Conference program

The conference is split into the morning and afternoon parts, with the speakers distributed evenly among the two sections.

Speaker list

The list of confirmed speakers

Molecules section

Reconstituting eukaryotic chromosome replication

Dr. Joseph Yeeles

(1) MRC laboratory for molecular biology, UK

Precise chromosome replication is essential for maintaining genome stability. Replication is carried out by a large, sophisticated and highly regulated molecular machine called the Replisome. Replisome progression is often complicated by the presence of obstacles, such as DNA damage, that can stall or derail the replication machinery. We have recently reconstituted a eukaryotic replisome with purified proteins capable of complete leading-and lagging-strand synthesis in vitro at the in vivo rate. I will present our recent progress using this system, including insights into the mechanism of leading-strand synthesis establishment and the mechanism(s) by which the replisome responds to DNA template damage.

Molecules section

The functional mechanisms of the 26S proteasome

Miglė Kišonaitė and Paula da Fonseca

MRC Laboratory of Molecular Biology

Cell growth, homeostasis, division and death are critically regulated by highly specialised multi-subunit protein complexes. The structural insights of such complexes are essential for understanding their function in cells. Cryo-electron microscopy and single particle analysis are particularly well suited to investigate macromolecules and acquire precise structural information. Today we are witnessing the resolution revolution where structures of very large molecules can be obtained at near-atomic resolution by averaging thousands of electron microscope images [1]. Our work has been focusing on complexes involved in the ubiquitin/proteasome pathway, in particular the 26S proteasome. The 26S proteasome is a 32-subunit complex that plays a key role in the highly regulated and selective degradation of a wide range of proteins. This complicated machinery recognises ubiquitinated substrates that are targeted for degradation, unfolds them and cleaves them into small peptides [2]. In this study, we are particularly interested in the initial step of the recognition of a ubiquitinated substrate. We aim to combine the structural information obtained in different functional states, together with biochemical and biophysical data to determine the detailed functional mechanisms of the substrate recognition by the 26S proteasome.

[1] Kühlbrandt W, Biochemistry. The resolution revolution. Science. 2014 Mar 28;343(6178):1443-4. [2] da Fonseca P, He J, Morris EP, Molecular Model of the Human 26S Proteasome. Molecular Cell. 2012 Apr 13:46, 54–66.

Molecules section

Analysis and assessment of protein 3D structures using interatomic contact areas

Kliment Olechnovič(1), Česlovas Venclovas(1)

(1) Vilnius University, Lithuania

Knowledge about three-dimensional structures of proteins is crucial for understanding processes in living cells. Experimental determination of molecular structures is expensive and not always successful. Therefore, life sciences make use of bioinformatics for predicting protein structures from their genomic sequences. Most current structure prediction methods work in two stages: 1) generating a set of candidate models; 2) selecting the best model. We present a novel method [1] that helps to make better decisions in the second stage. VoroMQA (Voronoi diagram­-based Model Quality Assessment) is a method for the evaluation of predicted protein structures when the native structure is unknown. VoroMQA efficiently combines the idea of knowledge-based statistical potential with the concept of interatomic contact areas derived from the Voronoi tessellation of atomic balls. Interatomic contact areas allow capturing important structural features of proteins better than the traditional distance-based approaches. VoroMQA-based model selection protocol was blindly tested in CASP12 experiment (12th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction) and showed top results (link:, outperforming other methods that were based on the idea of selecting best models from automatic prediction servers using structure quality assessment methods. VoroMQA also played an important role in achieving the best results in protein-protein complex structure modeling experiment CAPRI in 2016 [2].

[1] Olechnovič K, Venclovas Č. VoroMQA: Assessment of protein structure quality using interatomic contact areas. Proteins. 2017 Jun;85(6):1131-1145. [2] Dapkūnas J, Olechnovič K, Venclovas Č. Modeling of protein complexes in CAPRI Round 37 using template-based approach combined with model selection. Proteins. 2017 Sep;doi:10.1002/prot.25378.

Molecules section

Kinesin stepper-motor

Algirdas Toleikis, Nick Carter, Rob Cross

University of Warwick

Kinesin-1 is a processive motor responsible for transporting cargos inside cells over large distances. It can take up to 100 directional steps, each being 8 nm in size. It is known that kinesin-1 can also backstep, particularly at high (hindering) loads, approaching stall force (7pN). However, neither the mechanism of choosing the stepping direction nor the mechanism of backstepping is fully understood. In this work, we are using optical trapping to apply directional force to single kinesins in vitro to study the mechanism of (back)stepping.

Molecules section

Understanding cryptic pocket formation in protein targets by enhanced sampling simulations

V. Oleinikovas(1), G. Saladino(1), B. P. Cossins(3) and F. L. Gervasio(1,2)

(1) Department of Chemistry and (2) Institute of Structural and Molecular Biology, University College London, London WC1E 6BT, United Kingdom (3) UCB Pharma, Slough SL1 3WE, United Kingdom

Over 75% of disease-involved proteins cannot be readily targeted by conventional chemical biology approaches. Cryptic binding pockets, i.e. pockets that transiently form in a folded protein, but are not apparent in the crystal structure of the unliganded apo-form, offer outstanding opportunities to target proteins otherwise deemed ‘undruggable’ and are thus of considerable interest in academia and the pharmaceutical industry. Unfortunately, not only they are notoriously difficult to identify, but also the molecular mechanisms by which they open is still widely debated. Indeed, most of the known cryptic pockets have been found serendipitously, and neither experimental nor computational approaches are very effective in their localization. The aim of the present work, is to fill the knowledge gaps by clarifying the molecular mechanisms underlying the cryptic site formation and then to devise an effective computational approach to systematically detect known and unknown cryptic pockets. To this aim[1] we performed a computational tour-de-force on three systems of pharmaceutical interest with experimentally-validated cryptic pockets, including TEM1 β-lactamase, interleukin-2 (IL2) and Polo-like kinase-1 (PLK1). We ran several μs-long fully solvated atomistic molecular dynamics simulations (MD), massive parallel tempering simulations and a number of parallel-tempering-Metadynamics runs as well as developed and used a Hamiltonian replica exchange-based approach "SWISH" (Sampling Water Interfaces through Scaled Hamiltonians) in combination with fragment-based simulations.

[1]. V. Oleinikovas, G. Saladino, B. P. Cossins and F. L. Gervasio, J. Am. Chem. Soc., 2016, 138 (43), pp 14257–14263, DOI: 10.1021/jacs.6b05425

Molecules section

Hydration indused phase transitions of proteins studied by Calorimetry and Vibrational Spectroscopy

Jekaterina Latynis (1), Gediminas Niaura (1), Justas Barauskas(2), Vitaly Kocherbitov (2)

(1) Vilnius University Life Science Center, Vilnius, Lithuania (2) Biomedical Science, Faculty of Health and Society, Malmö University, Malmö, Sweden

This study was aimed to investigate structural and thermodynamic behavior of cytochrome c (cyt.c) during the hydration by FTIR, Differential Scanning Calorimetry(DSC), Sorption calorimetry and compare it to lysozyme hydration studies[1,2]. We found a correlation between the spectroscopic/thermodynamic data. There was a reversible structural transition (β-sheets/unordered structures) in samples containing 3-14wt% of water with a peak of β-sheets loss in a sample containing 7wt%, where an cyt.c denaturation/melting enthalpy ∆Em(cyt.c) had a minimum value. We observed an increase of α-helices with an inflection point in a sample containing 14-15wt% that correlated with a glass transition(GT) midpoint at isothermal 25°C conditions. The onset and endset of GT correlated with the start and finish of mentioned structural transition (an increase of relative percentage of α-helices). The second conformational transition occured as a loss of relative β-sheets percentage was in a range between 26 and 34-40wt% of water content that correlated with water crystallization reaction that appeared at DSC scans. Sample containing 30wt% was an inflection point of second structural transition which coincided with maximum value of ∆Em(cyt.c). Phase transition for both cyt c and lyz occurred in samples containing comparable water quantity. The onset of a glass transition was at 10(cyt.c)/11(lyz.)wt% of water in samples; the end of a glass transition and the start of an elastic protein phase was at the same water quantity for both proteins: 20wt% of water a system. Finally, a “free water” in protein molecule occurred in the range of 34-39(cyt.c)/38(lyz)wt% of water a water/protein system.

[1] Kocherbitov V, Latynis J, Misiunas A, Barauskas J, Niaura G. Hydration of lysozyme studied by Raman spectroscopy. J Phys Chem B. 2013 May 2;117(17):4981-92 [2] Kocherbitov V, Arnebrant T, Söderman O. Lysozyme−Water Interactions Studied by Sorption Calorimetry. J. Phys. Chem. B, 2004 Nov 3;108 (49):19036–19042

Cells section

Deep learning accelerating our understanding of human intelligence

Dr. Jonas Kubilius

KU Leuven, Belgium, and Massachusetts Institute of Technology (MIT), USA

I will discuss how deep learning is accelerating our understanding of human intelligence. How can we use powerful machine learning techniques to investigate information processing mechanisms in the brain? And how neuroscience can meaningfully inform artificial intelligence research? Focusing on one aspect of perceptual intelligence – human object recognition – I will describe the history and our current efforts to build, evolve, and train brain-like models that account for human behavior in this task and capture neural responses in the primate visual cortex.

Cells section

Role of medial amygdala GABA neurons in aggression control

Aiste Baleisyte (1), Ralf Schneggenburger (2), Olexiy Kochubey (3)

Laboratory of Synaptic Mechanisms, Brain Mind Institute, Ecole Polytechnique Federale de Lausanne (EPFL)

The medial amygdala (MeA) integrates socially relevant information from olfactory and pheromonal sensory inputs, and regulates social behaviors like mating and aggression. The majority (~70%) of neurons in the MeA are GABAergic inhibitory neurons (MeA-GABA neurons). However, the role of genetically defined sub-populations of MeA-GABA neurons in social behavior has not been addressed. We find that 18% and 30% of the MeA-GABA neurons express Somatostatin (SOM) and neuronal nitric oxide synthase (nNOS), respectively. We used in-vivo optogenetic stimulation of SOM+ and nNOS+ neurons in the MeA, and found that this manipulation tends to inhibit ongoing inter-male territorial aggression in the resident-intruder test. Stimulation of pan-GABAergic population of cells in the MeA using VGAT-Cre mouse line revealed similar results. Initial optrode recording of SOM+ MeA neurons in behaving mice showed an increase of SOM+ MeA-GABA neuron spiking towards the end of aggressive bouts, suggesting a “pre-motor” like activity of these neurons in terminating aggression. Using anterograde viral tracing techniques we found putative output synapses of SOM+ neurons in various hypothalamic nuclei, including the ventro-medial hypothalamus (VMH), a region previously identified in aggression control [1]. Axons of nNOS+ MeA-GABA neurons show similar targeting pattern, but nNOS targeted VMH more intensely. Correspondingly, ex-vivo optogenetic stimulation of ChETA+ fibers in VMH after expression of ChETA in a cre-dep. manner in the MeA of SOMcre or nNOScre mice, showed PSCs in many VMH neurons. Thus, our data begins to separately address the role of sub-population of MeA-GABA neurons in aggression control.

[1] Lin D, Boyle MP, Dollar P, Lee H, Lein ES, Perona P, Anderson DJ (2011) Functional identification of an aggression locus in the mouse hypothalamus. Nature 470:221

Cells section

Computational modelling of the self-organization of luminous bacteria

Žilvinas Ledas(1), Romas Baronas(2), Remigijus Šimkus(3)

(1) Vilnius University Faculty of Mathematics and Informatics, Lithuania; (2) Vilnius University Faculty of Mathematics and Informatics, Lithuania; (3) Vilnius University Institute of Biochemistry, Lithuania

Microorganisms and bacteria move toward and away from various chemical gradients [1]. Such directed movement is called chemotaxis and it plays an important role in a wide range of biological processes [2]. Lux gene engineered Escherichia coli become unstable when the density of the population is sufficiently high [3]. We will discuss computational modelling of the spatiotemporal pattern formation in the fluid cultures of luminous E. coli placed in a rounded glass container using the non-linear Keller-Segel equations of chemotaxis with logistic cell growth [4]. Acknowledgement This research was funded by a grant (No. S-MIP-17-98) from the Research Council of Lithuania.

[1] T. C. Williams. Chemotaxis: Types, Clinical Significance, and Mathematical Models. Nova Science, New York, (2011). [2] T. Hillen, K. J. Painter. A users guide to PDE models for chemotaxis. Journal of Mathematical Biology, Vol. 58 (1), (2009), 183–217. [3] R. Šimkus, V. Kirejev, R. Meškienė, R. Meškys, Torus generated by Escherichia coli, Exp. Fluids, 2009, 46, 365–69. [4] R. Baronas, Ž. Ledas, R. Šimkus. Computational modeling of the bacterial self-organization in a rounded container: The effect of dimensionality. Nonlinear Analysis: Modelling and Control, 20(4), 2015, p. 603-620.

Cells section

Cell Polarity in Imposed Migration

Kotryna Vaidžiulytė (1), Kristine Schauer (2), Mathieu Coppey (3)

(1) Laboratoire Physico-Chimie, Institut Curie, CNRS UMR168, PSL Research University, Université Pierre et Marie Curie-Paris 6, FRANCE (2) Laboratoire Physico-Chimie, Institut Curie, CNRS UMR144, PSL Research University, Université Pierre et Marie Curie-Paris 6, FRANCE (3) Laboratoire Physico-Chimie, Institut Curie, CNRS UMR168, PSL Research University, Université Pierre et Marie Curie-Paris 6, FRANCE

Directionally migrating cells need to coordinate multiple signaling pathways in space and time to orchestrate the dynamics of their cytoskeleton and the distribution of their internal components. Yet, it remains unclear how the signaling programs are coupled and to what extent a proper cell polarity is required for directional migration. More specifically, is the orientation of the nucleus-centrosome axis a necessary directional cue? Is a sustained local activation of RhoGTPase signaling sufficient to establish a functional polarized cellular state? Difficulty to answer this rises from the numerous feedbacks in the cell signaling circuitry. Usual genetic perturbations disrupt the system’s functioning point hereby killing the fine spatiotemporal coordination. It has been shown that a stable cell polarity axis is induced by cell adhesion on defined micropatterns of extracellular matrix [1]. By providing a mean to average the distribution of cellular components, this system allowed the quantitative study of the asymmetric distribution of intracellular organelles as a function of cellular polarization [2]. However, this method enforces a static picture of the cell which may differ considerably from the freely migrating situation. We propose a new method to standardize cell shape and migration while keeping the cell free to move. Using a feedback routine based on optogenetic control of RhoGTPase activation, we will constrain the cell morphology and dynamics using signaling instead of adhesion [3], [4]. This assay will allow us to build probabilistic density maps of cellular components, in action, in order to assess the intracellular polarity required to sustain directional migration.

[1] Thery, M., et al. Anisotropy of cell adhesive microenvironment governs cell internal organization and orientation of polarity. Proceedings of the National Academy of Sciences of the United States of America 103, 19771-19776 (2006). [2] Schauer, K., et al. Probabilistic density maps to study global endomembrane organization. Nature methods 7, 560-566 (2010). [3] Toettcher, J.E., Voigt, C.A., Weiner, O.D. & Lim, W.A. The promise of optogenetics in cell biology: interrogating molecular circuits in space and time. Nature methods 8, 35-38 (2011). [4] Valon, L., et al. Predictive Spatiotemporal Manipulation of Signaling Perturbations Using Optogenetics. Biophysical journal 109, 1785-1797 (2015).

Cells section

Effects of manipulating GDNF pathway in human testis: potential mechanism for protection from chemotherapy-induced damage

Gabriele Matilionyte, Rod T Mitchell

Centre for Reproductive Health, The University of Edinburgh, Scotland Centre for Reproductive Health, The University of Edinburgh, Scotland

Advanced development of chemotherapeutic drugs has increased the survival rates of childhood cancer patients up to 80% [1]. However, post-cessation of treatment leaves some male survivors oligospermic or azoospermic, meaning that chances for these patients to father a child in the future are close to nil [2]. Thus, it is essential to understand how spermatogonial cell sub-populations within testis are regulated in the immature human and to determine their role in modulating spermatogonial stem cell (SSC) sensitivity to chemotherapy-induced damage. Protection of testis from adverse effects of chemotherapeutic treatment has not been extensively investigated. Whilst animal studies have provided insights into pathways involved in regulation of SSCs, only limited understanding is available on mechanisms in pre-pubertal human testis. One of the potential targets to be manipulated in order to preserve fertility is glial cell line-derived neurotrophic factor (GDNF) which is known to be a key molecule in regulation of SSC fate. In vitro and in vivo studies have shown that high levels of GDNF present in testicular environment sustain SSC self-renewal whereas gdnf knockout results to accelerated spermatogonial cell differentiation [3]. Moreover, recent study has shown that increased expression of GDNF family receptor α-1 favours the tumour growth by enhancing chemoresistance in mouse model for osteosarcoma [4]. Current project aims to understand the role of GDNF in maintaining the SSC population in human testis, and whether manipulation of GDNF signalling may promote chemoresistance in the germ cell population.

[1] Mariotto AB, Rowland JH, Yabroff KR, Scoppa S, Hachey M, Ries L & Feuer EJ (2009). Long-Term Survivors of Childhood Cancers in the United States. Cancer Epidemiology, Biomarkers & Prevention 18, 1033-1040. [2] Brook PF, Radfort JA, Shalet SM, Joyce AD & Gosden RG (2001). Isolation of germ cells from human testicular tissue for low temperature storage and autotransplantation. Fertility and Sterility 75, 269-274. [3] Meng X, Lindahl M, Hyvonen ME, Parvinen M, de Rooij DG, Hess MW, Raatikainen-Ahokas A, Sainio K, Rauvala H, Lakso M, Pichel JG, Westphal H, Saarma M & Sariola H (2000). Science 287, 1489-1493. [4] Kim M, Jung JY, Choi S, Lee H, Morales LD, Koh JT, Kim SH, Choi YD, Choi C, Slaga TJ, Kim WJ & Kim DJ (2017). GFRA1 promotes cisplatin-induced chemoresistance in osteosarcoma by inducing autophagy. Autophagy 13, 149-168.

Cells section

New cell type discovery by single cell RNA sequencing

Rapolas Žilionis

Institute of Biotechnology, Vilnius University, Vilnius, LT 10257, Lithuania Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA

High-throughput single cell RNA sequencing (scRNAseq) recently emerged as a new tool providing rich and unbiased molecular descriptions of individual cells, and inviting the scientific community to better appreciate the diversity of heterogeneous cellular systems. In my talk I will discuss inDrops, a droplet-based scRNAseq method [1, 2], and share my experience from applying it to have a fresh look at the compositions and homeostasis of the airway epithelium, on the way discovering an intriguing new cell type with potential relevance to cystic fibrosis.

[1] Klein AM, Mazutis L, Akartuna I, Tallapragada N, Veres A, Li V, et al. Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell. 2015;161(5):1187-201. [2] Zilionis R, Nainys J, Veres A, Savova V, Zemmour D, Klein AM, et al. Single-cell barcoding and sequencing using droplet microfluidics. Nat Protoc. 2017;12(1):44-73.

Cells section

Design and enhancement of a novel 1,3-butanediol production pathway in Escherichia coli: from in vitro to in vivo

Rokas Juodeikis (1), Michelle Gradley (2), Martin Warren (1)

(1) University of Kent, UK (2) Zuvasyntha Ltd., UK

R)-1,3-butanediol (1,3-BDO) is a non-natural alcohol, which is used as a nutraceutical as well as in the production of various commodity chemicals and pharmaceuticals [1]. To date, the only source for industrial 1,3-BDO is extraction from crude oil, although the bioproduction of the chemical has been demonstrated via a 3-hydroxybutyryl-CoA, with yields up to 9.05 g/l [2]. A novel pathway, using deoxyribose phosphate aldolase (DERA) to condense two acetaldehyde molecules, has been discovered by ZuvaSyntha Ltd and has been shown to function in vitro [3]. The aim of the project is to develop this metabolic pathway in vivo using the model organism Escherichia coli. Furthermore, based on previous observations, co-aggregation of the enzymes will be carried out in an attempt to improve the efficiency of the pathway [4].

[1] A. Matsuyama, H. Yamamoto, N. Kawada, and Y. Kobayashi (2001). Industrial production of (R)-1,3-butanediol by new biocatalysts. J. Mol. Catal. B: Enzym., 11, 513-521. [2] N. Kataoka, A. S. VangnInline image 1ai, T. Tajima, Y. Nakashimada, and J. Kato (2013). Improvement of (R)-1,3-butanediol production by engineered Escherichia coli. J. Bioscience. Bioengineering., 115, 475-480. [3] Patent: PCT/EP2015/072552 [4] M. J. Lee, I.R. Brown, R. Juodeikis, S. Frank, and M.J. Warren (2016). Employing bacterial microcompartment technology to engineer a shell-free enzyme-aggregate for enhanced 1,2-propanediol production in Escherichia coli. Metab. Eng., 36, 48–56.



Dr. Monika Kavaliauskė (1), Dr. Giedrius Gasiūnas (2)

(1) Director of „CasZyme“ (2) Head of R&D of „CasZyme“

CasZyme  is a start up company, based in Vilnius, Lithuania. Company aims to deliver inventions by novel and top quality research activities in the field of CRISPR based Molecular Tools. CasZyme is developing and characterizing new tools in support of CRISPR-Cas gene editing technology research. One of the founders of CasZyme is Prof. Virginius Siksnys, the pioneer of CRISPR-Cas gene editing research and first to demonstrate that CRISPR-Cas9 can be used to operate precise double strand breaks in DNA, thereby enabling a new era of gene editing.



Rho Nano

Dr. Gediminas Galinis

Head of R&D “Rho Nano"

UAB “Rho nano” (Rho nano) was established in 2016 to develop and commercialize novel nanoparticle production technology and to offer silver nanoparticle products worldwide. Silver nanoparticles are antibacterial, have high electrical conductivity and low melting point enabling applications in textiles, household items, filters medical devices and printed electronics markets. The company develops new methods to produce nanoparticle suspensions and conductive inks using liquid jets in vacuum. Invented innovative nanoparticle production method is environmental and sustainable as it reduces consumption and waste of chemical materials.