High-throughput hyperdimensional vertebrate phenotyping

Carlos Pardo-Martin, Amin Allalou, Jaime Medina, Peter M. Eimon, Carolina Wählby and Mehmet Fatih Yanik ()
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Carlos Pardo-Martin: Massachusetts Institute of Technology (MIT), 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, USA
Amin Allalou: Massachusetts Institute of Technology (MIT), 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, USA
Jaime Medina: Massachusetts Institute of Technology (MIT), 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, USA
Peter M. Eimon: Massachusetts Institute of Technology (MIT), 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, USA
Carolina Wählby: Centre for Image Analysis, Science for Life Laboratory, Uppsala University, Box337, Uppsala SE-75105, Sweden
Mehmet Fatih Yanik: Massachusetts Institute of Technology (MIT), 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, USA

Nature Communications, 2013, vol. 4, issue 1, 1-9

Abstract: Abstract Most gene mutations and biologically active molecules cause complex responses in animals that cannot be predicted by cell culture models. Yet animal studies remain too slow and their analyses are often limited to only a few readouts. Here we demonstrate high-throughput optical projection tomography with micrometre resolution and hyperdimensional screening of entire vertebrates in tens of seconds using a simple fluidic system. Hundreds of independent morphological features and complex phenotypes are automatically captured in three dimensions with unprecedented speed and detail in semitransparent zebrafish larvae. By clustering quantitative phenotypic signatures, we can detect and classify even subtle alterations in many biological processes simultaneously. We term our approach hyperdimensional in vivo phenotyping. To illustrate the power of hyperdimensional in vivo phenotyping, we have analysed the effects of several classes of teratogens on cartilage formation using 200 independent morphological measurements, and identified similarities and differences that correlate well with their known mechanisms of actions in mammals.

Date: 2013
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DOI: 10.1038/ncomms2475

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