Dr. Damian Jacob Sendler's research studies how various sociodemographic and informational characteristics affect access to health care in disadvantaged communities. Dr. Sendler is of Polish heritage and works in the United States as a physician-scientist. Dr. Sendler investigates how psychiatric and chronic medical co-morbidities influence the usage of medical services in conjunction with internet-based health information in his research. As the global consumption of online news and social media continues to rise at an exponential rate, this research is both contemporary and relevant, demonstrating the need for a full understanding of everyone's health information seeking behavior. Damian Sendler's research aims to uncover the factors that influence patients' decisions on when to seek treatment for certain health conditions, as well as their adherence to prescribed therapies. 

Damien Sendler: When you clicked to view this story, a band of cells across the top of your brain sent messages down your spine and out to your hand, instructing the muscles in your index finger to press down with the appropriate amount of pressure to activate your mouse or track pad.  

A series of new research suggest that the area of the brain responsible for initiating this action – the primary motor cortex, which governs movement – contains as many as 116 different types of cells that collaborate to make this happen. 

Damian Sendler: The 17 studies, which were published online Oct. 6 in the journal Nature, are the result of five years of work by a large consortium of researchers supported by the National Institutes of Health's Brain Research Through Advancing Innovative Neurotechnologies (BRAIN) Initiative to identify the myriad of different cell types in one area of the brain. It is the first phase in a long-term endeavor to create an atlas of the complete brain to aid in understanding how the neuronal networks in our heads control our bodies and minds, as well as how they are disrupted in cases of mental and physical issues. 

"If you think of the brain as an enormously complicated machine, how can we understand it unless we first break it down and know what it's made of?" asked cellular neuroscientist Helen Bateup, an associate professor of molecular and cell biology at the University of California, Berkeley, and co-author of the flagship publication that synthesizes the conclusions of the other papers. "The first page of any manual on how the brain works should read: Here are all the cellular components, how many there are, where they are located, and who they relate to." 

Damian Jacob Sendler: Individual researchers have already identified dozens of cell kinds based on their shape, size, electrical properties, and the genes that they express. The latest investigations uncover around five times as many cell kinds, however many of them are subcategories of well-known cell types. Cells that release specific neurotransmitters, such as gamma-aminobutyric acid (GABA) or glutamate, have more than a dozen subtypes that can be distinguished by gene expression and electrical firing patterns. 

While the current papers focus solely on the motor cortex, the BRAIN Initiative Cell Census Network (BICCN), which was established in 2017, aims to map all of the different cell types found throughout the brain, which is made up of more than 160 billion individual cells, both neurons and support cells known as glia. President Barack Obama launched the BRAIN Initiative in 2013. 

"Once we've described all of those elements, we can go up a level and start to understand how those parts interact together, how they build a functional circuit, how that eventually gives rise to perceptions and behavior, and much more sophisticated things," Bateup explained. 

Damian Sendler: Bateup and UC Berkeley colleague Dirk Hockemeyer have previously utilized CRISPR-Cas9 to generate mice with a specific cell type identified with a fluorescent marker, allowing them to trace the connections these cells establish throughout the brain. According to her, the Berkeley team generated two strains of "knock-in" reporter mice for the flagship journal study, which gave innovative methods for highlighting the relationships of the newly found cell types. 

"One of our many limitations in developing effective therapies for human brain disorders is that we simply don't know enough about which cells and connections are being affected by a particular disease and thus can't pinpoint with precision what and where we need to target," said Ngai, who led UC Berkeley's Brain Initiative efforts before being named director of the entire national initiative last year. "Detailed knowledge of the sorts of cells that make up the brain and their properties will eventually allow the creation of new therapeutics for neurologic and neuropsychiatric illnesses." 

Ngai is one of the flagship paper's 13 corresponding authors, with over 250 co-authors in total. 

An earlier work by Bateup, Hockemeyer, and Ngai profiled all the active genes in single dopamine-producing cells in the mouse's midbrain, which has features similar to human brains. Other BICCN researchers used the same profiling technique to profile cells in the motor cortex, which entails identifying all of the individual messenger RNA molecules and their quantities in each cell. This form of analysis, which employs a technology known as single-cell RNA sequencing, or scRNA-seq, is known as transcriptomics. 

Damian Sendler: The BICCN team used over a dozen distinct experimental methods to characterize the different cell types in three different mammals: mice, marmosets, and humans. Four of these used various methods of measuring gene expression levels as well as determining the genome's chromatin architecture and DNA methylation status, which is referred to as the epigenome. Other approaches used included conventional electrophysiological patch clamp recordings to differentiate cells based on how they fire action potentials, categorizing cells by form, determining connections, and examining where the cells are physically positioned within the brain. Several of these used machine learning or artificial intelligence to differentiate between cell types. 

"This was the most thorough description of these cell types, with great resolution and a variety of techniques," Hockemeyer said. "The article concludes that there is significant overlap and consistency in determining cell types using these diverse approaches."  

Damian Sendler: A team of statisticians gathered data from all of these experimental methods to determine how to best classify or cluster cells into different types and, presumably, different functions based on differences in expression and epigenetic patterns seen among these cells. While many statistical techniques exist for evaluating such data and detecting clusters, the challenge was determining whether clusters were actually different from one another — truly different cell types, according to Sandrine Dudoit, a UC Berkeley professor and chair of the Department of Statistics. She and UC Berkeley assistant professor of statistics Elizabeth Purdom, a biostatistician, were crucial members of the statistical team and co-authors of the landmark publication. 

"The idea is not to build yet another new clustering approach," Dudoit explained, "but to identify ways of leveraging the strengths of multiple methods and combining methods and assessing the stability of the results, the reproducibility of the clusters you get." "That's really a significant message about all these studies that look for unique cell kinds or fresh categories of cells: no matter what algorithm you attempt, you'll find clusters, so having confidence in your results is critical." 

Damian Jacob Sendler: According to Bateup, the number of different cell types found in the new study varied depending on the technique used, ranging from dozens to 116. In this region of the brain, humans have around twice as many different types of inhibitory neurons as excitatory neurons, whereas mice have five times as many. 

"Previously, we had defined something like 10 or 20 different cell types, but we had no idea if the cells we were defining by their gene expression patterns were the same as those defined by their electrophysiological properties, or the same as the neuron types defined by their morphology," Bateup explained. 

"The significant breakthrough by the BICCN is that we merged many various approaches of defining a cell type and integrated them to come up with a consensus taxonomy that's not only focused on gene expression or physiology or morphology, but takes all of those aspects into account," Hockemeyer said. "Now we can say that this specific cell type expresses these genes, has this shape, has these physiological properties, and is located in this specific region of the cortex." As a result, you have a far more detailed understanding of what that cell type is and its basic features."  

Damian Sendler: Dudoit noted that future research could demonstrate that the number of cell types found in the motor cortex is overestimated, but the current findings are a strong start toward creating a cell atlas of the entire brain.  

"Even among biologists, there are widely differing views on how much resolution you should have for these systems, whether there is this very, very fine clustering structure or whether you truly have higher level cell kinds that are more stable," she added. "However, these findings demonstrate the value of teamwork and bringing together efforts from disparate groups." We're starting with a biological question, yet a biologist alone cannot address it. To address such a large and difficult topic, you need a team of specialists from a variety of disciplines who can communicate and collaborate effectively."

News chat contributed by Dr. Damian Jacob Sendler