The contribution of refractoriness to arrhythmic substrate in hypokalemic Langendorff-perfused murine hearts

The clinical effects of hypokalemia including action potential prolongation and arrhythmogenicity suppressible by lidocaine were reproduced in hypokalemic (3.0 mM K+) Langendorff-perfused murine hearts before and after exposure to lidocaine (10 μM). Novel limiting criteria for local and transmural, epicardial, and endocardial re-excitation involving action potential duration (at 90% repolarization, APD90), ventricular effective refractory period (VERP), and transmural conduction time (Δlatency), where appropriate, were applied to normokalemic (5.2 mM K+) and hypokalemic hearts. Hypokalemia increased epicardial APD90 from 46.6 ± 1.2 to 53.1 ± 0.7 ms yet decreased epicardial VERP from 41 ± 4 to 29 ± 1 ms, left endocardial APD90 unchanged (58.2 ± 3.7 to 56.9 ± 4.0 ms) yet decreased endocardial VERP from 48 ± 4 to 29 ± 2 ms, and left Δlatency unchanged (1.6 ± 1.4 to 1.1 ± 1.1 ms; eight normokalemic and five hypokalemic hearts). These findings precisely matched computational predictions based on previous reports of altered ion channel gating and membrane hyperpolarization. Hypokalemia thus shifted all re-excitation criteria in the positive direction. In contrast, hypokalemia spared epicardial APD90 (54.8 ± 2.7 to 60.6 ± 2.7 ms), epicardial VERP (84 ± 5 to 81 ± 7 ms), endocardial APD90 (56.6 ± 4.2 to 63.7 ± 6.4 ms), endocardial VERP (80 ± 2 to 84 ± 4 ms), and Δlatency (12.5 ± 6.2 to 7.6 ± 3.4 ms; five hearts in each case) in lidocaine-treated hearts. Exposure to lidocaine thus consistently shifted all re-excitation criteria in the negative direction, again precisely agreeing with the arrhythmogenic findings. In contrast, established analyses invoking transmural dispersion of repolarization failed to account for any of these findings. We thus establish novel, more general, criteria predictive of arrhythmogenicity that may be particularly useful where APD90 might diverge sharply from VERP.
Introduction
Hypokalemia exerts important clinical effects on cardiac function that in some respects resemble those seen in the congenital long-QT syndromes (LQTS). Thus, both conditions result in electrocardiographic QT prolongation [12, 23] and premature ventricular depolarizations (PVDs), which may result in the initiation of an arrhythmic activity [41, 52]. In contrast to the cardiac effects of hypokalemia, arrhythmic activity in LQTS has been extensively studied and has often been attributed to after-depolarizations occurring against a background of re-entrant substrate [2, 36, 44]. Re-entry may take place as a result of inhomogeneities producing regions of conduction block, which lead to wave-break and circus movement [21, 37] or altered repolarization gradients, which lead to wave reflection [1]. In this situation, depolarization propagates from active cells into previously active adjacent regions, establishing re-entrant circuits. These may become established either locally or over larger regions of the myocardium, such as across the thickness of the myocardial wall.
Tendencies to transmural re-entrant excitation in models of LQTS have been previously analyzed in terms of transmural dispersions of repolarization (TDR) obtained from the positive part of the difference between respective endocardial and epicardial stimulation to repolarization times [36, 44, 45]. In human LQTS, increases in the interval between the peak and full recovery of electrocardiographic precordial T waves (Tpeak to Tend), previously shown to reflect TDR [54], are indeed associated with arrhythmic activity [33]. Certainly, recent reports correlate Tpeak to Tend to arrhythmic risk more closely than more widely accepted indicators such as corrected QT interval and QT dispersion [53]. However, such re-excitation may also be limited by recovery from refractoriness; re-entrant excitation would require this to precede the return of the membrane potential to threshold [40]. Certainly, class 1 antiarrhythmic drugs such as lidocaine are known to increase ventricular effective refractory period (VERP) [28]. Yet, such use of spatial differences in action potential repolarization times to quantify arrhythmic substrate neither explicitly considers changes in VERP nor applies such criteria to potential local as opposed to transmural re-excitation.
This paper associates for the first time the proarrhythmic effect of hypokalemia with a significant decrease in VERP, despite contrasting prolongation of action potentials, in agreement with computer-modeling studies of action potential waveforms using established data on the various effects of hypokalemia on ionic conductivity properties of ventricular myocytes. Furthermore, it associates the antiarrhythmic effects of lidocaine with a significant increase in VERP, despite having little effect on action potential duration, in agreement with clinical observations. Analyses using TDR were insufficiently sensitive to account for any of these arrhythmogenic findings. This study accordingly established more general novel criteria that would provide necessary conditions for local and transmural and epicardial and endocardial re-excitation incorporating not only action potential duration but also VERP and conduction times that may be particularly useful when action potential duration differs sharply from VERP. These criteria successfully accounted for all the arrhythmogenic findings.
Materials and methods
Experimental animals
Mice were housed in an animal facility at 21 ± 1°C with 12 h light/dark cycles. Animals were fed sterile chow (RM3 Maintenance Diet, SDS, Witham, Essex, UK) and had free access to water. Wild-type 129 Sv mice aged 3–6 months were used in the experiments. All procedures complied with UK Home Office regulations (Animals [Scientific Procedures] Act 1986).
Solutions
All solutions were based on bicarbonate-buffered Krebs-Henseleit solution (mM: NaCl 119, NaHCO3 25, KCl 4, KH2PO4 1.2, MgCl2 1, CaCl2 1.8, glucose 10 and Na-pyruvate 2; pH adjusted to 7.4) bubbled with 95% O2/5% CO2 (British Oxygen Company, Manchester, UK). Hypokalemic (3.0 mM K+) solutions were prepared by reducing the quantity of KCl added. Lidocaine-containing normokalemic and hypokalemic solutions were prepared by adding lidocaine (Sigma–Aldrich, Poole, UK) to a final concentration of 10 μM.
Preparation
A Langendorff-perfusion protocol previously adapted for murine hearts [4] was used. In brief, mice were killed by cervical dislocation (Schedule 1: UK Animals [Scientific Procedures] Act 1986), and hearts were then quickly excised and placed in ice-cold bicarbonate-buffered Krebs-Henseleit solution. A short section of aorta was cannulated under the surface of the solution and attached to a custom-made 21-gauge cannula filled with the same solution using an aneurysm clip (Harvard Apparatus, Edenbridge, Kent, UK). Fresh Krebs-Henseleit solution was then passed through 200 and 5 μm filters (Millipore, Watford, UK) and warmed to 37°C using a water jacket and circulator (Techne model C-85A, Cambridge, UK) before being used for constant-flow retrograde perfusion at 2–2.5 ml/min using a peristaltic pump (Watson-Marlow Bredel model 505S, Falmouth, Cornwall, UK). Hearts were regarded as suitable for experimentation if, on rewarming, they regained a healthy pink colour and began to contract spontaneously.
Electrophysiological measurements
An epicardial monophasic action potential (MAP) electrode (Hugo Sachs, Harvard Apparatus) was placed against the basal region of the left ventricular epicardium. In addition, a small access window was created in the interventricular septum to allow access to the left ventricular endocardium [9]. A custom-made endocardial MAP electrode composing two twisted strands of high-purity Teflon-coated 0.25 mm diameter silver wire (Advent Research Materials, UK) was constructed. The Teflon coat was removed from the distal 1 mm of the electrode, which was then galvanically chlorided to eliminate DC offset, inserted and placed against the septal endocardial surface. MAPs were amplified, band-pass filtered (0.5 Hz to 1 kHz: Gould 2400S, Gould-Nicolet Technologies, Ilford, Essex, UK), and digitized at a sampling frequency of 5 kHz (micro1401, Cambridge Electronic Design, Cambridge, UK). Analysis of MAPs was performed using Spike II software (Cambridge Electronic Design).
Experimental protocol
A bipolar platinum stimulating electrode (1 mm interpole spacing) was placed on the basal surface of the right ventricular epicardium. Square-wave stimuli (Grass S48 stimulator, Grass-Telefactor, Slough, UK) of 2 ms duration and with amplitudes of twice the excitation threshold were initially applied to hearts at a constant cycle length of 125 ms for at least 10 min and until MAPs showed stable baselines, rapid upstroke phases that reached consistent amplitudes and smooth repolarization phases [30]. Hearts were then exposed to test solutions for 20 min, during which time stimulation was continued, before subsequent recordings were made.
Intrinsically evoked MAPs were recorded in the absence of stimulation while action potential duration (at 90% repolarization, APD90) and stimulation to depolarization latency were determined during regular stimulation at a constant interstimulus interval of 125 ms. Hearts were then subjected to an adapted form of an extrasystolic electrical stimulation procedure previously used to assess arrhythmogenicity and refractoriness in both human [43] and murine [22] studies of congenital LQTS, described in detail later. The possibility that events evoked by extrasystolic stimuli rather represented motion artifacts was excluded by their being reproducible between hearts and appearing identical in both electrodes.
All data are presented as means±standard errors of the means and include both the number of repetitions and the number of hearts. Comparisons were made using analysis of variance (significance threshold set at P ≤ 0.05).
Modeling
The charge-difference model of Fraser and Huang [16, 18] was adapted to permit computational modeling of the murine ventricular cardiac myocyte using ion channel equations and parameters from the model of Bondarenko et al. [6] with the Na+/K+-ATPase model of Hernandez et al. [24]. The use of charge-difference modeling allowed the model to reach a true beat-to-beat steady state that was independent of initial intracellular ion concentrations [17], thus permitting simulation of the influence of changes in extracellular ion concentrations that are well recognized to influence Na+/K+-ATPase activity, and hence steady-state intracellular ion concentrations.
Model cells were studied under normokalemic (5.2 mM K+) conditions with normal ion permeabilities, hypokalemic (3 mM K+) conditions with these same ion permeabilities and hypokalemic (3 mM K+) conditions with the K+ permeabilities of channels carrying the repolarizing currents IK1 and Ito reduced by 20%, replicating the effect of such hypokalemia on transmembrane K+ permeabilities observed experimentally by Killeen et al. [29]. Stimulation was applied at a regular 125 ms interstimulus interval at an amplitude of twice the diastolic threshold, as for the experimental preparations. After beat-to-beat stability was achieved, APD90 was measured under each condition. Refractory periods were then determined using a similar protocol to that used in the experiments, every eighth (S1) stimulus being followed by an extrasystolic (S2) stimulus. S1S2 interval was initially 70 ms and was subsequently decremented by 1 ms with each successive cycle until an S2 stimulus failed to initiate an action potential.
Results
After-depolarizations initiate arrhythmic activity in bradycardic hypokalemic hearts
In initial experiments, isolated perfused hearts were stimulated at a constant interstimulus interval of 125 ms for 20 min after 20 min exposure to test solutions. This demonstrated stable trains of MAPs, under all normokalemic (5.2 mM K+, n = 7; five hearts), hypokalemic (3.0 mM K+, n = 8; five hearts), or lidocaine-treated (10 μM) normokalemic (n = 6; five hearts) or hypokalemic (n = 7; five hearts) conditions: After-depolarizations and arrhythmic activity were consistently absent throughout. The subsequent experiments then examined arrhythmic properties at the longer cycle lengths (between 224 and 271 ms) that occurred in the absence of extrinsic stimulation (Fig. 1) and that have previously been reported to be proarrhythmic both under hypokalemic conditions and in the congenital LQTS [11]. Intrinsic cycle length did not differ significantly (P > 0.05) between normokalemic (250 ± 21 ms, six hearts), hypokalemic (253 ± 16 ms, seven hearts), lidocaine-treated normokalemic (248 ± 22 ms, six hearts), and lidocaine-treated hypokalemic (260 ± 10 ms, eight hearts) hearts.
Fig. 1After-depolarizations and arrhythmic activity in spontaneously contracting hypokalemic hearts. Epicardial monophasic action potential recordings in the absence of extrinsic stimulation in hearts exposed to normokalemic (5.2 mM K+, a) and hypokalemic (3.0 mM K+, b) test solutions and normokalemic (c) and hypokalemic (d) test solutions containing lidocaine (10 μM) for 20 min
Epicardial MAPs then retained morphologically consistent waveforms and were entirely free of after-depolarization and arrhythmic phenomena through 116 min of recordings over six normokalemic hearts (Fig. 1a). In contrast, 46 ± 7% of MAPs showed after-depolarizations early in their repolarization phases during 140 min of recordings that led to episodes of arrhythmic activity in 52 ± 3% of cases in five out of seven hypokalemic hearts (P < 0.01 as compared to normokalemic hearts, Fig. 1b). However, MAPs showed consistent waveforms without such after-depolarizations or arrhythmic activity during 118 min of recordings over six lidocaine-treated normokalemic hearts (Fig. 1c). Finally, 40 ± 9% of MAPs showed after-depolarizations occurring late in the repolarization phase in 40 ± 9% of cases more than 98 min of recordings in six out of eight lidocaine-treated hypokalemic hearts (P > 0.05 as compared to hypokalemic hearts). After-depolarizations occurred more frequently in those instances where intrinsic cycle length was long. However, these events were never followed by arrhythmic activity (P < 0.01 as compared to hypokalemic hearts, Fig. 1d).
Extrasystolic stimulation immediately after recovery from refractoriness initiates arrhythmic activity in hypokalemic hearts
A programmed electrical stimulation protocol recently shown to predict arrhythmogenicity in clinical LQTS [43] and previously adapted for use in murine models of LQTS [22] confirmed the above arrhythmogenic tendencies in hypokalemic hearts (Fig. 2). This comprised regular (S1) stimulation at a constant interstimulus interval of 125 ms interrupted by an extrasystolic (S2) stimulus after every eighth S1 stimulus. The S1S2 interval was decremented in 1 ms steps with each successive stimulus cycle from an initial value of 120 ms until the S2 stimulus either appeared to initiate arrhythmic activity, confirmed during an imposed 250 ms pause, or failed to initiate a MAP suggesting that the VERP has been reached. Accordingly, VERP values are reported to the nearest millisecond.
Fig. 2Arrhythmic activity in hypokalemic hearts after extrasystolic stimulation applied close to the refractory period. Epicardial monophasic action potential recordings resulting from application of extrasystolic (S2) stimuli at S1S2 intervals greater than the action potential duration at 90% repolarization (A), just greater than the ventricular effective refractory period (VERP; B), and just less than the VERP (C) in hearts exposed to normokalemic (5.2 mM K+, a) and hypokalemic (3.0 mM K+, b) test solutions and normokalemic (c) and hypokalemic (d) test solutions containing lidocaine (10 μM) for 20 min. Single vertical lines indicate the timing of S1 stimuli, and double lines indicate the timing of S2 stimuli
Normokalemic hearts (Fig. 2a, A–C) again were consistently free from arrhythmic activity after S2 stimulation after any S1S2 interval (n = 11; eight hearts). This also applied to hypokalemic hearts when S2 stimuli were delivered when MAPs had reached 90% repolarization (Fig. 2b, A, n = 7; five hearts). However, S2 stimuli delivered within the period just after recovery from refractoriness consistently initiated arrhythmic activity under these conditions (Fig. 2b, B). In contrast, S2 stimuli delivered before recovery from refractoriness failed to elicit MAPs, and this was followed by the resumption of stable rhythms (Fig. 2b, C). Finally, S2 stimulation did not result in arrhythmic activity in lidocaine-treated hearts whatever the S1S2 interval, whether under normokalemic (Fig. 2c, A–C, n = 8; six hearts) or hypokalemic (Fig. 2d, A–C, n = 8; five hearts) conditions. When taken together, the presence or absence of arrhythmogenicity in these experiments parallels clinical findings.
Arrhythmic tendency in hypokalemia correlates with increased local critical intervals
One hypothesis for the tendency towards either local or transmural re-excitation during action potential repolarization might consider the relationship between the time course of the recovery of membrane voltage and the corresponding time course of recovery of excitability from total refractoriness to a finite threshold for excitation in the myocardial regions concerned. These parameters were approximated by action potential duration at 90% repolarization (APD90) and VERP, respectively. Both these were measured during the procedures of the kind illustrated in Fig. 2, allowing for the delay between endocardial and epicardial excitation where appropriate. Firstly, the risk of local reexcitation of either the epicardium or the endocardium would be reflected in a critical interval given by the relevant APD90–VERP. Secondly, the risk of transmural re-excitation of either the epicardium by the endocardium (or the reverse) would require incorporation of the delay between endocardial and epicardial excitation given by the difference between endocardial and epicardial stimulation to depolarization latencies, Δlatency. This would give critical intervals of (endocardial APD90 + Δlatency−epicardial VERP) and (epicardial APD90 + Δlatency−endocardial VERP), respectively.
Figures 3a and 4a show typical epicardial and endocardial action potential waveforms during regular stimulation under each of the four above conditions (A–D). Figures 3b and 4b show the corresponding APD90s (vertical solid lines and dense hashing), VERPs (vertical broken lines and sparse hashing), and local critical intervals (shading). Asterisks indicate values that are significantly (P < 0.05) larger and daggers those that are smaller than those recorded in normokalemic hearts. Neither epicardial (46.6 ± 1.2 ms) nor endocardial (58.2 ± 3.7 ms) APD90s were significantly different (P > 0.05) from the corresponding VERPs (41 ± 4 and 48 ± 4 ms) under normokalemic conditions (Figs. 3A and 4A, n = 10; eight hearts). This resulted in local critical intervals taking small positive values of 5.4 ± 4.3 ms in the epicardium and 9.8 ± 5.3 ms in the endocardium. In contrast, epicardial (53.1 ± 0.7 ms) but not endocardial (56.9 ± 4.0 ms) APD90 increased significantly (P < 0.05), whereas both epicardial (29 ± 1 ms) and endocardial (29 ± 2 ms) VERPs decreased significantly under hypokalemic conditions (Figs. 3B and 4B, n = 6; five hearts). This resulted in significant positive shifts (P < 0.01) in both epicardial (23.7 ± 1.2 ms) and endocardial (28.5 ± 4.6 ms) local critical intervals, in fitting with the occurrence of arrhythmic activity under hypokalemic conditions.
Fig. 3Changes in epicardial action potential duration, ventricular effective refractory period, and local critical interval after exposure to hypokalemia and to lidocaine. Epicardial MAP waveforms during regular stimulation in hearts exposed to normokalemic (5.2 mM K+, A) and hypokalemic (3.0 mM K+, B) test solutions and normokalemic (C) and hypokalemic (D) test solutions containing lidocaine (10 μM) for 20 min comparing action potential duration at 90% repolarization; APD90 (vertical solid lines), VERP (vertical broken lines), and local critical interval (shading; a). Action potential duration at 90% repolarization, APD90 (dense hashing), VERP (sparse hashing) and critical interval (shading) under these conditions (b). Asterisks indicate values that are significantly (P < 0.05) larger and daggers those that are smaller than those recorded in normokalemic heartsFig. 4Changes in endocardial action potential duration, ventricular effective refractory period, and local critical interval after exposure to hypokalemia and to lidocaine. Endocardial MAP morphologies during regular stimulation in hearts exposed to normokalemic (5.2 mM K+, A) and hypokalemic (3.0 mM K+, B) test solutions and normokalemic (C) and hypokalemic (D) test solutions containing lidocaine (10 μM) for 20 min comparing action potential duration at 90% repolarizationl; APD90 (vertical solid lines), VERP (vertical broken lines), and local critical interval (shading; a). Action potential duration at 90% repolarization, APD90 (dense hashing), VERP (sparse hashing), and critical interval (shading) under these conditions (b). Asterisks indicate values that are significantly (P < 0.05) larger and daggers those that are smaller than those recorded in normokalemic hearts
The opposing effects of hypokalemia on APD90 and VERP can be explained in terms of alterations in conductances of repolarizing K+-channels
The above MAP findings concerning APD90 and VERP were in close agreement with the predictions of established ion channel equations and parameters from the model of Bondarenko et al. [6] with the Na+/K+-ATPase model of Hernandez et al. [24] using charge-difference modeling in simulated single cells. The model simulated the effects of regular stimulation at a 125 ms interstimulus interval until a steady state was reached, as reflected in beat-to-beat stability. Action potential characteristics were then simulated under normokalemic conditions, hypokalemic conditions with normal K+ permeabilities, and hypokalemic condition with the 20% reduction in the permeabilities of channels carrying the repolarizing K+ currents IK1 and Ito (C) as reported in recent experimental results [29] (Fig. 5). Figure 5a demonstrates the predicted steady-state action potential waveforms under each condition. Figure 5a and b also show APD90  (vertical solid lines and dense hashing), VERP (vertical broken lines and sparse hashing), and critical intervals (shading). Under normokalemic conditions (A), the resting membrane potential was −83 mV. APD90 (22 ms) was shorter than recorded in the whole hearts in keeping with previous results from microelectrode studies [7, 20]. Nevertheless, APD90 was shorter than VERP (27 ms) resulting in a critical interval of −5 ms. Figures 5B (a and b) demonstrate the consequences of an altered Nernst potential for K+  alone both upon resting membrane potential and the time course of a subsequent action potential. Hypokalemia hyperpolarized the membrane potential (−93 mV) and shortened both APD90 (19 ms) and VERP (25 ms), thus having little effect on the limiting criterion for re-excitation (−6 ms). In contrast, Fig. 5C (a and b) additionally demonstrate the combined effects of hypokalemia on both the Nernst potential and K+ permeabilities of the respective channels carrying IK1 and Ito. Although there was no additional effect on the resting membrane potential (−93 mV), hypokalemia increased both APD90 (29 ms) and VERP (27 ms) causing a positive shift in critical interval from −5 ms to +2 ms (Fig. 5C).
Fig. 5Computational modeling of murine ventricular action potentials showing changes in action potential duration, ventricular effective refractory period, and critical interval after exposure to hypokalemia. Action potential morphologies during regular stimulation in cells under normokalemic (5.2 mM K+, A) and hypokalemic (3.0 mM K+) conditions comparing action potential duration at 90% repolarization; APD90 (vertical solid lines), VERP (vertical broken lines), and critical interval (shading; a). In B, permeabilities of ion channel are under normokalemic conditions. In C, permeabilities of ion channels carrying the repolarizing K+ currents IK1 and Ito are reduced by 20%. APD90 (dense hashing), VERP (sparse hashing), and critical interval (shading) under these conditions (b)
The abolition of arrhythmic tendency by lidocaine correlates with negative shifts in local critical intervals
Exposure of normokalemic hearts to lidocaine (Figs. 3, C and 4C) significantly increased (P < 0.05) epicardial (54.8 ± 2.7 ms), although not endocardial (56.6 ± 4.2 ms), APD90 and significantly increased (P < 0.01) both epicardial (84 ± 5 ms) and endocardial (80 ± 2 ms) VERPs (n = 5; five hearts). This resulted in significant (P < 0.01) negative shifts in local critical intervals in both the epicardium (−31.7 ± 5.3 ms) and endocardium (−23.4 ± 4.7 ms). Lidocaine exerted concordant effects on hypokalemic hearts (Figs. 3D and 4D): Epicardial APD90 increased to 60.6 ± 2.7 ms, and endocardial APD90 remained unchanged (63.7 ± 6.4 ms), whereas both epicardial (81 ± 7 ms) and endocardial (84 ± 4 ms) VERPs were significantly increased (P < 0.05, n = 6; five hearts). The resulting significant negative shifts (P < 0.01) in local critical intervals in both epicardium (−20.4 ± 7.5 ms) and endocardium (−20.7 ± 7.6 ms) paralleled the antiarrhythmic effect of lidocaine.
Arrhythmic tendency in hypokalemia also correlates with increased transmural critical intervals
Figures 6a and 7a show epicardial and endocardial action potential waveforms during regular stimulation under each condition. Figures 6b and 7b show APD90 (vertical solid lines and dense hashing) and VERPs (vertical dotted lines and sparse hashing), as detailed above, together with Δlatencies (horizontal arrows and horizontal shading) and transmural critical intervals (shading) under the four conditions studied. Asterisks indicate values that are significantly (P < 0.05) larger and daggers those that are smaller than recorded in normokalemic hearts. Figure 6 thus compares endocardial APD90s with epicardial VERPs, allowing for Δlatency to describe critical intervals for epicardial re-excitation. In contrast, Fig. 7 compares epicardial APD90s with endocardial VERPs, allowing for Δlatency to describe critical intervals for endocardial re-excitation.
Fig. 6Changes in endocardial action potential duration, epicardial ventricular effective refractory period, transmural conduction time, and epicardial transmural critical interval after exposure to hypokalemia and to lidocaine. Epicardial and endocardial MAP morphologies during regular stimulation cross-comparing epicardial and endocardial waveforms and the relationship between the action potential duration at 90% repolarization; APD90 (vertical solid lines) and VERP (vertical broken lines) of one waveform and the decay of the other, indicating critical intervals (shading). Hearts were exposed to normokalemic (5.2 mM K+, A) and hypokalemic (3.0 mM K+, B) test solutions and normokalemic (C) and hypokalemic (D) test solutions containing lidocaine (10 μM) for 20 min. Horizontal arrows indicate the time taken for depolarization to spread from epicardium to endocardium (a). APD90 (dense hashing), VERP (sparse hashing), transmural conduction time (horizontal hashing), and critical interval (shading) under these conditions (b). Asterisks indicate values that are significantly (P < 0.05) larger, and daggers those that are smaller than those recorded in normokalemic heartsFig. 7Changes in epicardial action potential duration, endocardial ventricular effective refractory period, transmural conduction time, and endocardial transmural critical interval after exposure to hypokalemia and to lidocaine. Epicardial and endocardial MAP morphologies during regular stimulation cross-comparing epicardial and endocardial waveforms and the relationship between the action potential duration at 90% repolarization; APD90 (vertical solid lines) and VERP (vertical broken lines) of one waveform and the decay of the other, indicating critical intervals (shading). Hearts were exposed to normokalemic (5.2 mM K+, A) and hypokalemic (3.0 mM K+, B) test solutions and normokalemic (C) and hypokalaemic (D) test solutions containing lidocaine (10 μM) for 20 min. Horizontal arrows indicate the time taken for depolarization to spread from epicardium to endocardium (a). APD90 (dense hashing), VERP (sparse hashing), transmural conduction time (horizontal hashing), and critical interval (shading) under these conditions (b). Asterisks indicate values that are significantly (P < 0.05) larger and daggers those that are smaller than those recorded in normokalemic hearts
Epicardial (21.0 ± 0.82 ms) and endocardial (58.2 ± 3.7 ms) latencies were statistically indistinguishable in normokalemic hearts giving a Δlatency of 1.6 ± 1.4 ms. This contributed to significant (P < 0.05) negative shifts in transmural critical intervals in both the epicardium and endocardium (−14.3 ± 6.1 and −3.3 ± 4.2 ms, respectively, Figs. 6A and 7A). Hypokalemia had no significant effect (P > 0.05) on latencies or on Δlatency (1.1 ± 1.1 ms) but resulted in significant (P > 0.01) positive shifts in transmural critical intervals in both the epicardium (23.6 ± 2.6 ms) and endocardium (29.2 ± 6.0 ms; Figs. 6B and 7B).
The abolition of arrhythmic tendency by lidocaine also correlates with significantly decreased transmural critical intervals
In contrast, exposure of normokalemic hearts to lidocaine significantly increased both epicardial and endocardial latencies (33.8 ± 2.6 and 46.3 ± 5.6 ms, respectively) but still did not significantly alter (P > 0.05) Δlatency (12.5 ± 6.2 ms). However, transmural critical intervals became significantly negative in both the epicardium (−15.2 ± 6.6 ms) and endocardium (−16.6 ± 8.8 ms; Figs. 6C and 7C). This was also true when hypokalemic hearts were exposed to lidocaine: Both epicardial and endocardial latencies were significantly increased (26.3 ± 3.2 and 33.8 ± 1.3 ms, respectively) but Δlatency was not significantly altered (P > 0.05, 7.6 ± 3.4 ms). Again, transmural critical intervals were significantly decreased (P < 0.05) in both the epicardium (−12.8 ± 5.9 ms) and endocardium (−10.4 ± 1.7 ms; Figs. 6D and 7D).
Arrhythmogenesis occurs in the absence of significant alterations in the TDR
The analysis above thus established four critical intervals, which, when taken together, provided a clear prediction of arrhythmogenicity under these circumstances when changes in APD90 did not correspond to changes in VERP. In contrast, an analysis in terms of TDR, previously shown to predict arrhythmogenicity in both congenital and acquired forms of the LQTS [2], gave insufficiently sensitive predictions. TDR was calculated as the time between stimulation and 90% repolarization in the endocardium minus the time between stimulation and 90% repolarization in the epicardium. TDR values did not significantly alter with the presence or otherwise of arrhythmogenicity (Fig. 8). Thus, in normokalemic hearts (Fig. 8, A) epicardial repolarization time (67.6 ± 1.5 ms) was significantly shorter (P < 0.05) than endocardial repolarization time (77.6 ± 3.9 ms), giving a TDR of 10.0 ± 4.2 ms (n = 10; eight hearts). Epicardial and endocardial repolarization times, as well as the resulting TDR, remained unchanged under hypokalemic conditions (Fig. 8, B). Finally, although treatment with lidocaine significantly increased (P < 0.05) epicardial and endocardial repolarization times under both normokalemic (Fig. 8, C, to 86.1 ± 2.8 and 103.0 ± 7.0 ms, respectively, n = 6; five hearts) and hypokalemic (Fig. 8, D, to 86.9 ± 4.1 and 97.6 ± 6.6 ms, respectively, n = 5; five hearts) conditions, in neither case did it affect TDR.
Fig. 8Changes in transmural dispersion of repolarization after exposure to hypokalemia and to lidocaine. Epicardial (up-sloping hashing) and endocardial (down-sloping hashing) stimulation to repolarization times, and the difference between these values giving transmural dispersion of repolarization (open bars) in hearts exposed to normokalemic (5.2 mM K+, A) and hypokalemic (3.0 mM K+, B) test solutions and normokalemic (C) and hypokalemic (D) test solutions containing lidocaine (10 μM) for 20 min. Asterisks indicate values that are significantly (P < 0.05) larger than those recorded in normokalemic hearts
These findings indicate that despite similarities, criteria that have been established to predict arrhythmogenicity in LQTS do not necessarily apply in hypokalemia. However, explicit inclusion of refractory behavior yields novel criteria, which may constitute more sensitive general predictors of arrhythmogenicity and may prove particularly useful in situations where APD90 diverges sharply from VERP. Further, these novel criteria provide a physiological basis for the participation of refractoriness in arrhythmogenicity.
Discussion
In clinical situations, hypokalemia is associated with arrhythmogenesis initiated by PVDs [52] and accompanied by prolongation of the electrocadiographic QT interval, reflecting increased action potential duration [23]. Furthermore, class 1 antiarrhythmic agents are effective in suppressing arrhythmic activity in hypokalemic patients [42]. These features thus resemble corresponding characteristics of the congenital LQTS [12, 41], where arrhythmic activity is thought to result from re-entrant excitation [2]. This has been attributed to the propagation of depolarization from active cells to previously active adjacent regions subsequently triggering spread of excitation and thus establishing re-entrant circuits [1, 3, 37].
We sought to study the physiological basis for the arrhythmogenicity observed under hypokalemic conditions, particularly the extent to which this resembles or differs from the corresponding features of LQTS, in intact isolated perfused murine hearts. Epicardial and endocardial MAPs were first recorded from hypokalemic hearts, confirming that stimulation at a regular interstimulus interval of 125 ms (S1 stimulation) resulted in stable rhythms. In contrast, at the long intrinsic cycle lengths occurring in the absence of extrinsic stimulation, frequent after-depolarizations were observed and were often followed by the initiation of an arrhythmic activity. This is consistent with the known proarrhythmic effect of bradycardia [10, 13, 46, 51]. Previous studies correlating results from single-cell and whole-heart preparations have attributed such after-depolarizations to inward currents flowing through reactivated voltage-operated Ca2+ channels [27, 35], Ca2+-coupled inward Na+ currents via the Na+–Ca2+ exchanger [47], or Ca2+-induced Ca2+-release from intracellular stores [26]. In the presence of the class 1b antiarrhythmic agent lidocaine, after-depolarizations persisted. These events were especially common in hearts where intrinsic cycle length was particularly long, again in agreement with the known proarrhythmic effect of bradycardia [10, 13, 46, 51]. However, in the presence of lidocaine, these events were never followed by the initiation of arrhythmic activity. Thus, the experiments demonstrated that hypokalemic murine hearts showed arrhythmogenic properties in agreement with clinical findings and established conditions in which arrhythmogenicity was and was not observed.
A quantitative assessment of MAP waveforms and refractory characteristics associated with this arrhythmogenicity was then performed using an extrasystolic stimulation (S2) procedure previously established in the assessment of arrhythmogenicity in both clinical [43] and murine [22] studies of LQTS. S2 stimulation reproducing the effect of after-depolarizations immediately after recovery from refractoriness failed to initiate arrhythmic activity in normokalemic hearts. However, such stimulation consistently resulted in arrhythmic activity in hypokalemic hearts. This is in agreement with previous reports that after-depolarizations and S2 stimulation early during action potential repolarization are particularly arrhythmogenic [14, 38] and also parallels clinical observations that PVDs coincident with T-waves frequently initiate arrhythmic activity [48]. In contrast, S2 stimuli did not elicit arrhythmic activity in lidocaine-treated hearts, whether studied under normokalemic or hypokalemic conditions. These are consistent with after-depolarizations having occurred late in action potential repolarization, and thence, failing to initiate arrhythmic activity.
Previous studies in murine [30], canine [15], and human [31] ventricles have consistently reported that maneuvers, which alter action potential duration, also produce corresponding changes in refractory period, with the notable exception of exposure to class 1 antiarrhythmic drugs [39]. However, the effect of isolated reduction in [K+]o on these parameters has not been studied. Exploration of the effect of varying S1S2 interval demonstrated for the first time that although action potential duration (quantified at 90% repolarization, APD90) was increased in hypokalemia, VERP was decreased. Furthermore, exposure to lidocaine had no effect on APD90 in the epicardia or endocardia of normokalemic hearts and significantly increased APD90 only in the endocardia of hypokalemic hearts, despite significantly increasing VERP in all cases. Thus, the proarrhythmic effect of hypokalemia was associated with recovery from refractoriness occurring earlier in action potential repolarization, whereas the antiarrhythmic effect of lidocaine was associated with recovery from refractoriness occurring later in action potential repolarization.
Reduction of [K+]o might be expected to increase outward K+ currents and thereby decrease APD90. Indeed, computer modeling of single ventricular myocytes confirmed that reduction of [K+]o per se resulted in decreased APD90. Furthermore, the Nernst equation would predict that reduction of [K+]o should hyperpolarize the resting membrane potential, thereby increasing the proportion of sodium channels available for activation [19] and decreasing the VERP: our model replicated this effect. However, incorporation of recent data from our group demonstrating that reduction of [K+]o decreases the repolarizing K+ currents IK1 and Ito [29] resulted in VERP returning to its normokalemic value and APD90 being increased beyond its normokalemic value. Thus, although reduction in K+ permeability compensates for the change in VERP, it overcompensates for the change in APD90, rendering the APD90 longer than the VERP, in fitting with experimental results and with the proarrhythmic effect of hypokalemia. Previous studies have reported that although exposure to lidocaine increases VERP through an effect on the gating of fast Na+-channels [32, 34], it has a proportionately smaller effect on action potential duration [5]. Exposure to lidocaine is thus established to result in postrepolarization refractoriness [39], in fitting with experimental results and with the antiarrhythmic effect of lidocaine.
We then applied an analytical scheme to provide a simple physiological explanation for these findings. Subject to electrotonic coupling between cells [25], the simplest condition for local re-excitation between adjacent cells within either epicardium or endocardium would require membrane potential to exceed threshold at some point during action potential repolarization, the recovery of membrane potential lagging behind the recovery of excitability. Recovery of excitability was approximated by the VERP, measured using a standard stimulus of consistent amplitude and duration. Recovery of membrane potential was approximated by the action potential duration at 90% repolarization (APD90). Accordingly, APD90−VERP gives a critical interval that reflects tendency towards local re-excitation and arrhythmogenicity. Positive shifts in this interval would reflect a relatively proarrhythmic state, whereas negative shifts in this interval would reflect an antiarrhythmic state. The corresponding analytical condition for transmural re-excitation across the thickness of the myocardial wall with a transmural conduction time given by Δlatency [40] yields transmural critical intervals of (endocardial APD90 + Δlatency−epicardial VERP) for the epicardium and (epicardial APD90 + Δlatency−endocardial VERP) for the endocardium, again subject to electrotonic spread of current between cells [25]. Although exposure to lidocaine increased both epicardial and endocardial stimulation to depolarization latencies, attributable to its established effect on conduction velocity [8], it had no significant effect on Δlatency. Hypokalemia resulted in significant positive shifts in the magnitude of all four critical intervals, whereas exposure to lidocaine resulted in significant negative shifts, in precise agreement with the presence or absence of arrhythmogenicity. Modelling of single ventricular myocytes predicted shorter APD90s than were recorded from whole-heart preparations, in agreement with previous experimental observations in such single-cell preparations [7, 20, 30]. Nevertheless, hypokalemia when similarly modeled for such single-cell preparations resulted in a positive shift in critical interval, in common with our experimental observations from whole hearts.
Although changes in all four critical intervals correlated with arrhythmogenicity, TDR, previously shown to predict arrhythmogenicity in LQTS [36, 44, 45], proved an insufficiently sensitive predictor. This finding may be attributable to sharp differences between APD90 and VERP: it is possible that APD90 and VERP were in close agreement in previous studies on LQTS [49, 50]. In the latter event, the present analysis would have yielded identical results to one adopting TDR.
Thus, we establish for the first time that hypokalemia decreases VERP despite increasing APD90 and attribute this surprising finding to effects of reduced [K+]o on ion channel gating. Secondly, we establish novel indices incorporating VERP as general criteria for re-entrant arrhythmogenicity that additionally provide a physiological basis for the association between changes in epicardial and endocardial VERP and APD90 and susceptibility to arrhythmogenesis. Thirdly, we establish that such analyses provide more sensitive indications of arrhythmogenicity than previous analyses invoking TDR.

action potential duration
refractory period
conduction time
transmural dispersion of repolarization
critical intervals
arrhythmia


Morphogenesis of post-Golgi transport carriers

The trans-Golgi network (TGN) is one of the main, if not the main, sorting stations in the process of intracellular protein trafficking. It is therefore of central importance to understand how the key players in the TGN-based sorting and delivery process, the post-Golgi carriers (PGCs), form and function. Over the last few years, modern morphological approaches have generated new insights into the questions of PGC biogenesis, structure and dynamics. Here, we present a view by which the “lifecycle” of a PGC consists of several distinct stages: the formation of TGN tubular export domains (where different cargoes are segregated from each other and from the Golgi enzymes); the docking of these tubular domains onto molecular motors and their extrusion towards the cell periphery along microtubules; the fission of the forming PGC from the donor membrane; and the delivery of the newly formed PGC to its specific acceptor organelle. It is now important to add the many molecular machineries that have been described as operating at the TGN to this “morphofunctional map” of the TGN export process.
Introduction
The Golgi complex serves as the central station in the biosynthetic pathway, where proteins are sorted for their different destinations, such as various domains of the cell surface and the endosomal–lysosomal system. This delivery of cargo proteins from the Golgi complex to their target compartments is carried out by dynamic, membrane-bound organelles that are frequently called either “transport carriers” or “post-Golgi carriers” (PGCs) (Luini et al. 2005). As these PGCs have an important role in the process of intracellular transport, their morphology, living dynamics and molecular compositions have become the focus of significant interest, particularly over the last few years.
These PGC transport organelles were originally defined through the development of green fluorescent protein (GFP) technology and living-cell imaging (Lippincott-Schwartz et al. 2000), whereby the first fluorescent cargo protein that was followed in living cells revealed a new world of images of these relatively large and highly dynamic structures that travel from the Golgi complex to the plasma membrane (Wacker et al. 1997; Hirschberg et al. 1998; Nakata et al. 1998). Then, with time, the list of cargo molecules that could be visualized in vivo expanded, further exposing the unexpected complexity of the post-Golgi transport pathways. Finally, further technical advances resulted in the combination of video and electron microscopy (correlative light-electron microscopy, CLEM), which provided the means to define the morphogenesis of these PGCs at the ultrastructural level.
As a result of these studies we now know that PGCs arise from specific membrane domains of the Golgi complex that lack resident Golgi enzymes, forming what are known as the “PGC precursors” (Hirschberg et al. 1998; Keller et al. 2001; Polishchuk et al. 2003; Puertollano et al. 2003). The shapes and sizes of PGCs that even carry the same cargo can vary across a wide range, and under the light microscope, most of them are seen to be clearly larger that plasma-membrane associated clathrin vesicles and 100-nm fluorescent beads (Hirschberg et al. 1998). The smaller PGCs usually have a size of 300–400 nm, although some of the larger ones can reach several microns in length. Video microscopy has also revealed that many of these carriers appear globular, although they frequently stretch out into tubular shapes during their translocation through the cytosol; thus PGCs have frequently been termed as “pleiomorphic” structures.
In transporting their cargoes to the correct acceptor compartments, the movement of PGCs is mediated via microtubules. However, carriers can also form and support post-Golgi transport without microtubules, although the correct targeting of their cargo proteins is usually compromised under these conditions (Rindler et al. 1987; Kreitzer et al. 2003). Finally, the life cycle of a PGC can be schematically imagined to consist of three stages: (1) its formation (which can in turn be further divided into several substages; see below); (2) its transition through the cytosol; and (3) its docking and fusion with the target membrane (Polishchuk et al. 2000). The first of these steps, the formation of the PGC, appears to be the most complex, and it also probably remains the least understood.
Since the question of the morphogenesis of a PGC is closely intertwined with that of the structure of the organelle from which it originates, the trans-Golgi network (TGN), both of these issues will now be discussed in an integrated fashion.
The trans-Golgi network and the origin of PGCs
The process of PGC morphogenesis has been characterized in detail using video and electron microscopy, as well as with the combination of these techniques (CLEM). As indicated above, this process comprises the formation, the extrusion and the fission of the export domain from the TGN, thus generating the free carrier (Polishchuk et al. 2003; see also Fig. 1). The first step (the formation of the tubular export domains) also includes the segregation of the cargo proteins from the Golgi resident enzymes. These events appear to be common to the proteins directed towards different post-Golgi compartments, such as basolateral plasma membrane (Hirschberg et al. 1998; White et al. 2001; Polishchuk et al. 2003), the apical plasma membrane (Keller et al. 2001) and the endosomal–lysosomal system (Puertollano et al. 2003). These export domains usually contain TGN markers; i.e. they are part of the TGN (Polishchuk et al. 2003; Puertollano et al. 2003). Of note, these three post-Golgi compartments are the ones that have been best characterized for the PGCs leaving the TGN, with the total number and types of pathways for cargo exit from the TGN at present not known, although there are at least six, and probably more (Rodriguez-Boulan et al. 2005).
Fig. 1Formation of post-Golgi transport carriers. Subsequent frames extracted from a time-lapse sequence illustrating the different stages of PGC biogenesis (arrows): a formation of the tubular domain containing the cargo VSVG-YFP and devoid of the Golgi-resident protein galatosyltransferase-CFP. b Extrusion of this tubular domain from the Golgi complex. c, d Fission of the domain from the parental Golgi membranes. e Thin section of a cell expressing the TGN38-HRP construct. Arrows indicate tubular PGC precursor that has been pulled out of the TGN area of the Golgi complex
Although the existence of the TGN has been known for many years (Griffiths and Simons 1986), its precise structure and identity still remain to be ascertained. In one view, which predominated in the field until recently, the TGN was considered to consist of essentially an anastomosing tubular network that emanates from (or that results from the breakdown of) the trans-most Golgi cisterna, and that projects mainly in the trans direction (Griffiths et al. 1989, 1985; Clermont et al. 1995). Rambourg and colleagues have thoroughly described the TGN in several different cell types. In these descriptions, this trans-most cisterna also tends to “peel off” from the rest of the Golgi stack, and together with the other morphological characteristics of the Golgi stack, this is a feature that is suggestive (Clermont et al. 1995) of the cisternal progression-maturation trafficking model (Bannykh and Balch 1997; Mironov et al. 1997; Bonfanti et al. 1998; Losev et al. 2006; Matsuura-Tokita et al. 2006). Thus, in a simple version of this scheme, the TGN would result from the final stages of maturation of the Golgi cisternae. This would include the partial transformation of this trans-most cisternae into a tubular network, and the various carriers that leave the TGN for their different destinations would all originate form different domains of this tubular network.
A more complex and more recent view of the organization at the trans face of the Golgi complex comes from studies using electron microscopy tomography of cryofixed, freeze-substituted cells (Ladinsky et al. 1999, 2002). These studies have indicated that the TGN derives not only from the last trans cisterna, but instead from the three trans-most cisternae (Roth et al. 1985), from where tubules emanate into the trans space of the Golgi stacks. Remarkably, only the trans-most cisterna exhibits clathrin-coated buds, with the other buds appearing to have different, yet-to-be identified, types of coats (Ladinsky et al. 1999). Thus, only the trans-most cisterna would be responsible for the clathrin- and AP-1-dependent trafficking towards the endo-lysosomes, and although all of these three trans-most cisternae of the Golgi stacks would serve as the classical TGN, each of them could be specialized in the packaging and export of specific cargo proteins. This might have important functional and mechanistic implications for the proteins sorting and export process.
Another remarkable TGN feature that has been revealed by these tomographic studies is that these three trans-most cisternae can intercalate with the cisternae of the endoplasmic reticulum (ER) (Ladinsky et al. 1999, 2002). These have been proposed to have important roles in the transfer of lipids (through specialized contact sites) between the ER itself and the Golgi complex.
It will be important to establish whether the morphological discrepancies described above reflect fundamental differences in the organization of the export of cargo in different cell systems. Indeed, it is possible that the first model (the TGN as a network resulting from the tubular disassembly of the last trans-most cisterna) might actually only represent a special case of the more complete three-trans-cisterna model, and that both of these two different models of TGN may apply, depending on the cell type and the functional conditions.
In support of this possibility, it is clear that the TGN can vary significantly in both size and composition across different cell types. For example, cells with a well-developed endo-lysosomal system and without secretory granules exhibit an extensive tubular TGN, while the tubular component of the TGN is reduced in cells that are specialized in regulated secretion (Clermont et al. 1995). This appears to occur in the latter because most of the TGN membranes are used for the packaging of secretory granules, and the tubules only form the thin bridges between the granule precursors. Such an organization simplifies the release of the granules, which occurs through the rupture of these tubular elements (Clermont et al. 1995). Similarly, human fibroblasts have large collagen-containing distensions that are connected to tubular elements in the trans-Golgi area (Polishchuk et al. 2003). Thus, the morphology and size of the TGN apparently depend on the predominant type and amount of cargo protein departing from the Golgi complex.
The morphology of the TGN depends also on its secretory status. When exit from the TGN is blocked by a lowering of the temperature to 20°C in the presence of abundant cargo (Matlin and Simons 1983), the volume and surface areas of the TGN increase greatly (Griffiths et al. 1989); while in the absence of cargo, the 20°C block results in all three of the trans-most cisternae producing bulging exit domains (Ladinsky et al. 2002). At physiological temperatures, three-dimensional (3D) analyses of the Golgi stacks have revealed well developed, tubular–reticular, TGN-like membranes at the trans side of the Golgi complex in actively secreting cells (Trucco et al. 2004), while the TGN is nearly absent in quiescent cells (Trucco et al. 2004). Thus, the TGN is a very dynamic structure, the shape and size of which is potently regulated by the extent of traffic flowing through it. To discover the regulatory mechanisms is an important challenge for the future.
Another challenge will be to define whether the three-cisterna organization really underlies a functional specialization of these cisternae in the sorting and packaging of different cargo classes, as suggested by the presence of clathrin buds only on the last cisterna of the Golgi stack. So far, the lack of immunolabeling studies does not allow determining whether different trans cisternae really do contain different transport proteins.
In addition to being an organelle of the biosynthetic pathways, the TGN is involved in endocytic transport routes (Griffiths and Simons 1986; Mellman and Simons 1992; Pavelka et al. 1998). Several studies with different cell types showed that the TGN and Golgi stacks can contain plasma-membrane constituents and internalized materials (Stoorvogel et al. 1988; van Weert et al. 1997). These exchanges with the endocytic systems could well introduce a further level of structural complications, since the recycling endosomes, in particular, reside in the Golgi area and are tubular in nature. In conclusion, both the dynamics and the structure of the TGN are variable and incompletely defined, thereby presenting an additional layer of difficulty to our understanding of the biogenesis of the carriers that depart from this organelle.
Formation of PGC precursors at the TGN
There are two key aspects to the formation of the PGC precursors: their morphogenesis at the TGN; and the segregation between different types of cargo proteins that are targeted for different destinations, as well as between the Golgi-resident proteins, such as the Golgi enzymes.
Regarding PGCs morphogenesis, in principle, the tubular carrier precursors might form through the mechanical pulling force exerted by microtubule-based motors on a flatter, parent, membrane domain (e.g., a Golgi cisterna). This has been shown to be mechanistically possible for both artificial and natural membranes (Roux et al. 2002). If this is the case, the PGC precursors would be expected to be essentially simple linear tubular structures (Roux et al. 2002). The second possibility is that these precursors are actually formed from the tubular subdomains of the TGN, which are generated prior to docking and extrusion by microtubules. In this case, the GPCs should reflect the morphologically complex structure of their parent membranes.
Recent studies have provided compelling support in favor of the latter model (Polishchuk et al. 2003). First, both free PGCs and their precursors at the TGN comprise complex tubulo-reticular structures, which have often been described as the main component of the TGN in many cell types (Clermont et al. 1995). For example, PGCs carrying VSVG show a mostly tubular morphology, and can have a complex structure that even contains clearly visible fenestrae (Polishchuk et al. 2003); this would be expected of membranes that derive from protrusions of the TGN. Indeed, PGC precursors that have been visualized using CLEM, appear to be comprised of tubular segments that are interconnected with complex branching and fenestrated membranes; they are also seen to be continuous with the parent membranes of the Golgi stack (Polishchuk et al. 2003). Similarly, carriers containing the apical cargo protein hemagglutinin (HA) frequently have a tubular morphology as well as HA-positive domains at the TGN (Puertollano et al. 2001). Thus structural similarities between PGC precursors and the TGN appear to be a common feature of different types of PGCs. This strongly suggests that PGCs form via the fission of an entire precursor domain (or a large part thereof) from the rest of the TGN membranes.
Thus the question regarding the mechanism by which the originally flat Golgi membranes are converted into highly bent, tubular–reticular TGN structures arises. Essentially, this can be achieved by one of two mechanisms: either by the action of proteins that can bend these membranes into tubules, in a manner that is possibly similar to that of amphiphysin, endophilin, sorting nexins and others (Antonny 2006), or via the alteration of the lipid composition of these trans-Golgi membranes, which can be mediated, in turn, by several processes. For instance, changes in lipid content, and hence membrane curvature, can be modulated via the lipid-metabolizing enzymes that reside at the Golgi complex (for review, see De Matteis and Godi 2004; Luini et al. 2005). The transmembrane or inter-organelle transfer of lipids can contribute to the generation of particular lipid environments in the membranes of the TGN. In this respect, it is important to note that numerous contact sites between the ER and the trans-cisternae of the Golgi complex have been detected by electron microscopy tomography (Ladinsky et al. 1999, 2002). Such contact sites can be explored for lipid transfer between the ER and trans-Golgi that is mediated by specific lipid-transfer proteins. Also, since the cisterna-like morphology of Golgi compartments can be stabilized by large polymers of Golgi enzymes (Nilsson et al. 1996), the loss of oligomerized Golgi enzymes in the trans-Golgi should, in principle, favor cisterna-to-tubule transformation of cargo-containing membranes. Moreover, this process can be accompanied by the loss of the stacking mechanisms at the trans side of the Golgi complex. Here, GRASP65 and GRASP55 are two proteins that have been suggested to be involved in the maintenance of cisterna juxtapositioning, and they are located mainly at the cis and medial Golgi, rather than the trans-Golgi (Barr et al. 1997; Shorter et al. 1999). So this intercisternal “glue” may be gradually lost as a cisterna progresses towards the trans pole of the Golgi complex. This has been confirmed both in mammals and yeast by the observation that the trans-most cisterna frequently peels off from the main Golgi stack (Clermont et al. 1995; Mogelsvang et al. 2003). It is possible that more than two or more mechanisms act in synergy to provide this transition from flat Golgi cisternae to the tubulo-reticular TGN morphology.
In addition to the formation of tubular domains at the exit face of the Golgi complex, this is also the level at which cargo proteins that are directed to different post-Golgi destinations should be sorted. The classical view in the membrane transport field implies that sorting at the TGN (as well as throughout the whole secretory pathway) is driven mainly by the coat-adaptor-protein machinery, which interacts specifically with amino-acid signals of certain transmembrane cargo proteins; this then provides the mechanical force for budding and fission of transport vesicle (Mellman and Warren 2000).
This holds true for the endo-lysosome-directed carriers that have been thoroughly characterized. These carriers consist of clusters of clathrin-coated buds that are connected by tubular regions, and thus exhibit a grape-like structure. In contrast, PGCs carrying a cargo like the G-protein of vesicular stomatitis virus (VSVG) form in a coat and an AP-independent manner. Both PGCs and their precursors do not show β-COP or γ-, δ- and ε-adaptins at their membranes (Polishchuk et al. 2003). Other adaptors, such as the GGAs, are excluded from VSVG carriers as well (Puertollano et al. 2003; Polishchuk et al. 2003). Similarly, coats and adaptors have also never been detected on PGCs that are carrying proteins to the apical surface in polarized cells (Kreitzer et al. 2003). Thus, these carriers should form either by virtue of some still-unknown adaptors that cannot yet be visualized by electron microscopy, or by their association with specific lipid microdomains that are involved in sorting (Schuck and Simons 2004). This might be the case for proteins directed to the apical surface in polarized epithelial cells, the concentration of which at the TGN appear to be through their partition into cholesterol- and sphingolipid-rich membrane domains that are known as “rafts” (Schuck and Simons 2004).
The scission of PGCs from the TGN
The morpho-dynamics of the fission process are also fairly complex. Observations in living cells have revealed that the fission of PGCs frequently coincides with mechanical pulling of carrier precursor from the TGN along microtubules. Apparently, the pulling force which the molecular motors such as kinesin (see below) can apply to the TGN membranes is important to facilitate the extension of PGC precursors from the Golgi body and for the later fission of the PGC (Kreitzer et al. 2000; Polishchuk et al. 2003). In cell-free systems, the addition of kinesin to Golgi membranes (and even to liposomes) together with microtubules induces the formation of tubule-like membranes that are similar to PGC precursors (Roux et al. 2002), while a block of kinesin function by microinjection of an inhibitory antibody (Kreitzer et al. 2000) or expression of the headless kinesin mutant (Nakata and Hirokawa 2003) prevent PGC formation from the Golgi complex. Kinesin has been seen to be associated with the tip of PGC precursors, although it can also attach to other points along the PGC precursor membrane (Polishchuk et al. 2003). The movement of kinesins along microtubules can then create tension within the PGC precursor that will facilitate the fission process. Indeed, based on in vitro data, membranes under tension have recently been proposed to have an important role in fission (Roux et al. 2006). However, PGCs can also form when microtubules have been destroyed by nocodozole treatment; in this case, the pulling force to create membrane tension in fission-prone regions might be provided by actin motors (Warner et al. 2003; Sahlender et al. 2005).
Live cell imaging and CLEM have also shown that fission does not take place randomly along the membranes of PGC precursors. In this case, which regions of a PGC precursor can be defined as prone to fission? First, this depends on the geometry of the precursor membranes. Our data suggest that fission usually takes place at the thinnest parts of the PGC precursor (Fig. 2a), which at the electron microscopy level corresponding to thin tubular segments of membranes (Polishchuk et al. 2003). In contrast, fission does not take place at the TGN regions with a complex morphology (i.e., in those containing tubular networks and branching tubules, or in thick vacuolar regions). Obviously, the precise points of fission will define not only the compositions of the PGC carriers, but also their morphology. If fission occurs close to the tip of the TGN tubule, a carrier will be smaller in size. In contrast, larger PGCs can form by cleavage at the base of the PGC precursors (Fig. 2a). Similarly, endosome-directed PGCs can apparently detach from the TGN as simple cargo-containing vesicles if the fission occurs at the neck of the clathrin-coated buds (Fig. 2b). However, many clathrin-positive PGCs have a grape-like morphology (tubule with several buds), suggesting that entire chunks of TGN membranes containing 2–3 clathrin-coated buds can be cleaved from the Golgi complex (Polishchuk et al. 2006).
Fig. 2Fission of post-Golgi transport carriers. a TGN precursors of post-Golgi carriers are pulled along microtubules by kinesin. The fission (red line) of the carriers occurs at the thinnest parts of the PGC precursor, which correspond to thin tubular segments of the TGN membrane at the electron microscopy level. In contrast, fission does not take place at the TGN regions with a complex morphology (i.e., containing tubular networks and fenestrae, or in thick vacuolar regions). If fission occurs close to the tip of a PGC precursor, the carrier will be smaller in size (1). In contrast, larger PGCs can be formed by cleavage at the bottom of a PGC precursor ( 2). b PGCs directed to endosomes detach from the TGN as simple clathrin-coated vesicles if fission (red line) occur at the neck of the clathrin-coated bud (1). Alternatively, entire chunks of the TGN membrane containing 2-3 clathrin-coated buds can be cleaved from the Golgi complex
Another factor that might be important for PGC shaping is the type of cargo that is embedded in the PGC. For example, procollagen-I usually forms quite large aggregates that are visible within 300–400-nm-diameter membrane distensions of the Golgi membranes. As a consequence, similar distensions have been detected in most collagen-containing PGCs (Polishchuk et al. 2003; Canty et al. 2004).
Movement of PGCs from the Golgi complex to the target membrane
After fission from the TGN, PGCs move to the acceptor membrane. Different members of the kinesin superfamily (Kamal et al. 2000; Nakata and Hirokawa 2003; Teng et al. 2005), and also the other microtubule motor dynein (Tai et al. 1999), have been shown to drive post-Golgi transport of specific cargo to various destinations. This high fidelity of cargo selection by molecular motors at the TGN and their further delivery to the correct surface or intracellular domain may be regulated by interactions of motor protein directly with the cargo (Kamal et al. 2000; Teng et al. 2005) or with components of the sorting machinery at the TGN (Nakagawa et al. 2000).
As an example, transport of HA and annexin 13b to the apical surface in epithelial cells relies on raft-associated motor KIFC3 (Noda et al. 2001). KIF13A operates in the other post-Golgi route that is used for the transport of the mannose-6-phosphate receptor (Nakagawa et al. 2000). A number of neuronal proteins, including bAPP, GAP43 and vamp-2, require KIF5 for their correct targeting (Nakata and Hirokawa 2003), while the microtubule minus-end-directed motor dynein has been shown to support rhodopsin transport in rod photoreceptors (Tai et al. 1999; Yeh et al. 2006).
Selection of specific cargoes by motors could be driven by various mechanisms. The simplest would use a direct interaction between the motor and a specific domain of a cargo protein, as is seen for the dynein light chain and the cytoplasmic tail of rhodopsin (Tai et al. 1999). Alternatively, adaptor proteins could serve as a bridge between a motor and its cargo. For example, KIF13A transports the mannose-6-phosphate receptor through its interaction with the AP-1 complex (Nakagawa et al. 2000). Finally, both motor and cargo could associate with the same specific lipid microdomain, as for instance, for KIFC3 and the apically targeted annexin XIIIb.
Another issue that needs to be addressed is whether any of these sorting processes take place in the PGCs while they are moving toward their acceptor compartment. This happens, for example, with the maturation of secretory granules when the mannose-6-phosphate receptor is concentrated and sorted from the secretory granules by clathrin-coated vesicles (Klumperman et al. 1998). So several strategies have been used to determine whether similar sorting events happen with PGCs. Mature exocytic carriers can be arrested before their fusion with the plasma membrane either by microinjection of an anti-NSF antibody or by treatment with tannic acid (which fixes the plasma membrane but does not penetrate inside the cell). In contrast to secretory granules, the comparison of mature and newly formed PGCs did not reveal significant changes in either their ultrastructure or their composition (Polishchuk et al. 2003, 2004). Similarly, mature Golgi-to-endosome carriers were accumulated in cells upon endosome inactivation. However, they did not show any significant transformation, except for a very moderate reduction in the area covered by clathrin (Polishchuk et al. 2006).
Live-cell imaging of subconfluent MDCK cells has shown that PCGs that initially contained both a basolateral marker (VSVG-CFP) and an apical marker (GPI-YFP) did not sort out either of these cargoes into any separate structures, and instead delivered both of the proteins to the plasma membrane (Polishchuk et al. 2004). GPI-GFP was then sorted from the basolateral surface to the apical membrane through transcytosis (Polishchuk et al. 2004). On the other hand, the partitioning of two proteins from a common PGC into separate carriers has also been reported (Jacob and Naim 2001). This suggests that sorting from the PGC may exist, but that it should depend on the nature of the cargo proteins being transported.
Intermediate stations in post-Golgi transport
The complexity of sorting events in the post-Golgi space appears to be even worse since the discovery that certain cargoes may pass through the endosomal compartments before their arrival at the plasma membrane. Sporadic reports in the past have suggested that some secretory proteins do not move from the Golgi complex directly to the plasma membrane, but instead pass through an endocytic intermediate on their way to the cell surface (Leitinger et al. 1995). This indirect “through-endosome” delivery of cargo to the plasma membrane might be also facilitated by the intimate association of TGN membranes with number of endocytic compartments in the perinuclear area of the cell (Marsh et al. 2001). The list of the proteins using this pathway has been recently updated, and it has now been shown that in MDCK epithelial cells, VSVG, the LDL receptor and E-cadherin can be detected in the endosomes before their exit to the plasma membrane (Ang et al. 2004; Lock and Stow 2005).
These findings, however, promote a number of further questions. The first is whether this transport route is ubiquitous (i.e., does it exist in different cells?). The second question is whether different cargoes move through the same endosomal compartment on their way to the cell surface in epithelial cells? A number of proteins (such as VSVG and the LDL receptor) have been reported to use a Rab8-positive sub-population of endosomes as an intermediate station on their way to the basolateral membrane in epithelial cells (Ang et al. 2003). These proteins require the AP-1B adaptor complex to be properly sorted from these Rab8 endosomes towards the basolateral surface domain (Ang et al. 2003). Other cargoes (such as E-cadherin, for example) move to the plasma membrane through a Rab11 endocytic compartment (Lock and Stow 2005). It remains to be determined, however, whether there is any cross-talk between these Rab8- and Rab11-dependent routes. This possibility apparently exists, since Rab8 and Rab11 endosomes are both accessible to transferrin (Ang et al. 2004; Lock and Stow 2005).
Finally it is important to clarify as to what extent this through-endosome transport route is used by different cargo proteins in epithelial cells. This issue has been partially addressed by the silencing of the μ1B subunit of the AP-1B adaptor complex, which resides at the endosomes and is required for the correct delivery of many basolateral proteins. The use of RNA interference has revealed, however, that a number of cargoes (such as transferrin and Fc receptors, for example) can be targeted correctly even in the absence of AP-1B, which suggests that these proteins can move directly from the Golgi complex to the basolateral surface without crossing the endocytic routes (Gravotta et al. 2007). The existence of more than one basolateral pathway has also been supported by the observation that transport of different basolateral proteins can be selectively regulated by different PKD isoforms (Yeaman et al. 2004). Thus, further efforts need to be made to understand to what extent an endocytic post-Golgi compartment is involved in the sorting and transport events of cell-surface proteins.
Conclusions
The extensive characterization of PGC morphology by video and electron microscopy has provided a framework for the positioning of the molecular machineries in the morpho-functional maps of various trafficking segments. At the same time, many molecular players in TGN-to-plasma membrane transport have been identified. The attribution of each of the molecular components to each of the pathways is probably now the main challenge. We believe that the development of specific assays will significantly assist in the achieving of this objective. Video microscopy of GFP-tagged cargo proteins has allowed us to evaluate the process of PGC formation, as well as the speed and directionality of PGC movement through the cytosol. Other assays use tannic acid treatment (Polishchuk et al. 2004; Jakob et al. 2006) or horse-radish-peroxidase-based endosome immobilization (Ang et al. 2004; Polishchuk et al. 2006) to prevent the fusion of PGCs with their target membranes. These conditions allow us to trap mature PGCs and to compare their compositions to newly formed carriers and the TGN membranes. Moreover, preferential sites of PGC docking and fusion can also be easily identified in this way. The combination of these experimental approaches with specific molecular inhibitors now allows us to attribute a protein of interest to one of the steps in post-Golgi transport.

post-golgi transport
trans-golgi network
post-golgi carriers
golgi complex