What drives protein production and localization in a major fungal pathogen?

Fungal pathogens such as Cryptococcus, Candida, and Aspergillus, are a global threat to human, animal, and plant health, and new understanding is essential to countering them (Cairns 2016). Fungi are also a platform for understanding fundamental eukaryotic biology, including how environmental adaptation relies on regulation of protein synthesis (translation), as well as of RNA synthesis (transcription) and decay.

We have recently found that there are many fungal genes that are likely to make two alternative protein products, localized to different parts of the cell, by starting from two alternative start codons on the same messenger RNA (Wallace 2019). This suggests an intriguing mechanism that could link regulation of start codon selection to cell shape and environmental responses.

What will you do?

This project will study how Cryptococcus neoformans regulates protein synthesis in dynamic and varied environments, primarily using high-throughput sequencing and reporter gene assays. We will build on our recent work using ribosome profiling to understand translation regulation in Cryptococcus and other fungi. To ask how alternative start codons are used in different environments, we will use ribosome profiling and bioinformatics to quantify translation starts genome-wide. Your high-throughput studies will be complemented by new functional genomics tools to understand the mechanistic basis of these responses: a library of gene deletion mutants, CRISPR/Cas9 transformation to generate new mutants, and novel reporter gene systems. For example, we would use fluorescent reporter genes and microscopy to find how mRNA sequence affects protein localization within the cell.

What will you learn?

The project relies on making high-throughput sequencing "libraries”, a lengthy protocol that develops fastidious organizational and experimental skills. You will use automation, including pipetting robots, to maximize your productivity. You will of course learn fundamental good lab practice including cell growth, molecular biology, and experimental design. The data analysis side will also be intense, using bioinformatics and statistics software, and organizing the data into a resource for the entire community. We will help you with this, as members of the group are engaged with developing bioinformatics methods and teaching research computing skills.

The rigour and intensity come with substantial rewards, starting with learning a very great deal about biology: genome-wide measurements at nucleotide resolution that bring mechanistic insight. The skills developed in the process are in high demand in research and industry: designing experiments, executing difficult protocols, bioinformatics, and data science.

What kind of student would this project suit?

Our group will be excited to teach the experimental skills to a motivated student with a computational background, or vice versa, but either laboratory or programming/bioinformatics experience will be important to establishing the project.

In addition to the technical skills, this interdisciplinary project would suit a student with a sense of adventure for lengthy protocols and unconventional approaches. Your sense of adventure will likewise be important in the data analysis, as unexpected gene regulation patterns can be discovered in big rich datasets (Otto 2019), and we would like to do that too.

https://ewallace.github.io/