FADD and Caspase-8 Regulate Gut Homeostasis and Inflammation by Controlling MLKL- and GSDMD-Mediated Death of Intestinal Epithelial Cells.

Pathways controlling intestinal epithelial cell (IEC) death regulate gut immune homeostasis and contribute to the pathogenesis of inflammatory bowel diseases. Here, we show that caspase-8 and its adapter FADD act in IECs to regulate intestinal inflammation downstream of Z-DNA binding protein 1 (ZBP1)- and tumor necrosis factor receptor-1 (TNFR1)-mediated receptor interacting protein kinase 1 (RIPK1) and RIPK3 signaling. Mice with IEC-specific FADD or caspase-8 deficiency developed colitis dependent on mixed lineage kinase-like (MLKL)-mediated epithelial cell necroptosis. However, MLKL deficiency fully prevented ileitis caused by epithelial caspase-8 ablation, but only partially ameliorated ileitis in mice lacking FADD in IECs. Our genetic studies revealed that caspase-8 and gasdermin-D (GSDMD) were both required for the development of MLKL-independent ileitis in mice with epithelial FADD deficiency. Therefore, FADD prevents intestinal inflammation downstream of ZBP1 and TNFR1 by inhibiting both MLKL-induced necroptosis and caspase-8-GSDMD-dependent pyroptosis-like death of epithelial cells.

Nuclear export is a limiting factor in eukaryotic mRNA metabolism.

The eukaryotic mRNA life cycle includes transcription, nuclear mRNA export and degradation. To quantify all these processes simultaneously, we perform thiol-linked alkylation after metabolic labeling of RNA with 4-thiouridine (4sU), followed by sequencing of RNA (SLAM-seq) in the nuclear and cytosolic compartments of human cancer cells. We develop a model that reliably quantifies mRNA-specific synthesis, nuclear export, and nuclear and cytosolic degradation rates on a genome-wide scale. We find that nuclear degradation of polyadenylated mRNA is negligible and nuclear mRNA export is slow, while cytosolic mRNA degradation is comparatively fast. Consequently, an mRNA molecule generally spends most of its life in the nucleus. We also observe large differences in the nuclear export rates of different 3'UTR transcript isoforms. Furthermore, we identify genes whose expression is abruptly induced upon metabolic labeling. These transcripts are exported substantially faster than average mRNAs, suggesting the existence of alternative export pathways. Our results highlight nuclear mRNA export as a limiting factor in mRNA metabolism and gene regulation.

Reliable genotyping of recombinant genomes using a robust hidden Markov model.

Meiotic recombination is an essential mechanism during sexual reproduction and includes the exchange of chromosome segments between homologous chromosomes. New allelic combinations are transmitted to the new generation, introducing novel genetic variation in the offspring genomes. With the improvement of high-throughput whole-genome sequencing technologies, large numbers of recombinant individuals can now be sequenced with low sequencing depth at low costs, necessitating computational methods for reconstructing their haplotypes. The main challenge is the uncertainty in haplotype calling that arises from the low information content of a single genomic position. Straightforward sliding window-based approaches are difficult to tune and fail to place recombination breakpoints precisely. Hidden Markov model (HMM)-based approaches, on the other hand, tend to over-segment the genome. Here, we present RTIGER, an HMM-based model that exploits in a mathematically precise way the fact that true chromosome segments typically have a certain minimum length. We further separate the task of identifying the correct haplotype sequence from the accurate placement of haplotype borders, thereby maximizing the accuracy of border positions. By comparing segmentations based on simulated data with known underlying haplotypes, we highlight the reasons for RTIGER outperforming traditional segmentation approaches. We then analyze the meiotic recombination pattern of segregants of 2 Arabidopsis (Arabidopsis thaliana) accessions and a previously described hyper-recombining mutant. RTIGER is available as an R package with an efficient Julia implementation of the core algorithm.

Developmental HCN channelopathy results in decreased neural progenitor proliferation and microcephaly in mice.

The development of the cerebral cortex relies on the controlled division of neural stem and progenitor cells. The requirement for precise spatiotemporal control of proliferation and cell fate places a high demand on the cell division machinery, and defective cell division can cause microcephaly and other brain malformations. Cell-extrinsic and -intrinsic factors govern the capacity of cortical progenitors to produce large numbers of neurons and glia within a short developmental time window. In particular, ion channels shape the intrinsic biophysical properties of precursor cells and neurons and control their membrane potential throughout the cell cycle. We found that hyperpolarization-activated cyclic nucleotide-gated cation (HCN) channel subunits are expressed in mouse, rat, and human neural progenitors. Loss of HCN channel function in rat neural stem cells impaired their proliferation by affecting the cell-cycle progression, causing G1 accumulation and dysregulation of genes associated with human microcephaly. Transgene-mediated, dominant-negative loss of HCN channel function in the embryonic mouse telencephalon resulted in pronounced microcephaly. Together, our findings suggest a role for HCN channel subunits as a part of a general mechanism influencing cortical development in mammals.

IGF1R expression by adult oligodendrocytes is not required in the steady-state but supports neuroinflammation.

In the central nervous system (CNS), insulin-like growth factor 1 (IGF-1) regulates myelination by oligodendrocyte (ODC) precursor cells and shows anti-apoptotic properties in neuronal cells in different in vitro and in vivo systems. Previous work also suggests that IGF-1 protects ODCs from cell death and enhances remyelination in models of toxin-induced and autoimmune demyelination. However, since evidence remains controversial, the therapeutic potential of IGF-1 in demyelinating CNS conditions is unclear. To finally shed light on the function of IGF1-signaling for ODCs, we deleted insulin-like growth factor 1 receptor (IGF1R) specifically in mature ODCs of the mouse. We found that ODC survival and myelin status were unaffected by the absence of IGF1R until 15 months of age, indicating that IGF-1 signaling does not play a major role in post-mitotic ODCs during homeostasis. Notably, the absence of IGF1R did neither affect ODC survival nor myelin status upon cuprizone intoxication or induction of experimental autoimmune encephalomyelitis (EAE), models for toxic and autoimmune demyelination, respectively. Surprisingly, however, the absence of IGF1R from ODCs protected against clinical neuroinflammation in the EAE model. Together, our data indicate that IGF-1 signaling is not required for the function and survival of mature ODCs in steady-state and disease.

Investigating non-inferiority or equivalence in time-to-event data under non-proportional hazards.

The classical approach to analyze time-to-event data, e.g. in clinical trials, is to fit Kaplan-Meier curves yielding the treatment effect as the hazard ratio between treatment groups. Afterwards, a log-rank test is commonly performed to investigate whether there is a difference in survival or, depending on additional covariates, a Cox proportional hazard model is used. However, in numerous trials these approaches fail due to the presence of non-proportional hazards, resulting in difficulties of interpreting the hazard ratio and a loss of power. When considering equivalence or non-inferiority trials, the commonly performed log-rank based tests are similarly affected by a violation of this assumption. Here we propose a parametric framework to assess equivalence or non-inferiority for survival data. We derive pointwise confidence bands for both, the hazard ratio and the difference of the survival curves. Further we propose a test procedure addressing non-inferiority and equivalence by directly comparing the survival functions at certain time points or over an entire range of time. Once the model's suitability is proven the method provides a noticeable power benefit, irrespectively of the shape of the hazard ratio. On the other hand, model selection should be carried out carefully as misspecification may cause type I error inflation in some situations. We investigate the robustness and demonstrate the advantages and disadvantages of the proposed methods by means of a simulation study. Finally, we demonstrate the validity of the methods by a clinical trial example.

Global analysis of eukaryotic mRNA degradation reveals Xrn1-dependent buffering of transcript levels.

The rates of mRNA synthesis and degradation determine cellular mRNA levels and can be monitored by comparative dynamic transcriptome analysis (cDTA) that uses nonperturbing metabolic RNA labeling. Here we present cDTA data for 46 yeast strains lacking genes involved in mRNA degradation and metabolism. In these strains, changes in mRNA degradation rates are generally compensated by changes in mRNA synthesis rates, resulting in a buffering of mRNA levels. We show that buffering of mRNA levels requires the RNA exonuclease Xrn1. The buffering is rapidly established when mRNA synthesis is impaired, but is delayed when mRNA degradation is impaired, apparently due to Xrn1-dependent transcription repressor induction. Cluster analysis of the data defines the general mRNA degradation machinery, reveals different substrate preferences for the two mRNA deadenylase complexes Ccr4-Not and Pan2-Pan3, and unveils an interwoven cellular mRNA surveillance network.

Clustering of samples with a tree-shaped dependence structure, with an application to microscopic time lapse imaging.

MOTIVATION: Recent imaging technologies allow for high-throughput tracking of cells as they migrate, divide, express fluorescent markers and change their morphology. The interpretation of these data requires unbiased, efficient statistical methods that model the dynamics of cell phenotypes. RESULTS: We introduce treeHFM, a probabilistic model which generalizes the theory of hidden Markov models to tree structured data. While accounting for the entire genealogy of a cell, treeHFM categorizes cells according to their primary phenotypic features. It models all relevant events in a cell's life, including cell division, and thereby enables the analysis of event order and cell fate heterogeneity. Simulations show higher accuracy in predicting correct state labels when modeling the more complex, tree-shaped dependency of samples over standard HMM modeling. Applying treeHFM to time lapse images of hematopoietic progenitor cell differentiation, we demonstrate that progenitor cells undergo a well-ordered sequence of differentiation events. AVAILABILITY AND IMPLEMENTATION: The treeHFM is implemented in C++. We provide wrapper functions for the programming languages R (CRAN package, https://CRAN.R-project.org/package=treeHFM) and Matlab (available at Mathworks Central, http://se.mathworks.com/matlabcentral/fileexchange/57575-treehfml). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

GenoGAM: genome-wide generalized additive models for ChIP-Seq analysis.

MOTIVATION: Chromatin immunoprecipitation followed by deep sequencing (ChIP-Seq) is a widely used approach to study protein-DNA interactions. Often, the quantities of interest are the differential occupancies relative to controls, between genetic backgrounds, treatments, or combinations thereof. Current methods for differential occupancy of ChIP-Seq data rely however on binning or sliding window techniques, for which the choice of the window and bin sizes are subjective. RESULTS: Here, we present GenoGAM (Genome-wide Generalized Additive Model), which brings the well-established and flexible generalized additive models framework to genomic applications using a data parallelism strategy. We model ChIP-Seq read count frequencies as products of smooth functions along chromosomes. Smoothing parameters are objectively estimated from the data by cross-validation, eliminating ad hoc binning and windowing needed by current approaches. GenoGAM provides base-level and region-level significance testing for full factorial designs. Application to a ChIP-Seq dataset in yeast showed increased sensitivity over existing differential occupancy methods while controlling for type I error rate. By analyzing a set of DNA methylation data and illustrating an extension to a peak caller, we further demonstrate the potential of GenoGAM as a generic statistical modeling tool for genome-wide assays. AVAILABILITY AND IMPLEMENTATION: Software is available from Bioconductor: https://www.bioconductor.org/packages/release/bioc/html/GenoGAM.html . CONTACT: gagneur@in.tum.de. SUPPLEMENTARY INFORMATION: Supplementary information is available at Bioinformatics online.

Simultaneous characterization of sense and antisense genomic processes by the double-stranded hidden Markov model.

Hidden Markov models (HMMs) have been extensively used to dissect the genome into functionally distinct regions using data such as RNA expression or DNA binding measurements. It is a challenge to disentangle processes occurring on complementary strands of the same genomic region. We present the double-stranded HMM (dsHMM), a model for the strand-specific analysis of genomic processes. We applied dsHMM to yeast using strand specific transcription data, nucleosome data, and protein binding data for a set of 11 factors associated with the regulation of transcription.The resulting annotation recovers the mRNA transcription cycle (initiation, elongation, termination) while correctly predicting strand-specificity and directionality of the transcription process. We find that pre-initiation complex formation is an essentially undirected process, giving rise to a large number of bidirectional promoters and to pervasive antisense transcription. Notably, 12% of all transcriptionally active positions showed simultaneous activity on both strands. Furthermore, dsHMM reveals that antisense transcription is specifically suppressed by Nrd1, a yeast termination factor.

Heterochrony underpins natural variation in Cardamine hirsuta leaf form.

A key problem in biology is whether the same processes underlie morphological variation between and within species. Here, by using plant leaves as an example, we show that the causes of diversity at these two evolutionary scales can be divergent. Some species like the model plant Arabidopsis thaliana have simple leaves, whereas others like the A. thaliana relative Cardamine hirsuta bear complex leaves comprising leaflets. Previous work has shown that these interspecific differences result mostly from variation in local tissue growth and patterning. Now, by cloning and characterizing a quantitative trait locus (QTL) for C. hirsuta leaf shape, we find that a different process, age-dependent progression of leaf form, underlies variation in this trait within species. This QTL effect is caused by cis-regulatory variation in the floral repressor ChFLC, such that genotypes with low-expressing ChFLC alleles show both early flowering and accelerated age-dependent changes in leaf form, including faster leaflet production. We provide evidence that this mechanism coordinates leaf development with reproductive timing and may help to optimize resource allocation to the next generation.

G-EYE advanced colonoscopy for improved polyp detection rates - a randomized tandem pilot study with different endoscopists.

BACKGROUND AND AIMS: The most commonly missed polyps in colonoscopy are those located behind haustral folds. The G-EYE system is a standard colonoscope consisting of re-processable balloon at its distal tip. The G-EYE balloon improves the detection of polyps by straightening the haustral folds. In our back-to-back tandem study, we aimed to determine whether and to what extent the G-EYE system could reduce adenoma miss rates in screening colonoscopy. METHODS: Patients referred to colonoscopy were randomized into 2 groups. Group A underwent a standard colonoscopy (SC) followed by balloon colonoscopy (BC), and Group B underwent BC followed by SC. In this randomized tandem study, the investigator's level of training and the endoscopists themselves were changed after each withdrawal. Each endoscopist was blinded to the results of the first withdrawal. RESULTS: Fifty-eight patients were enrolled and randomized into 2 groups with similar baseline characteristics. Nine patients were excluded from the study. Twenty-five patients underwent SC followed by BC while 24 underwent BC followed by SC. The adenoma miss rate for SC was 41 %, with an additional detection rate of 69 % for BC (ratio 1.69). The overall miss rate for polyps was 60 % for SC, with an additional detection rate of 150 % for BC (ratio 2.5). Experienced investigators who used BC were able to identify an additional 7 polyps while inexperienced investigators. CONCLUSIONS: Although our results could not clearly confirm that BC improves adenoma detection, the investigator's experience appears to be a major determinant of the adenoma detection rate.

The Manchester Triage System (MTS): a score for emergency management of patients with acute gastrointestinal bleeding.

BACKGROUND: Suspected gastrointestinal (GI) bleeding is a common initial diagnosis in emergency departments. Despite existing endoscopic scores to estimate the risk of GI bleeding, the primary clinical assessment of urgency can remain challenging. The 5-step Manchester Triage System (MTS) is a validated score that is often applied for the initial assessment of patients presenting in emergency departments. METHODS: All computer-based records of patients who were admitted between January 2014 and December 2014 to our emergency department in a tertiary referral hospital were analyzed retrospectively. The aim of our retrospective analysis was to determine if patient triage using the MTS is associated with rates of endoscopy and with presence of active GI bleeding. RESULTS: In summary, 5689 patients with a GI condition were treated at our emergency department. Two hundred eighty-four patients (4.9 %) presented with suspected GI bleeding, and 165 patients (58 %) received endoscopic diagnostic. Endoscopic intervention for hemostasis was needed in 34 patients (21 %). In patients who underwent emergency endoscopy, triage into MTS categories with higher urgency was associated with higher rates of endoscopic confirmation of suspected GI bleeding (79 % of patients with MTS priority levels 1 or 2, 53 % in level 3 patients, and 40 % in levels 4 or 5 patients; p = 0.024). CONCLUSIONS: The MTS is an established tool for triage in emergency departments and could have a potential to guide early clinical decision-making with regards to urgency of endoscopic evaluation in patients with suspected GI bleeding.

Efficient Maximum Likelihood Estimation for Pedigree Data with the Sum-Product Algorithm.

OBJECTIVE: We analyze data sets consisting of pedigrees with age at onset of colorectal cancer (CRC) as phenotype. The occurrence of familial clusters of CRC suggests the existence of a latent, inheritable risk factor. We aimed to compute the probability of a family possessing this risk factor as well as the hazard rate increase for these risk factor carriers. Due to the inheritability of this risk factor, the estimation necessitates a costly marginalization of the likelihood. METHODS: We propose an improved EM algorithm by applying factor graphs and the sum-product algorithm in the E-step. This reduces the computational complexity from exponential to linear in the number of family members. RESULTS: Our algorithm is as precise as a direct likelihood maximization in a simulation study and a real family study on CRC risk. For 250 simulated families of size 19 and 21, the runtime of our algorithm is faster by a factor of 4 and 29, respectively. On the largest family (23 members) in the real data, our algorithm is 6 times faster. CONCLUSION: We introduce a flexible and runtime-efficient tool for statistical inference in biomedical event data with latent variables that opens the door for advanced analyses of pedigree data.

Factor graph analysis of live cell-imaging data reveals mechanisms of cell fate decisions.

MOTIVATION: Cell fate decisions have a strong stochastic component. The identification of the underlying mechanisms therefore requires a rigorous statistical analysis of large ensembles of single cells that were tracked and phenotyped over time. RESULTS: We introduce a probabilistic framework for testing elementary hypotheses on dynamic cell behavior using time-lapse cell-imaging data. Factor graphs, probabilistic graphical models, are used to properly account for cell lineage and cell phenotype information. Our model is applied to time-lapse movies of murine granulocyte-macrophage progenitor (GMP) cells. It decides between competing hypotheses on the mechanisms of their differentiation. Our results theoretically substantiate previous experimental observations that lineage instruction, not selection is the cause for the differentiation of GMP cells into mature monocytes or neutrophil granulocytes. AVAILABILITY AND IMPLEMENTATION: The Matlab source code is available at http://treschgroup.de/Genealogies.html.

Comparative dynamic transcriptome analysis (cDTA) reveals mutual feedback between mRNA synthesis and degradation.

To monitor eukaryotic mRNA metabolism, we developed comparative dynamic transcriptome analysis (cDTA). cDTA provides absolute rates of mRNA synthesis and decay in Saccharomyces cerevisiae (Sc) cells with the use of Schizosaccharomyces pombe (Sp) as an internal standard. cDTA uses nonperturbing metabolic labeling that supersedes conventional methods for mRNA turnover analysis. cDTA reveals that Sc and Sp transcripts that encode orthologous proteins have similar synthesis rates, whereas decay rates are fivefold lower in Sp, resulting in similar mRNA concentrations despite the larger Sp cell volume. cDTA of Sc mutants reveals that a eukaryote can buffer mRNA levels. Impairing transcription with a point mutation in RNA polymerase (Pol) II causes decreased mRNA synthesis rates as expected, but also decreased decay rates. Impairing mRNA degradation by deleting deadenylase subunits of the Ccr4-Not complex causes decreased decay rates as expected, but also decreased synthesis rates. Extended kinetic modeling reveals mutual feedback between mRNA synthesis and degradation that may be achieved by a factor that inhibits synthesis and enhances degradation.

Genome-wide quantitative analysis of DNA methylation from bisulfite sequencing data.

UNLABELLED: Here we present the open-source R/Bioconductor software package BEAT (BS-Seq Epimutation Analysis Toolkit). It implements all bioinformatics steps required for the quantitative high-resolution analysis of DNA methylation patterns from bisulfite sequencing data, including the detection of regional epimutation events, i.e. loss or gain of DNA methylation at CG positions relative to a reference. Using a binomial mixture model, the BEAT package aggregates methylation counts per genomic position, thereby compensating for low coverage, incomplete conversion and sequencing errors. AVAILABILITY AND IMPLEMENTATION: BEAT is freely available as part of Bioconductor at www.bioconductor.org/packages/devel/bioc/html/BEAT.html. The package is distributed under the GNU Lesser General Public License 3.0.

Exact likelihood computation in Boolean networks with probabilistic time delays, and its application in signal network reconstruction.

MOTIVATION: For biological pathways, it is common to measure a gene expression time series after various knockdowns of genes that are putatively involved in the process of interest. These interventional time-resolved data are most suitable for the elucidation of dynamic causal relationships in signaling networks. Even with this kind of data it is still a major and largely unsolved challenge to infer the topology and interaction logic of the underlying regulatory network. RESULTS: In this work, we present a novel model-based approach involving Boolean networks to reconstruct small to medium-sized regulatory networks. In particular, we solve the problem of exact likelihood computation in Boolean networks with probabilistic exponential time delays. Simulations demonstrate the high accuracy of our approach. We apply our method to data of Ivanova et al. (2006), where RNA interference knockdown experiments were used to build a network of the key regulatory genes governing mouse stem cell maintenance and differentiation. In contrast to previous analyses of that data set, our method can identify feedback loops and provides new insights into the interplay of some master regulators in embryonic stem cell development. AVAILABILITY AND IMPLEMENTATION: The algorithm is implemented in the statistical language R. Code and documentation are available at Bioinformatics online. CONTACT: duemcke@mpipz.mpg.de or tresch@mpipz.mpg.de SUPPLEMENTARY INFORMATION: Supplementary Materials are available at Bioinfomatics online.

Annotation of genomics data using bidirectional hidden Markov models unveils variations in Pol II transcription cycle.

DNA replication, transcription and repair involve the recruitment of protein complexes that change their composition as they progress along the genome in a directed or strand-specific manner. Chromatin immunoprecipitation in conjunction with hidden Markov models (HMMs) has been instrumental in understanding these processes, as they segment the genome into discrete states that can be related to DNA-associated protein complexes. However, current HMM-based approaches are not able to assign forward or reverse direction to states or properly integrate strand-specific (e.g., RNA expression) with non-strand-specific (e.g., ChIP) data, which is indispensable to accurately characterize directed processes. To overcome these limitations, we introduce bidirectional HMMs which infer directed genomic states from occupancy profiles de novo. Application to RNA polymerase II-associated factors in yeast and chromatin modifications in human T cells recovers the majority of transcribed loci, reveals gene-specific variations in the yeast transcription cycle and indicates the existence of directed chromatin state patterns at transcribed, but not at repressed, regions in the human genome. In yeast, we identify 32 new transcribed loci, a regulated initiation-elongation transition, the absence of elongation factors Ctk1 and Paf1 from a class of genes, a distinct transcription mechanism for highly expressed genes and novel DNA sequence motifs associated with transcription termination. We anticipate bidirectional HMMs to significantly improve the analyses of genome-associated directed processes.

Periodic mRNA synthesis and degradation co-operate during cell cycle gene expression.

During the cell cycle, the levels of hundreds of mRNAs change in a periodic manner, but how this is achieved by alterations in the rates of mRNA synthesis and degradation has not been studied systematically. Here, we used metabolic RNA labeling and comparative dynamic transcriptome analysis (cDTA) to derive mRNA synthesis and degradation rates every 5 min during three cell cycle periods of the yeast Saccharomyces cerevisiae. A novel statistical model identified 479 genes that show periodic changes in mRNA synthesis and generally also periodic changes in their mRNA degradation rates. Peaks of mRNA degradation generally follow peaks of mRNA synthesis, resulting in sharp and high peaks of mRNA levels at defined times during the cell cycle. Whereas the timing of mRNA synthesis is set by upstream DNA motifs and their associated transcription factors (TFs), the synthesis rate of a periodically expressed gene is apparently set by its core promoter.