Single-cell Bayesian deconvolution.

Individual cells exhibit substantial heterogeneity in protein abundance and activity, which is frequently reflected in broad distributions of fluorescently labeled reporters. Since all cellular components are intrinsically fluorescent to some extent, the observed distributions contain background noise that masks the natural heterogeneity of cellular populations. This limits our ability to characterize cell-fate decision processes that are key for development, immune response, tissue homeostasis, and many other biological functions. It is therefore important to separate the contributions from signal and noise in single-cell measurements. Addressing this issue rigorously requires deconvolving the noise distribution from the signal, but approaches in that direction are still limited. Here, we present a non-parametric Bayesian formalism that performs such a deconvolution efficiently on multidimensional measurements, providing unbiased estimates of the resulting confidence intervals. We use this approach to study the expression of the mesodermal transcription factor Brachyury in mouse embryonic stem cells undergoing differentiation.

Integration of metabolism and regulation reveals rapid adaptability to growth on non-native substrates.

Engineering synthetic heterotrophy is a key to the efficient bio-based valorization of renewable and waste substrates. Among these, engineering hemicellulosic pentose utilization has been well-explored in Saccharomyces cerevisiae (yeast) over several decades-yet the answer to what makes their utilization inherently recalcitrant remains elusive. Through implementation of a semi-synthetic regulon, we find that harmonizing cellular and engineering objectives are a key to obtaining highest growth rates and yields with minimal metabolic engineering effort. Concurrently, results indicate that "extrinsic" factors-specifically, upstream genes that direct flux of pentoses into central carbon metabolism-are rate-limiting. We also reveal that yeast metabolism is innately highly adaptable to rapid growth on non-native substrates and that systems metabolic engineering (i.e., functional genomics, network modeling, etc.) is largely unnecessary. Overall, this work provides an alternate, novel, holistic (and yet minimalistic) approach based on integrating non-native metabolic genes with a native regulon system.

Towards universal synthetic heterotrophy using a metabolic coordinator.

Engineering the utilization of non-native substrates, or synthetic heterotrophy, in proven industrial microbes such as Saccharomyces cerevisiae represents an opportunity to valorize plentiful and renewable sources of carbon and energy as inputs to bioprocesses. We previously demonstrated that activation of the galactose (GAL) regulon, a regulatory structure used by this yeast to coordinate substrate utilization with biomass formation during growth on galactose, during growth on the non-native substrate xylose results in a vastly altered gene expression profile and faster growth compared with constitutive overexpression of the same heterologous catabolic pathway. However, this effort involved the creation of a xylose-inducible variant of Gal3p (Gal3pSyn4.1), the sensor protein of the GAL regulon, preventing this semi-synthetic regulon approach from being easily adapted to additional non-native substrates. Here, we report the construction of a variant Gal3pMC (metabolic coordinator) that exhibits robust GAL regulon activation in the presence of structurally diverse substrates and recapitulates the dynamics of the native system. Multiple molecular modeling studies suggest that Gal3pMC occupies conformational states corresponding to galactose-bound Gal3p in an inducer-independent manner. Using Gal3pMC to test a regulon approach to the assimilation of the non-native lignocellulosic sugars xylose, arabinose, and cellobiose yields higher growth rates and final cell densities when compared with a constitutive overexpression of the same set of catabolic genes. The subsequent demonstration of rapid and complete co-utilization of all three non-native substrates suggests that Gal3pMC-mediated dynamic global gene expression changes by GAL regulon activation may be universally beneficial for engineering synthetic heterotrophy.

A stem cell zoo uncovers intracellular scaling of developmental tempo across mammals.

Differential speeds in biochemical reactions have been proposed to be responsible for the differences in developmental tempo between mice and humans. However, the underlying mechanism controlling the species-specific kinetics remains to be determined. Using in vitro differentiation of pluripotent stem cells, we recapitulated the segmentation clocks of diverse mammalian species varying in body weight and taxa: marmoset, rabbit, cattle, and rhinoceros. Together with mouse and human, the segmentation clock periods of the six species did not scale with the animal body weight, but with the embryogenesis length. The biochemical kinetics of the core clock gene HES7 displayed clear scaling with the species-specific segmentation clock period. However, the cellular metabolic rates did not show an evident correlation. Instead, genes involving biochemical reactions showed an expression pattern that scales with the segmentation clock period. Altogether, our stem cell zoo uncovered general scaling laws governing species-specific developmental tempo.

Understanding the interplay of membrane trafficking, cell surface mechanics, and stem cell differentiation.

Stem cells can generate a diversity of cell types during development, regeneration and adult tissue homeostasis. Differentiation changes not only the cell fate in terms of gene expression but also the physical properties and functions of cells, e.g. the secretory activity, cell shape, or mechanics. Conversely, these activities and properties can also regulate differentiation itself. Membrane trafficking is known to modulate signal transduction and thus has the potential to control stem cell differentiation. On the other hand, membrane trafficking, particularly from and to the plasma membrane, depends on the mechanical properties of the cell surface such as tension within the plasma membrane or the cortex. Indeed, recent findings demonstrate that cell surface mechanics can also control cell fate. Here, we review the bidirectional relationships between these three fundamental cellular functions, i.e. membrane trafficking, cell surface mechanics, and stem cell differentiation. Furthermore, we discuss commonly used methods in each field and how combining them with new tools will enhance our understanding of their interplay. Understanding how membrane trafficking and cell surface mechanics can guide stem cell fate holds great potential as these concepts could be exploited for directed differentiation of stem cells for the fields of tissue engineering and regenerative medicine.

Flow cytometric evaluation of yeast-bacterial cell-cell interactions.

Synthetic cell-cell interaction systems can be useful for understanding multicellular communities or for screening binding molecules. We adapt a previously characterized set of synthetic cognate nanobody-antigen pairs to a yeast-bacteria coincubation format and use flow cytometry to evaluate cell-cell interactions mediated by binding between surface-displayed molecules. We further use fluorescence-activated cell sorting to enrich a specific yeast-displayed nanobody within a mixed yeast-display population. Finally, we demonstrate that this system supports the characterization of a therapeutically relevant nanobody-antigen interaction: a previously discovered nanobody that binds to the intimin protein expressed on the surface of enterohemorrhagic Escherichia coli. Overall, our findings indicate that the yeast-bacteria format supports efficient evaluation of ligand-target interactions. With further development, this format may facilitate systematic characterization and high-throughput discovery of bacterial surface-binding molecules.

A Silk-Based Platform to Stabilize Phenylalanine Ammonia-lyase for Orally Administered Enzyme Replacement Therapy.

Phenylalanine ammonia-lyase (PAL) has gained attention in recent years for the treatment of phenylketonuria (PKU), a genetic disorder that affects ∼1 in 15 000 individuals globally. However, the enzyme is easily degraded by proteases, unstable at room temperature, and currently administered in PKU patients as daily subcutaneous injections. We report here the stabilization of the PAL from Anabaena variabilis, which is currently used to formulate pegvaliase, through incorporation in a silk fibroin matrix. The combination with silk stabilizes PAL at 37 °C. In addition, in vitro studies showed that inclusion in a silk matrix preserves the biological activity of the enzyme in simulated intestinal fluid, which will enable oral administration of PAL to treat PKU.

Arrested coalescence of multicellular aggregates.

Multicellular aggregates are known to exhibit liquid-like properties. The fusion process of two cell aggregates is commonly studied as the coalescence of two viscous drops. However, tissues are complex materials and can exhibit viscoelastic behaviour. It is known that elastic effects can prevent the complete fusion of two drops, a phenomenon known as arrested coalescence. Here we study this phenomenon in stem cell aggregates and provide a theoretical framework which agrees with the experiments. In addition, agent-based simulations show that active cell fluctuations can control a solid-to-fluid phase transition, revealing that arrested coalescence can be found in the vicinity of an unjamming transition. By analysing the dynamics of the fusion process and combining it with nanoindentation measurements, we obtain the effective viscosity, shear modulus and surface tension of the aggregates. More generally, our work provides a simple, fast and inexpensive method to characterize the mechanical properties of viscoelastic materials.

Periodic formation of epithelial somites from human pluripotent stem cells.

During embryonic development, epithelial cell blocks called somites are periodically formed according to the segmentation clock, becoming the foundation for the segmental pattern of the vertebral column. The process of somitogenesis has recently been recapitulated with murine and human pluripotent stem cells. However, an in vitro model for human somitogenesis coupled with the segmentation clock and epithelialization is still missing. Here, we report the generation of human somitoids, organoids that periodically form pairs of epithelial somite-like structures. Somitoids display clear oscillations of the segmentation clock that coincide with the segmentation of the presomitic mesoderm. The resulting somites show anterior-posterior and apical-basal polarities. Matrigel is essential for epithelialization but dispensable for the differentiation into somite cells. The size of somites is rather constant, irrespective of the initial cell number. The amount of WNT signaling instructs the proportion of mesodermal lineages in somitoids. Somitoids provide a novel platform to study human somitogenesis.

Sculpting tissues by phase transitions.

Biological systems display a rich phenomenology of states that resemble the physical states of matter - solid, liquid and gas. These phases result from the interactions between the microscopic constituent components - the cells - that manifest in macroscopic properties such as fluidity, rigidity and resistance to changes in shape and volume. Looked at from such a perspective, phase transitions from a rigid to a flowing state or vice versa define much of what happens in many biological processes especially during early development and diseases such as cancer. Additionally, collectively moving confluent cells can also lead to kinematic phase transitions in biological systems similar to multi-particle systems where the particles can interact and show sub-populations characterised by specific velocities. In this Perspective we discuss the similarities and limitations of the analogy between biological and inert physical systems both from theoretical perspective as well as experimental evidence in biological systems. In understanding such transitions, it is crucial to acknowledge that the macroscopic properties of biological materials and their modifications result from the complex interplay between the microscopic properties of cells including growth or death, neighbour interactions and secretion of matrix, phenomena unique to biological systems. Detecting phase transitions in vivo is technically difficult. We present emerging approaches that address this challenge and may guide our understanding of the organization and macroscopic behaviour of biological tissues.

In-depth Sequence-Function Characterization Reveals Multiple Pathways to Enhance Enzymatic Activity.

Deep mutational scanning (DMS) has recently emerged as a powerful method to study protein sequence-function relationships but it has not been well-explored as a guide to enzyme engineering and identifying pathways by which their catalytic cycle may be improved. We report such a demonstration in this work using a Phenylalanine ammonia-lyase (PAL), which deaminates L-phenylalanine to trans-cinnamic acid and has widespread application in chemo-enzymatic synthesis, agriculture, and medicine. In particular, the PAL from Anabaena variabilis (AvPAL*) has garnered significant attention as the active ingredient in Pegvaliase®, the only FDA-approved drug treating classical Phenylketonuria (PKU). Although an extensive body of literature exists on the structure, substrate-specificity, and catalytic cycle, protein-wide sequence determinants of function remain unknown, as do intermediate reaction steps that limit turnover frequency, all of which has hindered rational engineering of these enzymes. Here, we created a detailed sequence-function landscape of AvPAL* by performing DMS and revealed 112 mutations at 79 functionally relevant sites that affect a positive change in enzyme fitness. Using fitness values and structure-function analysis, we picked a subset of positions for comprehensive single- and multi-site saturation mutagenesis and identified combinations of mutations that led to improved reaction kinetics in cell-free and cellular contexts. We then performed QM/MM and MD to understand the mechanistic role of the most beneficial mutations and observed that different mutants confer improvements via different mechanisms, including stabilizing transition and intermediate states, improving substrate diffusion into the active site, and decreasing product inhibition. This work demonstrates how DMS can be combined with computational analysis to effectively identify significant mutations that enhance enzyme activity along with the underlying mechanisms by which these mutations confer their benefit.

Cheating the Cheater: Suppressing False-Positive Enrichment during Biosensor-Guided Biocatalyst Engineering.

Transcription factor (TF)-based biosensors are very desirable reagents for high-throughput enzyme and strain engineering campaigns. Despite their potential, they are often difficult to deploy effectively as the small molecules being detected can leak out of high-producer cells, into low-producer cells, and activate the biosensor therein. This crosstalk leads to the overrepresentation of false-positive/cheater cells in the enriched population. While the host cell can be engineered to minimize crosstalk (e.g., by deleting responsible transporters), this is not easily applicable to all molecules of interest, particularly those that can diffuse passively. One such biosensor recently reported for trans-cinnamic acid (tCA) suffers from crosstalk when used for phenylalanine ammonia-lyase (PAL) enzyme engineering by directed evolution. We report that desensitizing the biosensor (i.e., increasing the limit of detection) suppresses cheater population enrichment. Furthermore, we show that, if we couple the biosensor-based screen with an orthogonal prescreen that eliminates a large fraction of true negatives, we can successfully reduce the cheater population during the fluorescence-activated cell sorting. Using the approach developed here, we were successfully able to isolate PAL variants with ∼70% higher kcat after a single sort. These mutants have tremendous potential in phenylketonuria (PKU) treatment and flavonoid production.

Sculpting with stem cells: how models of embryo development take shape.

During embryogenesis, organisms acquire their shape given boundary conditions that impose geometrical, mechanical and biochemical constraints. A detailed integrative understanding how these morphogenetic information modules pattern and shape the mammalian embryo is still lacking, mostly owing to the inaccessibility of the embryo in vivo for direct observation and manipulation. These impediments are circumvented by the developmental engineering of embryo-like structures (stembryos) from pluripotent stem cells that are easy to access, track, manipulate and scale. Here, we explain how unlocking distinct levels of embryo-like architecture through controlled modulations of the cellular environment enables the identification of minimal sets of mechanical and biochemical inputs necessary to pattern and shape the mammalian embryo. We detail how this can be complemented with precise measurements and manipulations of tissue biochemistry, mechanics and geometry across spatial and temporal scales to provide insights into the mechanochemical feedback loops governing embryo morphogenesis. Finally, we discuss how, even in the absence of active manipulations, stembryos display intrinsic phenotypic variability that can be leveraged to define the constraints that ensure reproducible morphogenesis in vivo.

linus: Conveniently explore, share, and present large-scale biological trajectory data in a web browser.

In biology, we are often confronted with information-rich, large-scale trajectory data, but exploring and communicating patterns in such data can be a cumbersome task. Ideally, the data should be wrapped with an interactive visualisation in one concise packet that makes it straightforward to create and test hypotheses collaboratively. To address these challenges, we have developed a tool, linus, which makes the process of exploring and sharing 3D trajectories as easy as browsing a website. We provide a python script that reads trajectory data, enriches them with additional features such as edge bundling or custom axes, and generates an interactive web-based visualisation that can be shared online. linus facilitates the collaborative discovery of patterns in complex trajectory data.

MOrgAna: accessible quantitative analysis of organoids with machine learning.

Recent years have seen a dramatic increase in the application of organoids to developmental biology, biomedical and translational studies. Organoids are large structures with high phenotypic complexity and are imaged on a wide range of platforms, from simple benchtop stereoscopes to high-content confocal-based imaging systems. The large volumes of images, resulting from hundreds of organoids cultured at once, are becoming increasingly difficult to inspect and interpret. Hence, there is a pressing demand for a coding-free, intuitive and scalable solution that analyses such image data in an automated yet rapid manner. Here, we present MOrgAna, a Python-based software that implements machine learning to segment images, quantify and visualize morphological and fluorescence information of organoids across hundreds of images, each with one object, within minutes. Although the MOrgAna interface is developed for users with little to no programming experience, its modular structure makes it a customizable package for advanced users. We showcase the versatility of MOrgAna on several in vitro systems, each imaged with a different microscope, thus demonstrating the wide applicability of the software to diverse organoid types and biomedical studies.

Studying evolution of the primary body axis in vivo and in vitro.

The metazoan body plan is established during early embryogenesis via collective cell rearrangements and evolutionarily conserved gene networks, as part of a process commonly referred to as gastrulation. While substantial progress has been achieved in terms of characterizing the embryonic development of several model organisms, underlying principles of many early patterning processes nevertheless remain enigmatic. Despite the diversity of (pre-)gastrulating embryo and adult body shapes across the animal kingdom, the body axes, which are arguably the most fundamental features, generally remain identical between phyla. Recently there has been a renewed appreciation of ex vivo and in vitro embryo-like systems to model early embryonic patterning events. Here, we briefly review key examples and propose that similarities in morphogenesis and associated gene expression dynamics may reveal an evolutionarily conserved developmental mode as well as provide further insights into the role of external or extraembryonic cues in shaping the early embryo. In summary, we argue that embryo-like systems can be employed to inform previously uncharted aspects of animal body plan evolution as well as associated patterning rules.

Gastruloids: Embryonic Organoids from Mouse Embryonic Stem Cells to Study Patterning and Development in Early Mammalian Embryos.

Gastruloids are embryonic organoids made from small, defined numbers of mouse embryonic stem cells (mESCs) aggregated in suspension culture, which over time form 3D structures that mimic many of the features of early mammalian development. Unlike embryoid bodies that are usually disorganized when grown over several days, gastruloids display distinct, well-organized gene expression domains demarcating the emergence of the three body axes, anteroposterior axial elongation, and implementation of collinear Hox transcriptional patterns over 5-7 days of culture. As such gastruloids represent a useful experimental system that is complementary to in vivo approaches in studying early developmental patterning mechanisms regulating the acquisition of cell fates. In this protocol, we describe the most recent method for generating gastruloids with high reproducibility, and provide a comprehensive list of possible challenges as well as steps for protocol optimization.

Rethinking embryology in vitro: A synergy between engineering, data science and theory.

Pluripotent stem cells, in the recent years, have been demonstrated to mimic different aspects of metazoan embryonic development in vitro. This has led to the establishment of synthetic embryology: a field that makes use of in vitro stem cell models to investigate developmental processes that would be otherwise inaccessible in vivo. Currently, a plethora of engineering-inspired techniques, including microfluidic devices and bioreactors, exist to generate and culture organoids at high throughput. Similarly, data analysis and deep learning-based techniques, that were established in in vivo models, are now being used to extract quantitative information from synthetic systems. Finally, theory and data-driven in silico modeling are starting to provide a system-level understanding of organoids and make predictions to be tested with further experiments. Here, we discuss our vision of how engineering, data science and theoretical modeling will synergize to offer an unprecedented view of embryonic development. For every one of these three scientific domains, we discuss examples from in vivo and in vitro systems that we think will pave the way to future developments of synthetic embryology.