Imagine that you want to know the plot of a movie, but you only have access to either the visuals or the sound. With visuals alone, you\u2019ll miss all the dialogue. With sound alone, you will miss the action. Understanding our biology can be similar. Measuring one kind of data \u2014 such as which genes are being expressed \u2014 can be informative, but it only captures one facet of a multifaceted story. For many biological processes and disease mechanisms, the entire \u201cplot\u201d can\u2019t be fully understood without combining data types.<\/p>\n
However, capturing both the \u201cvisuals and sound\u201d of biological data, such as gene expression and cell structure data, from the same cells requires researchers to develop new approaches. They also have to make sure that the data they capture accurately reflects what happens in living organisms, including how cells interact with each other and their environments.<\/p>\n
Whitehead Institute for Biomedical Research and Harvard University researchers have taken on these challenges and developed Perturb-Multimodal (Perturb-Multi), a powerful new approach that simultaneously measures how genetic changes such as turning off individual genes affect both gene expression and cell structure in intact liver tissue. The method, described in Cell on June 12, aims to accelerate discovery of how genes control organ function and disease.<\/p>\n
The research team, led by Whitehead Institute Member Jonathan Weissman and then-graduate student in his lab Reuben Saunders, along with Xiaowei Zhuang, the David B. Arnold Professor of Science at Harvard University, and then-postdoc in her lab Will Allen, created a system that can test hundreds of different genetic modifications within a single mouse liver while capturing multiple types of data from the same cells.<\/p>\n
\u201cUnderstanding how our organs work requires looking at many different aspects of cell biology at once,\u201d Saunders says. \u201cWith Perturb-Multi, we can see how turning off specific genes changes not just what other genes are active, but also how proteins are distributed within cells, how cellular structures are organized, and where cells are located in the tissue. It\u2019s like having multiple specialized microscopes all focused on the same experiment.\u201d<\/p>\n
\u201cThis approach accelerates discovery by both allowing us to test the functions of many different genes at once, and then for each gene, allowing us to measure many different functional outputs or cell properties at once \u2014 and we do that in intact tissue from animals,\u201d says Zhuang, who is\u00a0also a Howard Hughes Medical Institute (HHMI) investigator.<\/p>\n
A more efficient approach to genetic studies<\/strong><\/p>\n Traditional genetic studies in mice often turn off one gene and then observe what changes in that gene\u2019s absence to learn about what the gene does. The researchers designed their approach to turn off hundreds of different genes across a single liver, while still only turning off one gene per cell \u2014 using what is known as a mosaic approach. This allowed them to study the roles of hundreds of individual genes at once in a single individual. The researchers then collected diverse types of data from cells across the same liver to get a full picture of the consequences of turning off the genes.<\/p>\n \u201cEach cell serves as its own experiment, and because all the cells are in the same animal, we eliminate the variability that comes from comparing different mice,\u201d Saunders says. \u201cEvery cell experiences the same physiological conditions, diet, and environment, making our comparisons much more precise.\u201d<\/p>\n \u201cThe challenge we faced was that tissues, to perform their functions, rely on thousands of genes, expressed in many different cells, working together. Each gene, in turn, can control many aspects of a cell\u2019s function. Testing these hundreds of genes in mice using current methods would be extremely slow and expensive \u2014 near impossible, in practice.\u201d Allen says.<\/p>\n Revealing new biology through combined measurements<\/strong><\/p>\n The team applied Perturb-Multi to study genetic controls of liver physiology and function. Their study led to discoveries in three important aspects of liver biology: fat accumulation in liver cells \u2014 a precursor to liver disease; stress responses; and hepatocyte zonation (how liver cells specialize, assuming different traits and functions, based on their location within the liver).<\/p>\n One striking finding emerged from studying genes that, when disrupted, cause fat accumulation in liver cells. The imaging data revealed that four different genes all led to similar fat droplet accumulation, but the sequencing data showed they did so through three completely different mechanisms.<\/p>\n \u201cWithout combining imaging and sequencing, we would have missed this complexity entirely,\u201d Saunders says. \u201cThe imaging told us which genes affect fat accumulation, while the sequencing revealed whether this was due to increased fat production, cellular stress, or other pathways. This kind of mechanistic insight could be crucial for developing targeted therapies for fatty liver disease.\u201d<\/p>\n The researchers also discovered new regulators of liver cell zonation. Unexpectedly, the newly discovered regulators include genes involved in modifying the extracellular matrix \u2014 the scaffolding between cells. \u201cWe found that cells can change their specialized functions without physically moving to a different zone,\u201d Saunders says. \u201cThis suggests that liver cell identity is more flexible than previously thought.\u201d<\/p>\n Technical innovation enables new science<\/strong><\/p>\n Developing Perturb-Multi required solving several technical challenges. The team created new methods for preserving the content of interest in cells \u2014 RNA and proteins \u2014 during tissue processing, for collecting many types of imaging data and single-cell gene expression data from tissue samples that have been fixed with a preservative, and for integrating multiple types of data from the same cells.<\/p>\n \u201cOvercoming the inherent complexity of biology in living animals required developing new tools that bridge multiple disciplines \u2014 including, in this case, genomics, imaging, and AI,\u201d Allen says.<\/p>\n The two components of Perturb-Multi \u2014 the imaging and sequencing assays \u2014 together, applied to the same tissue, provide insights that are unattainable through either assay alone.<\/p>\n \u201cEach component had to work perfectly while not interfering with the others,\u201d says Weissman, who is also a professor of biology at MIT and an HHMI investigator. \u201cThe technical development took considerable effort, but the payoff is a system that can reveal biology we simply couldn\u2019t see before.\u201d<\/p>\n Expanding to new organs and other contexts<\/strong><\/p>\n The researchers plan to expand Perturb-Multi to other organs, including the brain, and to study how genetic changes affect organ function under different conditions like disease states or dietary changes.<\/p>\n \u201cWe\u2019re also excited about using the data we generate to train machine learning models,\u201d adds Saunders. \u201cWith enough examples of how genetic changes affect cells, we could eventually predict the effects of mutations without having to test them experimentally \u2014 a \u2018virtual cell\u2019 that could accelerate both research and drug development.\u201d<\/p>\n \u201cPerturbation data are critical for training such AI models and the paucity of existing perturbation data represents a major\u00a0hindrance in such \u2018virtual cell\u2019 efforts,\u201d Zhuang says. \u201cWe hope Perturb-Multi will fill this gap by accelerating the collection of perturbation data.\u201d<\/p>\n The approach is designed to be scalable, with the potential for genome-wide studies that test thousands of genes simultaneously. As sequencing and imaging technologies continue to improve, the researchers anticipate that Perturb-Multi will become even more powerful and accessible to the broader research community.<\/p>\n \u201cOur goal is to keep scaling up. We plan to do genome-wide perturbations, study different physiological conditions, and look at different organs,\u201d says Weissman. \u201cThat we can now collect so many types of data from so many cells, at speed, is going to be critical for building AI models like virtual cells, and I think it\u2019s going to help us answer previously unsolvable questions about health and disease.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"Imagine that you want to know the plot of a movie, but you only have access to either…\n","protected":false},"author":2,"featured_media":4420,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[272],"tags":[18,4790,458,4792,4788,19,17,4795,4791,4793,4786,4789,4796,133,4794,4787],"class_list":{"0":"post-4419","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-genetics","8":"tag-eire","9":"tag-fatty-liver-disease","10":"tag-genetics","11":"tag-hepatocyte-zonation","12":"tag-howard-hughes-medical-institute-hhmi","13":"tag-ie","14":"tag-ireland","15":"tag-jonathan-weissman","16":"tag-liver-biology","17":"tag-liver-cell-zonation","18":"tag-mit-biology","19":"tag-perturb-multi","20":"tag-reuben-saunders","21":"tag-science","22":"tag-virtual-cell","23":"tag-whitehead-institute"},"share_on_mastodon":{"url":"","error":""},"_links":{"self":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/posts\/4419","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/comments?post=4419"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/posts\/4419\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/media\/4420"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/media?parent=4419"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/categories?post=4419"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/ie\/wp-json\/wp\/v2\/tags?post=4419"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}