Using MERSCOPE to Generate a Cell Atlas of the Mouse Brain that Includes Lowly Expressed Genes
George Emanuel* and Jiang He Vizgen, Cambridge, Massachusetts
*
george@vizgen.com
Abstract: The structure and organization of cells within organs is essential to their function, but nowhere in the body is this more spectacular than the brain. There, sprawling, snowflake-like neurons have grown into a precise arrangement, reaching out to neighboring cells to form neural circuits. Communication within neural circuits, made possible by spatial positioning, forms the basis of our physiology. Recently, a high-resolution cell atlas generated by MERFISH (multiplex error-robust fluorescence in situ hybridization) technology has mapped this spectacular organ with unmatched resolution, depth, and scale. The atlas catalogs cells as they exist in the intact biological system and will allow us to learn more about rare cell types and sparsely expressed cell signaling receptors fundamental to health and disease.
Keywords: spatial genomics, cell transcriptome
atlas, MERFISH, MERSCOPE,
Introduction Tere are hundreds of different cell types within the brain,
all expressing genes at unique, well-controlled levels in order to achieve their diverse biological functions [1–3]. Groups of cells and cell types that work together to execute larger goals make up a neural circuit. Tese neurons communicate with one another via neurotransmitters, which are expelled by one neuron and sensed when they bind to receptors on neighboring cells. Neurotransmitters binding to receptors trigger reactions such as a change in the cell’s physiology or the propagation of the signal to additional cells in the circuit. Neurotransmitter receptors come in many shapes and sizes based on functionality and are expressed by neurons at varying levels. For example, nonsensory G-protein coupled receptors (GPCRs), gatekeepers of our most fundamental physiological processes, are ironically expressed at very low levels, making them difficult to study experimentally despite their functional relevance [4]. With such intricate spatial organization defined by
difficult-to-study gene expression, there is still much to learn about the brain. Scientists still don’t fully understand the fundamentals of neuronal positioning, neuronal circuits, or how neuronal phenotypes contribute to brain function. Tis is, in part, thanks to the brain’s incredibly complex architecture and position in the body. Te delicate cells can be studied in high resolution under a microscope, and single cells can be cataloged through single-cell sequencing; however, the spatial organization of the organ is lost in these experiments. Imaging under a microscope preserves spatial context, but due to the limited plexing level of traditional imaging technoigies, it is oſten impossible to characterize hundreds or thousands of biomarkers at the same time. How does the wildly complicated structure of the brain develop? How does the brain change as we age at a cellular
16 doi:10.1017/S1551929521001346
level? What cell circuits are responsible for our senses, our emotions, our instincts? How do neurodegenerative diseases progress? Are specific cell types and regions responsible, and can the progression be reversed by drug treatment? Due to the brain’s mind-boggling complexity, we need
detailed reference maps, “cell atlases,” to form answers to these questions through high-resolution, spatially resolved genomic, transcriptomic, proteomic, and metabolomic data. Only then can we understand the roles individual cells play in a healthy brain—and how disease or injury disrupts the status quo.
What It Takes to Create a Cell Atlas Cell atlases result from a collective scientific effort that
involves collecting multiomic data spanning transcriptomics, proteomics, metabolomics, and metabolic flux [5,6,7]. High- throughput genomics projects, particularly those that characterize cells based on their gene expression profiles, have contributed large volumes of invaluable data to that global effort. However, a longstanding trade-off is that most methods can offer some combination of single-cell resolution, high detection efficiency, or spatial context—but not all three qualities at once. A recent dataset called the MERFISH Mouse Brain
Receptor Map was generated on Vizgen’s new MERFISH (multiplex error-robust fluorescence in situ hybridization) end-to-end platform solution, MERSCOPETM
[8]. Te data
suggest that spatial genomics researchers may not have to compromise on resolution or detection efficiency anymore. Several elements of the MERFISH method make its
unprecedented scope and sensitivity possible. In a MERFISH experiment, whole tissue sections are exposed to an RNA panel representing probes for hundreds to thousands of genes. Te method employs multiple fluorescent probes for each RNA species to ensure sensitivity, allowing it to reliably detect RNA species, even those that are expressed at low levels in a tissue. And to achieve extremely high multiplexing capacity, combinatorial, error-robust barcoding is used to detect hundreds to thousands of RNA species at a time. Te fluorescently labeled cells are imaged and the data analyzed to create spatial genomics data at unparalleled, nanometer- scale spatial resolution. Each experiment provides extremely rich spatial transcriptomic information and, depending on the RNA panel being used, can be completed in as little as one day on the MERSCOPE instrument.
Unlocking Knowledge with a Massive Dataset Te map encompasses three full coronal slices (and three biological replicates per slice). It contains the exact
www.microscopy-today.com • 2021 November
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