Using Changes in Leaf Transmission to Investigate Chloroplast Movement in <em>Arabidopsis thaliana</em>

Martina K&#246;niger; Anna Knapp; Lauren Futami; Susan Kohler

doi:10.3791/62881

JoVE Journal > Environment

環境学

Using Changes in Leaf Transmission to Investigate Chloroplast Movement in Arabidopsis thaliana

Published: July 14, 2021

doi:

10.3791/62881

Martina Königer¹, Anna Knapp¹, Lauren Futami¹, Susan Kohler¹

¹Department of Biological Sciences,Wellesley College

概要

Many plant species change the positioning of chloroplasts to optimize light absorption. This protocol describes how to use a straightforward, home-built instrument to investigate chloroplast movement in Arabidopsis thaliana leaves using changes in the transmission of light through a leaf as a proxy.

Abstract

Chloroplast movement in leaves has been shown to help minimize photoinhibition and increase growth under certain conditions. Much can be learned about chloroplast movement by studying the chloroplast positioning in leaves using e.g., confocal fluorescence microscopy, but access to this type of microscopy is limited. This protocol describes a method that uses the changes in leaf transmission as a proxy for chloroplast movement. If chloroplasts are spread out in order to maximize light interception, the transmission will be low. If chloroplasts move towards the anticlinal cell walls to avoid light, the transmission will be higher. This protocol describes how to use a straightforward, home-built instrument to expose leaves to different blue light intensities and quantify the dynamic changes in leaf transmission. This approach allows researchers to quantitatively describe chloroplast movement in different species and mutants, study the effects of chemicals and environmental factors on it, or screen for novel mutants e.g., to identify missing components in the process that leads from light perception to the movement of chloroplasts.

Introduction

Light is essential for photosynthesis, plant growth, and development. It is one of the most dynamic abiotic factors as light intensities not only change over the course of a season or day, but also rapidly and in unpredictable ways depending on the cloud cover. At the leaf level, light intensities are also influenced by the density and nature of the surrounding vegetation and the plant's own canopy. One important mechanism that allows plants to optimize light interception under variable light conditions is the ability of chloroplasts to move in response to blue light stimuli¹^,². Under low light conditions, chloroplasts spread out perpendicular to the light (along the periclinal cell walls) in a so-called accumulation response, maximizing light interception and hence photosynthesis. Under high light conditions, chloroplasts move towards the anticlinal cell wall in a so-called avoidance response, minimizing light interception and the danger of photoinhibition. In many species, chloroplasts also assume a specific dark position, which is distinct from the accumulation and avoidance positions and often intermediary between those two³^,⁴. Various studies have demonstrated that chloroplast movement is not only important for the short-term stress tolerance of leaves⁵^,⁶^,⁷, but also for the growth and reproductive success of plants, especially under variable light conditions⁸^,⁹.

Chloroplast movement is readily observed in real time in certain live specimens (e.g., algae or thin-leafed plants like Elodea) using light microscopy¹. Studying chloroplast movement in most leaves, however, requires a pretreatment to induce chloroplast movement, chemical fixation, and preparation of cross sections before viewing the samples under a light microscope¹⁰. With the introduction of confocal laser microscopy, it also became possible to image the 3D arrangement of chloroplasts in intact or fixed leaves⁴^,¹¹^,¹². These imaging techniques greatly aid the understanding of chloroplast movement by providing important qualitative information. Quantifying chloroplast positioning (e.g., as a percentage of chloroplasts in the periclinal or anticlinal positions in these images or the percentage of area covered by chloroplasts per total cell surface) is also possible but quite time-consuming, especially if conducted at the intervals necessary to capture rapid changes in positioning¹⁰^,⁸. The simplest way to show whether dark-adapted leaves of a certain species or mutants are capable of chloroplast movement into the avoidance response is by covering most of the area of a leaf to keep the chloroplasts in the dark while exposing a strip of the leaf to high light. After a minimum of 20 min of high light exposure, the chloroplasts in the exposed area will have moved into the avoidance position, and the exposed strip will be visibly lighter in color than the rest of the leaf. This is true for wild type A. thaliana but not for some of the chloroplast movement mutants described in more detail later on¹³. This method and modifications of it (e.g., reversing what parts of the leaf are exposed, changing light intensities) are useful for screening large numbers of mutants and to identify null mutants that lack either the ability to exhibit an avoidance or accumulation response or both. However, it does not provide information about the dynamic changes in chloroplast movement.

In contrast, the method described here allows for the quantification of chloroplast movement in intact leaves using changes in light transmission through a leaf as a proxy for overall chloroplast movement: under conditions when chloroplasts are spread out in the mesophyll cells in the accumulation response, less light is transmitted through the leaf than when many chloroplasts are in an avoidance response, positioning themselves along the anticlinal cell walls. Hence, changes in transmission can be used as a proxy for the overall chloroplast movement in leaves¹⁴. The details of the instrument are described elsewhere (see Supplementary File), but basically, the instrument uses blue light to trigger chloroplast movement and measures how much red light is transmitted through that leaf at set intervals. More recently, a modification of this system has been described, which uses a modified 96-well microplate reader, a blue LED, a computer, and a temperature-controlled incubator¹⁵.

The option to use a combination of methods, including the optical assessment of leaves for screening, followed by measuring dynamic changes in transmission and the use of microscopy, has greatly aided our understanding of both the underlying mechanisms and the physiological/ecological significance of chloroplast movement. For example, it led to the discovery and characterization of various mutants, which are impaired in specific aspects of their movements. For example, A. thaliana phot 1 mutants lack the ability to accumulate their chloroplasts in low light, while phot 2 mutants lack the ability to perform an avoidance reaction. These phenotypes are due to an impairment in two respective blue light receptors¹⁶^,¹⁷^,¹⁸. In contrast, chup1 mutants lack the ability to form proper actin filaments around the chloroplasts which are essential to move the chloroplasts into the desired position within a cell¹¹^,¹⁹. In addition to mutant studies, researchers have assessed the effects of various inhibitors on chloroplast movement to elucidate the mechanistic aspects of the process. For example, chemicals such as H₂O₂ and various antioxidants were used to investigate the effects of this signaling molecule on chloroplast movement²⁰. Various inhibitors were used to elucidate the role of calcium in chloroplast movement²¹. In addition to helping to uncover the mechanisms of chloroplast movement, these methods can be used to compare chloroplast movement in various species or mutants grown in different conditions in an attempt to understand the ecological and evolutionary context of this behavior. For example, it has been shown that the extent of the effects of various mutations in the chloroplast movement pathway are dependent on the growth conditions⁷^,⁹, and that sun-adapted plants do not seem to move their chloroplasts much. In contrast, movement is very important for shade plants¹⁰^,²²^,²³.

This methods paper, focused on the model plant A. thaliana, describes how to use a transmission device which is an updated version of a previously developed instrument⁹. While this instrument is not commercially available, people with a basic understanding of electronics or the help of engineering or physics colleagues and students will be able to build the instrument using affordable parts and following the detailed instructions (see Supplementary File). The open-source platform used to build the instrument has extensive web support and a community forum which offers help should problems arise²⁴.

The protocol focuses on how to use the instrument to determine changes in leaf transmission in a standard exploratory run that exposes a leaf to a wide range of light conditions and captures the dark, accumulation, and avoidance reactions of A. thaliana. These runs can be modified depending on the goal of the experiment and can be used with most plant species. The paper provides examples of transmission data of A. thaliana wildtype and several mutants and shows how to further analyze the data.

Protocol

1. Preparing leaves for a run

Place 8 A. thaliana plants in the dark overnight (> 6 h works for most species) to ensure that the chloroplasts move into their dark position. All replicas start with comparable transmission values.
Alternatively, place 8 complete leaves into a Petri dish with a moist filter paper at the bottom, close the Petri dish, and wrap it with aluminum foil.

2. Testing if the transmission device works

Connect the transmission device to a stable power source and press the power switch (ON/OFF button) of the device to reset the instrument (Figure 1A,B).
Connect the iPad to a stable power source, press the Home Screen button to activate the screen, and enter the passcode to log in.
Press the Settings icon, press the Display & Brightness icon, press Auto-Lock, and select Never by pressing this option to ensure that the screen stays on permanently. Otherwise the program will stop running when the screen goes to sleep. Press the Home Screen button to return to the main screen.
Double press the Home Screen button to see which applications are open, and close all of them by swiping them towards the top of the screen. Press the Home Screen button to return to the main screen.
1. Find the LeafSensor app on the main screen or by swiping left or right. Press the icon of the app to open it (see Supplementary File). A green screen with text and white fields will appear to enter the information.
2. Ensure the word Connected is seen in the lower part of the screen as it indicates that the app is communicating with the transmission device. If the message 'Adafruit NOT Found' appears, check that the device is plugged in and press the start button on the device again.
Fill in the first 4 fields on the app page to name the experiment and to set up the conditions for a brief test run without leaves and with the leaf clips open:
1. Name the experiment (use 8 or fewer uppercase letters or numbers) e.g., by typing TEST into the field named Expt Name.
2. Choose how many different blue light intensities will be used in the experiment, e.g., by typing 3 into the field named # Light Intensities.
3. Choose the blue light intensities for this run (choose an integer between 0 and 3000 and separate each number from the next with a comma; see Supplementary File on how to convert these numbers into actual blue light intensities of LEDs) e.g., by typing 0,100,1000 into the field named Blue Intensities.
4. Choose the length of time each blue light intensity will shine onto the leaf (separate each number from the next with a comma) e.g., by typing 2,2,2 into the field named Blue Duration (minutes).
Press Start Experiment in the middle section of the screen. In the lower part of the screen 8 hyphens and the message Starting Experiment will appear.
1. Ensure that no light is being emitted from the LEDs for the first two minutes, then weak blue light is being emitted, and after 2 min the blue light intensity is increasing.
2. Ensure that intense red light is being emitted from the LEDs once a minute for the measurements.
  NOTE: As the experiment is running, numbers will appear on the app page for each of the eight sensors, and data will be updated once a minute. Ensure the output numbers from the photodiodes are around 1000-1023 (if the room is dark). An update on the lower left shows how many measurements were done so far e.g., Done 1 of 6 measurements (one measurement each minute).
3. When the experiment is done, check for the appearance of the Experiment finished on the lower left of the app page. Now the instrument is ready for a run with leaves.
Press twice the Home Screen button, swipe out of the app and open it again. Press the ON/OFF button on the instrument to reset it.

3. Setting up leaves in the leaf clips

NOTE: This step has to be done in the dark with a green light source (e.g., place a green filter in front of a light bulb) to avoid inducing chloroplast movement. Alternatively, use very low white light and an extended dark period in the leaf clips. Remember, one part of the leaf clip holds the LED (larger opening), while the other holds the phototransistor (Figure 1C).

If the plants are dark-adapted entire, pick 8 leaves wide enough to cover the LEDs. Otherwise, remove the leaves from the Petri dish. Prepare 8 strips of filter paper about the length of a leaf clip and with a hole punched out at the top to not cover the LED.
1. Moisten the filter paper and place it onto the leaf clip part that holds the LED. Repeat this for each of the eight leaf clips.
Place each leaf on the top of the wet filter paper of its leaf clip. Ensure the correct leaf side is facing towards the LED (usually experiments are done with the adaxial leaf surface facing the LED).
1. Avoid placing the midribs of the leaf on top of the LEDs, and for more consistent results, place similar parts of each leaf (e.g., the widest section of the leaf) over the LED.
2. Place the other leaf clip part with the phototransistor on top. Use a rubber band to hold the two leaf clip parts together if needed (Figure 1C,D).
Place each leaf clip into its 'boat' and fill the reservoirs with water using a pipette. Ensure the leaf or at least the filter paper touches the water to avoid dehydration of the leaves during the run (Figure 1D).

4. Conducting a run

NOTE: For a standard exploratory run, start out with 4 h of darkness (0 µmol photon m^-2 s^-1), followed by 7 h of low blue light (2 µmol photon m^-2 s^-1), followed by 60 min each of 5, 10, 30, 40, 50, 60, 90, 100 µmol photon m^-2 s^-1 of blue light. This will induce the leaves to exhibit their dark transmission, induce chloroplast movement into the maximum accumulation, and show different degrees of avoidance response.

Set up the LeafSensor app on the iPad using the steps described below.
1. タイプ EXPLORA1 into the field named Expt Name.
2. タイプ 10 into the field named # Light Intensities.
3. タイプ 0,1,60,160,550,750,950,1150,1350,1950 into the field named Blue intensities.
4. タイプ 240,420,60,60,60,60,60,60,60,60 into the field named Blue Duration.
Press Start Experiment. After the first min, the output values (usually between 990 and 820) will appear on the screen. If the values are far off, check if the leaves were placed correctly into the leaf clips.
When the run is done, ensure that the message Experiment Finished appears at the bottom left of the screen. Data will be saved automatically.
1. Put the screen in the upright position (not horizontal). Two new options will appear on the screen, namely Save and Utilities.
2. Press Utilities and a list of saved files will appear. Select the file of interest, in this case, EXPLORA1.
3. Below the list of files , look for Selected Expt: EXPLORA1. Press Eメール, enter an email address, and the data file will be automatically attached to the message. Press Send.
  NOTE: If there is a long delay until the files arrive, restart the app and send the file again.
If a run was aborted, but data up to that point are of interest, press Save before selecting Utilities. After several runs, clean up the memory space: Press Utilities, select one file at a time, swipe left next to file, and press Delete to remove file.
Press 戻る to run another experiment or if done, press the Home Screen button, swipe to the main screen, press Settings, press Display & Brightness, press Auto-Lock, and press 2 Minutes.

5. Data analysis

Download the file EXPLORA1 from the email, add extension .csv to the file, double-click on the file. Data will be sorted into a spreadsheet with the data for the eight different sensors sorted into separate columns. The last column shows the time (in seconds) at which the data were collected. Delete the first row under the headings (Sensor1-8) if it contains nonsensical data.
Set up a master data sheet that will contain the results for each sensor in a separate sheet and that converts the output values into % transmission values using the equations obtained from the calibration of each leaf clip and sensor (see Supplementary File).
1. Copy each data set into a separate data sheet (e.g., column A contains the time; column C contains the data of Sensor1).
2. Set up column B so that it converts time from seconds to minutes. Set up column D so that it contains the formula to convert voltage to % transmission using the equation from the calibration.
3. Set up a similar data sheet for each sensor and remember the formula used to convert the voltage output into % transmission values may be different for each sensor.
Plot % transmission (T) against time, min (Figure 2).
Save the data sheet under a new name so that the master data sheet can be reused.
To further analyze data (Figure 2), calculate ΔT (%) accumulation (e.g., change of T at maximum accumulation compared to T at dark), ΔT (%) avoidance (e.g., change of T at maximum avoidance compared to T at dark), or dT/dt (%/h) (e.g., change in T during the fastest part of the accumulation or avoidance reaction). For further details see ⁸.

Representative Results

The different parts of the transmission device are shown in Figure 1. The microcontroller is the control unit of the device and controls the light conditions that the leaves, secured in black leaf clips, are experiencing, and stores the light transmission data it receives (Figure 1A,B). A close-up of the control unit of the instrument shows the ON/OFF button, the SD card for data storage capability, the Bluetooth shield (which sends the data to the LeafSensor app), and the cables that connect to the LEDs (Light Emitting Diodes) and phototransistors. The microcontroller is positioned at the base of the instrument, and only the edges are visible in the picture (Figure 1B). 3D-printed, black leaf clips hold the leaves, LEDs, and phototransistors in place. A wet filter paper is positioned on the leaf clips part with the LED such that the LED is unobstructed, and a dark-adapted leaf is positioned with the adaxial leaf surface facing the LED. The schematic shows that the LED and phototransistor are positioned on the opposite sides of the leaf. The LED can emit blue or red light. The blue light is used to induce chloroplast movement and is turned off for a brief period every minute during which the red measuring light shines onto the leaf. The phototransistor, positioned on the opposite side of the leaf, detects how much red light is transmitted through the leaf and sends the data to the microcontroller and SD card (Figure 1C). The two parts of the leaf clip are assembled, and placed into a 3D-printed 'boat' that is filled with water and helps keep the leaf moist during the experiment (Figure 1D).

Figure 2 shows a typical data set in which the % transmission data are plotted against time (min). This particular transmission run involved 1 h of darkness, followed by 3 h of low blue light (2 µmol photon m^-2 s^-1), and 1 h each of intermediate (30 µmol photon m^-2 s^-1) and high blue light (100 µmol photon m^-2 s^-1) intensities. The data show that the transmission in A. thaliana decreases at low light intensities (accumulation response), while an avoidance response is induced when light intensities further increased. This is not an all or nothing response and the degrees of changes relative to the dark values depend on the exact blue light intensities. These percent changes in transmission (ΔT) can be calculated using the formulas shown below the data. In addition, the speed of transmission changes (dT/dt) during the initial changes in transmission when an accumulation or avoidance response is triggered can be calculated using the slope of the curve.

The average % transmission values of wild type (WT) (Figure 3A), as well as phot 1 and phot 2 mutant A. thaliana leaves (Figure 3B) during 19 h long runs are shown. Such extended, exploratory transmission runs are helpful to establish which blue light intensities to use in future runs. The leaves were first exposed to 4 h of darkness, and consistent transmission values indicate that the leaves were fully dark-adapted, which will make the data between replicas more consistent. For the next 7 h, the leaves were exposed to low blue light (2 µmol photon m^-2 s^-1). In WT and phot 2, the initial fast decrease in transmission is followed by a slow decrease which indicates that the chloroplasts were moving into the accumulation response. Depending on the species used, it may take different amounts of time to obtain the lowest possible transmission. In many cases, a researcher may only be interested in comparing various mutants at a given time point, so the exposure to very low light may be limited to an hour. Compared to WT, phot 1 shows a reduced accumulation response. The extended exposure to low blue light is followed by a stepwise increase in blue light intensities each hour (5, 10, 30, 40, 50, 60, 90, 100 µmol photon m^-2 s^-1). The % transmission in A. thaliana WT and phot 1 increases with each increase in light intensity, showing that the chloroplasts move into the avoidance response but this is not seen in phot 2. The degrees of change in transmission relative to the dark value (ΔT) depend on the exact blue light intensities and may differ depending on the genotype (Figure 3C). An example is shown of the speed of transmission changes (dT/dt) during the initial responses in transmission when avoidance is triggered as the blue intensity is increased from 5 to 10 µmol photon m^-2 s^-1 (Figure 3D). The speed is the same for WT and phot 1, while it is very slow for phot 2 mutants.

Figure 1: Overview of the transmission device. Picture of the home-built transmission device with the control unit in the black box on the bottom right and the leaf clips on top and the bottom left (A). Close-up of the control unit with the ON/OFF button, the SD card for data storage capability, and the Bluetooth shield for wireless communication. Cables connect the control unit to the Light Emitting Diodes (LEDs) and phototransistors. The microcontroller is positioned at the base of the instrument and only the edges are visible in this picture (B). The 3D-printed black leaf clips: on the left the leaf clip part holding the LED is shown, on the right the leaf clip part holding the phototransistor is shown. To set-up a run, a moist filter paper (with a hole the size of the LED) is placed on the clip without obscuring the LED. Then the leaf is placed in the clip covering the LED. The schematic shows that the LED and the phototransistor (PT) are located opposite each other, close to the leaf, when the two parts of each leaf clip are assembled (C). Leaf clips are positioned into 3D-printed 'boats' that are filled with water, keeping the leaves and the filter papers hydrated (D). Please click here to view a larger version of this figure.

Figure 2: Transmission data of a typical A. thaliana leaf. Transmission (T) data for an A. thaliana leaf that was exposed to dark for 1 h, followed by 3 h of low light (2 µmol photon m^-2 s^-1), followed by 1 h each of intermediate (30 µmol photon m^-2 s^-1) and high blue light (100 µmol photon m^-2 s^-1). Low light intensities induced the accumulation response, while higher light intensities induced different degrees of an avoidance response. The T levels at dark serve as the baseline (blue line). The % changes in T relative the dark levels (ΔT) e.g., at maximum accumulation or different levels of avoidance (differences to dark T are indicated by the blue arrows) can be calculated. In addition, the speed with which T changes (dT/dt) e.g., during the initial phase of the avoidance response can be calculated from the slope of T plotted against time (indicated by the blue triangle). The equations are shown below the graph. Please click here to view a larger version of this figure.

Figure 3: Chloroplast movement in wildtype and mutant A. thaliana leaves. Dark adapted, mature leaves were exposed to dark for 4 h, followed by a 7 h exposure to 2 µmol photon m^-2 s^-1, followed by a step wise increase in blue light intensity each hour (5, 10, 30, 40, 50, 60, 90, 100 µmol photon m^-2 s^-1). Average % Transmission (T) values (n = 20) of WT (A) as well as phot 1 and phot 2 leaves (B). Change in % T relative to the dark values: negative values indicate that the leaves showed an accumulation response, while positive values indicate an avoidance response. The numbers on the right indicate the blue light intensity at which the ΔT data were calculated. The color scheme is the same as in the rest of the figure (C). The dT/dt data were calculated as leaves responded to an increase in blue light intensity from 5 to 10 µmol photon m^-2 s^-1 and indicate the speed with which % T changed per hour (D). Data for A and B are means, for C and D means ± SD (n = 20). Please click here to view a larger version of this figure.

Supplemantary File. Please click here to download this File.

Discussion

The device is extremely easy to use but it is of crucial importance to calibrate each leaf clip set-up of the transmission device independently since the positioning of the LEDs and phototransistors may slightly vary from leaf clip to leaf clip. Ensure the LEDs and phototransistors are inserted stably and re-check the calibration if the data seem off. Avoid getting water onto the device. The leaves in the leaf clips are placed into 'boats' filled with water to avoid water stress. Place these boats e.g., into a low rimmed plastic container separate from the control unit and do NOT knock them over. Do not unplug or bend the cable connections. Be careful when inserting leaves into the leaf clips and avoid pulling or bending the cables too much.

It is important to dark-adapt the leaves long enough to ensure the initial transmission values are representing the dark position. Check that the values during the dark period in the device have been stable at least 30 min before shining blue light onto the leaves. If they are not, dark-adapt the leaves for a longer period of time before the next run or extend the dark period in the transmission device to monitor how long it takes for the leaves to reach a steady state. Typically, the transmission data are presented as % change in transmission at a given blue light intensity relative to the dark value (ΔT). Hence it is crucial to obtain the correct baseline values.

The exploratory run can be used for any A. thaliana mutant (including mutants known to affect other aspects of a plant's physiology e.g., photosynthesis, myosin or uncharacterized mutants) or different species as long as the leaf area is large enough to cover the LED in the leaf clip and the leaves are not too thick. The program can be easily adapted to fill any needs of a researcher e.g., the blue light intensities can be changed within the ranges that have been shown to elicit chloroplast movement (the reaction saturates around 100 µmol photon m^-2 s^-1), the exposure times can be altered, the number of consecutive light conditions can be changed. In addition, leaves can be pretreated before being run in the device e.g., with inhibitors of actin polymerization or signaling pathway components, which is important for researchers who want to fill in the blanks in the signaling pathway regulating chloroplast movement.

Like every method, this one too has its limitations and drawbacks. The procedure relies on changes in the optical properties of leaves, namely how much light is transmitted. Therefore, it works best with relatively thin leaves, while thick leaves often do not allow for sufficient transmission of red light to be detected beyond the noise level. It would be possible to modify the transmission device to increase the red-light intensity shining onto the leaf and increase the sensitivity of the phototransistors by changing the resistors. Since the method only provides an integrated measure of the movements of chloroplast in all cells and cell layers, one may miss some subtle changes e.g., chloroplasts moving in opposite directions may result in no net change of transmission. Especially when working with previously uncharacterized mutants or species, it is important to complement the transmission results with images of chloroplast positioning using microscopy. For example, slow changes in transmission in response to changes in blue light intensity were observed in an A. thaliana mutant and could have been due to a range of reasons. Microscopy revealed that cells only had two chloroplasts which were much larger than normal chloroplasts. The mutant was later confirmed to be the chloroplast division mutant arc6-1²⁵.

開示

The authors have nothing to disclose.

Acknowledgements

Funding was provided by a Fiske Award and a Wellesley College Faculty Award.

Materials

Aluminum foil
Dark adapted leaves
Filter paper
iPad with LeafSensor app installed (see Supplemental Info)
Pipette	Any
Petri dish	Any
Transmission device (see Supplemental info)
Water

参考文献

Senn, G. . Die Gestalts- und Lageveränderung der Pflanzenchromatophoren. , (1908).
Zurzycki, J. The influence of chloroplast displacements on the optical properties of leaves. Acta Societatis Botanicorum Poloniae. 30, 503-527 (1961).
Wada, M., Kagawa, T., Sato, Y. Chloroplast movement. Annual Review of Plant Biology. 54, 455-468 (2003).
Wada, M. Chloroplast movement. Plant Science. 210, 177-182 (2013).
Kasahara, M., Kagawa, T., Oikawa, K., Suetsugu, N., Miyao, M., Wada, M. Chloroplast avoidance movement reduces photodamage in plants. Nature. 420, 829-832 (2002).
Davis, P. A., Hangarter, R. P. Chloroplast movement provides photoprotection to plants by redistributing PSII damage within leaves. Photosynthesis Research. 112, 153-161 (2012).
Howard, M. M., Bae, A., Königer, M. The importance of chloroplast movement, nonphotochemical quenching, and electron transport rates in light acclimation and tolerance to high light in Arabidopsis thaliana. American Journal of Botany. 106 (11), 1-10 (2019).
Gotoh, E., et al. Chloroplast accumulation response enhances leaf photosynthesis and plant biomass production. Plant Physiology. 178, 1358-1369 (2018).
Howard, M. M., Bae, A., Pirani, Z., Van, N., Königer, M. Impairment of chloroplast movement reduces growth and delays reproduction of Arabidopsis thaliana in natural and controlled conditions. American Journal of Botany. 107 (9), 1309-1318 (2020).
Trojan, A., Gabryś, H. Chloroplast distribution in Arabidopsis thaliana (L.) depends on light conditions during growth. Plant Physiology. 111, 419-425 (1996).
Oikawa, K., et al. Chloroplast unusual positioning is essential for proper chloroplast positioning. The Plant Cell. 15, 2805-2815 (2003).
Königer, M., Bollinger, N. Chloroplast movement behavior varies widely among species and does not correlate with high light stress tolerance. Planta. 236, 411-426 (2012).
Kagawa, T., et al. Arabidopsis NPL1: a phototropin homolog controlling the chloroplast high-light avoidance response. Science. 291, 2138-2141 (2001).
Berg, R., et al. A simple low-cost microcontroller-based photometric instrument for monitoring chloroplast movement. Photosynthesis Research. 87, 303-311 (2006).
Johansson, H., Zeidler, M. Automatic chloroplast movement analysis. 分子生物学. 1398, 29-35 (2016).
Briggs, W. R., et al. The phototropin family of photoreceptors. Plant Cell. 13, 993-997 (2001).
Jarillo, J. A., et al. Phototropin-related NPL1 controls chloroplast relocation induced by blue light. Nature. 410, 952-954 (2001).
Sakai, T. Arabidopsis nph1 and npl1: blue light receptors that mediate both phototropism and chloroplast relocation. Proceedings of the National Academy of Sciences, USA. 98 (12), 6969-6974 (2001).
Wada, M., Kong, S. -. G. Actin-mediated movement of chloroplasts. Journal of Cell Science. 131, 1-8 (2018).
Wen, F., Xing, D., Zhang, L. Hydrogen peroxide is involved in high blue light-induced chloroplast avoidance movements in Arabidopsis. Journal of Experimental Botany. 59 (10), 2891-2901 (2008).
Tlalka, M., Fricker, M. The role of calcium in blue-light dependent chloroplast movement in Lemna trisulca L. The Plant Journal. 20, 461-473 (1999).
Königer, M., Bollinger, N. Chloroplast movement behavior varies widely among species and does not correlate with high light stress tolerance. Planta. 236, 411-426 (2012).
Higa, T., Wada, M. Chloroplast avoidance movement is not functional in plants grown under strong sunlight. Plant, Cell and Environment. 39, 871-882 (2016).
. Arduino.cc Available from: https://www.arduino.cc (2021)
Königer, M., Delamaide, J. A., Marlow, E. D., Harris, G. C. thaliana leaves with altered chloroplast numbers and chloroplast movement exhibit impaired adjustments to both low and high light. Journal of Experimental Botany. 59, 2285-2297 (2008).

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Königer, M., Knapp, A., Futami, L., Kohler, S. Using Changes in Leaf Transmission to Investigate Chloroplast Movement in Arabidopsis thaliana. J. Vis. Exp. (173), e62881, doi:10.3791/62881 (2021).

Using Changes in Leaf Transmission to Investigate Chloroplast Movement in Arabidopsis thaliana