Spatial Neurobiology in Brain Organoids Using Mass Spectrometry Imaging-Based Multiomics Approach

Brain organoids are stem cell-derived, three-dimensional models that more accurately mimic the cellular complexity and architecture of human brain tissues compared to traditional two-dimensional (2D) cultures or animal models. Their physiological relevance and human-specific neurobiology enhance translational research while aligning with current regulatory shifts toward reducing animal testing in biomedical science. A thorough understanding of the molecular landscape of various biomolecules, such as lipids, metabolites, proteins, and glycans in physiologically relevant brain models, such as organoids, is essential to deciphering complex neurobiology. While mass spectrometry has long been used to understand such molecular landscape in tissues, a single-omics approach is insufficient to fully capture the complexity of brain biology. Therefore, multiomics strategies, such as high-resolution mass spectrometry imaging (MSI), mass spectrometry-based proteomics, and lipidomics, together can provide a holistic view of biomolecular interplay within tissue microenvironments. Moreover, since MSI retains spatial information within tissues, MSI-based multiomics approaches hold immense potential to uncover complex neurobiology within brain organoids. In this article, we present our perspectives on leveraging MSI-based multiomics in brain organoids to understand the complex molecular interplay underlying neurobiology.

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Publication Details

Journal
ACS Chemical Neuroscience
Published
2026-03-03
DOI
https://doi.org/10.1021/acschemneuro.5c00971
Primary Topic
Mass Spectrometry Techniques and Applications
Type
article
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article

Spatial Neurobiology in Brain Organoids Using Mass Spectrometry Imaging-Based Multiomics Approach

Nav Raj Phulara, Herana Kamal Seneviratne, Yuejia Huang, Kadia Lissit et al.
ACS Chemical Neuroscience
Mass Spectrometry Techniques and Applications
article

Spatial Neurobiology in Brain Organoids Using Mass Spectrometry Imaging-Based Multiomics Approach

Nav Raj Phulara, Herana Kamal Seneviratne, Yuejia Huang, Kadia Lissit, Jin-Chong Xu
article en

Abstract

Brain organoids are stem cell-derived, three-dimensional models that more accurately mimic the cellular complexity and architecture of human brain tissues compared to traditional two-dimensional (2D) cultures or animal models. Their physiological relevance and human-specific neurobiology enhance translational research while aligning with current regulatory shifts toward reducing animal testing in biomedical science. A thorough understanding of the molecular landscape of various biomolecules, such as lipids, metabolites, proteins, and glycans in physiologically relevant brain models, such as organoids, is essential to deciphering complex neurobiology. While mass spectrometry has long been used to understand such molecular landscape in tissues, a single-omics approach is insufficient to fully capture the complexity of brain biology. Therefore, multiomics strategies, such as high-resolution mass spectrometry imaging (MSI), mass spectrometry-based proteomics, and lipidomics, together can provide a holistic view of biomolecular interplay within tissue microenvironments. Moreover, since MSI retains spatial information within tissues, MSI-based multiomics approaches hold immense potential to uncover complex neurobiology within brain organoids. In this article, we present our perspectives on leveraging MSI-based multiomics in brain organoids to understand the complex molecular interplay underlying neurobiology.

ACS Chemical NeuroscienceVol. 17(6)
Johns Hopkins University (US), Johns Hopkins Medicine (US), Alzheimer’s Disease Neuroimaging Initiative (US), University of Maryland, Baltimore County (US)
Openalex Percentile: Top 38%
Mass Spectrometry Techniques and Applications
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Spatial Neurobiology in Brain Organoids Using Mass Spectrometry Imaging-Based Multiomics Approach — Nav Raj Phulara, Herana Kamal Seneviratne, et al. · ACS Chemical Neuroscience (2026) | TGRS Research Map | TGRS