The brain is one of organs with higher cell diversity, containing thousands of different types of neurons and glia. Each of these cell types carries out different functions, for which cells have specialized during evolution. This is the reason for them to differ in morphology, gene expression, electrical properties, etc.
Organisms are generated from a single cell, the zygote. This cell proliferates to ultimately give rise to all the cells that make up an animal. Cell proliferation and cell specification, process by which cells acquire a specific cellular identity, must be perfectly coordinated. For normal development, cells derived from different progenitors at different times must acquire a precise cell identity.
Our lab seeks to understand the mechanisms of cell specification that are behind the generation of the nervous system. In addition, we also are keen to emulate these processes to generate cell types of therapeutic interest. We believe the limiting factor for most of our problems in developmental biology is the lack of proper tools. That’s why we devote an important part of our efforts to develop new but, most importantly, useful technology.
I. Mechanisms of cell diversity in the brain
Thousands of different neuronal and glial types are generated from a single cell (zygote) throughout the development of an organism. Thus, each cell has a genealogical relationship that connects it to the zygote. This family tree is known as cell lineage.
Cell lineage is intimately related to the acquisition of cell identity and, ultimately, cell function. In the cerebral cortex, neurons are more likely to form synapses with siblings compared to non-sibling neurons. In invertebrates such as C. elegans or Drosophila, neuronal identity can be predicted reliably from lineage data. Although development seems less predictable in vertebrates, the lack of lineage maps with single-cell resolution impedes us to understand how a cell’s lineage relates to its identity.
In the laboratory we try to understand how lineage and identity are related in the development of the mouse cerebral cortex. We seek to demonstrate the existence of distinct progenitor subtypes that would produce specific neuron types. To this end, we are working to gain genetic access to these specific progenitor subtypes through genetic intersections. These techniques allow us to mark and study the entire lineage of those cells generated from a particular neural, progenitor subtype.
Two scenarios have been proposed to explain how neuronal diversity in the cerebral cortex emerges during development: 1) different neuronal types arise from fate-restricted progenitors that exhibit subtle molecular differences, and 2) a homogeneous pool of neural progenitors produces different neuronal types.
II. Engineering cell types with therapeutic interest
Neurodegenerative diseases such as Parkinson or multiple sclerosis are associated with the death of specific cell types. In most cases, cell loss is irreplaceable and triggers a symptomatology that deteriorates the quality of life of patients. Replacing these cells could alleviate the most severe symptoms and improve the life of patients and their families.
Previous efforts have attempted to produce specific cell types to replace those lost in disease. These involved inducing the expression of a single gene or a simultaneous combination of genes in postmitotic or progenitor cells, resulting in cells that are far from resembling those found in the brain. The main problem with these attempts is that they obviated how cells are naturally specified during development. During cell specification, cells navigate a multivariable space of gene expression. Over time, this process involves the expression of a sequence of transcription factors that, coordinated with cell proliferation, results in a fairly precise number of cells with a specific identity. These gene expression sequences can be conceptualized as a password that protects certain cell differentiation programs. Cell specification relies on sequences of genes in which the order of factors seems critical.
The gene expression space that cells navigate to acquire their final identity is highly complex and consists of thousands of interdependent variables (genes). In practice, this makes it impossible to artificially reproduce the natural processes of cell specification. However, a number of master genes can regulate the expression of other genes and have a bigger impact in the final identity of cells. The multivariate space can then be modeled with a number of few principal components (master genes). The sequential expression of critical master genes could result in cell types that are very similar to those produced during normal development.
We currently work to crack the molecular passwords behind specific differentiation programs, aimed to generate cell types with therapeutic interest through the expression of specific genetic sequences.
RNA-seq has revealed the transcriptomic trajectories of cells during development. Cell specification relies on sequences of genes that drive cells in the multivariable space of gene expression throughout development. These sequences result in cell types with specific identities. In our lab, we try to find the correct sequences that produce cell types with therapeutic interest.
III. New tools for developmental biology
New technology has been by far the greatest driver of scientific progress. The generation of new tools has made it possible to solve long standing problems for which there was not an obvious solution. Inspired by this firm belief, we dedicate considerable effort to developing tools to solve our questions on cell development and specification.
We believe that new tools must meet at least one of the following two requirements 1) utility, generating small improvements that are useful to many people (i.e. a brighter GFP protein), or 2) novelty, producing a significant breakthrough in the field, even if than means most people will wait for further optimization to use them. Useful tools tend to have a significant impact in the short term. Novel tools may have a rather limited impact in the short term, but change the field in the long term or even inspire a new generation of useful tools.
Out of these options, we chose to aim at novelty when creating our tools😉.
CLADES is an example of the technology developed by us. This tools allows to label neurons generated at different times with different combinations of reporters.