Academic Profile

Marek received his Bachelor and Master degrees in biochemistry at the University of Copenhagen, Denmark, where he studied the biosynthesis of polysaccharides in tip-growing cells in the group of prof. William G.T. Willats. He then joined the group of prof. Staffan Persson at the Max Planck Institute of Molecular Plant Physiology (MPIMP), focusing on computational biology of plants. After a brief postdoc, he established a research group at MPIMP, where he used computational biology to study gene co-function networks, with the aim to understand how genes work together to express plant traits and to elucidate how plants evolve new pathways. His group at NTU was established in December 2017.
Marek Mutwil.jpg picture
Asst Prof Marek Mutwil
Assistant Professor, School of Biological Sciences

Dr. Marek Mutwil and his research group combine bioinformatics, machine learning, data science, and experimental biology to study the evolution of the plant kingdom from the perspective of gene expression.

More specifically, we ask the questions:
1) What are the functions of plant genes? To generate cutting-edge gene function predictions we utilize our own and publicly available large-scale biological data, together with state-of-the-art ensemble prediction algorithms. We make these predictions publicly available with our popular online databases.

2) How are biological networks evolving? Biological features (e.g. secondary metabolites or disease resistance) are encoded by polygenic gene modules, which often cannot be identified by genomics. To uncover them, we combine genomic and gene expression information to identify modules of functionally-related genes. By constructing and comparing the modules of green algae, mosses, vascular-, seed- and flowering plants, we will gain a systems-level, kingdom-wide understanding of when these modules appear and how they change in plant evolution.

3) Which gene modules biosynthesize high-value compounds found in plants? Co-function networks based on RNA sequencing data are a proven tool to identify genes involved in the biosynthesis of plant secondary metabolites. The group will focus on elucidating module-metabolite relationships with a special focus on plants of importance to Singapore and the bioprospecting of the rainforest. The functions of the elucidated modules, i.e. production of the secondary metabolites, will be tested by expression in heterologous systems, such as bacteria and/or yeast.
  • A Comprehensive Survey Of The Interactome Inside The Cytoplasm Of Red Blood Cell Infected By Plasmodium Parasite

  • Characterization, in vitro and in vivo validation of local tropical herbs for colon cancer, stomach cancer and liver cancer prevention and treatment

  • Gene Co-function Networks As Tools To Understand Plant Evolution And Secondary Metabolism

  • Improving yield, cultivating efficiency and nutrient quality of hydroponically-grown crops with rapid testing of growth conditions and gene expression analysis

  • Towards revealing biosynthesis of anti-tumor metabolites in Hedyotis diffusa

  • Uncovering the temporal gene expression dynamics of phytoplankton with single-cell RNA sequencing
  • Delli-Ponti R, Shivhare D, Mutwil M (2020) Using gene expression to study specialized metabolism - a practical guide. Front Plant Sci.

    Lim JJJ, Koh J, Moo JR, Villanueva EMF, Putri DA, Lim YS, Seetoh WS, Mulupuri S, Ng JWZ, Nguyen NLU, Reji R, Foo H, Zhao MX, Chan TL, Rodrigues EE, Kairon RS, Hee KM, Chee NC, Low AD, Chen ZHX, Lim SC, Lunardi V, Fong TC, Chua CX, Koh KTS, Julca I, Delli-Ponti R, Ng JWX, Mutwil M (2020) Comparative genomic and transcriptomic resource for the fungi kingdom. Comput Struct Biotechnol J

    Hew B, Tan QW, Goh W, Ng JWX, Mutwil M (2020) LSTrAP-Crowd: prediction of novel components of bacterial ribosomes with crowd-sourced analysis of RNA sequencing data. BMC Biol

    Tan QW, Goh W, Mutwil M (2020) LSTrAP-Cloud: A User-Friendly Cloud Computing Pipeline to Infer Coexpression Networks. Genes (Basel).

    Mutwil M (2020) Computational approaches to unravel the pathways and evolution of specialized metabolism. Curr Opin Plant Biol. 19;55:38-46.

    Ferrari C, Shivhare D, Hansen BO, Pasha A, Esteban E, Provart NJ, Kragler F, Fernie AR, Tohge T, Mutwil M (2020) Expression Atlas of Selaginella moellendorffii Provides Insights into the Evolution of Vasculature, Secondary Metabolism, and Roots. Plant Cell.​ Jan

    Ran QW, Mutwil M (2019) Inferring biosynthetic and gene regulatory networks from Artemisia annua RNA sequencing data on a credit card-sized ARM computer. Biochim Biophys Acta Gene Regul Mech.​ Oct

    Ferrari C, Mutwil M (2019) Gene expression analysis of Cyanophora paradoxa reveals conserved abiotic stress responses between basal algae and flowering plants. New Phytol.

    Ng JWX, Tan QW, Ferrari C, Mutwil M (2019) comparative transcriptomic and co-expression analyses of diurnal gene expression of the Archaeplastida kingdom. Plant Cell Physiol.​

    Tan QW, Mutwil M (2019) genomic and transcriptomic database for Plasmodium species. Nucleic Acids Res. Aug

    Ferrari C, Proost S, Janowski M, Becker J, Nikoloski Z, Bhattacharya D, Price D, Tohge T, Bar-Even A, Fernie A, Stitt M, Mutwil M (2019) Kingdom-wide comparison reveals the evolution of diurnal gene expression in Archaeplastida. Nat Commun. 13

    Janowski M, Zoschke R, Scharff L, Martinez Jaime S, Ferrari C, Proost S, Ng Wei Xiong J, Omranian N, Musialak-Lange M, Nikoloski Z, Graf A, Schöttler MA, Sampathkumar A, Vaid N, Mutwil M (2018). AtRsgA from Arabidopsis thaliana is important for maturation of the small subunit of the chloroplast ribosome. Plant J. 96, 404-420.

    Proost S, Mutwil M (2018). CoNekT: an open-source framework for comparative genomic and transcriptomic network analyses. Nucleic Acids Res. 46, W133-W140.

    Ferrari C, Proost S, Ruprecht C, Mutwil M (2018). PhytoNet: Comparative co-expression network analyses across phytoplankton and land plants. Nucleic Acids Res. 46, W76-W83

    Hansen BO, Meyer EH, Ferrari C, Vaid N, Movahedi S, Vandepoele K, Nikoloski Z, Mutwil M (2018). Ensemble gene function prediction database reveals genes important for complex I formation in Arabidopsis thaliana. New Phytol. 217, 1521-1534.

    Proost S, Krawczyk A, Mutwil M (2017). LSTrAP: efficiently combining RNA sequencing data into co-expression networks. BMC Bioinformatics. 18, 444.

    Sibout R, Proost S, Hansen BO, Vaid N, Giorgi FM, Ho-Yue-Kuang S, Legée F, Cézart L, Bouchabké-Coussa O, Soulhat C, Provart N, Pasha A, Le Bris P, Roujol D, Hofte H, Jamet E, Lapierre C, Persson S, Mutwil M (2017). Expression atlas and comparative coexpression network analyses reveal important genes involved in the formation of lignified cell wall in Brachypodium distachyon. New Phytol. 215, 1009-1025.

    Ruprecht C, Proost S, Hernandez-Coronado M, Ortiz-Ramirez C, Lang D, Rensing SA, Becker JD, Vandepoele K, Mutwil M (2017). Phylogenomic analysis of gene co-expression networks reveals the evolution of functional modules. Plant J. 90, 447-465.

    Ruprecht C, Vaid N, Proost S, Persson S, Mutwil M (2017). Beyond Genomics: Studying Evolution with Gene Coexpression Networks. Trends Plant Sci. 22, 298-307.

    Proost S, Mutwil M (2017). PlaNet: Comparative Co-Expression Network Analyses for Plants. Methods Mol Biol. 1533, 213-227.