Individual Cells Research Articles

Compact Linear Flow Phantom Model for Retinal Blood-Flow Evaluation.

Impaired retinal blood flow is associated with ocular diseases such as glaucoma, macular degeneration, and diabetic retinopathy. Among several ocular imaging techniques developed to measure retinal blood flow both invasively and non-invasively, adaptive optics (AO)-enabled scanning laser ophthalmoscopy (AO-SLO) resolves individual red blood cells and provides a high resolution with which to measure flow across retinal microvasculature. However, cross-validation of flow measures remains a challenge owing to instrument and patient-specific variability in each imaging technique. Hence, there is a critical need for a well-controlled clinical flow phantom for standardization and to establish blood-flow measures as clinical biomarkers for early diagnosis. Here, we present the design and validation of a simple, compact, portable, linear flow phantom based on a direct current motor and a conveyor-belt system that provides linear velocity tuning within the retinal microvasculature range (0.5-7 mm/s). The model was evaluated using a sensitive AO-SLO line-scan technique, which showed a <6% standard deviation from the true velocity. Further, a clinical SLO instrument showed a linear correlation with the phantom's true velocity (r2 > 0.997). This model has great potential to calibrate, evaluate, and improve the accuracy of existing clinical imaging systems for retinal blood flow and aid in the diagnosis of ocular diseases with abnormal blood flow.

Investigating the effect of turbulence on hemolysis through cell-resolved fluid-structure interaction simulations of individual red blood cells

Investigating the effect of turbulence on hemolysis through cell-resolved fluid-structure interaction simulations of individual red blood cells

Cell-Cell Interactions: How Coupled Boolean Networks Tend to Criticality.

Biological cells are usually operating in conditions characterized by intercellular signaling and interaction, which are supposed to strongly influence individual cell dynamics. In this work, we study the dynamics of interacting random Boolean networks, focusing on attractor properties and response to perturbations. We observe that the properties of isolated critical Boolean networks are substantially maintained also in interaction settings, while interactions bias the dynamics of chaotic and ordered networks toward that of critical cells. The increase in attractors observed in multicellular scenarios, compared to single cells, allows us to hypothesize that biological processes, such as ontogeny and cell differentiation, leverage interactions to modulate individual and collective cell responses.

Imaging and quantification of human and viral circular RNAs.

We present a robust approach for cellular detection, imaging, localization, and quantification of human and viral encoded circular RNAs (circRNA) using amplified fluorescence in situ hybridization (ampFISH). In this procedure, a pair of hairpin probes bind next to each other at contiguous stretches of sequence and then undergo a conformational reorganization which initiates a target-dependent hybridization chain reaction (HCR) resulting in deposition of an amplified fluorescent signal at the site. By harnessing the capabilities of both ampFISH and single-molecule FISH (smFISH), we selectively identified and imaged circular RNAs and their linear counterparts derived from the human genome, SARS-CoV-2 (an RNA virus), and human cytomegalovirus (HCMV, a DNA virus). Computational image processing facilitated accurate quantification of circular RNA molecules in individual cells. The specificity of ampFISH for circular RNA detection was confirmed through an in situ RNase R treatment that selectively degrades linear RNAs without impacting circular RNAs. The effectiveness of circular RNA detection was further validated by using ampFISH probes with mismatches and probe pairs that do not bind to the continuous sequence in their target RNAs but instead bind at segregated sites. An additional specificity test involved probes against the negative strands of the circular RNA sequence, absent in the cell. Importantly, our technique allows simultaneous detection of circular RNAs and their linear counterparts within the same cell with single molecule sensitivity, enabling explorations of circular RNA biogenesis, subcellular localization, and functions.

Experimental determination of stray currents in parallel operated cells exemplified on alkaline water electrolysis

Avoiding undesired electric field-driven cell-to-cell ion conduction is a common issue in electrochemical bipolar stacks affecting many processes such as alkaline water electrolysis, chlor-alkali electrolysis, and redox flow batteries. In bipolar stack systems, they are known as ionic shunt or stray currents and flow alongside a cell stack through the electrolyte manifolds bypassing the bipolar plates. A similar phenomenon occurs if multiple single cells are operated in parallel with a common electrolyte supply, even though each individual cell is galvanically isolated. If the parallel cells are operated at different voltages, an electrochemical potential gradient is formed across the electrolyte tube manifold, causing stray currents to flow from one cell to the other. It is important to determine and reduce stray currents and its implications to ensure high system efficiency and maximum system lifetime. This work presents a new approach with which stray currents between parallel operated, galvanically isolated electrochemical cells has been determined for the first time. For this purpose, an ionic 4-point measurement was implemented into an experimental setup with two electrolyzer flow cells with a common electrolyte supply using reference electrodes. This approach was used to measure the potential differences ΔE between both electrolyzers exemplarily for alkaline water electrolysis. Combined with the measured ionic resistances of the electrolyte within the polymeric tube manifold, stray currents were accurately determined. The presented results show that the ionic 4-point measurement could be successfully implemented and validated to experimentally determine stray currents between parallelly operated cells. The method presented enabled stray current measurements with high precision in the mA range. Due to the high cell currents and high ionic tube resistance, the stray current is less than 1 % in the introduced electrochemical setup. The demonstrated systematic measurement approach can be easily transferred to other electrochemical systems or processes.

SnapHiC-G: identifying long-range enhancer-promoter interactions from single-cell Hi-C data via a global background model.

Harnessing the power of single-cell genomics technologies, single-cell Hi-C (scHi-C) and its derived technologies provide powerful tools to measure spatial proximity between regulatory elements and their target genes in individual cells. Using a global background model, we propose SnapHiC-G, a computational method, to identify long-range enhancer-promoter interactions from scHi-C data. We applied SnapHiC-G to scHi-C datasets generated from mouse embryonic stem cells and human brain cortical cells. SnapHiC-G achieved high sensitivity in identifying long-range enhancer-promoter interactions. Moreover, SnapHiC-G can identify putative target genes for noncoding genome-wide association study (GWAS) variants, and the genetic heritability of neuropsychiatric diseases is enriched for single-nucleotide polymorphisms (SNPs) within SnapHiC-G-identified interactions in a cell-type-specific manner. In sum, SnapHiC-G is a powerful tool for characterizing cell-type-specific enhancer-promoter interactions from complex tissues and can facilitate the discovery of chromatin interactions important for gene regulation in biologically relevant cell types.

Illuminating microbial mat assembly: Cyanobacteria and Chloroflexota cooperate to structure light-responsive biofilms.

Microbial mats are stratified communities often dominated by unicellular and filamentous phototrophs within an exopolymer matrix. It is challenging to quantify the dynamic responses of community members in situ as they experience steep gradients and rapid fluctuations of light. To address this, we developed a binary consortium using two representative isolates from hot spring mats, the unicellular oxygenic phototrophic cyanobacterium Synechococcus OS-B' (Syn OS-B') and the filamentous anoxygenic phototroph Chloroflexus MS-CIW-1 (Chfl MS-1). We quantified the motility of individual cells and entire colonies and demonstrated that Chfl MS-1 formed bundles of filaments that moved in all directions with no directional bias to light. Syn OS- B' was slightly less motile but exhibited positive phototaxis. This binary consortium displayed cooperative behavior by moving further than either species alone and formed ordered arrays where both species aligned with the light source. No cooperative motility was observed when a non-motile pilB mutant of Syn OS-B' was used instead of Syn OS-B'. The binary consortium also produced more adherent biofilm than individual species, consistent with the close interspecies association revealed by electron microscopy. We propose that cyanobacteria and Chloroflexota cooperate in forming natural microbial mats, by colonizing new niches and building robust biofilms.

Characterizing Mesoscale Cellular Convection in Marine Cold Air Outbreaks With a Machine Learning Approach

AbstractDuring marine cold‐air outbreaks (MCAOs), when cold polar air moves over warmer ocean, a well‐recognized cloud pattern develops, with open or closed mesoscale cellular convection (MCC) at larger fetch over open water. The Cold‐Air Outbreaks in the Marine Boundary Layer Experiment provided a comprehensive set of ground‐based in situ and remote sensing observations of MCAOs at a coastal location in northern Norway. MCAO periods that unambiguously exhibit open or closed MCC are determined. Individual cells observed with a profiling Ka‐band radar are identified using a watershed segmentation method. Using self‐organizing maps (SOMs), these cells are then objectively classified based on the variability in their vertical structure. The SOM nodes contain some information about the location of the cell transect relative to the center of the MCC. This adds classification noise, requiring numerous cell transects to isolate cell dynamical information. The SOM‐based classification shows that comparatively intense convection occurs only in open MCC. This convection undergoes an apparent lifecycle. Developing cells are associated with stronger updrafts, large spectrum width, larger amounts of liquid water, lower surface precipitation rates, and lower cloud tops than mature and weakening cells. The weakening of these cells is associated with the development of precipitation‐induced cold pools. The SOM classification also reveals less intense convection, with a similar lifecycle. More stratiform vertical cloud structures with weak vertical motions are common during closed MCC periods and are separated into precipitating and non‐precipitating stratiform cores. Convection is observed only occasionally in the closed MCC environment.

Evaluating computational efforts and physiological resolution of mathematical models of cardiac tissue

Computational techniques have significantly advanced our understanding of cardiac electrophysiology, yet they have predominantly concentrated on averaged models that do not represent the intricate dynamics near individual cardiomyocytes. Recently, accurate models representing individual cells have gained popularity, enabling analysis of the electrophysiology at the micrometer level. Here, we evaluate five mathematical models to determine their computational efficiency and physiological fidelity. Our findings reveal that cell-based models introduced in recent literature offer both efficiency and precision for simulating small tissue samples (comprising thousands of cardiomyocytes). Conversely, the traditional bidomain model and its simplified counterpart, the monodomain model, are more appropriate for larger tissue masses (encompassing millions to billions of cardiomyocytes). For simulations requiring detailed parameter variations along individual cell membranes, the EMI model emerges as the only viable choice. This model distinctively accounts for the extracellular (E), membrane (M), and intracellular (I) spaces, providing a comprehensive framework for detailed studies. Nonetheless, the EMI model’s applicability to large-scale tissues is limited by its substantial computational demands for subcellular resolution.

Negative selection allows human primary fibroblasts to tolerate high somatic mutation loads induced by N-ethyl-N-nitrosourea.

Single-cell sequencing has shown that thousands of mutations accumulate with age in most human tissues. While there is ample evidence that some mutations can clonally amplify and lead to disease, the total burden of mutations a cell tolerates without functional decline remains unknown. Here we addressed this question by exposing human primary fibroblasts to multiple, low doses of N-ethyl-N-nitrosourea (ENU) and analyzed somatic mutation burden using single-cell whole genome sequencing. The results indicate that individual cells can sustain ∼60,000 single-nucleotide variants (SNVs) with only a slight adverse effect on growth rate. We provide evidence that such high levels of mutations are only tolerated through negative selection against variants in gene coding regions, and in sequences associated with genetic pathways for maintaining basic cellular function and growth. Since most tissues in adults are non-dividing, these results suggest that somatic mutations in the absence of negative selection may have functionally adverse effects.

High-resolution three-dimensional imaging of topological textures in nanoscale single-diamond networks.

Topological defects-extended lattice deformations that are robust against local defects and annealing-have been exploited to engineer novel properties in both hard and soft materials. Yet, their formation kinetics and nanoscale three-dimensional structure are poorly understood, impeding their benefits for nanofabrication. We describe the fabrication of a pair of topological defects in the volume of a single-diamond network (space group Fd m) templated into gold from a triblock terpolymer crystal. Using X-ray nanotomography, we resolve the three-dimensional structure of nearly 70,000 individual single-diamond unit cells with a spatial resolution of 11.2 nm, allowing analysis of the long-range order of the network. The defects observed morphologically resemble the comet and trefoil patterns of equal and opposite half-integer topological charges observed in liquid crystals. Yet our analysis of strain in the network suggests typical hard matter behaviour. Our analysis approach does not require a priori knowledge of the expected positions of the nodes in three-dimensional nanostructured systems, allowing the identification of distorted morphologies and defects in large samples.

Hair cells in the cochlea must tune resonant modes to the edge of instability without destabilizing collective modes.

Sound produces surface waves along the cochlea's basilar membrane. To achieve the ear's astonishing frequency resolution and sensitivity to faint sounds, dissipation in the cochlea must be canceled via active processes in hair cells, effectively bringing the cochlea to the edge of instability. But how can the cochlea be globally tuned to the edge of instability with only local feedback? To address this question, we use a discretized version of a standard model of basilar membrane dynamics, but with an explicit contribution from active processes in hair cells. Surprisingly, we find the basilar membrane supports two qualitatively distinct sets of modes: a continuum of localized modes and a small number of collective extended modes. Localized modes sharply peak at their resonant position and are largely uncoupled. As a result, they can be amplified almost independently from each other by local hair cells via feedback reminiscent of self-organized criticality. However, this amplification can destabilize the collective extended modes; avoiding such instabilities places limits on possible molecular mechanisms for active feedback in hair cells. Our work illuminates how and under what conditions individual hair cells can collectively create a critical cochlea.

Ribosomal protein RPL39L is an efficiency factor in the cotranslational folding of a subset of proteins with alpha helical domains.

Increasingly many studies reveal how ribosome composition can be tuned to optimally translate the transcriptome of individual cell types. In this study, we investigated the expression pattern, structure within the ribosome and effect on protein synthesis of the ribosomal protein paralog 39L (RPL39L). With a novel mass spectrometric approach we revealed the expression of RPL39L protein beyond mouse germ cells, in human pluripotent cells, cancer cell lines and tissue samples. We generated RPL39L knock-out mouse embryonic stem cell (mESC) lines and demonstrated that RPL39L impacts the dynamics of translation, to support the pluripotency and differentiation, spontaneous and along the germ cell lineage. Most differences in protein abundance between WT and RPL39L KO lines were explained by widespread autophagy. By CryoEM analysis of purified RPL39 and RPL39L-containing ribosomes we found that, unlike RPL39, RPL39L has two distinct conformations in the exposed segment of the nascent peptide exit tunnel, creating a distinct hydrophobic patch that has been predicted to support the efficient co-translational folding of alpha helices. Our study shows that ribosomal protein paralogs provide switchable modular components that can tune translation to the protein production needs of individual cell types.

ALTMAN: A Novel Method for Cell Cycle Analysis.

Accurate analysis of S-phase fraction is crucial for the assessment of cell proliferation levels, tumor malignancy and prognostic effects of treatment. Most of the currently developed methods for S-phase cell analysis rely on flow cytometric analysis of DNA content determination. However, the lack of standardized procedures for sample analysis and interpretation of cell cycle fitting graphs poses a significant limitation in clinical practice for utilizing flow cytometry to measure the cell cycle based on DNA content. Herein, we developed an approach for analyzing S-phase cells based on telomerase activity determination. Briefly, this approach distinguishes S-phase cells in cell populations via direct fluorescence tracking of telomerase activity within individual cells. The dynamic analysis of telomerase activity in different cell cycles was made possible by the ALTMAN strategy developed in our previous studies, which has been successfully employed to distinguish S-phase cells in cultured cells. This method offers a novel avenue for the assessment of cell cycle status and the evaluation of the proliferation status of tumor cells and the prognosis effect of tumor patients via analyzing the differences in telomerase activity during different cell cycle processes.

Simulation of Soluble and Bound VEGF-stimulated in vitro Capillary-like Network Formation on Deformed Substrate.

Capillary plexus cultivation is crucial in tissue engineering and regenerative medicine. Theoretical simulations have been conducted to supplement the expensive experimental works. However, the mechanisms connecting mechanical and chemical stimuli remained undefined, and the functions of the different VEGF forms in the culture environment were still unclear. In this paper, we developed a hybrid model for simulating short-term in vitro capillary incubations. We used the Cellular Potts model to predict individual cell migration, morphology change, and continuum mechanics to quantify biogel deformation and VEGF transport dynamics. By bridging the mechanical regulation and chemical stimulation in the model, the results showed good agreement between the predicted network topology and experiments, in which elongated cells connected, forming the network cords and round cells gathered, creating cobblestone-like aggregates. The results revealed that the capillary-like networks could develop in high integrity only when the mechanical and chemical couplings worked adequately, with the cell morphology and haptotaxis driven by the soluble and bound forms of VEGF, respectively, functioning simultaneously.

Genetic Identity of Neural Crest Cell Differentiation in Tissue and Organ Development.

The neural crest (NC), also known as the "fourth germ layer", is an embryonic structure with important contributions to multiple tissue and organ systems. Neural crest cells (NCCs) are subjected to epithelial to mesenchymal transition and migrate throughout the embryo until they reach their destinations, where they differentiate into discrete cell types. Specific gene expression enables this precise NCCs delamination and colonization potency in distinct and diverse locations therein. This review aims to summarize the current experimental evidence from multiple species into the NCCs specifier genes that drive this embryo body axes segmentation. Additionally, it attempts to filter further into the genetic background that produces these individual cell subpopulations. Understanding the multifaceted genetic makeup that shapes NC-related embryonic structures will offer valuable insights to researchers studying organogenesis and disease phenotypes arising from dysmorphogenesis.

Perturbation of periodic spot-generation balance leads to diversified pigmentation patterning of harlequin Phalaenopsis orchids: in silico prediction

BackgroundA retrotransposon HORT1 in the promoter of the anthocyanin activator gene PeMYB11, microRNA858 (miR858) that targets PeMYB11, and a repressor PeMYBx have been implicated in pigmentation patterning diversity of harlequin Phalaenopsis orchids. However, the interrelationship among them remains to be elucidated.ResultsTo understand how these factors interact to generate anthocyanin spots in Phalaenopsis, we successfully developed a mathematical model based on the known reaction–diffusion system to simulate their interplay and refined the conceptual biological model. Intriguingly, the expression of both PeMYBx and PeMYB11 were in phase for purple spot formation, even though they showed adverse effects on anthocyanin accumulations. An increase in the self-activation rate of PeMYB11 resulted in the increased size of purple spots, but no effects on spot fusion. Decreased degradation rate of miR858 in the purple regions, led to disruption of the formation of spotted pigmentation patterning and a full-red pigmentation pattern. Significantly, the reduced miR858 level promotes the fusion of large dark purple dots induced by the solo-LTR of HORT1, eventually generating the purple patches. In addition, the spatially heterogeneous insertion of HORT1 caused by the remnant solo-LTR of HORT1 derived from random homologous unequal recombination of HORT1 in individual cells of floral organs could explain the diverse pigmentation patterning of harlequin Phalaenopsis.ConclusionsThis devised model explains how HORT1 and miR858 regulate the formation of the pigmentation patterning and holds great promise for developing efficient and innovative approaches to breeding harlequin Phalaenopsis orchids.

Single-cell gene-expression measurements in Vibrio cholerae biofilms reveal spatiotemporal patterns underlying development.

Bacteria commonly exist in multicellular, surface-attached communities called biofilms. Biofilms are central to ecology, medicine, and industry. The Vibrio cholerae pathogen forms biofilms from single founder cells that, via cell division, mature into three-dimensional structures with distinct, yet reproducible, regional architectures. To define mechanisms underlying biofilm developmental transitions, we establish a single-molecule fluorescence in situ hybridization (smFISH) approach that enables accurate quantitation of spatiotemporal gene-expression patterns in biofilms at individual-cell resolution. smFISH analyses of V. cholerae biofilm regulatory and structural genes demonstrate that, as biofilms mature, matrix gene expression decreases, and simultaneously, a pattern emerges in which matrix gene expression is largely confined to peripheral biofilm cells. Both quorum sensing and c-di-GMP-signaling are required to generate the proper temporal pattern of matrix gene expression, while c-di-GMP-signaling sets the regional expression pattern without input from quorum sensing. The smFISH strategy provides insight into mechanisms conferring particular fates to individual biofilm cells.

Proteomics-based method to comprehensively model the removal of host cell protein impurities.

Mechanistic models mostly focus on the target protein and some selected process- or product-related impurities. For a better process understanding, however, it is advantageous to describe also reoccurring host cell protein impurities. Within the purification of biopharmaceuticals, the binding of host cell proteins to a chromatographic resin is far from being described comprehensively. For a broader coverage of the binding characteristics, large-scale proteomic data and systems level knowledge on protein interactions are key. However, a method for determining binding parameters of the entire host cell proteome to selected chromatography resins is still lacking. In this work, we have developed a method to determine binding parameters of all detected individual host cell proteins in an Escherichia coli harvest sample from large-scale proteomics experiments. The developed method was demonstrated to model abundant and problematic proteins, which are crucial impurities to be removed. For these 15 proteins covering varying concentration ranges, the model predicts the independently measured retention time during the validation gradient well. Finally, we optimized the anion exchange chromatography capture step in silico using the determined isotherm parameters of the persistent host cell protein contaminants. From these results, strategies can be developed to separate abundant and problematic impurities from the target antigen.

Single-cell mass cytometry in immunological skin diseases.

Immune-related skin diseases represent a collective of dermatological disorders intricately linked to dysfunctional immune system processes. These conditions are primarily characterized by an immoderate activation of the immune system or deviant immune responses, involving diverse immune components including immune cells, antibodies, and inflammatory mediators. However, the precise molecular dysregulation underlying numerous individual cases of these diseases and unique subsets respond under disease conditions remains elusive. Comprehending the mechanisms and determinants governing the homeostasis and functionality of diseases could offer potential therapeutic opportunities for intervention. Mass cytometry enables precise and high-throughput quantitative measurement of proteins within individual cells by utilizing antibodies labeled with rare heavy metal isotopes. Imaging mass cytometry employs mass spectrometry to obtain spatial information on cell-to-cell interactions within tissue sections, simultaneously utilizing more than 40 markers. The application of single-cell mass cytometry presents a unique opportunity to conduct highly multiplexed analysis at the single-cell level, thereby revolutionizing our understanding of cell population heterogeneity and hierarchy, cellular states, multiplexed signaling pathways, proteolysis products, and mRNA transcripts specifically in the context of many autoimmune diseases. This information holds the potential to offer novel approaches for the diagnosis, prognostic assessment, and monitoring responses to treatment, thereby enriching our strategies in managing the respective conditions. This review summarizes the present-day utilization of single-cell mass cytometry in studying immune-related skin diseases, highlighting its advantages and limitations. This technique will become increasingly prevalent in conducting extensive investigations into these disorders, ultimately yielding significant contributions to their accurate diagnosis and efficacious therapeutic interventions.