Experimental exposure to ocean and freshwater acidification affects the behaviour of multiple aquatic organisms in laboratory tests. One proposed cause involves an imbalance in plasma chloride and bicarbonate ion concentrations as a result of acid–base regulation, causing the reversal of ionic fluxes through GABAA receptors, which leads to altered neuronal function. This model is exclusively based on differential effects of the GABAA receptor antagonist gabazine on control animals and those exposed to elevated CO2. However, direct measurements of actual chloride and bicarbonate concentrations in neurons and their extracellular fluids and of GABAA receptor properties in aquatic organisms are largely lacking. Similarly, very little is known about potential compensatory mechanisms, and about alternative mechanisms that might lead to ocean acidification-induced behavioural changes. This article reviews the current knowledge on acid–base physiology, neurobiology, pharmacology and behaviour in relation to marine CO2-induced acidification, and identifies important topics for future research that will help us to understand the potential effects of predicted levels of aquatic acidification on organisms.
Carbon dioxide (CO2) is continuously generated by the geological processes of weathering and volcanic activity, as well as by anthropogenic activities such as the burning of fossil fuels and cement production. Additionally, CO2 is a substrate for photosynthesis and an end product of aerobic respiration, two of the most essential biological processes in nature. In aquatic ecosystems, CO2 levels can vary locally owing to biological activity, upwelling and CO2 vents, and also globally owing to atmospheric and oceanographic processes such as winds, currents and gas exchange with the atmosphere. Since the onset of the industrial revolution, anthropogenic activities have induced a steep elevation in atmospheric CO2 levels and have also increased average CO2 levels in surface ocean waters (Sabine et al., 2004). Because CO2 hydration produces H+ that decreases seawater pH, this phenomenon has been termed ‘ocean acidification’ (OA) (Caldeira and Wickett, 2003).
The initial concern regarding OA was that the additional H+ would react with CO32− in seawater and the CaCO3 in exoskeletons of certain marine organisms, impairing calcification (Kleypas and Langdon, 2006). However, subsequent laboratory experiments on marine fish exposed to values of pH/CO2 predicted for the end of this century and beyond revealed impacts on additional organisms and processes, such as embryonic and larval development (Frommel et al., 2012, 2016; Rossi et al., 2015), otolith growth (Checkley et al., 2009; Munday et al., 2011), reproduction (Miller et al., 2013), metabolic rate (Couturier et al., 2013; Rummer et al., 2013; Enzor et al., 2013) and behaviour (Allan et al., 2013; Dixson et al., 2010; Domenici et al., 2012; Hamilton et al., 2013; Munday et al., 2009, 2010, 2016; Rossi et al., 2015); however, it is worth noting that these effects are highly variable and depend on the species, experimental conditions, parameters analyzed and experimental techniques used. Most of these effects were proposed to be due to acid–base (A–B) regulatory processes, leading to altered ionic concentrations, energy expenditure and allocation; however, the specific molecular and cellular mechanisms remain largely unexplored.
OA-induced alteration of behaviour represents a unique case for which a specific mechanism has been proposed and tested: it is thought to result from a reversal of ionic flux through neuronal gamma-aminobutyric acid type A receptors (GABAARs) owing to an alteration of [Cl−] and/or [HCO3−] that may result from A–B regulatory responses. In this Review, we assess the supporting data and assumptions of the ‘GABAAR model’, and propose specific topics that, in our opinion, require further experimentation in order for this model to be validated, refuted or expanded. We begin by reviewing the original experiments that found an OA-induced alteration of fish behaviour and proposed alteration of GABAAR as a cause. We then discuss basic aspects of neurobiology and acid–base regulation relevant for the GABAAR model, and propose essential experiments that must be conducted to support, expand or refute the GABAAR model. Finally, we identify additional neurobiological mechanisms that should be affected, assuming the GABAAR model is correct.
Discovery of OA-induced behavioural alteration
In 2009, Munday and colleagues reported that orange clownfish (Amphiprion percula) larvae reared in seawater with a partial pressure of CO2 (PCO2) of ∼1050 µatm (pH 7.80) in the laboratory demonstrated an altered response to settlement olfactory cues administered in a 2-min, two-channel choice flume test (Munday et al., 2009). While larvae reared in control seawater (PCO2 ∼440 µatm; pH 8.15) completely avoided the side of the water flume with olfactory cues from pungent tree leaves and from parents, larvae reared in elevated PCO2 spent almost all of their time in the side with those odours. The responses to cues from other tree leaves, grass and anemone were also impaired, although less dramatically. Interestingly, larvae reared in a much higher PCO2, 1700 µatm (pH 7.60), did not respond to any of the cues presented, suggesting that there are additional effects at higher PCO2. Larvae exposed to elevated CO2 had the same external appearance and nasal cavity morphology as control fish, ruling out developmental effects and damage to olfactory organs.
brain interstitial fluid
reversal potential for GABAAR
K+/2Cl− cotransporter 2
Na+/K/2Cl− cotransporter 1
partial pressure of CO2
Another study conducted concurrently by the same group reported that the detection of predator olfactory cues was also altered by acidifed seawater in the same species (Dixson et al., 2010). In this case, the choices in the two-channel choice flume were untreated seawater and seawater with olfactory cues from predator or non-predator fish. There were no differences in choice between newly hatched larvae reared in control and acidified seawater; both groups preferred untreated seawater over seawater with any fish olfactory cues, and both preferred cues from non-predator over predator fish. However, settlement-stage larvae (11 days post-hatch) reared in CO2-acidified seawater did show important significant differences compared with controls: they preferred predator cues to untreated seawater, and demonstrated no preference between cues from predator and non-predator fish.
A third paper (Munday et al., 2010) reported that the onset timing of olfactory and behavioural alteration in clownfish larvae was dependent on the magnitude of the CO2 elevation, taking approximately 4 days after exposure to 700 µatm CO2, but only 2 days following exposure to 860 µatm CO2. Furthermore, it reported three other important findings: (1) the OA effects on clownfish larvae were reversible after exposure to control seawater for 2 days; (2) the effects were also evident in wild-caught Pomacentrus wardi damselfish larvae; and (3) when released back to the reef, P. wardi settlement-stage larvae exposed to elevated CO2 in the laboratory experienced significantly higher mortality compared with larvae exposed to control CO2 (Munday et al., 2010). These three pioneer studies suggested that future OA could have important deleterious consequences for fish populations, and also hinted at a CO2 dose-dependent, reversible mechanism that required some time to take effect. A few years later, another seminal paper (Nilsson et al., 2012) proposed that the mechanism behind these behavioural disruptions related to changes in [Cl−] and [HCO3−] in blood plasma and neurons as a result of A–B regulation, which caused an alteration of neuronal GABAAR function and downstream effects on fish behaviour.
Series of membranes that separate brain interstitial fluid and cerebrospinal fluid from blood. It is composed of endothelial cells, astrocyte end feet and a thick fibrous basement membrane, and is highly selectively permeable to molecules.
Branching network of capillaries and epithelial cells located in each of the brain ventricles (four in humans). The choroid plexus secretes the cerebrospinal fluid.
Equilibrium potential (Eion)
The membrane potential at which there is no net movement of an ion through a permeable ion channel.
Membrane potential (Vm)
The voltage difference between the intracellular and extracellular compartments.
GABAAR reversal potential (EGABA)
The membrane potential at which there is no net movement of Cl− and HCO3− ions through GABAARs.
The GABAAR model
The concepts behind the elegant GABAAR model are grounded on decades of basic research on fish A–B regulation and mammalian neurobiology. Firstly, exposure to elevated CO2 in the environment is known to result in a proportional increase in CO2 in the blood, a condition known as hypercapnia (Table 1). Hypercapnic aquatic organisms typically restore blood A–B balance by upregulating active H+ excretion and accumulating HCO3− in physiological fluids (reviewed in Evans et al., 2005; Larsen et al., 2014). In fish exposed to high CO2 levels (>10,000 µatm) in both freshwater and seawater, the increased [HCO3−] in blood plasma is associated with decreased [Cl−], at a ratio close to 1:1 (Heisler, 1988; Larsen et al., 1997; Toews et al., 1983) (Table 1). Secondly, it is known that ion flow through GABAARs can reverse – during development, the mammalian fetal brain experiences an increase in intracellular [Cl−] that reverses the (normally inward) Cl− flux through GABAARs – and GABAARs also display some permeability to HCO3− (Bormann et al., 1987; Inomata et al., 1986). Under GABA-hyperactivating conditions, altered Cl− and HCO3− gradients can reverse net ionic fluxes through GABAARs, turning their function from inhibitory to excitatory (Staley et al., 1995; Stein and Nicoll, 2003), thus affecting neuronal action potential generation and multiple neuronal functions (see Basic neurobiology considerations). Because OA is a mild case of hypercapnia, Nilsson et al. (2012) reasoned that it would result in slight HCO3− accumulation and Cl− loss in extracellular and intracellular fluids in a manner consistent with the reversal of GABAARs from inhibitory to excitatory (Fig. 1). To test this hypothesis, they pre-treated control and CO2-exposed clownfish with gabazine (an arylaminopyridazine derivative also known as SR-95531), a specific GABAAR antagonist (Heaulme et al., 1986), and examined their response to olfactory predator cues (Nilsson et al., 2012). As predicted, gabazine restored predator avoidance in fish exposed to elevated CO2, and it did not have any effect on control fish, which was interpreted as evidence of ‘reversal’ of the effect on GABAAR currents. The term ‘reversal’ will be used throughout this Review; however, it is important to clarify that this is not necessarily a full reversal of function, as GABAARs can still be inhibitory at depolarized potentials (see Basic neurobiology considerations). This has also been referred to as a ‘switch’ in GABAAR action in other studies (see Tyzio et al., 2006).
Nilsson et al. (2012) sparked a flurry of studies in which gabazine was applied to a variety of animals that were exposed to elevated CO2 and subjected to diverse tests (Table 2). For the most part, gabazine reversed the effects of elevated CO2 (reviewed in Heuer and Grosell, 2014; Nilsson and Lefevre, 2016). One of those studies using gabazine was our own (Hamilton et al., 2013); working on the California splitnose rockfish (Sebastes diploproa), we found increased anxiety-like behaviour in fish exposed to ∼1100 µatm CO2 (pH 7.75) for 7 days and subjected to the light/dark preference test (Hamilton et al., 2013). This test is routinely used in biomedical research to assess GABAAR function in rodents (Bourin and Hascoët, 2003), and has also been validated for fish (Maximino et al., 2010a,b; Holcombe et al., 2013). Briefly, an animal is placed in the middle of an arena in which half of the walls are white and half are black, and time spent in the different areas of the arena is recorded, ideally using automated motion-tracking software. This test presents the animal with a conflict between exploring a new environment and avoiding the unfamiliar. Because administration of anxiogenic drugs (see Glossary) increases the time spent in the dark area of the arena, and anxiolytic drugs (see Glossary) increase the time spent in the light area (Bourin and Hascoët, 2003), this test is said to assess ‘anxiety-like’ behaviour. GABAAR antagonists such as gabazine are potent anxiogenics. Thus, the light/dark preference test is an indication of anxiety-like behaviour and GABAAR function. This test is not necessarily relevant for animal performance in the wild; however, this point does not matter for the purpose of studying GABAAR function.
In our experiments, we found that rockfish exposed to elevated CO2 spent more time in the dark area of the light/dark arena. But how can we know that this represented increased anxiety-like behaviour for a rockfish? The key was that gabazine increased the time that control fish spent in the dark area, thus causing them to behave like CO2-exposed rockfish, but it did not affect CO2-exposed rockfish (Hamilton et al., 2013). In other words, CO2 exposure likely induced neuronal hyperexcitability, which resulted in increased anxiety-like behaviour, an effect that was mimicked by blocking GABAARs with gabazine in control fish. We concluded that gabazine did not have any effect on CO2-exposed rockfish in this test because their anxiety levels had already reached a maximum. In addition, these results have three important, often overlooked and misinterpreted implications: (1) gabazine can have anxiogenic effects on control fish; (2) gabazine does not necessarily reverse the phenotype resulting from elevated CO2 exposure; instead, its effect depends on the specific experimental conditions/tests; and (3) blocking of GABAARs with gabazine presumably increases excitatory neuronal activity in fish with normal GABAAR function. Thus, gabazine could help to counteract any condition that reduces neuronal excitability, regardless of that condition being originally caused by impaired GABAAR function (see Basic neurobiology considerations).
Additional mechanistic support for the GABAAR model was provided by a second set of experiments using the GABAAR agonist muscimol in a ‘shelter test’ (Hamilton et al., 2013). Unlike the commonly used anxiolytic drugs benzodiazepines and barbiturates, which bind to GABAAR regulatory sites, muscimol binds to the same site as GABA and therefore activates GABAARs independently of GABA release from presynaptic neurons (Frølund et al., 2002) (Fig. 1). Thus, if the GABAAR model is valid, muscimol should increase anxiety levels of CO2-exposed fish, but decrease it in control fish. However, the light/dark test already demonstrated a ceiling level of anxiety in CO2-exposed fish, so the potential effect of muscimol would not be detectable. To overcome this limitation, we used the shelter test, which is based on the propensity of juvenile rockfish to stay near kelp paddies during the juvenile life stage. Unlike the light/dark test, there were no differences in baseline behaviour between control and CO2-exposed fish in the shelter test, as both groups of fish spent similar amounts of time in close proximity to the shelter. However, with muscimol application we did observe a difference in preference for the shelter, with control fish spending more time away from the shelter exploring the arena relative to the CO2-exposed fish, who spent more time near the shelter, consistent with the GABAAR reversal proposed by Nilsson et al. (2012).
Although the effects of elevated CO2 exposure on certain fish species and behavioural tests under laboratory conditions are clear and there is also strong experimental support for the GABAAR model, there are several aspects of the normal biology of aquatic organisms that must be resolved. Specifically: (1) what are the actual [HCO3−], [Cl−] and pH levels in the relevant intra- and extracellular fluids; (2) do OA-relevant CO2 levels cause significant alterations of those parameters; and (3) what is the membrane potential (Vm; see Glossary) of neurons from marine organisms and what are the GABAAR permeabilities for Cl− and HCO3−, and how do these neurons regulate their intracellular pH? After these aspects are resolved for animals exposed to current CO2 conditions, the next questions should be: (4) are there any species-specific mechanisms that might determine species-specific responses to OA; (5) could neuronal mechanisms other than GABAAR, either related to GABA or other neurotransmitters, be affected by exposure to OA-like conditions; and (6) are there compensatory mechanisms that act over longer time scales, and when PCO2 slowly rises over generational times?
Basic neurobiology considerations
To understand the potential effects of OA on fish neurobiology, it is essential to understand some fundamental properties of neuronal functioning. Here, we review basic neurobiology concepts, mostly based on mammalian research, and identify key aspects relevant for the GABAAR model.
What are membrane, equilibrium and reversal potentials?
where R is the gas constant (8.315 J K−1 mol−1), T is the temperature in degrees Kelvin, F is the Faraday constant (96,485 Coulombs mol−1), P is the permeability of each anion across the membrane, and [ion]e and [ion]i refer to the extra- and intracellular concentrations of each ion, respectively.
where z is the valence of the ion.
The entrance of a cation or the exit of an anion shifts the Vm of the neuron to a more positive value, which is known as ‘depolarization’. Conversely, the exit of a cation or the entrance of an anion shifts Vm to a more negative value, known as ‘hyperpolarization’. If Vm is depolarized above a certain value (‘threshold’), an action potential is triggered, and this electrical signal is propagated along the neuron's axon and neurotransmitters are released at the presynaptic terminal. By contrast, if Vm is hyperpolarized, a neuron is farther from threshold and less likely to generate an action potential. Neuronal excitation is largely regulated by the neurotransmitter glutamate, which is released from presynaptic terminals of axons, diffuses across the synapse and binds to postsynaptic glutamate receptors on dendrites of the target neuron. This leads to Na+ or Na+ and Ca2+ entry (depending on the receptor to which glutamate binds) that depolarizes Vm, and therefore is excitatory. To prevent excessive excitation, the neurotransmitter GABA acts on postsynaptic GABAARs, leading to Cl− entry that hyperpolarizes Vm, and therefore is inhibitory. Proper neurological functioning depends on the balanced activity of glutamatergic and GABAergic synapses (Hille, 2001; Levinthal and Hamilton, 2015; Mele et al., 2016). However, things become more complicated because whether an ion enters or leaves the neuron and the resulting magnitude of the Vm change induced depends on the ion permeability and on the relationship between Vm and Eion. For anions such as Cl− and HCO3−, if Eanion is more negative than Vm, the anion would flow into the cell, hyperpolarizing Vm towards Eanion and making an action potential less likely. By contrast, if Eanion is more positive than Vm and a permeable channel opens, the anion will flow out of the cell, depolarizing Vm and therefore making an action potential more likely. The larger the difference between Vm and Eion, the larger the ion flux, and therefore the larger the depolarizing or hyperpolarizing effect.
The classic (and correct) method to empirically measure EGABA is with sharp electrodes that impale the cell body of the neuron. A GABAAR response is evoked by applying GABA or by injecting a current to manipulate Vm and stimulate an inhibitory postsynaptic potential, followed by anion substitutions and additional recordings to observe GABAAR-dependent changes in Vm and estimate the permeability of each anion. Whole-cell intracellular recordings and cell-attached recordings (Verheugen et al., 1999) have also been used to calculate EGABA. Under normal conditions, EGABA is more negative than Vm, and therefore it is hyperpolarizing and inhibitory. Using these methods, Kaila et al. (1989) found that increasing [HCO3−]i (by elevating intracellular pH) depolarized EGABA, and Bormann et al. (1987) reported that EGABA was depolarized 56 mV for every 10-fold change in [Cl−]i.
It is clear that under specific circumstances, the Cl− flux through GABAARs is inhibitory rather than excitatory. The degree of the change in polarity of GABAARs depends on how far the EGABA moves away from Vm. However, caution should be taken when applying the Goldman equation to neurons from a live animal, because in vivo ionic permeabilities and concentration ratios are not constant (Nicholson, 1980; Sandblom and Eisenman, 1967). Furthermore, because each parameter is correlated with the others, the Goldman equation requires knowledge of Vm and actual ion concentrations in the same neuron (or in a group of the same neuron type), and using parameters from different neurons or neuron groups will most likely give misleading results. Thus, calculating EGABA using the Goldman equation is ideal for isolated systems, such as brain slices, cultured neurons or channels in oocytes.
Regulation of GABAAR
In mammals, GABAARs are made up of five subunits that form the pore that allows anions across the cell membrane (Fig. 1). However, the number of potential combinations of subunits is astronomically high because there are 19 known homologous subunit gene products: six α, three β, three γ, three ρ, and one each of the ε, θ, δ and π subunits (Sigel and Steinmann, 2012). To date, 26 GABAARs with different subunit compositions have been identified (Olsen and Sieghart, 2008). The distinct subunits that make up the pentameric complex are important because subunit composition dictates binding affinity for GABA, pharmacological agonists and antagonists, channel kinetics, cellular localization and Cl− and HCO3− permeability, among other functional properties (Lee and Maguire, 2014). Multiple GABAAR subunits are also present in invertebrates (Martyniuk et al., 2007) and fish (Biggs et al., 2013; Martyniuk et al., 2007), but their relation to GABAAR function is much less studied. To our knowledge, only two papers so far have studied GABAAR mRNA isoform abundance in brains from OA-exposed fish (Lai et al., 2015; Schunter et al., 2016), and neither study found any major changes compared with control fish. However, changes in protein abundance, changes in specific neuron types and differential responses in OA-tolerant fish cannot be ruled out.
Another mechanism known to affect GABAAR function is changes in [Cl−]i resulting from the balance in activity of the Na+/K/2Cl− cotransporter 1 (NKCC1), which moves Cl− into the neuron, and the K+/2Cl− cotransporter 2 (KCC2), which moves Cl− out of the neuron. For example, in neurons from developing embryos, KCC2 is expressed at low levels (Banke and McBain, 2006; Ben-Ari, 2002). As a result, NKCC1 activity prevails over KCC2 activity, resulting in higher [Cl−]i (Ito, 2016), a resting Vm 10–20 mV more positive than in adult neurons (Khazipov et al., 2015), Cl− flux out of the neuron through GABAARs or glycine receptors, and excitatory Vm depolarization (Banke and McBain, 2006; Ben-Ari, 2002; Ito, 2016). A similar effect is seen in ventral spinal cord motoneurons from KCC2 knockout mice (Hübner et al., 2001), in which GABA depolarized neurons ∼21.1 mV more than in controls, consistent with increased [Cl−]i. This leads to an important question relevant to the GABAAR model: if exposure to elevated CO2 induces GABAAR reversal because of altered Cl− and/or HCO3− gradients across neuronal membranes, could neurons downregulate NKCC1 and/or upregulate KCC2 to increase [Cl−]i and thereby restore normal GABAAR inhibitory function? GABAAR function can be modulated by multiple other dynamic and long-term translational and posttranslational regulatory mechanisms – too many to describe here (the interested reader is directed to Mele et al., 2016). If the GABAAR model is correct, regulation of GABAAR function may explain the fact that some studies show no effect of elevated CO2 on fish behaviour (Jutfelt and Hedgärde, 2013, 2015; Lonthair et al., 2017). However, this hypothesis should be experimentally tested.
Gabazine is a competitive GABAAR antagonist (Heaulme et al., 1986), meaning it binds to the same active site as GABA (Fig. 1) and prevents channel opening. With the exception of our previous study that used the GABAAR agonist muscimol (Hamilton et al., 2013; discussed above), experiments using gabazine have provided the only mechanistic evidence in support of the GABAAR model thus far. Table 2 details the studies that have, to date, used gabazine on fish and invertebrates exposed to elevated CO2. In most cases, gabazine reversed the effect of elevated CO2 and restored normal behaviour. Gabazine also significantly alters the behaviour of control rockfish (Hamilton et al., 2013) and pink salmon (Ou et al., 2015). However, no other study found any effect of gabazine on behaviour (Chivers et al., 2014; Lai et al., 2015; Lopes et al., 2016; Munday et al., 2016; Nilsson et al., 2012; Watson et al., 2014) or visual processing (Chung et al., 2014) in control fish. This is an interesting point because gabazine should also affect normal inhibitory GABA regulation, inducing neuronal excitation; in fact, one of the features precluding the use of gabazine as a therapeutic agent in humans is the risk of convulsions resulting from inappropriate neuronal excitation (Enna and Bowery, 1997). A similar effect was seen in intact zebrafish (Danio rerio) brains, where gabazine increased the spontaneous firing rate of olfactory neurons, altered the dynamics of odour-induced firing, blocked fast oscillatory synchronization of local neurons and induced epileptiform activity (Tabor et al., 2008).
To confirm that the effects of gabazine on CO2-exposed aquatic animals are indeed due to alteration of GABAARs, we suggest that it will be important to test the effects of other GABA antagonists not structurally related to gabazine, such as bicuculline or picrotoxin (Johnston, 2013), or an agonist such as muscimol (Andrews and Johnston, 1979). A final consideration is that gabazine causes a net increase in excitation of the nervous system, and it would counteract any other mechanism that decreases excitatory activity, not only GABAAR reversal. For example, a theoretical OA-induced decrease in glutamate release could be ‘restored’ by gabazine, and this could be erroneously interpreted as GABAAR reversal. The GABAAR model does seem to fit with principles of basic neuroscience, but it must be validated with more than the use of gabazine and behavioural studies.
Ionic and A–B regulation considerations
Theoretical models of the effects of OA on fish GABAARs using the Goldman equation typically consider PCO2, [HCO3−], pH and [Cl−] in blood plasma and whole brain as the extra- and intracellular parameters, respectively (Heuer and Grosell, 2014; Heuer et al., 2016; Nilsson and Lefevre, 2016; Regan et al., 2016). However, only a few studies have measured these parameters in the blood plasma of fish exposed to OA-relevant conditions (i.e. PCO2 between 600 and 2000 µatm). The pattern that emerged was complete regulation of blood plasma pH and a 2–5 mmol l−1 increase in blood plasma [HCO3−] (Ern and Esbaugh, 2016; Esbaugh et al., 2016, 2012; Green and Jutfelt, 2014; Heinrich et al., 2014; Heuer et al., 2016; Strobel et al., 2012) (Table 1). Only three studies measured blood plasma [Cl−], but none of them found significant changes after exposure to OA-like conditions (Esbaugh et al., 2016; Green and Jutfelt, 2014; Heinrich et al., 2014). The lack of change in plasma [Cl−] in marine fish could be due to the difficulty in accurately measuring small changes in [Cl−] compared with ‘background’ control levels of 140–200 mmol l−1 (see Genz et al., 2008; Erlacher-Reid et al., 2011; Esbaugh et al., 2016; Lin et al., 2003; Toews et al., 1983; reviewed in Evans et al., 2005). However, it is also possible that the large range of reported values of [Cl−] reflect species-, life stage- or metabolism-specific differences. Surprisingly, very little is known about the molecular and cellular mechanisms of A–B regulation in marine bony fish. The little we do know is largely derived from whole-animal experiments that exposed adult fish to extreme hypercapnia, and is based on marine elasmobranchs or on freshwater fish models which, because of different ionic conditions in the surrounding water, are not relevant for marine fish. Most relevant to the GABAAR model, the tight link between Cl− loss and HCO3− accumulation has so far only been demonstrated for adult fish exposed to PCO2 levels ≥10,000 µatm (most notably, Toews et al., 1983), which is much higher than OA-relevant PCO2 levels. Therefore, different compensatory mechanisms during OA-relevant conditions cannot be ruled out. For example, a combination of buffering, H+ secretion and Cl−-independent HCO3− accumulation would result in elevated plasma [HCO3−] without associated Cl− loss (Table 1, Fig. 2C). Another common misconception is that elevated PCO2 during OA will diffuse inside fish and elevate blood CO2. However, as explained in detail in Melzner et al. (2009), values of PCO2 in fish internal fluids are several-fold higher than seawater PCO2, even for the most extreme case of OA (Table 1). Thus, although OA indeed results in elevated blood PCO2, it does so by reducing the diffusive rate of metabolic PCO2 excretion to seawater (Fig. 2). Far from a technicality, this affects the magnitude of the A–B disturbance, and potentially also the regulatory mechanisms involved (Table 1, Fig. 2).
An urgent topic of future research is elucidating common, species-specific and life-stage-specific mechanisms of A–B regulation in the skin, gill and choroid plexus (see Glossary) of fish exposed to control and OA-relevant CO2 levels. Complicating this quest, marine fish gills are constantly secreting NaCl to maintain blood ionic balance. This process uses enzymes and ion-transporting proteins that may overlap with A–B balance (most notably, the Na+/K+-ATPase) (Fig. 2B). Because ionoregulation is, by far, more energy demanding than A–B regulation, it imposes baseline protein levels against which detecting putative changes in enzyme activity and mRNA and protein abundance in response to OA becomes challenging. Another intriguing question is whether the robust ionoregulatory mechanisms of marine fish in gill, skin, kidney and intestine (reviewed in Larsen et al., 2014), which can maintain blood plasma [NaCl] ∼200 mmol l−1 lower than seawater, can handle the few additional millimoles of Cl− expected to result from blood A–B regulation during OA exposure.
To our knowledge, only Heuer et al. (2016) have estimated A–B parameters in the brains of fish exposed to OA-relevant PCO2 levels. They reported elevated pH and [HCO3−] in brain homogenates of spiny damselfish exposed to 1900 µatm (pH 7.60) for 4 days. These values were taken as representative of neuronal cytoplasm; [Cl−] in blood or brain was not measured. When plasma and whole brain [HCO3−] values were plugged into the EGABA (Goldman) equation together with theoretical values from intra- and extracellular [Cl−] and theoretical GABAAR Cl− and HCO3− permeability ratios, the results generally supported the GABAAR model. However, these results are not without potential issues, amongst which is the very high PCO2 of ∼16,000 µatm that was estimated for whole brains from control fish (which was surprisingly unchanged in OA-exposed fish) as well as the theoretical intracellular [Cl−] of 8 mmol l−1, which was also considered to not change in OA-exposed fish. Another interesting point is that CO2 has been reported to impair olfactory predator discrimination at levels as low as 700 µatm (Munday et al., 2010), which are very unlikely to induce changes in [HCO3−] and [Cl−] large enough to cause significant alteration of EGABA. Is it possible that the mechanisms that induce behavioural alteration at mildly increased CO2 levels (≥700 µatm) are different from those acting at higher CO2 levels (∼1900 atm)? This might explain why larvae reared at 1700 µatm (pH 7.60) did not respond to any olfactory cues (Munday et al., 2009). Similarly, the effects seen in different behavioural tests might be caused by different mechanisms.
The actual fluids that should be considered in order to confirm the GABAAR model are the cerebrospinal fluid (CSF) or BIF (representing the extracellular fluid) and the neuron cytoplasm (representing the intracellular fluid) (Fig. 3, Table 3). This is an important point, because CSF and BIF have different ionic and A–B composition compared with blood plasma (reviewed in Damkier et al., 2013; Syková and Nicholson, 2008), neurons have different composition compared with whole brain homogenate, and the Goldman equation is extremely sensitive to even minute differences in the parameters used. In fact, a tiny difference in one of the parameters can change the calculation of GABAAR equilibrium potential from hyperpolarizing to depolarizing in relation to Vm, and minute differences in various parameters can compensate for (or potentiate) each other's effects on equilibrium potential (see Basic neurobiology considerations). Furthermore, at least in humans, the brain is composed of similar numbers of neurons and glial cells (Azevedo et al., 2009), so measurements on brain homogenates provide an average estimation of the two (plus contaminating CSF and BIF). Additionally, the choroid plexus, blood–brain barrier (see Glossary) and astrocytes tightly regulate the ionic and A–B composition of CSF and BIF (reviewed in Damkier et al., 2013; Syková and Nicholson, 2008). In fact, the chief evolutionary selective pressure favouring the evolution of the blood–brain barrier is believed to be the maintenance of a stable ionic environment to promote neuronal function (Abbott, 1992; Cserr and Bundgaard, 1984). This is a very important point for the GABAAR model, because fish experience large fluctuations in blood plasma [NaCl] and [HCO3−], for example, during migration between freshwater and seawater (e.g. Maxime et al., 1990; reviewed in Evans et al., 2005), in the postprandial period (Bucking et al., 2009; Cooper and Wilson, 2008; Wood and Bucking, 2011; Wood et al., 2005) and upon temperature changes (reviewed in Heisler, 1988). If fish were unable to maintain a stable ionic composition of the CSF and BIF and the GABAAR model was correct, these animals would regularly experience olfactory disturbances such as lack of predator odour discrimination, with the subsequent obvious negative impact on survival.
The few available studies on fish CSF are on elasmobranchs, and have reported higher [Na+], [Cl−], [HCO3−] and PCO2, and lower pH and protein-buffering capacity compared with blood (Maren, 1972, 1977; Smith et al., 1929; Wood et al., 1990). At least in the skate Raja ocellata, active aerobic metabolism by brain cells results in CSF/BIF having PCO2 levels that are approximately threefold higher compared with blood plasma, and ∼0.25 pH units more acidic (Wood et al., 1990). In addition, the blood–brain barrier of R. ocellata is highly permeable to CO2 (Wood et al., 1990), which is advantageous for CO2 diffusion to blood plasma down its partial pressure gradient. However, the blood–brain barrier is also permeable to inwardly directed CO2 diffusion, and exposure to environmental hypercapnia (∼10,000 µatm) induces a proportional increase in CSF PCO2 (Wood et al., 1990). Similar to blood plasma, the initial drop in CSF PCO2 is compensated by HCO3− accumulation. Can this process result in changes in [Cl−] and [HCO3−] in the CSF consistent with the GABAAR model? This question can only be answered by performing experiments to elucidate fish CSF and BIF composition and regulatory mechanisms, which should consider the following points: (1) the high PCO2 and low pH in the CSF imply that OA-relevant PCO2 elevations will induce smaller A–B disturbances in CSF compared with blood plasma; (2) in mammals, HCO3− secretion into the CSF and BIF takes place by both Cl−- and Na+-dependent mechanisms (Damkier et al., 2013; Hladky and Barrand, 2016), implying that HCO3− accumulation does not necessarily mean a reciprocal reduction in [Cl−]; and (3) inhibition of choroid plexus carbonic anhydrase significantly reduces both HCO3− and Cl− transport into the CSF, implying that a vast majority of secreted HCO3− originates from aerobic CO2 production in choroid plexus cells, and that there is some degree of HCO3−/Cl− co-transport (Maren, 1988; Maren and Broder, 1970).
Because the GABAAR model also implies intracellular HCO3− accumulation in exchange for Cl− (Nilsson et al., 2012; Nilsson and Lefevre, 2016), the neuronal mechanism for intracellular pH regulation is a final point to consider. To our knowledge this has not been studied in fish neurons, but mammalian neurons typically regulate their intracellular pH by a combination of Na+/H+ exchangers, Na+/HCO3− co-transporters, Na+-dependent Cl−/HCO3− exchangers and Cl−/HCO3− exchangers (reviewed in Ruffin et al., 2014). If we assume that fish have similar mechanisms of ion transport, a linear inverse correlation between HCO3− and Cl− concentrations is unlikely to occur in fish, because Na+ would compensate for at least part of the excess negative charge resulting from HCO3− accumulation.
Fish are the most diverse group of vertebrate animals and occupy ecological niches with very diverse ionic, A–B and temperature conditions. Therefore, species-specific mechanisms of CSF, BIF and neuronal A–B regulation could very well explain differential sensitivity to OA in a GABAAR-dependent manner. In addition, the GABAAR model has also been proposed to explain the effects of OA on the behaviour of a few marine invertebrates (Rossi et al., 2016; Watson et al., 2014). With the exception of cephalopods, marine invertebrates lack a blood–brain barrier, which suggests a lesser ability to regulate the micro-environment around neurons compared with mammals (Cserr and Bundgaard, 1984). However, the nervous central ganglia of marine invertebrates possess other structural adaptations that isolate neuronal processes from the hemolymph (Cserr and Bundgaard, 1984). In addition, [Cl−] in the hemolymph of marine invertebrates is similar to seawater at ∼560 mmol l−1 (Larsen et al., 2014), which raises the question of whether the potential reduction in hemolymph [Cl−] in response to OA would be large enough to induce a reversal of GABAAR.
Other potential effects of OA on neuronal function
If exposure to OA-relevant elevations in PCO2 indeed changes [HCO3−] and [Cl−] in brain intra- and extracellular fluids, this would not just affect the function of central GABAARs; other neurobiological aspects that could be affected include glycine receptors, neuronal network dynamics, certain K+ channels, astrocyte–neuron metabolic communication and CO2-sensing peripheral neurons, to name a few. The implications of OA-associated effects on these features are discussed below.
Glycine receptors are abundant inhibitory ligand-gated channels in the mammalian spinal cord, the brainstem, and the forebrain hippocampus and prefrontal cortex (Legendre, 2001; Salling and Harrison, 2014). Upon binding of the neurotransmitter glycine, these channels open, allowing Cl− to flow according to the reversal potential for glycine receptors (Eglycine) and Vm as explained above. As for GABAARs, activation of glycine receptors under normal conditions hyperpolarizes the neuron via Cl− influx, and in neurons of the immature nervous system, activation of glycine receptors depolarizes the neuron owing to Cl− efflux (Avila et al., 2013). Also similar to GABAARs, glycine receptors are permeable to HCO3− (Bormann et al., 1987). Thus, if OA-like conditions affect GABAARs according to the GABAAR model, glycine receptors should undoubtedly also be affected. Because glycine receptors are involved in generating motor patterns for locomotion and spinal reflex actions (Avila et al., 2013), future research should investigate OA-induced changes in reversal potential in these receptors as well as the potential physiological and behavioural implications. Furthermore, if both EGABA and Eglycine are reversed during OA and no compensatory mechanism exists, their effects on neuronal hyperexcitation would be additive.
Mammalian cortical neurons fluctuate between a resting hyperpolarized ‘down state’ and another ‘up state’ that is more depolarized, can last up to hundreds of milliseconds, and are close to the action potential threshold (Wilson, 2008). In a cellular network, neurons move between these two states in a rhythmic manner and, although the exact function is unknown, this is thought to help synchronize distant neuronal populations (Hahn et al., 2006) and maintain attention and memory formation (Holcman and Tsodyks, 2006). This important feature of neurons is relevant to the function of voltage and ligand-gated ion channels and whether they will reach the threshold for action potential generation. For example, when neurons are in a down state, the reversal potential for Cl− can be higher than the membrane potential, so the opening of GABAARs can be excitatory in nature; however, in an up state, GABAAR regains its inhibitory action (Plenz, 2003). Intracellular recordings in larval zebrafish demonstrate that Purkinje neurons also fluctuate between up states, when they fire bursts of action potentials, and down states, when only short bursts of action potentials occur with AMPA receptor activation (Sengupta and Thirumalai, 2015). Taken together, a shift in EGABA would have a prominent effect when the neuron is in the down state but not in the up state. As we learn more about the down and up states of neurons during different behaviours (e.g. mobile versus immobile, exploring, searching for food, under different stress levels), we will hopefully be able to discern under which circumstances an OA-induced change in EGABA may affect neuronal dynamics, and how these dynamics might be affected by the behavioural state of the organism.
Other potential effects of HCO3−
In addition to potential reversal of EGABA and Eglycine, the elevation in intra- and extracellular [HCO3−] during OA predicted by the GABAAR model could affect other ion channels and signalling pathways. For example, changes in [HCO3−] could modulate K+ channels in neurons (Jones et al., 2014; Kaila et al., 1997) and astrocytes (Ma et al., 2012), or affect metabolic coupling between these two cell types (Choi et al., 2012). A potential role for such effects in OA-induced behavioural alterations remains to be explored.
CO2-sensing peripheral neurons
The GABAAR model proposes an OA-induced alteration of neuronal function in the brain; however, it is possible that peripheral neurons are additionally, or alternatively, affected. Because CO2-sensing peripheral neurons are directly exposed to seawater and not immersed in BIF and CSF, the ionic considerations that may result in neuronal malfunction would be different compared with brain neurons. For example, seawater acidification can reduce the sensitivity of chemosensing neurons in the barbels of Japanese sea catfish Plotosus japonicus (Caprio et al., 2014). Although the magnitude of the seawater acidification in that study was within the range of OA, a caveat was that acidification was experimentally achieved by addition of HCl instead of CO2.
Another example of peripheral CO2-sensing neurons is the neuroepithelial cells present in the gills of adult zebrafish. Vm of these cells becomes gradually depolarized when exposed to increasing PCO2 from control levels to 0.5% CO2 (∼5000 µatm) (Qin et al., 2010), which encompasses the OA-relevant PCO2 range. Zebrafish neuroepithelial cells have been proposed to regulate important cardiorespiratory processes such as increasing ventilatory amplitude in adult zebrafish (Vulesevic et al., 2006) and tachycardia in 7-day-old larval zebrafish (Miller et al., 2014). Interestingly, the ventilatory response was blunted in zebrafish chronically exposed to hypercapnia (Vulesevic et al., 2006), suggesting potential acclimation. And in zebrafish larvae, the tachycardia response to hypercapnia was absent in 7-day-old larval zebrafish (Miller et al., 2014), showing life-stage-specific differences. Thus, as reported in freshwater zebrafish, OA-relevant CO2 disturbances could potentially affect CO2-sensing neurons in marine fish and trigger physiological responses, which could be compensatory or maladaptive. However, this type of neuron has not been described in any marine fish to date, and their CO2-sensing mechanisms and sensitivity may well differ from those of zebrafish because of the different A–B properties of seawater and freshwater.
While short exposure to OA-relevant elevations in CO2 induces clear alterations in neurobiology and behaviour in aquatic organisms, the mechanisms behind these effects are not clear. To date, the only mechanistic explanation is an alteration of GABAAR function caused by putative changes in [Cl−] and [HCO3−] in intra- and/or extracellular fluids. At this point, we would like to highlight the importance of basic science research, without which the identification of this putative mechanism would have been impossible, or at least severely delayed. Indeed, the GABAAR model is based on over a century of basic research on A–B and ionic regulation, both at the comparative and human health levels, as well as decades of research that perfected the behavioural techniques that allowed us to identify effects caused by OA.
When OA was identified as a potential problem for marine animals and the deleterious effects on fish behaviour were noticed, the GABAAR mechanistic model was proposed and experimentally tested relatively shortly after. Similarly, more basic science research is required to confirm, expand or refute the GABAAR model. Together with long-term acclimation and trans-generational studies, mechanistic information on physiological processes potentially affected by OA will allow us to identify species- and life-stage-specific differences and responses to OA that could determine the trite ‘winners and losers’ of this process. Some of the relevant avenues of research have been highlighted throughout this Review, which we hope will serve as frame of reference for future work.
The authors are grateful to Mr Dustin Newton for helping compile papers related to gabazine.
M.T. was supported by grants from the National Science Foundation (NSF) [IOS 1354181 and EF 1220641]; T.J.H. was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) [Discovery Grant 04843].
The authors declare no competing or financial interests.