OBJECTIVES: The research aims to explore mechanisms (molecular toxicology, biomarkers of effects, toxicogenomic responses) triggered in humans and natural biota by organic pollutants, their metabolites and mixtures. The outcomes contribute to protection of the environment and health by providing scientific evidence and support to pragmatic risk assessment and management of chemicals.

FOCUS: Doctoral research projects focus on the effects of chemical groups that are broadly used in practice but their (eco)toxicological characterization is poor such as novel types of flame retardants, pharmaceuticals, pesticides and other potential endocrine-disrupters. Students benefit from outstanding research facilities of RECETOX that include high-end analytical instrumentations, molecular toxicology laboratories, alternative toxicological models - aquatic invertebrates and zebrafish.

EXAMPLES of potential student doctoral projects:
* Development of quantitative Adverse Outcome Pathways (AOPs) for liver toxicity and obesogenicity
* AOP networks beyond the male reproductive disorders
* In vitro toxicological investigations of novel flame retardants
* Molecular and biochemical effect biomarkers of low-dose mixture exposures in human cohort samples
* Automated text-mining approaches integrating toxicological data to toxicological knowledge

MORE INFORMATION: www.recetox.muni.cz

PLEASE NOTE: before initiating the formal application process to doctoral studies, all interested candidates are required to contact Prof. Ludek Blaha (blaha@sci.muni.cz) for informal discussion.

Školitel

prof. RNDr. Luděk Bláha, Ph.D.

OBJECTIVES: Access to water of sufficient quality is a major societal issue, and the present research aims to investigate processes during final purification of waste waters suitable for recycling and re-use for different purposes. Currently, new combinations of technologies for final purification of recycled water are being introduced at waste water treatment plants, WWTPs. These include, e.g., UV/UVLED disinfection, ozonization, cavitation/plasma, use of reactive nanomaterials etc. However, the full impacts on the final water quality have not been fully elucidated.

FOCUS: The doctoral research, which is a part of multi-partner applied projects supported by TAČR, will combine chemical analytical tools (including LC-MS/MS) together with bioanalytical approaches (cell-based in vitro assays and ecotoxicological models) to investigate performance of various WWTP technologies focusing on micropollutants, endocrine disruptive compounds and their transformation products and metabolites. The results will be combined with other water quality parameters such as microbiota, antibiotic resistence, etc., to fully characterize, improve and automatize (digital twin models) processes for recycling of waste waters.

ADDITIONAL INFORMATION: before initiating the formal application process to doctoral studies, all interested candidates are required to contact Prof. Ludek Blaha (blaha@sci.muni.cz) for informal discussion.

Školitel

prof. RNDr. Luděk Bláha, Ph.D.

Práce se bude zaměřovat na nové přístupy hodnocení vlivu vybraných faktorů exposomu na biomarkery efektu a možná zdravotní rizika v lidské populaci. Hodnoceny budou například vybrané skupiny chemických látek a stresorů, které byly prioritizovány v rámci mezinárodního projektu HBM4EU. Důraz bude kladen také na statistické metody hodnocení. Do analýz budou zahrnuta jak data o externí expozici chemickým směsím, tak i výsledky analýz biomarkerů efektu. Metody budou aplikovány na reálná data získaná z kohortových studií (například CELSPAC – FIREexpo, CELSPAC-SPECIMEn, CELSPAC-YA, atd.), ale také i z populačních dat.
Detaily o tomto Ph.D. výzkumném zaměření budou sděleny při osobní konzultaci - doc. RNDr. Pavel Čupr, Ph.D. (cupr@recetox.muni.cz). Zaměření odborné skupiny je popsáno zde - WEB: https://www.recetox.muni.cz/hear
Před výběrem výzkumného zaměření mne prosím kontaktujte: pavel.cupr@recetox.muni.cz.

Školitel

doc. RNDr. Pavel Čupr, Ph.D.

Miniaturization and automation are key trends in modern experimental methods in the natural sciences and biomedicine. Microfluidics makes it possible to perform thousands of experiments per second thanks to the precise handling of nano- to pico-liter volumes of solutions in the microenvironment of channels measuring tens of micrometers. The project will focus on the development and optimization of microfluidic systems for high-performance characterization and study of proteins obtained from genomic databases and constructed by protein engineering methods. The obtained data will be evaluated by artificial intelligence methods. The newly developed methods will be applied in the study of the mechanism of Alzheimer's disease and the development of new drugs for stroke. The project will be solved in cooperation with the research group Prof. Andrew deMello at ETH Zurich, Switzerland (https://www.demellogroup.ethz.ch/) and the International Center for Clinical Research, University Hospital at St. Anny in Brno

Školitel

prof. RNDr. Zbyněk Prokop, Ph.D.

Today, there are numerous male reproductive health issues. For instance, over 20% of couples struggle with infertility, with 40-60% of those cases being caused by male infertility. Male reproductive cancers are also on the rise. Exposure to chemicals surrounding us, including drugs, are thought to contribute to these health problems. To study the health effects of chemicals, modern toxicology aims at increasing the use in vitro appraoches to reduce animal experimentation. However, the current in vitro testicular models used for human research, biomedicine, and safety testing are not adequately mimicking human (patho)physiological conditions because they are mostly based on rodent cancer cell lines cultured as a single layer, lacking key functional parameters and mainly resemble adult testicular cell types. At first, this doctoral research project will overview how chemicals are currently assessed for their impact on male reproductive health and the challenges in using animal-free models for male reproductive toxicology and biomedicine. The goal of the research is to contribute to the development of more human-relevant in vitro testicular models and evaluate the performance of the different models in hazard assessment.

Školitel

RNDr. Iva Sovadinová, Ph.D.

Project summary: Enzymes catalyse most of the chemical reactions that occur in biological systems and can be given non-natural catalytic functions by protein engineering. However, despite their vast importance, we do not know how enzymes acquire the structural diversity and conformational flexibility that enables them to evolve towards new molecular functions. Our proof-of-concept data on three structurally similar but functionally distinct enzyme classes of haloalkane dehalogenases (EC 3.8.1.5), beta-lactone decarboxylases (EC 4.1.1.114), and light-emitting monooxygenases (EC 1.13.12.5) suggest that as-yet-underexplored molecular elements – access tunnels and flexible loops – play a pivotal role in their functional diversification.

The proposed PhD project will investigate the molecular structures of these model enzymes using an innovative multi-method biology approach to identify the key structural and dynamic elements that govern enzymes’ evolvability. This project will combine X-ray crystallography, single-particle cryo-electron microscopy, and advanced mass spectrometry techniques to capture unprecedented molecular details of the conformational sampling that is required for productive enzymatic biocatalysis. Complementary protein simulations, mutational and biochemical experiments will delineate the evolutionary trajectories that lead to the emergence of novel enzymatic functions. The resulting knowledge will extend our understanding of molecular evolution beyond the current state-of-the-art, particularly by revealing how the conformational diversity of proteins is associated with specific biocatalytic functions. The gained knowledge from this PhD project will pave the way for the development of new theoretical concepts and cutting-edge software tools for the rational engineering of tailor-made biocatalysts exploitable in biotechnology and biomedicine.

PLEASE NOTE: Before starting formal application/admission process, all applicants are requested to contact supervisor (martin.marek@recetox.muni.cz).

Školitel

Ing. RNDr. Martin Marek, Ph.D.

Aims: The aim of the thesis is to build a framework for estimating effects of xenobiotics on human microbiome metabolic pathways.

Background and methods: Food with its variety of dietary compounds, environmental chemicals, pollutants, as well as medications can be considered as xenobiotics to the human microbiome. In homeostasis (the healthy state that is maintained by the constant adjustment of biochemical and physiological pathways), human microbiome provides an extra set of biochemical reactions. The intrusion of xenobiotics has the potential to introduce a departure from homeostasis in many ways seen from the perspective of human microbiome, but both human cells and microbial communities living in their surroundings have to cope with these perturbations: pollutants can trigger latent enzymatic activities changing the functional potential of these microbial consortia; other drug metabolites can block important enzymes or can be biotransformed making antibiotics or other medical interventions useless or ineffective. Such perturbations (blocks and diversions of normal enzymatic activities) can be modeled and explored in the context of metabolic network models. Computational System Biology approaches can model and explore consequences of changes in the structure of networks simulated by random or target attack to nodes/metabolites in the metabolic network of the microbiome of interest. The assembled metabolic network model for the community understudy will be dynamically “updated” based on selected computational approaches aimed at predicting latent enzymatic activities (edge insertion update), enzymatic inhibition (edge deletion update), or changes in kinetics (edge weight update).

Školitel

Mgr. Eva Budinská, Ph.D.

Cílem práce bude studium enzymů pomocí výpočetních metod molekulového modelování a bioinformatiky. Výstupem analýz budou nejen nové poznatky v enzymologii, ale také varianty enzymů vytvořené metodami proteinového inženýrství, které budou mít potenciál v biotechnologických či biomedicínských aplikacích. Analýzy i design nových variant se zaměří na vylepšování stability molekul, které budou studovány metodami jako je Rosetta, FoldX nebo FireProt. Dále bude studována a optimalizována aktivita, specificita a selektivita enzymů metodami molekulového dokování, molekulové dynamiky, kvantová chemie a dalších. Poznatky ze studia enzymů budou také využity pro zlepšování softwarových nástrojů k analýze a designu proteinů, které tým v Loschmidtových laboratořích dlouhodobě vyvíjí.

The aim of this thesis will be to study enzymes by in silico approaches of molecular modeling and bioinformatics. The outcomes of the project will be used both in understanding the basics of enzymology and also to design enzyme variants by methods of protein engineering which can be applicable in biotechnology or biomedicine. The analysis and design of new enzyme variants will focus on improving the protein stability by methods like Rosetta, FoldX, or FireProt. Morover, other enzyme properties like activity, selectivity, or specificity will be analysed and optimized by molecular docking, molecular dynamics, or quantum chemistry calculations. The knowledge obtained during the analysis and design of enzymes will be utilized to improve functionality of software tools for protein engineering which are developed in Loschmidt laboratories.

Školitel

Mgr. David Bednář, Ph.D.

The recent advancements of Machine Learning (ML) techniques, coupled with growing protein data, provide promising directions for protein engineering. There are three types of protein data with an excellent ML potential: (i) in silico simulations, (ii) experimental measurements, and (iii) databases of protein sequences and structures. While ML has already leveraged some data from all the three sources in various applications in protein engineering, the field has only recently emerged, and much data remain unexplored. This project aims to explore the potential of machine learning methods in collecting protein data, reducing its dimensionality, performing data analysis, prediction, and optimization, to produce designs of improved proteins. The impact will primarily be (i) the new knowledge of the underlying mechanisms, (ii) promising protein variants, and (iii) user-friendly software tools that will provide access to the developed algorithms to the broader community of protein engineers.

Školitel

Stanislav Mazurenko, PhD