Martin Engqvist, PhD

Martin Engqvist, PhD

Researcher, Enzyme Engineering
martin.engqvist [at]
se Sweden


2010 Ph.D. summa cum laude in Botany, University of Cologne, Germany
2006 M.Sc. in Molecular Biology, Lund University, Sweden


2017 – Assistant Professor, Chalmers University of Technology, Sweden
2016-2017 Senior Researcher, University of Gothenburg, Sweden
2015-2016 Senior Scientist in Trait Knowledge, BASF CropDesign, Belgium
2014-2015 Postdoctoral scholar, Chalmers University of Technology, Sweden
2011-2014 Postdoctoral scholar, California Institute of Technology, USA
2010 Postdoctoral scholar, University of Cologne, Germany
2006-2010 PhD student, Max Planck Institute for Plant Breeding and University of Cologne, Germany
2005 Research assistant, University of Missouri-St. Louis, USA


2006 Exchange studies through ERASMUS, University of Cologne, Germany
2006 Research project, Lund University, Sweden
2004-2005 Exchange studies through MAUI, University of Missouri-St. Louis, USA
2002-2006 Studies in the molecular biology program, Lund University, Sweden

Positions of trust

2016- Member of the Gothenburgs Bioinformatic Network (GOTBIN) organizing committee, Sweden
2008 Co-organizer of the 1st Joint Retreat of Ph.D. Students in Experimental Plant Sciences in Wageningen, The Netherlands
2007-2008 Ph.D. student representative at the Max Planck Institute for Plant Breeding, Germany
2006 Mentor during orientation activities for the international students at Lund University, Sweden
2004 Mentor during orientation activities for the chemistry students at Lund University, Sweden

Peer-reviewed publications

As of October 2019 (Google Scholar)
Citations: 1045
h-index: 14
Original research articles: 21
Research review articles: 3
Book chapters: 2


As of October 2019 (Google Scholar)
citations: 1045
h-index: 14

Current preprints

ϕ Indicates shared first-authorship as noted in publications.


“Expanding functional protein sequence space using generative adversarial networks”.
Repecka Dϕ, Jauniskis Vϕ, Karpus Lϕ, Rembeza E, Zrimec J, Poviloniene S, Rokaitis I, Laurynenas A, Abuajwa W, Savolainen O, Meskys R, Engqvist MKM, Zelezniak A
bioRxiv (2019)
doi: 10.1101/789719

“Age-dependent loss of mitochondrial DNA integrity in mammalian muscle”.
Wanrooij PH, Tran P, Thompson LJ, Sharma S, Kreisel K, Navarrete C, Feldberg AL, Watt D, Nilsson AK, Engqvist MKM, Clausen AR, Chabes A
bioRxiv (2019)
doi: 10.1101/746719

Peer-reviewed original articles

ϕ Indicates shared first-authorship as noted in publications


“3D Printed phenacrylate decarboxylase flow reactors for the chemoenzymatic synthesis of 4-hydroxystilbene”
Peng M, Mittmann E, Wenger L, Hubbuch J, Engqvist MKM, Niemeyer CM, Rabe KS
Chemistry, In print (2019).
doi: 10.1002/chem.201904206

“Machine learning applied to predicting microorganism growth temperatures and enzyme catalytic optima”
Li G, Rabe KS, Nielsen J, Engqvist MKM
ACS Synthetic Biology 8(6) (2019).
doi: 10.1021/acssynbio.9b00099

“DNA polymerase η contributes to genome-wide lagging strand synthesis”
Kreisel K, Engqvist MKM, Kalm J, Thompson LJ, Boström M, Navarrete C, McDonald JP, Larsson E, Woodgate R, Clausen AR
Nucleic Acids Research 47(5) (2019).
doi: 10.1093/nar/gky1291


“Correlating enzyme annotations with a large set of microbial growth temperatures reveals metabolic adaptations to growth at diverse temperatures”
MKM Engqvist
BMC Microbiology 18 (177) (2018).
doi: 10.1186/s12866-018-1320-7


“Ribonucleotides incorporated by the yeast mitochondrial DNA polymerase are not repaired”
Wanrooij PH, Engqvist MKM, Forslund JME, Navarrete C, Nilsson AK, Sedman J, Wanrooij S, Clausen AR, Chabes A.
Proceedings of the National Academy of Sciences, Nov 7 (2017)
doi: 10.1073/pnas.1713085114

“Simultaneous Mapping and Quantitation of Ribonucleotides in Human Mitochondrial DNA”
Kreisel, K, Engqvist, MKM, Clausen, AR.
Journal of Visualized Experiments, e56551 (2017).
doi: 10.3791/56551

“Nucleotide pools dictate the identity and frequency of ribonucleotide incorporation in mitochondrial DNA”
Berglund AKϕ, Navarrete Cϕ, Engqvist MKM, Hoberg E, Szilagyi Z, Taylor RW, Gustafsson CM, Falkenberg M and Clausen AR.
PLOS Genetics, 13(2): e1006628 (2017).
doi: 10.1371/journal.pgen.1006628


“Highlighting the need for systems-level experimental characterization of plant metabolic enzymes”
Engqvist MKM
Frontiers in Plant Science, 7: 1127 (2016).
doi: 10.3389/fpls.2016.01127

“The influence of alternative pathways of respiration that utilize branched-chain amino acids following water shortage in Arabidopsis”
Pires MV, Júnior AA, Medeiros DB, Daloso DM, Pham PA, Barros KA, Engqvist MKM, Florian A, Krahnert I, Maurino VG, Araújo WL, Fernie AR.
Plant, Cell & Environment, 39 (6): 1304-19 (2016).
doi: 10.1111/pce.12682


“ANT: software for generating and evaluating degenerate codons for natural and expanded genetic codes”
Engqvist MKM, Nielsen J.
ACS Synthetic Biology, 4 (8): 935–938 (2015).
doi: 10.1021/acssynbio.5b00018

“GLYCOLATE OXIDASE3, a Glycolate Oxidase Homolog of Yeast l-Lactate Cytochrome c Oxidoreductase, Supports l-Lactate Oxidation in Roots of Arabidopsis”
Engqvist MKMϕ, Schmitz Jϕ, Gertzmann Aϕ, Florian A, Jaspert N, Arif M, Balazadeh S, Mueller-Roeber B, Fernie AR, Maurino VG.
Plant Physiology, 169 (2): 1042-1061 (2015).
doi: 10.1104/pp.15.01003

“Plants Possess a Cyclic Mitochondrial Metabolic Pathway similar to the Mammalian Metabolic Repair Mechanism Involving Malate Dehydrogenase and l-2-Hydroxyglutarate Dehydrogenase”
Hüdig M, Maier A, Scherrers I, Seidel L, Jansen EEW, Mettler-Altmann T, Engqvist MKM, Maurino VG.
Plant and Cell Physiology, 56 (9): 1820-1830 (2015).
doi: 10.1093/pcp/pcv108

“Adaptive mutations in sugar metabolism restore growth on glucose in a pyruvate decarboxylase negative yeast strain”
Zhang Y, Liu G, Engqvist MKM, Krivoruchko A, Hallström BM, Chen Y, Siewers V, Nielsen J.
Microbial cell factories, 14 (1): 116 (2015).
doi: 10.1186/s12934-015-0305-6

“Directed Evolution of a Far-Red Fluorescent Rhodopsin”
McIsaac RSϕ, Engqvist MKMϕ, Wannier T, Rosenthal AZ, Herwig L, Flytzanis NC, Imasheva ES, Lanyi JK, Balashov SP, Gradinaru V and Arnold FH.
Proceedings of the National Academy of Sciences, 111 (36): 13034-13039 (2015).
doi: 10.1073/pnas.1413987111


“Archaerhodopsin variants with enhanced voltage-sensitive fluorescence in mammalian and Caenorhabditis elegans neurons”
Flytzanis NCϕ, Bedbrook CNϕ, Chiu H, Engqvist MKM, Xiao C, Chan KY, Sternberg PW, Arnold FH, Gradinaru V.
Nature Communications, 5(4894) (2014).
doi: 10.1038/ncomms5894

“Directed Evolution of Gloeobacter violaceus Rhodopsin Spectral Properties”
Engqvist MKM, McIsaac RS, Dollinger P, Flytzanis NC, Abrams M, Schor S and Arnold FH.
Journal of Molecular Biology, 427 (1): 205-220 (2014).
doi: 10.1016/j.jmb.2014.06.015


“D-2-hydroxyglutarate metabolism is linked to photorespiration in the shm1-1 mutant”
Kuhn Aϕ, Engqvist MKMϕ, Jansen EEW, Jakobs C, Weber APM and Maurino VG.
Plant Biology, 15(4): 776-84 (2013).
doi: 10.1111/plb.12020


“Transgenic Introduction of a Glycolate Oxidative Cycle into A. thaliana Chloroplasts Leads to Growth Improvement”
Maier A, Fahnenstich H, von Caemmerer S, Engqvist MKM, Weber APM, Flügge UI and Maurino VG.
Frontiers in Plant Science, 3(February): 1-12 (2012).
doi: 10.3389/fpls.2012.00038

“D-Lactate dehydrogenase as a marker gene allows positive selection of transgenic plants”
Wienstroer Jϕ, Engqvist MKMϕ, Kunz HHϕ, Flügge UI and Maurino VG.
FEBS Letters, 586(1): 36-40 (2012).
doi: 10.1016/j.febslet.2011.11.020


“Plant D-2-hydroxyglutarate dehydrogenase participates in the catabolism of lysine especially during senescence”
Engqvist MKMϕ, Kuhn Aϕ, Wienstroer J, Weber K, Jansen EE, Jakobs C, Weber APM and Maurino VG.
Journal of Biological Chemistry, 286(13): 11382-90 (2011).
doi: 10.1074/jbc.m110.194175


“Two D-2-hydroxyacid dehydrogenases in Arabidopsis thaliana with catalytic capacities to participate in the last reactions of the methylglyoxal and β-oxidation pathways”
Engqvist M, Drincovich MF, Flügge UI and Maurino VG.
Journal of Biological Chemistry, 284(37): 25026-37 (2009).
doi: 10.1074/jbc.m109.021253


“HAG2/MYB76 and HAG3/MYB29 exert a specific and coordinated control on the regulation of aliphatic glucosinolate biosynthesis in Arabidopsis thaliana”
Gigolashvili Tϕ, Engqvist Mϕ, Yatusevich R, Müller C, Flügge UI.
New Phytologist 177 (3), 627-642 160 (2008)
doi: 10.1111/j.1469-8137.2007.02295.x


“Effect of poly (ethylene glycol) on enzymatic hydrolysis and adsorption of cellulase enzymes to pretreated lignocellulose”
Börjesson J, Engqvist M, Sipos B, Tjerneld F.
Enzyme and Microbial Technology 41 (1), 186-195 (2007)
doi: 10.1016/j.enzmictec.2007.01.003

Review articles

“Applications of protein engineering and directed evolution in plant research”
Engqvist MKM, Rabe KS
Plant Physiology, 179(3) (2019).
doi: 10.1104/pp.18.01534

“Biochemical control systems for small molecule damage in plants”
Hüdig M, Schmitz J, Engqvist MKM, VG Maurino
Plant signaling & behavior 13 (5), e1477906 (2018).
doi: 10.1080/15592324.2018.1477906

“Mitochondrial 2-hydroxyglutarate metabolism”
Engqvist MKM, Eßer C, Maier A, Lercher MJ and Maurino VG.
Mitochondrion. 19: 275-281 (2014).
doi: 10.1016/j.mito.2014.02.009

Book chapters

“Metabolic engineering of photorespiration - bypass approaches”
Engqvist MKM, Maurino VG.
In Methods in Molecular Biology: Photorespiration (eds. Fernie AR, Weber A, Bauwe H) 1653:137-155 (2017)
doi: 10.1007/978-1-4939-7225-8_10

“2-Hydroxy Acids in Plant Metabolism”
Maurino VG, Engqvist MKM.
In The Arabidopsis Book, Sep 4, 13:e0182 (2015).
doi: 10.1199/tab.0182


Ambiguous Nucleotide Tool (ANT)
Degenerate codons are used to represent DNA positions that have multiple possible nucleotide alternatives. This is useful for protein engineering and directed evolution, where primers specified with degenerate codons are used as a basis for generating libraries of protein sequences. ANT provides Python code for generating and evaluating degenerate codons for natural and expanded genetic codes.

Manually editing a large number of plasmid files, to annotate them with mutations discovered in the lab or other features, is tedious and error-prone. DNApy provides Python code for DNA and plasmid editing. It allows for batch in silico cloning of an unlimited number of sequences from FASTA files as well as the batch introduction and annotation of mutations.

Making accurate color scales for communicating data in visualizations is critical. In many presentations and publications unbalanced scales are used. A common error is to use color scales which does not have smooth and constant change in lightness, leading to difficulty in interpreting the visualized data. colcol provides Python code to deal with color conversions as well as with generating publication-quality color scales.

Many good plotting libraries exist for Python, but sometimes it is necessary to generate custom vector art visualizations of data. wsvg is a light Python wrapper around the svg (scalable vector graphics) format, enabling scripting of svg files.

Reproducible research
Computational analysis of data in a research setting is often difficult to reproduce due to poor documentation of steps taken and software used. Determining which version of what script was used to process a raw data file to generate publishable results can be challenging. As ever-increasing amounts of data is being generated in biological research it is critical that this problem is addressed and that computational analysis becomes as reproducible as laboratory experiments. The reproducible research repository provides a folder structure and conventions aimed at achieving such reproducibility. Note: This repository was originally created by others and made public here. The Engqvist Lab version has been modified from this source to fit our own research needs.

Reproducible reports
Scientific writing should not be bound to any given proprietary software or file format, especially one which is ill-suited for handling complex texts and large figures. Unfortunately many scientific publishers have built their publication pipelines around such software. An alternative in many journals is to submit LaTeX documents, by this is intimidating to most users. Pandoc offers a great alternative. By writing your documents using markdown Pandoc can convert that text into a whole range of common file formats, including LaTeX, pdf, doc, and others. The reproducible reports repository sets up a folder structure and utilities for using Pandoc to write reports.