Delineation of chicken immune markers in the era of omics and multicolor flow cytometry.

Multiparameter flow cytometry is a routine method in immunological studies incorporated in biomedical, veterinary, agricultural, and wildlife research and routinely used in veterinary clinical laboratories. Its use in the diagnostics of poultry diseases is still limited, but due to the continuous expansion of reagents and cost reductions, this may change in the near future. Although the structure and function of the avian immune system show commonalities with mammals, at the molecular level, there is often low homology across species. The cross-reactivity of mammalian immunological reagents is therefore low, but nevertheless, the list of reagents to study chicken immune cells is increasing. Recent improvement in multicolor antibody panels for chicken cells has resulted in more detailed analysis by flow cytometry and has allowed the discovery of novel leukocyte cell subpopulations. In this article, we present an overview of the reagents and guidance needed to perform multicolor flow cytometry using chicken samples and common pitfalls to avoid.

The single-cell chromatin landscape in gonadal cell lineage specification.

Gonad development includes sex determination and divergent maturation of the testes and ovaries. Recent advances in measuring gene expression in single cells are providing new insights into this complex process. However, the underlying epigenetic regulatory mechanisms remain unclear. Here, we profiled chromatin accessibility in mouse gonadal cells of both sexes from embryonic day 11.5 to 14.5 using single-cell assay for transposase accessible chromatin by sequencing (scATAC-seq). Our results showed that individual cell types can be inferred by the chromatin landscape, and that cells can be temporally ordered along developmental trajectories. Integrative analysis of transcriptomic and chromatin-accessibility maps identified multiple putative regulatory elements proximal to key gonadal genes Nr5a1, Sox9 and Wt1. We also uncover cell type-specific regulatory factors underlying cell type specification. Overall, our results provide a better understanding of the epigenetic landscape associated with the progressive restriction of cell fates in the gonad.

Emerging tools for uncovering genetic and transcriptomic heterogeneities in bacteria.

Bacterial communities display an astonishing degree of heterogeneities among their constituent cells across both the genomic and transcriptomic levels, giving rise to diverse social interactions and stress-adaptation strategies indispensable for proliferating in the natural environment (Ackermann in Nat Rev Microbiol 13:497-508, 2015). Our knowledge about bacterial heterogeneities and their physiological ramifications critically depends on our ability to unambiguously resolve the genetic and phenotypic states of the individual cells that make up the population. In this short review, I highlight several recently developed methods for studying bacterial heterogeneities, primarily focusing on single-cell techniques based on advanced sequencing and microscopy technologies. I will discuss the working principle of each technique as well as the types of problems each technique is best positioned to address. With significant improvements in resolution and throughput, these emerging tools together offer unprecedented and complementary views of various types of heterogeneities found within bacterial populations, paving the way for mechanistic dissections and systematic interventions in laboratory and clinical settings.

Flow Cytometry Quantification of Transient Transfections in Mammalian Cells.

Flow cytometry is a powerful quantitative assay supporting high-throughput collection of single-cell data with a high dynamic range. For flow cytometry to yield reproducible data with a quantitative relationship to the underlying biology, however, requires that (1) appropriate process controls are collected along with experimental samples, (2) these process controls are used for unit calibration and quality control, and (3) data are analyzed using appropriate statistics. To this end, this chapter describes methods for quantitative flow cytometry through the addition of process controls and analyses, thereby enabling better development, modeling, and debugging of engineered biological organisms. The methods described here have specifically been developed in the context of transient transfections in mammalian cells but may in many cases be adaptable to other categories of transfection and other types of cells.

A spatial cell atlas of neuroblastoma reveals developmental, epigenetic and spatial axis of tumor heterogeneity.

Neuroblastoma is a pediatric cancer arising from the developing sympathoadrenal lineage with complex inter- and intra-tumoral heterogeneity. To chart this complexity, we generated a comprehensive cell atlas of 55 neuroblastoma patient tumors, collected from two pediatric cancer institutions, spanning a range of clinical, genetic, and histologic features. Our atlas combines single-cell/nucleus RNA-seq (sc/scRNA-seq), bulk RNA-seq, whole exome sequencing, DNA methylation profiling, spatial transcriptomics, and two spatial proteomic methods. Sc/snRNA-seq revealed three malignant cell states with features of sympathoadrenal lineage development. All of the neuroblastomas had malignant cells that resembled sympathoblasts and the more differentiated adrenergic cells. A subset of tumors had malignant cells in a mesenchymal cell state with molecular features of Schwann cell precursors. DNA methylation profiles defined four groupings of patients, which differ in the degree of malignant cell heterogeneity and clinical outcomes. Using spatial proteomics, we found that neuroblastomas are spatially compartmentalized, with malignant tumor cells sequestered away from immune cells. Finally, we identify spatially restricted signaling patterns in immune cells from spatial transcriptomics. To facilitate the visualization and analysis of our atlas as a resource for further research in neuroblastoma, single cell, and spatial-omics, all data are shared through the Human Tumor Atlas Network Data Commons at www.humantumoratlas.org.

Unraveling the secrets of γδ T cells with single-cell biology.

Recent technological advancements have enabled us to study the molecular features of cellular states at the single-cell level, providing unprecedented resolution for comprehending the identity and function of a cell. By applying these techniques across multiple time frames, tissues, and diseases, we can delve deeper into the mechanisms governing the development and functions of cell lineages. In this review, I focus on γδ T cells, which are a unique and functionally nonredundant T cell lineage categorized under the umbrella of unconventional T cells. I discuss how single-cell biology is providing unique insights into their development and functions. Furthermore, I explore how single-cell methods can be used to answer several key questions about their biology. These investigations will be essential to fully understand their translational potential, including their role in cytotoxicity and tissue repair in cancer and regeneration.

Parsing 20 Years of Public Data by AI Maps Trends in Proteomics and Forecasts Technology.

The trends of the last 20 years in biotechnology were revealed using artificial intelligence and natural language processing (NLP) of publicly available data. Implementing this "science-of-science" approach, we capture convergent trends in the field of proteomics in both technology development and application across the phylogenetic tree of life. With major gaps in our knowledge about protein composition, structure, and location over time, we report trends in persistent, popular approaches and emerging technologies across 94 ideas from a corpus of 29 journals in PubMed over two decades. New metrics for clusters of these ideas reveal the progression and popularity of emerging approaches like single-cell, spatial, compositional, and chemical proteomics designed to better capture protein-level chemistry and biology. This analysis of the proteomics literature with advanced analytic tools quantifies the Rate of Rise for a next generation of technologies to better define, quantify, and visualize the multiple dimensions of the proteome that will transform our ability to measure and understand proteins in the coming decade.

Time-resolved single-cell transcriptomics defines immune trajectories in glioblastoma.

Deciphering the cell-state transitions underlying immune adaptation across time is fundamental for advancing biology. Empirical in vivo genomic technologies that capture cellular dynamics are currently lacking. We present Zman-seq, a single-cell technology recording transcriptomic dynamics across time by introducing time stamps into circulating immune cells, tracking them in tissues for days. Applying Zman-seq resolved cell-state and molecular trajectories of the dysfunctional immune microenvironment in glioblastoma. Within 24 hours of tumor infiltration, cytotoxic natural killer cells transitioned to a dysfunctional program regulated by TGFB1 signaling. Infiltrating monocytes differentiated into immunosuppressive macrophages, characterized by the upregulation of suppressive myeloid checkpoints Trem2, Il18bp, and Arg1, over 36 to 48 hours. Treatment with an antagonistic anti-TREM2 antibody reshaped the tumor microenvironment by redirecting the monocyte trajectory toward pro-inflammatory macrophages. Zman-seq is a broadly applicable technology, enabling empirical measurements of differentiation trajectories, which can enhance the development of more efficacious immunotherapies.

Macrophage states: there's a method in the madness.

Single-cell approaches have shone a spotlight on discrete context-specific tissue macrophage states, deconstructed to their most minute details. Machine-learning (ML) approaches have recently challenged that dogma by revealing a context-agnostic continuum of states shared across tissues. Both approaches agree that 'brake' and 'accelerator' macrophage subpopulations must be balanced to achieve homeostasis. Both approaches also highlight the importance of ensemble fluidity as subpopulations switch between wide ranges of accelerator and brake phenotypes to mount the most optimal wholistic response to any threat. A full comprehension of the rules that govern these brake and accelerator states is a promising avenue because it can help formulate precise macrophage re-education therapeutic strategies that might selectively boost or suppress disease-associated states and phenotypes across various tissues.

Atlas of the aging mouse brain reveals white matter as vulnerable foci.

Aging is the key risk factor for cognitive decline, yet the molecular changes underlying brain aging remain poorly understood. Here, we conducted spatiotemporal RNA sequencing of the mouse brain, profiling 1,076 samples from 15 regions across 7 ages and 2 rejuvenation interventions. Our analysis identified a brain-wide gene signature of aging in glial cells, which exhibited spatially defined changes in magnitude. By integrating spatial and single-nucleus transcriptomics, we found that glial aging was particularly accelerated in white matter compared with cortical regions, whereas specialized neuronal populations showed region-specific expression changes. Rejuvenation interventions, including young plasma injection and dietary restriction, exhibited distinct effects on gene expression in specific brain regions. Furthermore, we discovered differential gene expression patterns associated with three human neurodegenerative diseases, highlighting the importance of regional aging as a potential modulator of disease. Our findings identify molecular foci of brain aging, providing a foundation to target age-related cognitive decline.

Towards single cell encapsulation for precision biology and medicine.

The primary impetus of therapeutic cell encapsulation in the past several decades has been to broaden the options for donor cell sources by countering against immune-mediated rejection. However, another significant advantage of encapsulation is to provide donor cells with physiologically relevant cues that become compromised in disease. The advances in biomaterial design have led to the fundamental insight that cells sense and respond to various signals encoded in materials, ranging from biochemical to mechanical cues. The biomaterial design for cell encapsulation is becoming more sophisticated in controlling specific aspects of cellular phenotypes and more precise down to the single cell level. This recent progress offers a paradigm shift by designing single cell-encapsulating materials with predefined cues to precisely control donor cells after transplantation.

User-Controlled 4D Biomaterial Degradation with Substrate-Selective Sortase Transpeptidases for Single-Cell Biology.

Stimuli-responsive biomaterials show great promise for modeling disease dynamics ex vivo with spatiotemporal control over the cellular microenvironment. However, harvesting cells from such materials for downstream analysis without perturbing their state remains an outstanding challenge in 3/4-dimensional (3D/4D) culture and tissue engineering. In this manuscript, a fully enzymatic strategy for hydrogel degradation that affords spatiotemporal control over cell release while maintaining cytocompatibility is introduced. Exploiting engineered variants of the sortase transpeptidase evolved to recognize and selectively cleave distinct peptide sequences largely absent from the mammalian proteome, many limitations implicit to state-of-the-art methods to liberate cells from gels are sidestepped. It is demonstrated that evolved sortase exposure has minimal impact on the global transcriptome of primary mammalian cells and that proteolytic cleavage proceeds with high specificity; incorporation of substrate sequences within hydrogel crosslinkers permits rapid and selective cell recovery with high viability. In composite multimaterial hydrogels, it is shown that sequential degradation of hydrogel layers enables highly specific retrieval of single-cell suspensions for phenotypic analysis. It is expected that the high bioorthogonality and substrate selectivity of the evolved sortases will lead to their broad adoption as an enzymatic material dissociation cue and that their multiplexed use will enable newfound studies in 4D cell culture.

Translational opportunities of single-cell biology in atherosclerosis.

The advent of single-cell biology opens a new chapter for understanding human biological processes and for diagnosing, monitoring, and treating disease. This revolution now reaches the field of cardiovascular disease (CVD). New technologies to interrogate CVD samples at single-cell resolution are allowing the identification of novel cell communities that are important in shaping disease development and direct towards new therapeutic strategies. These approaches have begun to revolutionize atherosclerosis pathology and redraw our understanding of disease development. This review discusses the state-of-the-art of single-cell analysis of atherosclerotic plaques, with a particular focus on human lesions, and presents the current resolution of cellular subpopulations and their heterogeneity and plasticity in relation to clinically relevant features. Opportunities and pitfalls of current technologies as well as the clinical impact of single-cell technologies in CVD patient care are highlighted, advocating for multidisciplinary and international collaborative efforts to join the cellular dots of CVD.

Revisiting the significance of keratin expression in complex epithelia.

A large group of keratin genes (n=54 in the human genome) code for intermediate filament (IF)-forming proteins and show differential regulation in epithelial cells and tissues. Keratin expression can be highly informative about the type of epithelial tissue, differentiation status of constituent cells and biological context (e.g. normal versus diseased settings). The foundational principles underlying the use of keratin expression to gain insight about epithelial cells and tissues primarily originated in pioneering studies conducted in the 1980s. The recent emergence of single cell transcriptomics provides an opportunity to revisit these principles and gain new insight into epithelial biology. Re-analysis of single-cell RNAseq data collected from human and mouse skin has confirmed long-held views regarding the quantitative importance and pairwise regulation of specific keratin genes in keratinocytes of surface epithelia. Furthermore, such analyses confirm and extend the notion that changes in keratin gene expression occur gradually as progenitor keratinocytes commit to and undergo differentiation, and challenge the prevailing assumption that specific keratin combinations reflect a mitotic versus a post-mitotic differentiating state. Our findings provide a blueprint for similar analyses in other tissues, and warrant a more nuanced approach in the use of keratin genes as biomarkers in epithelia.

Identification and characterization of in vitro expanded hematopoietic stem cells.

Hematopoietic stem cells (HSCs) cultured outside the body are the fundamental component of a wide range of cellular and gene therapies. Recent efforts have achieved > 200-fold expansion of functional HSCs, but their molecular characterization has not been possible since the majority of cells are non-HSCs and single cell-initiated cultures have substantial clone-to-clone variability. Using the Fgd5 reporter mouse in combination with the EPCR surface marker, we report exclusive identification of HSCs from non-HSCs in expansion cultures. By directly linking single-clone functional transplantation data with single-clone gene expression profiling, we show that the molecular profile of expanded HSCs is similar to proliferating fetal HSCs and reveals a gene expression signature, including Esam, Prdm16, Fstl1, and Palld, that can identify functional HSCs from multiple cellular states. This "repopulation signature" (RepopSig) also enriches for HSCs in human datasets. Together, these findings demonstrate the power of integrating functional and molecular datasets to better derive meaningful gene signatures and opens the opportunity for a wide range of functional screening and molecular experiments previously not possible due to limited HSC numbers.

Optogenetic actuator - ERK biosensor circuits identify MAPK network nodes that shape ERK dynamics.

Combining single-cell measurements of ERK activity dynamics with perturbations provides insights into the MAPK network topology. We built circuits consisting of an optogenetic actuator to activate MAPK signaling and an ERK biosensor to measure single-cell ERK dynamics. This allowed us to conduct RNAi screens to investigate the role of 50 MAPK proteins in ERK dynamics. We found that the MAPK network is robust against most node perturbations. We observed that the ERK-RAF and the ERK-RSK2-SOS negative feedback operate simultaneously to regulate ERK dynamics. Bypassing the RSK2-mediated feedback, either by direct optogenetic activation of RAS, or by RSK2 perturbation, sensitized ERK dynamics to further perturbations. Similarly, targeting this feedback in a human ErbB2-dependent oncogenic signaling model increased the efficiency of a MEK inhibitor. The RSK2-mediated feedback is thus important for the ability of the MAPK network to produce consistent ERK outputs, and its perturbation can enhance the efficiency of MAPK inhibitors.

New Views of Old Proteins: Clarifying the Enigmatic Proteome.

All human diseases involve proteins, yet our current tools to characterize and quantify them are limited. To better elucidate proteins across space, time, and molecular composition, we provide a >10 years of projection for technologies to meet the challenges that protein biology presents. With a broad perspective, we discuss grand opportunities to transition the science of proteomics into a more propulsive enterprise. Extrapolating recent trends, we describe a next generation of approaches to define, quantify, and visualize the multiple dimensions of the proteome, thereby transforming our understanding and interactions with human disease in the coming decade.

Spatially Defined Gene Delivery into Native Cells with the Red Light-Controlled OptoAAV Technology.

The OptoAAV technology allows spatially defined delivery of transgenes into native target cells down to single-cell resolution by the illumination with cell-compatible and tissue-penetrating red light. The system is based on an adeno-associated viral (AAV) vector of serotype 2 with an engineered capsid (OptoAAV) and a photoreceptor-containing adapter protein mediating the interaction of the OptoAAV with the surface of the target cell in response to low doses of red and far-red light. In this article, we first provide detailed protocols for the production, purification, and analysis of the OptoAAV and the adapter protein. Afterward, we describe in detail the application of the OptoAAV system for the light-controlled transduction of human cells with global and patterned illumination. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Production, purification, and analysis of PhyB-DARPinEGFR adapter protein Basic Protocol 2: Production, purification, and analysis of OptoAAV Basic Protocol 3: Red light-controlled viral transduction with the OptoAAV system Support Protocol: Spatially resolved transduction of two transgenes with the OptoAAV system.

The myogenesis program drives clonal selection and drug resistance in rhabdomyosarcoma.

Rhabdomyosarcoma (RMS) is a pediatric cancer with features of skeletal muscle; patients with unresectable or metastatic RMS fare poorly due to high rates of disease recurrence. Here, we use single-cell and single-nucleus RNA sequencing to show that RMS tumors recapitulate the spectrum of embryonal myogenesis. Using matched patient samples from a clinical trial and orthotopic patient-derived xenografts (O-PDXs), we show that chemotherapy eliminates the most proliferative component with features of myoblasts within embryonal RMS; after treatment, the immature population with features of paraxial mesoderm expands to reconstitute the developmental hierarchy of the original tumor. We discovered that this paraxial mesoderm population is dependent on EGFR signaling and is sensitive to EGFR inhibitors. Taken together, these data serve as a proof of concept that targeting each developmental state in embryonal RMS is an effective strategy for improving outcomes by preventing disease recurrence.

Combined protein and nucleic acid imaging reveals virus-dependent B cell and macrophage immunosuppression of tissue microenvironments.

Understanding the mechanisms of HIV tissue persistence necessitates the ability to visualize tissue microenvironments where infected cells reside; however, technological barriers limit our ability to dissect the cellular components of these HIV reservoirs. Here, we developed protein and nucleic acid in situ imaging (PANINI) to simultaneously quantify DNA, RNA, and protein levels within these tissue compartments. By coupling PANINI with multiplexed ion beam imaging (MIBI), we measured over 30 parameters simultaneously across archival lymphoid tissues from healthy or simian immunodeficiency virus (SIV)-infected nonhuman primates. PANINI enabled the spatial dissection of cellular phenotypes, functional markers, and viral events resulting from infection. SIV infection induced IL-10 expression in lymphoid B cells, which correlated with local macrophage M2 polarization. This highlights a potential viral mechanism for conditioning an immunosuppressive tissue environment for virion production. The spatial multimodal framework here can be extended to decipher tissue responses in other infectious diseases and tumor biology.