Reconstruction of cellular variability from spatiotemporal patterns of Dictyostelium discoideum

Variability in cell properties can be an important driving mechanism behind spatiotemporal patterns in biological systems, as the degree of cell-to-cell differences determines the capacity of cells to locally synchronize and, consequently, form patterns on a larger spatial scale. In principle, certain features of spatial patterns emerging with time may be regulated by variability or, more specifically, by certain constellations of cell-to-cell differences. Similarly, measuring variability in a system (i.e. the spatial distribution of cell-cell differences) may help predict properties of later-stage patterns.     

Role of AF6 protein in cell-to-cell spread of Herpes simplex virus 1

AF6 and its rat homologue afadin are multidomain proteins localized at cell junctions and involved in intercellular adhesion. AF6 interacts via its PDZ domain with nectin-1 at epithelial adherens junctions. Nectin-1 serves as a mediator of cell-to-cell spread for Herpes simplex virus 1 (HSV-1). We analyzed the role of AF6 protein in the viral spread and nectin-1 clustering at cell-cell contacts by knockdown of AF6 in epithelial cells. AF6 knockdown reduced efficiency of HSV-1 spreading, however, the clustering of nectin-1 at cell-cell contacts was not affected. Thus, AF6 protein is important for spreading of HSV-1 in epithelial cells, independently of nectin clustering, possibly by stabilization of the E-cadherin-dependent cell adhesion.     

CCAST: A Model-Based Gating Strategy to Isolate Homogeneous Subpopulations in a Heterogeneous Population of Single Cells

A model-based gating strategy is developed for sorting cells and analyzing populations of single cells. The strategy, named CCAST, for Clustering, Classification and Sorting Tree, identifies a gating strategy for isolating homogeneous subpopulations from a heterogeneous population of single cells using a data-derived decision tree representation that can be applied to cell sorting. Because CCAST does not rely on expert knowledge, it removes human bias and variability when determining the gating strategy. It combines any clustering algorithm with silhouette measures to identify underlying homogeneous subpopulations, then applies recursive partitioning techniques to generate a decision tree that defines the gating strategy. CCAST produces an optimal strategy for cell sorting by automating the selection of gating markers, the corresponding gating thresholds and gating sequence; all of these parameters are typically manually defined. Even though CCAST is optimized for cell sorting, it can be applied for the identification and analysis of homogeneous subpopulations among heterogeneous single cell data. We apply CCAST on single cell data from both breast cancer cell lines and normal human bone marrow. On the SUM159 breast cancer cell line data, CCAST indicates at least five distinct cell states based on two surface markers (CD24 and EPCAM) and provides a gating sorting strategy that produces more homogeneous subpopulations than previously reported. When applied to normal bone marrow data, CCAST reveals an efficient strategy for gating T-cells without prior knowledge of the major T-cell subtypes and the markers that best define them. On the normal bone marrow data, CCAST also reveals two major mature B-cell subtypes, namely CD123+ and CD123- cells, which were not revealed by manual gating but show distinct intracellular signaling responses. More generally, the CCAST framework could be used on other biological and non-biological high dimensional data types that are mixtures of unknown homogeneous subpopulations.     

Emergence of bimodal cell population responses from the interplay between analog single-cell signaling and protein expression noise

ABSTRACT: BACKGROUND: Cell-to-cell variability in protein expression can be large, and its propagation through signaling networks affects biological outcomes. Here, we apply deterministic and probabilistic models and biochemical measurements to study how network topologies and cell-to-cell protein abundance variations interact to shape signaling responses. RESULTS: We observe bimodal distributions of extracellular signal-regulated kinase (ERK) responses to epidermal growth factor (EGF) stimulation, which are generally thought to indicate bistable or ultrasensitive signaling behavior in single cells. Surprisingly, we find that a simple MAPK/ERK-cascade model with negative feedback that displays graded, analog ERK responses at a single cell level can explain the experimentally observed bimodality at the cell population level. Model analysis suggests that a conversion of graded input--output responses in single cells to digital responses at the population level is caused by a broad distribution of ERK pathway activation thresholds brought about by cell-to-cell variability in protein expression. CONCLUSIONS: Our results show that bimodal signaling response distributions do not necessarily imply digital (ultrasensitive or bistable) single cell signaling, and the interplay between protein expression noise and network topologies can bring about digital population responses from analog single cell dose responses. Thus, cells can retain the benefits of robustness arising from negative feedback, while simultaneously generating population-level on/off responses that are thought to be critical for regulating cell fate decisions.     

Myeloid Dendritic Cells Induce HIV-1 Latency in Non-proliferating CD4+ T Cells

Latently infected resting CD4⁺ T cells are a major barrier to HIV cure. Understanding how latency is established, maintained and reversed is critical to identifying novel strategies to eliminate latently infected cells. We demonstrate here that co-culture of resting CD4⁺ T cells and syngeneic myeloid dendritic cells (mDC) can dramatically increase the frequency of HIV DNA integration and latent HIV infection in non-proliferating memory, but not naïve, CD4⁺ T cells. Latency was eliminated when cell-to-cell contact was prevented in the mDC-T cell co-cultures and reduced when clustering was minimised in the mDC-T cell co-cultures. Supernatants from infected mDC-T cell co-cultures did not facilitate the establishment of latency, consistent with cell-cell contact and not a soluble factor being critical for mediating latent infection of resting CD4⁺ T cells. Gene expression in non-proliferating CD4⁺ T cells, enriched for latent infection, showed significant changes in the expression of genes involved in cellular activation and interferon regulated pathways, including the down-regulation of genes controlling both NF-κB and cell cycle. We conclude that mDC play a key role in the establishment of HIV latency in resting memory CD4⁺ T cells, which is predominantly mediated through signalling during DC-T cell contact.     

On-chip single-cell-based microcultivation method for analysis of genetic information and epigenetic correlation of cells

We have developed an on-chip single-cell based microcultivation method for analyzing the variability of genetic information stored in single cells and their epigenetic correlations. The method uses four systems: an on-chip cell sorter for purifying the cells in a non-destructive manner; an on-chip single-cell cultivation chip for isolating single cells; an on-chip agarose microchamber system for constructive cell-cell network formation during cultivation; and an on-chip single-cell-based expression analysis system. Using these systems, we could measure the variability of prokaryotic cells and eukaryotic cells having the same DNA and found that, although prokaryotic cells have a large variability in their interdivision times, sister eukaryotic cells having the same DNA synchronized well. We also measured the dynamics of synchronization of beating cardiac myocytes and found that two isolated cells synchronize by one cell following the other after a short pause in beating. These results showed the potential of the on-chip microcultivation method's constructive approach to analyzing cell systems.     

BASiCS: Bayesian Analysis of Single-Cell Sequencing Data

Single-cell mRNA sequencing can uncover novel cell-to-cell heterogeneity in gene expression levels in seemingly homogeneous populations of cells. However, these experiments are prone to high levels of unexplained technical noise, creating new challenges for identifying genes that show genuine heterogeneous expression within the population of cells under study. BASiCS (Bayesian Analysis of Single-Cell Sequencing data) is an integrated Bayesian hierarchical model where: (i) cell-specific normalisation constants are estimated as part of the model parameters, (ii) technical variability is quantified based on spike-in genes that are artificially introduced to each analysed cell’s lysate and (iii) the total variability of the expression counts is decomposed into technical and biological components. BASiCS also provides an intuitive detection criterion for highly (or lowly) variable genes within the population of cells under study. This is formalised by means of tail posterior probabilities associated to high (or low) biological cell-to-cell variance contributions, quantities that can be easily interpreted by users. We demonstrate our method using gene expression measurements from mouse Embryonic Stem Cells. Cross-validation and meaningful enrichment of gene ontology categories within genes classified as highly (or lowly) variable supports the efficacy of our approach.     

Effects of blocking integrin β1 and N-cadherin cellular interactions on mechanical properties of vascular smooth muscle cells

Experimental measurements of cellular mechanical properties have shown large variability in whole-cell mechanical properties between cells from a single population. This heterogeneity has been observed in many cell populations and with several measurement techniques but the sources are not yet fully understood. Cell mechanical properties are directly related to the composition and organization of the cytoskeleton, which is physically coupled to neighboring cells through adherens junctions and to underlying matrix through focal adhesion complexes. This high level of heterogeneity may be attributed to varying cellular interactions throughout the sample. We tested the effect of cell-cell and cell-matrix interactions on the mechanical properties of vascular smooth muscle cells (VSMCs) in culture by using antibodies to block N-cadherin and integrin β1 interactions. VSMCs were cultured on substrates of varying stiffness with and without tension. Under each of these conditions, cellular mechanical properties were characterized by performing atomic force microscopy (AFM) and cellular structure was analyzed through immunofluorescence imaging. As expected, VSMC mechanical properties were greatly affected by the underlying culture substrate and applied tension. Interestingly, the cell-to-cell variation in mechanical properties within each sample decreased significantly in the antibody conditions. Thus, the cells grown with blocking antibodies were more homogeneous in their mechanical properties on both glass and soft substrates. This suggests that diversified adhesion binding between cells and the ECM is responsible for a significant amount of mechanical heterogeneity that is observed in 2D cell culture studies.     

DLGCN:基于图卷积网络的药物-lncRNA[]关联预测

为实现高通量识别新的药物-长链非编码RNA(Long non-coding RNA, lncRNA)关联,本文提出了一种基于图卷积网络模型来识别潜在药物-lncRNA关联的方法DLGCN(Drug-LncRNA graph convolution network)。首先,基于药物的结构信息和lncRNA的序列信息分别构建了药物-药物和lncRNA-lncRNA相似性网络,并整合实验证实的药物-lncRNA关联构建了药物-lncRNA异质性网络。然后,将注意力机制和图卷积运算应用于该网络中,学习药物和lncRNA的低维特征,基于整合的低维特征预测新的药物-lncRNA关联。通过效能评估,DLGCN的受试者工作特性曲线下面积(Area under receiver operating characteristic, AUROC)达到0.843 1,优于经典的机器学习方法和常见的深度学习方法。此外,DLGCN预测到姜黄素能够调控lncRNA MALAT1的表达,已被最近的研究证实。DLGCN能够有效预测药物-lncRNA关联,为肿瘤治疗新靶点的识别和抗癌药物的筛选提供了重要参考。     

Predictive power of cell-to-cell variability

Much of our current knowledge of biology has been constructed based on population-average measurements. However, advances in single-cell analysis have demonstrated the omnipresent nature of cell-to-cell variability in any population. On one hand, tremendous efforts have been made to examine how such variability arises, how it is regulated by cellular networks, and how it can affect cell-fate decisions by single cells. On the other hand, recent studies suggest that the variability may carry valuable information that can facilitate the elucidation of underlying regulatory networks or the classification of cell states. To this end, a major challenge is determining what aspects of variability bear significant biological meaning. Addressing this challenge requires the development of new computational tools, in conjunction with appropriately chosen experimental platforms, to more effectively describe and interpret data on cell-cell variability. Here, we discuss examples of when population heterogeneity plays critical roles in determining biologically and clinically significant phenotypes, how it serves as a rich information source of regulatory mechanisms, and how we can extract such information to gain a deeper understanding of biological systems.     

Revealing non-genetic adhesive variations in clonal populations by comparative single-cell force spectroscopy

Cell populations often display heterogeneous behavior, including cell-to-cell variations in morphology, adhesion and spreading. However, better understanding the significance of such cell variations for the function of the population as a whole requires quantitative single-cell assays. To investigate adhesion variability in a CHO cell population in detail, we measured integrin-mediated adhesion to laminin and collagen, two ubiquitous ECM components, by AFM-based single-cell force spectroscopy (SCFS). CHO cells generally adhered more strongly to laminin than collagen but population adhesion force distributions to both ECM components were broad and partially overlapped. To determine the levels of laminin and collagen binding in individual cells directly, we alternatingly measured single cells on adjacent microstripes of collagen and laminin arrayed on the same adhesion substrate. In repeated measurements (≥60) individual cells showed a stable and ECM type-specific adhesion response. All tested cells bound laminin more strongly, but the scale of laminin over collagen binding varied between cells. Together, this demonstrates that adhesion levels to different ECM components are tightly yet differently set in each cell of the population. Adhesion variability to laminin was non-genetic and cell cycle-independent but scaled with the range of α6 integrin expression on the cell surface. Adhesive cell-to-cell variations due to varying receptor expression levels thus appear to be an inherent feature of cell populations and should to be considered when fully characterizing population adhesion. In this approach, SCFS performed on multifunctional adhesion substrates can provide quantitative single-cell information not obtainable from population-averaging measurements on homogeneous adhesion substrates.     

Oscillatory dynamics of cell cycle proteins in single yeast cells analyzed by imaging cytometry

Progression through the cell division cycle is orchestrated by a complex network of interacting genes and proteins. Some of these proteins are known to fluctuate periodically during the cell cycle, but a systematic study of the fluctuations of a broad sample of cell-cycle proteins has not been made until now. Using time-lapse fluorescence microscopy, we profiled 16 strains of budding yeast, each containing GFP fused to a single gene involved in cell cycle regulation. The dynamics of protein abundance and localization were characterized by extracting the amplitude, period, and other indicators from a series of images. Oscillations of protein abundance could clearly be identified for Cdc15, Clb2, Cln1, Cln2, Mcm1, Net1, Sic1, and Whi5. The period of oscillation of the fluorescently tagged proteins is generally in good agreement with the inter-bud time. The very strong oscillations of Net1 and Mcm1 expression are remarkable since little is known about the temporal expression of these genes. By collecting data from large samples of single cells, we quantified some aspects of cell-to-cell variability due presumably to intrinsic and extrinsic noise affecting the cell cycle.     

Phenotypic heterogeneity in expression of epitopes in the Cryptococcus neoformans capsule

The opportunistic yeast Cryptococcus neoformans is surrounded by a polysaccharide capsule comprised primarily of glucuronoxylomannan (GXM). GXM is a key component of the antigenic character of the capsule. Expression of the epitope that allows for binding of mAbs that require O -acetylation of GXM for mAb recognition was greatly influenced by cell age, growth conditions and serotype. Yeast cells of serotype A grown in vitro under capsule induction conditions showed considerable cell-to-cell variability in binding of two O -acetyl-dependent mAbs, and such mAbs uniformly failed to bind to GXM that covers yeast buds. Expression of the O -acetyl-dependent epitope increased with cell age. In contrast, all serotype A cells harvested from brain tissue bound the same O -acetyl-dependent mAbs. The ability of the cryptococcal capsule to activate the complement cascade and bind C3 occurred uniformly over the surface of all yeast cells, including the bud. Finally, the cell-to-cell variability in binding of O -acetyl-dependent mAbs with strains of serotype A was not found with strains of serotype D; almost all cells of serotype D showed homogeneous binding of O -acetyl-dependent mAbs. These results indicate that variability in expression of antigenic epitopes by GXM should be considered in selection of mAbs used for immunodiagnosis or immunotherapy.     

Cell-to-cell binding induced by different lectins

The cell-to-cell binding induced by concanavalin A (Con A) and the lectins from wheatgerm, soybean, and waxbean has been analyzed by measuring the ability of single cells to bind to lectin-coated cells immobilized on nylon fibers. The cells used were lymphoma, myeloid leukemia, and normal fibroblast cells. With all lectins, cell-to-cell binding was inhibited if both cells were prefixed with glutaraldehyde. However, in most cases cell-to-cell binding was enhanced when only the lectin-coated cell was prefixed. With normal fibroblasts, treatment of either one or both cells with trypsin enhanced the cell-to-cell binding induced by Con A and the wheatgerm lectin. Neuraminidase, which increases the number of receptors for soybean agglutinin, increased cell-to-cell binding only if both cells were treated. Although cell-to- cell binding induced by the lectins from soybean and wheatgerm could be partially reversed by the appropriate competitive saccharide inhibitor, binding induced by Con A could not be reversed. The experiments indicate that cell-to-cell binding induced by a lectin can be prevented by an insufficient density of receptors for the lectin, insufficient receptor mobility, or induced clustering of receptors. These effects can explain the differences in cell-to-cell binding and agglutination observed with different cell types and lectins. They also suggest that cell-to-cell binding induced by different lectins with a variety of cell types is initiated by a mechanism involving the alignment of complementary receptors on the colliding cells for the formation of multiple cell-to-lectin-to-cell bridges.     

Analysis of individual cells identifies cell‐to‐cell variability following induction of cellular senescence

Senescent cells play important roles in both physiological and pathological processes, including cancer and aging. In all cases, however, senescent cells comprise only a small fraction of tissues. Senescent phenotypes have been studied largely in relatively homogeneous populations of cultured cells. In vivo, senescent cells are generally identified by a small number of markers, but whether and how these markers vary among individual cells is unknown. We therefore utilized a combination of single‐cell isolation and a nanofluidic PCR platform to determine the contributions of individual cells to the overall gene expression profile of senescent human fibroblast populations. Individual senescent cells were surprisingly heterogeneous in their gene expression signatures. This cell‐to‐cell variability resulted in a loss of correlation among the expression of several senescence‐associated genes. Many genes encoding senescence‐associated secretory phenotype (SASP) factors, a major contributor to the effects of senescent cells in vivo, showed marked variability with a subset of highly induced genes accounting for the increases observed at the population level. Inflammatory genes in clustered genomic loci showed a greater correlation with senescence compared to nonclustered loci, suggesting that these genes are coregulated by genomic location. Together, these data offer new insights into how genes are regulated in senescent cells and suggest that single markers are inadequate to identify senescent cells in vivo.     

Effects of cytochalasin D on fusion of cells by HVJ (Sendai virus).

Fusion of cells mediated by HVJ was inhibited completely with 5 μg/ml or more of cytochalasin D (CD). With cytochalasin, HVJ-cell interaction at 0 °C proceeded as well as without cytochalasin; HVJ was adsorbed to cell surfaces and the cells agglutinated together. Then the virus particles were enfolded with cell membranes, which resulted in the disappearance of hemadsorption activity on the cell surfaces. When the cell-virus complex was incubated at 37 °C, the early reactions proceeded as well as without cytochalasin; the hemadsorption activity reappeared on the cell surfaces, the viral envelopes fused with cell membranes at the same degree as without cytochalasin, and a stage sensitive to sodium azide appeared as in a control without cytochalasin. But cell-to-cell fusion did not occur in the presence of cytochalasin; cells were dissociated freely from the cell aggregates during incubation. This indicates that cell-to-cell fusion was inhibited but HVJ envelope to cell membrane interactions proceeded well on incubation at 37 °C. These findings suggest that viral envelope-cell membrane fusion and cell-cell fusion are separable, and participation of a cytoskeleton system including microfilaments in the cells is essential for cell-cell fusion.     

Kolmogorov complexity of epithelial pattern formation: The role of regulatory network configuration

The tissues of multicellular organisms are made of differentiated cells arranged in organized patterns. This organization emerges during development from the coupling of dynamic intra- and intercellular regulatory networks. This work applies the methods of information theory to understand how regulatory network structure both within and between cells relates to the complexity of spatial patterns that emerge as a consequence of network operation. A computational study was performed in which undifferentiated cells were arranged in a two dimensional lattice, with gene expression in each cell regulated by identical intracellular randomly generated Boolean networks. Cell–cell contact signalling between embryonic cells is modeled as coupling among intracellular networks so that gene expression in one cell can influence the expression of genes in adjacent cells. In this system, the initially identical cells differentiate and form patterns of different cell types. The complexity of network structure, temporal dynamics and spatial organization is quantified through the Kolmogorov-based measures of normalized compression distance and set complexity. Results over sets of random networks that operate in the ordered, critical and chaotic domains demonstrate that: (1) ordered and critical networks tend to create the most information-rich patterns; (2) signalling configurations in which cell-to-cell communication is non-directional mostly produce simple patterns irrespective of the internal network domain; and (3) directional signalling configurations, similar to those that function in planar cell polarity, produce the most complex patterns, but only when the intracellular networks function in non-chaotic domains.     

Nef does not inhibit F-actin remodelling and HIV-1 cell-cell transmission at the T lymphocyte virological synapse

Nef, a HIV-1 pathogenesis factor, elevates virus replication in vivo and thus progression to AIDS by incompletely defined mechanisms. As one of its biological properties, Nef enhances the infectivity of cell-free HIV-1 particles in single round infections, however it fails to provide a significant and amplifying growth advantage for HIV-1 on such virus producing cells. A major difference between HIV-1 cell-free single round infections and virus replication kinetics on T lymphocytes consists in the predominant role of cell-associated virus transmission rather than cell-free infection during multiple round virus replication. HIV-1 cell-to-cell transmission occurs across close cell contacts also referred to as virological synapse (VS) and involves polarization of the F-actin cytoskeleton, formation of F-actin rich membrane bridges as well as virus budding to cell-cell contacts. Since Nef potently interferes with triggered actin remodelling in several cell systems to reduce e.g. cell motility and signal transduction, we set out here to address whether Nef also affects organization and possibly function of the T lymphocyte VS. We find that in addition to increasing infectivity of cell-free virions, Nef can also moderately enhance single rounds of HIV-1 cell-cell transmission between Jurkat T lymphocytes. This occurs without affecting cell conjugation efficiencies or polarization of F-actin and HIV-1 p24Gag at the VS, identifying actin remodelling at the VS as an example of Nef-insensitive host cell actin rearrangements. However, Nef-mediated enhancement of single round cell-free infection or cell-to-cell transmission does not potentiate over multiple rounds of infection. These results suggest that Nef affects cell-free and cell-associated HIV-1 infection by the same mechanism acting on the intrinsic infectivity of HIV-1 particles. They further indicate that the high efficacy of cell-to-cell transmission can compensate such infectivity defects. Nef therefore selectively interferes with actin remodelling processes involved in antiviral host cell defense while actin driven processes that promote virus propagation remain unaltered.