Laser capture microdissection–targeted mass spectrometry: a method for multiplexed protein quantification within individual layers of the cerebral cortex
The mammalian neocortex is organized into layers distinguished by the size, packing density, and connectivity of their constituent neurons. Many neuropsychiatric illnesses are complex trait disorders with etiologic factors converging on neuronal protein networks. Cortical pathology of neuropsychiatr...
Saved in:
Published in | Neuropsychopharmacology (New York, N.Y.) Vol. 44; no. 4; pp. 743 - 748 |
---|---|
Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
England
Nature Publishing Group
01.03.2019
Springer International Publishing |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | The mammalian neocortex is organized into layers distinguished by the size, packing density, and connectivity of their constituent neurons. Many neuropsychiatric illnesses are complex trait disorders with etiologic factors converging on neuronal protein networks. Cortical pathology of neuropsychiatric diseases, such as schizophrenia, is often restricted to, or more pronounced in, certain cortical layers, suggesting that genetic vulnerabilities manifest with laminar specificity. Thus, the ability to investigate cortical layer-specific protein levels in human postmortem brain is highly desirable. Here, we developed and validated a laser capture microdissection-mass spectrometry (LCM-MS) approach to quantify over 200 proteins in cortical layers 3 and 5 of two cohorts of human subjects as well as a monkey model of postmortem interval. LCM-MS was readily implementable and reliably identified protein patterns that differed between cortical layers 3 and 5. Our findings suggest that LCM-MS facilitates the precise quantification of proteins within individual cortical layers from human postmortem brain tissue, providing a powerful tool in the study of neuropsychiatric disease. |
---|---|
Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
ISSN: | 0893-133X 1740-634X 1740-634X |
DOI: | 10.1038/s41386-018-0260-0 |