Single-cell Labeling Research Articles

High-Throughput Single-Cell Metabolic Labeling, Sorting, and Sequencing of Active Antibiotic-Resistant Bacteria in the Environment.

Active antibiotic-resistant bacteria (ARB) play a major role in spreading antimicrobial resistance (AMR) in the environment; however, they have remained largely unexplored. Herein, we coupled bio-orthogonal noncanonical amino acid tagging with high-throughput fluorescence-activated single-cell sorting (FACS) and sequencing to characterize the phenome and genome of active ARB in complex environmental matrices. Active ARB, conferring resistance to six antibiotics throughout wastewater treatment, were distinguished and quantified. The percentage and concentration of active ARB ranged from 0.28% to 45.3% and from 1.1 × 104 to 2.09 × 107 cells/mL, respectively. Notably, the final effluents retained up to 4.79 × 104 cells/mL of active ARB. Targeted FACS and genomic sequencing revealed a distinct taxonomic composition of active ARB compared with that of the overall population. The coexistence of antibiotic resistome and mobilome in active ARB was also identified, including three high-quality metagenomic assembly genomes assigned to pathogenic bacteria, highlighting the substantial health risks due to their activity, phenotypic resistance, mobility, and pathogenicity. This study advances our understanding of previously overlooked active ARB in the environment by linking their resistance phenotype to their genotype. This high-throughput method will enable efficient quantitative surveillance of active AMR, providing valuable insights into risk control and management.

Retinal neurons establish mosaic patterning by excluding homotypic somata from their dendritic territories

In vertebrate retina, individual neurons of the same type are distributed regularly across the tissue in a pattern known as a mosaic. Establishment of mosaics during development requires cell-cell repulsion among homotypic neurons, but the mechanisms underlying this repulsion remain unknown. Here, we show that two mouse retinal cell types, OFF and ON starburst amacrine cells, establish mosaic spacing by using their dendritic arbors to repel neighboring homotypic somata. Using transgenic tools and single-cell labeling, we identify a developmental period when starburst somata are contacted by neighboring starburst dendrites; these serve to exclude somata from settling within the neighbor's dendritic territory. Dendrite-soma exclusion is mediated by MEGF10, a cell-surface molecule required for starburst mosaic patterning. Our results implicate dendrite-soma exclusion as a key mechanism underlying starburst mosaic spacing and raise the possibility that this could be a general mechanism for mosaic patterning across many cell types and species.

An arginine-rich nuclear localization signal (ArgiNLS) strategy for streamlined image segmentation of single cells

High-throughput volumetric fluorescent microscopy pipelines can spatially integrate whole-brain structure and function at the foundational level of single cells. However, conventional fluorescent protein (FP) modifications used to discriminate single cells possess limited efficacy or are detrimental to cellular health. Here, we introduce a synthetic and nondeleterious nuclear localization signal (NLS) tag strategy, called "Arginine-rich NLS" (ArgiNLS), that optimizes genetic labeling and downstream image segmentation of single cells by restricting FP localization near-exclusively in the nucleus through a poly-arginine mechanism. A single N-terminal ArgiNLS tag provides modular nuclear restriction consistently across spectrally separate FP variants. ArgiNLS performance in vivo displays functional conservation across major cortical cell classes and in response to both local and systemic brain-wide AAV administration. Crucially, the high signal-to-noise ratio afforded by ArgiNLS enhances machine learning-automated segmentation of single cells due to rapid classifier training and enrichment of labeled cell detection within 2D brain sections or 3D volumetric whole-brain image datasets, derived from both staining-amplified and native signal. This genetic strategy provides a simple and flexible basis for precise image segmentation of genetically labeled single cells at scale and paired with behavioral procedures.

Integrating Multiple Bacterial Phenotypes and Bayesian Network for Analyzing Health Risks of Pathogens in Plastisphere.

Plastic pollution represents a critical threat to soil ecosystems and even humans, as plastics can serve as a habitat for breeding and refuging pathogenic microorganisms against stresses. However, evaluating the health risk of plastispheres is difficult due to the lack of risk factors and quantification model. Here, DNA sequencing, single-cell Raman-D2O labeling, and transformation assay were used to quantify key risk factors of plastisphere, including pathogen abundance, phenotypic resistance to various stresses (antibiotic and pesticide), and ability to acquire antibiotic resistance genes. A Bayesian network model was newly introduced to integrate these three factors and infer their causal relationships. Using this model, the risk of pathogen in the plastisphere is found to be nearly 3 magnitudes higher than that in free-living state. Furthermore, this model exhibits robustness for risk prediction, even in the absence of one factor. Our framework offers a novel and practical approach to assessing the health risk of plastispheres, contributing to the management of plastic-related threats to human health.

Structural and Functional Organization of Visual Responses in the Inferior Olive of Larval Zebrafish.

The olivo-cerebellar system plays an important role in vertebrate sensorimotor control. Here, we investigate sensory representations in the inferior olive (IO) of larval zebrafish and their spatial organization. Using single-cell labeling of genetically identified IO neurons, we find that they can be divided into at least two distinct groups based on their spatial location, dendritic morphology, and axonal projection patterns. In the same genetically targeted population, we recorded calcium activity in response to a set of visual stimuli using two-photon imaging. We found that most IO neurons showed direction-selective and binocular responses to visual stimuli and that the functional properties were spatially organized within the IO. Light-sheet functional imaging that allowed for simultaneous activity recordings at the soma and axonal level revealed tight coupling between functional properties, soma location, and axonal projection patterns of IO neurons. Taken together, our results suggest that anatomically defined classes of IO neurons correspond to distinct functional types, and that topographic connections between IO and cerebellum contribute to organization of the cerebellum into distinct functional zones.

Heterogeneity in the projections and excitability of tyraminergic/octopaminergic neurons that innervate the Drosophila reproductive tract.

Aminergic nuclei in mammals are generally composed of relatively small numbers of cells with broad projection patterns. Despite the gross similarity of many individual neurons, recent transcriptomic, anatomic and behavioral studies suggest previously unsuspected diversity. Smaller clusters of aminergic neurons in the model organism Drosophila melanogaster provide an opportunity to explore the ramifications of neuronal diversity at the level of individual cells. A group of approximately 10 tyraminergic/octopaminergic neurons innervates the female reproductive tract in flies and has been proposed to regulate multiple activities required for fertility. The projection patterns of individual neurons within the cluster are not known and it remains unclear whether they are functionally heterogenous. Using a single cell labeling technique, we show that each region of the reproductive tract is innervated by a distinct subset of tyraminergic/octopaminergic cells. Optogenetic activation of one subset stimulates oviduct contractions, indicating that the cluster as a whole is not required for this activity, and underscoring the potential for functional diversity across individual cells. Using whole cell patch clamp, we show that two adjacent and morphologically similar cells are tonically inhibited, but each responds differently to injection of current or activation of the inhibitory GluCl receptor. GluCl appears to be expressed at relatively low levels in tyraminergic/octopaminergic neurons within the cluster, suggesting that it may regulate their excitability via indirect pathways. Together, our data indicate that specific tyraminergic/octopaminergic cells within a relatively homogenous cluster have heterogenous properties and provide a platform for further studies to determine the function of each cell.

Increased PAFAH1B3 was associated with poor prognosis and T-cell exhaustion microenvironment in hepatocellular carcinoma

The link between T-cell exhaustion (TEX) and PAFAH1B3 in hepatocellular carcinoma (HCC) remains unknown, even though both of them are related to overall survival. PAFAH1B3 expression was investigated in TCGA and ICGC data, and 50 paired clinical tissue section samples were used for qRT-PCR and immunohistochemistry (IHC) confirmation. The Immunocell Abundance Identifier (ImmuCellAI) was used to precisely calculate the abundance of TEX, and its accuracy was verified by single-cell RNA-seq and labeling of CD8 + T cells in clinical tissue sections. The IMVigor 210 cohort was used to demonstrate the predictive value of PAFAH1B3 for immunotherapy efficacy. Increased PAFAH1B3 is a standalone effector of poor prognosis in HCC patients. Patients who had greater PAFAH1B3 levels had more TEX infiltration. PAFAH1B3 expression was increased in TEX in the single-cell RNA-seq data. Patients with high PAFAH1B3 expression were more likely to respond favorably to PD1/PD-L1 treatment. In conclusion, PAFAH1B3 is closely related to TEX in the tumor microenvironment (TME) and can be a useful indicator for PD1/PD-L1 therapy.

Modular interneuron circuits control motion sensitivity in the mouse retina

Neural computations arise from highly precise connections between specific types of neurons. Retinal ganglion cells (RGCs) with similar stratification patterns are positioned to receive similar inputs but often display different response properties. In this study, we used intersectional mouse genetics to achieve single-cell type labeling and identified an object motion sensitive (OMS) AC type, COMS-AC(counter-OMS AC). Optogenetic stimulation revealed that COMS-AC makes glycinergic synapses with the OMS-insensitive HD2p-RGC, while chemogenetic inactivation showed that COMS-AC provides inhibitory control to HD2p-RGC during local motion. This local inhibition, combined with the inhibitory drive from TH2-AC during global motion, explains the OMS-insensitive feature of HD2p-RGC. In contrast, COMS-AC fails to make synapses with W3(UHD)-RGC, allowing it to exhibit OMS under the control of VGlut3-AC and TH2-AC. These findings reveal modular interneuron circuits that endow structurally similar RGC types with different responses and present a mechanism for redundancy-reduction in the retina to expand coding capacity.

Primed conversion: The emerging player of precise and nontoxic photoconversion.

In 2015, we reported primed conversion, a novel way to convert green-to-red photoconvertible fluorescent proteins, which emerges as a powerful tool for precision optical imaging. Primed conversion uses the intercept of blue and red-to-far-red light instead of traditional violet or near-UV light illumination which offers a series of advantages. Here, we review the fundamental principles and applications of primed conversion with a focus on its use in single-cell labelling and lineage tracing. We provide a historical perspective of lineage tracing techniques, thereby covering basic principles of fluorescence, photoconvertible fluorescent proteins, and eventually primed conversion. We then present the molecular requirements for primed conversion to take place and showcase how it can be used for dual-colour high-fidelity lineage tracing. Further, we discuss potential future developments of the primed conversion imaging toolkit that can benefit the study of both development and disease progression.

Whole human-brain mapping of single cortical neurons for profiling morphological diversity and stereotypy.

Quantifying neuron morphology and distribution at the whole-brain scale is essential to understand the structure and diversity of cell types. It is exceedingly challenging to reuse recent technologies of single-cell labeling and whole-brain imaging to study human brains. We propose adaptive cell tomography (ACTomography), a low-cost, high-throughput, and high-efficacy tomography approach, based on adaptive targeting of individual cells. We established a platform to inject dyes into cortical neurons in surgical tissues of 18 patients with brain tumors or other conditions and one donated fresh postmortem brain. We collected three-dimensional images of 1746 cortical neurons, of which 852 neurons were reconstructed to quantify local dendritic morphology, and mapped to standard atlases. In our data, human neurons are more diverse across brain regions than by subject age or gender. The strong stereotypy within cohorts of brain regions allows generating a statistical tensor field of neuron morphology to characterize anatomical modularity of a human brain.

Drebrin Regulates Collateral Axon Branching in Cortical Layer II/III Somatosensory Neurons.

Proper cortical lamination is essential for cognition, learning, and memory. Within the somatosensory cortex, pyramidal excitatory neurons elaborate axon collateral branches in a laminar-specific manner that dictates synaptic partners and overall circuit organization. Here, we leverage both male and female mouse models, single-cell labeling and imaging approaches to identify intrinsic regulators of laminar-specific collateral, also termed interstitial, axon branching. We developed new approaches for the robust, sparse, labeling of Layer II/III pyramidal neurons to obtain single-cell quantitative assessment of axon branch morphologies. We combined these approaches with cell-autonomous loss-of-function (LOF) and overexpression (OE) manipulations in an in vivo candidate screen to identify regulators of cortical neuron axon branch lamination. We identify a role for the cytoskeletal binding protein drebrin (Dbn1) in regulating Layer II/III cortical projection neuron (CPN) collateral axon branching in vitro LOF experiments show that Dbn1 is necessary to suppress the elongation of Layer II/III CPN collateral axon branches within Layer IV, where axon branching by Layer II/III CPNs is normally absent. Conversely, Dbn1 OE produces excess short axonal protrusions reminiscent of nascent axon collaterals that fail to elongate. Structure-function analyses implicate Dbn1S142 phosphorylation and Dbn1 protein domains known to mediate F-actin bundling and microtubule (MT) coupling as necessary for collateral branch initiation upon Dbn1 OE. Taken together, these results contribute to our understanding of the molecular mechanisms that regulate collateral axon branching in excitatory CPNs, a key process in the elaboration of neocortical circuit formation.SIGNIFICANCE STATEMENT Laminar-specific axon targeting is essential for cortical circuit formation. Here, we show that the cytoskeletal protein drebrin (Dbn1) regulates excitatory Layer II/III cortical projection neuron (CPN) collateral axon branching, lending insight into the molecular mechanisms that underlie neocortical laminar-specific innervation. To identify branching patterns of single cortical neurons in vivo, we have developed tools that allow us to obtain detailed images of individual CPN morphologies throughout postnatal development and to manipulate gene expression in these same neurons. Our results showing that Dbn1 regulates CPN interstitial axon branching both in vivo and in vitro may aid in our understanding of how aberrant cortical neuron morphology contributes to dysfunctions observed in autism spectrum disorder and epilepsy.

Synergising single-cell resolution and 4sU labelling boosts inference of transcriptional bursting

Despite the recent rise of RNA-seq datasets combining single-cell (sc) resolution with 4-thiouridine (4sU) labelling, analytical methods exploiting their power to dissect transcriptional bursting are lacking. Here, we present a mathematical model and Bayesian inference implementation to facilitate genome-wide joint parameter estimation and confidence quantification (R package: burstMCMC). We demonstrate that, unlike conventional scRNA-seq, 4sU scRNA-seq resolves temporal parameters and furthermore boosts inference of dimensionless parameters via a synergy between single-cell resolution and 4sU labelling. We apply our method to published 4sU scRNA-seq data and linked with ChIP-seq data, we uncover previously obscured associations between different parameters and histone modifications.

Biocytin-Labeling in Whole-Cell Recording: Electrophysiological and Morphological Properties of Pyramidal Neurons in CYLD-Deficient Mice.

Biocytin, a chemical compound that is an amide formed from the vitamin biotin and the amino acid L-lysine, has been used as a histological dye to stain nerve cells. Electrophysiological activity and morphology are two key characteristics of neurons, but revealing both the electrophysiological and morphological properties of the same neuron is challenging. This article introduces a detailed and easy-to-operate procedure for single-cell labeling in combination with whole-cell patch-clamp recording. Using a recording electrode filled with a biocytin-containing internal solution, we demonstrate the electrophysiological and morphological characteristics of pyramidal (PNs), medial spiny (MSNs) and parvalbumin neurons (PVs) in brain slices, where the electrophysiological and morphological properties of the same individual cell are elucidated. We first introduce a protocol for whole-cell patch-clamp recording in various neurons, coupled with the intracellular diffusion of biocytin delivered by the glass capillary of the recording electrode, followed by a post hoc procedure to reveal the architecture and morphology of biocytin-labeled neurons. An analysis of action potentials (APs) and neuronal morphology, including the dendritic length, number of intersections, and spine density of biocytin-labeled neurons, were performed using ClampFit and Fiji Image (ImageJ), respectively. Next, to take advantage of the techniques introduced above, we uncovered defects in the APs and the dendritic spines of PNs in the primary motor cortex (M1) of deubiquitinase cylindromatosis (CYLD) knock-out (Cyld-/-) mice. In summary, this article provides a detailed methodology for revealing the morphology as well as the electrophysiological activity of a single neuron that will have many applications in neurobiology.

Building and Characterization of an Affordable diOlistic Device for Single-Cell Labeling in Rodent and Non-Human Primate Brain Slices.

In the brain, cell morphology often reflects function and thus provides a first glance into cell-specific changes in health and disease. Studying the morphology of individual cells, including neurons and glia, is essential to fully understand brain connectivity and changes in disease states. Many recent morphological studies of brain cells have relied on transgenic animals and viral vectors to label individual cells. However, transgenic animals are not always available, and in non-human primate (NHP) models, viral transduction poses several practical and financial challenges, limiting the number of researchers that can thoroughly investigate cell morphology in NHP or other non-transgenic animals. The diOlistic system for delivering fluorescent lipophilic dye-coated gold or tungsten particles into brain tissue has been used to label single cells, but the currently available systems are expensive, have limited applications, and are rare in laboratories. Investigations of cell morphology without transgenic or viral approaches rely on immunohistochemical markers that may not reveal structural detail, such as in astrocytes. To overcome these practical limitations to expand our understanding of cell morphology across species with an emphasis on astrocytes, we constructed a low-cost ballistic method to deliver dye-coated gold or tungsten particles into NHP and rodent brain slices. We have optimized the tissue processing parameters to achieve penetration of DiI-coated particles, allowing for the complete reconstruction of individual cells within a brain slice. While we report on astrocytes in rodent and NHP brain slices, this protocol can be adapted and implemented across species and tissue types to evaluate cell morphology. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Building the diOlistic device Basic Protocol 2: Preparation of dye "bullet" carriers Basic Protocol 3: Perfusion, brain sectioning, and diOlistic labeling Alternate Protocol: Immunohistochemical labeling of sections prior to diOlistic bombardment.

Synergising single-cell resolution and 4sU labelling boosts inference of transcriptional bursting

Synergising single-cell resolution and 4sU labelling boosts inference of transcriptional bursting

Synergising single-cell resolution and 4sU labelling boosts inference of transcriptional bursting

Synergising single-cell resolution and 4sU labelling boosts inference of transcriptional bursting

Cerebrospinal fluid-contacting neuron tracing reveals structural and functional connectivity for locomotion in the mouse spinal cord.

Cerebrospinal fluid-contacting neurons (CSF-cNs) are enigmatic mechano- or chemosensory cells lying along the central canal of the spinal cord. Recent studies in zebrafish larvae and lampreys have shown that CSF-cNs control postures and movements via spinal connections. However, the structures, connectivity, and functions in mammals remain largely unknown. Here we developed a method to genetically target mouse CSF-cNs that highlighted structural connections and functions. We first found that intracerebroventricular injection of adeno-associated virus with a neuron-specific promoter and Pkd2l1-Cre mice specifically labeled CSF-cNs. Single-cell labeling of 71 CSF-cNs revealed rostral axon extensions of over 1800 μm in unmyelinated bundles in the ventral funiculus and terminated on CSF-cNs to form a recurrent circuitry, which was further determined by serial electron microscopy and electrophysiology. CSF-cNs were also found to connect with axial motor neurons and premotor interneurons around the central canal and within the axon bundles. Chemogenetic CSF-cNs inactivation reduced speed and step frequency during treadmill locomotion. Our data revealed the basic structures and connections of mouse CSF-cNs to control spinal motor circuits for proper locomotion. The versatile methods developed in this study will contribute to further understanding of CSF-cN functions in mammals.

Single-Cell Labeling Strategies to Dissect Neuronal Structures and Local Functions.

The brain network consists of ten billion neurons and is the most complex structure in the universe. Understanding the structure of complex brain networks and neuronal functions is one of the main goals of modern neuroscience. Since the seminal invention of Golgi staining, single-cell labeling methods have been among the most potent approaches for dissecting neuronal structures and neural circuits. Furthermore, the development of sparse single-cell transgenic methods has enabled single-cell gene knockout studies to examine the local functions of various genes in neural circuits and synapses. Here, we review non-transgenic single-cell labeling methods and recent advances in transgenic strategies for sparse single neuronal labeling. These methods and strategies will fundamentally contribute to the understanding of brain structure and function.

Cre recombinase microinjection for single-cell tracing and localised gene targeting.

Tracing and manipulating cells in embryos are essential to understand development. Lipophilic dye microinjections, viral transfection and iontophoresis have been key to map the origin of the progenitor cells that form the different organs in the post-implantation mouse embryo. These techniques require advanced manipulation skills and only iontophoresis, a demanding approach of limited efficiency, has been used for single-cell labelling. Here, we perform lineage tracing and local gene ablation using cell-permeant Cre recombinase (TAT-Cre) microinjection. First, we map the fate of undifferentiated progenitors to the different heart chambers. Then, we achieve single-cell recombination by titrating the dose of TAT-Cre, which allows clonal analysis of nascent mesoderm progenitors. Finally, injecting TAT-Cre to Mycnflox/flox embryos in the primitive heart tube revealed that Mycn plays a cell-autonomous role in maintaining cardiomyocyte proliferation. This tool will help researchers identify the cell progenitors and gene networks involved in organ development, helping to understand the origin of congenital defects.

Evaluation of single-cell RNAseq labelling algorithms using cancer datasets.

Single-cell RNA sequencing (scRNA-seq) clustering and labelling methods are used to determine precise cellular composition of tissue samples. Automated labelling methods rely on either unsupervised, cluster-based approaches or supervised, cell-based approaches to identify cell types. The high complexity of cancer poses a unique challenge, as tumor microenvironments are often composed of diverse cell subpopulations with unique functional effects that may lead to disease progression, metastasis and treatment resistance. Here, we assess 17 cell-based and 9 cluster-based scRNA-seq labelling algorithms using 8 cancer datasets, providing a comprehensive large-scale assessment of such methods in a cancer-specific context. Using several performance metrics, we show that cell-based methods generally achieved higher performance and were faster compared to cluster-based methods. Cluster-based methods more successfully labelled non-malignant cell types, likely because of a lack of gene signatures for relevant malignant cell subpopulations. Larger cell numbers present in some cell types in training data positively impacted prediction scores for cell-based methods. Finally, we examined which methods performed favorably when trained and tested on separate patient cohorts in scenarios similar to clinical applications, and which were able to accurately label particularly small or under-represented cell populations in the given datasets. We conclude that scPred and SVM show the best overall performances with cancer-specific data and provide further suggestions for algorithm selection. Our analysis pipeline for assessing the performance of cell type labelling algorithms is available in https://github.com/shooshtarilab/scRNAseq-Automated-Cell-Type-Labelling.