Concentration for One and Two Species One-Dimensional Reaction-Diffusion Systems

We look for similarity transformations which yield mappings between different one-dimensional reaction-diffusion processes. In this way results obtained for special systems can be generalized to equivalent reaction-diffusion models. The coagulation (A + A -> A) or the annihilation (A + A -> 0) models can be mapped onto systems in which both processes are allowed. With the help of the coagulation-decoagulation model results for some death-decoagulation and annihilation-creation systems are given. We also find a reaction-diffusion system which is equivalent to the two species annihilation model (A + B ->0). Besides we present numerical results of Monte Carlo simulations. An accurate description of the effects of the reaction rates on the concentration in one-species diffusion-annihilation model is made. The asymptotic behavior of the concentration in the two species annihilation system (A + B -> 0) with symmetric initial conditions is studied.Comment: 20 pages latex, uuencoded figures at the en

Prediction of Metabolic Profiles from Transcriptomics Data in Human Cancer Cell Lines

The Metabolome and Transcriptome are mutually communicating within cancer cells, and this interplay is translated into the existence of quantifiable correlation structures between gene expression and metabolite abundance levels. Studying these correlations could provide a novel venue of understanding cancer and the discovery of novel biomarkers and pharmacological strategies, as well as laying the foundation for the prediction of metabolite quantities by leveraging information from the more widespread transcriptomics data. In the current paper, we investigate the correlation between gene expression and metabolite levels in the Cancer Cell Line Encyclopedia dataset, building a direct correlation network between the two molecular ensembles. We show that a metabolite/transcript correlation network can be used to predict metabolite levels in different samples and datasets, such as the NCI-60 cancer cell line dataset, both on a sample-by-sample basis and in differential contrasts. We also show that metabolite levels can be predicted in principle on any sample and dataset for which transcriptomics data are available, such as the Cancer Genome Atlas (TCGA)

The Transcriptome of SH-SY5Y at Single-Cell Resolution: A CITE-Seq Data Analysis Workflow

Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) is a recently established multimodal single cell analysis technique combining the immunophenotyping capabilities of antibody labeling and cell sorting with the resolution of single-cell RNA sequencing (scRNA-seq). By simply adding a 12-bp nucleotide barcode to antibodies (cell hashing), CITE-seq can be used to sequence antibody-bound tags alongside the cellular mRNA, thus reducing costs of scRNA-seq by performing it at the same time on multiple barcoded samples in a single run. Here, we illustrate an ideal CITE-seq data analysis workflow by characterizing the transcriptome of SH-SY5Y neuroblastoma cell line, a widely used model to study neuronal function and differentiation. We obtained transcriptomes from a total of 2879 single cells, measuring an average of 1600 genes/cell. Along with standard scRNA-seq data handling procedures, such as quality checks and cell filtering procedures, we performed exploratory analyses to identify most stable genes to be possibly used as reference housekeeping genes in qPCR experiments. We also illustrate how to use some popular R packages to investigate cell heterogeneity in scRNA-seq data, namely Seurat, Monocle, and slalom. Both the CITE-seq dataset and the code used to analyze it are freely shared and fully reusable for future research

Multiplex giant magnetoresistive biosensor microarrays identify interferon-associated autoantibodies in systemic lupus erythematosus.

High titer, class-switched autoantibodies are a hallmark of systemic lupus erythematosus (SLE). Dysregulation of the interferon (IFN) pathway is observed in individuals with active SLE, although the association of specific autoantibodies with chemokine score, a combined measurement of three IFN-regulated chemokines, is not known. To identify autoantibodies associated with chemokine score, we developed giant magnetoresistive (GMR) biosensor microarrays, which allow the parallel measurement of multiple serum antibodies to autoantigens and peptides. We used the microarrays to analyze serum samples from SLE patients and found individuals with high chemokine scores had significantly greater reactivity to 13 autoantigens than individuals with low chemokine scores. Our findings demonstrate that multiple autoantibodies, including antibodies to U1-70K and modified histone H2B tails, are associated with IFN dysregulation in SLE. Further, they show the microarrays are capable of identifying autoantibodies associated with relevant clinical manifestations of SLE, with potential for use as biomarkers in clinical practice

Coarsening dynamics of adsorption processes with diffusional relaxation

We investigate the late coarsening stages of one dimensional adsorption processes with diffusional relaxation. The nonequilibrium domain size distribution is studied by means of the field theory associated to the stochastic evolution. An exact asymptotic solution satisfying dynamical scaling is given for cluster sizes smaller than the average domain length. Our results are supported and compared with Monte Carlo simulations.Comment: 5 pages, 1 Postscript figur

Single-cell gene network analysis and transcriptional landscape of MYCN-amplified neuroblastoma cell lines

Neuroblastoma (NBL) is a pediatric cancer responsible for more than 15% of cancer deaths in children, with 800 new cases each year in the United States alone. Genomic amplification of the MYC oncogene family member MYCN characterizes a subset of high-risk pediatric neuroblastomas. Several cellular models have been implemented to study this disease over the years. Two of these, SK-N-BE-2-C (BE2C) and Kelly, are amongst the most used worldwide as models of MYCN-Amplified human NBL. Here, we provide a transcriptome-wide quantitative measurement of gene expression and transcriptional network activity in BE2C and Kelly cell lines at an unprecedented single-cell resolution. We obtained 1105 Kelly and 962 BE2C unsynchronized cells, with an average number of mapped reads/cell of roughly 38,000. The single-cell data recapitulate gene expression signatures previously generated from bulk RNA-Seq. We highlight low variance for commonly used housekeeping genes between different cells (ACTB, B2M and GAPDH), while showing higher than expected variance for metallothionein transcripts in Kelly cells. The high number of samples, despite the relatively low read coverage of single cells, allowed for robust pathway enrichment analysis and master regulator analysis (MRA), both of which highlight the more mesenchymal nature of BE2C cells as compared to Kelly cells, and the upregulation of TWIST1 and DNAJC1 transcriptional networks. We further defined master regulators at the single cell level and showed that MYCN is not constantly active or expressed within Kelly and BE2C cells, independently of cell cycle phase. The dataset, alongside a detailed and commented programming protocol to analyze it, is fully shared and reusable

Complete Exact Solution of Diffusion-Limited Coalescence, A + A -> A

Some models of diffusion-limited reaction processes in one dimension lend themselves to exact analysis. The known approaches yield exact expressions for a limited number of quantities of interest, such as the particle concentration, or the distribution of distances between nearest particles. However, a full characterization of a particle system is only provided by the infinite hierarchy of multiple-point density correlation functions. We derive an exact description of the full hierarchy of correlation functions for the diffusion-limited irreversible coalescence process A + A -> A.Comment: 4 pages, 2 figures (postscript). Typeset with Revte

Novel Phospholipid-Protein Conjugates Allow Improved Detection of Antibodies in Patients with Autoimmune Diseases

Reliable measurement of clinically relevant autoimmune antibodies toward phospholipid-protein conjugates is highly desirable in research and clinical assays. To date, the development in this field has been limited to the use of natural heterogeneous antigens. However, this approach does not take structural features of biologically active antigens into account and leads to low reliability and poor scientific test value. Here we describe novel phospholipid-protein conjugates for specific detection of human autoimmune antibodies. Our synthetic approach includes mild oxidation of synthetic phospholipid cardiolipin, and as the last step, coupling of the product with azide-containing linker and copper-catalyzed click chemistry with β2-glycoprotein I and prothrombin. To prove utility of the product antigens, we used enzyme-linked immunosorbent assay and three cohorts of samples obtained from patients in Denmark (n = 34) and the USA (n = 27 and n = 14). Afterwards we analyzed correlation of the obtained autoantibody titers with clinical parameters for each patient. Our results prove that using novel antigens clinically relevant autoantibodies can be detected with high repeatability, sensitivity and specificity. Unlike previously used antigens the obtained autoantibody titers strongly correlate with high disease activity and in particular, with arthritis, renal involvement, anti-Smith antibodies and high lymphocyte count. Importantly, chemical composition of antigens has a strong influence on the correlation of detected autoantibodies with disease activity and manifestations. This confirms the crucial importance of antigens' composition on research and diagnostic assays, and opens up exciting perspectives for synthetic antigens in future studies of autoimmunity

MiR203 Mediates Subversion of Stem Cell Properties During Mammary Epithelial Differentiation via Repression of ΔNP63α and Promotes Mesenchymal-to-Epithelial Transition

During reproductive life, the mammary epithelium undergoes consecutive cycles of proliferation, differentiation and apoptosis. Doing so relies on the retained proliferative capacity, prolonged lifespan and developmental potency of mammary stem cells (MaSCs). ΔNp63α, the predominant TP63 isoform in mammary epithelia, is robustly expressed in MaSCs and is required for preservation of self-renewing capacity in diverse epithelial structures. However, the mechanism(s) underlying subversion of this activity during forfeiture of self-renewing capacity are poorly understood. MicroRNAs (miRNAs) govern critical cellular functions including stem cell maintenance, development, cell cycle regulation and differentiation by disrupting translation of target mRNAs. Data presented here indicate that expression of miR203, a miRNA that targets ΔNp63α and ΔNp63β is activated during luminal epithelial differentiation and that this pattern is observed in the murine mammary hierarchy. In addition, we present evidence that the transcription factor Zeb1 represses miR203 expression, thus enhancing ΔNp63α protein levels. Furthermore, ectopic miR203 suppresses ΔNp63α expression, proliferation and colony formation. The anti-clonogenic effects mediated by miR203 require suppression of ΔNp63α. In addition, ectopic miR203 promotes mesenchymal-to-epithelial transition and disrupts activities associated with epithelial stem cells. These studies support a model in which induction of miR203 mediates forfeiture of self-renewing capacity via suppression of ΔNp63α and may also have anti-tumorigenic activity through its reduction of EMT and cancer stem cell populations

On the universality of a class of annihilation-coagulation models

A class of $d$-dimensional reaction-diffusion models interpolating continuously between the diffusion-coagulation and the diffusion-annihilation models is introduced. Exact relations among the observables of different models are established. For the one-dimensional case, it is shown how correlations in the initial state can lead to non-universal amplitudes for time-dependent particles density.Comment: 18 pages with no figures. Latex file using REVTE