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Method Article
This protocol describes a standard intermittent-access two-bottle choice home cage drinking paradigm to model alcohol consumption in rats. In addition, it provides step-by-step instructions to augment the standard protocol with a DIY lick detection system that enables microstructural analysis of drinking behavior.
Two-bottle choice home cage drinking is one of the most widely used paradigms to study ethanol consumption in rodents. In its simplest form, animals are provided with access to two drinking bottles, one of which contains regular tap water and the other ethanol, with daily intake measured by change in bottle weight over the 24 h period. Consequently, this approach requires no specialized laboratory equipment. While such ease of implementation is likely the greatest contributor to its widespread adoption by preclinical alcohol researchers, the resolution of drinking data acquired using this approach is limited by the number of times the researcher measures bottle weight (e.g., once daily). However, the desire to examine drinking patterns in the context of overall intake, pharmacological interventions, and neuronal manipulations has prompted the development of home cage lick detection systems that can acquire data at the level of individual licks. Although a number of these systems have been developed recently, the open-source system, LIQ HD (Lick Instance Quantifier Home cage Device), has garnered significant attention in the field for its affordability and user friendliness. Although exciting, this system was designed for use in mice. Here, we review appropriate procedures for standard and lickometer-equipped two-bottle choice home cage drinking. We also introduce methods for adapting the LIQ HD system to rats including hardware modifications to accommodate larger cage size and a redesigned 3D printed bottle holder compatible with standard off-the-shelf drinking bottles. Using this approach, researchers can examine daily drinking patterns in addition to levels of intake in many rats in parallel thereby increasing the resolution of acquired data with minimal investment in additional resources. These methods provide researchers with the flexibility to use either standard bottles or a lickometer-equipped apparatus to interrogate the neurobiological mechanisms underlying alcohol drinking depending on their precise experimental needs.
Although moderate alcohol use has historically been associated with moderate health benefits, recent large-scale comprehensive studies have revealed that no amount of alcohol consumption is safe1,2. In fact, alcohol use is the 7th leading risk factor for death and disability globally1 with individuals who drink even small amounts of alcohol having increased risk for cancers, infectious diseases, and injury1,3. In the United States, deaths from alcohol use increased by almost 30% between 2016 and 20214. Importantly, the risk of death and disability increases monotonically with increased consumption1.
Although studies in humans have provided valuable insight into the neurobiology of alcohol use and misuse, the experimental control afforded by animal models is crucial for an in-depth understanding of the mechanisms underlying drinking behavior and risk for heavy drinking. These models are also valuable tools for the development of treatments aimed at reducing uncontrolled consumption. Two-bottle choice home cage drinking is one of the most widely used preclinical paradigms to study alcohol consumption in rodents. This is due, in large part, to its ease of implementation as it allows for the measurement of total voluntary alcohol drinking and preference without the need for specialized research equipment or complex analyses. Using this approach, researchers can collect measurements at their desired intervals (e.g., hours, days, weeks) by calculating the change in bottle weight from the beginning to the end of a drinking session. Variations on this basic method have been used by many in the field to facilitate low to moderate to binge levels of alcohol intake over both short and long periods of time. For example, continuous and intermittent two-bottle choice procedures have been used to facilitate low and moderate levels of alcohol intake, respectively, in both mice5 and rats6,7,8. The same paradigms can promote high levels of intake in alcohol-preferring strains7,9. Alternatively, an adaptation of this method that limits alcohol access to 2-4 h daily beginning approximately 3 h after the start of the dark cycle has been shown to engender binge drinking in mice (i.e., Drinking in the Dark)10,11. Additional variations on these methods have been used in conjunction with methods that facilitate alcohol dependence (i.e., chronic intermittent ethanol vapor exposure) to examine the escalation of voluntary alcohol drinking during withdrawal12,13,14,15,16,17,18,19.
Although widely adopted by the field, the standard approach of measuring alcohol intake by change in bottle weight is limited in resolution to total consumption per drinking session. Consequently, this approach is unable to capture drinking patterns, which are well known to impact both the risk for and severity of alcohol use disorder (AUD)20,21,22. Indeed, an individual's average intake over time can be a consequence of several heavy drinking episodes or many drinking episodes each associated with relatively low consumption and these nuances go undetected when consumption is measured as total intake per drinking session. Importantly, significantly more drinking episodes associated with large drinking bouts (i.e., gulping) are observed in individuals with AUD relative to healthy controls23 and data in nonhuman primates suggests that individuals who establish a pattern of alcohol consumption that includes large drinking bouts early in their drinking history are at significant risk for AUD22. Moreover, drinking episodes that include large bouts of consumption significantly increase risk for morbidity and mortality independent of AUD diagnosis21. Altogether, these data have led to increased interest in examining drinking patterns in addition to levels of overall intake in preclinical models and has prompted the development of a number of systems of varying complexity that are able to capture drinking data at the level of individual licks.
Among the first was the development of a two-bottle system equipped with photobeam lick detection designed for use in mice24. This system was subsequently adapted by a separate group for use in rats25. In the years since, variations on this theme have been used to develop similar systems contained within custom rodent housing26, that allow for lick detection of individual socially housed animals27,28, and that capture both feeding and drinking behavior29. Among these, LIQ HD (Lick Instance Quantifier Home cage Device)30 has garnered significant attention for offering a system for use in mice that parallels the ease of implementation and affordability of the system developed by Godnyuck et al.24. This system utilizes capacitive sensing to directly detect contact between the tongue and the conductive metal sipper tube, as opposed to indirect measures such as sipper approach or interaction that are afforded using the photobeam detection system. The authors provide data demonstrating that their capacitive sensing system affords significantly greater precision and sensitivity in lick detection, producing stronger correlations between lick number and change in bottle weight than photobeam detection. The authors further demonstrate the ability to use this system in conjunction with a continuous access two-bottle choice home cage drinking paradigm to capture measures of alcohol drinking microstructure in addition to measures of overall daily intake30.
Here, we describe procedures for two-bottle choice home cage alcohol drinking using a standard approach as well as methods that enable lick detection (Figure 1). We also introduce methods for building and implementing LIQ HDR - an adaptation of LIQ HD30 for use in rats that includes hardware modifications to accommodate larger cage sizes and a redesigned 3D-printed bottle holder compatible with standard off-the-shelf bottles. These methods provide researchers with the flexibility to use either a standard or lickometer-equipped approach depending on their experimental resources and data collection needs.
Below is a description of the materials needed and step-by-step instructions for capturing home cage drinking using the intermittent-access two-bottle choice drinking procedure adapted from Simms et al.7. In this procedure, rats are provided 24 h access to two drinking bottles 7 days a week. On Mondays, Wednesdays, and Fridays (MWF), rats receive one bottle containing water (H2O) and another bottle containing ethanol (EtOH). These bottles are removed on Tuesdays, Thursdays, and Saturdays (TRS) and replaced with two bottles of water. Rats drink from the same two bottles of water on Saturdays and Sundays. Note that these methods can easily be adjusted for alternate schedules of ethanol access (e.g., continuous, binge, etc.) if desired. Separate instructions are provided for standard and lickometer-equipped approaches.
All representative data were collected using singly-housed adult Long-Evans rats with the approval of the University of Illinois Chicago Institutional Animal Care and Use Committee and in accordance with the NIH Guidelines for the Care and Use of Laboratory Animals. Single housing is required in order to accurately monitor fluid consumption by each subject. Adult male (n = 38) and female (n = 22) Long-Evans rats were P50-80 upon arrival and allowed to acclimate to the vivarium for one week prior to starting the experiment. Rats had ad libitum access to standard chow (Teklad 7912, Envigo) and water unless otherwise stated.
1. Preparation before the experiment
2. Daily procedures and maintenance
3. Lick detection during two-bottle choice experiments
NOTE: Researchers interested in capturing high resolution drinking data can modify the above procedure by adding lick detection capabilities to the bottles. LIQ HD30 is a low-cost do-it-yourself (DIY) system that allows for this type of data collection in mice. The procedures outlined below describe the modifications necessary to adapt LIQ HD for use in rats (referred to as LIQ HDR). See Table of Materials for a list of all commercially sold and custom 3D-printed parts necessary to construct one lick detection system, which can capture two-bottle choice data for up to 18 rats. The 3D print .stl files and instructions can be found at the author's website (www.ejgloverlab.com/3dprints).
4. Daily procedures for two-bottle choice home cage drinking using lick detection
5. Data analysis
Standard intermittent two-bottle choice home cage EtOH drinking data
Using the standard procedure (Figure 7A), researchers can capture 24 h intake (Figures 7B-D) as well as binge-like drinking if bottle weights are collected shortly after the onset of the drinking session (Figures 7E-F). By calculating ethanol intake relative to water intake, researchers can also obtain prefer...
The current protocol provides step-by-step instructions for capturing ethanol drinking data using an intermittent-access two-bottle choice home cage procedure. This method can be implemented with relative ease and with little-to-no cost or need for specialized research equipment. Using the procedures provided here for constructing and implementing LIQ HDR - a lick detection system for use in rats - researchers can capture high-resolution drinking microstructure data in addition to standard measures of intake and preferen...
All authors declare no conflicts of interest.
The authors thank Joseph Pitock and Katie Przybysz, PhD for technical assistance during LIQ HDR development. We also thank Nicholas Petersen and Marie Doyle, PhD for many helpful conversations during the development of LIQ HDR. This work was supported by the National Institute on Alcohol Abuse and Alcoholism at the National Institutes of Health (P50 AA022538 and R01 AA029130 to EJG).
Name | Company | Catalog Number | Comments |
Commercially Available Components | Quantity | ||
12-Key capacitive touch sensor breakout (MPR121) | Adafruit | 1982 | 3 |
2-Pin cable matching pair (JST XH 2.5mm pitch) | Adafruit | 4872 | 18 |
4-Pin breadboard jumper (Qwiic) | SparkFun | PRT-17912 | 1 |
4-Pin cable (100mm Qwiic) | SparkFun | PRT-17259 | 1 |
4-Pin cable (50mm Qwiic) | SparkFun | PRT-17260 | 3 |
5V-to-3V level shifter breakout | Adafruit | 5637 | 1 |
Capacitive touch shield (2.8inch) | Adafruit | 1947 | 1 |
Copper conductive tape (1/4inch) | DigiKey | 4393-CFT-1/4-ND | 1 |
Data logging shield | Adafruit | 1141 | 1 |
Differential I2C communication breakout kit (QwiicBus) | SparkFun | KIT-17250 | 1 |
Electrical tape | DigiKey | 3M156004-ND | 1 |
Heat shrink tubing (3/16inch various colors) | Cable Ties and More | HS357-S10 | 6 |
Heat shrink tubing kit (4inch black) | Jameco | 2095963 | 1 |
Lithium coin battery (3V 12.5mm) | DigiKey | 1908-CR1220JAUCHSB-ND | 1 |
M5 flat washer | Grainger | 54FN66 | 1 |
M5 hex nut | Grainger | 6CA72 | 1 |
M5 machine screw (12mm) | Grainger | 6GU88 | 1 |
M5 machine Screw (25mm) | Grainger | 6GU91 | 2 |
Male/male jumper wire | Adafruit | 1957 | 1 |
Microcontroller board (Arduino Mega 2560 Rev3) | DigiKey | 1050-1018-ND | 1 |
PETG filament (2.85mm silver) | MatterHackers | M-DDH-UZR2 | 2 |
PLA filament (2.85mm black) | MatterHackers | M-SEW-RUAW | 2 |
PLA filament (2.85mm silver) | MatterHackers | M-66P-6CLE | 1 |
Power supply (DC 9V 1A) | Newegg | 9SIBPPKJYR5991 | 1 |
SD/microSD memory card (8GB) | Adafruit | 1294 | 1 |
Shield stacking headers | Adafruit | 85 | 1 |
Solid-core wire (22AWG red) | Adafruit | 288 | 1 |
Stranded-core wire (22AWG black) | Adafruit | 2976 | 1 |
Stranded-core wire (22AWG red) | Adafruit | 3068 | 1 |
Twist cap sipper tube with ball | Alternative Design | TCCN8.5-ST2.5SB | 38 |
Water bottle (8oz) | Alternative Design | WB8FS | 38 |
Custom 3D-Printed Components | Quantity | ||
3D-printed Arduino case bottom | N/A | ARDUINO_Bottom.stl | 1 |
3D-printed Arduino case top | N/A | ARDUINO_Top.stl | 1 |
3D-printed cable clip L | N/A | CLIP_L.stl | 18 |
3D-printed cable clip nut | N/A | CLIP_Nut.stl | 18 |
3D-printed cable clip R | N/A | CLIP_R.stl | 18 |
3D-printed lickometer bottle holder | N/A | LICKOMETER_Bottle Holder.stl | 19 |
3D-printed lickometer cable protector L | N/A | LICKOMETER_Cable Protector_L.stl | 6 |
3D-printed lickometer cable protector R | N/A | LICKOMETER_Cable Protector_R.stl | 12 |
3D-printed lickometer letters | N/A | LICKOMETER_Letters.stl | 19 |
3D-printed mount screw | N/A | Mount Screw.stl | 4 |
3D-printed sensor case A bottom | N/A | SENSOR_A_Bottom.stl | 1 |
3D-printed sensor case A top | N/A | SENSOR_A_Top.stl | 1 |
3D-printed sensor case B bottom | N/A | SENSOR_B_Bottom.stl | 1 |
3D-printed sensor case B top | N/A | SENSOR_B_Top.stl | 1 |
3D-printed sensor case C bottom | N/A | SENSOR_C_Bottom.stl | 1 |
3D-printed sensor case C top | N/A | SENSOR_B_Top.stl | 1 |
3D-printed sensor case letters | N/A | SENSOR_Letters.stl | 1 |
3D-printed sipper blocker | N/A | SIPPER_Blocker.stl | 36 |
3D-printed sipper blocker base | N/A | SIPPER_Base.stl | 18 |
3D-printed sipper blocker gear | N/A | SIPPER_Gear.stl | 18 |
3D-printed sipper blocker nut | N/A | SIPPER_Nut.stl | 18 |
3D-printed sipper blocker worm | N/A | SIPPER_Worm.stl | 18 |
Laser-cut lickometer acrylic panel | N/A | LICKOMETER_Acrylic Panel_Sketch.dxf | 19 |
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