Dr. Math P. Cuajungco

Additional Info

  • Role: Professor
  • Phone: 657-278-8522
  • Email: This email address is being protected from spambots. You need JavaScript enabled to view it.
  • Department: Department of Biological Science
  • Bio/Interests:


    Dr. Cuajungco is Professor of Biological Science at CSUF. He earned his Ph.D. in Neuroscience at the University of Auckland, New Zealand, where he worked productively on zinc metabolism and toxicity in the brain. As a pre-doctoral researcher at Harvard Medical School (HMS), he pursued a link between metal toxicity and Alzheimer’s disease. Upon obtaining his degree, he undertook post-doctoral work at HMS studying a rare sensory neuropathy known as familial dysautonomia. A second post-doctoral work at HMS involved characterizing proteins associated with hearing. His HMS mentor’s laboratory subsequently moved to Stanford’s School of Medicine where he then studied a family of membrane protein known as the Transient Receptor Potential (TRP) ion channels.

    At CSUF, he is currently investigating the pathological mechanism behind the functional loss of TRP Mucolipin (TRPML) ion channel, which results in Mucolipidosis type IV (MLIV) disease. His laboratory is interested in the roles that specific lysosomal membrane proteins and ion channels play during normal and pathological states. His work involves collaborations from various disciplines within CSUF and other renowned institutions. The laboratory uses mammalian cell culture model, as well as molecular and cellular biology approaches. One of his projects aims to characterize the function of transmembrane proteins, TMEM163, TMEM176A, and TMEM176B, using molecular, biochemical, and microscopy techniques. Another project includes investigating the possibility of using TRPML2 (MCOLN2) or TRPML3 (MCOLN3) gene complementation for the missing TRPML1 (MCOLN1) gene as a therapeutic approach for the MLIV disease. Finally, he works on identifying the role of abnormal zinc transport associated with many neurodegenerative diseases, and he also employs next generation sequencing (NGS) to define changes in gene expression levels associated with brain diseases using various model systems.