Electrophysiology of Optic Nerves in Methylglyoxal Treated Mice

ELECTROPHYSIOLOGY OF OPTIC NERVES IN METHYLGLYOXAL TREATED MICE

A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science

PARKER ANDREW VAUGHAN B.S., Wright State University, 2018

2020 Wright State University

WRIGHT STATE UNIVERSITY GRADUATE SCHOOL

April 24, 2020

I HEREBY RECOMMEND THAT THE THESIS PREPARED UNDER MY SUPERVISION BY Parker Andrew Vaughan ENTITLED Electrophysiology of Optic Nerves in Methylglyoxal Treated Mice BE ACCEPTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF Master of Science.

David R. Ladle, Ph.D. Thesis Director

Eric S. Bennett, Ph.D Department Chair Department of Neuroscience, Cell Biology and Physiology

Committee on Final Examination

David R. Ladle, Ph.D.

Patrick M. Sonner, Ph.D.

Keiichiro Susuki, MD, Ph.D.

Barry Milligan, Ph.D. Interim Dean of the Graduate School

ABSTRACT

Vaughan, Parker Andrew. M.S. Department of Neuroscience, Cell Biology and Physiology, Wright State University, 2020. Elecrophysiology of Optic Nerves in Methylglyoxal Treated Mice.

The nervous system is responsible for interpreting information and coordinating that organism’s physiological response. Action potentials conduct along neuron axons to carry information within the nervous system. Saltatory conduction allows the action potential to travel rapidly along the axon from one Node of Ranvier to the next. Nodes of

Ranvier are densely packed with different proteins, notably voltage-gated sodium channels (Nav). Methylglyoxal, a toxic metabolite of glycolysis that is elevated in diabetes mellitus, alters nerve excitability by eliciting changes in protein function and structure within the Nodes of Ranvier. This study investigated the effects of methylglyoxal exposure on nerve conduction in optic nerves of mice, to test the hypothesis that methylglyoxal exposure would decrease conduction velocity. The conduction velocity, peak amplitude, and latency of optic nerve compound action potentials were recorded from saline- and methylglyoxal-treated mice. While results did not reach statistical significance, trends were evident in the analyzed parameters.

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Table of Contents

Page

I. Introduction……………………………………………………………………1

Action Potential………………………………………………...…………2

Paranode………………………………………………………………...... 3

Juxtaparanode…………………………………………………………..…4

Nodes of Ranvier…………………………………………………….……4

Myelin Disease……………………………………………………….……5

Diabetes……………………………………………………………...…….6

Diabetes and Methylglyoxal………………………………………..……..7

Methylglyoxal and Pain………………………………………….………..9

II. Materials and Methods……………………………………………………….13

Animals…………………………………………………………………..13

Dissection Procedures………………………………………...………….13

Extracellular recording of optic nerve action potentials…………………14

Statistical Analyses………………………………………………………14

III. Results………………………………………………………………………..15

Effect of temperature on peak amplitude and conduction velocity……...16

Effects of stimulation intensity on CAP peak amplitude………………...17

Effects of methylglyoxal treatment on optic nerve compound action

potential properties……………………………………………………….18

IV. Discussion……………………………………………………………………29

V. References……………………………………………………………………33

LIST OF FIGURES

Figure Page

1. Optic nerve electrophysiology recorded using suction electrodes…………….…20

2. Extracellular recording of compound action potential in optic nerve……….…...21

3. Peak amplitude increases at physiological temperatures…………………….…..22

4. Conduction velocity increases with increasing temperature……………….…….23

5. Amplitude dramatically increases with increasing stimulus strength

until a plateau is reached…………………………………………………..……..24

6. Recording sequence does not correlate with conduction velocity

measurements in single optic nerves……………………………………………..25

7. Average peak amplitude does not increase in MG treated mice…………………26

8. Latency values do not increase in MG treated mice……………………………..27

9. Conduction velocity unaffected by methylglyoxal in mouse models…………....28

I. Introduction

The nervous system is responsible for interpreting information and stimuli received from all parts of the body and then coordinating the organism’s physiological response. Information processing takes place primarily in the central nervous system, made up of the brain and spinal cord, and information must travel from the body to these centers to interpret the environment and then back to the peripheral tissues to respond to stimuli. If we are to be efficient and effective organisms, the transmission of information from one part of the body to another must be rapid.

One mechanism to increase the conduction velocity of action potential signals along an axon is to surround the axon with an insulating layer of myelin. This is the case for peripheral nerves and major axon pathways in the central nervous system which are myelinated and transmit information across long distances. Myelination enables a rapid mode of action potential transmission called saltatory conduction. Glial cells produce the lipid-rich myelin that insulates axons. Along with providing insulation, the multilayered myelin also decreases membrane capacitance and increases membrane resistance

(Hartline, 2008). In myelinated axons, the myelin is arranged along the entirety of the axon in a manner that leaves small spaces of exposed axon between adjacent myelin sheaths. The spaces of exposed nerve fiber interspersed between the myelin sheaths are called Nodes of Ranvier. The nerves that adapt this organization of myelin and internodes can utilize saltatory conduction. Saltatory conduction allows the action potential to travel along the axon, bypassing the areas of the axon that are myelinated and

“jump” from one Node of Ranvier to the next. Nodes of Ranvier are densely packed with different proteins, notably voltage-gated sodium channels (Nav).

Action Potential

The action potential is first generated at the axonal initial segment, or the AIS, and is then propagated along the axon to its destination, bypassing the regions of the axon that are insulated by the myelin sheathing. If the membrane of the nerve has been depolarized enough to reach the threshold, then an action potential will propagate down the length of an axon in a waveform. The polarization of the neuron is dependent upon the concentration gradients across the membrane of the cell. The inside of the cell has a negative charge in relation to the outside of the cell, resulting in a resting potential of around -75 mV. This net negative value is due to the movement of potassium out of the cell, relative to the movement of sodium into the cell. This difference in concentration of ions across the cell membrane is what drives each ion towards its own equilibrium.

When a neuron cell membrane reaches threshold, it is the drive of sodium and potassium towards their respective concentration equilibriums that results in the depolarization and subsequent repolarization of the cell membrane. Once the threshold is reached and the depolarization is great enough, there will be an increase in sodium influx into the cell relative to the outward flow of potassium ions. Due to positive feedback, the charge of the inside of the cell will continue to become further depolarized as it drives to reach its sodium equilibrium at +55mV. As the cell nears equilibrium and the sodium channels are fully opened, the influx of sodium ions will slow and the sodium channel pores will begin to close. During this time, the permeability of the potassium will increase the flow of potassium ions out of the cell will increase. This change will, in turn, drive the cell towards the equilibrium voltage of potassium, resulting in rapid repolarization of the cell membrane. As the voltage of the cell reaches its normal resting membrane potential, the

potassium channels begin to close. However, the potassium channels close slowly, resulting in an after-hyperpolarization of the membrane as the membrane potential briefly drops below the resting membrane potential before returning to -75mV.

Given the importance of the structure and function of the Nodes of Ranvier to the efficient and rapid transmission of actional potentials along the axon, the modification of these nodes would likely result in a variety of neurological dysfunctions. The different interactions and modifications of various proteins found in and around the nodes of

Ranvier result in different neurological diseases and dysfunctions. The Nodes of Ranvier can be divided into several different regions, each containing a variety of different proteins that characterize each domain. A Node of Ranvier is flanked on each side with a portion of the myelin sheath called the paranode. Immediately adjacent to the paranode is a region referred to as the juxtaparanode.

Paranode

The paranode, the region of the myelin on either side of the nodes of Ranvier, is a region of tightly packed myelin that forms glial loops that are filled with cytoplasm. The paranodal region of the axon is characterized by two protein complexes, contactin- associated protein (Caspr) and contactin. Both contactin and Caspr are transmembrane proteins that are involved in cell-to-cell adhesion and communication. (Poliak & Peles,

2003). The importance of Caspr and contactin to the intercellular adhesion is evidenced by the fact that the absence of such protein complexes will result in an increased distance between the axon and the paranodal loops (Poliak & Peles, 2003).

Juxtaparanode

The juxtaparanode is a small region of the myelin sheath that is immediately adjacent to the paranode, opposite of the Node of Ranvier. The proteins that characterize this region of the myelin appear to be more concentrated near the paranodal junction and more diffuse towards the internode (Rosenbluth, 1976). It is believed that the proteins that characterize this region are potassium channels that will co-localize together and create a protein complex with Caspr2 (Poliak et al., 1999; Rhodes et al., 1997; Hao Wang et al., 1993). Other important proteins that are found within the juxtaparanodal domains include a contactin related protein, transient axonal glycoprotein-1 (Tag1)(Traka et al.,

2002) and connexin 29 (Cx29)(Altevogt et al., 2002; Li et al., 2002).

Nodes of Ranvier

The formation and maintenance of the Nodes of Ranvier rely on neuron glial interaction and changes to the myelin would result in axonal defects that affect conduction velocity. Structural defects of the myelin at the paranodal regions have been found in patients with diabetic neuropathy (Doppler et al., 2017) and multiple sclerosis

(Howell et al., 2006). Furthermore, zonula occludens 1 (ZO-1) clusters found in the paranodal regions are disrupted by methylglyoxal in peripheral nerves (Griggs et al.,

2018). Exposure to methylglyoxal has been shown to cause disorder in Schwann cell proteins at the paranodes. Furthermore, immunostaining of neurofascin (NF155) at the paranode showed reduced and disorganized ZO-1 staining in areas where NF155 was disrupted (Griggs et al., 2018). Similarly, immunostaining for Caspr and NF155 showed a decrease in staining immediately adjacent to the node, indicating an elongation of the

Node of Ranvier following methylglyoxal exposure (Griggs et al., 2018). Simulated

action potentials have shown a decrease in conduction velocity as nodal length increases when the number of sodium channels within the node remains constant. These results are indicative of an increase in capacitance at the node and an increase in intracellular resistance as the nodal length increases (Arancibia-Cárcamo et al., 2017). An increase in the nodal length to double the mean value resulted in a 6.5% decrease in conduction velocity (Arancibia-Cárcamo et al., 2017). Though further experimental testing is needed, such computational models provide insight into the effects of nodal elongation on conductional velocity.

An increase in the levels of methylglyoxal has been observed in patients with diabetic neuropathy and under hyperglycemic conditions, while methylglyoxal has been shown to reduce nerve conduction in mice (Angelika Bierhaus et al., 2012). Increased nerve excitability may be an underlying factor in diabetic neuropathy (Misawa et al.,

2005). Post-translational modification of Nav1.8 channels by methylglyoxal in diabetic patients has been suggested to be a mechanism for enhanced neuron excitability and neuropathic pain (Angelika Bierhaus et al., 2012). Clusters of sodium channels (Nav) at the Nodes of Ranvier are critical for action potential propagation, thus modification and disruption of Nav clusters would result in neurological symptoms. Mitochondrial dysfunction and endoplasmic reticulum stress have also been observed following methylglyoxal exposure (Chan et al., 2016).

Myelin Disease

Given that the clusters of voltage-gated sodium channels within the nodes are vital for action potential propagation and the ability of the nerve to transmit information,

it would be reasonable to assume that any dysfunction of voltage-gated sodium channels within the Nodes of Ranvier would lead to neurological irregularities. Certain autoimmune diseases, demyelination neuropathies, and metabolic disease have shown an association with dysfunction and displacement of nodal proteins (Susuki, 2013).

Tetrodotoxin, a neurotoxin derived from pufferfish, is a sodium channel blocker that may result in paralysis. It has been shown that tetrodotoxin blocks sodium conductance and reduced nerve excitability (Kiernan et al., 2005). Similarly, various forms of epilepsy and similar neurological disorders have been linked to disruptions of sodium channel encoding (Veeramah et al., 2012). Metabolic disease, such as type 1 diabetes mellitus has also been linked to the disruption of proteins in the Nodes of Ranvier. A decrease in the number of proteins and molecules present in the Nodes of Ranvier has been shown in type 1 diabetic mouse models in multiple studies (Susuki, 2013).

Diabetes

Diabetes mellitus is a metabolic disease that affects hundreds of millions of people worldwide (Shaw et al., 2010). Diabetes is a chronic metabolic disease that most often results in hyperglycemia, or elevated blood glucose levels. High blood glucose levels in individuals affected by diabetes are associated with various complications including ketoacidosis, blindness, nephropathy, and heart disease.

Diabetes is generally classified into two different classes, type one diabetes, and type two diabetes. The diabetes classification depends on the cause of the disease. Type

1 diabetes is an autoimmune disease that destroys beta cells that are located within the islets of the pancreas. Because the beta cells of the pancreas are responsible for the

production and secretion of insulin, their destruction results in the dysfunction of glucose absorption and a loss of blood glucose regulation. Type 2 diabetes is a result of insulin dysfunction and in turn leads to chronic hyperglycemia, or high blood glucose levels.

Chronic hyperglycemia will often lead to the reduction of insulin sensitivity and thus lead to insulin resistance. Popular therapies for diabetes mellitus include medications and exogenous administration of insulin.

Apart from the metabolic dysfunctions caused by diabetes mellitus, there are also microvascular complications that have been associated with the disease such as retinopathy and nephropathy. Microvascular or small vessel abnormalities may represent larger issues related to cardiovascular and nerve pathologies. The chronic hyperglycemia observed in diabetes is also associated with non-vascular pathologies including damage to the myelin sheathing of nerves, peripheral nerves, and the un-myelinated autonomic nerves. Symptoms that result from these dysfunctions can be a loss of sensation, proprioception, and dysregulation of autonomic function altogether. Though many of the pathologies related to diabetes mellitus are characterized as peripheral neuropathies, some research indicates that central neuropathy may also play an important role in diabetes mellitus.

Diabetes and Methylglyoxal

Diabetes mellitus is most commonly diagnosed based upon the characterization of many factors such as the concentration of glucose in the blood, urine, and saliva. More recently, methylglyoxal, a metabolite of glycolysis, has been presented as a possible

indicator of diabetes mellitus due to its role in insulin resistance (Ramachandra Bhat et al., 2019).

Methylglyoxal is an intracellular dicarbonyl metabolite that can be synthesized from a variety of metabolic pathways, but is derived mainly from triose phosphate, a glucose intermediate in the glycolysis pathway (Paul J. Thornalley, 1996; Paul J.

Thornalley et al., 1999). Methylglyoxal is a highly toxic and reactive electrophilic molecule that has been shown to affect neuronal functions (Angelika Bierhaus et al.,

2012). A strong non-enzymatic reaction between methylglyoxal and the functional groups of arginine, lysine, and cysteine residues of specific proteins (Lo et al., 1994) results in the formation of advanced glycation end products, or AGEs (Lo et al., 1994), apoptosis and mitochondrial damage (Nakayama et al., 2008). Under normal physiological conditions, methylglyoxal can be detoxified from the body by the glyoxalase system, however, under hyperglycemic conditions, the necessary glyoxalase enzyme is not elevated sufficiently in relation to the levels of methylglyoxal (P. J.

Thornalley et al., 1989). Increased levels of endogenous methylglyoxal and advanced glycation end products (AGEs) have been recorded in patients with diabetes mellitus and have indicated an association with various complications in individuals with diabetes

(Huang et al., 2016; Kalapos, 2013). Retinopathy, nephropathy (Paul J. Thornalley,

1996; Hui Wang et al., 2007; X. Wang et al., 2005), and neuropathic pain (Angelika

Bierhaus et al., 2012) have all been shown to be associated with high methylglyoxal levels.

Insulin resistance leads to a reduction in the ability of cells to take up glucose, resulting in a decrease in insulin clearance from cells (Ramachandra Bhat et al., 2019).

Methylglyoxal has been shown to contribute to insulin resistance by inhibiting certain receptor substrates and pathways that result in decreased insulin secretion (Cantero et al.,

2007; Fiory et al., 2011; Matafome et al., 2017). Overall, this increase in insulin resistance leads to hyperglycemia (Guo et al., 2009). Beta cells, found within pancreatic islets, are responsible for insulin secretion and act in response to blood glucose levels.

Methylglyoxal has been shown to result in apoptosis of adipose tissue (Bo et al., 2016;

Guo et al., 2009). Furthermore, methylglyoxal leads to a decrease in insulin release from beta cells due to the production of reactive oxygen species (Pi et al., 2007).

Methylglyoxal has also been shown to decrease the production of insulin by reducing the levels of transcription factors responsible for insulin synthesis (Dhar et al., 2011).

Furthermore, methylglyoxal can have direct effects on the insulin peptide itself, by binding to arginine residues in the peptide and causing dysfunction of their ß-chain adducts. (Dhar et al., 2011; Jia et al., 2006). The binding of methylglyoxal to insulin also disrupts the insulin feedback mechanism on the beta cells that produce it, resulting in an overall imbalance in insulin removal and maintenance (Jia et al., 2006). Taken together, methylglyoxal modifies insulin molecules and disrupts signaling pathways, resulting in decreased insulin secretion.

Methylglyoxal has been shown to increase peripheral nerve excitability and nociceptive responses (Eberhardt et al., 2012; Shimatani et al., 2015), as well as interact with and modify ion channels, specifically Nav1.8 (Angelika Bierhaus et al., 2012). Due to its chemical similarities to formaldehyde, methylglyoxal may act as an agonist for transient receptor potential channel A1 (TRPA1), which is expressed by nociceptive neurons (Eberhardt et al., 2012). Methylglyoxal has been shown to activate TRPA1

receptor channels by modifications of lysine and cysteine residues in neurons of the dorsal root ganglion (Eberhardt et al., 2012). Furthermore, methylglyoxal results in a decrease in nerve conduction in nociceptive C- fibers via a TRPA1 mechanism

(Eberhardt et al., 2012).

Methylglyoxal and Pain

Chronic pain and hyperalgesia, or increased sensitivity to pain, are common symptoms of diabetes mellitus. Though the current understanding of the mechanisms of diabetic neuropathic pain is incomplete, the hyperglycemic levels of blood glucose found in patients with diabetes appear to not be the likely causal mechanism. In support of this, it has been shown that normalization of high blood glucose levels in diabetic patients does not affect associated neuropathic pain (Nawroth et al., 2010; Tavee & Zhou, 2009).

The increase in blood-glucose concentration in diabetic patients leads to increased levels of methylglyoxal (Paul J. Thornalley, 2005). Methylglyoxal is then metabolized and detoxified by the enzyme glyoxalase 1 (GLO1) and glyoxalase 2 (GLO2) (Paul J.

Thornalley, 1993). The peripheral nervous system has been shown to have lower GLO1 activity, which in turn may result in increased susceptibility to higher methylglyoxal levels (A. Bierhaus & Nawroth, 2009; Jack et al., 2011). Reduced expression of GLO1 has been shown to cause increased levels of methylglyoxal in diabetic rats (Angelika

Bierhaus et al., 2012). The relationship between methylglyoxal, GLO1, and pain perception may be significant, as mice with higher levels of GLO1 expression display reduced mechanical hyperalgesia (Jack et al., 2011).

An increase in nerve excitability appears to be an underlying cause of hyperalgesia in diabetic neuropathy (Misawa et al., 2005; Suzuki et al., 2002). A reduction in sodium-potassium ATPase activity and a decrease in potassium conductance may be a cause of this increased excitability associated with diabetic neuropathy (Misawa et al., 2005). Another potential cause of increased excitability may be attributed to altered expression of voltage-gated sodium channels, resulting in a change of shape or propagation of action potentials (Craner et al., 2002; Hong et al., 2004).

Nav1.8 channels are a subtype of voltage-gated sodium channels that are found in the dorsal root ganglia (DRG) and C-fibers, or nerves involved in nociception (Lampert et al., 2010). These particular voltage-gated sodium channels (VGSC's) are classified as tetrodotoxin-resistant (TTXr) and their expression has been observed to be lower in diabetic rats (Craner et al., 2002; Hong et al., 2004). It has been shown that the higher levels of methylglyoxal found in diabetic individuals may result in the associated hyperalgesia due to post-translational modification of Nav1.8 channels that results in a change of function.(Angelika Bierhaus et al., 2012). Subsequently, individuals that suffered from diabetes-associated pain were found to higher levels of methylglyoxal in their blood when compared to controls and diabetic individuals who did not suffer from neuropathic pain (Angelika Bierhaus et al., 2012). Furthermore, methylglyoxal has been shown to have a concentration-dependent effect on both thermal and mechanical hyperalgesia (Angelika Bierhaus et al., 2012). Additionally, there was an increase in methylglyoxal modifications of Nav1.8 found in diabetic patients when compared to patients without diabetes (Angelika Bierhaus et al., 2012). Together, these results

suggest an important role of methylglyoxal in hyperexcitability and nociception associated with diabetes.

Literature has shown that elevated levels of methylglyoxal can affect nerve excitability and lead to chronic pain and hyperalgesia in diabetic patients. Methylglyoxal alters nerve excitability by eliciting changes in protein function and structure within the

Nodes of Ranvier and elsewhere. Literature has similarly shown that methylglyoxal can result in an increase in the nodal gap, or the space between adjacent myelin sheaths. An increase in the length of the node will increase both the capacitance and the resistance of the membrane, which will in turn result in a decrease in conduction velocity (Arancibia-

Cárcamo et al., 2017).

Given that the structure and function of proteins, specifically voltage gated sodium channels, are vital for efficient nerve conduction, we hypothesized that elevated levels of methylglyoxal would reduce nerve conduction velocity. To test this hypothesis, the conduction of action potentials along the optic nerve, a model of nerve conduction in the central nervous system, were measured in cohorts of control mice and mice exposed to elevated levels of methylglyoxal for either two or four weeks prior to the experiments.

II. Materials and Methods

Animals

Experimental procedures were conducted with the approval of the Institutional

Animal Care and Use Committee at Wright State University. Beginning at 8 weeks of ages, male and female C57BL/6J mice (JAX 000664) were given daily intraperitoneal injections of 5 mL/kg of saline or 10 mg/mL of methylglyoxal, resulting in a total final dose of 50 mg/kg/d. Methylglyoxal treated mice were divided into two cohorts, receiving methylglyoxal injections for either two or four weeks.

Dissection procedures

Mice were first anesthetized using isoflurane inhalation and then decapitated. To remove the optic nerves for nerve conduction studies, the skin was first removed from the superior surface of the skull until access to the orbitals was available. Small cuts were made in the connective tissue around the superior portion of the orbitals to facilitate access to the optic nerves. Microdissection spring scissors were inserted behind the eyes and the optic nerve was cut close to the eyeball. To expose the central portion of the optic nerve, the parietal bones were separated along the sagittal suture by cutting caudal to rostral, and the brain was removed along with the attached optic nerves. From the inferior surface of the brain, the two optic nerves were then separated at the optic chiasm and immediately placed in a circulating bath of room temperature (21-23° C), oxygenated

(95% O2; 5% CO2) artificial cerebral spinal fluid (aCSF) containing (in mM): 127 NaCl,

1.9 KCl, 1.2 KH2PO4, 1 MgSO47H2O, 26 NaHCO3, 16.9 D(+)-glucose monohydrate, and

2 CaCl2.

Extracellular recording of optic nerve action potentials

Both ends of each optic nerve were trimmed with microdissection spring scissors to ensure clean cuts and consistent exposure of the nerve fibers. Each end of the optic nerve was then placed in tight-fitting glass capillary tubes attached to suction electrodes.

A stimulus isolation unit (A365D) was used to generate 0.1ms current pulses ranging from 10µA to 10mA. Electrophysiology recordings were taken for each optic nerve using a Dagan EX4-400 four channel differential amplifier (Dagan Corp., Minneapolis, USA).

Stimulus protocols were controlled with WinLTP software (WinLTP Ltd., Bristol, UK) and responses were digitized at 20kHz and stored for later analysis. Beginning with a stimulus of 50% on the 1mA range, stimulus strength was increased in 10% increments until the maximum amplitude response was found for each optic nerve. Similarly, the minimum stimulus required to evoke an action potential was recorded by decreasing stimulus intensity. Following the recording of the first optic nerve from an animal, a digital caliper was used to measure the length of the optic nerve between the two suction electrodes. The second optic nerve was then loaded into the glass capillaries for recording. For saline and methylglyoxal treated animals, recordings were made at room temperature (21-23° C).

Statistical analysis

Statistical analysis was accomplished via Microsoft Excel. Single-factor

ANOVAs and two sample t-Tests assuming equal variance were used to calculate statistical significance among the samples.

III. Results

Optic nerve compound action potential recording was accomplished using tight- fitting capillary tubes attached to suction electrodes and immersed in a circulating bath of oxygenated artificial cerebral spinal fluid (aCSF). Both optic nerves were removed, trimmed, and placed in the bath. One end of each nerve was placed within the stimulus suction electrode while the other end was placed in the recording suction electrode.

Action potentials recorded with this technique represent the summation of thousands of individual action potentials from individual retinal ganglion cell axons found in the optic nerve (see Figure 2). Each recording begins with a 10ms baseline period, then a 0.1ms stimulation pulse is given to generate action potentials in RGC axons at one end of the nerve. The stimulus artifact, which is clearly seen in Figure 2, varies in amplitude with the strength of the stimulus, but serves as a marker for when the stimulation was given. The resulting compound action potential then conducts down the axon and the electrical waveform associated with the action potential is recorded at the other end. Following the stimulus artifact, the depolarization of the cell results in the propagation of an action potential, as shown in Figure 2. The overall shape of the compound action potential recorded with this technique is similar action potential waveforms observed in single axons. A rapid depolarization phase is followed by a repolarization phase as the action potential trace trends back towards the baseline potential. Since voltage-gated potassium channels are slow to close, there is an after- hyperpolarization that is seen as the value temporarily drops below baseline potential levels.

The amplitude of the compound action potential can be influenced by a number of factors. First, the number of axons activated by the stimulus is dependent on the stimulus intensity and this is a major contribution to the amplitude of the overall compound action potential waveform. The amplitude can also be affected by the tightness of the fit of the glass capillary of the recording electrode around the optic nerve. Tighter fits increase electrical resistance and allow less of the current generated by the axons to escape into the chamber, this can increase the amplitude of the recorded signal. However, the time between the stimulus and the peak of the action potential, termed the latency, is relatively stable and is used to calculate the overall conduction velocity of action potentials along the nerve.

Effect of temperature on peak amplitude and conduction velocity

To determine if the temperature of the ACSF during the recordings had an influence on optic nerve preparations, the temperature was steadily increased from room temperature to values closer to physiological temperature in one control preparation. The stimulation intensity was first set to evoke the maximum compound action potential response at room temperature and was held constant throughout this experiment. As shown in Figure 3, the amplitude of the compound action potential remained fairly constant up to a temperature of approximately 27° C. At temperatures higher than 29° C, the amplitude increased by roughly 1mV, but did not appear to linearly increase with even higher ACSF temperatures.

As shown in Figure 4, the conduction velocity increases as the temperature increases, though the increase is not linear. There was an unexpected decrease in

conduction velocity around 24°C and remained low, but increasing until temperature was increased to 27°C. At temperature higher than 29°C, there was a dramatic increase in conduction velocity and the trend continued upward for the remainder of the temperatures tested. This control experiment indicated that temperatures closer to the physiological range correlate with higher conduction velocities. Given that degradation of ex vivo nerve tissue is accelerated at high temperatures, subsequent recordings in saline- and methylglyoxal-treated animals were made a room temperature (21-23° C).

Effects of stimulation intensity on CAP peak amplitude

For each nerve tested, the peak amplitude of the compound action potential increased steeply with increasing stimulus strength until a plateau value was reached

(Figure 5). This plateau represents maximum recruitment of all axons in the optic nerve.

In other words, no additional axons are activated even with stronger current pulses; the signal is saturated. To quantify the peak amplitude value for each nerve tested, the maximum peak amplitude observed and all measurements made at higher stimulus strengths were averaged together to generate the peak amplitude measurement for that animal. For example, in Figure 5, Peak amplitudes for both nerves illustrated were evoked by 2mA stimulation. Thus, the average peak amplitude for each nerve was calculated as the average peak values recorded at stimulations of 2mA and all higher stimulation strengths (2, 3, and 4mA for the methylglyoxal treated example, and 2, 3, 4, and 5mA for the saline treated example). Although the stimulation profiles of the two nerves shown in this figure have different peak amplitudes, there appeared to be no

differences in the overall profile of the stimulation-to-amplitude relationship between methylglyoxal- and saline-treated animals.

Effects of methylglyoxal treatment on optic nerve compound action potential properties

Three cohorts of mouse models were used. Beginning at 8 weeks of age, both male and female mice were given daily intraperitoneal injections of 5 mL/kg of saline or

10 mg/mL of methylglyoxal, resulting in a total final dose of 50 mg/kg/d. The methylglyoxal treated mice were further split into different cohorts. A total of six mice were given daily intraperitoneal injections of methylglyoxal for a duration of two weeks, while five mice were given daily methylglyoxal injections for a period of four weeks.

Saline injected mice were given daily injections for periods of both two and four weeks.

At the end of the treatment period, both optic nerves were removed from each mouse and used for electrophysiology recordings. The average values for latency, peak amplitude, and conduction velocity were averaged from both optic nerves and used as a single representative data point for the respective mouse. These values were used for the calculations and the statistical analyses.

While action potentials were recorded from both optic nerves of each animal, measurements from both nerves could not be made simultaneously, and so nerves were analyzed one at a time. To determine if conduction velocity was affected by the order of optic nerve recordings, we plotted the conduction velocity for both optic nerves for each mouse. The variability observed between the first and second optic nerves does not suggest a sequence dependence for recordings. These results do not suggest any

degradation of the optic nerve preparations during the time window we conducted the experiments.

There were no differences in conduction velocity between saline mice and the two week or four week treated cohorts (saline (n= 11): 1.92 ± 0.24; 2wkMG (n=6): 1.81 ±

0.23; 4wkMG (n=5): 1.99 ± 0.12; p=0.355), per an ANOVA single factor statistical test.

Similarly, two-sample t-Tests did not indicate any differences between the two week and four week treated cohorts.

There was an almost significant difference in average peak amplitude between the saline and MG treated animals for the two week and four weeks cohorts (saline (n= 11):

9.93 ± 3.41; 2wkMG (n=6): 8.55 ± 2.09; 4wkMG (n=5): 13.49 ± 3.69; p=0.051), as indicated by a single factor ANOVA statistical test. A two-sample t-Test indicated that methylglyoxal treated cohorts of two and four weeks did differ (p=0.021).

An ANOVA single factor statistical test did indicate a significant difference between the latency values of saline and methylglyoxal treated animals for 2 weeks and 4 weeks (saline (n= 11): 1.41 ± 0.18; 2wkMG (n=6): 1.51 ± 0.21; 4wkMG (n=5): 1.21 ±

0.14; p=0.043). A two-sample t-Test showed that there was a difference in the latency found between saline and mice treated with methylglyoxal for 2 weeks (p=0.046). There was also a difference between two weeks and four-week cohorts (p=0.028) of mice treated with methylglyoxal. There was no difference in latency found between saline treated mice and mice treated with methylglyoxal for two weeks (p=0.332).

Figure 1. Optic nerve electrophysiology recorded using suction electrodes

A representative diagram of the optic nerve situated in capillary tubes within the stimulus and recording suction electrodes. The length of each optic nerve was measured from the opening of stimulation electrode to the opening of the recording electrode. The opening of each electrode and the entire optic nerve was submerged in a circulating bath of oxygenated artificial cerebral spinal fluid (aCSF).

Figure 2. Extracellular recording of compound action potential in optic nerve

A representative action potential trace from a methylglyoxal treated mouse within the 2- week cohort. The artifact preceding the action potential represents the stimulus.

Following the stimulus, a rapid depolarization leads to the peak amplitude of the compound action potential followed by repolarization back towards resting membrane potential. Following repolarization, an after-hyperpolarization occurs as axons hyperpolarize compared to resting membrane potential as voltage-gated potassium channels remain open. The eventual return to baseline potential values is caused by the slow inactivation and closure of the voltage-gated potassium channels.

Figure 3. Peak amplitude increases at physiological temperatures

Peak amplitude remains relatively constant at temperatures of 19°C through 27°C, roughly room temperature. A dramatic increase in peak amplitude occurs from 27°C to

30°C. An overall positive trend indicates that peak amplitude may increase with temperature.

Figure 4. Conduction velocity increases with increasing temperature

Conduction velocity appears to be stable until around 23°C. An unexplained decrease in conduction velocity occurs at 24°C, followed by a dramatic increase around 30°C and a steady increase to 33°C. An overall positive trend indicates that conduction velocity may increase with temperature. However, to mitigate the degradation of the optic nerve at high temperatures, recordings were conducted at room temperature (21-23°C).

Figure 5. Amplitude dramatically increases with increasing stimulus strength until a plateau is reached. The amplitude profiles as a function of stimulation strength are similar between methylglyoxal- and saline-treated mice. The variability in peak amplitude between these two profiles is consistent with variability seen in peak amplitudes across all animals and is not suggestive of significant population differences in peak amplitudes.

Figure 6. Recording sequence does not correlate with conduction velocity measurements in single optic nerves

In these experiments, both optic nerves were removed simultaneously and immediately placed into circulating aCSF. While both nerves were utilized for recordings, only one optic nerve at a time could be used. Conduction velocity values calculated for the first

(optic nerve 1) and second (optic nerve 2) optic nerves recorded from a single animal are shown vertically for each animal, grouped by experimental condition along the x-axis.

No consistent pattern was observed in the ranking (high to low) of conduction velocities measured from each animal. The lack of sequence dependence between the first and the second optic nerves suggests that the possible degradation of the second optic nerve was not a significant factor in conduction velocity measurements.

Figure 7. Average peak amplitude does not increase in MG treated mice

Peak amplitude was recorded with a steady increase in stimulus intensity until a plateau was reached. The values of the plateau were averaged for the peak amplitude. Saline

(n=11) animals did not differ significantly from the two week (n=6) or four week (n=5) cohorts (p=0.051). The peak amplitude of mice treated with methylglyoxal for two weeks did differ from those treated for four weeks (p=0.021). Bar graphs show mean +

SD for each cohort.

Figure 8. Latency values do not increase in MG treated mice

The latency measurement is the time between the stimulus onset and the peak of the compound action potential. There was a difference found between saline (n=11) treated mice and the two week (n=6) and four week (n=5) MG treated cohorts (p=0.042). The given latency values were used to calculate the conduction velocity of each optic nerve.

Bar graphs show mean + SD for each cohort.

Figure 9. Conduction velocity unaffected by methylglyoxal in mouse models

The length of each optic nerve was measured following the recordings and the conduction velocity was calculated by dividing the length of each optic nerve by the given latency for that particular nerve. There was no difference found between the saline

(n=11) and two week (n=6) or four week (n=4) MG treated cohorts (p=0.355). Bar graphs show mean + SD for each cohort.

IV. Discussion

This study investigated the effects of methylglyoxal on nerve conduction in optic nerves of mice. Literature has shown that elevated levels of methylglyoxal can affect nerve excitability and lead to chronic pain and hyperalgesia in diabetic patients.

Methylglyoxal alters nerve excitability by eliciting changes in protein function and structure within the Nodes of Ranvier and elsewhere. Literature has similarly shown that methylglyoxal can result in an increase in the nodal gap, or the space between adjacent myelin sheaths. Given that the structure and function of proteins, specifically voltage gated sodium channels, are vital for efficient nerve conduction, we hypothesized that elevated levels of methylglyoxal would reduce nerve conduction velocity. Throughout this study, we recorded and analyzed the conduction velocity, peak amplitude, and latency of optic nerves across three cohorts of animal models. Mice were given daily intraperitoneal injections of saline or methylglyoxal for a period of two or four weeks.

Latency values were calculated offline using automated detection algorithms in the WinLTP software package. A single factor ANOVA statistical test determined that there was a difference in latency between the three cohorts of saline, mice treated with methylglyoxal for two weeks, and those treated for four weeks. While this may appear to suggest an effect of the methylglyoxal treatment, the latency between the stimulus and the peak of the compound action potential depends on the length of the nerve the action potential must conduct along between the two electrodes. Both the latency values and the length of each nerve are required to calculate the conduction velocities for a given mouse.

The conduction velocity was calculated by dividing the length of each optic nerve by the given latency for that particular nerve. The conduction velocity of both optic nerves was

averaged for each mouse. After considering the length of each optic nerve and calculating the conduction velocity, a single factor ANOVA statistical test determined there was no difference in conduction velocity between the three cohorts.

Though the conduction velocity did not differ between saline and methylglyoxal cohorts, there is indication of a trend across all parameters that were analyzed. A small decrease in conduction velocity is seen when the two-week methylglyoxal cohort is compared to the saline group. However, there is a small increase in conduction velocity when comparing the two-week and four-week cohorts. A similar scenario was observed when analyzing the peak amplitude recorded from each nerve. The average peak amplitude of saline animals did not differ significantly from the two-week or four-week cohorts. Though the value was close, it did not reach the threshold of significance.

Nevertheless, a trend similar to that observed for conduction velocity was evident, as peak amplitude decreases in the two-week cohort compared to the saline cohort. When comparing the peak amplitude of the two-week cohort with the four-week cohort, there is a significant increase in peak amplitude in the four-week cohort (P<0.05). Latency appears to increase with the two-week cohort compared to the saline cohort, while there is significant decrease in latency with the four-week cohort compared to the two-week cohort (P<0.05).

The average conduction velocity for saline treated mice in this study was 1.92 m/s.

Conduction velocity in optic nerves of 23 and 60 week old wild-type mice had been reported elsewhere to be >4.0m/s (Susuki et al., 2018). The lower conduction velocity values obtained during this study may be attributed to temperature differences at which recordings were made. As shown in Figure 4, conduction velocity does increase with

temperature and much of the literature analyzing conduction velocity in optic nerves conducted the recordings at 37°C (Shrager & Youngman, 2017), and 35°C (Devaux &

Gow, 2008).

We observed that peak amplitude varied notably within each cohort and even between both optic nerves of the same mouse. These results could be attributed to a combination of factors related to the capillary tubes and suction electrodes used to make the recordings. Most notably, the amount of optic nerve within each capillary tube and the effectiveness of its seal around each optic nerve can have a significant effect on the recorded amplitude. A tighter seal would result in an increase in peak amplitude. For this study, we did not control for any change in seal resistance during each recording. By recording the pipet resistance before and after insertion of each nerve, a normalization of the amplitude of the compound action potential for each nerve could have mitigated the variability that was observed. Furthermore, the methods of measuring the optic nerves may differ from previous studies, resulting in differences in calculated conduction velocity.

Though the results of this study did not support the original hypothesis, there remain questions to be explored and this study provides a groundwork for future studies. The lack of significance in the results could be due to a small number of animals, with a total sample size of n=22 animals across three experimental conditions. Given the trends that were seen, there are compelling reasons to increase the sample size for a more accurate representation of the results. Furthermore, an increase in the duration of methylglyoxal treatments for each cohort might be considered to further address the trends that were observed between the two-week and four-week methylglyoxal cohorts. If there was

compensation in protein expression that occurred at the Nodes of Ranvier over time to mitigate the effects of methylglyoxal treatment, an adjustment to the treatment timetable might address these questions.

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