Best Poster Awards – EMBO|EMBL Symposium: Systems Genetics: From Genomes to Complex Traits

The first EMBO|EMBL Symposium: Systems Genetics: From Genomes to Complex Traits (29 Sep – 2 Oct 2019) brought together over 150 international researchers to discuss how genetic variation alters molecular mechanisms to cause phenotypic changes amongst individuals, including quantitative traits and human disease. 

From the 77 posters that were presented on-site, 3 were selected as the winners after a shortlist round by popular vote, followed by a selection round by the conference organisers.

Resolving noise-control conflict by gene duplication

Michal Chapal is a PhD student in Naama Barkai’s lab at the Weizmann Institute of Science in Israel. PHOTO: Michal Chapal

Authors: Michal Chapal, Sefi Mintzer, Sagie Brodsky, Miri Carmi, Naama Barkai, Weizmann Institute of Science, Israel

Gene duplication promotes adaptive evolution in two principle ways: allowing one duplicate to evolve a new function and resolving adaptive conflicts by splitting ancestral functions between the duplicates. In an apparent departure from both scenarios, low-expressing transcription factor duplicates commonly regulate similar sets of genes and act in overlapping conditions. To examine for possible benefits of such apparently redundant duplicates, we examined the budding yeast duplicated stress regulators Msn2 and Msn4. We show that Msn2,4 indeed function as one unit, inducing the same set of target genes in overlapping conditions, yet this two-factor composition allows its expression to be both  environmental-responsive and with low-noise, thereby resolving an adaptive conflict that inherently limits expression of single genes. Our study exemplified a new model for evolution by gene duplication whereby duplicates provide adaptive benefit through cooperation, rather than functional divergence: attaining two-factor dynamics with beneficial properties that cannot be achieved by a single gene.

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Deep learning on single-cell ATAC-seq data to decipher enhancer logic

Ibrahim Taskiran is a PhD student in Stein Aerts’ lab at the VIB & KU Leuven Center for Brain & Disease Research. PHOTO: Ibrahim Taskiran

Authors: Ibrahim Ihsan Taskiran, Liesbeth Minnoye, Carmen Bravo Gonzalez-Blas, Sara Aibar Santos, Gert Hulselmans, Valerie Christiaens, Stein Aerts
KU Leuven – VIB, Belgium

Single-cell ATAC-seq provides new opportunities to study gene regulation in heterogeneous cell populations such as complex tissues or dynamic processes. We recently developed a probabilistic topic modeling approach, called cisTopic, to predict regulatory topics and sets of co-accessible enhancers from scATAC-seq data. Here, we apply deep learning approaches to analyze these sets of co-accessible enhancers, with the goal to predict the spatiotemporal pattern of enhancer accessibility directly from the enhancer sequence. We trained different types of Artificial Neural Networks, including a hybrid model that combines Convolutional and Recurrent Neural Networks. By applying this approach to a cohort of melanoma patient samples and Drosophila eye disc, we show that key transcription factors can be identified from the convolutional filters. In addition, we use the trained model to analyze the motif architecture in enhancers, such as motif combinations and relationship to nucleosome preferences. We furthermore exploit network explaining methods to predict the impact of somatic mutations, using publicly available SNP databases and in-house whole genome sequencing of inbred fly lines. Currently, to validate our models we are testing (mutated) synthetic cell state specific enhancers using massively parallel enhancer reporter assays (MPRA). In conclusion, training deep learning models on single-cell epigenomics data sets has multiple applications to understand the underlying enhancer logic and decipher gene expression programs.

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ROADdt: Regulation network remodeling along disease development trajectories

Celine Sin is a Postdoctoral Fellow in Jörg Menche’s Group at the CeMM Research Center for Molecular Medicine, Austria. PHOTO: Celine Sin

Authors: Celine Sin, Jörg Menche
CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Austria

The human body is comprised of over 200 different cell types varying in size, shape, and function. The differentiation and subsequent maintenance of these different phenotypic states are governed by complex gene regulatory networks that dynamically orchestrate the activation and deactivation of genes. Abnormalities in these networks may lead to dysfunctional expression programs, e.g. uncontrolled cell proliferation. In order to understand the conditions resulting in disease, we must understand the underlying gene regulatory networks governing
the gene expression program. As cells move through the differentiation space, the networks that govern gene regulation are remodeled in order to achieve the appropriate gene expression program. While statistical physics and network theory have demonstrated numerous relationships between the structure of networks and the dynamic processes that act on them,
few studies link these mathematically rigorous principles to gene regulatory networks, none at the level of cell-trajectory-states. The overall goal of this project is to understand the fundamental architecture of gene regulatory networks associated with cell differentiation processes in disease. We hypothesize that the gene regulatory networks of different
cell-trajectory-states along the differentiation trajectory – e.g. transitory, branching, or terminal states – are each characterized by distinct structural features. I will present our first steps in this direction, starting from single-cell RNA seq profiles of tumors. Ultimately, we expect that detailed characterization of the gene regulatory networks in these disease processes will reveal basic principles applicable to other diseases and cell  developmental processes.

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Creating is Understanding: Synthetic Biology Masters Complexity – Best Poster Awards

The recent EMBO Workshop: Creating is Understanding: Synthetic Biology Masters Complexity (22 – 25 Sep) covered various themes that are geared toward basic research while being at the forefront of synthetic biology.

110 researchers came together at the EMBL Advanced Training Centre in Heidelberg, Germany for 3,5 days of talks, posters and networking. Here we present the work of 4 scientists who received best poster awards at the conference by popular vote.

Engineering portability of the CcaSR light switch for the control of biofilm formation in Pseudomonas putida

Angeles Hueso-Gil is a PhD researcher at the Spanish National Centre for Biotechnology in Madrid.

Authors: Angeles Hueso-Gil (1), Ákos Nyerges (2), Csaba Pál (2), Belén Calles (1), Victor de Lorenzo (1)

Two of the technical challenges faced by contemporary microbiology involve controlling gene expression using light and regulating bacterial biofilm formation, determined by the intracellular levels of the secondary messenger c-di-GMP. CcaSR system is one of the light switches repeatedly used for transcription induction in Escherichia coli. This two-component system represented a good candidate for its adaptation to Pseudomonas putida. Previous attempts have tried to use this microorganism as chassis for the implementation of new pathways, being biofilm formation an important function to control. To this end, we unified CcaSR components in one single construct and randomly mutagenized their regulatory regions to find a clone with a balanced expression of the system key parts inside P. putida. The combination of this novel mutagenization process with a proper screening, which included a first sorting of the libraries and the later isolation of colonies, lead us to a clone with a much improved induction by green light. The selected variant had a notable capacity in response to green light. Finally, optimized CcaSR was used to control the expression of super-efficient variant of PleD, a diguanylate cyclase of Caulobacter which allowed a tight control of c-di-GMP levels, and therefore, of biofilm production.

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(1) National Centre for Biotechnology, Spain
(2) Biological Research Centre of the Hungarian Academy of Sciences, Hungary

Designer membraneless organelles enable orthogonal translation in eukaryotes

Christopher Reinkemeier is a PhD student at EMBL Heidelberg, JGU Mainz and IMB Mainz, Germany

Christopher Reinkemeier (1,2,3), Gemma Estrada Girona (3), Edward A. Lemke (1,2,3)

Genetic code expansion is a powerful tool to study and control protein function with single-residue precision. It is widely used to e.g. perform labeling for microscopy or to photocontrol proteins. This is achieved by introducing an orthogonal tRNA/synthetase suppressor pair into the host, to recode a stop codon to incorporate a noncanonical amino acid (ncAA) into the nascent chain. This technique is codon-specific, but it cannot select specific mRNAs, so naturally occurring stop codons could be suppressed leading to potential interference with housekeeping translation. Nature avoids cross-talk between cellular processes by confining specific functions into organelles. We aimed to design an organelle dedicated to protein engineering, but as translation is a complex process requiring hundreds of factors to work together, membrane-encapsulation would not be feasible. Inspired by the concept of phase separation we hypothesized that such an organelle could instead be designed membraneless. Phase separation can generate high local concentrations of proteins and RNAs in cells and has recently gained attention owing to its role in the formation of specialized organelles such as nucleoli or stress granules. Despite being membraneless and constantly exchanging with the cytoplasm/nucleoplasm, these organelles still perform complex tasks, such as transcription. We combined phase separating proteins with microtubule motor proteins to generated orthogonally translating organelles in living cells that contain an RNA-targeting system, the stop codon suppression machinery and ribosomes. These large organelles enable site- and mRNA-specific ncAA incorporation, decoding one specific codon exclusively in the mRNA of choice. Our results demonstrate a simple yet effective approach to the generation of semi-synthetic eukaryotic cells containing artificial organelles to harbor two
distinct genetic codes, providing a route towards customized orthogonal translation and protein engineering.

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(1) Johannes Gutenberg University Mainz, Germany
(2) Institute of Molecular Biology, Germany
(3) EMBL Heidelberg, Germany

Metabolic perceptrons for neural computing in biological systems

Paul Soudier is a PhD Student at the French National Institute of Agricultural Research, France

Amir Pandi (1), Mathilde Koch (1), Peter Voyvodic (2), Paul Soudier (1), Jerome Bonnet (2), Manish Kushwaha (1), Jean-Loup Faulon(1)

Synthetic biological circuits are promising tools for developing sophisticated systems for medical, industrial, and environmental applications. So far, circuit implementations commonly rely on gene expression regulation for information processing using digital logic. Here, we present a new approach for biological computation through metabolic circuits designed by computer-aided tools, implemented in both whole-cell and cell-free systems. We first combine metabolic transducers to build an analog adder, a device that sums up the concentrations of multiple input metabolites. Next, we build a weighted adder where the contributions of the different metabolites to the sum can be adjusted. Using a computational model fitted on experimental data, we finally implement two four-input of metabolite combinations by applying model-predicted weights to the metabolic perceptron. The perceptron-mediated neural computing introduced here lays the groundwork for more advanced metabolic circuits for rapid and scalable multiplex sensing.

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(1) French National Institute of Agricultural Research, France
(2) INSERM, France

Programmed uptake of biomacromolecules into protocells

Wiggert Altenburg is a PhD student at the Eindhoven University of Technology, The Netherlands

Wiggert Altenburg, Amy Yewdall, Daan Vervoort, Alex Mason, Jan van Hest

The bottom up recreation of cellular processes into synthetic compartments has, in recent years, emerged as an exciting line of research with which to study biological processes in a controlled environment. However, the interior of a living cell is a difficult milieu to mimic in bottom-up synthetic cells, as it is an environment crowded with high concentrations of many different biomacromolecules. In this work, we describe the development of a powerful new tool to more accurately emulate the cell cytosol in discrete coacervate-based protocells. The coacervate core utilized herein not only provides an inherently crowded and highly charged microenvironment, but has also been chemically modified to interact specifically with recombinantly expressed proteins. Our method leverages the well-established binding of His-tagged proteins to Ni2+-nitrilotriacetic acid, which ensures that macromolecules are taken up in a highly efficient, yet gentle manner, thus preserving biological activity. The straightforward method allowed for both control over the amount taken up and an increased local concentration. Moreover, the engineered uptake of proteins was then employed to study two key aspects: the effect of the Ni-NTA interaction on the diffusivity of incorporated proteins, and the enhancement in activity of an encapsulated two-enzyme cascade. This direct and targeted method of protein uptake into a discrete, membrane bound platform is a significant step forward for synthetic cells, and will enable the engineering of highly complex enzyme and signaling networks with increasingly life-like properties.

Poster currently not available

Eindhoven University of Technology, The Netherlands

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