Typical Single Cell Research Articles

Performance enhancement of air-cooled PEMFC stack by employing tapered oblique fin channels: Experimental study of a full stack and numerical analysis of a typical single cell

In this study, a novel cathode flow field plate with additional tapered oblique fin (OF) channels is proposed for air-cooled proton exchange membrane fuel cells (PEMFCs) to promote their heat dissipation and output power. Air-cooled PEMFC stacks with conventional (parallel configuration) and novel flow fields are respectively manufactured and experimentally tested under various load currents. The performance and temperature distributions of the stacks are comparatively studied in detail. Besides, a three-dimensional and two-phase numerical model is established and validated by the experiment data to further comparative investigate the heat and mass transport mechanism of the two studied flow field designs. The results show that the stack with the novel flow field has higher output power, which is 4.87% higher than that with a conventional design at a load current density of 0.55 A cm−2. Due to the forced convection and secondary vortex phenomena in the OF channels, the local overheating in the porous electrode is relieved. Moreover, the entropy generations due to heat transfer of the cathode CL and cooling channels are significantly increased. The oxygen transport under cathode ribs is also noteworthily enhanced when the OF channels are adopted.

A simple joint detection platform for high-throughput single-cell heterogeneity screening

Single cell heterogeneity plays an important role in many biological phenomena and distinguishing cells that exhibit certain mutation in sample could benefit clinical diagnose and drug screening. Typical single cell detection methods such as flow cytometry, in-situ hybridization, real-time amplification or sequencing test either protein or nucleic acid as target and usually require specialized instruments. Joint measurement of the both types of targets could be done by combining the above strategies precisely but also unwieldly. Methods for rapidly and parallelly screening single cells with target genotype and antigen is needed. In this study, we describe a gel plate platform to distinguish cell types based on their phenotypes on target gene and antigen with low equipment requirement. Integrated cell lysis and immobilization were done in the gel solidification step, after which antibody hybridization and real-time amplification were sequentially carried out without losing the original loci information of individual single cells so the three types of information of individual single cells could be combined to distinguished cells with expected genotype and phenotype. The easy-to-use gel platform has potential in point-of-care circumstances and single-cell stimulation response that have high requirements on efficiency and simplicity.

Cytocipher determines significantly different populations of cells in single-cell RNA-seq data.

Identification of cell types using single-cell RNA-seq is revolutionizing the study of multicellular organisms. However, typical single-cell RNA-seq analysis often involves post hoc manual curation to ensure clusters are transcriptionally distinct, which is time-consuming, error-prone, and irreproducible. To overcome these obstacles, we developed Cytocipher, a bioinformatics method and scverse compatible software package that statistically determines significant clusters. Application of Cytocipher to normal tissue, development, disease, and large-scale atlas data reveals the broad applicability and power of Cytocipher to generate biological insights in numerous contexts. This included the identification of cell types not previously described in the datasets analysed, such as CD8+ T cell subtypes in human peripheral blood mononuclear cells; cell lineage intermediate states during mouse pancreas development; and subpopulations of luminal epithelial cells over-represented in prostate cancer. Cytocipher also scales to large datasets with high-test performance, as shown by application to the Tabula Sapiens Atlas representing >480 000 cells. Cytocipher is a novel and generalizable method that statistically determines transcriptionally distinct and programmatically reproducible clusters from single-cell data. The software version used for this manuscript has been deposited on Zenodo (https://doi.org/10.5281/zenodo.8089546), and is also available via github (https://github.com/BradBalderson/Cytocipher).

Abstract 5930: Single day workflow for high-quality whole genome analysis of thousands of single cells

Abstract DNA sequencing technology provides the capability to tell the story of every cell in a heterogenous sample. ResolveDNA® generates uniform coverage of >95% of a single genome, enabling researchers to generate single-cell genomic data of unparalleled quality. Here, we report an enhancement to the ResolveDNA® workflow that increases the rate of data collection; the ability to reliably generate complete genomic information from up to 1536 cells in parallel from a single experiment. To achieve this, we have coupled a high-throughput automated process to a low volume reaction using the latest ResolveDNA® 2.5-hour chemistry. This establishes the potential for users to go from a single cell, or low-input DNA sample, to ready to sequence libraries in a single day for >3000 samples. As with earlier ResolveDNA® workflows, these reactions generate negligible amounts of contaminating and off target DNA during the reaction. A typical single-cell reaction yields ~ 85 ng of DNA. The single cell’s amplified DNA product is amenable to multiple post amplification library preparation processes. We utilized both BioSkryb ResolveDNA® and Watchmaker Library Preparation kits for Illumina sequencing. We did not identify significant differences in the performance of the two products. Libraries were assessed at a depth of ~ 2million reads and determined to be of high quality, with low rates of chimeric DNA formation and less than 1% mtDNA resulting in the reaction product. A subset of samples was probed at >200 million reads, with >85% of the genome covered at 1x. Consistent with earlier ResolveDNA® workflows, the libraries were characterized with >99% precision and >80% sensitivity. The story told from a single cell’s genome drives discovery and shines a light on the questions surrounding the causes of disease and cellular function. This workflow is designed to empower researchers to probe the genomic landscape of a heterogenous tissue sample. Citation Format: Jay A. West, Jeff G. Blackinton, Kyle Hukari, Joe Dahl. Single day workflow for high-quality whole genome analysis of thousands of single cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5930.

ICARUS, an interactive web server for single cell RNA-seq analysis.

Here we present ICARUS, a web server to enable users without experience in R to undertake single cell RNA-seq analysis. The focal point of ICARUS is its intuitive tutorial-style user interface, designed to guide logical navigation through the multitude of pre-processing, analysis and visualization steps. ICARUS is easily accessible through a dedicated web server (https://launch.icarus-scrnaseq.cloud.edu.au/) and avoids installation of software on the user's computer. Notable features include the facility to apply quality control thresholds and adjust dimensionality reduction and cell clustering parameters. Data is visualized through 2D/3D UMAP and t-SNE plots and may be curated to remove potential confounders such as cell cycle heterogeneity. ICARUS offers flexible differential expression analysis with user-defined cell groups and gene set enrichment analysis to identify likely affected biological pathways. Eleven organisms including human, dog, mouse, rat, zebrafish, fruit fly, nematode, yeast, cattle, chicken and pig are currently supported. Visualization of multimodal data including those generated by CITE-seq and the 10X Genomics Multiome kit is included. ICARUS incorporates a function to save the current state of analysis avoiding computationally intensive steps during repeat analysis. The complete analysis of a typical single cell RNA-seq dataset by inexperienced users may be achieved in 1–2 h.

Dynamic 3D genome architecture of cotton fiber reveals subgenome-coordinated chromatin topology for 4-staged single-cell differentiation

BackgroundDespite remarkable advances in our knowledge of epigenetically mediated transcriptional programming of cell differentiation in plants, little is known about chromatin topology and its functional implications in this process.ResultsTo interrogate its significance, we establish the dynamic three-dimensional (3D) genome architecture of the allotetraploid cotton fiber, representing a typical single cell undergoing staged development in plants. We show that the subgenome-relayed switching of the chromatin compartment from active to inactive is coupled with the silencing of developmentally repressed genes, pinpointing subgenome-coordinated contribution to fiber development. We identify 10,571 topologically associating domain-like (TAD-like) structures, of which 25.6% are specifically organized in different stages and 75.23% are subject to partition or fusion between two subgenomes. Notably, dissolution of intricate TAD-like structure cliques showing long-range interactions represents a prominent characteristic at the later developmental stage. Dynamic chromatin loops are found to mediate the rewiring of gene regulatory networks that exhibit a significant difference between the two subgenomes, implicating expression bias of homologous genes.ConclusionsThis study sheds light on the spatial-temporal asymmetric chromatin structures of two subgenomes in the cotton fiber and offers a new insight into the regulatory orchestration of cell differentiation in plants.

Smart-RRBS for single-cell methylome and transcriptome analysis.

The integration of DNA methylation and transcriptional state within single cells is of broad interest. Several single-cell dual- and multi-omics approaches have been reported that enable further investigation into cellular heterogeneity, including the discovery and in-depth study of rare cell populations. Such analyses will continue to provide important mechanistic insights into the regulatory consequences of epigenetic modifications. We recently reported a new method for profiling the DNA methylome and transcriptome from the same single cells in a cancer research study. Here, we present details of the protocol and provide guidance on its utility. Our Smart-RRBS (reduced representation bisulfite sequencing) protocol combines Smart-seq2 and RRBS and entails physically separating mRNA from the genomic DNA. It generates paired epigenetic promoter and RNA-expression measurements for ~24% of protein-coding genes in a typical single cell. It also works for micro-dissected tissue samples comprising hundreds of cells. The protocol, excluding flow sorting of cells and sequencing, takes ~3 d to process up to 192 samples manually. It requires basic molecular biology expertise and laboratory equipment, including a PCR workstation with UV sterilization, a DNA fluorometer and a microfluidic electrophoresis system.

A data-driven clustering recommendation method for single-cell RNA-sequencing data

Recently, the emergence of single-cell RNA-sequencing (scRNA-seq) technology makes it possible to solve biological problems at the single-cell resolution. One of the critical steps in cellular heterogeneity analysis is the cell type identification. Diverse scRNA-seq clustering methods have been proposed to partition cells into clusters. Among all the methods, hierarchical clustering and spectral clustering are the most popular approaches in the downstream clustering analysis with different preprocessing strategies such as similarity learning, dropout imputation, and dimensionality reduction. In this study, we carry out a comprehensive analysis by combining different strategies with these two categories of clustering methods on scRNA-seq datasets under different biological conditions. The analysis results show that the methods with spectral clustering tend to perform better on datasets with continuous shapes in two-dimension, while those with hierarchical clustering achieve better results on datasets with obvious boundaries between clusters in two-dimension. Motivated by this finding, a new strategy, called QRS, is developed to quantitatively evaluate the latent representative shape of a dataset to distinguish whether it has clear boundaries or not. Finally, a data-driven clustering recommendation method, called DDCR, is proposed to recommend hierarchical clustering or spectral clustering for scRNA-seq data. We perform DDCR on two typical single cell clustering methods, SC3 and RAFSIL, and the results show that DDCR recommends a more suitable downstream clustering method for different scRNA-seq datasets and obtains more robust and accurate results.

A “Press and Go” Thin Biofuel Cell Patch for Power Generation

Biofuel cells are devices that generate portable electrical power, typically from glucose, alcohols or related biofuels, by using enzymatic anodes and cathodes. We report on the performance of membrane- and mediator-free enzymatic glucose biofuel cells (BFCs) fabricated in a sandwiched, patch geometry with carbon nanotube nanopaper bio-electrodes prepared using a compression technique to immobilize the enzymes. A gel electrolyte comprised of agar mixed with glucose is sandwiched between the two bio-electrodes to form a patch. Power densities up to 111.90 μW/cm2 at a current density of 334.50 μA/cm2 at a voltage of 0.335 V were obtained for a typical single cell BFC of this design. The sandwich BFC also showed good stability with a half-life of about 1.5 days under continuous operation. The relatively high power density for this new design is attributed to the compression-induced immobilization of the enzymes by the nanotubes as indicated by scanning electron microscope images. This compression-induced immobilization of enzymes provides improved direct electron transfer at the carbon nanotube electrodes.

Dispersion feature of elastic waves in a 1-D phononic crystal with consideration of couple stress effects

The couple stress effects upon the propagation behavior and the dispersive feature of Bloch waves in the periodically laminated structure are studied in this paper. First, the various modes of wave motion in the elastic solid with consideration of the couple stress are formulated. Apart from the dispersive P wave, SV wave, and SH wave, there are two evanescent waves, namely SS wave and SSH wave. These modes of wave motion are considered to formulate the state vector and further the transfer matrix in each layer. Then, the non-classic interface continuity conditions with consideration of couple stress effects are used to derive the transfer matrix of the state vector in a typical single cell. At last, the Bloch theorem is used to give the dispersive equations of Bloch waves in the periodical structure. The in-plane Bloch waves and the anti-plane Bloch waves which propagate either obliquely or vertically are both considered in the present work. The numerical results are obtained by solving the dispersive equations and shown graphically. The influences of the couple stress effects on the propagation and the dispersive feature of Bloch waves are discussed based on the numerical results.

McImpute: Matrix Completion Based Imputation for Single Cell RNA-seq Data.

Motivation: Single-cell RNA sequencing has been proved to be revolutionary for its potential of zooming into complex biological systems. Genome-wide expression analysis at single-cell resolution provides a window into dynamics of cellular phenotypes. This facilitates the characterization of transcriptional heterogeneity in normal and diseased tissues under various conditions. It also sheds light on the development or emergence of specific cell populations and phenotypes. However, owing to the paucity of input RNA, a typical single cell RNA sequencing data features a high number of dropout events where transcripts fail to get amplified.Results: We introduce mcImpute, a low-rank matrix completion based technique to impute dropouts in single cell expression data. On a number of real datasets, application of mcImpute yields significant improvements in the separation of true zeros from dropouts, cell-clustering, differential expression analysis, cell type separability, the performance of dimensionality reduction techniques for cell visualization, and gene distribution.Availability and Implementation: https://github.com/aanchalMongia/McImpute_scRNAseq

Dispersion relations of elastic waves in three-dimensional cubical piezoelectric phononic crystal with initial stresses and mechanically and dielectrically imperfect interfaces

• The theoretical model of a 3D cubical piezoelectric phononic crystal has been established. • Contrastive influences of non-dimensional structural and modal parameters have been considered. • Contrastive influences of initial stresses and imperfect interfaces have been considered. • Properties of partial and global dispersion relations have been discussed. A three-dimensional cubical piezoelectric phononic crystal is theoretically studied in this paper, formed by pre-stressed piezoelectric rectangular blocks and imperfect interfaces. Firstly, transfer matrices of pre-stressed piezoelectric rectangular blocks and imperfect interfaces are obtained based on the structural characteristics. The Bloch waves consist of three groups of sub-coupled elastic waves corresponding with three orthogonal periodical directions in the three-dimensional periodical structure. Furthermore, based on the transfer matrices of typical single cell and the Bloch theorem, it is established that the theoretical model of above-mentioned three-dimensional cubical piezoelectric phononic crystal to obtain the dispersion relations of Bloch waves. Finally, the influences of non-dimensional geometrical parameters (structural and modal parameters) and physical parameters (initial stress and mechanically and dielectrically imperfect interface parameters) on the dispersion relations are discussed based on the graphically numerical results. Numerical calculation results show that the existences of initial stresses and mechanically and dielectrically imperfect interfaces equivalently lead to the alterations of structural flexibilities or rigidities. The theoretical model and numerical discussions will provide a direct guidance of multi-material additive manufacturing for pre-stressed and inhomogeneous periodic structures with partial and global dispersion properties.

Characterization of symmetrical SrFe0.75Mo0.25O3−δ electrodes in direct carbon solid oxide fuel cells

Symmetrical solid oxide fuel cells (SOFCs) that feature nanostructured SrFe0.75Mo0.25O3−δ (SFMO) electrodes which are impregnated into porous La0.9Sr0.1Ga0.8Mg0.2O3−δ (LSGM) skeletons by solution infiltration technique are prepared. The symmetrical SOFCs are investigated in detail by operating with 5 wt% Fe-loaded activated carbon as fuel and ambient air as oxidant. A typical single cell can give a maximum power density of 405 mW cm−2 at 850 °C, which is comparable to the results with Ni-based anode-supported SOFCs. Also, the direct carbon SOFC (DC-SOFC) with reloaded fuel can recover to its initial performance. The microstructures and XRD of the electrodes after test are also examined and analysed. The results show that the SFMO-LSGM composite anode remains porous and maintains its structure stability, implying that the symmetrical SFMO electrodes can be applied into DC-SOFCs.

Band gaps of elastic waves in 1-D phononic crystal with dipolar gradient elasticity

The dispersive relations of Bloch waves in the periodic laminated structure formed by periodically repeating of two different gradient elastic solids are studied in this paper. First, the various wave modes in the gradient elastic solid, which are different from those in the classical elastic solid, are formulated. Apart from the dispersive P wave and SV wave, there are two evanescent waves, which become the P type and S type surface waves at the interface of two different gradient elastic solids. Next, the continuity conditions of displacement vector, the normal derivative of the displacement vector and the monopolar and dipolar tractions across the interface between two different gradient elastic solids are used to derive the transfer matrix of the state vector in a typical single cell. At last, the Bloch theorem of Bloch waves in the periodical structure is used to give the dispersive equation. The in-plane Bloch waves and the anti-plane Bloch waves are both considered in the present work. The oblique propagation situation and the normal propagation situation are also considered, respectively. The numerical results are obtained by solving the dispersive equation. The influences of two microstructure parameters of the gradient elastic solid and the microstructure parameter ratio of two different gradient elastic solids on the dispersive relation are discussed based on the numerical results.

Plasma membrane temperature gradients and multiple cell permeabilization induced by low peak power density femtosecond lasers

Calculations indicate that selectively heating the extracellular media induces membrane temperature gradients that combine with electric fields and a temperature-induced reduction in the electropermeabilization threshold to potentially facilitate exogenous molecular delivery. Experiments by a wide-field, pulsed femtosecond laser with peak power density far below typical single cell optical delivery systems confirmed this hypothesis. Operating this laser in continuous wave mode at the same average power permeabilized many fewer cells, suggesting that bulk heating alone is insufficient and temperature gradients are crucial for permeabilization. This work suggests promising opportunities for a high throughput, low cost, contactless method for laser mediated exogenous molecule delivery without the complex optics of typical single cell optoinjection, for potential integration into microscope imaging and microfluidic systems.

Dispersion relations of elastic waves in one-dimensional piezoelectric phononic crystal with mechanically and dielectrically imperfect interfaces

The effects of mechanically and dielectrically imperfect interfaces on dispersion relations of elastic waves in a one-dimensional piezoelectric phononic crystal are studied in this paper. Six kinds of imperfect interfaces between two different piezoelectric materials constituting the phononic crystal are considered. These imperfect interfaces include: the mechanically compliant dielectrically weakly conducting interface, the mechanically compliant dielectrically highly conducting interface, the grounded metallized interface, the low dielectric interface, the tangent fixed interface and the tangent slippery interface. Based on transfer matrices of piezoelectric slabs and imperfect interfaces, the total transfer matrix of a typical single cell in the periodical structure is obtained. Furthermore, the Bloch theorem is used to obtain the dispersive equations of in-plane and anti-plane Bloch waves. The dispersive equations are solved numerically and the numerical results are shown graphically. In the case of normal propagation of elastic waves within piezoelectric slabs, the analytical expressions of the dispersion equations are derived and compared with other literatures. The influences of mechanically and dielectrically imperfect interfaces on the dispersive relations are discussed based on the numerical results.

SC3-seq: a method for highly parallel and quantitative measurement of single-cell gene expression.

Single-cell mRNA sequencing (RNA-seq) methods have undergone rapid development in recent years, and transcriptome analysis of relevant cell populations at single-cell resolution has become a key research area of biomedical sciences. We here present single-cell mRNA 3-prime end sequencing (SC3-seq), a practical methodology based on PCR amplification followed by 3-prime-end enrichment for highly quantitative, parallel and cost-effective measurement of gene expression in single cells. The SC3-seq allows excellent quantitative measurement of mRNAs ranging from the 10,000-cell to 1-cell level, and accordingly, allows an accurate estimate of the transcript levels by a regression of the read counts of spike-in RNAs with defined copy numbers. The SC3-seq has clear advantages over other typical single-cell RNA-seq methodologies for the quantitative measurement of transcript levels and at a sequence depth required for the saturation of transcript detection. The SC3-seq distinguishes four distinct cell types in the peri-implantation mouse blastocysts. Furthermore, the SC3-seq reveals the heterogeneity in human-induced pluripotent stem cells (hiPSCs) cultured under on-feeder as well as feeder-free conditions, demonstrating a more homogeneous property of the feeder-free hiPSCs. We propose that SC3-seq might be used as a powerful strategy for single-cell transcriptome analysis in a broad range of investigations in biomedical sciences.

Behavior of strontium- and magnesium-doped gallate electrolyte in direct carbon solid oxide fuel cells

Perovskite-type La0.9Sr0.1Ga0.8Mg0.2O3−δ (LSGM) is synthesized by conventional solid state reaction. Its phase composition, microstructure, relative density, and oxygen-ionic conductivity are investigated. Tubular electrolyte-supported solid oxide fuel cells (SOFCs) are prepared with the LSGM as electrolyte and gadolinia doped ceria (GDC) mixed with silver as anode. The SOFCs are operated with Fe-loaded activated carbon as fuel and ambient air as oxidant. A typical single cell gives a maximum power density of 383mWcm−2 at 850°C, which is nearly 1.3times higher than that of the similar cell with YSZ as electrolyte. A stability test of 72min is carried out at a constant current density of 210mAcm−2, with a fuel utilization of 60%, indicating that LaGaO3-based electrolyte is promising to be applied in direct carbon SOFCs (DC-SOFCs).

Specific energy distribution within cytoplasm and nucleoplasm of a typical mammalian cell due to various beta radionuclides

The use of beta radionuclides for treatment in radiotherapies leads for a need of better understanding of interactions and local energy depositions of beta particles within tissue and tissue equivalent media. The aim of this work is to determine microdosimetric quantities for various radionuclides. Specific energy, z, and its distribution, $$ f(z) $$ , mean specific energy, $$ \bar{z} $$ , and its standard deviations, $$ \sigma \left( {\bar{z}_{f} } \right) $$ , were evaluated for typical single cell where nucleus is the cellular region of interest. Three possible positions of radionuclides were taken into account—cellular membrane, cytoplasm and nucleoplasm. Taking these regions as the source of radiation, microdosimetric quantities were calculated for beta emitting radionuclides: 191Os, 199Au, 177Lu, 67Cu, 77As, 131I, 186Re, 32P, 188Re and 90Y. It was found that low range beta emitters have the largest efficiency and can deliver radiation doses up to 1 mGy per decay. Determination of the specific energy and its distribution for radionuclides is a useful start in order to determine beta emitters for a particular radionuclide therapy.

Modification of Results From Computational-Fluid-Dynamics Simulations of Single-Cell Solid-Oxide Fuel Cells to Estimate Multicell Stack Performance

A typical single-cell fuel cell is capable of producing less than 1 V of direct current. Therefore, to produce the voltages required in most industrial applications, many individual fuel cells must typically be stacked together and connected electrically in series. Computational fluid dynamics (CFD) can be helpful to predict fuel-cell performance before a cell is actually built and tested. However, to perform a CFD simulation using a three-dimensional model of an entire fuel-cell stack can require a considerable amount of time and multiprocessor computing capability that may not be available to the designer. To eliminate the need to model an entire multicell assembly, a study was conducted to determine the incremental effect on fuel-cell performance of adding individual solid-oxide fuel cells (SOFCs) to a CFD model of a multicell stack. As part of this process, a series of simulations was conducted to establish a CFD-nodal density that would not only produce reasonably accurate results but could also be used to create and analyze the relatively large models of the multicell stacks. Full three-dimensional CFD models were then created of a single-cell SOFC and of SOFC stacks containing two, three, four, five, and six cells. Values of the voltages produced when operating with various current densities, together with temperature distributions, were generated for each of these CFD models. By comparing the results from each of the simulations, adjustment factors were developed to permit single-cell CFD results to be modified to estimate the performance of stacks containing multiple fuel cells. The use of these factors could enable fuel-cell designers to predict multicell stack performance using a CFD model of only a single cell.