Trends, Applications and Advances in Spatial Transcriptomics
Trends, Applications and Advances in Spatial Transcriptomics
While understanding the cellular diversity within tissue types is critical to understanding biological systems, established methods often lack the simultaneous subcellular resolution and multiplexing capacity to provide a comprehensive view of the cellular diversity that exists within a tissue of interest.
To address these issues, Vizgen, a life science company dedicated to advancing human health by visualizing single-cell spatial genomics information, is commercializing MERFISH (Multiplexed Error-Robust Fluorescence in situ Hybridization) technology. Highlighted in Nature Methods “Method of the Year 2020” feature, MERFISH spatially profiles hundreds to thousands of genes simultaneously within a single tissue slice with subcellular information.
Technology Networks recently had the pleasure of speaking to Dr George Emanuel, scientific cofounder, director of technology and partnerships at Vizgen, to learn more about MERFISH, what it can reveal and how it is being used to gain insight into the biological complexity within and around us. In this interview, Dr Emanuel also discusses the power of spatial transcriptomic profiling and some of the biggest trends in the field.
Anna MacDonald (AM): Can you discuss some of the biggest trends in the spatial genomics field?
George Emanuel (GE): Although spatial genomics is a nascent field, we are already seeing broad interest among the community and excitement across a range of questions, all the way from plant biology to improving our understanding of the complex interactions of the tumor microenvironment. On one side, researchers are performing large scale single-cell sequencing experiments to catalog the different transcription profiles across different tissues in health and disease. However, once they understand which cell types are present in the sample, they would like to better understand the variation they are seeing from single-cell sequencing. These complementary research goals lead naturally to the use of spatial genomics to truly atlas the cellular composition of these tissues and establish how the different cell states and organization are perturbed by disease, aging, or drug treatment. This leads into the second trend we are seeing: profiling the response of tissues or cells to perturbations, from understanding the importance of different signaling pathways for disease progression to understanding the mechanism of action or toxicity of therapeutic interventions.
Together, these types of research deepen our understanding of the tissue’s natural state and can uncover how cell signaling, regulatory pathways, and developmental processes work to create and maintain complex tissues.
AM: Why is spatial profiling such a powerful technique?
GE: Spatial transcriptomic profiling provides the genomic information of single cells as they are intricately spatially organized within their native tissue environment. With techniques such as single-cell sequencing, researchers can learn about cell type composition; however, these techniques isolate individual cells in droplets and do not preserve the tissue structure that is a fundamental component of every biological organism. Tissues are built from the complex interactions between cells; cells are constantly communicating with each other through ligand-receptor interactions, secreting proteins and small molecules, or even mechanical forces. So, while you can understand which cell types might be in a tissue by single-cell sequencing, direct spatial profiling the cellular composition of the tissue allows you to better understand why certain cell types are observed there and how variations in cell state might be a consequence of the unique microenvironment within the tissue. In this way, spatial transcriptomics allows us to measure the complexity of biological systems along the axes that are most relevant to their function: The highly multiplexed transcriptomic readout reveals the complexity that arises from the very large number of genes in the genome, while high spatial resolution captures the exact locations where each transcript is being expressed.
AM: How was MERFISH technology developed?
GE: MERFISH technology is a result of the evolution of various FISH technologies over the past 50 years. FISH experiments visualize target RNA species by hybridizing them to fluorescent probes, but the core method does not have very high resolution by today’s standards. A high-resolution method called single molecule (sm)FISH, was published in Science in 1998 by Singer et al. smFISH has extremely high sensitivity because it uses multiple probes to image and count transcripts using a fluorescent microscope to detect a target RNA. As the name suggests, this powerful method enables researchers to directly quantify the abundance and spatial location of the target nucleic acid in individual cells, but it can only be used to look at a handful of genes at a time. MERFISH is essentially a massively multiplexed version of smFISH. It was developed by Zhuang et al. and first reported in Science in 2015. A key aspect of MERFISH is that it uses combinatorial error-robust barcoding, so that each experiment can measure thousands of RNA species across thousands of cells at once with high accuracy, while still employing multiple probes per gene to preserve the sensitivity and quantitative nature of smFISH. MERFISH experiments are captured via single molecule imaging and the images are processed to reveal variations in the transcriptomes of cells in the sample, with spatial context.
AM: How is MERFISH being used to gain insight into the biological complexity within and around us?
GE: High resolution spatial profiling of RNA expression in single cells in their native context with MERFISH has revealed cell type, state, organization, interactions, and function within cell culture and tissue. This has been demonstrated in a number of publications, both peer-reviewed and in preprint. In a 2018 paper published in Science, Moffit et al. demonstrated the capacity of MERFISH to spatially atlas the cellular and molecular composition of the MPOA region of the mouse brain. The cell types identified by MERFISH were consistent with those identified by scRNA-seq, but in some cases MERFISH was able to more finely differentiate neuronal subtypes with its higher detection efficiency. In the paper, they also performed MERFISH in combination with profiling immediate early genes to understand which neurons within this brain region were activated during different behaviors.
More recently, in a 2020 preprint paper, Zhuang et al. have extended this work to atlas the primary motor cortex in combination with retrograde tracing and to profile the expression of the transcriptome along the length of axons and dendrites in cultured neurons. These are only the demonstrations we are able to publicly disclose, from Vizgen, and we are also supporting a broad variety of projects through our Accelerator Lab Services and our early access program.
Credit: Vizgen's MERFISH Mouse Brain Receptor Map
AM: What sets MERFISH apart from other spatial technologies? What can MERFISH reveal?
GE: Currently commercially available spatial technologies are deficient in two critical areas that we touched on previously, and our MERFISH platform addresses these. First is resolution. The current lack of single cell and subcellular resolution is a significant limitation to applying spatial information in the most useful way. Second, MERFISH can detect nearly all of the transcripts from the selected gene panel while other spatial technologies have very low detection efficiency. Transcription is already a sparse signal. A typical gene may be expressed at 10 to 100 copies per cell. When fewer than 50-fold of those transcripts are actually detected, significant information is lost, and many genes are not even detected even though they may have significant relevance. The low detection efficiency from other spatial technologies introduces substantial bias. But by using the hybridization approach based on single molecule FISH, MERFISH can detect low expressing genes significantly better than other methods. MERFISH provides the full resolution measurement with high detection efficiency across an entire tissue slice, rather than just profiling select regions of the tissue.
AM: How will Vizgen help make MERFISH technology more accessible to the scientific community?
GE: Vizgen is commercializing the MERSCOPE platform which is an end-to-end solution for running MERFISH measurements. The MERSCOPE instrument integrates high-resolution imaging, fluidics, and image processing into automated hardware to deliver precise measurements. Additionally, the MERSCOPE software enables automated image processing to extract the relevant information from the raw images and interactive visualization for understanding the depth of a MERFISH experiment. This solution allows you to get high quality spatial genomics data from your sample without the need or cost of sequencing, which we see as the next generation of genomics.
George Emanuel was speaking to Anna MacDonald, Science Writer for Technology Networks.