Last month, you learned about how math helps to understand T cell immunity. This time, it is about how software engineering and innate immunity come together. Jonathan Schmid-Burgk studied Molecular Biomedicine in Bonn and is now about to finish his PhD at the Institute of Molecular Medicine. Here, Jonathan tells us how developing several software tools allowed him to study open questions in innate immunity.
Jonathan, recently you set up a CRISPR/Cas9 screen to identify novel proteins involved in the activation of NLRP3, a mediator protein of sterile inflammation. For this project you made use of several software tools you developed. First, can you give us some insights what the bottlenecks were to set up such a genome wide screen and what the beauty of CRISPR/Cas9 screens is?
One challenge was the screening itself, including the design of a genome-wide CRISPR gRNA library, its physical production and the viral transduction of the library, but the main challenge was rather the optimization of the biological readout. In fact, I needed a stimulation condition in which >95% of all macrophage cells would die only via the pathway we were interested in, namely the NLRP3 inflammasome pathway. It took more than a year to find this optimal condition, which in the end sounds simple: stimulating the macrophages in suspension for five hours and subsequently sorting them by FACS. After having established this protocol the genome-wide screen actually worked out right away.
The nice thing about forward-genetic CRISPR screens is that you start without a hypothesis and test all annotated genes of an organism at once for their involvement in a biological phenomenon to identify novel relevant genes.
Back to software programming. Which programming languages do you speak?
One of the software tools you developed and made use of in your CRISPR screen is the OutKnocker . This software allows to identify knockout clones from high throughput sequencing data. Can you tell us a bit more on what your OutKnocker software can be used for?
OutKnocker.org is an open web app that can be used for genotyping nuclease-edited cell clones by analyzing deep sequencing data.
If you want to generate knockout cells, you can for example use the CRISPR/Cas9 technology to introduce frameshift mutations into a protein-coding genomic region. To obtain a knockout cell line of choice you would typically screen 50-100 monoclones for frameshift mutations present on all alleles. The most reliable way to achieve this is to use deep sequencing. OutKnocker.org analyzes raw deep sequencing data and delivers the genotype of each clone using a convenient graphical pie chart representation. In addition, the software displays a detailed alignment of the detected alleles to the wild type sequence. Apart from the identification of knockout clones, OutKnocker can also be used for the analysis of polyclonal genome editing frequencies.
Next to the OutKnocker you developed a further open source program that can be used to visualize RNA sequencing data named BrowserGenome. What can I use this software for and how did you come up with the idea to develop this new software tool?
BrowserGenome.org is a web-based software that can be used to analyze raw data from RNA sequencing experiments. First, the software maps millions of sequencing reads to the human or other genome. Then, it calculates read densities for individual genes. These read densities typically correlate with the absolute expression of genes.
The strength of the tool is that it visualizes the normalized read densities in a graphical and interactive way, allowing to explore the data intuitively. A further advantage of BrowserGenome is that it can be used from a web browser and does not require installation of any software.
The idea to write a web-based genome analysis software came up when browser games were becoming more and more complex a few years ago, which was possible due to improvements in web browser engines and web standards like HTML5.
The TALEN and later the CRISPR/Cas9 technology you are working with a lot were a revolutionary tool in the Genome Engineering field. What do you think are the main future technologies and trends in basic research?
It is hard to imagine a further improvement that will solve as many problems in functional genome research as the CRISPR technology has solved. For sure however, the wild type Cas9 nuclease from Streptococcus pyogenes will not be the final nuclease enzyme, as it suffers from high off-target rates and induces rather unpredictable lesions in the genome. In contrast for example, the group of David Liu has recently published an engineered Cas9-based enzyme that specifically changes cytidine into uridine, allowing to edit the genome of cells in a very defined way. Besides that, I believe that the efficient integration of tag genes might be an important new element in the genome editing toolbox in order to visualize protein expression, localization, and interaction. Setting up such a toolbox is what we are currently working on.
You are already about to defend your PhD thesis. What are your future plans?
I plan to start a postdoc at the Broad Institute in Boston in the labs of Feng Zhang and Aviv Regev. In the long term, I would like to start my own lab, but that is still some way to go!