A patterned human neural tube model using microfluidic gradients.

The human nervous system is a highly complex but organized organ. The foundation of its complexity and organization is laid down during regional patterning of the neural tube, the embryonic precursor to the human nervous system. Historically, studies of neural tube patterning have relied on animal models to uncover underlying principles. Recently, models of neurodevelopment based on human pluripotent stem cells, including neural organoids1-5 and bioengineered neural tube development models6-10, have emerged. However, such models fail to recapitulate neural patterning along both rostral-caudal and dorsal-ventral axes in a three-dimensional tubular geometry, a hallmark of neural tube development. Here we report a human pluripotent stem cell-based, microfluidic neural tube-like structure, the development of which recapitulates several crucial aspects of neural patterning in brain and spinal cord regions and along rostral-caudal and dorsal-ventral axes. This structure was utilized for studying neuronal lineage development, which revealed pre-patterning of axial identities of neural crest progenitors and functional roles of neuromesodermal progenitors and the caudal gene CDX2 in spinal cord and trunk neural crest development. We further developed dorsal-ventral patterned microfluidic forebrain-like structures with spatially segregated dorsal and ventral regions and layered apicobasal cellular organizations that mimic development of the human forebrain pallium and subpallium, respectively. Together, these microfluidics-based neurodevelopment models provide three-dimensional lumenal tissue architectures with in vivo-like spatiotemporal cell differentiation and organization, which will facilitate the study of human neurodevelopment and disease.

A Standardized Set of MoClo-Compatible Inducible Promoter Systems for Tunable Gene Expression in Yeast.

Small-molecule control of gene expression underlies the function of numerous engineered gene circuits that are capable of environmental sensing, computation, and memory. While many recently developed inducible promoters have been tailor-made for bacteria or mammalian cells, relatively few new systems have been built for Saccharomyces cerevisiae, limiting the scale of synthetic biology work that can be done in yeast. To address this, we created the yeast Tunable Expression Systems Toolkit (yTEST), which contains a set of five extensively characterized inducible promoter systems regulated by the small-molecules doxycycline (Dox), abscisic acid (ABA), danoprevir (DNV), 1-naphthaleneacetic acid (NAA), and 5-phenyl-indole-3-acetic acid (5-Ph-IAA). Assembly was made to be compatible with the modular cloning yeast toolkit (MoClo-YTK) to enhance the ease of use and provide a framework to benchmark and standardize each system. Using this approach, we built multiple systems with maximal expression levels greater than those of the strong constitutive TDH3 promoter. Furthermore, each of the five classes of systems could be induced at least 60-fold after a 6 h induction and the highest fold change observed was approximately 300. Thus, yTEST provides a reliable, diverse, and customizable set of inducible promoters to modulate gene expression in yeast for applications in synthetic biology, metabolic engineering, and basic research.

A Microfluidic Platform for Screening Gene Expression Dynamics across Yeast Strain Libraries.

The relative ease of genetic manipulation in S. cerevisiae is one of its greatest strengths as a model eukaryotic organism. Researchers have leveraged this quality of the budding yeast to study the effects of a variety of genetic perturbations, such as deletion or overexpression, in a high-throughput manner. This has been accomplished by producing a number of strain libraries that can contain hundreds or even thousands of distinct yeast strains with unique genetic alterations. While these strategies have led to enormous increases in our understanding of the functions and roles that genes play within cells, the techniques used to screen genetically modified libraries of yeast strains typically rely on plate or sequencing-based assays that make it difficult to analyze gene expression changes over time. Microfluidic devices, combined with fluorescence microscopy, can allow gene expression dynamics of different strains to be captured in a continuous culture environment; however, these approaches often have significantly lower throughput compared to traditional techniques. To address these limitations, we have developed a microfluidic platform that uses an array pinning robot to allow for up to 48 different yeast strains to be transferred onto a single device. Here, we detail a validated methodology for constructing and setting up this microfluidic device, starting with the photolithography steps for constructing the wafer, then the soft lithography steps for making polydimethylsiloxane (PDMS) microfluidic devices, and finally the robotic arraying of strains onto the device for experiments. We have applied this device for dynamic screens of a protein aggregation library; however, this methodology has the potential to enable complex and dynamic screens of yeast libraries for a wide range of applications. Key features • Major steps of this protocol require access to specialized equipment (i.e., microfabrication tools typically found in a cleanroom facility and an array pinning robot). • Construction of microfluidic devices with multiple different feature heights using photolithography and soft lithography with PDMS. • Robotic spotting of up to 48 different yeast strains onto microfluidic devices.

Fabrication of Microfluidic Devices for Continuously Monitoring Yeast Aging.

For several decades, aging in Saccharomyces cerevisiae has been studied in hopes of understanding its causes and identifying conserved pathways that also drive aging in multicellular eukaryotes. While the short lifespan and unicellular nature of budding yeast has allowed its aging process to be observed by dissecting mother cells away from daughter cells under a microscope, this technique does not allow continuous, high-resolution, and high-throughput studies to be performed. Here, we present a protocol for constructing microfluidic devices for studying yeast aging that are free from these limitations. Our approach uses multilayer photolithography and soft lithography with polydimethylsiloxane (PDMS) to construct microfluidic devices with distinct single-cell trapping regions as well as channels for supplying media and removing recently born daughter cells. By doing so, aging yeast cells can be imaged at scale for the entirety of their lifespans, and the dynamics of molecular processes within single cells can be simultaneously tracked using fluorescence microscopy. Key features This protocol requires access to a photolithography lab in a cleanroom facility. Photolithography process for patterning photoresist on silicon wafers with multiple different feature heights. Soft lithography process for making PDMS microfluidic devices from silicon wafer templates.

Age-dependent aggregation of ribosomal RNA-binding proteins links deterioration in chromatin stability with challenges to proteostasis.

Chromatin instability and protein homeostasis (proteostasis) stress are two well-established hallmarks of aging, which have been considered largely independent of each other. Using microfluidics and single-cell imaging approaches, we observed that, during the replicative aging of Saccharomyces cerevisiae, a challenge to proteostasis occurs specifically in the fraction of cells with decreased stability within the ribosomal DNA (rDNA). A screen of 170 yeast RNA-binding proteins identified ribosomal RNA (rRNA)-binding proteins as the most enriched group that aggregate upon a decrease in rDNA stability induced by inhibition of a conserved lysine deacetylase Sir2. Further, loss of rDNA stability induces age-dependent aggregation of rRNA-binding proteins through aberrant overproduction of rRNAs. These aggregates contribute to age-induced proteostasis decline and limit cellular lifespan. Our findings reveal a mechanism underlying the interconnection between chromatin instability and proteostasis stress and highlight the importance of cell-to-cell variability in aging processes.

Patterning of brain organoids derived from human pluripotent stem cells.

The emerging technology of brain organoids deriving from human pluripotent stem cells provides unprecedented opportunities to study human brain development and associated disorders. Various brain organoid protocols have been developed that can recapitulate some key features of cell type diversity, cytoarchitectural organization, developmental processes, functions, and pathologies of the developing human brain. In this review, we focus on patterning of human stem cell-derived brain organoids. We start with an overview of general procedures to generate brain organoids. We then highlight some recently developed brain organoid protocols and chemical cues involved in modeling development of specific human brain regions, subregions, and multiple regions together. We also discuss limitations and potential future improvements of human brain organoid technology.

A programmable fate decision landscape underlies single-cell aging in yeast.

Chromatin instability and mitochondrial decline are conserved processes that contribute to cellular aging. Although both processes have been explored individually in the context of their distinct signaling pathways, the mechanism that determines which process dominates during aging of individual cells is unknown. We show that interactions between the chromatin silencing and mitochondrial pathways lead to an epigenetic landscape of yeast replicative aging with multiple equilibrium states that represent different types of terminal states of aging. The structure of the landscape drives single-cell differentiation toward one of these states during aging, whereby the fate is determined quite early and is insensitive to intracellular noise. Guided by a quantitative model of the aging landscape, we genetically engineered a long-lived equilibrium state characterized by an extended life span.

Advances in quantitative biology methods for studying replicative aging in Saccharomyces cerevisiae.

Aging is a complex, yet pervasive phenomenon in biology. As human cells steadily succumb to the deteriorating effects of aging, so too comes a host of age-related ailments such as neurodegenerative disorders, cardiovascular disease and cancer. Therefore, elucidation of the molecular networks that drive aging is of paramount importance to human health. Progress toward this goal has been aided by studies from simple model organisms such as Saccharomyces cerevisiae. While work in budding yeast has already revealed much about the basic biology of aging as well as a number of evolutionarily conserved pathways involved in this process, recent technological advances are poised to greatly expand our knowledge of aging in this simple eukaryote. Here, we review the latest developments in microfluidics, single-cell analysis and high-throughput technologies for studying single-cell replicative aging in S. cerevisiae. We detail the challenges each of these methods addresses as well as the unique insights into aging that each has provided. We conclude with a discussion of potential future applications of these techniques as well as the importance of single-cell dynamics and quantitative biology approaches for understanding cell aging.

Divergent Aging of Isogenic Yeast Cells Revealed through Single-Cell Phenotypic Dynamics.

Although genetic mutations that alter organisms' average lifespans have been identified in aging research, our understanding of the dynamic changes during aging remains limited. Here, we integrate single-cell imaging, microfluidics, and computational modeling to investigate phenotypic divergence and cellular heterogeneity during replicative aging of single S. cerevisiae cells. Specifically, we find that isogenic cells diverge early in life toward one of two aging paths, which are characterized by distinct age-associated phenotypes. We captured the dynamics of single cells along the paths with a stochastic discrete-state model, which accurately predicts both the measured heterogeneity and the lifespan of cells on each path within a cell population. Our analysis suggests that genetic and environmental factors influence both a cell's choice of paths and the kinetics of paths themselves. Given that these factors are highly conserved throughout eukaryotes, divergent aging might represent a general scheme in cellular aging of other organisms.

Flavin-based metabolic cycles are integral features of growth and division in single yeast cells.

The yeast metabolic cycle (YMC) is a fascinating example of biological organization, in which cells constrain the function of specific genetic, protein and metabolic networks to precise temporal windows as they grow and divide. However, understanding the intracellular origins of the YMC remains a challenging goal, as measuring the oxygen oscillations traditionally associated with it requires the use of synchronized cultures growing in nutrient-limited chemostat environments. To address these limitations, we used custom-built microfluidic devices and time-lapse fluorescence microscopy to search for metabolic cycling in the form of endogenous flavin fluorescence in unsynchronized single yeast cells. We uncovered robust and pervasive metabolic cycles that were synchronized with the cell division cycle (CDC) and oscillated across four different nutrient conditions. We then studied the response of these metabolic cycles to chemical and genetic perturbations, showing that their phase synchronization with the CDC can be altered through treatment with rapamycin, and that metabolic cycles continue even in respiratory deficient strains. These results provide a foundation for future studies of the physiological importance of metabolic cycles in processes such as CDC control, metabolic regulation and cell aging.

Multigenerational silencing dynamics control cell aging.

Cellular aging plays an important role in many diseases, such as cancers, metabolic syndromes, and neurodegenerative disorders. There has been steady progress in identifying aging-related factors such as reactive oxygen species and genomic instability, yet an emerging challenge is to reconcile the contributions of these factors with the fact that genetically identical cells can age at significantly different rates. Such complexity requires single-cell analyses designed to unravel the interplay of aging dynamics and cell-to-cell variability. Here we use microfluidic technologies to track the replicative aging of single yeast cells and reveal that the temporal patterns of heterochromatin silencing loss regulate cellular life span. We found that cells show sporadic waves of silencing loss in the heterochromatic ribosomal DNA during the early phases of aging, followed by sustained loss of silencing preceding cell death. Isogenic cells have different lengths of the early intermittent silencing phase that largely determine their final life spans. Combining computational modeling and experimental approaches, we found that the intermittent silencing dynamics is important for longevity and is dependent on the conserved Sir2 deacetylase, whereas either sustained silencing or sustained loss of silencing shortens life span. These findings reveal that the temporal patterns of a key molecular process can directly influence cellular aging, and thus could provide guidance for the design of temporally controlled strategies to extend life span.