Unveiling the Secrets of the Macaque Cortex: A Breakthrough in Neuroscience with Single-cell Spatial Transcriptome

Unveiling the Secrets of the Macaque Cortex: A Breakthrough in Neuroscience with Single-cell Spatial Transcriptome

In a remarkable stride forward for neuroscience, a groundbreaking study titled “Single-cell spatial transcriptome reveals cell-type organization in the macaque cortex” was recently published in the journal Cell. This study has shed new light on the intricate organization of cell types within the macaque cortex, unraveling insights that could revolutionize our understanding of the human brain.

The cerebral cortex is responsible for higher cognitive functions, such as perception, memory, and decision-making. While previous research has made significant strides in comprehending the fundamental structure of the cortex in primates, the exact organization of various cell types has remained elusive due to the complexity and diversity of neural cells.

The researchers behind this study took advantage of a newly developed cutting-edge technology called Stereo-seq (spatial enhanced resolution omics-sequencing). Stereo-seq has three distinct advantages over most other spatial transcriptomic technologies:

• It has a detection resolution of under 500 nm.
• It is sequenced based, which allows it to detect any transcript with a poly A tail.
• It utilizes DNA nanoball technology which reduces sequencing costs, allowing a greater depth of transcriptome coverage.

Because of these advantages of Stereo-seq, they could explore the gene expression in the macaque cortex at an unprecedented level of resolution without sacrificing coverage.

To identify gene expression in each cell, they needed to identify the boundaries for each cell. They stained each stereo-seq section with a dye specific to nucleic acid and fluorescence-labeled concanavalin A (ConA), which marks the plasma membrane. Then they used an artificial intelligence (AI)-assisted automatic segmentation algorithm for single-cell identification based on nucleic acid and ConA images. This allowed them to analyze gene expression patterns of individual cells within their spatial context. For each cell, they identified an average of 819 transcripts and 458 genes. They performed their gene expression analysis across 143 cortical regions. Across these regions, they generated a comprehensive atlas of 264 transcriptome-defined cortical cell types while mapping their spatial distribution throughout the cortex. As a result of their study, they discovered a highly organized pattern of cell types, unveiling a mosaic-like arrangement of neural cells in the macaque cortex. This included characterizing the different cortical layers and regional preferences of glutamatergic, GABAergic, and non-neuronal cell types within these layers. They found that the distribution of specific cell types are spatially clustered, forming distinct territories that likely play crucial roles in the brain’s functioning.

Moreover, the study identified novel cell subtypes previously unknown to the scientific community. By analyzing the gene expression profiles of individual cells, the researchers could pinpoint these rare and elusive cell populations, providing a more comprehensive and accurate understanding of the brain’s cellular diversity.

One of the most fascinating aspects of this research is its potential implications for human neuroscience and neurological disorders. Macaque monkeys are often considered the closest animal models to humans when studying brain function and behavior. The insights gained from this study could thus be extrapolated to comprehend the organization of the human brain better, ultimately aiding in the study and treatment of various neurological conditions. Additionally, the single-cell spatial transcriptome technique employed in this study could serve as a powerful tool for future research, including the improvement of the Allen Brain Atlas. Stereo-seq also can uncover hidden cell types, and their spatial arrangements may pave the way for new avenues of investigation in neuroscience and potentially other fields.

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