{"id":1139,"date":"2021-04-30T14:34:16","date_gmt":"2021-04-30T06:34:16","guid":{"rendered":"https:\/\/mygenome.asia\/?p=1139"},"modified":"2021-04-30T14:34:17","modified_gmt":"2021-04-30T06:34:17","slug":"visualizing-the-future-spatialomics-transforms-study-of-gene-expression","status":"publish","type":"post","link":"https:\/\/mygenome.asia\/zh\/blog\/visualizing-the-future-spatialomics-transforms-study-of-gene-expression\/","title":{"rendered":"Visualizing the Future Spatialomics Transforms Study of Gene Expression"},"content":{"rendered":"<p>Spatialomics is considered by many to be the next frontier in understanding gene expression. Earlier this year, Nature named spatially resolved transcriptomics\u2014also known as spatialomics\u2014the 2020 Method of the Year. This burgeoning new technology is the combination of tissue imaging and single-cell transcriptomic analysis, the full expression profile of messenger RNA (mRNA). The technique creates an entirely new type of scientific information.<\/p>\n\n\n\n<p>Spatialomics information can be used to more deeply understand disease, potentially enabling the development of novel treatments. \u201cA disease ultimately comes from molecular defects in the behavior of some cells. What we\u2019ve been doing up to date is trying to address that defect without knowing how the system itself works,\u201d says Jeffrey Moffitt, assistant professor at Boston Children\u2019s Hospital, and co-developer of the MERFISH technology that has helped to pioneer spatialomics.<\/p>\n\n\n\n<p>\u201cImagine if you were trying to fix an engine without ever knowing the blueprints of the engine\u2014you can be effective, but you\u2019re limited. What spatialomics does is provide a window to determine the blueprint of a disease system, what the parts are, and how they fit together. I can\u2019t imagine a more useful resource in understanding disease,\u201d says Moffitt.<\/p>\n\n\n\n<p><strong>The Third Generation of Transcriptomic Analysis Tools<\/strong><\/p>\n\n\n\n<figure class=\"wp-block-video\"><video height=\"1080\" style=\"aspect-ratio: 1080 \/ 1080;\" width=\"1080\" controls src=\"https:\/\/mygenome.asia\/wp-content\/uploads\/2021\/04\/MOUSE-BRAIN-ZOOM-FOR-GIF_SQUARE_FAST.mp4\"><\/video><figcaption><em>Gene expression in a cross-section&nbsp;of a mouse brain.Video: Vizgen<\/em><\/figcaption><\/figure>\n\n\n\n<p>Spatialomics tools are what could be considered the third generation of transcriptome analysis technologies.&nbsp;The transcriptome is the total messenger RNA (mRNA) in a sample, whether at a whole tissue or single-cell level. This reveals all of the genes being expressed at the moment of analysis.<\/p>\n\n\n\n<p>Understanding the transcriptome is important because while the human genome has 3 billion base pairs, the majority of genes these base pairs encode for are either not expressed or are only expressed under certain conditions. This information can inform scientists how the genes expressed by, say, a cancer cell differ from a normal cell. Understanding these differences can garner new insight into diseases and pave the way for novel treatment.<\/p>\n\n\n\n<p>Spatialomics builds on the advances to two early gene expression research technologies, bulk RNA sequencing and single-cell RNA sequencing. Both of these methods illustrate just how far spatialomics has come:<\/p>\n\n\n\n<h5 class=\"wp-block-heading\"><strong>Bulk RNA Sequencing<\/strong><\/h5>\n\n\n\n<p>Early efforts to understand gene expression focused on analyzing the total mRNA of a tissue sample, also known as \u201cbulk RNA sequencing.\u201d Using this technique a tissue sample is homogenized (i.e., blended up) and its total mRNA is analyzed to show the average gene expression levels across the entire sample. However, this does not provide details about what the transcriptome looks like on the single-cell level. In many diseases such as cancer, the genetic profile of individual cells in a tumor is different. Without data for each cell, researchers cannot understand the full genetic profile of a tumor or other disease types.<\/p>\n\n\n\n<h5 class=\"wp-block-heading\"><strong>Single-cell RNA sequencing<\/strong><\/h5>\n\n\n\n<p>The next-generation technology in this field, single-cell RNA sequencing (scRNA-seq), enabled researchers to understand the transcriptome of a single cell in a dissociated tissue\u2014a tissue broken apart into its cellular components. This was a pioneering approach, but it did not provide spatial information, which is important for three primary reasons.&nbsp;<\/p>\n\n\n\n<p>First, the way one cell transcribes its genes (copies DNA to RNA) affects the way it signals to its neighbor. As this process repeats, each cell\u2019s signal creates a chain of information in a tissue. Second, complex tissues, such as the brain, liver, kidney, and other major organs are not homologous. There are differences between the genes transcribed by the various groups of cells in these tissues. These differences create the distinctions in cellular function needed to maintain a working organ. Third, there are some diseases for which RNA is localized differently than it is in healthy cells.<\/p>\n\n\n\n<p>The ability to see where and when genes express could provide a crucial understanding of why and how diseases arise. It could also create a stronger foundation for tissue engineering, from skin grafts to synthetic hearts and kidneys.&nbsp;<\/p>\n\n\n\n<p><strong>New Technology Solves Old Problems&nbsp;<\/strong><\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img fetchpriority=\"high\" decoding=\"async\" width=\"1024\" height=\"409\" src=\"https:\/\/mygenome.asia\/wp-content\/uploads\/2021\/04\/Spatial-Transcriptomics-1536x614-1-1024x409.jpeg\" alt=\"\" class=\"wp-image-1142\" srcset=\"https:\/\/mygenome.asia\/wp-content\/uploads\/2021\/04\/Spatial-Transcriptomics-1536x614-1-1024x409.jpeg 1024w, https:\/\/mygenome.asia\/wp-content\/uploads\/2021\/04\/Spatial-Transcriptomics-1536x614-1-300x120.jpeg 300w, https:\/\/mygenome.asia\/wp-content\/uploads\/2021\/04\/Spatial-Transcriptomics-1536x614-1-768x307.jpeg 768w, https:\/\/mygenome.asia\/wp-content\/uploads\/2021\/04\/Spatial-Transcriptomics-1536x614-1-16x6.jpeg 16w, https:\/\/mygenome.asia\/wp-content\/uploads\/2021\/04\/Spatial-Transcriptomics-1536x614-1-1200x480.jpeg 1200w, https:\/\/mygenome.asia\/wp-content\/uploads\/2021\/04\/Spatial-Transcriptomics-1536x614-1.jpeg 1536w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><figcaption><em>10X Genomics platform, Visium, visually maps gene expression in a tissue sample. Image: 10X Genomics<\/em><\/figcaption><\/figure>\n\n\n\n<p>Spatial single-cell transcriptomics resolves the drawbacks of older bulk RNA and scRNA-seq technologies.&nbsp; By combining imaging and single-cell RNA sequencing, researchers can map where particular transcripts are expressed within a tissue. This can not only reveal the \u201cwhere\u201d of gene expression but also indicate the context of how individual cells function within that tissue.<\/p>\n\n\n\n<p>\u201cSpatial transcriptomics enables the resolution we need to make connections and refine our understanding of how cells interact within a tissue,\u201d says David Walt, a pioneer in microwell arrays and single molecules, scientific founder of Illumina Inc., and co-founder of Vizgen. \u201cEarlier methods give us a picture of tissue heterogeneity, but achieving cellular and sub-cellular resolution is needed not just for a better understanding of biology, but also for a better understanding of disease.\u201d<\/p>\n\n\n\n<p><strong>Leading Spatialomics Platforms<\/strong><\/p>\n\n\n\n<p>There are three primary thought leaders and methodologies in the field of spatialomics. The largest of these is 10X Genomics. 10X moved into this field with two significant acquisitions, Swedish company Spatial Transcriptomics in 2018 and ReadCoor at the end of 2020. From the foundation of these acquisitions, 10X built its platform, Visium.<\/p>\n\n\n\n<p>Using a spatialomics platform begins much the same as a typical tissue analysis. For Visium, users start with a tissue section and image and stain it for histological purposes. Then, the RNA is captured using bead-bound probes\u2014barcoded for their spatial location\u2014then sequenced. The technology can then construct the general spatial organization of gene expression. In the last step, users can analyze transcripts at the cellular level based on fluorescent in situ sequencing technology, FISSEQ.<\/p>\n\n\n\n<p>Nanostring, an emerging life science tools company, has a Spatial Molecular Imaging platform for analyzing both RNA and protein for individual cells within a tissue sample. The platform is based on the company\u2019s Hyb &amp; Seq chemistry technology.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"646\" height=\"635\" src=\"https:\/\/mygenome.asia\/wp-content\/uploads\/2021\/04\/Spacialomics-1-1.jpeg\" alt=\"\" class=\"wp-image-1143\" srcset=\"https:\/\/mygenome.asia\/wp-content\/uploads\/2021\/04\/Spacialomics-1-1.jpeg 646w, https:\/\/mygenome.asia\/wp-content\/uploads\/2021\/04\/Spacialomics-1-1-300x295.jpeg 300w, https:\/\/mygenome.asia\/wp-content\/uploads\/2021\/04\/Spacialomics-1-1-12x12.jpeg 12w\" sizes=\"(max-width: 646px) 100vw, 646px\" \/><figcaption>Gary Nolan, Stanford (top left) Terry Lo, CEO of Vizgen (top right), and Sean Kendall (bottom left), Keith Crandell (bottom right), both at ARCH Ventures<\/figcaption><\/figure>\n\n\n\n<p>Vizgen, also a life science tools company, is the newest to this field. The company uses a molecular barcoding technology that can optically quantify single RNA molecules at a single-cell level. This is based on the MERFISH technology co-invented by Moffitt: a multiplex RNA imaging technology that can detect tens of thousands of molecules.<\/p>\n\n\n\n<p>\u201cWith non-spatial single-cell technologies, you get to see the complexity of the system but not how it fits together,\u201d says Sean Kendall, Principal at ARCH Venture Partners and a Board Observer at Vizgen. \u201cThe Vizgen technology, for example, is subcellular, highly sensitive, and quantitative. If you want to study an individual cell or interrogate a whole pathway at the transcriptional level, you could do it. It\u2019s faster and you can do a ton of experimentation rapidly. This gives you a level of understanding of a biological system that you were unable to get before.\u201d<\/p>\n\n\n\n<p>Terry Lo, CEO of Vizgen, emphasized the innovation incorporated into Vizgen\u2019s technology. \u201cWhat\u2019s been lacking in previous platforms are two things. One, the resolution to get down to the single-cell information level for gene expression. Second, sensitivity and detection efficiency. This is the ability to look at medium to low expressing genes. Oftentimes, the most biologically interesting new insights will be uncovered by these transcripts,\u201d says Lo. \u201cIf only a small percentage of the transcripts being expressed are detected, then the full picture of what is happening with the biology of that particular cell is incomplete.\u201d<\/p>\n\n\n\n<p><strong>Synthetic Biology Stands to Make Significant Discovery Gains<\/strong><\/p>\n\n\n\n<p>Spatialomics looks to be especially important for synthetic biology. As a field, synthetic biology is founded on engineering new biological systems with desirable functions. While current spatialomics research centers on biopharma, the technology could also provide new answers to key bioengineering questions in agriculture, biofuels, and other bio-based materials.<\/p>\n\n\n\n<p>Garry Nolan, Professor in the Department of Pathology at Stanford University School of Medicine, and a pioneer in single-cell analysis, and founder of Akoya, says spatialomics enables an understanding of biology at a fundamental level. \u201cIn synthetic biology, if I want to cause a tissue to organize a certain way, I better understand what the rules of the system are,\u201d says Nolan. \u201cSo much of what we measure is hugely distant from the lowest level with the base rules of the system. Spatialomics gives us data that is closer to the fundamental thing we are interested in understanding. Until we understand these fundamental rules, we will never be good synthetic biologists.\u201d<\/p>\n\n\n\n<p>Kendall shares Nolan\u2019s perspective and adds the importance of spatialomics specifically to engineering new biological systems. \u201cIf you want to engineer a brain someday, you need to understand spatial context,\u201d says Kendall. \u201cjust like a synthetic biologist might build genetic circuits at the cellular level, these tools could help build cellular networks at the tissue level.\u201d<\/p>\n\n\n\n<p><strong>\u201cA New Type of Drug Target is Coming\u2014It\u2019s Inevitable\u201d<\/strong><\/p>\n\n\n\n<p>For Nolan, spatialomics paves the way for new types of disease targets. \u201cWe need to understand the rules of why certain cells, such as immune cells, come together in various disease states. We need to decipher what these observations and patterns mean,\u201d he says.<\/p>\n\n\n\n<p>The next generation of drug targets are not going to look like today\u2019s typical protein or enzyme drug target, says Nolan. \u201cThe targets are going to be stopping groups of cells from coming together, or enabling groups of cells to come together that wouldn\u2019t have come together before,\u201d Nolan says. \u201cThis new type of drug target is coming\u2014it\u2019s inevitable.\u201d<\/p>\n\n\n\n<p>Walt believes that the future of spatialomics is multi-omics. This technology combines imaging with transcriptomic, proteomic, and potentially other types of analyses. Instead of focusing only on gene expression, multi-omics could create highly multiplexed images linking gene expression to other factors like protein expression, chromatin state, epigenomics, and metabolomic data.<\/p>\n\n\n\n<p>Keith Crandell, Managing Director and Co-Founder at ARCH and Board Member at Vizgen, sees the next generation technology as one of integration. He specifically cites another technology, Ultivue, a company that operates in the high-plex protein space. He sees technologies like Ultivue and Vizgen\u2019s becoming integrated in the future.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"703\" height=\"389\" src=\"https:\/\/mygenome.asia\/wp-content\/uploads\/2021\/04\/Spatialomics-MERFISH.png\" alt=\"\" class=\"wp-image-1144\" srcset=\"https:\/\/mygenome.asia\/wp-content\/uploads\/2021\/04\/Spatialomics-MERFISH.png 703w, https:\/\/mygenome.asia\/wp-content\/uploads\/2021\/04\/Spatialomics-MERFISH-300x166.png 300w, https:\/\/mygenome.asia\/wp-content\/uploads\/2021\/04\/Spatialomics-MERFISH-16x9.png 16w\" sizes=\"(max-width: 703px) 100vw, 703px\" \/><figcaption>Visualization of gene expression using MERFISH technology. Image: MERFISH<\/figcaption><\/figure>\n\n\n\n<p>\u201cSo far, we haven\u2019t really seen that tight integration between the proteome and the transcriptome, but I think it\u2019s coming, and then we\u2019ll have a better idea of how much each ultimately defines a particular disease,\u201d says Crandell. Visualizing multiple proteins at once is important as proteins are often used as key biomarkers in classifying disease. An example of this is PD1\/PDL1, which is often used to identify cancers that have evolved to hide from the immune system.&nbsp;<\/p>\n\n\n\n<p>But, as with any emerging technology, there is always the factor of cost.&nbsp; For Crandell, the key driver in determining the adoption of spatialomics technology is the cost per data point at the cellular level. \u201cI think that the critical metric is the cost per cell. And I think that\u2019s going to be subject to Emily\u2019s Law,\u201d says Crandell. By \u201cEmily\u2019s Law,\u201d Crandell is referencing Emily Leproust, CEO of Twist Biosciences. Leproust drove down the cost of gene synthesis through Twist\u2019s technology, making gene synthesis more accessible to researchers everywhere. \u201cI think that\u2019s going to happen in spatialomics.\u201d<\/p>\n\n\n\n<p>Provided spatialomics can clear this cost hurdle, it holds particular promise in the area of neurological disease. Diseases such as Alzheimer\u2019s and Parkinson\u2019s have arguably the highest unmet need in medicine currently\u2014no treatments currently exist. Paradoxically, however, potential medicines have the highest failure rate in treating these diseases.<\/p>\n\n\n\n<p>Moffitt says that this is due, in part, to our relatively rudimentary understanding of the brain compared to other organs. \u201cWhat we know about the brain is that it\u2019s very spatially organized. What we haven\u2019t been able to do to date is understand which different cells are present and map their spatial organization,\u201d he says. \u201cWe need to understand how those cell types are potentially changing in different biological states, and spatialomics has the ability to give us that information. I think that is what is going to lead us to an understanding of neurological diseases where we can begin to truly treat them.\u201d<\/p>\n\n\n\n<p>Neuroscience, with all its complexities, could see significant advances through spatialomics.&nbsp; The technology\u2019s potential also extends to immunology, gut microbiology, oncology, and beyond.<\/p>\n\n\n\n<p>\u201cSpatialomics is the next evolution of genomics,\u201d Lo says. \u201cIt\u2019s an exciting time right now.\u201d<\/p>\n\n\n\n<p>This article was originally published on: <strong><em>https:\/\/synbiobeta.com<\/em><\/strong><\/p>","protected":false},"excerpt":{"rendered":"<p>Spatialomics is considered by many to be the next frontier in understanding gene expression. Earlier this year, Nature named spatially resolved transcriptomics\u2014also known as spatialomics\u2014the 2020 Method of the Year. This burgeoning new technology is the combination of tissue imaging and single-cell transcriptomic analysis, the full expression profile of messenger RNA (mRNA). The technique creates [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":1140,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[22],"tags":[],"class_list":["post-1139","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news_updates"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.2 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Visualizing the Future Spatialomics Transforms Study of Gene Expression - MyGenome<\/title>\n<meta name=\"description\" content=\"Spatialomics is considered by many to be the next frontier in understanding gene expression. - MyGenome - News_Updates\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/mygenome.asia\/zh\/blog\/visualizing-the-future-spatialomics-transforms-study-of-gene-expression\/\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Visualizing the Future Spatialomics Transforms Study of Gene Expression - 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