 97 two WT dams maintained on control diet (319 s and 310 s), two Kv1.3-/- dams maintained on high-fat diet (68 s and 59 s), and two Kv1.3-/- dams maintained on control diet (92 s and 135 s). Based upon the above data I concluded that short-term (about 1 month) high-fat diet did not significantly affect maternal behavior of mice. It’s worth noting that short-term high-fat diet does not cause significant weight gain in female mice. If female mice were put on high-fat for a longer time period, it may cause detrimental effects on their maternal behavior.
Table C.1 Litter statistics comparing dams maintained on control- and high-fat diets
Group Diet Dams # Pups # Survived Pups
WT High-fat diet N=5 4, 8, 7, 9, 4 3, 8, 7, 9, 0
Control diet N=5 8, 6, 6, 7, 9 8, 4, 6, 5, 9
Kv1.3-/- High-fat diet N=4 7, 7, 8, 8 7, 7, 8, 8
Control diet N=4 7, 2, 8, 6 7, 2, 8, 5
98 APPENDIX D
ACUC APPROVAL LETTER
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126 BIOGRAPHICAL SKETCH
ZHENBO HUANG
Education Ph.D. Candidate, Neuroscience (08/2012 – Present) Department of Biological Science, Florida State University GPA = 3.99, GRE = 580 (82%) in Verbal and 800 (94%) in Quantitative M.Sc., Biochemistry and Molecular Biology (09/2007 - 07/2011) Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences B.S., Biological Sciences (09/2003 - 06/2007) Hunan University of Arts and Science
Awards and Honors Hunan University of Arts and Science Scholarship (2003 – 2007) Hunan University of Arts and Science Outstanding Thesis Award (06/2007) Association for Chemoreception Sciences (AChemS) Presenter Housing Award (04/2014) Association for Chemoreception Sciences (AChemS) Presenter Travel Award (04/2015) International Symposium on Olfaction and Taste (ISOT) Young Investigator Award ( 06/2016) Florida State University Neuroscience Fellowship (08/2016) Bryan Robinson Neuroscience Endowment award (06/2017)
Publications Huang ZB, Thiebaud N, Fadool DA (2016). Differential setrotonergic modulation across the main and accessory olfactory bulb. J Physiol. doi: 10.1113/JP273945.
Schwartz AB, Kapur A, Wang W, Huang ZB, Fardone E, Palui G, Mattoussi H, Fadool DA (2016). Margatoxin-bound quantum dots as a novel inhibitor of the voltage-gated ion channel Kv1.3. J Neurochem. doi: 10.1111/jnc.13891.
Kovach CP, Koborssy DA*, Huang ZB*, Chelette B, Fadool JM, Fadool DA (2016). Mitochondrial ultrastructure and glucose signaling pathways attributed to the Kv1.3 ion channel. Front Physiol, 7:178. (*equally contributed)
Niu SN, Wang H, Huang ZB, Rao XR, Cai XS, Liang T, Xu J, Xu X, & Sheng GQ (2012). Expression changes of hypothalamic Ahi1 in mice brain: implication in sensing insulin signaling. Mol Biol Rep 39, 9697-9705.
127 Wang H*, Huang ZB*, Niu SN, Rao XR, Xu J, Kong H, Yang JZ, Yang C, Wu DH, Li SH, Li XJ, Sheng GQ. (2012) Hypothalamic Ahi1 mediates feeding behavior through interaction with 5-HT2C receptor. J Biol Chem, 287(3):2237- 2246. (*equally contributed)
Niu SN*, Huang ZB*,Wang H, Rao XR, Kong H, Xu J, Li XJ, Yang C, Sheng GQ. (2011) Brainstem Hap1-Ahi1 is involved in insulin-mediated feeding control. FEBS Lett, 585(1):85-91. (*equally contributed)
Huang ZB, Wang H, Rao XR, Zhong GF, Hu WH, Sheng GQ. (2011) Different effects of scopolamine on the retrieval of spatial memory and fear memory. Behav Brain Res, 221: 604-609.
Huang ZB, Wang H, Rao XR, Liang T, Xu J, Cai XS, Sheng GQ. (2010) Effects of immune activation on the retrieval of spatial memory. Neurosci Bull, 26:355-364.
Huang ZB, Sheng GQ. (2010) Interleukin-1beta with learning and memory. Neurosci Bull, 26: 455-468.
Abstracts and Presentations Huang ZB. (2016-faculty selected biological science colloquium talk) Differential serotonergic modulation across the main and accessory olfactory bulb. Florida State University
Huang ZB, Nicolas T, Fadool DA. (2016-invited short talk) Differential serotonergic modulation across the main and accessory olfactory bulb. 17th International Symposium on Olfaction and Taste, Yokohama, Japan
Huang ZB. (2016-CTP retreat talk) Serotonin modulation of mitral cells of the main versus accessory olfactory bulb. NIH Chemosensory Training Program at Florida State University.
Huang ZB, Fadool DA. (2015-abstract and poster) Serotonin modulation of mitral cells of the main versus accessory olfactory bulb. Association for Chemoreception Sciences (AChemS) Annual Meeting, Florida, USA
Huang ZB, Hoffman CA, Fadool DA. (2014-abstract and poster) Olfaction and anxiety in Kv1.3 knock-out mice: possible application in ADHD. Association for Chemoreception Sciences (AChemS) Annual Meeting, Florida, USA
Huang ZB. (2013-neuroscience summer seminar talk) Small ion channel Kv1.3 plays big roles in metabolism and olfaction. Florida State University
Hoffman CA, Scheffers M., Sweeney K., Huang ZB, Fadool DA. (2013-
128 poster) What are the influences of diet and the deletion of the Kv1.3 potassium ion channel on anxiety levels in mice? Tri-beta Society Annual Poster Competition, Tallahassee, FL
Huang ZB, Wang H, Rao XR, Sheng GQ. (2009-abstract and poster) Age- related impairment of memory in the Morris Water Maze induced by Lipopolysaccharide. Chinese Society for Neuroscience Annual Meeting, Guangzhou, China
Core Courses in Neuroscience and Physiology Principles of Neuroscience, Neuroinformatics, Neurophysiology, Cell and Molecular Neuroscience, Systems and Behavioral Neuroscience, Vertebrate Neuroanatomy, Membrane Biophysics (Advanced Neurophysiology), Neurobiology of Learning and Memory, Research Design and Analysis
Research Skills and Techniques Molecular Level: Western blotting, RT-PCR, immunohistochemistry, ELISA
Cellular Level: cell culture and transfection, electrophysiology—heterologous expression / brain slice patch-clamp electrophysiology and analysis
Animal Level: mouse husbandry and behavioral phenotyping—light-dark box, elevated- plus maze, Morris water maze, novel object recognition test, passive avoidance test, oral gavage, stereotactic surgery; fruit fly husbandry and T-maze test
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