The Smad2/3 interactome and its role in the TGFß pathway
Nature publication 2018
microRNA expression profiles in brain tissues using divo.R
CRAN R-software 2017
Fitness Landscape of the Fission Yeast Genome
Molecular Biology and Evolution publication 2019
A model of thermotherapy treatment for bladder cancer
Mathematical Biosciences and Engineering publication 2015
Simulation of Amyloid-ß using Molecular Dynamics
Poster 2014
About
What happened so far?
1992-2003
The Beginning
Born in Schweinfurt, Bavaria, south Germany, in 1992, Chris developped a keen interest in sports, crafting and science after completion of many a construction kit and joining the local tennis club.
2003-2009
The first Move
There was a lot of moving to come but this being the first time, he quickly had to adjust to make friends in his new home in Mettmann, west Germany. He joined the school football team, maths society and local badminton club.
2009-2011
fáilte go hÉirinn
Welcome to Ireland! After much excitement, Chris left the secureness of home and travelled to a small green island in hopes of learning Gaelic. Little did he know that the main focus was on English on the emerald island and the boarding school he attended where he completed his school studies.
2011-2015
University College Dublin
Decisive in his opinion to stay in Ireland but undecisive in what science to study, he enrolled into a general science entry course at UCD with a focus on Biochemisty but decided after one year to switch and study something simpler, Theoretical Physcis.
2015-2016
London Calling
Completing his bachelor of physics with a publication, Chris decided it was time for a new challenge and left for London and his interdisciplinary Masters in UCL. This led to excursions of applying fluid mechanics to blood flow in a coarctation patient (simulation) and investigating miRNAs in the USA.
2016-2017
The Francis Crick Institute
Hooked on RNA (not a drug), he joined Jernej Ule's RNA networks group at The Francis Crick Institute in London, learning standard experimental wet lab techniques and the not so standard irCLIP method, spanning his knowledge from Physics to Biology and completing with a nature co-authorship and patent.
2018
Back to America
Having learned about computational and experimental biology it was time for Chris to combine his experiences at the Harvard Wyss Institute for Biologically Inspried Engineering in Boston. There he worked on a delivery device for organ-on-chips (tiny organs) enjoying the open minded and freedom loving environment of the US, hoping to return soon.
During my time at the Francis Crick Institute in 2017 I noticed a heavy reliance on manual work in the biosciences as compared to a much more automated approach typical in the physical sciences. My background and past experiences led me then to identify key procedures that could be isolated and automated, bringing a physical approach with high reproducibility to the complexity of biological techniques. To implement automation, I acquired my own 3D printer and learned the SolidWorks software using online tutorials. I developed two complementary devices to be used in magnetic particle manipulation for immunoprecipitations, an automated magnetic rack and a magnetic pipette. These devices decrease experimental execution time, while increasing reproducibility and overall efficiency. In working with the translation team at the Crick, we filed a patent in January 2018 for one of the devices. I also applied for an “Idea to Innovation” grant and obtained funding to industrially produce and beta-test 15 prototypes based on my original design. I am currently using the devices to supervise a market research study at the Crick, handing them out for testing to collect feedback and show market potential. Finally, we have been in discussion with a lab equipment manufacturer to potentially establish a licensing agreement for production. It is exciting to see my ideas come to life while learning about the hurdles of patent filing, non-disclosure agreements and grant applications. It showed me the importance of translation necessary to enable widespread application, as discovery does not immediately facilitate adoption.
The SMAD2/3 interactome reveals that TGFβ controls m6A mRNA methylation in pluripotency
While working at the Francis Crick Institute in 2017 I learned standard techniques such as PCR, cell culture and Western blotting and focused in particular on further developing and applying the complex techniques of irCLIP and miCLIP. These techniques use the premise of immunoprecipitation in conjunction with sequencing to target RNA binding proteins and elicit their binding sequence or position of RNA modifications. Through these techniques I was able contribute to a number of collaborative projects within and outside the lab. Most exciting for me was my work on the SMAD2/3 interactome. My work aimed to elucidate specific RNA binding sites of SMAD2/3 by using CLIP but instead revealed SMAD2/3 as an indirect binder, recruiting RNA binding proteins such as METTL3 for post-transcriptional modifications. My experimental efforts and computational analysis contributed to the published Nature paper, which I co-authored. The work opened my eyes to biological research and validated to me the importance of novel ideas gained through collaboration and scientific networks.
Analyzing microRNA expression profiles in human brain autopsy tissues by adapting divo.R
In 2016 I had the opportunity to join the Mathematical Biosciences Institute at the Ohio State University in the US for a short placement during my master’s. During the internship I redeveloped an R package for big data, by taking the R wrapper to parse data to my optimized C code, yielding at least a 60-fold speed improvement in computation. This made it possible for me to analyze miRNA data in different brain regions and re-uploaded the software on CRAN as my first author R package. The project showed me the need for appropriate computational tools to explore the ever expanding "omics" fields while allowing me to learn the fundamental C coding language.
In my interdisciplinary master’s at University College London I started working on the computational analysis of a transposon mutagenesis screen in fission yeast to identify previously unnannotated regions important for cell fitness. This being one of my first biochemically-focused projects, I learned about the idea of insertional inactivation by transposing a DNA vector into a quasi-random position of the genome and disrupting local function. In this study, insertion took place over a period of multiple growth cycles before being sequenced, and the effect of selective gene disruption on growth was assayed. Using a Hidden Markov Model (HMM) through R, I analyzed the data by classifying regions of the genome as one of three hidden states, essential, intermediate or non-essential for growth. To uncover the states, I trained the model on an annotated subset using online databases to match the regions. Initial results were poor, with low correlation of essential regions to known coding regions and with states rapidly flipping at positions of multiple insertions per location. In particular I noticed that at these turning points, transposon counts coalesced at certain values. Curious about their experimental basis, I approached the student who generated the data. At the end I concluded that multiple transposon counts at a single location are most likely not due to multiple insertion events but instead relate to a single insertion event and subsequent mitosis, duplicating the genome with its transposon at that position. Furthermore, the distinct values observed correspond to exponential growth values of base two, further underlining the relation. Therefore transposon counts can be log transformed to represent growth cycles after insertion occurred, with a single transposon count equivalent to no growth indicating the disruption of an essential region. Reanalyzing the transformed data yielded good agreement, with essential regions mostly falling within protein coding sequences, intermediate regions intersecting with 3’ and 5’ UTRs and non-essential regions mostly covered by ncRNAs. In addition to overlap with preexisting databases, the screen identified multiple areas without prior annotation as essential and provides high-resolution annotated sub-sections that can be explored on an individual basis. Due to my contribution the data was successfully interpreted and brought to publication with an expanded five state model for improved resolution in Molecular Biology and Evolution, listing me as second-author (with two first authors).
A model of thermotherapy treatment for bladder cancer
In the final year of my undergraduate studies I started working on a biomedical bladder cancer treatment device. The device operates through an inserted catheter, circulating a chemotherapy drug in the bladder while applying heat internally using a microwave applicator. Its FDA approved mechanism was found to have lower recurrence rates due to an apoptotic thermal effect but variations occurred by either burning the tissue or having no substantial effect. I investigated these differences by numerically solving Ampere’s and Faraday’s law in dispersive media to simulate microwave propagation through solution and tissue. The occurring loss factor was then matched as a source term to the convection-diffusion equation and numerically solved, revealing the generated heat in tissue and liquid. Varying model parameters, I found that the salinity of the chemotherapy solution played a vital role in heat uptake. High concentrations absorbed most of the radiation, heating the solution with little effect to tissue. However low concentrations allowed deep microwave penetration and excessive heating, explaining the observed burns. The changing salinity can be linked to the presence and addition of urine during the procedure, explaining the observed differences in outcome. My model indicates that there should be an ideal salt concentration for moderate tissue penetration. My findings are outlined in my first author publication.
Modeling of Alzheimer's Disease (AD) inducing Protein Amyloid-beta (Aβ) in 3D
Alzheimer's disease (AD) is a form of dementia affecting mainly the elderly. Symptoms are loss of short term memory in the early stages up to shut down of basic bodily functions leading to death in the final stages.There is currently no treatment for the prevention or delay of AD,with medication manly focusing on suppressing AD symptoms.The disease is caused by the protein fragment Amyloid-beta, clustering together with other fragments inside of the brain and forming a plaque around neurons,leading to their cell death! The main structure of Amyloid-beta is known and can be further investigated using Molecular dynamics (MD) simulations. MD uses classical mechanics to numerically analyse protein structures , which allows one to investigate structural changes to the protein.
