Honors & Awards
Nominated for International Society of Computational Biology Fight Against Ebola Award, International Society of Computational Biology (ISCB) (July 2016)
Research Scholarship for training of biological applications of microfluidics devices, imec (May 2013)
Doctor of Philosophy, Katholieke Universiteit Leuven (2017)
Master of Science, Swedish University of Agricultural Sciences (2013)
Current Research and Scholarly Interests
The focus of the research is to understand the impact of genomic variations appear in the experimental models on biological networks and pathways. To elaborate and interpret our findings from opioid addict mouse models we integrate multi-omics data. The integration of omics data can provide details of driver mutations and new outline of genotype to phenotype relationship.
Integrated Multi-Omits Analysis of Mechanisms Underlying Yeast Ethanol Tolerance
JOURNAL OF PROTEOME RESEARCH
2021; 20 (8): 3840-3852
For yeast cells, tolerance to high levels of ethanol is vital both in their natural environment and in industrially relevant conditions. We recently genotyped experimentally evolved yeast strains adapted to high levels of ethanol and identified mutations linked to ethanol tolerance. In this study, by integrating genomic sequencing data with quantitative proteomics profiles from six evolved strains (data set identifier PXD006631) and construction of protein interaction networks, we elucidate exactly how the genotype and phenotype are related at the molecular level. Our multi-omics approach points to the rewiring of numerous metabolic pathways affected by genomic and proteomic level changes, from energy-producing and lipid pathways to differential regulation of transposons and proteins involved in cell cycle progression. One of the key differences is found in the energy-producing metabolism, where the ancestral yeast strain responds to ethanol by switching to respiration and employing the mitochondrial electron transport chain. In contrast, the ethanol-adapted strains appear to have returned back to energy production mainly via glycolysis and ethanol fermentation, as supported by genomic and proteomic level changes. This work is relevant for synthetic biology where systems need to function under stressful conditions, as well as for industry and in cancer biology, where it is important to understand how the genotype relates to the phenotype.
View details for DOI 10.1021/acs.jproteome.1c00139
View details for Web of Science ID 000684095100006
View details for PubMedID 34236875
View details for PubMedCentralID PMC8353626
Analysis of Structural Variation Among Inbred Mouse Strains Identifies Genetic Factors for Autism-Related Traits
View details for DOI 10.1101/2021.02.18.43186
An international virtual hackathon to build tools for the analysis of structural variants within species ranging from coronaviruses to vertebrates.
2021; 10: 246
In October 2020, 62 scientists from nine nations worked together remotely in the Second Baylor College of Medicine & DNAnexus hackathon, focusing on different related topics on Structural Variation, Pan-genomes, and SARS-CoV-2 related research. The overarching focus was to assess the current status of the field and identify the remaining challenges. Furthermore, how to combine the strengths of the different interests to drive research and method development forward. Over the four days, eight groups each designed and developed new open-source methods to improve the identification and analysis of variations among species, including humans and SARS-CoV-2. These included improvements in SV calling, genotyping, annotations and filtering. Together with advancements in benchmarking existing methods. Furthermore, groups focused on the diversity of SARS-CoV-2. Daily discussion summary and methods are available publicly at https://github.com/collaborativebioinformatics provides valuable insights for both participants and the research community.
View details for DOI 10.12688/f1000research.51477.1
View details for PubMedID 34621504
View details for PubMedCentralID PMC8479851
High Throughput Computational Mouse Genetic Analysis
View details for DOI 10.1101/2020.09.01.278465
The Phosphatidylethanolamine Biosynthesis Pathway Provides a New Target for Cancer Chemotherapy.
Journal of hepatology
Since iPSC human develop into hepatic organoids through stages that resemble human embryonic liver development, they can be used to study developmental processes and disease pathology. Therefore, we examined the early stages of hepatic organoid formation to identify key pathways affecting early liver development.Single cell RNA-sequencing and metabolomic analysis was performed on developing organoid cultures at the iPSC, hepatoblast (day 9) and mature organoid stage. The importance of the phosphatidyl-ethanolamine biosynthesis pathway to early liver development was examined in developing organoid cultures using iPSC with a CRISPR-mediated gene knockout and an over the counter medication (meclizine) that inhibits the rate-limiting enzyme in this pathway. Meclizine's effect on the growth of a human hepatocarcinoma cell line in a xenotransplantation model and on the growth of acute myeloid leukemia cells in vitro was also examined.Transcriptomic and metabolomic analysis of organoid development indicated that the phosphatidyl-ethanolamine biosynthesis pathway is essential for early liver development. Unexpectedly, early hepatoblasts were selectively sensitive to the cytotoxic effect of meclizine. We demonstrate that meclizine could be repurposed for use in a new synergistic combination therapy for primary liver cancer: a glycolysis inhibitor reprograms cancer cell metabolism to make it susceptible to the cytotoxic effect of meclizine. This combination inhibited the growth of a human liver carcinoma cell line in vitro; and in a xenotransplantation model without causing significant side effets. This drug combination was also highly active against acute myeloid leukemic cells.Our data indicates that the phosphatidyl-ethanolamine biosynthesis is a targetable pathway for cancer; and that meclizine may have clinical efficacy as a repurposed anti-cancer drug when used as part of a new combination therapy.
View details for DOI 10.1016/j.jhep.2019.11.007
View details for PubMedID 31760071
- Pyntheon: A Functional Analysis Framework for Protein Modifications and Mutations of 83 Model Organisms Pyntheon: A Functional Analysis Framework for Protein Modifications and Mutations of 83 Model Organisms 2019
yMap: an automated method to map yeast variants to protein modifications and functional regions
View details for DOI 10.1093/bioinformatics/btw658
Evolutionary conservation of Ebola virus proteins predicts important functions at residue level
View details for DOI 10.1093/bioinformatics/btw610
Adaptation to High Ethanol Reveals Complex Evolutionary Pathways
2015; 11 (11): e1005635
Tolerance to high levels of ethanol is an ecologically and industrially relevant phenotype of microbes, but the molecular mechanisms underlying this complex trait remain largely unknown. Here, we use long-term experimental evolution of isogenic yeast populations of different initial ploidy to study adaptation to increasing levels of ethanol. Whole-genome sequencing of more than 30 evolved populations and over 100 adapted clones isolated throughout this two-year evolution experiment revealed how a complex interplay of de novo single nucleotide mutations, copy number variation, ploidy changes, mutator phenotypes, and clonal interference led to a significant increase in ethanol tolerance. Although the specific mutations differ between different evolved lineages, application of a novel computational pipeline, PheNetic, revealed that many mutations target functional modules involved in stress response, cell cycle regulation, DNA repair and respiration. Measuring the fitness effects of selected mutations introduced in non-evolved ethanol-sensitive cells revealed several adaptive mutations that had previously not been implicated in ethanol tolerance, including mutations in PRT1, VPS70 and MEX67. Interestingly, variation in VPS70 was recently identified as a QTL for ethanol tolerance in an industrial bio-ethanol strain. Taken together, our results show how, in contrast to adaptation to some other stresses, adaptation to a continuous complex and severe stress involves interplay of different evolutionary mechanisms. In addition, our study reveals functional modules involved in ethanol resistance and identifies several mutations that could help to improve the ethanol tolerance of industrial yeasts.
View details for DOI 10.1371/journal.pgen.1005635
View details for Web of Science ID 000366179000019
View details for PubMedID 26545090
View details for PubMedCentralID PMC4636377