Transcriptional Basis of Mouse and Human Dendritic Cell Heterogeneity

Dendritic cells (DCs) play a critical role in orchestrating adaptive immune responses due to their unique ability to initiate T cell responses and direct their differentiation into effector lineages. Classical DCs have been divided into two subsets, cDC1 and cDC2, based on phenotypic markers and their distinct abilities to prime CD8 and CD4 T cells. While the transcriptional regulation of the cDC1 subset has been well characterized, cDC2 development and function remain poorly understood. By combining transcriptional and chromatin analyses with genetic reporter expression, we identified two principal cDC2 lineages defined by distinct developmental pathways and transcriptional regulators, including T-bet and RORgt, two key transcription factors known to define innate and adaptive lymphocyte subsets. These novel cDC2 lineages were characterized by distinct metabolic and functional programs. Extending our findings to humans revealed conserved DC heterogeneity and the presence of the newly defined cDC2 subsets in human cancer

Single-Cell Transcriptional Profiling Reveals Signatures of Helper, Effector, and Regulatory MAIT Cells during Homeostasis and Activation

Mucosal-associated invariant T (MAIT) cells are innate-like lymphocytes that recognize microbial vitamin B metabolites and have emerging roles in infectious disease, autoimmunity, and cancer. Although MAIT cells are identified by a semi-invariant TCR, their phenotypic and functional heterogeneity is not well understood. Here we present an integrated single cell transcriptomic analysis of over 76,000 human MAIT cells during early and prolonged Ag-specific activation with the MR1 ligand 5-OP-RU and nonspecific TCR stimulation. We show that MAIT cells span a broad range of homeostatic, effector, helper, tissue-infiltrating, regulatory, and exhausted phenotypes, with distinct gene expression programs associated with CD4+ or CD8+ coexpression. During early activation, MAIT cells rapidly adopt a cytotoxic phenotype characterized by high expression of GZMB, IFNG and TNF In contrast, prolonged stimulation induces heterogeneous states defined by proliferation, cytotoxicity, immune modulation, and exhaustion. We further demonstrate a FOXP3 expressing MAIT cell subset that phenotypically resembles conventional regulatory T cells. Moreover, scRNAseq-defined MAIT cell subpopulations were also detected in individuals recently exposed to Mycobacterium tuberculosis, confirming their presence during human infection. To our knowledge, our study provides the first comprehensive atlas of human MAIT cells in activation conditions and defines substantial functional heterogeneity, suggesting complex roles in health and disease

High-throughput screening for industrial enzyme production hosts by droplet microfluidics

A high-throughput method for single cell screening by microfluidic droplet sorting is applied to a whole-genome mutated yeast cell library yielding improved production hosts of secreted industrial enzymes. The sorting method is validated by enriching a yeast strain 14 times based on its a-amylase production, close to the theoretical maximum enrichment. Furthermore, a 105 member yeast cell library is screened yielding a clone with a more than 2-fold increase in a-amylase production. The increase in enzyme production results from an improvement of the cellular functions of the production host in contrast to previous droplet-based directed evolution that has focused on improving enzyme protein structure. In the workflow presented, enzyme producing single cells are encapsulated in 20 pL droplets with a fluorogenic reporter substrate. The coupling of a desired phenotype (secreted enzyme concentration) with the genotype (contained in the cell) inside a droplet enables selection of single cells with improved enzyme production capacity by droplet sorting. The platform has a throughput over 300 times higher than that of the current industry standard, an automated microtiter plate screening system. At the same time, reagent consumption for a screening experiment is decreased a million fold, greatly reducing the costs of evolutionary engineering of production strains

Marimo machines: Oscillators, biosensors and actuators

BackgroundThe green algae balls (Aegagropila linnaei), known as Marimo, are large spherical colonies of live photosynthetic filaments, formed by rolling water currents in freshwater lakes. Photosynthesis therein produces gas bubbles that can attach to the Marimo, consequently changing its buoyancy. This property allows them to float in the presence of light and sink in its absence.ResultsWe demonstrate that this ability can be harnessed to make actuators, biosensors and bioprocessors (oscillator, logic gates). Factors affecting Marimo movement have been studied to enable the design, construction and testing of working prototypes.ConclusionsA novel actuator design is reported, incorporating an enhanced bubble retention system and the design and optimisation of a bio-oscillator is demonstrated. A range of logic gates (or, and, nor, nand, xor) implementable with Marimo have been proposed

Statistical Modeling of Single Target Cell Encapsulation

High throughput drop-on-demand systems for separation and encapsulation of individual target cells from heterogeneous mixtures of multiple cell types is an emerging method in biotechnology that has broad applications in tissue engineering and regenerative medicine, genomics, and cryobiology. However, cell encapsulation in droplets is a random process that is hard to control. Statistical models can provide an understanding of the underlying processes and estimation of the relevant parameters, and enable reliable and repeatable control over the encapsulation of cells in droplets during the isolation process with high confidence level. We have modeled and experimentally verified a microdroplet-based cell encapsulation process for various combinations of cell loading and target cell concentrations. Here, we explain theoretically and validate experimentally a model to isolate and pattern single target cells from heterogeneous mixtures without using complex peripheral systems.Wallace H. Coulter Foundation (Young Investigator in Bioengineering Award)National Institutes of Health (U.S.) (Grant R01AI081534)National Institutes of Health (U.S.) (Grant R21AI087107

Cognitive frames in corporate sustainability: managerial sensemaking with paradoxical and business case frames

Corporate sustainability confronts managers with tensions between complex economic, environmental, and social issues. Drawing on the literature on managerial cognition, corporate sustainability, and strategic paradoxes, we develop a cognitive framing perspective on corporate sustainability. We propose two cognitive frames—a business case frame and a paradoxical frame—and explore how differences between them in cognitive content and structure influence the three stages of the sensemaking process—that is, managerial scanning, interpreting, and responding with regard to sustainability issues. We explain how the two frames lead to differences in the breadth and depth of scanning, differences in issue interpretations in terms of sense of control and issue valence, and different types of responses that managers consider with regard to sustainability issues. By considering alternative cognitive frames, our argument contributes to a better understanding of managerial decision making regarding ambiguous sustainability issues, and it develops the underlying cognitive determinants of the stance that managers adopt on sustainability issues. This argument offers a cognitive explanation for why managers rarely push for radical change when faced with complex and ambiguous issues, such as sustainability, that are characterized by conflicting yet interrelated aspects

The study of atmospheric ice-nucleating particles via microfluidically generated droplets

Ice-nucleating particles (INPs) play a significant role in the climate and hydrological cycle by triggering ice formation in supercooled clouds, thereby causing precipitation and affecting cloud lifetimes and their radiative properties. However, despite their importance, INP often comprise only 1 in 10³–10⁶ ambient particles, making it difficult to ascertain and predict their type, source, and concentration. The typical techniques for quantifying INP concentrations tend to be highly labour-intensive, suffer from poor time resolution, or are limited in sensitivity to low concentrations. Here, we present the application of microfluidic devices to the study of atmospheric INPs via the simple and rapid production of monodisperse droplets and their subsequent freezing on a cold stage. This device offers the potential for the testing of INP concentrations in aqueous samples with high sensitivity and high counting statistics. Various INPs were tested for validation of the platform, including mineral dust and biological species, with results compared to literature values. We also describe a methodology for sampling atmospheric aerosol in a manner that minimises sampling biases and which is compatible with the microfluidic device. We present results for INP concentrations in air sampled during two field campaigns: (1) from a rural location in the UK and (2) during the UK’s annual Bonfire Night festival. These initial results will provide a route for deployment of the microfluidic platform for the study and quantification of INPs in upcoming field campaigns around the globe, while providing a benchmark for future lab-on-a-chip-based INP studies

Single-cell analysis tools for drug discovery and development

The genetic, functional or compositional heterogeneity of healthy and diseased tissues presents major challenges in drug discovery and development. Such heterogeneity hinders the design of accurate disease models and can confound the interpretation of biomarker levels and of patient responses to specific therapies. The complex nature of virtually all tissues has motivated the development of tools for single-cell genomic, transcriptomic and multiplex proteomic analyses. Here, we review these tools and assess their advantages and limitations. Emerging applications of single cell analysis tools in drug discovery and development, particularly in the field of oncology, are discussed