Taenia larvae possess distinct acetylcholinesterase profiles with implications for host cholinergic signalling

Larvae of the cestodes Taenia solium and Taenia crassiceps infect the central nervous system of humans. Taenia solium larvae in the brain cause neurocysticercosis, the leading cause of adult-acquired epilepsy worldwide. Relatively little is understood about how cestode-derived products modulate host neural and immune signalling. Acetylcholinesterases, a class of enzyme that breaks down acetylcholine, are produced by a host of parasitic worms to aid their survival in the host. Acetylcholine is an important signalling molecule in both the human nervous and immune systems, with powerful modulatory effects on the excitability of cortical networks. Therefore, it is important to establish whether cestode derived acetylcholinesterases may alter host neuronal cholinergic signalling. Here we make use of multiple techniques to profile acetylcholinesterase activity in different extracts of both Taenia crassiceps and Taenia solium larvae. We find that the larvae of both species contain substantial acetylcholinesterase activity. However, acetylcholinesterase activity is lower in Taenia solium as compared to Taenia crassiceps larvae. Further, whilst we observed acetylcholinesterase activity in all fractions of Taenia crassiceps larvae, including on the membrane surface and in the excreted/secreted extracts, we could not identify acetylcholinesterases on the membrane surface or in the excreted/secreted extracts of Taenia solium larvae. Bioinformatic analysis revealed conservation of the functional protein domains in the Taenia solium acetylcholinesterases, when compared to the homologous human sequence. Finally, using whole-cell patch clamp recordings in rat hippocampal brain slice cultures, we demonstrate that Taenia larval derived acetylcholinesterases can break down acetylcholine at a concentration which induces changes in neuronal signalling. Together, these findings highlight the possibility that Taenia larval acetylcholinesterases can interfere with cholinergic signalling in the host, potentially contributing to pathogenesis in neurocysticercosis

Intracellular chloride and hydrogen ion dynamics in the nervous system

Synaptic transmission in the nervous system involves the activation of receptor proteins that permit rapid transmembrane fluxes of ions. Ionic gradients across the membrane determine the direction and driving force for the flow of ions and are therefore crucial in setting the properties of synaptic transmission. These ionic gradients are established by a variety of mechanisms, including pump and transporter proteins. However, the gradients can be affected by periods of neural activity, which in turn, are predicted to influence the properties of ongoing synaptic transmission. In this thesis I have examined the concentration gradients of two ions that play a fundamental role in synaptic transmission: chloride ions (Cl-) and protons (H+). Type A γ-Aminobutyric acid receptors (GABAARs) are primarily permeable to Cl- and mediate the majority of fast post-synaptic inhibition in the brain. The transmembrane concentration gradient for Cl- is therefore a critical parameter in governing the strength of synaptic inhibition. In the first part of the Thesis I use a combination of experimental and theoretical approaches to demonstrate that influxes of Cl- via activated GABAARs can overwhelm a neurons ability to maintain a stable Cl- concentration gradient. The consequence is that subsequent activation of GABAARs results in weaker inhibition or even excitation, which alters how the neuron integrates synaptic inputs. This process is shown to be dependent upon the level of activity of the GABAAR, the post-synaptic cells membrane potential and the cellular compartment into which the Cl- flows. These principles were extended to demonstrate that popular optogenetic strategies for silencing neural activity have different effects upon GABAAR transmission. A light-activated Cl- pump was shown to cause substantial accumulations in intracellular Cl, which meant that the strength of synaptic inhibition was significantly reduced following light offset. In the second part of the Thesis I use electrophysiological and fluorescence imaging techniques to demonstrate that the activation of GABAARs during epileptiform activity results in pronounced changes to the transmembrane Cl- gradient. Indeed, these changes convert synaptic inhibition into synaptic excitation during the course of a seizure event. As part of this work I characterise a novel, genetically-encoded reporter for measuring intracellular Cl- dynamics in different cell types and subcellular compartments. A significant advantage of this reporter is that it permits the simultaneous quantification of H+ fluxes, which are also shown to change in an activity-dependent manner and which have been a confounding factor for previous Cl- reporters. In the third and final part of the Thesis I use genetically-encoded reporters to investigate activity-dependent changes in intracellular H+ concentration. I demonstrate that markedly different pH changes occur in neurons and astrocytes during epileptiform activity. Whereas neurons become acidic, astrocytes become alkaline and the dynamics of these pH shifts exhibit a very different temporal relationship with the seizure event. In conclusion, this thesis demonstrates that the intracellular concentrations of Cl- and H+ are dynamic variables that evolve across time and space, in an activity-dependent manner. Changes in the transmembrane gradients of these two ions influence ongoing synaptic transmission. Therefore this work has significant implications for our understanding of network activity and the balance of synaptic excitation and inhibition.</p

Ion dynamics during seizures

Changes in membrane voltage brought about by ion fluxes through voltage and transmitter-gated channels represent the basis of neural activity. As such, electrochemical gradients across the membrane determine the direction and driving force for the flow of ions and are therefore crucial in setting the properties of synaptic transmission and signal propagation. Ion concentration gradients are established by a variety of mechanisms, including specialised transporter proteins. However, transmembrane gradients can be affected by ionic fluxes through channels during periods of elevated neural activity, which in turn are predicted to influence the properties of on-going synaptic transmission. Such activity-induced changes to ion concentration gradients are a feature of both physiological and pathological neural processes. An epileptic seizure is an example of severely perturbed neural activity, which is accompanied by pronounced changes in intracellular and extracellular ion concentrations. Appreciating the factors that contribute to these ion dynamics is critical if we are to understand how a seizure event evolves and is sustained and terminated by neural tissue. Indeed, this issue is of significant clinical importance as status epilepticus – a type of seizure that does not stop of its own accord – is a life-threatening medical emergency. In this review we explore how the transmembrane concentration gradient of the six major ions (K+, Na+, Cl-, Ca2+, H+ and HCO3-) is altered during an epileptic seizure. We will first examine each ion individually, before describing how multiple interacting mechanisms between ions might contribute to concentration changes and whether these act to prolong or terminate epileptic activity. In doing so, we will consider how the availability of experimental techniques has both advanced and restricted our ability to study these phenomena

Intracellular chloride and hydrogen ion dynamics in the nervous system

Synaptic transmission in the nervous system involves the activation of receptor proteins that permit rapid transmembrane fluxes of ions. Ionic gradients across the membrane determine the direction and driving force for the flow of ions and are therefore crucial in setting the properties of synaptic transmission. These ionic gradients are established by a variety of mechanisms, including pump and transporter proteins. However, the gradients can be affected by periods of neural activity, which in turn, are predicted to influence the properties of ongoing synaptic transmission. In this thesis I have examined the concentration gradients of two ions that play a fundamental role in synaptic transmission: chloride ions (Cl-) and protons (H+). Type A γ-Aminobutyric acid receptors (GABAARs) are primarily permeable to Cl- and mediate the majority of fast post-synaptic inhibition in the brain. The transmembrane concentration gradient for Cl- is therefore a critical parameter in governing the strength of synaptic inhibition. In the first part of the Thesis I use a combination of experimental and theoretical approaches to demonstrate that influxes of Cl- via activated GABAARs can overwhelm a neurons ability to maintain a stable Cl- concentration gradient. The consequence is that subsequent activation of GABAARs results in weaker inhibition or even excitation, which alters how the neuron integrates synaptic inputs. This process is shown to be dependent upon the level of activity of the GABAAR, the post-synaptic cells membrane potential and the cellular compartment into which the Cl- flows. These principles were extended to demonstrate that popular optogenetic strategies for silencing neural activity have different effects upon GABAAR transmission. A light-activated Cl- pump was shown to cause substantial accumulations in intracellular Cl, which meant that the strength of synaptic inhibition was significantly reduced following light offset. In the second part of the Thesis I use electrophysiological and fluorescence imaging techniques to demonstrate that the activation of GABAARs during epileptiform activity results in pronounced changes to the transmembrane Cl- gradient. Indeed, these changes convert synaptic inhibition into synaptic excitation during the course of a seizure event. As part of this work I characterise a novel, genetically-encoded reporter for measuring intracellular Cl- dynamics in different cell types and subcellular compartments. A significant advantage of this reporter is that it permits the simultaneous quantification of H+ fluxes, which are also shown to change in an activity-dependent manner and which have been a confounding factor for previous Cl- reporters. In the third and final part of the Thesis I use genetically-encoded reporters to investigate activity-dependent changes in intracellular H+ concentration. I demonstrate that markedly different pH changes occur in neurons and astrocytes during epileptiform activity. Whereas neurons become acidic, astrocytes become alkaline and the dynamics of these pH shifts exhibit a very different temporal relationship with the seizure event. In conclusion, this thesis demonstrates that the intracellular concentrations of Cl- and H+ are dynamic variables that evolve across time and space, in an activity-dependent manner. Changes in the transmembrane gradients of these two ions influence ongoing synaptic transmission. Therefore this work has significant implications for our understanding of network activity and the balance of synaptic excitation and inhibition.This thesis is not currently available in ORA

Increasing branch occupancy with inhibitory synapses enhances Inhibitory Level at the junction but saturates relative inhibitory accumulation.

(A) The percentage of dendritic branches which have inhibitory synapses, “effective number of synapses”, indicates the diminishing return in additional IL when adding more synapses. (Ai-iv) 4 branch structure with 1 (Ai, 25%), 2 (Aii, 75%), 4 (Aiii, 100%), or 8 (Aiv, 200%) inhibitory synapses (∇EGABA = 0 mV). Note that inhibitory synapses are located at 0.2 X, so for 8 synapses on 4 branches (200%), there are 2 synapses per location. (B) IL as in ‘A’ for the effective number of synapses . Thinner lines indicate a lower effective number of synapses. Note that there is no “∇” marker for branches without synapses, “silent branches”. (C) As in ‘B’ but with 8 branches. Thus, 75% effective number of synapses for 8 branches is 6 of the branches with synapses and the other 2 without synapses. Inset, 150% (12/8) effective number of synapses has some branches with a single synapse and others with 2 synapses. The branches with extra synapses have stronger IL values while the branches without extra synapses have a moderately better IL than 100% effective number of synapses. (D) As in ‘B’ and ‘C’, but the synapses on the 4 branches each have ∇EGABA = -2 mV. (E) The IL for shunting synapses (lower portion) and IL for hyperpolarising synapses (upper portion) at the junction for 4 and 8 branches with inhibitory synapses either at ∇EGABA = 0 mV or 2 mV. Line and marker colours same as in ‘F’. (F) Accumulation Index for different dendritic structures when varying the effective number of synapses. Regardless of ∇EGABA or number of branches, the AccIdx is maximised at 100% effective number of synapses. As in Fig 2, ∇EGABA 0 facilitated by the branches with extra synapses. However, the difference in AccIdx between branches with and without extra synapses decreases with the number of synapses.</p

Inhibitory Level (IL) as a metric to assess the local efficacy of dendritic inhibition.

(A) The effect that an inhibitory synapse at location i (downward triangle) has on an excitatory input current at location d (circle) is termed the Inhibitory Level (IL). The IL at each location d, for stationary i at 0.4 X, is shown for the full length of the dendrite. (B) The IL is calculated by recording the membrane potential with only excitation at d (solid black line) or excitation at d and inhibition at i (dashed black line). The relative difference in the deflection of the membrane potential from rest, between Vd (without inhibition; shaded area) and Vdi (with inhibition; striped shaded area), is the IL (circles). IL with an integration time window Δt of 5 ms for d = 0.3 X (left, red circles) or d = 0.7 X (right, red circles) shows that the steady-state IL is reached within 150 ms. Small circles are IL every 5 ms. Bigger circles are every 50 ms. (C) For shunting inhibition, and given sufficient duration, the numerical calculation of IL (thin light grey line) matches the semi-analytical (medium thickness grey line) and analytical (thickest, black line) solutions. The inhibitory synapse was modelled as a fluctuating GABAA conductance, 〈g〉 = 0.001 μS, σ2 = 0.1 × 〈g〉, and the excitatory input as a constant current, 0.001 nA. Cm = 1 μF · cm-2, L = 707 μm, r = 1.0 μm, Rm = 10 MΩ · cm-2, and Raxial = 0.1 MΩ · cm-1.</p

The optimal placement of inhibitory synapses to maximise the suppression of dendritic excitability.

Given the same number of inhibitory synapses as dendritic branches we determined their optimal placement for different distribution strategies. (A) Left plots, for the “Tree” distribution (where each branch has a single inhibitory synapse at location i, example inset), the IL was measured (d) at the junction (IL0) and at the inhibitory synapses themselves (ILd = i). Due to Cl- loading, the maximum IL at the junction (IL0), large marker, occurs when inhibitory synapses are a short distance away from the junction (0.07 X). In constrast, dendrites with more branches generate maximum ILd = i when the inhibitory synapses are located closer to the junction (0.03 to 0.07 X) as more branches mean that there are more avenues for diffusion to ameliorate deleterious [Cl-]i loading. Second from right plot, Inhibitory synapses placed in the “Focal” distribution (all concentrated at one spot) result in substantial Cl- loading over 500 ms and therefore have an excitatory effect (IL d = i for each inhibitory synapse in “Branch” distributions where inhibitory synapses are placed with even spacing along a single branch. (B) The overall largest IL at any location on the dendritic tree is plotted for all varied synapse locations using the “Tree” distribution. The optimal location for inhibitory synapses to create the largest depression of dendritic excitability is ≈ 0.07 X and encircling a junction. For 2 branches (blue), the overall maximum IL is at i itself; but additional branches have their maximum IL at the junction (IL0). This location optimises the cumulative voltage-conductance inhibitory effect of the inhibitory synapses while reducing the pooling of Cl- loading via the synapses themselves. Inset, a dendrite with 4 branches and 4 synapses had its maximum IL when the inhibitory synapses were placed at 0.07 X and IL was measured at the junction (IL0). The ILd = i and the accumulation index (AccIdx = IL0 / ILd = i) are also shown for comparison. (C) EGABA and IL heatmaps with the optimal inhibitory synaptic placements (downward triangles) and the location for dampening dendritic excitability the most (arrowhead) for 2 (blue), 4 (green), 6 (purple), 8 (orange), and 16 (magenta) inhibitory synapses and branches.</p

Location and distribution of inhibitory synapses differentially affect the Inhibitory Level.

(A) Heatmaps show the maximum IL (∇EGABA = 0 mV, light green markers, top row or ∇EGABA = -2 mV, dark green markers, bottom row) for different inhibitory synapse locations, i, on a 4-branch dendritic structure. The inhibitory synapses are evenly placed from the junction (0.0 X in left column, 0.5 X in centre column, 0.8 X in right column). (B) The IL (∇EGABA = 0 mV, top and ∇EGABA = -2 mV, bottom) for each inhibitory synapse location i, in electrotonic units X, on a 4-branch dendrite. Each trace represents recordings at every excitatory input location d along the dendrite for a given synapse location i. Inhibitory synapses at the junction, i = 0 X, elicit the greatest IL. ILd = i for shunting synapses (∇EGABA = 0 mV) is the lowest when inhibitory synapses are between the junction and the end of the dendrite (0.4 X), yet ILd = i for hyperpolarising synapses (∇EGABA = -2 mV) is the lowest at the end of the dendrite (1.0 X). (C) The AccIdx for 4 branches with hyperpolarising synapses (∇EGABA = -2 mV) continues to increase, albeit with saturation, with farther locations for inhibitory synapses. Shunting synapses (∇EGABA = 0 mV), however, have their greatest AccIdx when i = 0.2 X. (D) The different trends in AccIdx between shunting (Di) and hyperpolarising (Dii) inhibitory synapses, as in ‘C’, holds for dendrites with more than 2 branches. For dendrites with 1 or 2 branches, the AccIdx is greatest when i = 0.0 X. For greater numbers of branches, the maximum AccIdx depends on whether the synapse is shunting or hyperpolarising. (E) The maximum IL is dependent on the distribution of the synapses. A dendrite with 4 branches can have 4 synapses placed in different configurations: evenly spaced from the junction on each branch (“Tree”), evenly spaced along a single branch (“Branch”), or all placed at a single location on a single branch (“Focal”). Inhibitory synapses were hyperpolarising (∇EGABA = -2 mV). (F) The IL values for the synapse distributions in ‘E’. Although the Tree configuration (green) produces an accumulative IL at the junction, the Focal distribution (turquoise) has the largest absolute IL (at d = i = 0.2 X), and the Branch distribution (lilac) facilitates a more even IL along its branch. However, both the Branch and Focal distributions are branch-selective and hence have to trade-off their gains for weaker ILs on their silent branches (lighter colours).</p

Chloride loading and shifts in EGABA progressively impact Inhibitory Level, but not Accumulation Index, over time.

(A) IL and related properties calculated at different points in time (5, 250, 500, 750, and 1000 ms), with a backward time integration window, Δt, of 5 ms. At 5 ms. A dendrite with a single branch, ‘Ai’, and a dendrite with four branches, ‘Aii’, is shown. IL with static Cl- (ILstat), and IL with dynamic Cl- (ILdyn), are identical. However, while ILstat reaches its steady-state by the next time point, ILdyn continues to decrease. Note that the heatmap is shared across time as well as IL with static or dynamic Cl-. The difference between ILstat and ILdyn, the IL Difference (ΔIL), is strongly focused at the site of the inhibitory synapse but spreads throughout the dendrite over time even while changes in EGABA remain local. The relative ILdyn (ILdyn scaled between that dendrite’s minimum and maximum ILdyn) indicates that although ILdyn changes over time, the changes are proportional. Initial ∇EGABA was -5 mV (EGABA = -70 mV, Vm = -65 mV). (B) IL over a 1000 ms period for both a single-branch dendrite, ‘Bi’, and four-branch dendrite, ‘Bii’. With prolonged input (1000 ms), ILstat decreases until the membrane capacitance is charged and ILdyn stabilises when an equilibrium is reached between Cl- influx (via GABAARs) and efflux (via KCC2). (C) The ΔIL at the synapse (solid lines, left y-axes) and ΔIL at the junction (dotted lines, right y-axes) remain in proportion to each other over time, regardless of the number of branches in the dendrite. Note that the scales are different for each axis. These are location-specific traces of what is represented across the dendrite in “Relative IL” heatmaps. (D) EGABA at the synapse (solid lines) increases from -70 mV (-5 mV ∇EGABA) to ≈ -67.5 mV over 1000 ms as in ‘A’. EGABA at the junction changes only marginally (dotted lines). Vertical dashed lines indicate the time at which EGABA reaches the corresponding horizontal integer values, ∇(t). (E) The proportional decrease in IL across the dendrite manifests as a consistent AccIdx, except for during the initial few milliseconds when the membrane capacitance is charging. The AccIdx depends on the number of branches, but not on EGABA or ΔIL.</p

Symbols, constants, parameters, and variables.

Symbols, constants, parameters, and variables.</p