Exploring sexual sensory-system evolution using synthetic and systems biology approaches

People involved:
Alvaro Banderas
Ariel Lindner

Keywords: bacterial sex, sensory system evolution, systems biology, synthetic biology

Project description

The existence of populations with exactly two sexes is an open problem in evolutionary biology. Why not three sexes? Or even better, why not one? Although exceptions exist, two-sex systems are the overwhelming majority. The diversity of sex determination systems only makes their tendency to produce binary sexual populations more mysterious, but at the same time suggests that general principles govern this naturally converging pattern. The study of binary sexual populations has been traditionally reserved for animal systems. However, it has been acknowledged that in order to understand its origins and general principles, asymmetries in simple unicellular systems must be understood. In this project we study the evolution of asymmetrical sexual populations by using a synthetic biology approach that allows the analysis to be independent from the details of specific organisms. By studying natural conjugation and engineering synthetic sexual systems in bacteria, we hope to build experimental models for the evolution of the sexes.

This project is part of the LabEx – Who am I? Initiative 


Beyond networks: the evolution of dynamic regulatory systems

People involved: Johannes Jaeger

Keywords: process thinking, evolutionary systems biology, organicism,
complex adaptive system, dynamical systems theory

Project Description

I am writing a book on evolutionary systems biology from an organismal,
dynamical systems perspective. It is based on the fundamental notion that
evolutionary dynamics arise from the struggle for survival of goal-oriented
organismal agents. In this radical view, organisms and their perceived
environments co-generate each other. The notion of organismal agency is
based on the organizationally closed but thermodynamically open structure
of living systems. Organismal agents are paradigm examples of complex
adaptive systems. I combine empirical, mathematical, and conceptual
approaches to approach this broad and complicated topic. I start from a
processual ontological perspective, examining the fundamental nature of
change and the patterned dynamics that constitute a system. The book then
develops a graphical and intuitive introduction to dynamical systems, based
on the notion that flow (a generalized mapping through time) is
fundamental, while abstract notions such as instantaneous states or
integral paths through time are derived. It presents a number of examples,
where dynamical systems theory in general, and the geometrical analysis of
configuration space in particular, have been successfully applied to
problems in organismic development, ecology, and evolution. It then goes on
to examine the limits of dynamical systems theory, the validity of
steady-state assumptions, the need for non-autonomous systems, and the
difficulties in integrating organizational closure into the formalism. It
discusses radical notions of organism-environment co-evolution, based on
the idea that living beings are not passive sufferers of evolutionary
processes, but actively engage in autonomous exploratory and adaptive
activities. Such an agent-based view leads to a tight interdependence of a
system and its configuration space. I am developing conceptual foundations
for new mathematical formalisms able to deal with this commingling, while
still remaining amenable to (numerical) analysis that enables novel
causal-mechanistic insights into organisms as autonomous agents and their

The book is aimed at an interdisciplinary audience with a wide variety of
intellectual backgrounds. My aim is to make the reader familiar with the
conceptual problems of agent-based evolution without presupposing an
advanced level of technical mathematical skills. The book is based on a
masterclass at the University of Vienna with 14 lectures, each one
providing one of the chapters. The aim of my six-month stay at the CRI is
to work on the book, while turning its content into a massive open online
course (MOOC) with the help of the infrastructure and the multi-media teams
at the CRI.

A minimal mold approach to shape engineering

People involved: Jonathan Grizou

Keywords: shape engineering, automating science

Project Description

A minimal mold could be defined as the minimal set of constraints that can bias a physical system into expressing desirable properties. In the case of shape engineering, we can harvest existing growth mechanisms of known organisms and aim at finding the minimal set of environmental constraints that can lead the system to adopt a desired physical shape. Such constraints can include physical constraints (walls, surface properties), chemical inhibitors and exhibitors, and conditions (temperature, humidity, light). 

This project aims at developing a proof of concept of the minimal mold approach. Because the set of variables is likely to be large and the system of study not fully understood, the search of the minimal mold would be driven by a trial-and-error process using automation and machine learning. Two important challenges will have to be solved:

  • The first challenge will be to identify a physical system well suited for the study (e.g. bacteria cellulose, chemical gardens, …). It will need to be easily observable (e.g. 2D via a webcam), have a relatively quick growth (e.g 1 day), and be automatable (easy to prepare, observe and clean). 
  • The second challenge will be to define the set of environmental variables that are both susceptible to bias the system’s growth and well suited for optimization via machine learning algorithms.

This project also aims to explore if we can devise machines that can help us generate specific engineering goals without the prerequisite to understand the inner working of a system. Hence, the desired outcome would be a compelling visual demonstration of the evolution of the shape-mold pairs created on a system whose inner workings are yet mostly unknown.

Synthetic FlyLab – Synthetic gene regulatory networks to investigate animal development.

Synthetic FlyLab is currently recruiting PhD students! All information available here.

Keywords: synthetic biology, Drosophila, transcription factors, genetic computation

People involved: Radoslaw Ejsmont

Project description:

During animal development, the different types of cells acquire their identities in a multistep process known as differentiation. Differentiation is governed by a special class of proteins, called transcription factors. Unlike typical proteins, transcription factors have the ability to regulate the expression of genes, changing the amount of RNA and eventually the amount of protein produced from those genes. To do so, they attach to a DNA binding domain, segment of the DNA in the vicinity of the target gene. The identity of the key transcription factors that determine the outcome of cell differentiation is already known. However, we do not understand how different transcription factors interact to form complex gene regulatory networks in order to achieve a precise developmental program. Several quantitative approaches have been developed to address these questions, including single cell RNA sequencing, in situ RNA sequencing and quantitative imaging of gene expression patterns using fluorescent reporters. Combination of these techniques finally allows researchers to get quantitative view of gene expression changes in every cell as it progresses through differentiation. This information can be in turn used to create accurate computer models of gene regulatory networks. However, the models should be verified, ideally by recreating and studying gene regulatory networks in vivo, during animal development, which is the goal of this project.

Our team will develop a comprehensive set of synthetic biology tools to study and recreate gene regulatory networks in vivo, using Drosophila, a well-established model organism for studying animal development. To do so, we will combine previously known activation and repression binding domains with engineered ones to create synthetic transcription factors capable of precise control of a target gene expression levels. Our synthetic biology toolkit development will be divided in two sub-projects: (1) recreateing gene regulatory motifs that commonly occur in developmental gene regulatory networks and creating genetic computation units that perform basic logical binary operations; (2) development of efficient methods to screen for groups of candidate target genes that are essential for the function of gene regulatory networks. In combination, these tools will enable researchers to bridge the gap between quantitative biology, that provides gene expression data, systems biology that aims to establish accurate models of gene regulatory network and synthetic biology that will be used to test these models. Data from the synthetic gene regulatory networks can also be used as the baseline, a reliable empirical dataset that can improve existing computational methods for network modeling. Finally, building on the long history of fruit fly in science education, we will use our synthetic gene regulatory networks to control visible and quantitative phenotypes, thus creating new tools for teaching the basics of both genetics and synthetic biology.

Synthetic Biology for Drug Discovery at the  Intersection of Teaching and Open Research

People involved: Jake Wintermute, Ariel Lindner, Nadine Bongaerts
Keywords: Tuberculosis, antibiotics, drug discovery, synthetic biology, citizen science
Project Description:
The need to discover new antibiotics is widely acknowledged. Commercial biotech companies, once leaders, are leaving the field as technically difficult and unprofitable. Public efforts must therefore take up the responsibility and open-science collaborations must be scaled up to match the global challenge. Fortunately, students and citizen scientists are eager to get involved, motivated by the potential to do good as they learn.
This project is about a new way to discover antibiotics and other medicines. We will take a safe, easy-to-grow lab bacterium and genetically modify it to express essential genes from a dangerous, hard-to-grow pathogen. The modified bacterium can then be used as a proxy to test for drugs that may kill the dangerous pathogen. Because there are many different genes to replace, and many different drugs to test, the technique could potentially scale to involve hundreds of labs and citizen scientists around the world.
This conceptually simple approach has only recently become possible due to advances in the field of synthetic biology. Next-generation inducible promoters and rationally designed expression cassettes allow gene dosage to be precisely controlled. Cheap DNA synthesis allows many designs to be tested in parallel, accelerating the design cycle. This project will challenge our ability to move genes between organisms in ways that are elegant, precise and non-perturbative.
Beyond our scientific goals, we will seek to activate, motivate and empower collaborators of all kinds. The work will seek to answer two questions at the intersection of science, eductation and human well-being.
First: How can we include the global public in biological research that is fundamentally hands-on? While lectures, quizzes and textbooks can be successfully communicated with digital media alone, real research requires free-form interaction and play. How can we provide an interactive experience in ways that scale?
Second: How can we align biotechnology to better serve the public good and earn the public trust? Drug development, as it is traditionally practiced by Big Pharma, is widely condemned as greedy and unaccountable. Synthetic biology, the technology of GMOs, is seen by many as unnatural and dangerous. When the two subjects are combined, the controversies multiply. We will need to abandon most of the established models and rebuild a process that is open, responsible, and inclusive.