Single-cell System Research Articles

Hypoxia promotes a perinatal-like progenitor state in the adult murine epicardium

The epicardium is a reservoir of progenitors that give rise to coronary vasculature and stroma during development and mediates cardiac vascular repair. However, its role as a source of progenitors in the adult mammalian heart remains unclear due to lack of clear lineage markers and single-cell culture systems to elucidate epicardial progeny cell fate. We found that in vivo exposure of mice to physiological hypoxia induced adult epicardial cells to re-enter the cell cycle and to express a subset of developmental genes. Multiplex single cell transcriptional profiling revealed a lineage relationship between epicardial cells and smooth muscle, stromal cells, as well as cells with an endothelial-like fate. We found that physiological hypoxia promoted a perinatal-like progenitor state in the adult murine epicardium. In vitro clonal analyses of purified epicardial cells showed that cell growth and subsequent differentiation is dependent upon hypoxia, and that resident epicardial cells retain progenitor identity in the adult mammalian heart with self-renewal and multilineage differentiation potential. These results point to a source of progenitor cells in the adult heart that can be stimulated in vivo and provide an in vitro model for further studies.

Hybrid Beamforming for Millimeter Wave Massive MIMO under Multicell Multiuser Environment

Objectives: Due to the high cost and power consumption of fully digital beamforming, the goal of this research is to thoroughly investigate Kalman-based beamformers in conjunction with existing beamformers for multicell multiuser scenarios. Methods: In this research work, Kalman based hybrid beamforming for millimeter wave massive MIMO along with existing linear beamformers has been investigated. Mathematical model for spectral efficiency has been developed for each linear beamformer under multicell multiuser scenario and the performance has been shown using MATLAB software. Findings: Simulation results show that all the beamformers perform better for multi-cell systems compared to single cell systems i.e. better spectral efficiency for a given signal to noise ratio has been achieved for multicell system. Simulation results also depict precoders spectral efficiency improved as the number of transmitting antennas increase and the number of users decrease for multicell multiuser scenario. Novelty: Expanding the kalman based beamformer that contains digital combiner for multicell multiuser scenario is the novelty of this research. Keywords: Hybrid Beamforming; Massive MIMO; Millimeter Wave; Multicell; Multiuser

Single-cell multi-omics analysis reveals IFN-driven alterations in T lymphocytes and natural killer cells in systemic lupus erythematosus.

Background: The characterisation of the peripheral immune system in the autoimmune disease systemic lupus erythematosus (SLE) at the single-cell level has been limited by the reduced sensitivity of current whole-transcriptomic technologies. Here we employ a targeted single-cell multi-omics approach, combining protein and mRNA quantification, to generate a high-resolution map of the T lymphocyte and natural killer (NK) cell populations in blood from SLE patients. Methods: We designed a custom panel to quantify the transcription of 534 genes in parallel with the expression of 51 surface protein targets using the BD Rhapsody AbSeq single-cell system. We applied this technology to profile 20,656 T and NK cells isolated from peripheral blood from an SLE patient with a type I interferon (IFN)-induced gene expression signature (IFN hi), and an age- and sex- matched IFN low SLE patient and healthy donor. Results: We confirmed the presence of a rare cytotoxic CD4 + T cell (CTL) subset, which was exclusively present in the IFN hi patient. Furthermore, we identified additional alterations consistent with increased immune activation in this patient, most notably a shift towards terminally differentiated CD57 + CD8 + T cell and CD16 + NK dim phenotypes, and the presence of a subset of recently-activated naïve CD4 + T cells. Conclusions: Our results identify IFN-driven changes in the composition and phenotype of T and NK cells that are consistent with a systemic immune activation within the IFN hi patient, and underscore the added resolving power of this multi-omics approach to identify rare immune subsets. Consequently, we were able to find evidence for novel cellular peripheral biomarkers of SLE disease activity, including a subpopulation of CD57 + CD4 + CTLs.

Single-cell multi-omics analysis reveals IFN-driven alterations in T lymphocytes and natural killer cells in systemic lupus erythematosus

Background: The characterisation of the peripheral immune system in the autoimmune disease systemic lupus erythematosus (SLE) at the single-cell level has been limited by the reduced sensitivity of current whole-transcriptomic technologies. Here we employ a targeted single-cell multi-omics approach, combining protein and mRNA quantification, to generate a high-resolution map of the T lymphocyte and natural killer (NK) cell populations in blood from SLE patients. Methods: We designed a custom panel to quantify the transcription of 534 genes in parallel with the expression of 51 surface protein targets using the BD Rhapsody AbSeq single-cell system. We applied this technology to profile 20,656 T and NK cells isolated from peripheral blood from an SLE patient with a type I interferon (IFN)-induced gene expression signature (IFN hi), and an age- and sex- matched IFN low SLE patient and healthy donor. Results: We confirmed the presence of a rare cytotoxic CD4 + T cell (CTL) subset, which was exclusively present in the IFN hi patient. Furthermore, we identified additional alterations consistent with increased immune activation in this patient, most notably a shift towards terminally differentiated CD57 + CD8 + T cell and CD16 + NK dim phenotypes, and the presence of a subset of recently-activated naïve CD4 + T cells. Conclusions: Our results identify IFN-driven changes in the composition and phenotype of T and NK cells that are consistent with a systemic immune activation within the IFN hi patient, and underscore the added resolving power of this multi-omics approach to identify rare immune subsets. Consequently, we were able to find evidence for novel cellular peripheral biomarkers of SLE disease activity, including a subpopulation of CD57 + CD4 + CTLs.

Energy Efficiency Optimization for Rate-Splitting Multiple Access-Based Indoor Visible Light Communication Networks

With the explosive proliferation of connected devices and mobile users in the Internet-of-things, multiple access techniques are urged to be developed for the next generation wireless communications. Recently, rate-splitting multiple access (RSMA) has been a promising communication technology that holds advantages of strong robustness, low complexity, and high spectral efficiency, which can be integrated with the indoor visible light communication (VLC) broadcast system to compensate for the shortcomings of limited modulation bandwidth of LEDs. However, the research on the RSMA-based VLC systems is still in its infancy and there exist various problems to be explored. To benefit from the RSMA technique, this paper investigates the energy efficiency optimizations for both single-cell and multi-cell RSMA-based VLC broadcast systems. Specifically, these two systems are modeled, where the VLC broadcast channel follows Lambertian radiation model, and the splitting design and successive interference cancellation of RSMA are employed to mitigate the multi-user interference. Especially for multi-cell networks, the zero-forcing approach is adopted to eliminate the inter-cell interference. To maximize the energy efficiency, the precoding and power allocation problems are formulated for single-cell and multi-cell networks while accommodating multiple constraints including dynamic operation ranges of LEDs, QoS requirements, and interference elimination. For solving these non-convex fractional problems, two pieces of successive convex approximation (SCA)-based algorithms are proposed, in which the variable transformation and linear approximation are adopted. Simulation results indicate that the proposed schemes can achieve superior energy efficiency with fast convergence for various network loads and user deployments.

Advancements in single cell multiomic profiling of antigen-specific T cells with dCODE Dextramer&[trade] (RiO) and BD® AbSeq Reagents on the BD Rhapsody&[trade] Single-Cell Analysis System

Abstract The advancement of immunotherapies and drug development relies on the characterization of antigen-specific T cells. However, due to their low frequency among T cells and their inherent weak affinity to bind known MHC-peptide complexes, detection of these cells has been difficult. Furthermore, pairing this information with the corresponding variable (V), diversity (D), and joining (J) [V(D)J] sequences of the antigen-specific T cell receptors has also been challenging due to hurdles in sequencing these large regions, particularly at the single-cell level. Here, we have expanded our previous work of combining two powerful technologies, Immudex dCODE Dextramer™ (RiO) Reagents and the BD Rhapsody™ Single-Cell Analysis System, to detect and characterize low-frequency antigen-specific T cells, including the full sequences of the V(D)J gene segments of the T cell receptors, as well as profile transcriptome and protein expression. Specifically, thousands of sorted PBMCs were multiplexed to provide high-throughput detection of individual antigen-specific CD8+ T cells in combination with the corresponding full V(D)J sequences of the T cell receptors. In addition, we simultaneously obtained gene expression data for over 400 immune-related mRNAs as well as cell phenotypes using a panel of 30 cell surface BD® AbSeq Protein Markers. Together these data can be used to define T cell phenotypes associated with T cell activation states, alongside antigen specificity of enriched CD8+ dextramer+ cells from PBMC populations. This study showcases the importance of multiomic analysis for high-resolution T cell profiling that has broader implications and utility in immuno-oncology, infectious diseases and autoimmunity.

An integrated single-cell multiomics approach to characterize mRNA, intracellular, and surface proteins using intracellular AbSeq and BD® AbSeq Immune Discovery Panel

Abstract DNA-barcoded antibodies enable single-cell multiomics approaches that examine protein alongside mRNA in a single cell. Although it is a powerful approach, leading methods are currently limited to surface proteins, which limits understanding of signal-transduction and transcriptional pathways that are often governed by expression changes and posttranslational modifications of intracellular proteins. The ability to analyze intracellular proteins alongside the transcriptome is complicated by the fix and perm processes necessary to access intracellular epitopes, which can negatively impact RNA assay sensitivity. Furthermore, nonspecific binding of antibody-oligos to nucleic acids can generate high background signals. To address these issues, we generated a protocol that can recover high-quality RNA alongside specific intracellular and surface protein information. Using this protocol in conjunction with the BD Rhapsody™ Single-Cell Analysis System, we simultaneously profiled over 50 protein markers including 14 intracellular proteins with the whole transcriptome. We identified predicted patterns, including increased phosphorylation of AKT protein correlated with the proliferation marker Ki67 upon immune stimulation, and transcription factor (T-bet) expression in a specific cell subset. Together these preliminary results suggest that analysis of intracellular proteins together with the transcriptome may be possible using single-cell sequencing technologies and can enable a deeper understanding of cellular states. For Research Use Only. Not for use in diagnostic or therapeutic procedures.

Effects of MiR-214-3p Regulation of SERCA2a Expression on Contractility of Cardiomyocytes in Heart Failure Model.

This study aimed to explore the targeted regulation of microRNA-214-3p (miR-214-3p) on sarcoplasmic/endoplasmic reticulum Ca(2+)-ATPase 2a (SERCA2a) and its mechanism on heart failure (HF). In this study, a rat model of HF was established by injecting isoproterenol to detect the changes in heart function. Then the primary rat cardiomyocytes were extracted and cultured. The cells were divided into the normal group, HF model group, miR-214-3p mimic group, and inhibitor group according to treatment methods. The expression differences of SERCA2a in each group were detected. The binding sites of miR-214-3p and SERCA2a were predicted, wild-type or mutant SERCA2a was prepared and co-transfected into cardiomyocytes with mimic, and the targeting effect was detected by the dual-luciferase reporter gene. Finally, the systolic function of each group was detected by a single-cell systolic dynamic edge detection system. The results showed that cardiac output and left ventricular ejection fraction of HF rats were significantly lower than those of normal rats (P<0.05). The results of the cell test showed that messenger ribonucleic acid (mRNA) and protein expression levels of SERCA2a in the model group and the mimic group were significantly lower than those in the mimic group (P<0.05), but there were no differences between normal group and inhibitor group (P>0.05). Target prediction revealed that miR-214-3p had a complementary pairing of 6 bases with the SERCA2a 3'non-coding region. After co-transfection with miR-214-3p mimic and wild-type SERCA2a expression vector, the dual-luciferase activity was significantly decreased (P<0.05). The percentage of maximal contraction amplitude, peak contraction time, and 50% diastolic time of cells in the model group and mimic group decreased significantly. The mimic group was significantly smaller (P<0.05), but there were no differences between the normal group and the inhibitor group (P>0.05). These results indicated that SERCA2a expression was significantly reduced in HF cells, and miR-214-3p could inhibit SERCA2a expression by targeting the SERCA2a 3'UTR region. Inhibition of miR-214-3p could promote the expression of SERCA2a, which in turn promoted the contractile function of HF rat cardiomyocytes.

Hierarchical porous N-doped carbon-supported PtCu nanoparticles as an efficient catalyst for oxygen reduction reaction

The catalyst of PtCu bimetallic nanoparticles anchored on hierarchical porous N-doped carbon (PtCu/NHPC) is successfully fabricated through a simple pyrolysis synthesis. The high surface area (827 m2 g−1) of N-doped porous carbon (NHPC) can effectively favor the high distribution of PtCu particles on carbon. The high mesopore ratio of NHPC helps to reduce mass transfer resistance. Furthermore, homogeneously distributed nitrogen in carbon can not only uniformly disperse nanoparticles but also optimize catalyst oxygen affinity, significantly improving catalytic efficiency for oxygen reduction reaction. PtCu/NHPC shows excellent electrocatalytic activity with a high half-wave potential (0.915 V vs. RHE) compared with commercial Pt/C (0.864 V) in half-cell test. In the single-cell system, PtCu/NHPC also behaves good performance, and its initial current density is 595 mA cm−2 at 0.85 V. PtCu/NHPC shows better durability (only 6.6% mass activity loss) after 10,000 potential cycles compared to JM Pt/C catalyst (30%). The research provides a simple preparation strategy for improving the oxygen reduction reaction activity and stability of fuel cell platinum-based catalysts.

Advancing animal health and disease research in the lab with three-dimensional cell culture systems.

The development of three-dimensional cell culture systems representative of tissues from animals of veterinary interest is accelerating research that seeks to address specific questions tied to animal health. In terms of their relevance and complexity, these in vitro models can be seen as a midpoint between the more reductionist single-cell culture systems and complex live animals. Organoids in particular represent a significant development due to their organised multicellular structure that more closely represents in vivo tissues than any other cell culture technology previously developed. In this review, we provide an overview of the different three-dimensional cell culture systems available to veterinary researchers and give examples of their application in contexts relating to animal health.

Computation and visualization of cell\u2013cell signaling topologies in single-cell systems data using Connectome

Single-cell RNA-sequencing data has revolutionized our ability to understand of the patterns of cell–cell and ligand–receptor connectivity that influence the function of tissues and organs. However, the quantification and visualization of these patterns in a way that informs tissue biology are major computational and epistemological challenges. Here, we present Connectome, a software package for R which facilitates rapid calculation and interactive exploration of cell–cell signaling network topologies contained in single-cell RNA-sequencing data. Connectome can be used with any reference set of known ligand–receptor mechanisms. It has built-in functionality to facilitate differential and comparative connectomics, in which signaling networks are compared between tissue systems. Connectome focuses on computational and graphical tools designed to analyze and explore cell–cell connectivity patterns across disparate single-cell datasets and reveal biologic insight. We present approaches to quantify focused network topologies and discuss some of the biologic theory leading to their design.

Analysis of the Impact of Detection Threshold Adjustments and Noise Uncertainty on Energy Detection Performance in MIMO-OFDM Cognitive Radio Systems.

Due to the capability of the effective usage of the radio frequency spectrum, a concept known as cognitive radio has undergone a broad exploitation in real implementations. Spectrum sensing as a core function of the cognitive radio enables secondary users to monitor the frequency band of primary users and its exploitation in periods of availability. In this work, the efficiency of spectrum sensing performed with the energy detection method realized through the square-law combining of the received signals at secondary users has been analyzed. Performance evaluation of the energy detection method was done for the wireless system in which signal transmission is based on Multiple-Input Multiple-Output—Orthogonal Frequency Division Multiplexing. Although such transmission brings different advantages to wireless communication systems, the impact of noise variations known as noise uncertainty and the inability of selecting an optimal signal level threshold for deciding upon the presence of the primary user signal can compromise the sensing precision of the energy detection method. Since the energy detection may be enhanced by dynamic detection threshold adjustments, this manuscript analyses the influence of detection threshold adjustments and noise uncertainty on the performance of the energy detection spectrum sensing method in single-cell cognitive radio systems. For the evaluation of an energy detection method based on the square-law combining technique, the mathematical expressions of the main performance parameters used for the assessment of spectrum sensing efficiency have been derived. The developed expressions were further assessed by executing the algorithm that enabled the simulation of the energy detection method based on the square-law combining technique in Multiple-Input Multiple-Output—Orthogonal Frequency Division Multiplexing cognitive radio systems. The obtained simulation results provide insights into how different levels of detection threshold adjustments and noise uncertainty affect the probability of detection of primary user signals. It is shown that higher signal-to-noise-ratios, the transmitting powers of primary user, the number of primary user transmitting and the secondary user receiving antennas, the number of sampling points and the false alarm probabilities improve detection probability. The presented analyses establish the basis for understanding the energy detection operation through the possibility of exploiting the different combinations of operating parameters which can contribute to the improvement of spectrum sensing efficiency of the energy detection method.

Channel Charting Aided Pilot Reuse for Massive MIMO Systems With Spatially Correlated Channels

Massive multiple-input multiple-output (mMIMO) technology is a way to increase the spectral efficiency of machine-type communications (MTC). To exploit the benefits from large antenna arrays, accurate channel estimation through pilot signals is needed. Massive MTC systems cannot avoid pilot reuse due to the enormous numbers of connected devices. We propose a pilot reuse algorithm based on channel charting (CC) to mitigate pilot contamination in a multi-sector single-cell massive MTC system having spatially correlated channels. We show that after creating an interference map via CC, a simple strategy to allocate the pilot sequences can be implemented. The simulation results show that the CC-based pilot reuse strategy improves channel estimation accuracy, which subsequently improves the symbol detection performance and increases the spectral efficiency compared to other existing schemes. Moreover, the performance of the CC pilot assignment method approaches that of exhaustive search pilot assignment for small network setups.

LabVIEW controlled automatic photocuring in single-cell screening system

LabVIEW controlled automatic photocuring in single-cell screening system

A novel approach for predicting PEMFC in varying ambient conditions by using a transient search optimization algorithm based on a semi-empirical model

&lt;abstract&gt; &lt;p&gt;Proton exchange membrane fuel cell (PEMFC) is an alternate energy source that produces electricity without any adverse effects on the environment. The drawbacks of PEMFC are its short life and its non-linear voltage with loading current. Also, PEMFC is prone to ambient conditions, and its performance varies with different ambient conditions. In this work, the semi-empirical modeling approach has been used to predict the PEMFC voltage accurately. However, when the ambient condition varies, the voltage of PEMFC varies accordingly and consequently the previous parameters of the EMI-empirical model don't produce good results. Previously the voltage variation due to changes in ambient has been predicted with the help of ambient conditions and load resistance, but this model isn't sui for all PEMFCs. In this work, a new method has been proposed where fast and accurate optimization technique such as Transient search optimization (TSO) has been used to optimize parameters when ambient condition varies and predicts the PEMFC voltage accurately and doesn't consume a lot of time. The proposed method will be very helpful in future research for predicting the PEMFC voltage for various PEMFC systems at different ambient conditions. The proposed method has been validated experimentally by performing experiments on n single-cell PEMFC system at normal and high ambient temperature.&lt;/p&gt; &lt;/abstract&gt;

High-Throughput Preparation of Improved Single-Cell Hi-C Libraries Using an Automated Liquid Handling System.

Hi-C is recognized as a gold standard approach to analyze the three-dimensional (3D) organization of chromatin or chromosomes on a genome-wide scale. It has revealed many characteristic features of structural organization and contributed to our understanding of how gene expression is related to the 3D organization of chromatin. However, the original Hi-C is designed to analyze the average structure across millions of cells, which makes the method unsuitable if the cell population of interest is not homogeneous or the purpose is to pursue the dynamic aspects of the structural features in individual cells. To overcome such limitations, we established single-cell Hi-C and have improved the method further in terms of data quality and throughput. Here we describe the revised single-cell Hi-C protocol, including the settings of the liquid handling system essential for increased throughput.

Single-cell systems neuroscience: A growing frontier in mental illness

The development of effective treatments for psychiatric disease has been disappointing in recent decades given the advancements in neuroscience. Moreover, rising rates of mental illness such as addiction and depression compel scientists and physicians to discover novel and creative solutions. One such approach that has proven effective is systems neuroscience: A focus on networks as opposed to mechanism. Further, investigation at the single-cell and circuit level is likely to be fruitful in such endeavors as this resolution describes the functional psychopathology that allows for intervention.

ABA Transport Assay in Plant Single-Cell System.

Compare with long history of the abscisic acid (ABA) study, our knowledge of ABA transporters is quite recent. This is due to at least one reason: ABA is a weak acid, and thus, it exists in either protonated form or in anionic form depending on the surrounding pH relative to its pKa value. Because the protonated form of ABA can permeate the cell membrane, it would foreclose a specific uptake transporter of ABA. Notwithstanding this theoretical base, ABA transporters belonging to different protein families have been reported a decade ago, steadily. A critical point of the identification of novel ABA transporters is to prove their transport activity. To do this, heterologous expression system is considered first as a facility of transport activity analysis. However, it is difficult to overexpress membrane proteins in their functional state in heterologous system. They have the tendency to aggregate and produce inclusion bodies caused by mistargeting. Thus, in this chapter, I describe the method of ABA transport assay based on single-cell system originated from plant tissues.

Thermal runaway behavior of nickel–manganese–cobalt 18650 lithium-ion cells induced by internal and external heating failures

Lithium-ion cells can fail in thermal runaway in a number of ways. Thermally-induced failures can be initiated by either external heating or an internal failure which leads to internal heating. Internal failures such as dendrite growth can lead to an internal short circuit (ISC) which subsequently causes internal heating. Internal failures are a common cause for lithium-ion battery thermal runaway that leads to fire incidents. Preventing and mitigating thermal runaway failure is of great interest in battery fire safety research and development. To evaluate safety measures in a repeatable manner, there is a need for a simple and repeatable technique to reliably fail a given cell, while minimally affecting the pack prior to cell failure. This paper introduces an internal failure mechanism targeted on a single (or multiple) 18650 cell(s) to trigger thermal runaway by (1) modifying commercially acquired 18650s to accommodate a mini-heater cartridge, (2) performing cycling tests on the modified cells and comparing their performance to that of the as-received (pristine) cells in a custom-built failure tube environment, and (3) experimentally examining the characteristics (temperature, flux-time product, voltage drop, and mass loss) of internally heated and failed cells in comparison to externally heated and failed cells. The results show that the modification procedures do not alter a cell’s performance and its charge capacity. Failure tube tests show that the thermal runaway behavior and damage to the modified cells are representative of ”real-world” cell failures. The internally heated cells had different venting behavior relative to externally heated cells, which affects mass loss profiles. When inserting a single, modified cell into a battery package (laptop power bank) and triggering it to cause thermal runaway, failure propagation to the surrounding cells can be characterized. Overall, this study introduces a realistic cell internal failure approach that can benefit the development of battery safety techniques in a variety of applications. The internal-heater failure approach is proven to be easily prepared with standard laboratory apparatus without affecting the battery performance and produces repeatable failure results for single and multiple cell systems.

Cellular variability of nonsense-mediated mRNA decay

Nonsense-mediated mRNA decay (NMD) is an mRNA degradation pathway that eliminates transcripts containing premature termination codons (PTCs). Half-lives of the mRNAs containing PTCs demonstrate that a small percent escape surveillance and do not degrade. It is not known whether this escape represents variable mRNA degradation within cells or, alternatively cells within the population are resistant. Here we demonstrate a single-cell approach with a bi-directional reporter, which expresses two β-globin genes with or without a PTC in the same cell, to characterize the efficiency of NMD in individual cells. We found a broad range of NMD efficiency in the population; some cells degraded essentially all of the mRNAs, while others escaped NMD almost completely. Characterization of NMD efficiency together with NMD regulators in single cells showed cell-to-cell variability of NMD reflects the differential level of surveillance factors, SMG1 and phosphorylated UPF1. A single-cell fluorescent reporter system that enabled detection of NMD using flow cytometry revealed that this escape occurred either by translational readthrough at the PTC or by a failure of mRNA degradation after successful translation termination at the PTC.