Activity Of Individual Cells Research Articles

Timing of resting zone parathyroid hormone-related protein expression affects maintenance of the growth plate during secondary ossification: a computational study.

Secondary ossification and maintenance of the growth plate are crucial aspects of long bone formation. Parathyroid hormone-related protein (PTHrP) has been implicated as a key factor in maintaining the growth plate, and studies suggest that PTHrP expression in the resting zone is closely related with formation of the secondary ossification center (SOC). However, details of the relationship between resting zone PTHrP expression and preservation of the growth plate remain unclear. In this study, we aim to investigate the role of resting zone PTHrP expression on maintenance of the growth plate using a computational method. We extend an existing continuum-based particle model of tissue morphogenesis to include PTHrP and Indian hedgehog (Ihh) signaling, allowing the model to capture biochemical and mechanical regulation of individual cell activities. Our model indicates that the timing of resting zone PTHrP expression-specifically the rate of increase in production at the onset of SOC formation-is potentially a crucial mechanism for maintenance of the growth plate.

Transport in cellular aggregates described by fluctuating hydrodynamics

Biological functionality of cellular aggregates is largely influenced by the activity and displacements of individual constituent cells. From a theoretical perspective this activity can be characterized by hydrodynamic transport coefficients of diffusivity and conductivity. Motivated by the clustering dynamics of bacterial microcolonies we propose a model of active multicellular aggregates and use recently developed macroscopic fluctuation theory to derive a fluctuating hydrodynamics for this model system. Both semianalytic theory and microscopic simulations show that the hydrodynamic transport coefficients are affected by nonequilibrium microscopic parameters and significantly decrease inside of the clusters. We further find that the Einstein relation connecting the transport coefficients and fluctuations breaks down in the parameter regime where the detailed balance is not satisfied. This study offers valuable tools for experimental investigation of hydrodynamic transport in other systems of cellular aggregates such as tumor spheroids and organoids. Published by the American Physical Society 2024

A simple MATLAB toolbox for analyzing calcium imaging data in vitro and in vivo

BackgroundFluorescence imaging of calcium dynamics in neuronal populations is powerful because it offers a way of relating the activity of individual cells to the broader population of nearby cells. The method’s growth across neuroscience has particularly been driven by the introduction of sophisticated mathematical techniques related to motion correction, image registration, cell detection, spike estimation, and population characterization. However, for many researchers, making good use of these techniques has been difficult because they have been devised by different workers and impose differing – and sometimes stringent – technical requirements on those who seek to use them. New methodWe have built a simple toolbox of analysis routines that encompass the complete workflow for analyzing calcium imaging data. The workflow begins with preprocessing of data, includes motion correction and longitudinal image registration, detects active cells using constrained non-negative matrix factorization, and offers multiple options for estimating spike times and characterizing population activity. The routines can be navigated through a simple graphical user interface. Although written in MATLAB, a standalone version for researchers who do not have access to MATLAB is included. ResultsWe have used the toolbox on two very different preparations: spontaneously active brain slices and microendoscopic imaging from deep structures in awake behaving mice. In both cases, the toolbox offered a seamless flow from raw data all the way through to prepared graphs. ConclusionThe field of calcium imaging has benefited from the development of numerous innovative mathematical techniques. Here we offer a simple toolbox that allows ordinary researchers to fully exploit these techniques.

SMAD4 promotes somatic-germline contact during murine oocyte growth.

Development of the mammalian oocyte requires physical contact with the surrounding granulosa cells of the follicle, which provide it with essential nutrients and regulatory signals. This contact is achieved through specialized filopodia, termed transzonal projections (TZPs), that extend from the granulosa cells to the oocyte surface. Transforming growth factor (TGFβ) family ligands produced by the oocyte increase the number of TZPs, but how they do so is unknown. Using an inducible Cre recombinase strategy together with expression of green fluorescent protein to verify Cre activity in individual cells, we examined the effect of depleting the canonical TGFβ mediator, SMAD4, in mouse granulosa cells. We observed a 20-50% decrease in the total number of TZPs in SMAD4-depleted granulosa cell-oocyte complexes, and a 50% decrease in the number of newly generated TZPs when the granulosa cells were reaggregated with wild-type oocytes. Three-dimensional image analysis revealed that TZPs of SMAD4-depleted cells were longer than controls and more frequently oriented towards the oocyte. Strikingly, the transmembrane proteins, N-cadherin and Notch2, were reduced by 50% in SMAD4-depleted cells. SMAD4 may thus modulate a network of cell adhesion proteins that stabilize the attachment of TZPs to the oocyte, thereby amplifying signalling between the two cell types.

Magnetic voluntary head-fixation in transgenic rats enables lifespan imaging of hippocampal neurons

The precise neural mechanisms within the brain that contribute to the remarkable lifetime persistence of memory are not fully understood. Two-photon calcium imaging allows the activity of individual cells to be followed across long periods, but conventional approaches require head-fixation, which limits the type of behavior that can be studied. We present a magnetic voluntary head-fixation system that provides stable optical access to the brain during complex behavior. Compared to previous systems that used mechanical restraint, there are no moving parts and animals can engage and disengage entirely at will. This system is failsafe, easy for animals to use and reliable enough to allow long-term experiments to be routinely performed. Animals completed hundreds of trials per session of an odor discrimination task that required 2–4 s fixations. Together with a reflectance fluorescence collection scheme that increases two-photon signal and a transgenic Thy1-GCaMP6f rat line, we are able to reliably image the cellular activity in the hippocampus during behavior over long periods (median 6 months), allowing us track the same neurons over a large fraction of animals’ lives (up to 19 months).

Network representation of multicellular activity in pancreatic islets: Technical considerations for functional connectivity analysis.

Within the islets of Langerhans, beta cells orchestrate synchronized insulin secretion, a pivotal aspect of metabolic homeostasis. Despite the inherent heterogeneity and multimodal activity of individual cells, intercellular coupling acts as a homogenizing force, enabling coordinated responses through the propagation of intercellular waves. Disruptions in this coordination are implicated in irregular insulin secretion, a hallmark of diabetes. Recently, innovative approaches, such as integrating multicellular calcium imaging with network analysis, have emerged for a quantitative assessment of the cellular activity in islets. However, different groups use distinct experimental preparations, microscopic techniques, apply different methods to process the measured signals and use various methods to derive functional connectivity patterns. This makes comparisons between findings and their integration into a bigger picture difficult and has led to disputes in functional connectivity interpretations. To address these issues, we present here a systematic analysis of how different approaches influence the network representation of islet activity. Our findings show that the choice of methods used to construct networks is not crucial, although care is needed when combining data from different islets. Conversely, the conclusions drawn from network analysis can be heavily affected by the pre-processing of the time series, the type of the oscillatory component in the signals, and by the experimental preparation. Our tutorial-like investigation aims to resolve interpretational issues, reconcile conflicting views, advance functional implications, and encourage researchers to adopt connectivity analysis. As we conclude, we outline challenges for future research, emphasizing the broader applicability of our conclusions to other tissues exhibiting complex multicellular dynamics.

Abstract 2343: Adapting gene set enrichment analysis to single cell data

Abstract Gene Set Enrichment Analysis (GSEA) is a method for quantifying the activation of pathways and processes in gene expression data. GSEA works by ranking genes and testing if genes in annotated gene sets representing molecular pathways are overrepresented at the top or bottom of the ranked list. Standard GSEA assumes a gene-by-sample matrix with samples falling in two phenotype class labels and ranks genes based on correlation of expression and sample class labels. Single sample (ssGSEA) uses a similar approach to enrichment scoring but ranks genes in a single sample based on their expression. There has been recent interest in using the ssGSEA modality to measure pathway activity in individual cells from single cell RNA-sequencing (scRNA-seq) data. However, we have observed that ssGSEA scores in scRNA-seq cells are prone to uncertainty due to the characteristic sparsity of scRNA-seq data. This is because sparse data leads to large groups of tied genes, that is, genes with equal expression and subsequently equivalent positions in the ranked list. Because ssGSEA, which was designed for bulk gene expression technologies which yield much less sparse data, breaks ties arbitrarily, these ties can lead to variability in enrichment scores that is purely algorithmic and not a result of the underlying biology. To address this issue, we performed benchmarking to characterize the stability of scores using different enrichment scoring statistics, normalization methods, and aggregation of similar single cells. We have implemented the best practices identified using this analysis as Single Cell GSEA (scGSEA), a software tool which we will make freely available to researchers as open-source software to enable robust gene set enrichment scoring in scRNA-seq data. Citation Format: Alexander T. Wenzel, John Jun, Jill P. Mesirov. Adapting gene set enrichment analysis to single cell data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2343.

Optical Photothermal Infrared - Fluorescence In Situ Hybridization (OPTIR-FISH).

Understanding the metabolic activities of individual cells within complex communities is critical for unraveling their role in human disease. Here, we present a comprehensive protocol for simultaneous cell identification and metabolic analysis with the OPTIR-FISH platform by combining rRNA-tagged FISH probes and isotope-labeled substrates. Fluorescence imaging provides cell identification by the specific binding of rRNA-tagged FISH probes, while OPTIR imaging provides metabolic activities within single cells by isotope-induced red shift on OPTIR spectra. Using bacteria cultured with 13C-glucose as a test bed, the protocol outlines microbial culture with isotopic labeling, fluorescence in situ hybridization (FISH), sample preparation, optimization of the OPTIR-FISH imaging setup, and data acquisition. We also demonstrate how to perform image analysis and interpret spectral data at the single-cell level with high throughput. This protocol's standardized and detailed nature will greatly facilitate its adoption by researchers from diverse backgrounds and disciplines within the broad single-cell metabolism research community.

The Photoprotective Behavior of a Motile Benthic Diatom as Elucidated from the Interplay Between Cell Motility and Physiological Responses to a Light Microgradient Using a Novel Experimental Setup

It has long been hypothesized that benthic motile pennate diatoms use phototaxis to optimize photosynthesis and minimize photoinhibitory damage by adjusting their position within vertical light gradients in coastal benthic sediments. However, experimental evidence to test this hypothesis remains inconclusive, mainly due to methodological difficulties in studying cell behavior and photosynthesis over realistic spatial microscale gradients of irradiance and cell position. In this study, a novel experimental approach was developed and used to test the hypothesis of photosynthesis optimization through motility, based on the combination of single-cell in vivo chlorophyll fluorometry and microfluidic chips. The approach allows the concurrent study of behavior and photosynthetic activity of individual cells of the epipelic diatom species Craspedostauros britannicus exposed to a light microgradient of realistic dimensions, simulating the irradiance and distance scales of light microgradients in benthic sediments. Following exposure to light, (i) cells explored their light environment before initiating light-directed motility; (ii) cells used motility to lower their light dose, when exposed to the highest light intensities; and (iii) motility was combined with reversible non-photochemical quenching, to allow cells to avoid photoinhibition. The results of this proof-of-concept study not only strongly support the photoprotective nature of photobehavior in the studied species but also revealed considerable variability in how individual cells reacted to a light microgradient. The experimental setup can be readily applied to study motility and photosynthetic light responses of other diatom species or natural assemblages, as well as other photoautotrophic motile microorganisms, broadening the toolset for experimental microbial ecology research.

Peak-agnostic high-resolution cis-regulatory circuitry mapping using single cell multiome data.

Single same cell RNAseq/ATACseq multiome data provide unparalleled potential to develop high resolution maps of the cell-type specific transcriptional regulatory circuitry underlying gene expression. We present CREMA, a framework that recovers the full cis-regulatory circuitry by modeling gene expression and chromatin activity in individual cells without peak-calling or cell type labeling constraints. We demonstrate that CREMA overcomes the limitations of existing methods that fail to identify about half of functional regulatory elements which are outside the called chromatin 'peaks'. These circuit sites outside called peaks are shown to be important cell type specific functional regulatory loci, sufficient to distinguish individual cell types. Analysis of mouse pituitary data identifies a Gata2-circuit for the gonadotrope-enriched disease-associated Pcsk1 gene, which is experimentally validated by reduced gonadotrope expression in a gonadotrope conditional Gata2-knockout model. We present a web accessible human immune cell regulatory circuit resource, and provide CREMA as an R package.

SEVtras delineates small extracellular vesicles at droplet resolution from single-cell transcriptomes.

Small extracellular vesicles (sEVs) are emerging as pivotal players in a wide range of physiological and pathological processes. However, a pressing challenge has been the lack of high-throughput techniques capable of unraveling the intricate heterogeneity of sEVs and decoding the underlying cellular behaviors governing sEV secretion. Here we leverage droplet-based single-cell RNA sequencing (scRNA-seq) and introduce an algorithm, SEVtras, to identify sEV-containing droplets and estimate the sEV secretion activity (ESAI) of individual cells. Through extensive validations on both simulated and real datasets, we demonstrate SEVtras' efficacy in capturing sEV-containing droplets and characterizing the secretion activity of specific cell types. By applying SEVtras to four tumor scRNA-seq datasets, we further illustrate that the ESAI can serve as a potent indicator of tumor progression, particularly in the early stages. With the increasing importance and availability of scRNA-seq datasets, SEVtras holds promise in offering valuable extracellular insights into the cell heterogeneity.

Moving horizon estimation of Amnioserosa cell dynamics during Drosophila dorsal closure

Dorsal closure is a morphogenetic process similar to wound healing, whereby a gap in the epithelium is closed through the coordination of the elongation of epidermal cells and contraction of Amnioserosa cells (AS). Throughout the early stages of this process, the AS cells exhibit fluctuations of their apical area which provides an ideal system to understand contractile epithelia, both in terms of the cellular mechanisms and how tissue behavior emerges from the activity of individual cells. In this work, we present a vertex-based model to explore the dynamics of Amnioserosa cells and provide insights into the regulation of dorsal closure. Towards this end, moving horizon estimation is used to predict the mechanics of AS cell oscillations and contractions modeled as a quasi-linear parameter-varying system with bounded unknown parameters. We perform estimation through the minimization of the least-squares moving horizon cost with respect to both state variables and unknown parameters simultaneously. For simulation purposes, data from the work published in [13] are used to evaluate the performance of moving-horizon estimation as compared to the extended Kalman filter. The comparative analysis reveals that the moving-horizon approach performs better than those provided by the Kalman filtering and with an increased robustness to measurement and process noises.

Parallel Dielectrophoretic Capture, Isolation, and Electrical Lysis of Individual Breast Cancer Cells to Assess Variability in Enzymatic Activity.

Tumor cell heterogeneity drives disease progression and response to therapy, and therefore, there is a need for single-cell analysis methods. In this paper, we present an integrated, scalable method to analyze enzymatic activity in many individual cancer cells at once. The reported method uses dielectrophoresis (DEP) to selectively capture tumor cells at wireless electrodes aligned to an overlying array of cell-sized micropockets. Following hydrodynamic transfer of the captured cells into microfluidic chambers, the chambers are fluidically isolated and sealed with a hydrophobic ionic liquid, which possesses sufficient conductivity to allow for subsequent electrical lysis of the cells to access their contents for enzymatic assay. The wireless electrodes have an interlocking spiral design that ensures successful electrical lysis regardless of the location of the cell within the chamber. Here, breast cancer cells are assessed for β-galactosidase through its activation of a fluorogenic substrate. A key point is that the fluorogenic assay solution was optimized to allow for dielectrophoretic cell capture, thereby obviating the need for a solution exchange step. Our approach has several distinct advantages including a high rate of single-cell capture, a capture efficiency that is independent of the dimensions of the reaction chambers, no need for mechanical closure of reaction volumes, and no observed cross-talk. In this study, first, the steps of cell capture, transfer, and lysis are established on this platform in the presence of the optimized assay solution. We then quantify the increase in fluorescence intensity obtained over the duration of the enzymatic assay of individual cells. Finally, this method is applied to the analysis of β-galactosidase activity in 258 individual MDA-MB-231 breast cancer cells, revealing heterogeneity in expression of this enzyme in this cell line. We expect that the adaptability of this method will allow for expanded studies of single-cell enzymatic expression and activity. This will in turn open avenues of research into cancer cell heterogeneity in metabolism, invasiveness, and drug response. The ability to study these features of cancer at the single-cell level raises the possibility for treatment plans tailored to target the specific combinations of cell subpopulations present in tumors. Furthermore, we expect that this method can be adapted to uses outside of cancer research, such as studies of neuron metabolism, pathogenesis in bacteria, and stem cell development.

All-optical physiology resolves a synaptic basis for behavioral timescale plasticity

Learning has been associated with modifications of synaptic and circuit properties, but the precise changes storing information in mammals have remained largely unclear. We combined genetically targeted voltage imaging with targeted optogenetic activation and silencing of pre- and post-synaptic neurons to study the mechanisms underlying hippocampal behavioral timescale plasticity. In mice navigating a virtual-reality environment, targeted optogenetic activation of individual CA1 cells at specific places induced stable representations of these places in the targeted cells. Optical elicitation, recording, and modulation of synaptic transmission in behaving mice revealed that activity in presynaptic CA2/3 cells was required for the induction of plasticity in CA1 and, furthermore, that during induction of these place fields in single CA1 cells, synaptic input from CA2/3 onto these same cells was potentiated. These results reveal synaptic implementation of hippocampal behavioral timescale plasticity and define a methodology to resolve synaptic plasticity during learning and memory in behaving mammals.

Spatial cognition in birds

Finding the kitchen refrigerator in the middle of a sleepless night or arriving at the home parking lot at the end of a daily drive are things that we mostly take for granted. However, such feats rely on complex brain computations that integrate multiple environmental and internal cues. Together these computations mediate the process referred to as spatial cognition, the study of which has been one of the most active research fields in modern neuroscience. In the early 1970s, John O'Keefe recorded the activity of individual cells in the hippocampus of a freely moving rat: he found cells that fired action potentials when the rat passed through a specific place in the environment. Examining the activity pattern of such 'place cells', he concluded that the hippocampus may contain a 'cognitive map' that represents the animal's location in its proximate environment. Since O'Keefe's seminal discovery about half a century ago, extensive research has led to a detailed characterization of hippocampal space processing in rats and other mammalian species.

Subepicardial ischemia vs cardiac memory after tachycardia by intranodal reentry. case report and literature review

Cardiac memory is an electrophysiological property that is expressed as persistent electrophysiological changes in response to variations in the rate and sequence of cardiac electric activation and is defined as the persistent changes of the T wave on the electrocardiogram after a period of rhythms of wide QRS widened, and that becomes evident once the normal ventricular activation pattern is restored.1 The first evidence of its existence arises from case reports where changes in the polarity of the T wave were observed after transient episodes of tachyarrhythmias. Subsequently, it was demonstrated how ventricular activation by external sources in a prolonged way induces persistent changes in the electrocardiogram, and those changes persist after eliminating this source.6,8 Electrical memory can occur in a short and long term, when it is short-term, the changes are due to the modulation of the electrical activity of individual cardiac cells or cell to cell interaction, while long-term memory involves the synthesis of proteins and / or structural changes.8

Reversible Photocontrol of Dopaminergic Transmission in Wild-Type Animals.

Understanding the dopaminergic system is a priority in neurobiology and neuropharmacology. Dopamine receptors are involved in the modulation of fundamental physiological functions, and dysregulation of dopaminergic transmission is associated with major neurological disorders. However, the available tools to dissect the endogenous dopaminergic circuits have limited specificity, reversibility, resolution, or require genetic manipulation. Here, we introduce azodopa, a novel photoswitchable ligand that enables reversible spatiotemporal control of dopaminergic transmission. We demonstrate that azodopa activates D1-like receptors in vitro in a light-dependent manner. Moreover, it enables reversibly photocontrolling zebrafish motility on a timescale of seconds and allows separating the retinal component of dopaminergic neurotransmission. Azodopa increases the overall neural activity in the cortex of anesthetized mice and displays illumination-dependent activity in individual cells. Azodopa is the first photoswitchable dopamine agonist with demonstrated efficacy in wild-type animals and opens the way to remotely controlling dopaminergic neurotransmission for fundamental and therapeutic purposes.

Basal and Stress-Induced Network Activity in the Adrenal Medulla In Vivo.

The adrenal medulla plays a critical role in mammalian homeostasis and the stress response. It is populated by clustered chromaffin cells that secrete epinephrine or norepinephrine along with peptides into the bloodstream affecting distant target organs. Despite been heavily studied, the central control of adrenal medulla and in-situ spatiotemporal responsiveness remains poorly understood. For this work, we continuously monitored the electrical activity of individual adrenomedullary chromaffin cells in the living anesthetized rat using multielectrode arrays. We measured the chromaffin cell activity under basal and physiological stress conditions and characterized the functional micro-architecture of the adrenal medulla. Under basal conditions, chromaffin cells fired action potentials with frequencies between ~0.2 and 4 Hz. Activity was almost completely driven by sympathetic inputs coming through the splanchnic nerve. Chromaffin cells were organized into independent local networks in which cells fired in a specific order, with latencies from hundreds of microseconds to a few milliseconds. Electrical stimulation of the splanchnic nerve evoked almost exactly the same spatiotemporal firing patterns that occurred spontaneously. Hypoglycemic stress, induced by insulin administration resulted in increased activity of a subset of the chromaffin cells. In contrast, respiratory arrest induced by lethal anesthesia resulted in an increase in the activity of virtually all chromaffin cells before cessation of all activity. These results suggest a stressor-specific activation of adrenomedullary chromaffin cell networks and revealed a surprisingly complex electrical organization that likely reflects the dynamic nature of the adrenal medulla’s neuroendocrine output during basal conditions and during different types of physiological stress.

TNF-α orchestrates the specific loss of tolerogenic dendritic cells during an acute maturation process in vivo

Abstract The recognition of pathogen-associated molecular patterns (PAMPs) through the corresponding pattern recognition receptors (PRRs) induces activation of individual conventional dendritic cells (cDC) in a process often referred to as maturation that results in a change from tolerogenic to immunogenic functions. In the absence of pro-inflammatory conditions (steady state), tolerogenic cDC that are present in systemic peripheral lymphoid organs promote tolerance that limits subsequent immune responses. However, the fate of such tolerogenic cDC in the presence of specific pro-inflammatory signals remains unclear. Here, we report that instead of reprogramming individual tolerogenic cDC for new immunogenic functions, canonical inducers of maturation such as LPS initiated a burst of TNF-α production in these cDC, which resulted in their acute and specific death mediated by TNFR1. This ablation of individual tolerogenic cDC was enhanced by TNF-α produced by neighboring cDC, amplifying the initial innate stimulus. Overall, our results expand the understanding of the functions of TNF-α and TNFR1 during the maturation process and uncover that immunogenic maturation involves a dynamic remodeling of the cDC functional landscape by selectively ablating the tolerogenic cDC population to prevent an aberrant induction of tolerance. Therefore, our results may also have implications for devising new immunotherapeutic approaches. This work was supported in part by grants from National Institute of Allergy and Infectious Diseases of the National Institutes of Health (R01AI113903) and National Multiple Sclerosis Society (RG-1902-33632), both to DH.

Distinct representations of body and head motion are dynamically encoded by Purkinje cell populations in the macaque cerebellum.

The ability to accurately control our posture and perceive our spatial orientation during self-motion requires knowledge of the motion of both the head and body. However, while the vestibular sensors and nuclei directly encode head motion, no sensors directly encode body motion. Instead, the integration of vestibular and neck proprioceptive inputs is necessary to transform vestibular information into the body-centric reference frame required for postural control. The anterior vermis of the cerebellum is thought to play a key role in this transformation, yet how its Purkinje cells transform multiple streams of sensory information into an estimate of body motion remains unknown. Here, we recorded the activity of individual anterior vermis Purkinje cells in alert monkeys during passively applied whole-body, body-under-head, and head-on-body rotations. Most Purkinje cells dynamically encoded an intermediate representation of self-motion between head and body motion. Notably, Purkinje cells responded to both vestibular and neck proprioceptive stimulation with considerable heterogeneity in their response dynamics. Furthermore, their vestibular responses were tuned to head-on-body position. In contrast, targeted neurons in the deep cerebellar nuclei are known to unambiguously encode either head or body motion across conditions. Using a simple population model, we established that combining responses of~40-50 Purkinje cells could explain the responses of these deep cerebellar nuclei neurons across all self-motion conditions. We propose that the observed heterogeneity in Purkinje cell response dynamics underlies the cerebellum's capacity to compute the dynamic representation of body motion required to ensure accurate postural control and perceptual stability in our daily lives.