Single-cell transcriptome data provide unprecedented resolution to study heterogeneity in cell populations and present a challenge for unsupervised classification. Popular methods, like principal ...component analysis (PCA), often suffer from the high level of noise in the data.
Here we adapt Nonnegative Matrix Factorization (NMF) to study the problem of identifying subpopulations in single-cell transcriptome data. In contrast to the conventional gene-centered view of NMF, identifying metagenes, we used NMF in a cell-centered direction, identifying cell subtypes ('metacells'). Using three different datasets (based on RT-qPCR and single cell RNA-seq data, respectively), we show that NMF outperforms PCA in identifying subpopulations in an accurate and robust way, without the need for prior feature selection; moreover, NMF successfully recovered the broad classes on a large dataset (thousands of single-cell transcriptomes), as identified by a computationally sophisticated method. NMF allows to identify feature genes in a direct, unbiased manner. We propose novel approaches for determining a biologically meaningful number of subpopulations based on minimizing the ambiguity of classification. In conclusion, our study shows that NMF is a robust, informative and simple method for the unsupervised learning of cell subtypes from single-cell gene expression data.
https://github.com/ccshao/nimfa CONTACTS: c.shao@Dkfz-Heidelberg.de or t.hoefer@Dkfz-Heidelberg.deSupplementary information: Supplementary data are available at Bioinformatics online.
Multisite phosphorylation is an important mechanism for fine-tuned regulation of protein function. Mathematical models developed over recent years have contributed to elucidation of the functional ...consequences of a variety of molecular mechanisms involved in processing of the phosphorylation sites. Here we review the results of such models, together with salient experimental findings on multisite protein phosphorylation. We discuss how molecular mechanisms that can be distinguished with respect to the order and processivity of phosphorylation, as well as other factors, regulate changes in the sensitivity and kinetics of the response, the synchronization of molecular events, signalling specificity, and other functional implications.
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, SIK, UILJ, UKNU, UL, UM, UPUK
Advances in genetic labeling and barcoding of hematopoietic stem cells (HSCs) in situ now allow direct measurements of physiological HSC output, both quantitatively and qualitatively. Turning on a ...heritable label in HSCs and measuring the kinetics of label emergence in downstream compartments reveal rates of differentiation and self-renewal of HSCs and progenitor cells, whereas endogenous HSC barcoding probes physiological precursor-product relationships. Labels have been inserted at different stages of the hematopoietic differentiation hierarchy. Recent genetic and functional evidence suggests a phenotype (Tie2+) for tip HSCs. Fate mapping shows that many tip HSCs regularly feed into downstream stages, with individual cells contributing infrequently. Stem and progenitor cells downstream of tip HSCs serve as a major, nearly self-renewing source of day-to-day hematopoiesis, rendering the blood and immune system HSC-independent for extended periods of time. HSCs realize multilineage output, yet, fates restricted to several lineages or even a single lineage have also been observed. Single HSCs within a clone in the bone marrow that develop from a fetal HSC precursor have been observed to express clone-specific fates. Thus, the new tools probing HSC differentiation in situ are progressing beyond assays for HSC activity based on proliferation measurements and fates of transplanted stem cells, and the data challenge lineage interpretations of single-cell gene expression snapshots. Linking in vivo fate analyses to gene expression and other molecular determinants of cell fate will aid in unraveling the mechanisms of lineage commitment and the architecture of physiological hematopoiesis.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
During differentiation of embryonic stem cells, chromatin reorganizes to establish cell type-specific expression programs. Here, we have dissected the linkages between DNA methylation (5mC), ...hydroxymethylation (5hmC), nucleosome repositioning, and binding of the transcription factor CTCF during this process. By integrating MNase-seq and ChIP-seq experiments in mouse embryonic stem cells (ESC) and their differentiated counterparts with biophysical modeling, we found that the interplay between these factors depends on their genomic context. The mostly unmethylated CpG islands have reduced nucleosome occupancy and are enriched in cell type-independent binding sites for CTCF. The few remaining methylated CpG dinucleotides are preferentially associated with nucleosomes. In contrast, outside of CpG islands most CpGs are methylated, and the average methylation density oscillates so that it is highest in the linker region between nucleosomes. Outside CpG islands, binding of TET1, an enzyme that converts 5mC to 5hmC, is associated with labile, MNase-sensitive nucleosomes. Such nucleosomes are poised for eviction in ESCs and become stably bound in differentiated cells where the TET1 and 5hmC levels go down. This process regulates a class of CTCF binding sites outside CpG islands that are occupied by CTCF in ESCs but lose the protein during differentiation. We rationalize this cell type-dependent targeting of CTCF with a quantitative biophysical model of competitive binding with the histone octamer, depending on the TET1, 5hmC, and 5mC state.
Summary
Experimental studies of the innate immune response of mammalian cells to viruses reveal pervasive heterogeneity at the level of single cells. Interferons are induced only in a fraction of ...virus‐infected cells; subsequently a fraction of cells exposed to interferons upregulate interferon‐stimulated genes. Nevertheless, quantitative experiments and linked mathematical models show that the interferon response can be effective in curbing viral spread through two distinct mechanisms. First, paracrine interferon signals from scattered source cells can protect many uninfected cells, and the self‐amplification of interferon production might serve to calibrate response amplitude to strength of viral infection. Second, models of the tug‐of‐war between viral replication and the innate interferon response imply a pivotal role of interferon action on already infected cells in curbing viral spread, through effectively lowering virus replication rate. This finding is in line with the observation that several pathogenic viruses selectively abrogate interferon action on infected cells. Thus, interferons may delay viral spread in acute infections by acting as sentinels, warning uninfected cells of imminent danger, or as negative feedback regulators of virus replication in infected cells. The timing of the interferon response relative to the onset of viral replication is critical for its effectiveness in curbing viral spread.
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, SIK, UILJ, UKNU, UL, UM, UPUK
Peracetic acid (PAA) is a disinfectant considered for use in ballast water treatment, but its chemical behavior in such systems (i.e., saline waters) is largely unknown. In this study, the reactivity ...of PAA with halide ions (chloride and bromide) to form secondary oxidants (HOCl, HOBr) was investigated. For the PAA–chloride and PAA–bromide reactions, second-order rate constants of (1.47 ± 0.58) × 10–5 and 0.24 ± 0.02 M–1 s–1 were determined for the formation of HOCl or HOBr, respectively. Hydrogen peroxide (H2O2), which is always present in PAA solutions, reduced HOCl or HOBr to chloride or bromide, respectively. As a consequence, in PAA-treated solutions with H2O2 > PAA, the HOBr (HOCl) steady-state concentrations were low with a limited formation of brominated (chlorinated) disinfection byproducts (DBPs). HOI (formed from the PAA–iodide reaction) affected this process because it can react with H2O2 back to iodide. H2O2 is thus consumed in a catalytic cycle and leads to less efficient HOBr scavenging at even low iodide concentrations (<1 μM). In PAA-treated solutions with H2O2 < PAA and high bromide levels, mostly brominated DBPs are formed. In synthetic water, bromate was formed from the oxidation of bromide. In natural brackish waters, bromoform (CHBr3), bromoacetic acid (MBAA), dibromoacetic acid (DBAA), and tribromoacetic acid (TBAA) formed at up to 260, 106, 230, and 89 μg/L, respectively for doses of 2 mM (ca. 150 mg/L) PAA and H2O2 < PAA. The same brackish waters, treated with PAA with H2O2 ≫ PAA, similar to conditions found in commercial PAA solutions, resulted in no trihalomethanes and only low haloacetic acid concentrations.
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IJS, KILJ, NUK, PNG, UL, UM
Lineage tracing reveals hematopoietic stem cell (HSC) fates, while single-cell RNA sequencing identifies snapshots of HSC transcriptomes. To obtain information on fate plus transcriptome in the same ...cell, we developed the PolyloxExpress allele, enabling Cre-recombinase-dependent RNA barcoding in situ. Linking fates to single HSC transcriptomes provided the information required to identify transcriptional signatures of HSC fates, which were not apparent in single-HSC transcriptomes alone. We find that differentiation-inactive, multilineage, and lineage-restricted HSC clones reside in distinct regions of the transcriptional landscape of hematopoiesis. Differentiation-inactive HSC clones are closer to the origin of the transcriptional trajectory, yet they are not characterized by a quiescent gene signature. Fate-specific gene signatures imply coherence of clonal HSC fates, and HSC output toward short-lived lineage progenitors indicates stability of HSC fates over time. These combined analyses of fate and transcriptome under physiological conditions may pave the way toward identifying molecular determinants of HSC fates.
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•PolyloxExpress barcoding jointly uncovers stem cell fate and single-cell transcriptome•Multilineage and myelo-erythroid-restricted HSC clones dominate•A subset of HSCs does not differentiate; differentiation-inactive HSCs are not quiescent•PolyloxExpress reveals transcriptome signatures associated with distinct HSC fates
Snapshot transcriptome data lack precursor-product (fate) information, while lineage tracing reveals stem cell fate but lacks transcriptome information. Pei and colleagues developed a mouse RNA barcoding system (PolyloxExpress) that reports fate and transcriptome in single cells, providing transcriptional signatures associated with distinct hematopoietic stem cell fates and output.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
We studied how intratumoral genetic heterogeneity shapes tumor growth and therapy response for isocitrate dehydrogenase (IDH)-wild-type glioblastoma, a rapidly regrowing tumor. We inferred the ...evolutionary trajectories of matched pairs of primary and relapsed tumors based on deep whole-genome-sequencing data. This analysis suggests both a distant origin of de novo glioblastoma, up to 7 years before diagnosis, and a common path of early tumorigenesis, with one or more of chromosome 7 gain, 9p loss, or 10 loss, at tumor initiation. TERT promoter mutations often occurred later as a prerequisite for rapid growth. In contrast to this common early path, relapsed tumors acquired no stereotypical pattern of mutations and typically regrew from oligoclonal origins, suggesting sparse selective pressure by therapeutic measures.
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•We inferred evolutionary trajectories of pairs of primary/relapsed glioblastomas•Chromosome 7 gain, 9p loss, or 10 loss commonly occurred at tumor initiation•TERT promoter mutations often occurred later as a prerequisite for rapid growth•Relapsed tumors typically regrew from oligoclonal origins
By analyzing 21 paired primary and locally relapsed IDH-wild-type glioblastomas (GBM), Körber et al. show that most GBM initiate by gains and losses of specific chromosomes; TERT promoter mutations often occur later as a prerequisite for rapid growth, and relapsed GBM acquire few stereotypical mutations.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
It is currently believed that type I and III interferons (IFNs) have redundant functions. However, the preferential distribution of type III IFN receptor on epithelial cells suggests functional ...differences at epithelial surfaces. Here, using human intestinal epithelial cells we could show that although both type I and type III IFNs confer an antiviral state to the cells, they do so with distinct kinetics. Type I IFN signaling is characterized by an acute strong induction of interferon stimulated genes (ISGs) and confers fast antiviral protection. On the contrary, the slow acting type III IFN mediated antiviral protection is characterized by a weaker induction of ISGs in a delayed manner compared to type I IFN. Moreover, while transcript profiling revealed that both IFNs induced a similar set of ISGs, their temporal expression strictly depended on the IFNs, thereby leading to unique antiviral environments. Using a combination of data-driven mathematical modeling and experimental validation, we addressed the molecular reason for this differential kinetic of ISG expression. We could demonstrate that these kinetic differences are intrinsic to each signaling pathway and not due to different expression levels of the corresponding IFN receptors. We report that type III IFN is specifically tailored to act in specific cell types not only due to the restriction of its receptor but also by providing target cells with a distinct antiviral environment compared to type I IFN. We propose that this specific environment is key at surfaces that are often challenged with the extracellular environment.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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