Speaking to her colleagues at the meeting in Israel, Regev, who is cochairing netbet online sports bettingthe Human Cell Atlas Organizing Committee with Sarah Teichmann of the Wellcome Trust Sanger Institute, displayed the no-nonsense demeanor you might expect of someone at the helm of a massive scientific undertaking. The project had been under way for a year, and Regev, an MIT biology professor who is also chair of the faculty of the Broad and director of its Klarman Cell Observatory and Cell Circuits Program, was reviewing a newly published white paper detailing how the Human Cell Atlas is expected to change the way we diagnose, monitor, and treat disease.<\/p>\n
As Regev made her way through the white paper, the possibilities began to seem almost endless. At the most basic level, as a reference map detailing the genes expressed by each different type of healthy cell, the Human Cell Atlas will make it easier to identify how gene expression and signaling go awry in the case of disease. The same map could also help drug developers avoid toxic side effects: researchers targeting a gene that\u2019s harmful in one part of the body would know if the same gene is playing a vital role in another. And because the atlas is expected to reveal many new types of cells, it could also add much more sensitivity to a type of standard blood test, which simply counts different subsets of immune cells. Likewise, looking at individual intestinal cells might provide new insights into the specific cells responsible for inflammation and food allergies. And a better understanding of types of neurons could have far-reaching implications for brain science.<\/p>\n
The final product, Regev says, will amount to nothing less than a \u201cperiodic table of our cells,\u201d a tool that is designed not to answer one specific question but to make countless new discoveries possible. Eric Lander, the founding director and president of the Broad Institute and a member of netbet online sports bettingthe Human Cell Atlas Organizing Committee, likens it to genomics. \u201cPeople thought at the beginning they might use genomics for this application or that application,\u201d he says. \u201cNothing has failed to be transformed by genomics, and nothing will fail to be transformed by having a cell atlas.\u201d<\/p>\n
Cellular circuits<\/strong><\/p>\n Regev\u2019s interest in cells began at Tel Aviv University, where she was one of just 15 or so entering students in a highly selective program that gave them the freedom to take high-level courses in any subject. \u201cYou could go your first day as a freshman and decide to take a graduate class in political science,\u201d she says.<\/p>\n Regev took a genetics class her first semester and got hooked on the computational challenge of finding order in the complex, interconnected networks of proteins and genes within each cell. She pursued that topic for her doctoral work, characterizing living systems in a mathematical language that had been designed to describe computer processes. As she finished her doctorate in 2002, she was accepted into a program at Harvard\u2019s Bauer Center for Genomics Research that allowed her to start her own lab without first training as a postdoc.<\/p>\n Not long after, Lander, who\u2019d begun his own career as a mathematician after studying algebraic coding theory and combinatorial mathematics at Oxford, was searching for star talent for the newly created Broad Institute, whose mission is to use genomics to study human disease and help advance its treatment. He first met Regev at a lunch at the Bauer Center during which the fellows took turns speaking about their research for five to 10 minutes. \u201cBy the time we got all the way around the table I had written down \u2018Hire Aviv Regev,\u2019\u201d he recalls.<\/p>\n Convinced by Lander to join the Broad after \u201cmany cups of tea\u201d at Cafe Algiers in Harvard Square, Regev continued to apply computational approaches to study the mind-bogglingly complicated machinery of the cell. A single cell is made up of millions of molecules that are in constant conversation as they work together to do all the things cells need to do: divide, grow, repair internal damage, and, in the case of immune cells, signal other cells about threats. Inside the nucleus, the DNA is transcribed into RNA. That in turn gives rise to proteins, the molecules that do the work inside a cell. Meanwhile, proteins on the surface of the cell are constantly receiving molecular messages from outside\u2014glucose is available, an invader has arrived. These must be relayed back to proteins in the nucleus, which will respond by transcribing other DNA, giving rise to new proteins and still more signaling networks.<\/p>\n \u201cIt\u2019s like a complex computer that is made of these many, many different parts that are interacting with each other and telling each other what to do,\u201d says Regev. The protein signaling networks are like \u201ccircuits\u201d\u2014and you can think about the cell \u201calmost like a wiring diagram,\u201d she says. But using computational approaches to understand their activity first requires gathering an enormous amount of data, which Regev has long done through RNA sequencing. Unlike DNA sequencing, she says, it can tell her which genes are actually being expressed, so it offers a far more dynamic picture of a cell in action. But simply sequencing the RNA of the cells she\u2019s studying can tell her only so much. To understand how the circuits change under different circumstances, Regev subjects cells to different stimuli, such as hormones or pathogens, to see how the resulting protein signals change.<\/p>\n Next comes what she calls \u201cthe modeling step\u201d\u2014creating algorithms that try to decipher the most likely sequence of molecular events following a stimulus. And just as someone might study a computer by cutting out circuits and seeing how that changes the machine\u2019s operation, Regev tests her model by seeing if it can predict what will happen when she silences specific genes and then exposes the cells to the same stimulus.<\/p>\n In a 2009 study, Regev and her team examined how exposure to molecular components of pathogens like bacteria, viruses, or fungi affected the circuitry of the immune system\u2019s dendritic cells. She turned to a technique known as RNA interference (she now uses CRISPR), which allowed her to systematically shut genes down. Then she looked at which genes were expressed to determine how the cells\u2019 response changed in each case. Her team singled out 100 different genes that were involved in regulating the response to the pathogens\u2014some of which weren\u2019t previously known to be involved in immune function. The study, published in\u00a0Science<\/em>, generated headlines. But according to longtime colleague Dana Pe\u2019er, now chair of computational and systems biology at the Sloan Kettering Institute at the Memorial Sloan Kettering Cancer Center and a member of netbet online sports bettingthe Human Cell Atlas Organizing Committee, what really sets Regev apart is the elegance of her work. Regev, says Pe\u2019er, \u201chas a rare, innate ability of seeing complex biology and simplifying it and formalizing it into beautiful, abstract, describable principles.\u201d<\/p>\n From smoothies to fruit salad<\/strong><\/p>\n There are lots of empty coffee mugs in Regev\u2019s office at the Broad Institute, but very little in the way of decoration. She approaches her science with a businesslike efficiency. \u201cThere are many brilliant people,\u201d says Lander. \u201cShe\u2019s a brilliant person who can get things done.\u201d<\/p>\n In the fast-changing arena of genomics (\u201c2015 in my field is considered ancient history,\u201d she says), she is known for making the most of the latest innovations\u2014and for helping to spur the next ones. For years, she and others in the field struggled with a dirty secret of RNA sequencing: though its promise has always been precision\u2014the power of knowing the exact code\u2014the techniques produced results that were unspecific. Every cell has only a minuscule amount of RNA. For sequencing purposes, the RNA from millions of cells had to be pooled together. Bulk RNA sequencing left researchers with what she likens to a smoothie. Once it\u2019s blended together, there\u2019s no way to distinguish all the fruits\u2014or in this case, the RNA from individual cells\u2014that went into it. What researchers needed was something more like a fruit salad, a way to separate all the blueberries, raspberries, and blackberries.<\/p>\n In 2011, working with Broad Institute colleague Joshua Levin, PhD \u201992, and postdocs Alex Shalek, now at MIT\u2019s Institute for Medical Engineering and Science, and Rahul Satija, now at the New York Genome Center,\u00a0Regev managed to obtain enough RNA from a single cell to sequence it. To test the method, they sequenced 18 individual dendritic cells from the bone marrow of a mouse. The cells were all obtained in the same way and were expected to be the same type. But to the researchers\u2019 amazement, they were expressing different genes and could be classified into two distinct subtypes. It was like finding out the smoothie you\u2019d been drinking for years had ingredients you\u2019d never known about.<\/p>\n Regev and her colleagues weren\u2019t the only ones figuring out how to sequence a single cell with such sensitivity, nor were they the very first to succeed. Other labs were making similar advances at approximately the same time, each using its own technology and algorithms. And they all faced the same problem: isolating and extracting enough RNA from individual cells was time consuming and expensive. Regev and her colleagues had spent many thousands of dollars to sequence only 18 cells. If the body was full of rare, undiscovered cells, it was going to take an extraordinarily long time to find them.<\/p>\n Skip ahead seven years and the cost of single-cell RNA sequencing is down to only pennies per cell. A critical breakthrough was Drop-Seq, a new technology developed by researchers at Harvard and the Broad Institute, including Regev and members of her lab. The device embeds individual cells into distinct oil droplets with a tiny \u201cbar-coded\u201d bead. When the cell is broken apart for sequencing, some of its RNA attaches to the bead in its droplet. This allows researchers to analyze thousands at once without getting their genetic material mixed up.<\/p>\n Cell theory 2.0<\/strong><\/p>\n When cell theory was first proposed by German scientists some 180 years ago, it was hard to fathom that our tissues are built from \u201cindividual elementary units,\u201d as Theodor\u00a0Schwann, one of the two scientists credited with the theory, described cells. But it soon became a central tenet of biology, and over the decades and centuries, cells began to give up their secrets. Microscopes improved; new staining and sorting techniques became available. With each advance, new distinctions became possible. Muscle cells could be distinguished from neurons, and then categorized again as smooth or skeletal muscle cells. Cells, it became clear, were all fundamentally similar but came in different forms that had different properties.<\/p>\n By the 21st century, 200 to 300 major cell types had been identified. And while biologists have long recognized that NetBet sportthe true number of cell types must be higher, the extent of their diversity is only now coming into full focus, thanks in large part to single-cell RNA sequencing. Regev says that the immune system alone can now be divided into more than 200 cell types and that even our retinas have 100 or more distinct types of neurons. She and her colleagues have discovered several of them.<\/p>\n The idea that knowing so much more about our cells could lead to medical breakthroughs is no longer hypothetical. By sequencing the RNA of individual cancer cells in recent years\u2014\u201cEvery cell is an experiment now,\u201d she says\u2014she has found remarkable differences between the cells of a single tumor, even when they have the same mutations. (Last year that work led to Memorial Sloan Kettering\u2019s\u00a0Paul Marks Prize for Cancer Research<\/a>.) She found that while some cancers are thought to develop resistance to therapy, a subset of melanoma cells were resistant from the start. And she discovered that two types of brain cancer, oligodendroglioma and astrocytoma, harbor the same cancer stem cells, which could have important implications for how they\u2019re treated.<\/p>\n The excitement in the field has become tangible as more new cell types have been found. And yet Regev realized that if the aim was comprehensive knowledge, the approach needed to be coordinated. If each lab were to rely on its own techniques, it would be hard to standardize the computational tools and the resulting data. The new studies were producing \u201cvery nice glimmers of light,\u201d Regev says\u2014\u201ca thing here, a thing there.\u201d But she wanted to make sure those findings could be connected.Regev has also been busily mapping cells from the immune system, brain, gut, and elsewhere. She is not alone. Other labs have started their own mapping projects, each tackling a different part of the body. Last year researchers at the University of Washington attempted to classify every cell type in the microscopic worm C. elegans<\/em>. \u201cEvery single field in biology is saying, \u2018Of course we have to look at single-cell resolution,\u2019\u201d says Lander. \u201cHow did we ever imagine we were going to solve a problem without single-cell resolution?\u201d<\/p>\n Regev began to advocate creating something more unified: a map that would allow researchers to chart gene expression and cell types across the entire body. Sarah Teichmann had been thinking along the same lines. When she reached out to Regev in late 2015 about the possibility of joining forces, Regev immediately said yes.<\/p>\n A Google Maps for our cells<\/strong><\/p>\n The Human Cell Atlas is a collaboration among hundreds of biologists, technologists, and software engineers across the globe. Results from single-cell RNA sequencing will be combined with other data points to provide a comprehensive catalogue of all human cells.<\/p>\n But the many researchers involved won\u2019t simply be compiling spreadsheets listing different cell types. The atlas will also reveal where the cells are located in the body, how many there are, what forms they can take, even the developmental history of different cell types as they differentiated from stem cells. And all of this will be made accessible through a data coordination platform and a rich visual interface that Regev compares to Google Maps. It will allow users to zoom in to the molecular level of our cells, but zooming out to the level of tissues and organs will be important too. As a 2017 overview of the Human Cell Atlas by the project\u2019s organizing committee noted, an atlas \u201cis a\u00a0map\u00a0that aims to show the\u00a0relationships among its elements.\u201d Just as corresponding coastlines seen in an atlas of Earth offer visual evidence of continental drift, compiling all the data about our cells in one place could reveal relationships among cells, tissues, and organs, including some that are entirely unexpected. And just as the periodic table made it possible to predict the existence of elements yet to be observed, the Human Cell Atlas, Regev says, could help us predict the existence of cells that haven\u2019t been found.<\/p>\n