Parameters of ionic currents used in computational models.
\r\n\t
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Ismail",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/10013.jpg",keywords:"Thermodynamics, Heat Transfer Analyses, Geothermal Power Generation, Economics, Geothermal Systems, Geothermal Heat Pump, Green Energy Buildings, Exploration Methods, Geologic Fundamentals, Geotechnical, Geothermal System Materials, Sustainability",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"October 29th 2020",dateEndSecondStepPublish:"November 26th 2020",dateEndThirdStepPublish:"January 25th 2021",dateEndFourthStepPublish:"April 15th 2021",dateEndFifthStepPublish:"June 14th 2021",remainingDaysToSecondStep:"2 months",secondStepPassed:!0,currentStepOfPublishingProcess:3,editedByType:null,kuFlag:!1,biosketch:"Leading research investigator in a collaborative project (2007-2010) with Goldcorp-Musselwhite Canada Ltd. and Engineering of Lakehead University, owner of a Ph.D. degree in Mechanical Engineering from McMaster University, Hamilton, Ontario, Canada and postdoctoral researcher (2004 to 2005) at McMaster University.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"62122",title:"Dr.",name:"Basel",middleName:"I.",surname:"Ismail",slug:"basel-ismail",fullName:"Basel Ismail",profilePictureURL:"https://mts.intechopen.com/storage/users/62122/images/system/62122.jpg",biography:"Dr. B. Ismail is currently an Associate Professor and Chairman of the Department of Mechanical Engineering, Lakehead University, Thunder Bay, Ontario, Canada. In 2004, Prof. Ismail earned his Ph.D. degree in Mechanical Engineering from McMaster University, Hamilton, Ontario, Canada. From 2004 to 2005, he worked as a Postdoctoral researcher at McMaster University. His specialty is in engineering heat transfer, engineering thermodynamics, and energy conversion and storage engineering. Dr. Ismail’s research activities are theoretical and applied in nature. Currently, his research areas of interest are focused on green engineering technologies related to alternative and renewable energy systems for power generation, heating and cooling. Dr. Ismail was the leading research investigator in a collaborative project (2007-2010) with Goldcorp-Musselwhite Canada Ltd. and Engineering of Lakehead University. This innovative project was state-of-the-art in geothermal heat pump technology applied in Northwestern Ontario, Canada. Dr. Ismail has published many technical reports and articles related to his research areas in reputable International Journals and Conferences. 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From chapter submission and review, to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. 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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"59650",title:"Long-Distance Modulation of Sensory Encoding via Axonal Neuromodulation",doi:"10.5772/intechopen.74647",slug:"long-distance-modulation-of-sensory-encoding-via-axonal-neuromodulation",body:'Flow of information in neurons of the sensory nervous system, as in the central nervous system, is usually thought of as unidirectional. The function of sensory neurons is to supply the central nervous system with information from the periphery, and this information is transmitted through action potentials (APs) propagating along the sensory axons. While this concept was introduced early in the history of neuroscience in Cajal’s neuron doctrine, it has been challenged many times. Such challenges include examples from retrograde transport from the synaptic terminals to the soma, which affects slow homeostatic processes [1], to APs that backpropagate from the axon initial segment into the dendritic regions where they modulate postsynaptic signaling and contribute to coincidence detection on fast time scales [2, 3]. Even axons, which are traditionally seen as faithful unidirectional conductors, can propagate APs backwards towards the axon origin [4]. Propagation direction depends on where APs are initiated, which is typically a spike initiation zone (SIZ) at the axon initial segment, near the axon hillock. Here, the excitability of the neuronal membrane is at its highest and integrated synaptic or sensory information has easy access.
The last decades have shown that membrane excitability, including that of the axon, is subject to changes depending on a diverse set of intrinsic and extrinsic conditions. The neuromodulatory system, for example, plays a critical role in sensory processing as a major contributor to the plasticity maintaining sensorimotor system function and animal behavior [5]. It typically targets local signal encoding, transmission, and AP initiation by modulating ion channel conductances though metabotropic (typically G-protein coupled) receptors. Modulator influences on long distance communication, however, remain enigmatic even though axons possess receptors for a plethora of modulators [4], and pathologies of the neuromodulatory system impair neuronal communication. Recent evidence suggests that neuromodulator-induced changes in axon membrane excitability facilitate AP propagation dynamics [6, 7, 8], and may serve to adapt sensory functions to different behavioral conditions.
The most dramatic change in axonal excitability is ectopic AP generation, a process common to many systems and neurons [4, 9, 10, 11, 12, 13]. In this case, axon trunk excitability increases to superthreshold levels, and APs are generated spatially distant from the primary SIZ. Since the axon membrane surrounding the AP initiation site is not refractory, APs propagate in both directions, orthodromically towards the axon terminal and antidromically towards the dendritic sites of signal integration. Excitability changes leading to ectopic spiking can be caused by various influences, including slow changes in local or global neuromodulators, external conditions such as temperature, or in different hormonal or pathological states. On faster time scales, antidromic APs can be elicited by axo-axonic synapses, such as those present in hippocampus [14], cortex [15], and most sensory neurons [16, 17, 18]. Furthermore, external axon stimulation is a common technique used by physicians to test reflex function and treat chronic neuropathic pain [19]. Little is known about the origin, control and functional effects of these additional APs. While postsynaptic effects of ectopic APs that propagate orthodromically have been shown, the effects of antidromic APs on information processing are mostly unknown [18].
In pseudounipolar neurons of the sensory system, such as pain fibers, proprioceptors, and somatosensory neurons, ectopic APs traveling towards the periphery may more easily invade the primary SIZ and the sensory dendrites. In these neurons, there is no soma between the axon and sensory dendrites, which is why in this case the latter are often referred to as receptive endings instead. Without a soma between the axon and the receptive endings, these neurons have fewer impedance changes [20] to stop antidromic AP propagation from reaching the periphery. Despite ectopic APs typically having lower frequencies, AP collisions [21] and failures due to refractory membrane block [22] must be rare whenever the sensory neuron’s primary SIZ is silent, giving ectopic APs ample opportunity to invade the receptive endings in the periphery.
We argue, using a ‘simple’ proprioceptor and computational modeling, that antidromic traveling ectopic APs modify sensory encoding by invading the primary SIZ in the periphery and modulating membrane excitability. This is a particularly intriguing concept, since the frequency of antidromic APs can be determined through external stimulation, or through neuromodulatory or synaptic actions on the axon trunk. These actions may allow humoral and neural influences to alter sensory information as it travels towards the central nervous system. To test our hypothesis, we utilized the experimentally advantageous anterior gastric receptor (AGR, [23, 24]). AGR is a single-cell muscle tendon organ in the crustacean stomatogastric ganglion [25] – a well-characterized system for the investigation of cellular and circuit neuromodulation [26]. AGR generates ectopic APs in its several centimeter-long axon trunk, spatially distant from the primary SIZ in the periphery [27]. To test whether changes in AGR’s ectopic AP frequency determine peripheral information encoding, we elicited different ectopic frequencies using extracellular axon stimulations while we chemically elicited peripheral AP bursts.
Our data show that ectopic APs propagated without failures towards the periphery, where they invaded the primary SIZ and caused three distinct frequency-dependent actions on sensory encoding: (1) an increase burst onset latency, (2) a reduction AP number, and (3) a reduction the burst duration. These effects increased when ectopic APs continued throughout the encoding of sensory information and caused significant frequency-dependent decreases in the average and maximum frequency. Using computational models of generic neurons, we show that slow ionic conductances facilitate antidromic AP modification of sensory encoding. Slow ionic conductances, such as those elicited by persistent Sodium, hyperpolarization-activated (HCN), and slow Potassium channels are ubiquitous in neurons and axons [28, 29, 30], indicating that sensory modification by antidromic APs may be inherent to many other systems. We conclude that axonal neuromodulation provides a means to rapidly influence sensory encoding via ectopic APs that invade the periphery, without directly or locally affecting the sites of stimulus reception and AP initiation.
The stomatogastric nervous system (STNS) of adult male crabs (Cancer borealis) was isolated following standard procedures [31], and superfused with physiological saline (10–12°C, [32]) KCl was increased 10–20 fold for high Potassium (K+) saline. To maintain osmolarity, NaCl was reduced appropriately. K+ saline depolarizes the membrane, and its effective concentration was determined for each preparation. Octopamine hydrochloride (OA, Sigma Aldrich) was diluted in saline to the desired concentration (0.1–100 μM). OA was cooled to 10–12°C and manually applied to the isolated STG in a petroleum jelly well. As a control, saline was applied at the same temperature 3 min before each neuromodulator application. Measurements were taken in steady-state (2–5 min after OA wash in). To prevent cumulative effects due to repeated modulator application, wash-outs were 5 min long with continuous superfusion of cooled saline. Peripheral bursts were elicited with a 0.1–0.5 s puff of K+ saline to a continuously saline-superfused well around the pdgn. To prevent accumulation of modulator effects 60–90 s washout occurred between puffs.
Standard techniques were used for extracellular recordings and data analysis [33]. The activity of AGR was monitored on multiple extracellular recordings simultaneously, namely on the stomatogastric nerve (stn), the dorsal gastric nerve (dgn), and the supraoesophageal nerve (son), see Figure 1A. To identify AGR, we used APs recorded on the dgn or stn and performed a time-correlation analysis (multisweep). Ectopic APs (1–10 Hz) were elicited with extracellular nerve stimulation [34] of the AGR axon trunk. The lipophilic voltage-sensitive dye Di-4-ANNEPDHQ [35] was used according to published protocols [36]. To facilitate access of the dye to the axons, the connective tissue sheath of the pdgn was manually removed. We used event-triggered averaging of APs to improve the signal-to-noise ratio of the optically recorded data (similar to [37]).
A. Schematic representation of STNS and AGR. AGR projects an axon to the gm1 muscles in the periphery, and to the premotor CoGs. The AGR ectopic SIZ is located in the stn, near the anterior end of the STG. The primary SIZ is near the gm1 muscles (*). B. AGR produces spontaneous ectopic APs in situ and in vitro (original recordings). Ectopic APs can be elicited with stimulation of AGR’s central axon. APs have been color coded for clarity. C. Overlay (‘multisweep’) and average (colored) of nerve recordings containing the AGR axon used to track AP propagation from posterior (dgn) to anterior (son), in different conditions. Stimulation artifacts are labeled with (*).
Data were analyzed using scripts for Spike2 (available at
Computation models were designed using NEURON [38] using standard Hodgkin-Huxley ionic conductances in a cable model of an unmyelinated axon. The model length was set to 1.213 cm with 10 μm compartments and the axon diameter was 0.6 μm. Axial resistivity (28 Ω*cm) and membrane capacitance (1 μF/cm2) were constant through the length of the neuron. The neuron had three sections, the axon (1012 μm), the peripheral SIZ (100 μm), and the dendritic terminal (101 μm). Active channel properties were conserved in the axon and peripheral SIZ, except only the peripheral SIZ had Ih or IKs (Table 1).
Ionic current | g̅max (mS/cm2) | Gating | Activation function | Tau (ms) | Ex (mV) |
---|---|---|---|---|---|
INa | 0.4 | m3 | 1/(1 + exp.(−0.4(36 + v)) | 0.19exp(−0.05(v + 40) | 50 |
h | 1/(1 + exp.(39.5 + v)) | 40exp(−0.025(v − 55)) | |||
IKd | 1.09 | n4 | 1/(1 + exp.(0.125(−33 − v))) | 55exp(−0.015(v −28)) | −77 |
IKs | 0.1 | n4 | 1/(1 + exp.(0.125(−33 − v))) | 4000/cosh((v + 73)/12) | −90 |
Il | 0.0016 | −60 | |||
Ih | 0.103 | h | 1/(1 + exp.((v + 70)/7) | 300 or 3000 | −10 |
Parameters of ionic currents used in computational models.
The effects of antidromic APs on sensory encoding can be challenging to delineate. We use the anterior gastric receptor neuron (AGR) of the crab, C. borealis because it is experimentally advantageous. AGR is a bipolar single-cell muscle tendon organ that projects two axons from its cell body - one towards the peripheral gastric mill 1 (gm1) muscles, and one to the commissural ganglia (CoGs, Figure 1A), where it innervates premotor control neurons [39]. The CoGs are analogous to the vertebrate brainstem, and contain a set of descending projection neurons that modulate downstream motor circuits in the stomatogastric ganglion (STG) and promote appropriate behavioral responses. The primary function of AGR is to encode information about changes in gm1 muscle tension and to convey this to the CoG networks. Sensory information is encoded as bursts of APs with maximum frequencies between 20 and 30 Hz at the primary SIZ in close proximity to the peripheral gm1 muscles (Figure 1B). APs generated at this site are propagated unidirectionally towards the integrating centers in the upstream CoGs. Figure 1C shows an in-situ recording of AGR, using multiple extracellular recordings at different sites along its axons. AGR burst activity was elicited by isometric gm1 muscle contractions that increased muscle tension (similar to [23]). All APs in this burst were recorded first in the dorsal gastric nerve (dgn), through which AGR innervates the gm1 muscles. They then passed through the soma before reaching the stomatogastric (stn) and superior esophageal (son) nerves, through which the AGR axon innervates the CoGs. The soma lies posterior to the STG, and functionally and physically connects the two AGR axons. Unlike most neuronal somata, AGR’s cell body possesses active properties and thus act as a continuation of the axon [40].
In addition to the peripheral SIZ, AGR generates APs at a second SIZ in its axon trunk whenever no sensory bursts are produced (Figure 1B, [23]). These APs first occurred in the stn, before appearing on the dgn and son (Figure 1C). These spontaneous APs thus traveled bidirectionally from the axon trunk towards the CoGs and the periphery, and were not elicited at the primary SIZ. Previous studies have estimated that these ectopic APs originate approximately 225 microns anterior to the STG neuropil, near the origin of the stn [32]. Thus, they were initiated spatially distant from the primary SIZ, at an approximate distance of 1 cm. AGR maintains its firing properties and SIZs even when isolated. In these in vitro conditions, the gm1 muscles are dissected away from the peripheral dendrites, removing the source of sensory stimuli, and only STG, CoGs, and the connecting nerves containing AGR’s axons were retained (see Figure 1A). Sensory-like bursts can be generated when short puffs of K+ physiological saline are applied locally to the peripheral dendrites. In the experiment shown in Figure 1B, a petroleum jelly well was placed around the pdgn containing the sensory dendrites of AGR (Figure 1A) and a puff of K+ saline was applied (see Materials and Methods). The elicited APs first appeared on the pdgn, demonstrating that they were initiated at the peripheral application site (Figure 1C). In contrast, spontaneous APs that occurred in between peripheral bursts, were first recorded on the stn and simultaneously on the dgn. They continued bidirectionally towards the CoGs, appearing on the son, and towards the peripheral AGR dendrites, appearing on the pdgn. This is consistent with previous results [27, 32] and the intact animal [23], and suggests that these in vitro spontaneous tonic APs are generated ectopically in AGR’s axon trunk. We used our ability to generate uniform sensory bursts at controlled times and track AP direction to investigate the modulatory effects of antidromic APs on sensory encoding. To control the frequency of ectopic APs in the axon trunk, we elicited APs through extracellular stimulation of the AGR axon in the STG well (Figure 1B, [34]). Forced ectopic APs followed the same pattern of propagation as spontaneously generated ectopic APs: bidirectionally from the STG well to the stn and dgn (Figure 1C).
To confirm that ectopic APs traveled without failures throughout the entire length of the AGR axon, we first recorded spontaneous and stimulated APs on the son, near the terminal ends of AGR in the CoGs, as well as from the pdgn, i.e. the dgn branch that responded to K+ stimulation and contained the primary SIZ. In all recordings (N = 14), ectopic APs reached the son and pdgn without ever failing.
This provided good evidence that ectopic APs propagated throughout the entire length of AGR. However, extracellular recordings have limited spatial resolution due to the space required to place electrodes. Therefore, it was difficult to determine if ectopic APs truly invaded the axon terminals in the CoG and the sensory encoding region, respectively. While we did not expect AGR’s APs to fail when they enter the CoG axon terminals, we decided to intracellularly record from a known postsynaptic target neuron of AGR, the commissural projection neuron 2 (CPN2). Figure 2A shows intracellular somatic recordings of CPN2 and AGR. AGR was tonically active and APs were generated at the ectopic AP SIZ. Each AGR AP was followed by a time-locked EPSP in CPN2 (Figure 2B), demonstrating that ectopic APs propagated all the way to the axon terminals and elicited postsynaptic responses.
A. Intracellular recordings of AGR and its postsynaptic partner, CoG projection neuron CPN2. EPSPs in CPN2 were time locked to APs in AGR during spontaneous ectopic AP activity, while strong AGR firing elicited a burst of APs (*). B. Multisweep and average of EPSPs in CPN2, triggered by APs in AGR. C. High resolution photo of pdgn with AGR’s peripheral axon (blue). D. AGR’s firing frequency increases when the peripheral (primary) SIZ is illuminated with fluorescent excitation light. E. Optical recordings of primary SIZ. Left: light-induced APs traveled orthodromically towards the CoGs. Right: stimulus evoked ectopic APs traveled antidromically towards the periphery and invaded the primary SIZ.
In the periphery, for ectopic APs to modulate sensory encoding, they must affect the primary SIZ. AGR encodes sensory stimuli pertaining to changes in muscle tension, and there are no postsynaptic structures to measure invading antidromic APs. In contrast to the output terminals in the CoGs, the AGR axon splits into several collaterals, with several branches innervating each of the two bilaterally symmetric gm1 muscles (Figure 1A). Axonal branching poses a problem for APs if they propagate from a single axon trunk towards a branch point, since the branching increases membrane impedance [20], and may decrease currents promoting AP propagation. This can lead to propagation failures, AP reflections, or both. Sensory APs from the AGR periphery propagate orthodromically from the branches into the main axon trunk, and are thus unlikely to be affected at these branch points. Antidromic APs, however, enter these branches coming from the main axon trunk, and may thus encounter non-permissive conditions. To test whether APs indeed invaded the primary SIZ without failure, we used the voltage sensitive dye, Di-4-ANNEPDHQ to record and identify the AGR axon in the periphery (see Materials and Methods). This dye has two major advantages: it changes fluorescence with membrane potential with high temporal and spatial acuity, which overcomes the limited spatial resolution of the extracellular recordings, and it selectively stains neuronal membranes, making it possible to visually identify and separate individual axons in a nerve bundle [32]. We applied the dye to the pdgn well used to isolate and activate the primary SIZ with K+ saline. This locally stained all axon membranes in the pdgn. Besides AGR, the dgn contains the axons of several STG motor neurons [41]. We identified the AGR axon by recording the optical signals of all stained axons, and aligning them to APs on the electrical recordings. Only optical signals from the AGR axon were consistently timed to extracellularly recorded AGR activity. We first used spontaneously generated APs to identify the AGR axon in the dgn, and then visually tracked the identified axon towards the periphery using the membrane staining. Lipophilic voltage-sensitive dyes such as the one we used here have excitatory side-effects with high-intensity fluorescence illumination [32, 42, 43]. We used this fact to our advantage: the excitation light was focused on a small area the nerve (225 μm, [32]). We found that when illuminated, APs originated in the periphery, i.e. they first appeared on the electrical recording of the dgn, and then propagated to the stn and son. As we moved illumination along the axon, AP frequencies varied substantially. SIZs are defined by an increased propensity to generate APs. Therefore, we determined that the region which generated the highest AP frequency would be the approximate location of the primary SIZ. Figure 2C shows the location on AGR that resulted in the highest firing frequency with illumination in Figure 2D. When we optically tracked APs initiated there, we found that they started at the site of illumination, and propagated orthodromically along the AGR axon (Figure 2E).
To determine if ectopic APs could penetrate this peripheral area, we first forced ectopic APs by extracellular stimulation of the AGR axon in the STG (see Figure 1C) and optically recorded the primary SIZ. Because illumination elicited orthodromic APs, there was a potential for collisions between orthodromic APs and antidromic ectopic APs [21]. To ensure that ectopic APs would not fail to be recorded in the periphery due to collisions, we forced ectopic APs at a higher frequency than the spontaneous firing frequency (1–2 Hz higher than the peripheral frequency). We found that all stimulated APs elicited an optical signal in the periphery time-locked to the stimulus (Figure 2E, right). Thus, ectopic APs invaded AGR’s stimulus encoding regions. Taken together, we find that AGR has two SIZs, one that spontaneously generates ectopic APs in the axon trunk, and one that generates APs in response to sensory stimuli. While APs encoding sensory stimuli travel unidirectionally in orthodromic direction, ectopic APs travel bidirectionally. Antidromic ectopic APs invade the primary SIZ of AGR.
Since AGR’s ectopic APs invade the periphery, we hypothesized that these APs modulate sensory encoding occurring there. In the simplest case, ectopic APs will penetrate the sensory SIZ at a constant frequency, leading to a static, continuous effect on sensory encoding. However, AGR’s spontaneous ectopic firing frequency is variable. In vivo, it varies between 0.7–9.4 Hz (3.66 ± 2.2 Hz, N = 17) between animals, but it can also change quickly within a given animal. Our in vitro recordings revealed an average ectopic firing frequency consistent with the in vivo data (3.36 ± 0.64 Hz, N = 14). However, the range of frequency changes in vitro is smaller in comparison to the in vivo range (2.31–4.74 Hz). The STG is subject to heavy neuromodulation from hormones in the blood stream and from peptide and amine modulators released from descending modulatory projection neurons [44, 45, 46]. In vitro, modulation is reduced, potentially leading to a much reduced variability in activity in comparison to in vivo [47]. The reduced modulation may account for the smaller range of AGR frequencies when compared to intact animals.
We have previously shown that the axon of AGR passes through the heavily modulated area in the STG as it projects from the periphery to the CoGs, and possesses receptors for the biogenic amine Octopamine (OA). OA is the invertebrate analog of norepinephrine and present in both the STG and stn [48]. We hypothesized that OA would affect the spontaneously generated ectopic APs, and increase their frequency. To test this, we locally applied OA at different concentrations to the recording well containing AGR’s ectopic SIZ. We identified the recording well nearest to the ectopic SIZ as shown previously, using a multisweep of several extracellular recording wells. AGR firing frequencies were measured in a steady state for all concentrations of OA. We followed each measurement by washing out OA through superfusion of physiological saline until the ectopic AP firing frequency returned to baseline frequency. First, we found that the ectopic firing frequency of AGR increased with the application of OA (Figure 3A), and it did so in a concentration dependent manner with an EC50 of 4.13 μM (Figure 3B, sigmoidal fit, R2 = 0.988, SE of estimate 0.053, p < 0.001). The average maximum frequency elicited by OA application ranged from 3.35 ± 1.054 Hz at 0.1 μM OA to 5.09 ± 1.34 Hz at 100 μM OA (N = 6), which corresponded to an average increase of 64.7 ± 47.8% at 100 μM OA. We further found that the latency between OA application and the half-maximum frequency diminished with increasing OA concentration, with an EC50 value of 1.00 μM (four parameter logistic curve fit, R2 0.994, SE of estimate 0.026, p < 0.001, Figure 3B, N = 6). Finally, the location of the ectopic SIZ remained unchanged and APs did not dislocate at any OA concentration, suggesting that OA exerted it actions directly at the axonal ectopic SIZ (Figure 3C). This demonstrates that there is OA concentration dependent ectopic firing frequency modulation in the AGR axon, enabling various frequencies at which ectopic APs will penetrate the periphery.
A. AGR firing frequency increases in a concentration dependent manner when OA is applied to the ectopic SIZ. Original recording of an individual animal at three concentrations. B. Dose response curves of AGR instantaneous firing frequency (top: raw; middle: normalized) and response latency (raw) after OA application. C. Multisweeps and averages of nerve recordings that contain the AGR axon to track AP propagation and the location of the ectopic SIZ at different concentrations of OA. OA did not displace the ectopic SIZ.
Since AGR’s ectopic APs invade the periphery at different frequencies, we hypothesized that there is frequency-dependent modulation of sensory encoding occurring there. To test this, we extracellularly forced ectopic APs to a set of fixed firing frequencies (1–10 Hz) and measured the effect on various parameters of stimulus encoding. Ectopic APs were continuously elicited (at least 20 APs at each ectopic frequency) before a local puff K+ saline was applied to elicit a peripheral burst (Figure 1B). Ectopic AP stimulation continued until the first AP in the burst, mimicking the behavior of the spontaneous and modulated ectopic APs in AGR (Figure 1B). We then compared changes in the peripheral bursts in control (no ectopic stimulation) to experimental bursts with stimulated ectopic APs preceding the burst. Sensory stimuli can be encoded in the number of APs, the frequency, and the precise timing of APs. We thus measured the change in number of APs per burst, the average and maximum AP frequencies, the durations of peripheral bursts, and their onset latencies (the time between the K+ saline puff and the first AP of the peripheral burst).
We found that invading ectopic APs had significant influences on several aspects of stimulus encoding. Figure 4 shows a comparison of a control burst to a burst with forced ectopic frequency of 6 Hz. Burst delay, burst duration and the number of APs in burst were clearly diminished when ectopic APs are present. The smaller number of burst APs was not due to AP collisions, since we (1) were able to account for all ectopic APs in the periphery, and (2) AP collisions could be identified by missing APs on the multisweep recordings. Since ectopic AP stimulation stopped when the first burst spike was detected, we found collisions to be rare (less than 2%). In general, increasing ectopic AP frequencies caused stronger effects on the sensory burst. For example, burst onset latency significantly increased with ectopic AP frequency (p = 0.01, Pearson correlation coefficient R2 = 0.532, Figure 4Aii), indicating that membrane excitability at the beginning of the burst decreased with higher ectopic AP frequencies. There was also a significant negative correlation between ectopic AP frequency and the number of APs in a burst (p = 0.001, Pearson correlation coefficient R2 = 0.729; Figure 4Aiii). This resulted in a nearly 30% decrease in the number of APs in a burst at 10 Hz ectopic frequency. Concurrently, burst duration decreased significantly with ectopic AP frequency (p < 0.001, Pearson correlation coefficient R2 = 0.750; Figure 4Aiv), reaching a nearly 30% decrease at 10 Hz. Neither average nor maximal burst frequency changed significantly with ectopic AP frequency (R2 = 0.122 and 0.0696 respectively, Figure 4Av, vi), although both tended to be lower at higher ectopic AP frequencies.
A. Original recordings of AGR ectopic and burst AP activities. i: Control sensory burst (bottom), elicited with high potassium (K+) in the periphery. Top: With forced ectopic APs that ended at the beginning of the sensory burst. ii: Corresponding changes in latency of elicited sensory bursts at different ectopic AP frequencies (mean ± SD). iii: Number of spikes per burst. iv: Burst duration. v: Average intraburst frequency. vi: Maximum intraburst frequency. B. i: Control sensory burst and burst with ectopic APs that continued throughout. ii–vi: Like in A.
Ectopic APs occur spontaneously and in response to modulator actions at the ectopic SIZ in AGR. However, ectopic APs can also be elicited by synaptic actions at axo-axonic synapses such that the ectopic firing frequency is determined by the occurrence of synaptic potentials in the axon [10, 11, 18]. In this case, ectopic firing would not cease when the sensory burst is elicited. While this is not the case for AGR, the effects of continuous ectopic spiking were tested by continuing the forced ectopic APs throughout the sensory burst. Figure 4B shows an example recording for continued ectopic spiking at 6 Hz, in comparison to a control burst without forced ectopic APs. As a consequence of the continued ectopic firing during the sensory burst, AP collisions were more prevalent, although still rare. We estimate less than 5% of all ectopic APs collided on their way to the periphery. This low number is mostly due to the small distance between ectopic and primary SIZs (about 1 cm), and that propagating APs ‘occupy’ the axon only for a short amount of time (around 10 ms given the propagation speed of AGR’s APs of around 1 m/s). Consequently, even at ectopic frequencies of 10 Hz (interspike intervals of 100 ms), axons were non-refractory for 90% of the time.
Like in the previous experiments, the effects of ectopic spiking on the sensory burst were immediately obvious. In this case, they were more pronounced: burst latency increased significantly with ectopic AP frequency (p = 0.03, Pearson correlation coefficient R2 = 0.4643, Figure 4Bii), further supporting the notion that membrane excitability at the burst start is lowered when ectopic APs enter the primary SIZ. Burst duration and the number of APs in a burst significantly decreased with ectopic AP frequency (AP number: p < 0.001, Pearson correlation coefficient R2 = 0.9152; duration: p = 0.001, Pearson correlation coefficient R2 = 0.7512, Figure 4Biii, iv), resulting in a greater than 40% reduction for both measurements at 10 Hz ectopic frequency. In contrast to the previous experiments, average and maximal burst frequency now changed significantly with ectopic AP frequency (R2 = 0.9192 and 0.7525 respectively, p < 0.001 and p = 0.001, Pearson correlation, Figure 4Bv, vi), following the same trend as already seen when ectopic APs did not penetrate the burst.
Taken together, our data indicate that ectopic APs invade the periphery where they affect sensory bursts in a frequency-dependent manner. This leads to the question; does this axon or its SIZ possesses distinct properties that facilitate the actions of invading ectopic APs, and if so, which properties may these be? To address this question, we created a computational model axon using NEURON [38]. The details of the model are given in the Materials and Methods. Briefly, the model was a linear axon trunk primary SIZ, and a single sensory dendrite. The axon and SIZ possessed active properties and were able to generate APs. The dendritic compartments were passive, i.e. did not possess any voltage-gated ion channels. Ectopic APs were elicited with pulsed current injections (40 nA, 1 ms) at different frequencies into the axon trunk. Ectopic APs propagated from the axon trunk towards the primary SIZ. Sensory bursts were elicited with ramp-and-hold current stimuli into the peripheral dendrites (Figure 5A). This assembly allowed us to reproduce ectopic APs that either penetrated the sensory burst (like in the case of strong synaptic inputs via axo-axonal synapses) or stopped upon burst start (like for spontaneous and modulated ectopic APs).
Comparison of membrane potential traces of AGR models without (A) and with (B) IKs at the primary SIZ. i: Truncated control sensory burst sensory burst, elicited by ramp-and-hold current in the peripheral dendrite. ii: With ectopic APs elicited in the axon trunk. Ectopic APs ended at the beginning of the sensory burst. Red arrowheads indicate ectopic stimulation. C. Corresponding changes in latency at different ectopic AP frequencies. Bottom: magnification of HH model burst latency. D. Changes in burst parameters with ectopic AP frequency. E. Comparison of burst shapes using instantaneous firing frequencies at burst start and end. AP number corresponds to the count of APs in the burst.
The simplest axonal configuration is probably the one described by Hodgkin and Huxley (HH) in their groundbreaking work on the squid giant axon [49]. HH axons are limited in that they only possess voltage-gated Sodium and Potassium currents in addition to the passive membrane properties. Thus, they may not reflect more complex propagation dynamics and AP modulation reported more recently for a variety of axons [4]. Nevertheless, HH axons explain the properties of AP initiation and propagation observed in many axons. To test which neuronal properties would facilitate the effects ectopic APs have on sensory bursts, we thus first started out with a HH axon that approximated biological firing frequencies. We implemented gate kinetics according to previously published axon models [6], and adjusted them to produce robust firing. We elicited sensory bursts of 3 s duration and approximately 30 Hz frequency. Figure 5A shows an example of these bursts following a 6 Hz ectopic stimulation sequence at its arrival at the peripheral SIZ. The corresponding sensory burst and a control burst without ectopic APs are shown as well. The sensory burst was unaffected by the presence of the ectopic APs. To exclude that this was due to the specific ectopic AP frequency used, we varied frequency from 1 to 10 Hz. We found no obvious influences on any burst parameters (Figure 5C, D, E, circles), with the exception of a small, but consistent frequency-dependent increase of burst latency with higher ectopic AP frequency (Figure 5C, bottom).
Which conductances could enable ectopic APs to affect sensory encoding then? In addition to the standard HH properties, AGR possesses several ionic conductances that may affect sensory encoding [40]. In specific, a slow hyperpolarization-activated cation current (Ih) seems to affect AP frequency in the sensory burst, and a slow Calcium-dependent Potassium current (IKs) seems to affect burst timing and structure such that firing frequencies during the burst accommodate and diminish towards burst end [40]. Slow conductances are common to many sensory neurons, including pain fibers [28, 50], for example. To test whether these slow ionic conductances may enable ectopic APs to exert a frequency-dependent effect on the sensory burst, we added them individually to our axon model. We first implemented Ih, with a time constant of 300 ms, according to previously published data in the stomatogastric ganglion [51]. While the sensory burst was strongly affected by the presence of Ih, this was independent of any ectopic firing, and adding ectopic APs at any frequency had no further influence on the burst (data not shown). This was also the case when we increased the Ih time constant to achieve 10× slower kinetics, as suggested by previous measurements in AGR [40]. Since Ih had no frequency-dependent effects on the sensory burst, we did not consider it further.
In contrast to Ih, Calcium-activated Potassium currents are activated when neurons depolarize, and are slow enough to maintain hyperpolarizing currents. When we implemented IKs in the primary SIZ, we saw a clear influence when we changed ectopic AP frequencies. Figure 5B shows the results from a model with 6 Hz ectopic AP frequency. Changes in ectopic AP frequency had similar effects to the biological system: with increasing ectopic AP frequencies, burst latencies increased, AP numbers in the burst decreased, and burst duration decreased (Figure 5C, D, diamonds). There was a small increase in average intraburst firing frequency, and a small decrease in the maximum firing frequency (Figure 5C, D). These frequency-dependent effects were most obvious between 1 and 5 Hz ectopic frequencies, and saturated at higher ectopic frequencies.
To also determine the effects of strong synaptic input at the axon trunk, we modeled continuous ectopic firing through the burst. Similar to what we observed experimentally, the effects of changes in ectopic AP frequency were exaggerated in comparison to when ectopic APs stopped with the burst onset. Specifically, there was an increase in burst latency that did not plateau with higher ectopic frequencies (Figure 5C). The maximum latency observed at 10 Hz was more than twice that of previous model. The effects on AP number and burst duration were also strengthened, resulting in larger decreases. There were again small effects on the average and maximum intraburst firing frequencies (less than 2 Hz). We noted that these small changes contrasted to the biological experiments. The smaller influence on maximum frequency is likely due to the strength of the ramp-and-hold current used, which was designed to reach biological relevant frequencies (~30 Hz). However, these frequencies are close to maximum frequencies the model can sustain. Consequently, the dynamic range around the maximum frequency might be limited.
To address the difference in average frequency between model and physiology, we assessed burst shape by measuring instantaneous firing frequencies at burst start and burst end (Figure 5E). We again compared the basic HH model with the ones containing the IKs. Firing frequencies in the HH model burst were not different from the control burst at any ectopic AP frequency, both at the beginning or end of the burst. In contrast, both models with IKS showed higher instantaneous firing frequencies at burst start when ectopic AP frequency was increased. Conversely, at the end of the burst, instantaneous firing frequencies were lower. These two effects were stronger in the model where ectopic APs continued through the burst. Together, these effects might explain why there are few changes in average intraburst firing frequency.
In conclusion, our experimental and model data demonstrate that antidromic APs can invade the primary SIZ of sensory neurons, and cause frequency-dependent modulation of sensory encoding at this site. Our model results suggest that for ectopic APs to exert their effects, ionic conductances with slow kinetics must be present at the primary SIZ.
We demonstrate that modulation of the axon trunk of a proprioceptive neuron influences the encoding of sensory information in the distant periphery. The frequency of ectopic APs initiated in the axon is increased by the biogenic amine Octopamine in a concentration dependent manner, leading to a larger number and higher density of APs that propagate towards and invade the sensory encoding SIZ. We show three frequency-dependent actions on sensory encoding with ectopic APs that stop once an orthodromic burst begins: (1) an increase in the onset latency, (2) a reduction of AP number, and (3) a reduction in the duration of the sensory burst. These effects are strengthened when ectopic APs are elicited throughout the burst, and there is a significant frequency-dependent decrease in the average and maximum burst frequencies. Computational models demonstrate that antidromic APs modify sensory encoding in generic neurons when slow ionic conductances are present. Thus, axonal neuromodulation serves to rapidly influence sensory encoding distantly from the sites of stimulus reception and AP initiation.
Sensory neurons are dynamic and change their responses in a state- and context-dependent manner. Consequently, their AP trains do not solely depend on stimulus properties, but also on internal and external conditions of the neuron. In recent years, increasing evidence about the ability of the neuromodulatory system to influence sensory systems has accumulated. Neuromodulation has been shown to modify the response to identical sensory stimulus and cause significant functional changes in behavior and perception by acting on intrinsic and synaptic properties [5]. Modulators like monoamines, peptides, and opiates, for example, alter reflexes such as startle responses [52]. While initially thought to be related to optimal energy expenditure, it is now clear that altering sensory responses is a widely used phenomenon to allow dynamic adaptations. Thus, neuromodulation allows organisms to modify neuronal and circuit responses to changing external and internal conditions, and allows sensory systems to contribute to not just one, but many behaviors.
More recently, many non-reflex sensory responses have been added to the list of modulated systems, including social communication [53], taste [54], olfaction [55], hearing [56], and pain [57]. For instance, the AP responses of mammalian pain and itch receptors are differentially affected by a variety of immune molecules and neuromodulators that alter nociceptive TRP channel activation during injury, inflammatory, and other pathological conditions [58], including Parkinson disease [59]. Neuromodulators also convey history- and state-dependent sensory responses. The receptor thresholds in newt primary olfactory receptors which determines odor perception sensitivity, for example, are modulated by adrenaline [55]. In the crustacean STNS, the AP response of a muscle stretch receptor is modulated by at least six distinct modulators, including monoamines, neuropeptides, and GABA [60, 61, 62]. These modulators switch how sensory information is encoded (from burst coding to AP coding), and encoding preciseness [63]. Neuromodulation enables the encoding process of both slow and fast processes to be largely plastic.
The actions and functions of neuromodulators on axons, as opposed to synaptic and dendritic regions, remain enigmatic, in part due to the common misconception that axons are only simple and robust carriers of information. Membranes of both myelinated and unmyelinated axon trunks are endowed with ionotropic and metabotropic receptors for transmitters and neuromodulators [4, 64, 65, 66], and several different types of ion channels (such as Ih [8, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76]; P, N and L type Ca channels [77, 78, 79, 80, 81, 82, 83, 84]), providing compelling evidence for axonal neuromodulation. While the origins of axonal modulators are often unknown, it is reasonable to assume that modulation stems from synaptic, paracrine, and endocrine sources [5, 85] and is an intricately balanced process that defines axon excitability. This results in more flexibility of propagation dynamics including conduction velocity and APs number [66, 86, 87, 88, 89, 90, 91, 92], thus increasing the computational and processing capabilities of the neuron [93, 94, 95, 96, 97]. Conversely, several disorders and pathologies of the neuromodulatory system severely impair neuronal communication and axonal properties [98, 99, 100].
A lesser-studied phenomenon is how axon modulation affects frequency encoding in neurons. Recent studies have suggested that the size and location of SIZs help regulate neuron excitability and define responses to synaptic inputs and membrane potential changes [101, 102, 103]. Moreover, pathologies and modulators can shift SIZ location [11, 32], or generate entirely new SIZs in the axon trunk. For example, hyper-excitability of spinal pain fibers in the dorsal horn is suggested to underlie chronic pain and itch [57]. Similarly, chronic inflammation can hyper-excite proprioceptive sensory axons and lead to ectopic APs that are initiated far from the primary SIZ and travel bi-directionally [11]. While common in many systems and neurons [4], including sensory neurons, the effects ectopic APs that travel antidromically towards the site of sensory reception may have on sensory encoding remain poorly understood.
We argue that antidromic traveling ectopic APs modify sensory encoding by invading the primary SIZ and modulating membrane excitability. This is a particularly intriguing concept, since it allows the modulatory system to alter sensory information before and after it is transduced, and as it travels towards the central nervous system. This is especially true when the ectopic AP frequency changes in different modulatory conditions, as we show for Octopamine modulation of AGR. In the STNS, modulatory descending projection neurons are a major source of neuromodulation [44, 104, 105], and it is reasonable to assume that these neurons modulate the AGR axon [106]. Given that descending modulatory projection neurons are a hallmark of most sensorimotor systems [107], axonal neuromodulation may be common and allow the nervous system to control its own sensory encoding.
The idea that backpropagating APs influence information encoding is not new. Studies in neocortex and hippocampus demonstrate that locally (at the axon initial segment) generated APs backpropagate into the dendritic areas, and modify subsequent signal encoding [2, 108]. To our knowledge, we are the first ones to directly show antidromic ectopic APs can serve a similar function, i.e. that APs generated distantly from the dendritic structures can affect information encoding. A similar phenomenon has been suggested in dorsal root ganglion cells [11, 13, 109]. The implications of antidromic ectopic APs and backpropagating APs from the axon initial segment are distinct though: APs initiated at the axon initial segment will always be elicited by dendritic activity, and therefore backpropagation can only affect future events. It thus can never modify the entirety of the information encoded. In contrast, ectopic APs influenced by axonal neuromodulation are not dependent on incoming sensory or synaptic events, and can thus modulate the entirety of the incoming sensory information. This may be a potential mechanisms by which motor systems control information entering the central nervous system.
Our data indicate that the effects ectopic APs have on sensory encoding depends on whether ectopic APs continue through the sensory burst or stop when it begins. Specifically, frequency-dependent decreases in average and maximal burst frequency are only present when ectopic APs continue through the burst. Though there are frequency-dependent changes in the burst onset latency, AP number, and burst duration in both paradigms, these effects are stronger when ectopic APs continue through the burst. This may be in particular pertinent to the treatment of neuropathologies using continuous high frequency stimulation [19, 110]. While the high frequency will overrun all sensory information, this may not be necessary to provide the best treatment. Examples for this come from the treatment of chronic neuropathic pain with spinal cord stimulation, where continuous stimulation is used to block all peripheral sensations with a tonic train of stimuli [111]. This prevents the perception of pain, but can result in paresthesia [112]. We show ectopic AP frequencies lower than sensory burst frequencies can change sensory encoding, suggesting high frequency stimulation may not be a prerequisite for treatment. Nevertheless, it seems reasonable to speculate about the relationship of sensory burst frequency and the ectopic APs frequency range, which modulates it. Higher frequencies of either SIZ leads to more ‘winner takes all’ situations, where the higher frequency SIZ simply overruns the lower frequency SIZ. The potential for modulation is thus limited by the opportunity of the ectopic APs to reach the encoding regions. In other words, the sensory AP frequencies must at some point fall below the ectopic AP frequency to allow them to invade the primary SIZ.
Our computational models indicate that a prerequisite for these actions is the presence of slow ionic conductances. While the detailed biophysical mechanisms that affected particular spike parameters are beyond the scope of this study, slow ionic conductances greatly influence neuronal behavior and responses to synaptic input. For example, transitions between tonic and bursting states are mediated by changes in slow Potassium currents and their functional antagonists, such as Ih, and persistent Sodium or T-type Calcium currents [29, 113]. In axons, slow conductances and membrane potential changes have been implicated in affecting axonal excitability and AP propagation. For example, slow potassium channels affect AP width and transmitter release in myelinated axons of cortex [30], and slow currents elicited by the Sodium-Potassium pump affect AP propagation in crustacean motor neurons [6]. It would not be surprising to find similar AP-induced, slow accumulating, currents in peripheral sensory axons or dendrites. For AGR, the main effect of the ectopic APs seems to stem from IKs, or a similar current that imposes a slow inhibitory action that accumulates as ectopic APs invade the primary SIZ. Axon modulation thus appears to give sensory neurons the opportunity to be more flexible, depending on the source and type of modulation, in their ability to encode stimuli. This may be particularly important for time critical processes, and behaviors that rely on time sensitive synaptic processes that require precise AP timing.
Many thanks to Carola Städele for helpful discussions of the data. Supported by NSF IOS 1354932.
Chlorophyll and carotenoid are important pigments that have been used as intrinsic optical molecular probes to observe plant performance during different phases of development. Chlorophyll and carotenoid are biosynthesized in chloroplast and their metabolism is closely related with the chloroplast development. Chlorophyll biosynthesis begins with the formation of 5-aminolevulinic acid (ALA) from glutamate (Glu) via Glu-tRNA synthetase, Glu-tRNA reductase (GluTR) and Glu-1-semialdehyde aminotransferase (GSA-AT) [1]. Eight molecules of ALA are condensed, eventually forming the symmetric metal-free porphyrin, protoporphyrin IX (Proto IX), which is a common precursor of haem and chlorophyll. The biosynthesis of chlorophyll continues by insertion of Mg2+ into Proto IX and followed by several steps in the chlorophyll cycle to create protochlorophyllide.
\nFurther, reaction is one of the most interesting steps because this is the first step in chlorophyll biosynthesis that requires light: the NADPH:protochlorophyllide oxidoreductase converts protochlorophyllide into chlorophyllide. This reaction is then continued to produce chlorophyll (chl) a and b. So, when dark-grown etiolated seedlings are exposed to light, protochlorophyllide is immediately converted to chlorophyllide and then further to synthesis of chl. Once chl a and b are formed and properly incorporated into the thylakoid membranes and associated photosystems, chloroplast is fully functional to do photosynthesis [2].
\nPlant carotenoids are synthesized and accumulated exclusively in plastids, most importantly, chloroplast and chromoplast [3]. There are two types of plant carotenoid: carotene, which is cyclized and uncyclized hydrocarbons, and xanthophylls, which are oxygenated derivatives of carotenes. Carotenoid synthesis is initiated by the formation of C40 compound phytoene by the head-to-head condensation of two molecules of geranylgeranyl diphosphate (GGDP) by phytoene synthase and then to a series of 4 sequential desaturation reactions, by two separate enzymes to produce lycopene, which has 11 conjugated double bonds [4]. Lycopene is then cyclized to α-carotene or β-carotene, which is then further hydroxylated to produce colorful xanthophylls such as lutein, β-cryptoxanthin, zeaxanthin, antheraxanthin, violaxanthin and neoxanthin. The biosynthesis and accumulation of carotenoids in the dark-grown etiolated seedling are essential for the assembly of membrane structure and benefits the development of chloroplast when seedlings emerge into the light [5]. Understanding the relationship between structure and photophysical properties of these pigments can provide insights into a better study of how photosynthesis works at the molecular level in chloroplast.
\nThe photophysical properties and functions of chlorophyll and carotenoid reside in their chemical structure. Chlorophylls are defined as cyclic tetrapyrroles carrying a characteristic isocyclic five-membered ring that are functional in light-harvesting or in charge separation in photosynthesis [6]. The chemical structure with IUPAC numbering scheme of chl a is shown in Figure 1. It is a squarish planar molecule, about 10 Å on a side. An Mg atom in the center of the planar portion is coordinated to four nitrogen atoms. The five rings in chlorophylls are lettered A through E, and the substituent positions on the macrocycle are numbered clockwise, beginning in ring A. Chlorophyll has two molecular axes: y-axis is defined as passing through the N atoms of rings A and C and x-axis passing through the N atoms of rings B and D. The delocalized π electron system extends over most of the molecule, except for ring D, in which the C-17—C-18 double bond is reduced to a single bond. The tail is formed by condensation of four isoprene units and is then esterified to ring D. It is often called phytol tail, after the polyisoprenoid alcohol precursor that is attached during biosynthesis. Because of the reduced ring D, plant chlorophylls such as chl a and b are classified as chlorins rather than porphyrins. These types of pigments have (in organic solvents) absorption bands around the blue and red spectral regions (Figure 2a), which are called B (or Soret) and Q bands, respectively, and arise from π→π* transition of the four frontier orbitals [7, 8]. One band each pair is polarized along the x-axis (Bx, Qx) and other along y-axis (By, Qy). The strong absorption band at the maximum absorption wavelength (λmax) 660 nm is called Qy transition band, which corresponds to the electronic transition polarized along the y-axis. The Qx-band of chl a shows a weak band near 550 nm, while the two overlapping Soret (B) bands show at about 430 nm. The chemical structure of Chl b is identical to chl a except at the C-7 position, where a formyl group replaces the methyl group. This structural change results in a shift of the Qy maximum absorption to shorter wavelength. The fluorescence spectrum of chlorophylls peaks at slightly longer wavelengths than the absorption maximum. The fluorescence emission (Figure 2b) is polarized along the y molecular axis, as it is emitted from the Qy transition. Shift of the emission to the longer wavelength side of the main transition is known as Stokes shift. In light reaction, chlorophyll plays as key pigment in the collection of light energy in the light-harvesting complexes and to carry out reversible photochemical redox reaction (Krasnovsky reaction) in the reaction centers.
\nChemical structure of Chl a (a), Chl b (b), lycopene (c), β-carotene (d), zeaxanthin (e) and lutein (f) with IUPAC numbering system.
(a) UV–Vis absorption of Chl a (black) and Chl b (red) in MeOH, (b) fluorescence emission spectra of Chl a (red) and Chl b (black) in MeOH, (c) β-carotene (red), zeaxanthin (black) and lutein (blue) in EtOH, (d) lutein in several organic solvents; MeOH (black), acetone (pink), diethyl ether (purple), hexane (light blue), EtOH (blue).
Structure of carotenoid is characterized by a linear chain of conjugated π-electron double bonds (Figure 1). In oxygenic organisms, carotenoid usually contains ring structures at each end, and most carotenoids contain oxygen atoms, usually as part of hydroxyl or epoxide groups. The primary molecular factor that gives rise to their strong absorption bands in the visible spectral region is the number of π-electron conjugated double bonds, N. The position of the absorption maxima is affected by the length of the chromophore, the position of the end double bond in the chain or ring and the taking out of conjugation of one double bond in the ring or eliminating it through epoxidation. Progressive movement to longer wavelengths (bathochromic shift) is illustrated by the absorption spectra of the acyclic carotenoid of increasing chromophore length. Carotenoids show different optical characteristics in various solvents, depending on the polarizability of the solvent [9, 10]; however, generally they have a typical three-peaked absorption spectrum with well-defined maxima and minima (fine structure) (Figure 2a). A ring closure as in β-carotene produces a less-defined fine structure. The introduction of a carbonyl group in conjugation with the polyene system produces a bathochromic shift and the loss of fine structure [4]. The influence of other substituents such as OH is negligible, for example, β-carotene, cryptoxanthin and zeaxanthin all have very identical absorption spectrums. Owing to the double bonds in the molecule, all carotenoids exhibit cis-trans isomerization (stereomutation). A cis double bond implies a configuration with the highest-priority group on the same side, whereas in the trans configuration they are on opposite sides. The absorption spectrum of a cis isomer presents a subsidiary peak in the near-ultraviolet, the cis peak; generally, it is located 143 nm from the longest wavelength maximum. For example, cis peak will appear at 330 nm if the longest wavelength maximum is 473 nm. In photosynthetic systems, carotenoid has essential functions. First, carotenoid is an accessory pigment in the collection of light energy in the spectral region which chl does not absorb and in transferring energy to a chl pigment [11, 12]. Second, carotenoid functions in a process called photoprotection by quenching triplet state of chl before it reacts with oxygen to form singlet oxygen species (ROS) [13, 14]. Third, carotenoid regulates energy transfer in the light-harvesting antenna through a process called xanthophyll cycle, to avoid over-excitation of the photosynthetic system by safely dissipating excess energy [15, 16].
\nIn the chloroplast interior, there are four main constituents in plant thylakoids, that is, photosystem II (PSII), cytochrome b6f, photosystem I (PSI) and the ATP synthesis. Chlorophylls and carotenoids are embedded in PS II and PSI, large pigment-protein clusters, the structures of which are perfectly adopted to ensure that almost every absorbed photon can be utilized to drive photochemistry. Both PSII and PSI consist of two moieties, that is, core complex or the reaction center that is responsible for charge separation and light-harvesting antenna complexes that surround the core complex and have functions to increase the capture of light energy and energy transfer to the reaction center in the core complex.
\nOne can detect chlorophyll and carotenoid bound in PSII and PSI in chloroplast by measuring their absorption and fluorescence spectra. Figure 3a (solid red line) shows the absorption spectrum of diluted chloroplast that is indicated by red shift of Chl a, Chl b and carotenoid’s bands because these molecules are bound as pigment-protein complexes in chloroplast. The Soret band of chl a in the complexes was detected at 438 nm while in the MeOH it was found at 432 nm (Figure 2a black line). The fluorescence emission spectra (Figure 3b) indicate a strong emission band of PSII complexes with maximum wavelength at (λmax) about 682 nm and weak emission band of PSI complexes with λmax at about 730 nm. It is shown here that Chl a acts as the main contributor to the excitation band at 434 nm and it shows that excitation at 434 nm (Soret band) produces stronger emission intensity, while the excitation at 475 and 512 nm, correspond to Chl b Soret band and carotenoid, respectively, produces weaker emission intensity. If we monitor the emission at 682 nm and measure the excitation spectrum, it shows that the PSII emission at 682 nm is the result of contribution from Chl a, Chl b and carotenoids (Figure 3a solid black lines) with bands at λmax about 414, 434, 475 nm, respectively.
\n(a) Overlaid of UV–Vis absorption (red) and fluorescence excitation (black) (λem = 682 nm) spectra of chloroplast and (b) emission spectra of chloroplast with excitation at 434 (black), 475 (red) and 512 (blue) nm. Measurements were conducted at ambient temperature. The isolation of chloroplast was carried out as follows: 20 g of suji leaves (Pleomele angustifolia) were washed with running water and cut. The leaves were then homogenized in 200 mL ice-cold isolation buffer (300 mM sorbitol, 50 mM HEPES-KOH pH 7.5, 2 mM EDTA, 80% acetone, 0.1% BSA) for 10 min in a cold environment, followed by filtration using cloth. Centrifugation was conducted in 2 steps, to discard cell debris at 200 g, 4°C, 20 min and to harvest chloroplast pellet at 3000 g, 4°C, 20 min. Final chloroplast pellet was collected and subjected to spectrum UV–VIS (Shimadzu UV-1700)and fluorescence measurement (Jasco FP-8500).
The current high-resolution structural models of antenna complexes have been obtained only for LHCII (2.72 Å) and recently for CP29 (2.8 Å) from PSII of spinach [17, 18]. Here we focus more on the LHCII structure. LHCII shows trimeric structure. Each monomeric contains three transmembrane α-helices, a, b and c (Figure 4a). One monomeric subunit contains eight chlorophyll (Chl) a pigments, six Chl b, two luteins (Lut), neoxanthin and one additional xanthophyll [17, 19]. The 14 chlorophylls are non-covalently attached in the protein cavity. Four carotenoid binding sites per monomer have also been characterized, but in this case the type of carotenoid bound can vary. Typically, two lutein molecules are in groves on both sides of helices a and b and have been likened to a cross-brace. A third carotenoid, 9-cis neoxanthin, is located in the Chl b-rich region near helix c. The fourth carotenoid is located at monomer-monomer interfaces in the trimer. It has been suggested that this site accommodates carotenoids that can participate in the xanthophyll cycle. It depends on the external stress level of the plant; the fourth carotenoid is either violaxanthin (no or low stress) or zeaxanthin (high stress) [20]. In this structure, the carotenoids are in van der Waals contact with the chlorophylls [9]. This is essential as carotenoids in LHCII act as accessory light-harvesting pigments and photoprotectors. The accessory light-harvesting function represents singlet-singlet energy transfer from the carotenoid to the chlorophylls. Since the singlet excited state lifetime of the carotenoid is quite short, approximately 200 fs, the carotenoid must be in close distance to a chlorophyll molecule if the energy transfer is to be efficient. Photoprotection function represents the quenching of triplet excited state of chlorophylls and so preventing the formation of singlet oxygen. This triplet-triplet exchange reaction also requires the carotenoid to be in close contact with the chlorophylls. Regarding CP29, it binds 3 carotenoids and 13 chlorophyll molecules [18]. The position of some chlorophyll binding sites in CP29 differs from LHCII.
\n(a) A view looking down on the top of trimeric complex of LHCII structure from spinach. Each monomer is colored magenta, yellow and pale green. The three-transmembrane helices (a, b and c) present in a monomer are labeled and are easily visible. Chl a molecules are in red, Chl b colored green and carotenoids colored orange. (b) Side-view of LHCII structure shows chlorophyll and carotenoid molecules are packed densely and close to each other (within van der Waals contact), enabling the crucial photo-protective role of these molecules to function by quenching triplet chlorophyll excited states. (c) Structure of PSII from Thermosynechococcus elongatus [28], a side-view representation of the overall dimer perpendicular normal with the pseudo-twofold symmetry axis. (e) PSII core reaction center is shown; component co-factors of the electron transport chain viewed along the membrane plane. The two branches are related by the pseudo-twofold symmetry axis. The respective pairs of pigments on the branches are labeled to indicate whether the Mg2_ is coordinated by D1, D2. (d) Structure of PSI from Synechococcus elongatus [29]; overview of the complete trimer looking along the membrane normal from the stromal side with each polypeptide of the trimer colored differently and chlorophyll molecules given in green. The two main proteins that comprise a monomer are PsaA (yellow) and PsaB (magenta). The electron transport chains are in the center of each monomer. (f) PSI core reaction center component co-factors of the electron transport chain are viewed along the membrane plane. The two branches are related by the pseudo-twofold symmetry axis. The representative pair of chlorophyll molecules on the branches are labeled A or B indicating whether the Mg2+ is coordinated by PsaA or PsaB. The iron–sulfur center of Fx involves residues from both PsaA and PsaB, while FA and FB are located in an extrinsic subunit called PsaC.
The current high-resolution crystal structure of PS II and PSI core complexes is limited to that from cyanobacteria and from pea, respectively [21, 22]. The core of PSII is a multi-subunit complex. Most of the chromophores involve light harvesting as well as electron transfer reaction and are bound to four main subunits, that is, D1, D2, CP43 and CP47. When the core of PSII and PSI reaction center structures is compared, the arrangement of the pigments and other electron transfer co-factors is also very similar (Figure 4c and d). Here, first we look at the PSII core reaction center. The core of reaction center of PSII is made from two major polypeptides called D1 and D2; each contains five membrane-spanning α-helices. These two helices clasp each other like two cupped hands holding on to each other. The redox cofactors are arranged into two arms that lie on either side of the point where the two groups of helices interact. This arrangement of the helices and the cofactors introduces a pseudo two-fold symmetry axes that runs through the center of reaction center normal to the plane of the membrane. In Figure 4e, it is seen that the electron transport pathway in PSII begins with a pair of chlorophyll molecules called P680 (PD1 and PD2). Then each arm contains, in order, one monomeric chlorophyll molecule, one pheophytin (a chlorophyll derivative) and one plastoquinone molecule. Here, only the D1 arm is active in electron transport. Upon excitation P680 becomes oxidized and one electron is injected out and passes down the active branch to the quinone QA. P680 is re-reduced by electron transfer from a special tyrosine residue called Z (Tyrz). A second turnover of P680 delivers a second electron to the plastoquinone and the secondary quinone QB is now reduced to QBH2. The hole on Tyrz is filled by electron transfer from the manganese cluster, the oxygen evolving complex. Every four turnovers of P680 stores four positive charges in the manganese cluster that are then used to oxidize water and evolve oxygen. While in CP43 and CP47, there are a total of 49 Chl a molecules that are bound and that function as internal antenna and allow excitation energy transfer from the peripheral antenna system to the reaction center.
\nUnlike PSII, in PS I, the same single polypeptides contain both antenna complexes (Lhca) and the reaction center core. The 3.3 Å resolution crystal structure of PSI from pea showed that plant PSI binds at least 173 Chl a and b molecules [22]. At this resolution of the crystal structure, it is not possible to identify the Chl species, but biochemical analysis of purified PSI indicated that it has a Chl a/b ratio in a range of 8.2–9.7 [23, 24]. A large number of Chl a and b molecules are bound to the Lhca protein, only about 100 Chl a are bound in the core complex, and the rest of Chl a and b are between these moieties. The latter represent the so-called “linker” chlorophylls which are located between Lhca monomers and “gap” chlorophylls (between Lhca and PSI core). The linker chlorophyll molecules probably play an important role in excitation energy transfer between Lhca antennas and from Lhca to the PSI core [20, 25, 26]. Based on biochemical analysis, PSI was reported to bind approximately 33/34 carotenoids, that is, about 12 carotenoid molecules are bound to Lhca, at the interface between Lhca and the core complex, and about 22 β-carotene are bound to the core [20, 23, 26]. Based on these biochemical analysis, it can be estimated that PSI-LHCII supercomplex contains about 215 chlorophyll and 45/46 carotenoid molecules.
\nThe core complex of PSI is composed of smaller number of subunits (15 subunit) than PSII. The large PsaA and PsaB subunit, which contain 11 trans-membrane helices each, forms a hetero-dimer that binds ~80 Chl a and ~20 β-carotene as cofactors for light harvesting as well as 6 Chl a, 2 phylloquinones and a 4Fe-4S cluster as cofactors for electron transfer reaction, with the exception of terminal electron acceptors (Fe-S clusters FA and FB) which are bound to the PsaC subunit [25]. At closer look (Figure 4f), the redox co-factors in the core reaction center are arranged into two arms that are located on either side of the region where two groups of helices interact with each other. Two chlorophylls form P700 and then each arm contains two monomeric chlorophyll molecules (the second one being in the equivalent position to the pheophytin present in photosystem II) followed by one quinone molecule. When P700 is oxidized, both arms of the electron transport pathway are able to work as it was reported that the electron can pass either down the B-branch or the A-branch [27].
\nChlorophyll and carotenoid can be isolated as free pigments, detached from the pigment-protein complexes, by organic solvent extraction. Important aspects such as the choice of organic solvents, light exposure and working temperature should be considered while isolating pigments. Based on the structure, chlorophyll is characterized with polar macrocycle ring with non-polar hydrocarbon tail. The structural difference between Chl b and Chl a is by having an aldehyde group in place of the methyl group at the macrocycle side group. This change is effecting the polarity of Chl b to be more polar in comparison to Chl a. In the case of carotenoid, structural difference can be seen from the number of conjugated double bonds and the presence of oxygen atoms. Considering these characteristics, mixtures of miscible polar and semi/non-polar solvents are used commonly to extract plant pigments. The mixture of solvent has double functions, that is, penetrating tissues/matrixes and extracting pigments from their lipophilic surrounding. During extraction, exposure of light should be avoided to reduce photodamage of the pigments. Temperature is also important. It is recommended to conduct extraction at lower temperatures, for example, on ice or using liquid nitrogen, to minimize activity of enzyme (e.g. chlorophyllase) that will catalyze breakdown. Antioxidant agent can be also added during extraction to avoid any unwanted oxidation.
\nAfter successful isolation, liquid chromatography has been widely used as an effective technique to separate individual type of pigments and for further purification. In this technique, the pigment separation is based on the polarity which depends on the interaction of pigment with the stationary and mobile phases. Elution method either normal phase or reversed phase is chosen according to the type of pigment to be separated. In addition, the choice of liquid chromatographic methods, namely thin layer chromatography (TLC), column chromatography (CC) and high-pressure liquid chromatography (HPLC), is referred to the speed, resolution and quantity of sample [30]. Currently, ultra-fast liquid chromatography (UFLC), a recent development of HPLC, has been used as a standard for liquid chromatography to achieve high-resolution data with low time consumption [31]. Purification with non-chromatographic method has also been developed, that is, purification method using dioxane has been effective to separate chlorophyll from most of the carotenoids and some lipids [32].
\nVarious types of column absorbents used for chromatographic separation of plant pigments have been well reviewed [30]. Here, we used a silica C30 column attached to UFLC analytic to achieve well separation of carotenoids from Pleomele angustifolia leaf using elution gradient program with mixture of water, methanol and methyl tert-butyl ether to separate, at least, 7 dominant pigments within 25 min. (Figure 5). The detailed identification of pigments, based on the chromatographic, spectrophotometric and mass properties, is summarized in Table 1. Chlorophyll a and chlorophyll b, α- and β-carotenes and violaxanthin are found to be the main chlorophylls and carotenoids, respectively, while the presence of lutein and zeaxanthin in this chloroplast is in low amount.
\nUFLC chromatogram of pigment extract from chloroplast of Pleomele angustifolia detected at 430 nm. The UFLC separation condition was as follows: Pigment separation was performed using UFLC equipped with PDA (Shimadzu) on C30 column (150 × 4.6 mm I.D; YMC) with a gradient elution program of water, methanol and methyl tert-butyl ether (MTBE) at the flow rate of 1 mL/min at 30°C.
Peak No | \ntR [min] | \nλmaxs [nm] | \nMolecular ion | \nFragment ions [m/z] | \nIdentification | \n|||
---|---|---|---|---|---|---|---|---|
HPLC eluent | \nHexane | \nEthanol | \nAcetone | \nspecies [m/z] | \n||||
1 | \n7.3 | \n412,436,464 | \n— | \n— | \n— | \n— | \n— | \nViolaxanthin | \n
2 | \n12.8 | \n470,601,650 | \n451,595,642 | \n465,601,649 | \n458,596,646 | \n907.7 [M]+ | \n881.7 [M – COH]+ 855.7 [M – COH – Mg]+ | \nChlorophyll b | \n
3 | \n13.4 | \n422,445,472 | \n422,444,473 | \n−,446,474 | \n−,448,476 | \n568.4 [M]+ | \n551.4 [M – OH]+ 476.4 [M – 92]+ 430.3 [M – 138]+ | \nLutein | \n
4 | \n15.3 | \n−,451,477 | \n425,449,478 | \n425,451, 478 | \n428,454,481 | \n568.6 [M]+ | \n476.4 [M – 92]+ | \nZeaxanthin | \n
5 | \n16.6 | \n431,618,664 | \n427,613,661 | \n430,616,664 | \n431,617,662 | \n893.5 [M]+ | \n871.5 [M – Mg]+ 615.2 [M – phytyl]+ | \nChlorophyll a | \n
6 | \n20.1 | \n421,446,473 | \n421,445,474 | \n421,446,476 | \n422,445,473 | \n536.6 [M]+ | \n445.4 [M + H – 92]+ | \nα-carotene | \n
7 | \n21.2 | \n–,452,478 | \n–,451,479 | \n–,453,480 | \n–,454,482 | \n536.6 [M]+ | \n444.5 [M – 92]+ | \nβ-carotene | \n
Chromatographic, spectrophotometric and mass properties of pigments separated from the chloroplast of Pleomele angustifolia.
Larger-scale separation of Chl a and b can be achieved by CC using Sepharose CL-6B as the stationary phase and a mixture of 2-propanol (IPA) and hexane as the mobile phase. Chl a could be eluted using 1.5% IPA in hexane and Chl b with 10% IPA in hexane [33]. To achieve a pure, free carotenoid, saponification step is sometimes necessary to eliminate contamination of lipids and chlorophylls. Moreover, carotenoid ester can be hydrolyzed to produce parent carotenoid by using this method [34]. CC is usually used for carotenoid isolation in high quantity of pigment extract. Generally, the purpose of CC is to separate mixtures into carotenoid fractions which are either having high purity to be processed to crystallization or low purity to be extensively separated with further chromatography, that is, HPLC [35].
\nSilica and alumina are frequently used as the absorbent in the CC with the normal phase elution to separate the distinct carotenoids; however, it is not easy to use this method to separate carotenoid isomers, that is, geometrical isomers, diastereoisomers, and so on. In this case HPLC/UFLC can be used to overcome the difficulty in the separation of carotenoids by CC. Turcsi et al. (2016) revealed that the polar carotenoids including optical isomers, and region and geometrical isomers as well as non-polar carotenes, could be well separated by HPLC on C18 and C30 columns, respectively [36]. High purity of isolated pigment can be achieved by HPLC and crystallization processes. UFLC analysis of the purified zeaxanthin shows that this carotenoid had a high purity of around 99.3% (Figure 2, left). All purified pigments have purity higher than 95% (Figure 6).
\nPurification of zeaxanthin: (a) chromatogram detected at 450 nm. Insert figure is UV–Vis spectrum measured by UFLC diode array detector in the eluent and (b) ESI-MS/MS spectrum identification. The conditions of UFLC and ESI-MS/MS analysis were as follows: UFLC analysis of the purified zeaxanthin was performed using UFLC equipped with PDA (Shimadzu) on C30 column (150 × 4.6 mm I.D; YMC) with a gradient elution program of water, methanol and MTBE at the flow rate of 1 mL/min at 30°C. The purified zeaxanthin was directly analyzed to LCMS 8030 (Shimadzu) with an isocratic elution of 0.1% formic acid (FA) in water (10%) and 0.1% FA in methanol (90%) at the flow rate of 0.3 mL/min. MS analysis was operated under the following conditions: (1) heat block temperature = 400°C; (2) desolvation line temperature = 250°C; (3) nebulizing N2 gas flow = 3 L/min; (4) drying N2 gas flow = 15 L/min; (5) interface voltage = 4.5 kV; (6) interface current = 0.1 μA; (7) mass range 400–700 m/z; (8) ionization mode = positive and negative.
Chromatographic, spectrophotometric and mass properties of pigment are minimum requirements for pigment identification [35]. These properties for all purified pigments are shown in the Table 1. In Figure 7 (right), absorption spectra of the purified chlorophyll a and the purified β-carotene in acetone have the same maximum absorption wavelength (λmax) and other spectral properties, such as the fine structure and spectrum shape, compared to these pigments in the references [37, 38]. Absorption spectrum of chlorophyll a in acetone shows typical Soret (431 nm), Qx (617 nm) and Qy (662 nm) bands, while two well-defined peaks in the absorption spectrum of β-carotene are found at 454 and 482 nm. This pigment analysis based on the results of spectrophotometer UV–Vis could support the advance pigment analysis using HPLC/UFLC equipped with photodiode array detection and coupled with the mass spectrometry. The LCMS technique has provided a power tool for pigment identification [39, 40]. Tentative identification for zeaxanthin peak separated by HPLC/UFLC analysis with PDA revealed that zeaxanthin has similar retention time (tR), maximum absorption wavelength (λmax) and the shape of absorption spectrum (data not shown) compared to the isolated zeaxanthin from corn which is a well-known source of zeaxanthin [41]. In addition the mass analysis provides the precursor and fragment ions at the specific m/z and characteristic fragmentation pattern for pigment identification. Mass spectrum of Chl a indicated the molecular ion [M]+ detected at m/z 893.6 and a fragment ion [M-Mg]+ at m/z 871.6 related to the loss of magnesium as the central metal of chlorophyll (Figure 1). This mass spectrum of Chl a agrees with the result that was reported [42].
\nPurification of Chl: (a) chromatogram detected at 660 nm. Insert figure is UV–Vis spectrum measured by UFLC diode array detector in the eluent and (b) ESI-MS/MS spectrum. The condition of UFLC and ESI-MS/MS analysis was as follows: UFLC analysis of the purified chlorophyll a was performed using HPLC equipped with PDA (Shimadzu) on C30 column (150 × 4.6 mm I.D; YMC) with a gradient elution program of water, methanol and MTBE at the flow rate of 1 mL/min at 30°C. The purified chlorophyll a was directly analyzed to LCMS 8030 (Shimadzu) with an isocratic elution of 0.1% formic acid (FA) in water (10%) and 0.1% FA in methanol (90%) at the flow rate of 0.3 mL/min. MS analysis was operated under the following conditions: (1) heat block temperature = 400°C; (2) desolvation line temperature = 250°C; (3) nebulizing N2 gas flow = 3 L/min; (4) drying N2 gas flow = 15 L/min; (5) interface voltage = 4.5 kV; (6) interface current = 0.1 μA; (7) mass range 400–1000 m/z; (8) ionization mode = positive and negative.
Chlorophyll and carotenoid are chloroplast pigments which are bound non-covalently to protein as pigment-protein complex and play a vital role in photosynthesis. Their functions include light harvesting, energy transfer, photochemical redox reaction, as well as photoprotection. The exact number and stoichiometry of these pigments in higher plants are varied, but their compositions include Chl a, Chl b, lutein, neoxanthin, violaxanthin, zeaxanthin and β-carotene. Liquid chromatography methods are well developed to separate and purify different types of pigments. Identification and characterization of pigments can be well observed by spectroscopy methods such as UV–Vis absorption, fluorescence and mass spectrometry.
\nTatas Hardo Panintingjati Brotosudarmo (THPB) acknowledges the competence research grant (No. 120/SP2H/LT/DRPM/IV/2017) from Kemenristekdikti for the financial support. We also acknowledge Chandra Ayu Siswanti who helped in preparation of chloroplast isolation, pigment isolation and UFLC separation works. We acknowledge Dr. Hendrik Octendy Lintang for supporting fluorescence measurements of photosystem II and I in chloroplast.
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I am also a member of the team in charge for the supervision of Ph.D. students in the fields of development of silicon based planar waveguide sensor devices, study of inelastic electron tunnelling in planar tunnelling nanostructures for sensing applications and development of organotellurium(IV) compounds for semiconductor applications. I am a specialist in data analysis techniques and nanosurface structure. 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