A unified physiological framework of transitions between seizures, sustained ictal activity and depolarization block at the single neuron level

The majority of seizures recorded in humans and experimental animal models can be described by a generic phenomenological mathematical model, the Epileptor. In this model, seizure-like events (SLEs) are driven by a slow variable and occur via saddle node (SN) and homoclinic bifurcations at seizure onset and offset, respectively. Here we investigated SLEs at the single cell level using a biophysically relevant neuron model including a slow/fast system of four equations. The two equations for the slow subsystem describe ion concentration variations and the two equations of the fast subsystem delineate the electrophysiological activities of the neuron. Using extracellular K+ as a slow variable, we report that SLEs with SN/homoclinic bifurcations can readily occur at the single cell level when extracellular K+ reaches a critical value. In patients and experimental models, seizures can also evolve into sustained ictal activity (SIA) and depolarization block (DB), activities which are also parts of the dynamic repertoire of the Epileptor. Increasing extracellular concentration of K+ in the model to values found during experimental status epilepticus and DB, we show that SIA and DB can also occur at the single cell level. Thus, seizures, SIA, and DB, which have been first identified as network events, can exist in a unified framework of a biophysical model at the single neuron level and exhibit similar dynamics as observed in the Epileptor.Author Summary: Epilepsy is a neurological disorder characterized by the occurrence of seizures. Seizures have been characterized in patients in experimental models at both macroscopic and microscopic scales using electrophysiological recordings. Experimental works allowed the establishment of a detailed taxonomy of seizures, which can be described by mathematical models. We can distinguish two main types of models. Phenomenological (generic) models have few parameters and variables and permit detailed dynamical studies often capturing a majority of activities observed in experimental conditions. But they also have abstract parameters, making biological interpretation difficult. Biophysical models, on the other hand, use a large number of variables and parameters due to the complexity of the biological systems they represent. Because of the multiplicity of solutions, it is difficult to extract general dynamical rules. In the present work, we integrate both approaches and reduce a detailed biophysical model to sufficiently low-dimensional equations, and thus maintaining the advantages of a generic model. We propose, at the single cell level, a unified framework of different pathological activities that are seizures, depolarization block, and sustained ictal activity.

Microfluidic Platforms Designed for Morphological and Photosynthetic Investigations of Chlamydomonas reinhardtii on a Single-Cell Level

Chlamydomonas reinhardtii is a model organism of increasing biotechnological importance, yet, the evaluation of its life cycle processes and photosynthesis on a single-cell level is largely unresolved. To facilitate the study of the relationship between morphology and photochemistry, we established microfluidics in combination with chlorophyll a fluorescence induction measurements. We developed two types of microfluidic platforms for single-cell investigations: (i) The traps of the “Tulip” device are suitable for capturing and immobilizing single cells, enabling the assessment of their photosynthesis for several hours without binding to a solid support surface. Using this “Tulip” platform, we performed high-quality non-photochemical quenching measurements and confirmed our earlier results on bulk cultures that non-photochemical quenching is higher in ascorbate-deficient mutants (Crvtc2-1) than in the wild-type. (ii) The traps of the “Pot” device were designed for capturing single cells and allowing the growth of the daughter cells within the traps. Using our most performant “Pot” device, we could demonstrate that the FV/FM parameter, an indicator of photosynthetic efficiency, varies considerably during the cell cycle. Our microfluidic devices, therefore, represent versatile platforms for the simultaneous morphological and photosynthetic investigations of C. reinhardtii on a single-cell level.

Single-Cell RNA Sequencing Reveals Heterogeneity Among Adult Mouse, Primate and Human Kidney Cells

Multiple studies have been performed to map the kidney landscape of human and rodent, along with the development of sequencing technique. Although rodent disease models have been widely applied, many disadvantages also exist. Non-human primates (NHPs) are considered as the closest experimental animals to humans and show great advantages in the construction of animal models of human disease. Therefore, a comprehensive understanding of the heterogeneity and homogeneity between human and multiple animal kidney cells is important for further establishing animal models of human renal disease. Here, we generated the first single-cell transcriptome data of normal adult cynomolgus monkey kidney using 10x Genomics scRNA-seq platform. Then, we further performed an in-depth comparison across species at the single-cell level, and our analysis indicated that the gene expression of adult primate kidney cells showed a better correlation with human kidney than mouse kidney. Furthermore, our results demonstrated that the cellular localization of GWAS-identified renal disease genes showed differences across species. The cellular localization of blood pressure associated genes in human displayed similarity to cynomolgus monkey. This study provided a reliable reference for further studies associated with renal diseases on NHPs. In addition, our results also provided a novel insight into the choice of renal disease animal model and a detailed explanation for close genetic relationship between NHPs and human at a single cell level.

Dynamic metabolic change of cancer cells induced by natural killer cells at single-cell level studied by label-free mass cytometry

Natural killer cell（NK cell）is an important immune cell which attracts increasing attention in cancer immunotherapy. Due to the heterogeneity of cells, individual cancer cell shows different resistance to NK cytotoxicity,...

Optimized Data-Independent Acquisition Approach for Proteomic Analysis at Single-Cell Level

Background: Single-cell proteomic analysis provides valuable insights into cellular heterogeneity allowing the characterization of the cellular microenvironment which is difficult to accomplish in bulk proteomic analysis. Currently, single-cell proteomic studies utilize data-dependent acquisition (DDA) mass spectrometry (MS) coupled with a TMT labelled carrier channel. Due to the extremely imbalanced MS signals among the carrier channel and other TMT reporter ions, the quantification is compromised. Thus, data-independent acquisition (DIA)-MS should be considered as an alternative approach towards single-cell proteomic study since it generates reproducible quantitative data. However, there are limited reports on the optimal workflow for DIA-MS-based single-cell analysis. Methods: We report an optimized DIA workflow for single-cell proteomics using Orbitrap Lumos Tribrid instrument. We utilized a breast cancer cell line (MDA-MB-231) and induced drug resistant polyaneuploid cancer cells (PACCs) to evaluate our established workflow. Results: We found that a short LC gradient was preferable for peptides extracted from single cell level with less than 2 ng sample amount. The total number of co-searching peptide precursors was also critical for protein and peptide identifications at nano- and sub-nano-gram levels. Post-translationally modified peptides could be identified from a nano-gram level of peptides. Using the optimized workflow, up to 1,500 protein groups were identified from a single PACC corresponding to 0.2 ng of peptides. Furthermore, about 200 peptides with phosphorylation, acetylation, and ubiquitination were identified from global DIA analysis of 100 cisplatin resistant PACCs (20 ng). Finally, we used this optimized DIA approach to compare the whole proteome of MDA-MB-231 parental cells and induced PACCs at a single-cell level. We found the single-cell level comparison could reflect real protein expression changes and identify the protein copy number. Conclusions: Our results demonstrate that the optimized DIA pipeline can serve as a reliable quantitative tool for single-cell as well as sub-nano-gram proteomic analysis.

Decode the Stable Cell Communications Based on Neuropeptide-Receptors Network in 36746 Tumor Cells

Background: As chemical signals of hormones, neuropeptides are essential to regulate cell growth by interacting with their receptors to achieve cell communications in cancer tissues. Previously, neuropeptide transcriptome analysis was limited to tissue-based bulk expression levels. The molecular mechanisms of neuropeptides and their receptors at the single-cell level remain unclear. We conducted a systematic single-cell transcriptome data integration analysis to clarify the similarities and variations of neuropeptide-mediated cell communication between various malignancies. Methods: Based on the single-cell expression information in 72 cancer datasets across 24 cancer types, we characterized actively expressed neuropeptides and receptors as having log values of the quantitative transcripts per million ≥ 1. Then, we created the putative cell-to-cell communication network for each dataset by using the known interaction of those actively expressed neuropeptides and receptors. To focus on the stable cell communication events, we identified neuropeptide and downstream receptors whose interactions were detected in more than half of all conceivable cell-cell interactions (square of the total cell population) in a dataset. Results: Focusing on those actively expressed neuropeptides and receptors, we built over 76 million cell-to-cell communications across 70 cancer datasets. Then the stable cell communication analyses were applied to each dataset, and about 14 million stable cell-to-cell communications could be detected based on 16 neuropeptides and 23 receptors. Further functional analysis indicates these 39 genes could regulate blood pressure and are significantly associated with patients’ survival among over ten thousand The Cancer Genome Atlas (TCGA)pan-cancer samples. By zooming in lung cancer-specific clinical features, we discovered the 39 genes appeared to be enriched in the patients with smoking. In skin cancer, they may differ in the patients with the distinct histological subtype and molecular drivers. Conclusions: At the single-cell level, stable cell communications across cancer types demonstrated some common and distinct neuropeptide-receptor patterns, which could be helpful in determining the status of neuropeptide-based cell communication and developing a peptide-based therapy strategy.

A Microphysiological Cell-Culturing System for Pharmacokinetic Drug Exposure and High-Resolution Imaging of Arrays of 3D Microtissues

Understanding the pharmacokinetic/pharmacodynamic (PK/PD)-relationship of a drug candidate is key to determine effective, yet safe treatment regimens for patients. However, current testing strategies are inefficient in characterizing in vivo responses to fluctuating drug concentrations during multi-day treatment cycles. Methods based on animal models are resource-intensive and require time, while traditional in vitro cell-culturing methods usually do not provide temporally-resolved information on the effects of in vivo–like drug exposure scenarios. To address this issue, we developed a microfluidic system to 1) culture arrays of three-dimensional spheroids in vitro, to 2) apply specific dynamic drug exposure profiles, and to 3) in-situ analyze spheroid growth and the invoked drug effects in 3D by means of 2-photon microscopy at tissue and single-cell level. Spheroids of fluorescently-labeled T-47D breast cancer cells were monitored under perfusion-culture conditions at short time intervals over three days and exposed to either three 24 h-PK-cycles or a dose-matched constant concentration of the phosphatidylinositol 3-kinase inhibitor BYL719. While the overall efficacy of the two treatment regimens was similar, spheroids exposed to the PK profile displayed cycle-dependent oscillations between regression and regrowth. Spheroids treated with a constant BYL719 concentration regressed at a steady, albeit slower rate. At a single-cell level, the cell density in BYL719-treated spheroids oscillated in a concentration-dependent manner. Our system represents a versatile tool for in-depth preclinical characterization of PK/PD parameters, as it enables an evaluation of drug efficacy and/or toxicity under realistic exposure conditions.