Christian Diener, PhD

Lifelong relationship with microbes. Now studying them for a living.

Who am I?

Hi, my name is Christian and I am german-born scientist currently living in Seattle. My primary areas of expertise are Microbial Systems Biology and Computational Biology, which means I am interested how all of the microbes, cells and molecules around and within us interact in order to form stable ecological systems and maintain you happy and healthy. In particular, I want to know what happens if those interactions are perturbed, for instance by disease. I strongly believe that we can leverage medical, biological, ecoogical, and environmental data to help us improve human health and to conserve our planet. However this will require an equitable, just, and diverse research community.

I love to learn new things and tinker and especially enjoy spending time with my partner and our dog. I also like to experiment and play around with different electronics. I enjoy sharing what I have learned and have taught many courses in academia and tech. If I am not doing any of that you will usually find me eating, cooking or baking.

If you want to know what I am currently up to follow me on twitter or see my projects on github.

What am I currently working on?

I am currently a Research Scientist at the Institute for Systems Biology and working in the field of Microbial Systems Ecology and Evolution. This is done within the Gibbons Lab.

My work is focussed on the human gut microbiome which means I basically study the genetic material, metabolism and ecology of microbial communities that live within us. I am participating in or leading various projects that study the microbiota across thousands of individuals to identify the major changes in the microbiome during the transition from a healthy state to a diseased one. To that effect, I use various methods ranging from statistical inference to mathematical modeling in order to understand how the microbiome affects the host metabolism. I am particularly interested in methods that go beyond mere correlations and also do some wet lab work in order to validate computational predictions.

Before that I studied signaling in microbial cultures and metabolic alterations in cancer (you can find more about that in my publications).

Latest publication

Constraint-Based Reconstruction and Analyses of Metabolic Models: Open-Source Python Tools and Applications to Cancer

The influence of metabolism on signaling, epigenetic markers, and transcription is highly complex yet important for understanding cancer physiology. Despite the development of high-resolution multi-omics technologies, it is difficult to infer metabolic activity from these indirect measurements. Fortunately, genome-scale metabolic models and constraint-based modeling provide a systems biology framework to investigate the metabolic states and define the genotype-phenotype associations by integrations of multi-omics data. Constraint-Based Reconstruction and Analysis (COBRA) methods are used to build and simulate metabolic networks using mathematical representations of biochemical reactions, gene-protein reaction associations, and physiological and biochemical constraints.

Latest post

Turing the microbiome

In those days analyzing microbiome data often means dealing with read counts from high-throughput sequencing. Usually, we stratify those counts by some entity of interest: phyla, species, genes, sequence variants and so on. Three questions that may pop up when analyzing those read counts are the following: Does the sample contain enough reads to observe the majority of phyla, species, genes that are actually in the sample? How well do the reads represent their distribution in the sample?