SAMPL is a high-throughput solution to study unconstrained vertical behavior in small animals
Yunlu Zhu,
Franziska Auer,
Hannah Gelnaw,
Samantha N. Davis,
Kyla R. Hamling,
Christina E. May,
Hassan Ahamed,
Niels Ringstad,
Katherine I. Nagel,
David Schoppik
Affiliations
Yunlu Zhu
Department of Otolaryngology, New York University Grossman School of Medicine, New York, NY 10016, USA; The Neuroscience Institute, New York University Grossman School of Medicine, New York, NY 10016, USA; Department of Neuroscience & Physiology, New York University Grossman School of Medicine, New York, NY 10016, USA
Franziska Auer
Department of Otolaryngology, New York University Grossman School of Medicine, New York, NY 10016, USA; The Neuroscience Institute, New York University Grossman School of Medicine, New York, NY 10016, USA; Department of Neuroscience & Physiology, New York University Grossman School of Medicine, New York, NY 10016, USA
Hannah Gelnaw
Department of Otolaryngology, New York University Grossman School of Medicine, New York, NY 10016, USA; The Neuroscience Institute, New York University Grossman School of Medicine, New York, NY 10016, USA; Department of Neuroscience & Physiology, New York University Grossman School of Medicine, New York, NY 10016, USA
Samantha N. Davis
Department of Otolaryngology, New York University Grossman School of Medicine, New York, NY 10016, USA; The Neuroscience Institute, New York University Grossman School of Medicine, New York, NY 10016, USA; Department of Neuroscience & Physiology, New York University Grossman School of Medicine, New York, NY 10016, USA
Kyla R. Hamling
Department of Otolaryngology, New York University Grossman School of Medicine, New York, NY 10016, USA; The Neuroscience Institute, New York University Grossman School of Medicine, New York, NY 10016, USA; Department of Neuroscience & Physiology, New York University Grossman School of Medicine, New York, NY 10016, USA
Christina E. May
The Neuroscience Institute, New York University Grossman School of Medicine, New York, NY 10016, USA; Department of Neuroscience & Physiology, New York University Grossman School of Medicine, New York, NY 10016, USA
Hassan Ahamed
Department of Cell Biology, Skirball Institute of Biomolecular Medicine, New York University Grossman School of Medicine, New York, NY 10016, USA
Niels Ringstad
Department of Cell Biology, Skirball Institute of Biomolecular Medicine, New York University Grossman School of Medicine, New York, NY 10016, USA
Katherine I. Nagel
The Neuroscience Institute, New York University Grossman School of Medicine, New York, NY 10016, USA; Department of Neuroscience & Physiology, New York University Grossman School of Medicine, New York, NY 10016, USA
David Schoppik
Department of Otolaryngology, New York University Grossman School of Medicine, New York, NY 10016, USA; The Neuroscience Institute, New York University Grossman School of Medicine, New York, NY 10016, USA; Department of Neuroscience & Physiology, New York University Grossman School of Medicine, New York, NY 10016, USA; Corresponding author
Summary: Balance and movement are impaired in many neurological disorders. Recent advances in behavioral monitoring provide unprecedented access to posture and locomotor kinematics but without the throughput and scalability necessary to screen candidate genes/potential therapeutics. Here, we present a scalable apparatus to measure posture and locomotion (SAMPL). SAMPL includes extensible hardware and open-source software with real-time processing and can acquire data from D. melanogaster, C. elegans, and D. rerio as they move vertically. Using SAMPL, we define how zebrafish balance as they navigate vertically and discover small but systematic variations among kinematic parameters between genetic backgrounds. We demonstrate SAMPL’s ability to resolve differences in posture and navigation as a function of effect size and data gathered, providing key data for screens. SAMPL is therefore both a tool to model balance and locomotor disorders and an exemplar of how to scale apparatus to support screens.
