Automated Multimodal Stimulation and Simultaneous Neuronal Recording from Multiple Small Organisms

Summary

We present a method for the flexible chemical and multimodal stimulation and recording of simultaneous neural activity from many Caenorhabditis elegans worms. This method uses microfluidics, open-source hardware and software, and supervised automated data analysis to enable the measurement of neuronal phenomena such as adaptation, temporal inhibition, and stimulus crosstalk.

Abstract

Fluorescent genetically encoded calcium indicators have contributed greatly to our understanding of neural dynamics from the level of individual neurons to entire brain circuits. However, neural responses may vary due to prior experience, internal states, or stochastic factors, thus generating the need for methods that can assess neural function across many individuals at once. Whereas most recording techniques examine a single animal at a time, we describe the use of wide-field microscopy to scale up neuronal recordings to dozens of Caenorhabditis elegans or other sub-millimeter-scale organisms at once. Open-source hardware and software allow great flexibility in programming fully automated experiments that control the intensity and timing of various stimulus types, including chemical, optical, mechanical, thermal, and electromagnetic stimuli. In particular, microfluidic flow devices provide precise, repeatable, and quantitative control of chemosensory stimuli with sub-second time resolution. The NeuroTracker semi-automated data analysis pipeline then extracts individual and population-wide neural responses to uncover functional changes in neural excitability and dynamics. This paper presents examples of measuring neuronal adaptation, temporal inhibition, and stimulus crosstalk. These techniques increase the precision and repeatability of stimulation, allow the exploration of population variability, and are generalizable to other dynamic fluorescent signals in small biosystems from cells and organoids to whole organisms and plants.

Introduction

Calcium imaging techniques have allowed the noninvasive recording of in vivo neural dynamics in real time using fluorescence microscopy and genetically encoded calcium indicators expressed in target cells^1,2,3. These sensors typically use a green fluorescent protein (GFP), such as the GFP-calmodulin-M13 peptide (GCaMP) family, to increase the fluorescence intensity upon neuronal activation and elevated intracellular calcium levels. Calcium imaging has been especially powerful in the nematode C. elegans for examining how neurons and neural circuits function in living, behaving animals^{4,5,6,7,8,9,10}, as their transparent nature means no surgical process is required for optical access, and cell-specific gene promoters target expression to the cells of interest. These techniques often make use of microfluidic devices, which provide precisely controlled environments to study biological, chemical, and physical phenomena at a small physical scale^11,12. Microfluidic devices abound for measuring neural activity, with new designs continually under development, and they are readily fabricated in the research lab. However, many designs trap a single animal at a time, limiting the experimental throughput^7,9,13. Neural responses often vary substantially across animals due to differences in prior experience, internal states such as stress or hunger, or stochastic factors such as gene expression levels. These differences establish a need for methods that can simultaneously stimulate and observe many animals and extract information from individuals⁴.

In addition, certain neuromodulatory phenomena become apparent only under specific stimulation conditions, such as temporal inhibition¹⁴, which refers to the brief suppression of responses when stimulation occurs in rapid succession. Electrophysiological systems can drive neural activity across a broad stimulus space for this purpose, modulating, for example, the electrical pulse current, voltage, frequency, waveform, duty cycle, and timing of periodic stimulus trains. Indirect stimulation by naturally detected stimuli or optogenetic systems would benefit from a similar breadth of control mechanisms. Currently, many natural stimuli are presented in a simple "on-off" manner, such as odor presentation and removal, using commercial systems that have been slow to add flexibility. However, inexpensive microcontrollers can now automate the delivery of several types of stimuli in a manner that is customizable to the researchers' needs. Combined with microfluidics, these systems have achieved the goal of increased experimental throughput and flexibility, allowing neural responses to a variety of precise stimuli to be measured simultaneously in many animals^4,6. Multimodal stimulation can be used to further interrogate the neuronal circuitry, such as by monitoring changes in neural excitability when consistently stimulating before, during, and after an orthogonal perturbation such as drug exposure⁴. The benefits of inexpensive, open microscopy systems are clear for advancing scientific research, yet in practice, the need for part sourcing, construction, and performance validation can impede the adoption of these techniques.

This protocol aims to alleviate some of these technical challenges. Whereas previous protocols have focused on microfluidic device use and basic stimulation^9,15,17, we describe here the construction and use of a flexible, automated, multimodal stimulus delivery system for neural imaging in C. elegans or other small organisms utilizing previously described microfluidic devices⁴. The open-source system is programmed via simple text files to define the experiments, and the NeuroTracker data analysis program semi-automatically extracts the neural activity data from the microscope videos. We demonstrate this system with examples of assessing temporal inhibition, disinhibition, and stimulus crosstalk using the chemosensory neuron AWA, which depolarizes in response to different food odors or in response to light when expressing optogenetic light-sensitive ion channels^5,6.

Protocol

1. Neural imaging equipment

NOTE: See Lawler and Albrecht¹⁵ for detailed instructions on building the imaging and stimulation system, which controls the microscope illumination timing, image acquisition, and stimulus delivery (Figure 1). An inexpensive Arduino Nano stimulus controller actuates the fluidic valves through digital signals to a valve controller and controls the optogenetic illumination through analog voltage signals to an LED controller. Other stimuli, such as vibration motors and thermal heaters, can be controlled using digital or analog signals. The stimulus controller synchronizes the stimulation and image recording via camera signals, as specified by the open-source Micro-Manager microscope control software (µManager)¹⁶. See the Table of Materials for details related to all the materials, reagents, equipment, and organisms used in this protocol.

1. Set up the neural imaging equipment, including an epifluorescence microscope with GFP optics, an sCMOS camera with a digital exposure output signal, and a stimulus controller¹⁵.
2. Connect the stimulus controller to the desired systems via digital or analog signals. For the examples presented below, the following systems are used:
   1. Use a valve controller for chemical stimulation. Connect the valve controller to fluidic solenoid or pinch valves (Figure 1)¹⁵.
   2. Use a 615 nm red LED and controller for optogenetic stimulation, mounted above the microscope stage.
3. Set up the computer with the microscope control software, create a Configuration Preset with equipment settings, and ensure proper operation of the stimulus control¹⁵.

2. Microfluidic device fabrication

NOTE: See Lagoy et al.¹⁷ for detailed information about obtaining or fabricating the master molds and the production, use, and cleaning of the microfluidic devices. These steps are summarized below.

1. Obtain or fabricate a master mold using the microfluidic design file provided (albrechtlab.github.io/microfluidics)¹⁷. For young adult C. elegans, ensure that the channel height is 55-70 µm.
2. Combine the PDMS base and curing agent at a 10:1 ratio by weight and mix thoroughly with transfer pipettes.
3. Degas for 30-60 min in a vacuum desiccator until the bubbles disappear.
4. Place the master mold into a large (150 mm diameter) Petri dish, and pour the degassed PDMS up to a depth of 4-5 mm (~100 g). Inspect and remove any dust or bubbles with a transfer pipette.
5. Bake at 65 °C on a level oven shelf for 3 h to overnight.
6. Once cured, use a scalpel to cut the PDMS from the mold and a straight razor blade to separate the devices.
7. Punch inlet and outlet holes using a 1 mm dermal punch, and clean them with dH₂O, ethanol, and again with dH₂O. Dry the device in an airstream (see Figure 2A).
8. Clean both sides of the PDMS device with adhesive tape, removing any dust or debris.
9. Prepare the glass slides to complete the microfluidic device as described¹⁷. Drill inlet holes in the top slide using a diamond bit, and render the bottom slide hydrophobic by exposure to TFOCS vapors or by applying water-repellant glass treatment (Figure 2B).
10. Assemble the glass-PDMS device sandwich into a clamp (Figure 2C).

3. Animal preparation

1. Obtain or create animals with genetically encoded calcium indicators expressed in the neurons of interest.
   NOTE: For example, line NZ1091 (kyIs587 [gpa-6p::GCaMP2.2b; unc-122p::dsRed]; kyIs5662 [odr-7p::Chrimson:SL2:mCherry; elt-2p::mCherry]) expresses GCaMP and the red light-sensitive cation channel Chrimson in the AWA sensory neuron pair⁶. Both transgenes are integrated into the genome for stable expression in every animal.
2. One day before experimentation, place at least 20 L4 larval stage C. elegans per experiment onto a nematode growth medium (NGM) agar plate seeded with an OP50 E. coli lawn. When maintained at 20 °C, this will synchronize the wild-type animals at the young adult stage the next day.
   NOTE: For array transgenes, pick animals using a fluorescence stereoscope to ensure transgene expression in the chosen animals.

4. Solution preparation

1. Prepare 1x S Basal buffer (100 mM NaCl and 0.05 M KPO₄, pH 6.0) from a 10x stock solution.
2. Prepare 1 mM tetramisole buffer by diluting 1 M stock in 1x S Basal. Use this paralytic buffer to prepare all the stimuli. An experiment typically uses about 150 mL.
3. Add 0.1-1 µg/mL fluorescein to the "control" buffer reservoirs to visualize the flow.
4. Create stimulus solutions by serial dilution to the desired final concentration. For example, create a 10⁻⁷ dilution of diacetyl attractant by first creating a 10⁻³ stock.
   NOTE: A small amount of fluorescein (0.1–1 µg/mL) may be added to the stimulus or buffer solution to verify stimulus timing, but concentration should be minimal to avoid artifacts in neural fluorescence.

5. Microfluidic device preparation

NOTE: See Reilly et al.⁹ for a video protocol showing the reservoir generation, device setup, and the loading of the animals. See also Lagoy et al.¹⁷ for a written protocol including many helpful tips.

1. Prepare three or more fluid reservoirs. For each, attach a 30 mL or 60 mL syringe reservoir, a 3 mL priming syringe, and a needle stub to a three-way Luer valve (Figure 2D). Connect the needle to microbore tubing fitted with a metal tube at the end. Label the reservoirs, mount them onto a rack attached to a ring stand, and fill them with the corresponding buffer or stimulus fluids (Figure 2E).
2. Degas the assembled microfluidic device in a vacuum desiccator for ~1 h.
3. Fill and remove the air bubbles from the reservoir tubing using the priming syringe. Fill the outflow tubing with buffer.
4. Remove the microfluidic device from the vacuum, and quickly insert the outlet tubing and inject the fluid through the device until a droplet emerges from one inlet.
5. At this inlet, use a "drop-to-drop" connection¹⁷ to insert the corresponding fluidic inlet tube (Figure 2F). Ensure that liquid drops are present on both the inlet tubing and the device port hole to avoid introducing a bubble.
6. Inject more fluid from the outlet, connect the next inlet tube, and repeat until all the inlets are filled. Insert a solid blocking pin at any unused inlets and the worm loading port.
7. Initiate flow by opening the inlet and outlet Luer valves. Inspect the device for leaks at the inlets and glass base. Inspect the device for any bubbles within the flow channels or inlets using the microscope image capture software in live mode.
   ​NOTE: If bubbles are present, wait for them to absorb into the PDMS material.

6. Animal loading

NOTE: See Lagoy et al.¹⁷.

1. Transfer young adult animals onto an unseeded NGM agar plate using a wire-tipped "pick".
2. Flood the plate with approximately 5 mL of 1x S Basal buffer such that the animals are swimming.
3. Draw the worms into a loading syringe (1 mL or 3 mL syringe with attached tubing that has been prefilled with 1x S Basal).
   1. Using a stereoscope, move the tubing end below the liquid surface with one hand to each desired animal, and draw it into the tubing using the syringe held in the other hand.
   2. Draw the worms only into the tubing, not into the syringe.
      NOTE: The tubing typically holds only about 100 µL. The animals can be expelled into a local area and then drawn again into the tubing with a small volume.
4. Close the outlet line, remove the worm loading pin, and connect the worm loading syringe to the device using a drop-to-drop connection.
5. Gently flow the animals into the arena, establish buffer flow, and allow up to 1 h for immobilization by tetramisole.
   ​NOTE: During the immobilization period, ensure that only buffer fluid enters the arena. The stimulus and control reservoirs can be turned off during this period but open them and verify the correct flow before running the stimulation trials.

7. Automated stimulation and neuronal recording

1. Create a stimulus definition text file called "User Defined Acquisition Settings.txt" with a text editor (e.g., Notepad) containing the stimulation settings for the automated image acquisition (see examples in Figure 3). The settings are divided into two sections:
   1. Microscope acquisition settings: Define the experiment type (Single-Stimulus or Multi-Pattern), exposure and excitation timing, trial duration and intervals, and save directory.
   2. Stimulation settings: Define the stimulus control parameters. A "stimulation command" specifies the actions occurring at certain video frames with the syntax <letter code><frame number>, where the letter codes are A = valve1, B = valve2, C = valve3, L = LED light; additionally, uppercase = on and lowercase = off. The LED intensity is set with the letter code "i" and a value of 0 (off) to 255 (maximum brightness).
      NOTE: The LED intensity value from 0 to 255 sets the output analog voltage from 0 V to 5 V. The current controller used here has a linear intensity scaling, and others should be calibrated with a light power meter.
      1. For a Single-Stimulus experiment with only one repeated stimulation command, use the format in Figure 3A.
      2. For a Multi-Pattern experiment with multiple stimulation commands, use the format in Figure 3B. Include a "Pattern Sequence" of digits that represents the order of the stimulus patterns. For each pattern, enter a stimulation command on a separate line.
         NOTE: A pseudorandom sequence or m-sequence can be useful to investigate stimulus history dependence.
2. Run the microscope control software. Verify that all the fluidic inlets are open, the flow is as desired within the arena (see Figure 2H), and the neurons of interest are in focus within the live window.
3. Close the live window and run the script "MultiPattern_RunScript.bsh" within the software.
   NOTE: It is useful to run a test experiment without animals to verify proper flow and stimulation. Substituting a different fluorescein concentration for each stimulus fluid can help visualize and document new stimulus patterns.
4. After experimentation, disassemble the microfluidic device, and rinse all the surfaces, tubing, and reservoirs with water.
   ​NOTE: All the components can be reused dozens of times if kept clean. Ensure that reservoirs, tubing, and microfluidic devices are maintained wet or fully dried in an air stream to avoid salt crystallization, which can clog and is difficult to remove. The devices can be kept in ethanol to sterilize but should be fully dried before reuse (>1 h at 65 °C)¹⁷.

8. Data analysis using NeuroTracker

NOTE: NeuroTracker^4,18,19 is an ImageJ/FIJI²⁰ software plugin for tracking the fluorescence intensity of multiple neurons and animals, even as they move during trials. This plugin saves data as text files with each neuron's position and background-corrected fluorescence intensity (F). The fluorescence data are normalized to the baseline fluorescence (F₀), for example, the average of several seconds prior to stimulation, as ΔF/F₀ = (F -F₀)/F₀, which can be averaged across populations.

1. Install NeuroTracker scripts as instructed (github.com/albrechtLab/Neurotracker).
2. Run NeuroTracker by clicking on Plugins | Tracking | NeuroTracker.
3. Select the folder containing the .TIF video files to be tracked, and select the desired settings.
   NOTE: If only a subset of the video files are to be tracked, select the numerical range of the files to analyze at the prompt. Default tracking settings are appropriate for nonmotile animals at 250 pix/mm resolution. Adjust the parameters proportionally for other resolutions. See the User Guide¹⁹ for further settings information.
4. Set the intensity threshold such that the neurons are visible for selection (Figure 4).
5. Open the Brightness/Contrast (B/C) and Threshold control windows using the Image | Adjust menu.
6. In the B/C window, adjust the Minimum and Maximum sliders until the neurons are clearly distinguishable (Figure 4A).
7. In the Threshold window, check Dark background and Don't Reset Range.
8. Slide the frame slider to observe the neuron movement and intensity changes, noting any animals to exclude from tracking, such as due to overlap with other animals.
9. Identify the neurons for tracking.
10. For each animal, adjust the threshold level such that the red threshold area above the neuron is visible in every frame before, during, and after stimulation.
11. Click on the neuron to record its position and threshold level.
12. Repeat the threshold adjustment and selection for each animal and neuron to track. See Figure 4C for a good threshold level example and Figure 4D,E for over-threshold and under-threshold examples. Previously selected neurons are indicated by a small box.
13. When all the neurons are selected, press the spacebar to begin tracking.
    NOTE: For additional NeuroTracker examples, see previous references^4,19.
14. Monitor the tracking process for each animal, and make any necessary corrections.
15. If NeuroTracker pauses, it has lost the neuron. Reclick on the neuron, adjusting the threshold level as needed.
16. If the integration box jumps to another nearby animal or non-neuronal structure, press the spacebar to pause, move the slider back to the first erroneous frame, and reclick on the correct neuron location.

9. Data exploration and visualization

NOTE: The MATLAB analysis script is used for data processing and visualization and to generate summary PDFs for each analysis.

1. Run the "NeuroTrackerSummary_pdf.m" file in MATLAB, and select the folder containing the NeuroTracker data text files.
2. Wait for a summary PDF to be produced, allowing the verification of the tracking process (Figure 5). Animals are identified by a number (Figure 5A), and the neural responses from each animal and trial can be viewed to assess the population variability (Figure 5B).
3. Use the function "databrowse.m" to explore the neural data, for example, grouping by trial number (Figure 5C), by animal number (Figure 5D), by stimulation pattern, or by another category.

Results

We present several examples of stimulus patterns that assess different neural phenomena, including temporal inhibition, adaptation, and disinhibition. Temporal inhibition is the momentary suppression of a neural response to a second stimulus presentation occurring shortly after the initial presentation¹⁴. To test this phenomenon, in a paired-pulse experiment, eight patterns consisting of two 1 s odorant pulses separated by an interval ranging from 0 s to 20 s were presented (

Discussion

In this protocol, we describe an open-access microscopy system for the assessment of neural activity phenomena using the temporally precise delivery of different stimulus patterns. The microfluidic platform delivers repeatable stimuli while keeping tens of animals in the microscope field of view. Few commercial microscopy software packages allow for the easy programming of various stimulus timing patterns, and those that do often require the manual entry of each pattern or proprietary file formats. In contrast, experimen...

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
Bacterial strains
E. coli (OP50)	Caenorhabditis Genetics Center (CGC)	Cat# OP50
Experimental models: Organisms/strains
C. elegans strains expressing GCaMP (and optionally, Chrimson) in desired neurons	Caenorhabditis Genetics Center (CGC) or corresponding authors of published work	NZ1091, for example
Chemicals, Treatments, and Worm Preparation Supplies
2,3-Butanedione	Sigma-Aldrich	Cat# B85307	diacetyl, example chemical stimulus
Calcium chloride, CaCl2	Sigma-Aldrich	Cat# C3881
Fluorescein, Sodium salt	Sigma-Aldrich	Cat# F6377
Glass water repellant	Rain-X	Cat #800002250	glass hydrophobic treatment (single-use)
Magnesium chloride, MgCl2	Sigma-Aldrich	Cat# M2393
Nematode Growth Medium (NGM) agar	Genesee	Cat #: 20-273NGM
Petri dishes (60 mm)	Tritech	Cat #T3305
Poly(dimethyl siloxane) (PDMS): Sylgard 184	Dow Chemical	Cat# 1673921
Potassium phosphate monobasic	Sigma-Aldrich	Cat# P5655
Potassium phosphate dibasic	Sigma-Aldrich	Cat# P8281
Sodium chloride, NaCl	Sigma-Aldrich	Cat# S7653
(tridecafluoro-1,1,2,2-tetrahydrooctyl)trichlorosilane (TFOCS)	Gelest	CAS# 78560-45-9	glass hydrophobic treatment (durable)
Software and algorithms
Arduino IDE	Arduino	https://www.arduino.cc/en/software
ImageJ	NIH	https://imagej.nih.gov/ij/
MATLAB	MathWorks	https://www.mathworks.com/products/matlab.html
Micro-manager	Micro-manager	https://micro-manager.org/
Microscope control software	Albrecht Lab	https://github.com/albrechtLab/MicroscopeControl
Neurotracker data analysis software	Albrecht Lab	https://github.com/albrechtLab/Neurotracker
Automated Microscope and Stimulation System
Axio Observer.A1 inverted microscope set up for epifluorescence (GFP filter cubes, 5× objective or similar)	Zeiss	Cat #491237-0012-000
Excelitas X-cite XYLIS LED illuminator	Excelitas	Cat #XYLIS
Orca Flash 4.0 Digital sCMOS camera	Hamamatsu	Cat #C11440-22CU
Arduino nano	Arduino	Cat #A000005
3-way Miniature Diapragm Isolation Valve (LQX12)	Parker	Cat #LQX12-3W24FF48-000	Valve 1: Control
2-way normally-closed (NC) Pinch Valve	Bio-Chem Valve Inc	Cat #075P2-S432	Valve 2: Outflow
3-way Pinch Valve	NResearch	Cat #161P091	Valve 3: Stimulus selection
Optogenetic stimulation LED and controller (615 nm)	Mightex	Cat #PLS-0625-030-S and #SLA-1200-2
ValveLink 8.2 digital/manual valve controller	AutoMate Scientific	Cat #01-18
Wires and connectors	various	See Fig. 2 of Cell STARS Protocol (Lawler, 2021)
Microfluidic Device Preparation
Dremel variable speed rotary cutter 4000	Dremel	Cat #F0134000AB	Set speed to 5k RPM for cutting glass
Dremel drill press rotary tool workstation	Dremel	Cat #220-01
Diamond drill bit	Dremel	Cat #7134
Glass slide, 1 mm thick	VWR	Cat #75799-268
Glass scribe (Diamond scriber)	Ted Pella	Cat #54468
Luer 3-way stopcock	Cole-Parmer	Cat #EW-30600-07
Luer 23 G blunt needle	VWR	Cat #89134-100
Microfluidic device	Corresponing author or fabricate from CAD files associated with this article	N/A
Microfluidic device clamp	Warner Instruments (or machine shop)	P-2
Microfluidic tubing, 0.02″ ID	Cole-Parmer	Cat #EW-06419-01
Tube 19 G, 0.5″	New England Small Tube	Cat #NE-1027-12