Katie Matho, Ph.D.

Research Investigator, Cold Spring Harbor Laboratory

SFARI Bridge to Independence Fellow

Katie Matho is a research investigator at Cold Spring Harbor Laboratory. She received her B.S. from Union College, and her M.S. and Ph.D., both in neuroscience, from Sorbonne Université in Paris, France. For her Ph.D. work with Jean Livet at Institut de la Vision in France, Matho mapped the microscale connectivity of auditory circuitry in the brainstem, in the emerging field of connectomics. She employed a multicolor “barcoding” strategy called “Brainbow,” whereby neurons express random combinations of fluorescent proteins, facilitating single-cell, large-volume image analysis. This technique enabled her to identify previously unknown instances of converging inputs within this circuit where 1:1 connectivity is thought to be the rule.

To improve large-volume and live multicolor imaging of tissues labeled with multiple fluorescent probes, she collaborated with Emmanuel Beaurepaire at École Polytechnique in France. She contributed to pioneering a method of non-linear multicolor two-photon microscopy by wavelength mixing. Continuing briefly as a postdoctoral fellow, this breakthrough project facilitated single-cell morphological reconstruction in volumes large enough to encompass neural circuitry at a functionally relevant scale.

She then pursued her postdoctoral training under the mentorship of Z. Josh Huang at Cold Spring Harbor Laboratory. Matho investigated the degree of cell type diversity in the mammalian cerebral cortex. Focusing on the largest group of cortical neurons, the glutamatergic excitatory pyramidal neurons (PyNs), Matho developed, characterized and manipulated an array of high-quality, temporally inducible mouse gene knockin (KI) “driver” lines, providing experimental access to specific PyN cell types. This genetic engineering approach involved directing Cre or Flp “driver” enzymes to genes (some of which are implicated in ASD) specifically expressed in the major progenitor cell types and mature PyN subsets. The cell types could be tracked and manipulated by using “reporters” of “driver” activity, thus providing a handle on key cell types and paving the way for future discoveries related to brain function at cell-type specificity. Her work established an experimental paradigm laying the ground to uncover the hierarchical organization and developmental trajectory of PyN subpopulations that assemble cortical processing networks.

Matho currently employs high-throughput, single-neuron resolution next-generation sequencing approaches to reveal the brain wiring’s complexity and organizational principles, mentored by Anthony Zador at Cold Spring Harbor Laboratory.

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