Anna Wierczeiko

About me

Anna Wierczeiko
PhD-student

anna.wierczeiko@uni-mainz.de, anna.wierczeiko@unimedizin-mainz.de

Anselm-Franz-von-Bentzel-Weg 3, 55128 Mainz

Current project

Project 1: Analysis and detection of RNA modification using Oxford Nanopore Technologie’s sequencing techniques

RNA modifications play a crucial role in many cellular and biological processes, opening an emerging research field known as epitranscriptomics. To this date, over 150 different RNA modifications have been identified, and only recently has it been possible to map selected RNA modifications at single-nucleotide resolution. In collaboration with the Helm Group, we synthesize artificial RNA containing various base modifications and analyze them using Oxford Nanopore's direct RNA sequencing approach. By implementing machine learning algorithms, we want to establish new protocols and tools for the accurate identification of RNA base modifications alongside the nucleotide sequence. Collaborations: Stefan Mündnich, Prof. Dr. Mark Helm

Project 2: NanopoReaTA: a user-friendly tool for nanopore-seq real-time transcriptional analysis

Oxford Nanopore Technologies’ (ONT) sequencing platform offers an excellent opportunity to perform real-time analysis during sequencing. This feature allows for early insights into experimental data and accelerates a potential decision-making process for further analysis. Here we introduce NanopoReaTA, a user-friendly real-time analysis toolbox for RNA sequencing data from ONT. Sequencing results from a running or finished experiment are processed through an R Shiny-based graphical user interface (GUI) with an integrated Nextflow pipeline for whole transcriptome and
gene-specific analyses. NanopoReaTA provides visual snapshots of analysis results in progress, thus enabling interactive sequencing and rapid decision-making. The application can be installed via conda or docker and can be found on Github.

Proejct 3: Transcriptomics in health and disease

RNA-seq is the gold-standard next-generation sequencing method that is used to detect differential expression of different kinds of RNA species between different conditions at a certain time-point. In this project, I use this technique to
1. Detect Molecular Changes after Different Sport duration in Alzheimer’s disease mouse models – Collaboration: PD Dr. Kristina Endres
2. Identify immune-associated differences in gene expression between male and female patients suffering from different types of psoriasis diseases – Collaboration: Dr. Sebastian Boegel, Univ.-Prof. Dr. med. Andreas Schwarting
3. Identify gene biomarker that distinguish patients suffering from rheumatic arthritis with lung involvement from those without lung involvement – Collaboration: PD Dr. med. Alexander Gerber, Prof. Dr. med. Andreas Krause
4. Investigate the communication between gut microbiota and the miRNome from feces of resilient and suceptible mouse samples - Collaboration: PD Dr. Kristina Endres

Project 4: Optimization of the Calcium Imaging Analysis Pipeline

Together with the group of Prof. Dr. Albrecht Stroh and in collaboration with the Fraunhofer ITWM, we are following the goal of improving and accelerating the analysis of calcium imaging data, starting with the automatic marking of neurons in the generated image files using deep learning. We developed some analytical procedures for calcium imaging analysis including the semi-automatic neuron detection tool ViNe-Seg, that is currently still under development and general experimental guidelines published in a book chapter. - Collaborations: LIR, Prof. Dr. Albrecht Stroh, Frauenhofer ITWM

 

Publications