RESUMO
Complex biological processes, such as cellular differentiation, require intricate rewiring of intra-cellular signalling networks. Previous characterisations revealed a raised network entropy underlies less differentiated and malignant cell states. A connection between entropy and Ricci curvature led to applications of discrete curvatures to biological networks. However, predicting dynamic biological network rewiring remains an open problem. Here we apply Ricci curvature and Ricci flow to biological network rewiring. By investigating the relationship between network entropy and Forman-Ricci curvature, theoretically and empirically on single-cell RNA-sequencing data, we demonstrate that the two measures do not always positively correlate, as previously suggested, and provide complementary rather than interchangeable information. We next employ Ricci flow to derive network rewiring trajectories from stem cells to differentiated cells, accurately predicting true intermediate time points in gene expression time courses. In summary, we present a differential geometry toolkit for understanding dynamic network rewiring during cellular differentiation and cancer.
Assuntos
Neoplasias , Transdução de Sinais , Humanos , Diferenciação Celular , Neoplasias/genética , Neoplasias/metabolismo , Células-Tronco/metabolismoRESUMO
Protection of telomeres 1a (POT1a) is a telomere binding protein. A decrease of POT1a is related to myeloid-skewed haematopoiesis with ageing, suggesting that protection of telomeres is essential to sustain multi-potency. Since mesenchymal stem cells (MSCs) are a constituent of the hematopoietic niche in bone marrow, their dysfunction is associated with haematopoietic failure. However, the importance of telomere protection in MSCs has yet to be elucidated. Here, we show that genetic deletion of POT1a in MSCs leads to intracellular accumulation of fatty acids and excessive ROS and DNA damage, resulting in impaired osteogenic-differentiation. Furthermore, MSC-specific POT1a deficient mice exhibited skeletal retardation due to reduction of IL-7 producing bone lining osteoblasts. Single-cell gene expression profiling of bone marrow from POT1a deficient mice revealed that B-lymphopoiesis was selectively impaired. These results demonstrate that bone marrow microenvironments composed of POT1a deficient MSCs fail to support B-lymphopoiesis, which may underpin age-related myeloid-bias in haematopoiesis.
Assuntos
Linfopoese , Telômero , Animais , Camundongos , Envelhecimento , Diferenciação Celular , Linfopoese/genética , Telômero/genética , Telômero/metabolismo , Proteínas de Ligação a Telômeros/genética , Proteínas de Ligação a Telômeros/metabolismoRESUMO
BACKGROUND: Single-cell sequencing (sc-Seq) experiments are producing increasingly large data sets. However, large data sets do not necessarily contain large amounts of information. RESULTS: Here, we formally quantify the information obtained from a sc-Seq experiment and show that it corresponds to an intuitive notion of gene expression heterogeneity. We demonstrate a natural relation between our notion of heterogeneity and that of cell type, decomposing heterogeneity into that component attributable to differential expression between cell types (inter-cluster heterogeneity) and that remaining (intra-cluster heterogeneity). We test our definition of heterogeneity as the objective function of a clustering algorithm, and show that it is a useful descriptor for gene expression patterns associated with different cell types. CONCLUSIONS: Thus, our definition of gene heterogeneity leads to a biologically meaningful notion of cell type, as groups of cells that are statistically equivalent with respect to their patterns of gene expression. Our measure of heterogeneity, and its decomposition into inter- and intra-cluster, is non-parametric, intrinsic, unbiased, and requires no additional assumptions about expression patterns. Based on this theory, we develop an efficient method for the automatic unsupervised clustering of cells from sc-Seq data, and provide an R package implementation.
Assuntos
Algoritmos , Perfilação da Expressão Gênica , Perfilação da Expressão Gênica/métodos , Análise de Sequência de RNA/métodos , RNA-Seq/métodos , Análise de Célula Única/métodos , Análise por ConglomeradosRESUMO
There is a wealth of data indicating human bone marrow contains skeletal stem cells (SSC) with the capacity for osteogenic, chondrogenic and adipogenic differentiation. However, current methods to isolate SSCs are restricted by the lack of a defined marker, limiting understanding of SSC fate, immunophenotype, function and clinical application. The current study applied single-cell RNA-sequencing to profile human adult bone marrow populations from 11 donors and identified novel targets for SSC enrichment. Spherical nucleic acids were used to detect these mRNA targets in SSCs. This methodology was able to rapidly isolate potential SSCs found at a frequency of <1 in 1,000,000 in human bone marrow, with the capacity for tri-lineage differentiation in vitro and ectopic bone formation in vivo. The current studies detail the development of a platform to advance SSC enrichment from human bone marrow, offering an invaluable resource for further SSC characterisation, with significant therapeutic impact therein.
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Stem cell biologists are increasingly making use of computational models to decipher their data. However, there is sometimes uncertainty about what makes a "good" model. The purpose of this commentary is to argue for closer integration of experiment and theory in stem cell research and propose guidelines for good theory.
Assuntos
Biologia Computacional , Células-TroncoRESUMO
Human epidermal Langerhans cells (LCs) maintain immune homeostasis in the skin. To examine transcriptional programming of human primary LCs during homeostasis, we performed scRNA-seq analysis of LCs before and after migration from the epidermis, coupled with functional assessment of their regulatory T cell priming capabilities. The analysis revealed that steady-state LCs exist in a continuum of maturation states and upregulate antigen presentation genes along with an immunoregulatory module including the genes IDO1, LGALS1, LAMTOR1, IL4I, upon their migration. The migration-induced transition in genomic state is accompanied by the ability of LCs to more efficiently prime regulatory T cell responses in co-culture assays. Computational analyses of the scRNAseq datasets using SCENIC and Partial Information Decomposition in Context identified a set of migration-induced transcription factors including IRF4, KLF6 and RelB as key nodes within a immunoregulatory gene regulatory network. These findings support a model in which efficient priming of immunoregulatory responses by LCs is dependent on coordinated upregulation of a migration-coupled maturation program with a immunoregulation-promoting genomic module.
Assuntos
Galectina 1 , Células de Langerhans , Movimento Celular/genética , Epiderme , Humanos , PeleRESUMO
Adaptive immune responses depend on interactions between T cell receptors (TCRs) and peptide major histocompatibility complex (pMHC) ligands located on the surface of T cells and antigen presenting cells (APCs), respectively. As TCRs and pMHCs are often only present at low copy numbers their interactions are inherently stochastic, yet the role of stochastic fluctuations on T cell function is unclear. Here, we introduce a minimal stochastic model of T cell activation that accounts for serial TCR-pMHC engagement, reversible TCR conformational change and TCR aggregation. Analysis of this model indicates that it is not the strength of binding between the T cell and the APC cell per se that elicits an immune response, but rather the information imparted to the T cell from the encounter, as assessed by the entropy rate of the TCR-pMHC binding dynamics. This view provides an information-theoretic interpretation of T cell activation that explains a range of experimental observations. Based on this analysis, we propose that effective T cell therapeutics may be enhanced by optimizing the inherent stochasticity of TCR-pMHC binding dynamics.
Assuntos
Ativação Linfocitária , Receptores de Antígenos de Linfócitos T , Complexo Principal de Histocompatibilidade , Peptídeos , Ligação Proteica , Receptores de Antígenos de Linfócitos T/química , Receptores de Antígenos de Linfócitos T/metabolismo , Linfócitos TRESUMO
Waddington's epigenetic landscape is a powerful metaphor for development. Recent work shows how molecular "noise" can shape the architecture of this landscape and how universal properties of cell fate commitment can be distilled from careful consideration of its geometry.
Assuntos
Epigênese Genética , Epigenômica , Diferenciação Celular , Epigênese Genética/genéticaRESUMO
Complex systems of intracellular biochemical reactions have a central role in regulating cell identities and functions. Biochemical reaction systems are typically studied using the language and tools of graph theory. However, graph representations only describe pairwise interactions between molecular species and so are not well suited to modelling complex sets of reactions that may involve numerous reactants and/or products. Here, we make use of a recently developed hypergraph theory of chemical reactions that naturally allows for higher-order interactions to explore the geometry and quantify functional redundancy in biochemical reactions systems. Our results constitute a general theory of automorphisms for oriented hypergraphs and describe the effect of automorphism group structure on hypergraph Laplacian spectra.
Assuntos
AlgoritmosRESUMO
The future of single cell diversity screens involves ever-larger sample sizes, dictating the need for higher throughput methods with low analytical noise to accurately describe the nature of the cellular system. Current approaches are limited by the Poisson statistic, requiring dilute cell suspensions and associated losses in throughput. In this contribution, we apply Dean entrainment to both cell and bead inputs, defining different volume packets to effect efficient co-encapsulation. Volume ratio scaling was explored to identify optimal conditions. This enabled the co-encapsulation of single cells with reporter beads at rates of â¼1 million cells per hour, while increasing assay signal-to-noise with cell multiplet rates of â¼2.5% and capturing â¼70% of cells. The method, called Pirouette coupling, extends our capacity to investigate biological systems.
Assuntos
Bioensaio , Análise de Célula Única , RuídoRESUMO
Background and Purpose: Outcome prediction after aneurysmal subarachnoid hemorrhage (aSAH) is challenging. CRP (C-reactive protein) has been reported to be associated with outcome, but it is unclear if this is independent of other predictors and applies to aSAH of all grades. Therefore, the role of CRP in aSAH outcome prediction models is unknown. The purpose of this study is to assess if CRP is an independent predictor of outcome after aSAH, develop new prognostic models incorporating CRP, and test whether these can be improved by application of machine learning. Methods: This was an individual patient-level analysis of data from patients within 72 hours of aSAH from 2 prior studies. A panel of statistical learning methods including logistic regression, random forest, and support vector machines were used to assess the relationship between CRP and modified Rankin Scale. Models were compared with the full Subarachnoid Hemmorhage International Trialists' (SAHIT) prediction tool of outcome after aSAH and internally validated using cross-validation. Results: One thousand and seventeen patients were included for analysis. CRP on the first day after ictus was an independent predictor of outcome. The full SAHIT model achieved an area under the receiver operator characteristics curve (AUC) of 0.831. Addition of CRP to the predictors of the full SAHIT model improved model performance (AUC, 0.846, P=0.01). This improvement was not enhanced when learning was performed using a random forest (AUC, 0.807), but was with a support vector machine (AUC of 0.960, P <0.001). Conclusions: CRP is an independent predictor of outcome after aSAH. Its inclusion in prognostic models improves performance, although the magnitude of improvement is probably insufficient to be relevant clinically on an individual patient level, and of more relevance in research. Greater improvements in model performance are seen with support vector machines but these models have the highest classification error rate on internal validation and require external validation and calibration.
Assuntos
Proteína C-Reativa/análise , Aprendizado de Máquina , Hemorragia Subaracnóidea/sangue , Hemorragia Subaracnóidea/terapia , Adulto , Idoso , Feminino , Humanos , Modelos Logísticos , Masculino , Pessoa de Meia-Idade , Modelos Estatísticos , Valor Preditivo dos Testes , Prognóstico , Curva ROC , Reprodutibilidade dos Testes , Máquina de Vetores de Suporte , Resultado do Tratamento , Adulto JovemRESUMO
Langerhans cells (LCs) reside in the epidermis as a dense network of immune system sentinels, coordinating both immunogenic and tolerogenic immune responses. To determine molecular switches directing induction of LC immune activation, we performed mathematical modelling of gene regulatory networks identified by single cell RNA sequencing of LCs exposed to TNF-alpha, a key pro-inflammatory signal produced by the skin. Our approach delineated three programmes of LC phenotypic activation (immunogenic, tolerogenic or ambivalent), and confirmed that TNF-alpha enhanced LC immunogenic programming. Through regulon analysis followed by mutual information modelling, we identified IRF1 as the key transcription factor for the regulation of immunogenicity in LCs. Application of a mathematical toggle switch model, coupling IRF1 with tolerance-inducing transcription factors, determined the key set of transcription factors regulating the switch between tolerance and immunogenicity, and correctly predicted LC behaviour in LCs derived from different body sites. Our findings provide a mechanistic explanation of how combinatorial interactions between different transcription factors can coordinate specific transcriptional programmes in human LCs, interpreting the microenvironmental context of the local tissue microenvironments.
Assuntos
Fatores Reguladores de Interferon/metabolismo , Células de Langerhans/imunologia , Células de Langerhans/metabolismo , Fator de Necrose Tumoral alfa/metabolismo , Epiderme/metabolismo , Regulação da Expressão Gênica , Redes Reguladoras de Genes , Humanos , Fatores Reguladores de Interferon/genética , Transdução de Sinais , Transcrição Gênica , Fator de Necrose Tumoral alfa/genéticaRESUMO
Adult tissues in multicellular organisms typically contain a variety of stem, progenitor and differentiated cell types arranged in a lineage hierarchy that regulates healthy tissue turnover. Lineage hierarchies in disparate tissues often exhibit common features, yet the general principles regulating their architecture are not known. Here, we provide a formal framework for understanding the relationship between cell molecular 'states' and cell 'types', based on the topology of admissible cell state trajectories. We show that a self-renewing cell type - if defined as suggested by this framework - must reside at the top of any homeostatic renewing lineage hierarchy, and only there. This architecture arises as a natural consequence of homeostasis, and indeed is the only possible way that lineage architectures can be constructed to support homeostasis in renewing tissues. Furthermore, under suitable feedback regulation, for example from the stem cell niche, we show that the property of 'stemness' is entirely determined by the cell environment, in accordance with the notion that stem cell identities are contextual and not determined by hard-wired, cell-intrinsic characteristics. This article has an associated 'The people behind the papers' interview.
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Linhagem da Célula/fisiologia , Autorrenovação Celular/fisiologia , Células-Tronco/fisiologia , Animais , Diferenciação Celular , Homeostase , Humanos , Modelos Biológicos , Nicho de Células-TroncoRESUMO
Cell fate decisions during development are governed by multi-factorial regulatory mechanisms including chromatin remodeling, DNA methylation, binding of transcription factors to specific loci, RNA transcription and protein synthesis. However, the mechanisms by which such regulatory "dimensions" coordinate cell fate decisions are currently poorly understood. Here we quantified the multi-dimensional molecular changes that occur in mouse embryonic stem cells (mESCs) upon depletion of Estrogen related receptor beta (Esrrb), a key pluripotency regulator. Comparative analyses of expression changes subsequent to depletion of Esrrb or Nanog, indicated that a system of interlocked feed-forward loops involving both factors, plays a central part in regulating the timing of mESC fate decisions. Taken together, our meta-analyses support a hierarchical model in which pluripotency is maintained by an Oct4-Sox2 regulatory module, while the timing of differentiation is regulated by a Nanog-Esrrb module.
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Epigenetic memories play an important part in regulating stem cell identities. Tools from the theory of non-Markov processes may help us understand these memories better and develop a more integrated view of stem cell fate and function.
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Epigênese Genética , Células-Tronco , Diferenciação CelularRESUMO
Despite the considerable progress that has been made in identifying cellular factors and pathways that contribute to establishment and maintenance of the latent HIV reservoir, it remains the major obstacle to eradicating this virus. Most recently, noncoding genes have been implicated in regulation of HIV expression. In this study, small RNA sequencing was used to profile expression of microRNAs (miRNAs) in a primary CD4+ T cell in vitro model of HIV latency. Previously, we have shown that protein-coding genes dysregulated in this model were enriched for the p53 signaling pathway, which was confirmed experimentally. We further found a link between p53 signaling and dysregulated long noncoding RNAs. In this study, we hypothesized that miRNAs may provide an additional level of regulation of the p53 signaling pathway during HIV latency. Twenty-six miRNAs were identified to be dysregulated in our latency model. A subset of these miRNAs was validated by real-time quantitative polymerase chain reaction. Predicted messenger RNA (mRNA) targets and cellular pathways enriched for mRNA targets were identified using several analytical methods. Our analyses showed that many protein-coding genes and pathways targeted by dysregulated miRNAs have relevance to regulation of HIV expression or establishment of HIV latency. The p53 signaling pathway was found among pathways that were targeted by dysregulated miRNAs at a greater level than expected by chance. This study provides a mechanistic insight into regulation of the p53 pathway through miRNAs that may contribute to the establishment of latency.
Assuntos
Infecções por HIV , HIV-1 , MicroRNAs , RNA Longo não Codificante , Perfilação da Expressão Gênica , HIV-1/genética , Humanos , MicroRNAs/genética , Latência ViralRESUMO
Changes in stem cell activity may underpin aging. However, these changes are not completely understood. Here, we combined single-cell profiling with machine learning and in vivo functional studies to explore how hematopoietic stem cell (HSC) divisions patterns evolve with age. We first trained an artificial neural network (ANN) to accurately identify cell types in the hematopoietic hierarchy and predict their age from single-cell gene-expression patterns. We then used this ANN to compare identities of daughter cells immediately after HSC divisions and found that the self-renewal ability of individual HSCs declines with age. Furthermore, while HSC cell divisions are deterministic and intrinsically regulated in young and old age, they are variable and niche sensitive in mid-life. These results indicate that the balance between intrinsic and extrinsic regulation of stem cell activity alters substantially with age and help explain why stem cell numbers increase through life, yet regenerative potency declines.