A Recipe for the Brain
How confident would you be in making a Victorian Tennis Cake, given a set of ingredients and the recipe? What about with a vague list of instructions instead of a detailed recipe? If you’ve ever watched The Great British Baking Show, this concept is familiar to you as the “technical challenge”. Britain’s best amateur bakers often struggle to bake something with only a list of ingredients and bare bones recipe, as do internet hopefuls, shown below.
In many ways, neuroscientists have spent the past one hundred years struggling with a similar challenge: understanding the ingredients and instructions that give rise to the brain. From bakers to car mechanics, experts in a given field must understand all the components involved in a domain, their functions, and their relationship to one another. Neuroscience is similar in that regard; however, the brain’s ~100 billion neurons, each connected to thousands of others, make this problem much more formidable.
The diversity of cells within the brain has long been appreciated in neuroscience, starting in 1906 with Camillo Golgi and Santiago Ramón y Cajal winning the Nobel Prize for their work on the structure of the nervous system. Ramon y Cajal used a method developed by Golgi to sparsely and randomly stain a few cells in the brain. Leaving the rest of the cells transparent, this technique produced beautiful high contrast images revealing the shape of individual neurons and highlighting their structural diversity. While transformative, these studies were limited to comparing neurons with obvious physical differences. In recent decades, neuroscientists have developed techniques to compare populations of neurons genetically. Even more recently, these technologies have advanced to the point where it is now economically feasible to genetically profile the brain – cell by cell.
A list of ingredients
The first step in developing this neuronal recipe was to assemble the list of ingredients. Each cell in the brain may have a different combination of genes turned on or off, but to start scientists first had to determine how many genes there are in total within the genome. The first complete sequences of the human genome were published in 2001, in a race between the Human Genome Project and Craig Venter’s private group Celera. These projects provided a list of ~20,000 total genes in the human genome, far fewer than originally speculated.
The genome is made of deoxyribonucleic acids, DNA. Each gene is a string of nucleic acids, which provide instructions for building a protein for the cell. Proteins perform many different functions. An example is the dopamine receptor – this protein detects the neurotransmitter dopamine outside the cell and allows the cell to respond accordingly. Interestingly, proteins are not made up of nucleic acids, but instead are made up of a chain of a different kind of molecule called amino acids. How does this conversion take place? A gene of interest is essentially copied into a slightly different type of nucleic acid called ribonucleic acid, RNA, through a process called transcription. The sequence of RNA is then translated into a corresponding chain of amino acids. The amino acids then fold up into a functional protein. This process is called the central dogma of molecular biology.
Every cell in the brain and body has the same genes, the same DNA. What varies is what each cell does with those genes – which genes are turned on or kept off. A neuron in the retina might need to express (turn on) genes for opsins, proteins which are sensitive to light. A neuron in a reward area in the brain might need a gene expressed to make a dopamine receptor. And both of those neurons may express a set of genes which imbue them with electrical properties that a skin cell might not need. The contents of DNA between cells is the same, but the RNA and proteins within each cell are diverse and dynamic.
Developing the Recipe
To comprehensively assess neuronal diversity in the brain, neuroscientists have set their sights on sequencing the RNA in the brain. By sequencing RNA, scientists are able to see how neurons express different combinations of genes to specialize their structure and function. Recently, sequencing technology has improved to the point where it is feasible to sequence the RNA of individual cells, rather than brain regions. Instead of averaging the RNA of thousands of cells, scientists can examine each cell’s gene expression separately, one by one. This task, which would have seemed impossible even in 2001, is manageable thanks to the plummeting costs of nucleic acid sequencing. Already, groups have begun sequencing individual cells in particular regions of the nervous system, such as a Harvard lab sequencing the retina  or the Allen Institute for Brain Science sequencing parts of the visual cortex . Both projects have uncovered novel types of cells, demonstrating that the technique is capable of uncovering uncharted diversity in the brain. Commercial kits are now available which allow scientists to sequence a few thousand individual cells of interest in their lab. Most ambitiously, the Chan Zuckerberg initiative has begun funding pilot studies to generate an entire human cell atlas. These daunting projects, requiring the combination of molecular biology, robotics, and computer science, are now underway.
Have your cake
What might we hope to achieve from all this data ? Having the list of the genetic profiles of every cell in the brain would be a monumental achievement, but ultimately, its value will be determined by what we can learn from the dataset. Like the first sequencing of the human genome, it will provide a new starting point for scientists. To understand the brain, scientists will still have to understand how all those types of neurons are connected. Furthermore, scientists will still have to monitor the activity from different types of neurons to learn when classes of neurons fire during cognition and behavior. To address issues of health, the genetic profiles of healthy neurons will need to be compared to neurons in states of disease, injury, or genetic mutation. It is likely that many pathologies of the brain preferentially affect particular types of neurons more than others, so understanding these genetic changes on a cell by cell level will hopefully lead to more effective and targeted therapies.
With advances in sequencing technologies, scientists are now able to explore the genetic recipes for individual neurons. As more and more neurons are profiled, scientists are beginning to assemble a recipe for the brain.
 Macosko, EvanÂ Z., et al. “Highly Parallel Genome-Wide Expression Profiling of Individual Cells Using Nanoliter Droplets.” Cell, vol. 161, no. 5, 2015, pp. 1202–1214., doi:10.1016/j.cell.2015.05.002.
 Tasic, Bosiljka, et al. “Adult Mouse Cortical Cell Taxonomy Revealed by Single Cell Transcriptomics.” Nature Neuroscience, vol. 19, no. 2, Apr. 2016, pp. 335–346., doi:10.1038/nn.4216.
 Regev, Teichmann, et al. “Science Forum: The Human Cell Atlas” eLife 2017;6:e27041 doi: 10.7554/eLife.27041
Central Dogma Diagram: https://en.wikipedia.org/wiki/Central_dogma_of_molecular_biology