Transcriptional and epigenetic regulation of differentially activated macrophages

Macrophages are an indispensable part of the innate immune system which mediate various functions including host defense against pathogens, metabolism, tissue homeostasis and even developmental processes. These extremely heterogeneous cells can adapt their transcriptional program upon a plethora of stimulatory cues and thus exist in different activation states to facilitate their diverse roles in the body. Corresponding transcriptional changes are established amongst others by transcriptional regulators (TRs) with diverse functions or by complex epigenetic alterations. Next generation sequencing technologies provide excellent experimental methods like ChIP- or RNA-sequencing, with which one can analyze genome wide enrichment properties of DNA binding proteins or the transcriptional activity of genes to elucidate in detail the activation of macrophages on the transcriptional level. Integrating the KO implemented normalization method (KOIN) into the standard peak calling procedure revealed multiple enhancements for ChIP-seq data analysis. False-positive signals can be eliminated in a tremendous amount, while signal-to-noise ratios are increased in low and even high quality ChIP-seq data sets. Besides the identification and removal of a recently identified special type of false-positive signal called “hyper-ChIPable regions”, the biological interpretation can profoundly benefit from KOIN. Overall, the KOIN method demonstrated its value as new possible gold standard control with various advantages compared to the currently established Input chromatin and IgG ChIP-seq controls. Furthermore, the ChIP-seq technology allows the definition of 1) different activity states for promoters or cis-regulatory regions and 2) important regulators in the establishment and maintenance of the transcriptional landscape by the detection of different covalent posttranslational histone modifications (HM), like acetylation or methylation. Four differentially activated primary human macrophages demonstrated a common epigenetic core program, maintained by various promoter sites. Simultaneously, activation state specific epigenetic differences at promoters, super-enhancer regions and especially at enhancer sites could mediate their specialization upon employed stimulatory signals. Finally, despite the detected epigenetic differences an astonishing fraction of genomic loci was defined by accessible promoter and enhancer markings in macrophage activation states. This was especially demonstrated in co-regulation networks for TRs and revealed an uncoupling of epigenetic and transcriptional control in monocyte-derived activated macrophages associated with cellular plasticity in response to microenvironmental signals. Other additional levels of transcriptional fine-tuning like enhancer RNAs, repressor proteins or the cross-talk between HMs could play an important role in fine-tuning macrophage transcription. Especially, the cooperative binding of pioneer transcription factors (TF) like PU.1 with other secondary TFs like STAT proteins to these open genomic macrophage loci could represent an additional important switch in macrophage transcription in concert with HMs

On the asymptotic normality of persistent Betti numbers

Persistent Betti numbers are a major tool in persistent homology, a subfield of topological data analysis. Many tools in persistent homology rely on the properties of persistent Betti numbers considered as a two-dimensional stochastic process $(r,s) \mapsto n^{-1/2} (\beta^{r,s}_q ( \mathcal{K}(n^{1/d} S_n))-\mathbb{E}[\beta^{r,s}_q ( \mathcal{K}( n^{1/d} S_n))])$. So far, pointwise limit theorems have been established in different set-ups. In particular, the pointwise asymptotic normality of (persistent) Betti numbers has been established for stationary Poisson processes and binomial processes with constant intensity function in the so-called critical (or thermodynamic) regime, see Yogeshwaran et al. [2017] and Hiraoka et al. [2018]. In this contribution, we derive a strong stabilizing property (in the spirit of Penrose and Yukich [2001] of persistent Betti numbers and generalize the existing results on the asymptotic normality to the multivariate case and to a broader class of underlying Poisson and binomial processes. Most importantly, we show that the multivariate asymptotic normality holds for all pairs $(r,s)$, $0\le r\le s<\infty$, and that it is not affected by percolation effects in the underlying random geometric graph

Bootstrapping Persistent Betti Numbers and Other Stabilizing Statistics

The present contribution investigates multivariate bootstrap procedures for general stabilizing statistics, with specific application to topological data analysis. Existing limit theorems for topological statistics prove difficult to use in practice for the construction of confidence intervals, motivating the use of the bootstrap in this capacity. However, the standard nonparametric bootstrap does not directly provide for asymptotically valid confidence intervals in some situations. A smoothed bootstrap procedure, instead, is shown to give consistent estimation in these settings. The present work relates to other general results in the area of stabilizing statistics, including central limit theorems for functionals of Poisson and Binomial processes in the critical regime. Specific statistics considered include the persistent Betti numbers of \v{C}ech and Vietoris-Rips complexes over point sets in $\mathbb R^d$, along with Euler characteristics, and the total edge length of the $k$-nearest neighbor graph. Special emphasis is made throughout to weakening the necessary conditions needed to establish bootstrap consistency. In particular, the assumption of a continuous underlying density is not required. A simulation study is provided to assess the performance of the smoothed bootstrap for finite sample sizes, and the method is further applied to the cosmic web dataset from the Sloan Digital Sky Survey (SDSS). Source code is available at github.com/btroycraft/stabilizing_statistics_bootstrap.Comment: 59 pages, 3 figures. Restructured paper with alternate problem settings moved to appendix. Rewrote data analysis and simulations study sections to be more comprehensive, moved each to the end of the pape

Incommensurate Phase in Λ-cobalt (III) Sepulchrate Trinitrate Governed by Highly Competitive N−H⋅⋅⋅O and C−H⋅⋅⋅O Hydrogen Bond Networks

The intermediate incommensurate modulated structure of Λ-cobalt (III) sepulchrate trinitrate is ordered yet retains amplitude of molecular rotations common to high temperature disordered as well as low temperature high Z′ structure. Contributions from bifurcated N−H⋅⋅⋅O bonds as well as very short H⋅⋅⋅H contacts in addition to C−H⋅⋅⋅O bonds leads to severe frustrations in crystal packing than that in the lock-in phase

OneStop:JWS Online&#x27;s access point to SBML,SBGN and MIRIAM compliant annotation

We have developed an online model constructor and validator called OneStop, which is compliant with SBGN, SBML and MIRIAM standards. Key features of OneStop are: 1) a human readable input form (in addition to SBML upload and saving); 2) live visualization (SBGN graphics) of the reaction network during the construction phase; and 3) online access from any machine with a compatible browser. Sophisticated error feedback simplifies the debugging process during model construction significantly and guides the efforts of new users in a step by step fashion. OneStop is seamlessly integrated with the JWS Online model repository and simulator and also facilitates the importation of models from the BioModels database. In addition, OneStop is part of the SysMO-SEEK platform, which is used for data and model management in the Pan-European SysMO consortium

ZBTB7A prevents RUNX1-RUNX1T1-dependent clonal expansion of human hematopoietic stem and progenitor cells

ZBTB7A is frequently mutated in acute myeloid leukemia (AML) with t(8;21) translocation. However, the oncogenic collaboration between mutated ZBTB7A and the RUNX1–RUNX1T1 fusion gene in AML t(8;21) remains unclear. Here, we investigate the role of ZBTB7A and its mutations in the context of normal and malignant hematopoiesis. We demonstrate that clinically relevant ZBTB7A mutations in AML t(8;21) lead to loss of function and result in perturbed myeloid differentiation with block of the granulocytic lineage in favor of monocytic commitment. In addition, loss of ZBTB7A increases glycolysis and hence sensitizes leukemic blasts to metabolic inhibition with 2-deoxy-d-glucose. We observed that ectopic expression of wild-type ZBTB7A prevents RUNX1-RUNX1T1-mediated clonal expansion of human CD34+ cells, whereas the outgrowth of progenitors is enabled by ZBTB7A mutation. Finally, ZBTB7A expression in t(8;21) cells lead to a cell cycle arrest that could be mimicked by inhibition of glycolysis. Our findings suggest that loss of ZBTB7A may facilitate the onset of AML t(8;21), and that RUNX1-RUNX1T1-rearranged leukemia might be treated with glycolytic inhibitors