The recent discovery of 7-deazapurine bases in bacterial and bacteriophage DNA revealed an unexpected interplay between RNA and DNA modification pathways. In phages, these hypermodified bases could play major roles in pathogen-host interactions, DNA replication, DNA-packaging into capsids, gene expression and bacteriophage evolution. Using a combination of genetic, biochemical and sequencing approaches, our objectives are to discover i) how widespread is this phenomenon, ii) the exact pathway(s) leading to the incorporation of these alternative bases into DNA, iii) the “raison d’être” for these modified bases, and iv) if this phenomenon arose as an offensive or as a defensive tool.
To characterize the distribution of 7-deazapurine bases in bacteriophages DNA, we will use several approaches including comparative genomics, mass-spectrometry analysis of modified bases, high-throughput sequencing of restriction endonuclease resistant environmental virome samples, and genome sequencing of phages infecting a wide range of bacterial hosts. This will generate a collection of diverse, sequenced and partially characterized phages that will be made publicly available via deposition in the Félix d’Hérelle Reference Center for Bacterial Viruses. Biochemical, molecular biology and genetic studies will be performed on phages harboring a variety 7-deazapurine variants to elucidate these novel DNA modification pathways. We will also study the role(s) played by the DNA modifications in phage biology, with a particular emphasis on understanding their potential role in overcoming host defences or in facilitating phage-mediated destruction of unmodified host DNA. In addition to classical biochemical, genetic and omics methods, third generation sequencing (PacBio and Nanopore) technologies will be exploited. These can already detect simple DNA modifications, like methylation, but we will combine machine learning with the sequencing of phage DNA molecules containing specific 7-deazapurines to expand the range of detectable DNA modifications. Although the scope of this project is limited to deciphering the role of 7-deazapurines in bacteriophage DNA, our results could spark developments of new genome editing tools and increased knowledge on gene regulation and epigenetics that may some day change paradigms in human health.

Proteins in the cell can undergo liquid-liquid phase separation (LLPS), forming liquid droplets - the so-called “non-membranous organelles”. The Michnick group has shown that protein liquid droplets generate work to drive membrane invagination in clathrin-mediated endocytosis. I propose an entirely new role for protein liquid droplets in membrane biology: protein transmembrane transport. My studies will focus on exploring a molecular-level mechanism of protein import from the cytosol to the peroxisome lumen, a mysterious process that occurs without the need of proteins being unfolded. Although this process is crucial to peroxisome biogenesis, its mechanisms remain unknown, due to lack of evidence of detectible transmembrane channels in these organelles. The Michnick group has evidence that two of the proteins involved in peroxisome protein translocation (Pex5 and Pex13) have both transmembrane domains and sequences that favor LLPS. My hypothesis is that these proteins form liquid droplets inside the peroxisome membrane (i.e. between the lipid bilayer leaflets), which would act as a conduit for transmembrane protein transport. After being recognized by a C-terminal peroxisome-targeting sequence, the cargo proteins could then dissolve in the droplet and emerge on the other side of the membrane. My studies will employ the budding yeast S. cerevisiae and will mainly use genetic manipulation with super-resolution and electron micrographic methods to characterize liquid droplets. Further spectroscopic and biophysical methods (e.g. fluorescence recovery after photobleaching, FRAP) will be used to assess protein dynamics inside the droplets and transmembrane protein transport.

Enzymes catalyze molecular transformations in living systems while being pushed and squeezed by other biomacromolecules. This molecular crowding generates excluded volume effects that result in large quantitative consequences on the rates and the equilibria of enzymatic activity by molecular mechanisms that are not yet fully elucidated. To recreate these features, we propose packing tens to hundreds of enzymes within bacteriophage capsids to create nanoreactors (NRs). Our nanoreactors allow control over packing density, protein environment, and boundaries at the nanoscale. Regulation of these conditions is key for understanding in vivo enzyme behaviour, and facilitating metabolic engineering efforts. We will focus on the mevalonate (MVA) isoprenoid pathway, which, despite demanding enzymatic cascade reactions, is widely used for production of industrially useful biochemicals. Limitations may be related to the lack of proximity between partner enzymes, unfavourable interactions under molecular crowding conditions, and/or unfavourable molecular ratios between cascade enzymes. Here we pursue an integrated study to produce materials where MVA enzyme packing and stoichiometry are controlled to mimic the complexity of the intracellular environment. The kinetics of enzymes within NRs will be measured using both ensemble and single-molecule techniques. The enzymatic activity of single nanoreactors will be monitored using a combination of atomic force and fluorescence microscopies, which will allow the in situ study and manipulation of single NRs in real time to provide individualized details not accessible with averaging ensemble approaches. These studies will be supported by multiscale modelling of the crowded enzyme environment. Our experiments will reveal the optimum biophysical conditions for maximizing metabolic flux in the MVA pathway. Further, designed NRs will be assembled and assessed within living cells. Our project has both fundamental and applied aims. First, to understand how crowding affects enzymes at the nanoscale, including metabolite diffusion and protein conformational changes. Second, to improve the biosynthesis of isoprenoids in biological and industrial systems.

Epithelial collective cell migration (CCM) is important in biological processes such as organ development, tissue maintenance and tissue repair. CCM usually occurs on curved surfaces such as that found in blood vessel walls and intestinal villi. However, current CCM research are still conducted on flat surfaces. This is due to lack of techniques to fabricate tubular and spherical microstructures resembling that of organs as well as difficulty in observing and measuring the collective dynamic behaviour of cells on these surfaces. Nevertheless, recent studies are beginning to show that cells do behave differently on curved surfaces. However, these studies were mainly focused on single cells, as such, there is limited insight into CCM which involves complex interactions among multiple cells.
Here, we claim that curved surfaces can significantly influence CCM. As such, we propose to systematically study CCM on such surfaces to better understand their underlying mechanisms. Our project will combine distinct but complementary scientific expertises coming from biology, biophysics and engineering. We aim to: 1) Develop novel techniques in fabricating different, well-defined curved geometries such as tubular and spherical surfaces with nano-patterns; 2) Identify biomolecules and proteins involved in CCM on curved surfaces; 3) Develop computational models to perform 3D imaging and analysis so as to better monitor and measure complex tissue dynamics; and 4) Develop a universal theory to better explain and unify experimental observations.
Together, the unique combination of these different approaches will enable us to better understand the fundamental mechanisms and impact of surface curvature on cell behaviour and tissue organization. These will shed light on related biological functions such as in organ development and tissue repair, as well as contributing towards better tissue engineering or regenerative medicine applications.

In mammalian development, a zygote gives rise to three germ layers and ultimately hundreds of cell types. How a single genome drives the cell fate decisions underlying development remains one of the most intriguing questions in biology. Extensive work over recent decades has identified some 'master regulator' transcription factors (TFs) that specify certain lineages upon expression, e.g. MYOD for muscles. However, for many lineages the TFs and regulatory regions governing cell type specification remain in the dark. In addition, the sequence of events that leads to open and TF-bound chromatin at developmental enhancers is unknown. These cell fate decisions inherently occur in heterogeneous cell populations, making them difficult to study with bulk techniques. The ability to simultaneously measure changes in chromatin accessibility and gene expression in each of many single cells, coupled to cell lineage information, would provide unprecedented insights into mammalian development. Here I propose to develop and apply such single-cell ‘co-assays’ using mouse embryoid bodies (EBs) as a model system. This will allow me to identify the TFs and regulatory regions involved in early mammalian lineage specification. I will then genetically perturb candidate genes and characterize the effects on lineage establishment. In addition I propose a systematic screen to identify lineage-specifying TFs that serve as ‘pioneer factors’, capable of accessing binding sites in previously closed chromatin. The approach developed in this easily accessible and perturbable system will provide unique insights into intricate biological processes in the future, from in vivo mouse development to disease.

The primary sequence of mRNA transcripts contains essential regulatory information in the form of internal chemical adducts, coined the epitranscriptome. Groundbreaking studies of N6-methyladenosine (m6A), by us and others, revealed that this abundant mRNA modification participates in many aspects of the mRNA life cycle to affect cellular, developmental and disease processes. It does so primarily through recruitment of specific binding proteins that channel modified transcripts to various processing pathways and fates. I recently identified a new mRNA modification, N1-methyladenosine (m1A), which occurs on thousands of human and mouse transcripts. It is strongly enriched at the 5’UTR and positively correlates with translation. These distinct features, together with its evolutionary conservation and dynamic nature, suggest a fundamental role in gene expression. The objective of this proposal is to establish the function of m1A in mRNA metabolism, focusing on 5’UTR and translation, and delineate the mechanisms through which it is executed. Aim 1 will systematically identify m1A-binding proteins that will be characterized to expose pathways controlling methylated transcripts. Aim 2 will functionally interrogate the effect of individual 5’UTR m1A sites on translational output in vitro and in vivo (now made possible by method advancement in my lab allowing robust mapping of m1A with single-base precision). Aim 3 will combine results of Aim 1 and 2 to mechanistically dissect the combination of factors and sequence features required for translation initiation. This study is expected to expose a new and central player in translation regulation affecting thousands of genes.

As intracellular, obligate parasites viruses rely on a diversity of strategies to survive. Some, like most RNA viruses, cause acute “hit-and-run” infections and require large susceptible host populations. Others, mostly DNA viruses, persistently infect their hosts. Morbilliviruses, like measles virus (MV) and canine distemper virus are examples of RNA viruses that can cause persistent infections. The exceptional circumstances which converge to drive RNA virus persistence remain unclear, since these viruses need to replicate continually in vivo. Bats are evolutionary and ecologically unique mammals standing out in their ability to tolerate viral infections. We recently showed that bats host major mammalian paramyxoviruses and described an ancient morbillivirus in vampire bats. This discovery provides a unique opportunity to explore RNA virus persistence in an important reservoir host that has high rates of contact with humans and domestic animals through its blood feeding habits. The primary objective of the proposed research is to unravel fundamental mechanisms that govern morbillivirus persistence and understand the consequences for immunity and infection. We hypothesize that within-host persistence in canonical morbilliviruses is a vestigial relic of a more common strategy that evolved in bats. Research activities comprise a multidisciplinary program involving investigations of natural and experimental infection of bats, reverse genetics to resurrect viruses from infectious clones, comparative studies of canonical morbilliviruses and hosts together with investigation of pathobiology and immunity underpinned by mathematical modeling. Existing materials, a unique field network for long-term monitoring vampire bats, novel approaches and critical insights from systematic field and laboratory studies make this project both exciting and feasible. This study represents an unusual integration of approaches and ideas from disease ecology, evolutionary biology and synthetic biology. We expect this fusion to resolve fundamental knowledge gaps in our understanding of how RNA viruses persist in hosts; a critical component for the understanding of rare disease manifestations, the consequences of viral persistence on the host immune system and for identifying patterns in risk of virus transmission between species.

Cells achieve reproducible outputs while relying on intrinsically stochastic molecular processes. In plants, cell division orientation is accurately predicted before mitosis by a microtubular ring, the preprophase band (PPB), through an unknown mechanism. Using high-throughput microscopy, quantitative image analysis, biomechanics and stochastic modeling, we will investigate how the stochasticity of microtubule (MT) self-organization is used, or filtered out, during PPB formation to sense temporal, geometric and mechanical cues in order to generate a robust placement of cell division planes. In short, we will test whether the PPB acts as a macromolecular mechanosensor. Using statistical mechanics such as Monte Carlo, event-based modeling and mean-field theory, we will assess how stochasticity leads to distinct dynamical states for MT arrays. We will develop biophysical models of dynamic MTs in 3D cells to explore how stochastic MTs self-organize into PPBs and how spatiotemporal cues modulate that process. Using the Arabidopsis shoot apical meristem, we will identify correlations between MT array dynamics, PPB behavior, cell shape, growth and mechanics, cell cycle progression, and cell division plane from statistically representative sample involving hundreds of dividing cells. To challenge the robustness of PPB and cell division in vivo and in silico, we will globally and locally increase variability in these cell parameters with mutants (MT dynamics, wall mechanics, cell cycle, mechanotransduction), inducible lines, mosaics, and micromechanical perturbations. Last, we will unravel the molecular mechanism processing molecular stochasticity to channel cell divisions: we will investigate how the TTP (TON1-TRM-PP2A) complex, a key regulator of PPB formation in connection with the cell cycle, contributes to generate reproducible divisions by monitoring MT self-organization, integrating geometric, mechanical and temporal cues. Implications of this project go beyond cell division robustness: while many cellular pathways are adapted to respond to rapid and discontinuous changes, we expect here to unravel mechanisms managing slow and continuous signals, like shape, growth or tissue-stress. We will also gain insight into the mathematical properties of stochastic extended objects like microtubules, and we will propose a mechanism for cells to perceive directional cues.

Protecting genome integrity from environmental stresses is essential for the stable propagation of genetic information from stem cells to their daughters. The most important significance of this work is to add to our basic knowledge of how some cell types, especially neural stem cells, are able to cope with ionising radiation damage better than other cells. The two main aims of this project are to identify the cell-autonomous mechanism of radiation resistance in neuroblasts and to determine the non-cell autonomous role of the stem cell niche in neuroblast resistance. To pursue both aims, I will use a combination of confocal microscopy with molecular markers, cell-type specific genetic manipulations, genetic screens and in vitro stem cell cultures. Using the power of fruit fly genetics to get at some of the underlying mechanisms for neural stem cell radiation resistance may also help to provide us with tools for manipulating the resistance process in many different cell types. The findings of this project will have long-term implications for improving our understanding of how stem cells react to challenging environments and the inputs they receive from their niche.

Ribonucleoprotein (RNP) granules are "membraneless organelles" found in eukaryotic cells. Common to RNP granules is enrichment of RNA-binding proteins harboring intrinsically disordered domains of low sequence complexity (LC) that may self interact, stabilizing granules via liquid-liquid phase separation (LLPS). Importantly, several LC domains of stress granule (SG) proteins are aggregation-prone and associated with inclusions observed in many neurodegenerative diseases. Although the constituent proteins and RNA are being enumerated by mass spectroscopy and sequencing approaches, and the ~100 nm-scale features are being resolved by fluorescence microscopy techniques with improving resolution, a fundamental conformational/physical-chemical understanding of structures and protein-protein interactions stabilizing SGs remains to be directly interrogated. Our goal is to observe with, residue-by-residue detail, the protein-protein interactions and structural changes caused by disease-causing missense mutations in human SGs both in vitro and in cells. Using the well-studied protein FUS to benchmark our spectroscopic tools and the SG marker and nucleator TIA-1 as a focal point, we will provide the first analysis of protein secondary structures and stabilizing interactions in granules. We will apply in-cell vibrational and Förster resonance energy transfer (FRET) imaging combined with NMR spectroscopy to determine the molecular details of LC domain structure in LLPS assemblies in vitro and SGs in cells. By examining disease-associated variants known to form intracellular aggregates or impair SG dynamics, we will probe the underlying physico-chemical protein changes underlying disease-associated SG biophysical changes. Our novel molecular toolbox and experimental protocols to probe protein structure in cellular (and in vitro) SGs will be immediately applicable to other RNP granules and phase separated structures and their disease-associated changes.

Muscles are producing the active forces that enable all our voluntary body movements. The cellular components of muscle are called muscle fibers and are very large cells that can be several centimeters in length in humans. Inside all muscle cells are millions of tiny molecular machines, called sarcomeres that produce the active forces of muscles. These sarcomeres are arrayed in highly regular long chains called myofibrils that span from one muscle end to the other. This arrangement ensures that the force produced by the myofibrils is transmitted to the connected tendons and bones at the muscles ends. The highly regular periodic organization of the myofibrils results in the cross-striated appearance of skeletal muscles under the microscope.
We assembled an international team of researchers from France, USA and Germany to study how myofibrils are built during muscle development. For this we combine two different experimental model systems, the fruit fly Drosophila muscles and human muscle cells generated in vitro from stem cells, together with mathematical modeling of myofibril assembly. Our starting hypothesis is that mechanical forces, which are generated early during muscle development, are an important factor for the polymerization of myofibrils. We will test this hypothesis in fly as well as in human muscles produced in vitro by following the localization of sarcomeric protein components with high-resolution microscopy techniques. We will measure when a sarcomeric protein pattern can be first detected and how this pattern is refined. These data will be used to generate a computer model that can produce periodic sarcomere-like structures that are linked together from homogenous components. We will further measure the strength of mechanical forces present during myofibril formation in fly muscles in vivo and in human muscles in culture. Finally, we aim to modify these forces and to observe the effect of these manipulations on the developing muscles and myofibrils. These data will be used to produce a refined computer model of myofibrillogenesis. Together, our research should lead to a better understanding of how the contractile apparatus of human muscle is built, which could eventually be helpful to treat muscle injuries or aged dependent myopathies.

Organisms must innovate to survive. While adaptation often occurs via mutations in existing proteins or through protein domain shuffling, evolution sometimes must invent functional proteins de novo. Such proteins can arise when organisms acquire the ability to express a short open reading frame encoding a peptide of benefit. Although nearly a third of the genes in many genomes are predicted to have emerged de novo, the mechanisms and constraints governing gene birth remain mostly elusive. During my post-doctoral studies, I will use the molecular, biochemical, and next-generation sequencing-based approaches that are fully accessible in the Laub lab to study how genes emerge during evolution and become integrated into cellular processes. I will develop an approach that explores the link between environmental challenges, existing cellular systems, and de novo gene birth – a largely uncharted area. Specifically, I will (i) screen for beneficial and deleterious randomized protein sequences under various conditions, (ii) characterize those sequences to reveal the molecular mechanisms behind their cellular effects, and (iii) generate models that identify and predict the potential functions of natural de novo genes. This project will provide insight into how cellular innovation arises and how the existing complexities of the cell shape such innovation.

Neuronal activity consists of electrical transients on the millisecond timescale. Recently developed genetically encoded voltage indicators (GEVIs) have potential to record optically those transients in thousands of neurons simultaneously. Despite great efforts and improvements on the GEVIs, many technical challenges must be overcome for GEVIs to being used in large-scale recordings in live animals. Here, we propose to develop and implement new imaging modalities to enable recordings of voltage dynamics from neuronal networks in layer 2/3 of the mouse cerebral cortex in vivo. As a voltage indicator, we will use a recently developed Archaerhodopsin mutant, called 'NovArch', offering optical sectioning by nonlinear activation. We will use protein engineering to further improve trafficking of NovArch to minimize background fluorescence, and we will co-express it with an actuator to allow for simultaneous optical stimulation. We also plan to develop a microscope specifically optimized for voltage imaging in vivo. It will contain adaptive optical elements to direct optical excitation to the two-dimensional cell membranes where the GEVIs reside, thereby minimizing illumination of non-signal-bearing regions of the sample. This approach will provide high signal levels, while minimizing light scattering and photodamage. We will use this novel microscope to map neural activity in cortical sensory circuits under conditions of sensory stimulation in vivo. The recordings will probe the precise activity levels, sub-threshold voltage dynamics, and intercellular correlations in activity of genetically defined neurons. These data will aid in constraining models of cortical function.

Microtubules form the basic structure, and transport systems in cells, responsible for fundamental processes including cell division, and hence are important drug targets for diseases including cancer, with common taxane-based drugs having them as their biological target of action. Broadly, one of the mysteries of cell biology is the basic set of properties involved in the seed and growth of microtubules and the processes underlying how these systems are initiated. New avenues for controlling cell development and division, possibly related to anticancer treatments will come with a fundamental understanding of the basic mechanisms that lead to unusual switching behavior – dynamic instability. After decades of studies, both in cells and in reconstituted systems there are many open questions about this fascinating behavior. The major bottleneck in exploring microtubules is that the process of seeding is short-lived and the molecular species are structurally very small making standard microscopy observations very difficult, especially for capturing dynamics. In situ liquid cell transmission electron microscopy (LCTEM) has the potential to solve this crucial problem. To enable these kinds of experiments, the microtubule growth, and concentration need to be optimized for confinement within the liquid-cell. Imaging conditions need to be optimized to maximize contrast (as biological systems produce very low contrast under electron beam). We contend that LCTEM experiments replicating naturally occurring nucleation, growth, shrinkage, and re-growth process of microtubules and quantitative image analysis would offer us unique insights into their formation and reorganization.

Perceiving and interpreting our sensory environment feels subjectively effortless, yet, it is one of the computationally most challenging tasks the brain needs to solve. Critically, our brain constantly fuses current sensory input with expectations derived from prior experience in order to be able to reliably interpret our environment in spite of ever-changing conditions, such as lighting, pose, or configuration, making every single experience unique. That prior expectations are constantly shaping our percepts has been well known for over a century from behavioral studies, but how neural circuits in sensory areas of the brain achieve this sensory-prior fusion has remained largely unknown. Progress in several research fields make it possible now to address the neural bases of sensory-prior fusion: novel recording techniques provide an unprecedented opportunity to track the activity of large populations of neurons over extended periods of time; advances in artificial intelligence and machine learning provide powerful new tools to analyse complex data; and advances in computational theories allow us to formulate experimentally testable hypotheses and compare their predictions to data. These techniques are now being used to great effect in sensory neuroscience, but almost exclusively to characterise how sensory input alone impacts neural responses along different stages of the visual processing system of the brain. Our project aims to bring these advances to bear on understanding the effects of prior expectations on neural responses, and their fusion with sensory information. We will rely on complementary approaches that provide insights into different aspects of sensory-prior fusion: experts in mouse experiments and monkey experiments will train complex tasks and record from brain areas that contribute to sensory-prior fusion, while experts in machine learning-based data analysis and computational neuroscience will develop cutting-edge analysis techniques and models to guide experiments and interpret data in a formal theoretical framework. Our project will thus help us understand how a brain that is composed of unreliable components and prone to a variety of perceptual distortions and illusions can efficiently process rapidly changing, cluttered, and noisy scenes to achieve feats such as driving us home safely in busy traffic.

Understanding how out of single cells functional tissues and organs develop is a major challenge of biology. Recent progress allows us to grow organ-like cell assemblies (organoids) from stem cells in vitro. Organoids offer great potential for studying diseases and development. However, in many cases we do not yet understand how these complex tissues emerge out of progenitor stem cells. A common feature in the initial growth phase of many organoid systems is the formation of a polarized epithelial cyst with a single or multiple internal apical lumen. This initial transition into an epithelial cyst establishes a tissue template that on the one hand enables maintenance of progenitor/stem cells (niche) and on the other hand guides the patterning of differentiated cells into a functional tissue. Our aim is to understand how the interplay between proliferation (cell divisions), polarization (epithelial transition) and differentiation (patterning) leads to self-organization of this epithelial progenitor template and how this structure facilitates correct patterning into functional organoids. To this end, we will systematically control and characterize the early growth phase of two organoid systems (pancreatic and neural tube) using microfabrication and micro-patterning approaches. We will quantify evolution of cell shapes, adhesion and cortical forces, apical-basal polarization and differentiation as a function of initial cell contact patterns. This approach will provide the means to find rules how local cell interactions (cell-cell, cell-matrix, cell-lumen) are connected to tissue growth and differentiation. We will then test sufficiency of the hypothetical rules to generate the observed organoid structures using an in silico mechano-chemical model. Taken together, by dissecting the early growth phase of two organoid systems, we aim to uncover the common rules on how progenitors establish a polarized epithelial template, and how this template is then differentially used to generate organ specific differentiation patterns.

Unlike humans, some multicellular organisms are able to regenerate their organs after severe injuries. Understanding how regeneration properties emerge from fundamental biological processes such as gene expression and stem cell differentiation is of utmost importance for basic science and regenerative medicine. Nevertheless, little is known on the mechanisms underlying the initiation, maintenance and control of regeneration. Therefore, many fundamental biological questions remain unanswered, i.e.: (i) how do stem cells migrate, divide and differentiate? and (ii) how do regenerating organs control their size and orientation? Thanks to their astonishing regenerative properties and simple body plan, planarians form an ideal model system for the study of regeneration. However, due to their opaque tissues, time-lapse microscopy of living planarians has so far been impossible and a comprehensive understanding of the mechanisms underlying their regeneration is still lacking. In the proposed research, I aim to use an interdisciplinary approach to characterize, for the first time, the single-cell dynamics of planarian regeneration. I will use light sheet microscopy, an ideal technique for live imaging of large specimens, and design microfluidic devices to keep the organism at physiological conditions. Fluorescently labelled animals will be used to follow the regeneration dynamics at the single-cell level. Together with complementary genetic and molecular biology techniques, this approach will give us new insights on single stem cells and gene expression dynamics during regeneration.

Life on earth depends upon the photosynthetic conversion of H2O, CO2 and light into fixed carbon (C) compounds including polysaccharides and lipids, and yet the biosynthesis, regulation and many aspects of the function of the photosynthetic apparatus are still not well understood. A major challenge for photosynthetic organisms is to capture light energy for growth while at the same time eliminating excess absorbed excitation to prevent photodamage, which can be energetically costly and potentially lethal. A major photoprotective mechanism in plants and most algae is qE (quenching energy), a quenching mechanism that dissipates absorbed excitation energy as heat, ensuring survival even under adverse conditions. In the green alga Chlamydomonas reinhardtii (Cr), two LHCSR proteins (Light Harvesting Complex Stress Related; LHCSR1 and LHCSR3) are required for qE function.
The LHCSRs are nucleus encoded, and their expression is governed by transcriptional and post-transcriptional processes that are impacted by CO2, nutrient availability, photosynthetic electron transport (PET), blue light perception and calcium(Ca2+)-elicited signalling. Despite their fundamental importance, mechanisms that regulate LHCSR accumulation are still not well understood and complicated by multiple inputs. For example, our findings demonstrate that LHCSR control is impacted by the metabolism of fixed C compounds. The combined use of physiology, biochemistry, genomics and mathematical modeling will allow us to elucidate transcriptional, post-transcriptional and epigenetic processes that link photosynthesis, C metabolism and photoperception to qE activity, and help establish a systems level view of photosynthetic dynamics.

In nature, cellular tissues efficiently remodel to attain crucial biological processes, both in health (organogenesis and development) and disease (cancer invasion and metastasis). Such reshaping events require collective cell migration, by means of which tissues can generate forces at large length scales. Although studies in vivo have evidenced the essential role of collective migration modes and flows within reshaping tissues, in vitro studies are necessary to explore these processes in simpler and better controlled microenvironments. In particular, this project aims at inducing reshaping events within confluent monolayers of cells by controlling cell flows through patterns of differential adhesiveness. First, we will explore the effects of geometrical confinement in the steady state positioning of topological defects in cellular nematics as a tool for localizing stress singularities of different strengths within cell tissues. Second, we will gain control over cellular active flows in order to induce unidirectional collective migration patterns. To this purpose, we will use gradients of surface-bound cues to control cell migration (haptotaxis) that, together with geometrical constraints, will provide with the tools for controlling flow and force fields within tissues. Finally, we will design patterns combining geometrical confinement and adhesion gradients to locally frustrate active flows and induce the creation of folds in preassigned regions within proliferative cell monolayers. Our work not only will provide experimental verification of the link between tissue mechanodynamics and reshaping, but also envisions the development of living 3D tissue structures in vitro.

The indeterminate growth of plant meristems is mediated by the long-term maintenance of stem cells. While patterns like the placement of stem cells are highly dependent on cell-cell communication in plants, there is incomplete understanding of the sources of signals that pattern the meristem. In addition, there is even less knowledge about how stem cells form during organogenesis and regeneration. In plant roots and other organs, patterning processes have been shown to be highly dependent on symplastic signaling through plasmodesmata -- membrane lined channels that connect every plant cells and allow trans-cellular movements of proteins (including transcription factors), miRNAs, RNAs, sugars and ions. To study cell-cell signaling on a broad scale, the host institute has developed a novel system to monitor complex communication from one cell to another during development. The system relies on recently developed tools to inducibly block plasmodesmata combined with single-cell RNA-seq profiling in plants. Here I propose to use this new set of techniques to sequentially block different cell identities and assess the consequent transcriptional changes using single-cell RNA-seq – a strategy we call “Block-Seq.” In particular, single-cell resolution offers the advantage of detecting responses in a subset of cells rather than expecting a tissue to respond uniformly. For the first time, these approaches will allow me to map communication from one cell type to another in the root meristem.