Post-docs wanted to work on single-cell encapsulation and genomics (please click the link for details)

Single Cell genomics

We develop technologies to enable single cell genomics, where genetic information is gleaned cell by cell. This approach contrasts with conventional strategies that average measurements over cell populations. Averages miss information about critical cell sub-populations that can play an important role in tissue homeostasis or in the development of diseases such as cancer.


Analyzing heterogeneity of cancer tissues

It is increasingly appreciated that cells within a population, even derived from a common ancestor, exhibit a high degree of heterogeneity. Cell sub-populations generally arise from genetic mutations, epigenetic modifications or stochastic gene expression. This heterogeneity underlines the importance of single-cell approaches that permits the analysis of correlations that are otherwise obscured with techniques that collect the average cellular response. The analysis of population heterogeneity is particularly relevant to certain pathologies like cancer.

Cancer development is generally described as an evolutionary process where a cell population randomly acquires mutations and natural selection acts on the resultant phenotypic diversity. This view has been recently challenged by the description of stochastic gene expression that can induce transitions between distinct phenotypes without genetic mutations. Hence, non-genetic phenotypic variations may play a more prominent role in disease than previously anticipated. Finally, cell phenotypes could be stabilized by cellular interactions and the loss of these interactions could trigger stochastic gene expression and tumorigenesis.

These different models, which try to reconcile the different data accumulated from a few decades of molecular biology studies, stress the importance of combining high-throughput single-cell techniques with system biology approaches for studying cancer.

Goals and approaches

We focus our efforts on streamlining sample preparation for multi-parameter single-cell analysis using microfluidic and microfabrication techniques. While sequencing technologies have greatly evolved in the past decades, sample preparation for single-cell genomics has remained laborious. Our complementary approaches rely on the advancement of droplet microfluidics and arrays of microwells.

Our projects address specific applications and cover novel microfabrication techniques, microfluidic methods, module and application development.

Our goals are to develop platforms that

  • streamlines laborious and low throughput sample preparation
  • adapt to different types of applications such as sequencing, qRT-PCR
  • perform multi-parameter analysis
  • perform in-situ or in-tissue analysis