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Knowledge about the biogeographic affinities of the world’s tropical forests helps to better understand regional differences in forest structure, diversity, composition, and dynamics. Such understanding will enable anticipation of region-specific responses to global environmental change. Modern phylogenies, in combination with broad coverage of species inventory data, now allow for global biogeographic analyses that take species evolutionary distance into account. Here we present a classification of the world’s tropical forests based on their phylogenetic similarity. We identify five principal floristic regions and their floristic relationships: (i) Indo-Pacific, (ii) Subtropical, (iii) African, (iv) American, and (v) Dry forests. Our results do not support the traditional neo- versus paleotropical forest division but instead separate the combined American and African forests from their Indo-Pacific counterparts. We also find indications for the existence of a global dry forest region, with representatives in America, Africa, Madagascar, and India. Additionally, a northern-hemisphere Subtropical forest region was identified with representatives in Asia and America, providing support for a link between Asian and American northern-hemisphere forests.
The two main phytocannabinoids—delta-9-tetrahydrocannabinol (THC) and cannabidiol (CBD)—have been extensively studied, and it has been shown that THC can induce transient psychosis. At the same time, CBD appears to have no psychotomimetic potential. On the contrary, emerging evidence for CBD's antipsychotic properties suggests that it may attenuate effects induced by THC. Thus, we investigated and compared the effects of THC and CBD administration on emotion, cognition, and attention as well as the impact of CBD pre-treatment on THC effects in healthy volunteers. We performed a placebo-controlled, double-blind, experimental trial (GEI-TCP II; ClinicalTrials.gov identifier: NCT02487381) with 60 healthy volunteers randomly allocated to four parallel intervention groups, receiving either placebo, 800 mg CBD, 20 mg THC, or both cannabinoids. Subjects underwent neuropsychological tests assessing working memory (Letter Number Sequencing test), cognitive processing speed (Digit Symbol Coding task), attention (d2 Test of Attention), and emotional state (adjective mood rating scale [EWL]). Administration of CBD alone did not influence the emotional state, cognitive performance, and attention. At the same time, THC affected two of six emotional categories—more precisely, the performance-related activity and extraversion—, reduced the cognitive processing speed and impaired the performance on the d2 Test of Attention. Interestingly, pre-treatment with CBD did not attenuate the effects induced by THC. These findings show that the acute intake of CBD itself has no effect per se in healthy volunteers and that a single dose of CBD prior to THC administration was insufficient to mitigate the detrimental impact of THC in the given setting. This is in support of a complex interaction between CBD and THC whose effects are not counterbalanced by CBD under all circumstances.
Gene-modified autologous hematopoietic stem cells (HSC) can provide ample clinical benefits to subjects suffering from X-linked chronic granulomatous disease (X-CGD), a rare inherited immunodeficiency characterized by recurrent, often life-threatening bacterial and fungal infections. Here we report on the molecular and cellular events observed in two young adults with X-CGD treated by gene therapy in 2004. After the initial resolution of bacterial and fungal infections, both subjects showed silencing of transgene expression due to methylation of the viral promoter, and myelodysplasia with monosomy 7 as a result of insertional activation of ecotropic viral integration site 1 (EVI1). One subject died from overwhelming sepsis 27 months after gene therapy, whereas a second subject underwent an allogeneic HSC transplantation. Our data show that forced overexpression of EVI1 in human cells disrupts normal centrosome duplication, linking EVI1 activation to the development of genomic instability, monosomy 7 and clonal progression toward myelodysplasia.
The nucleosynthesis of elements beyond iron is dominated by neutron captures in the s and r processes. However, 32 stable, proton-rich isotopes cannot be formed during those processes, because they are shielded from the s-process flow and r-process β-decay chains. These nuclei are attributed to the p and rp process.
For all those processes, current research in nuclear astrophysics addresses the need for more precise reaction data involving radioactive isotopes. Depending on the particular reaction, direct or inverse kinematics, forward or time-reversed direction are investigated to determine or at least to constrain the desired reaction cross sections.
The Facility for Antiproton and Ion Research (FAIR) will offer unique, unprecedented opportunities to investigate many of the important reactions. The high yield of radioactive isotopes, even far away from the valley of stability, allows the investigation of isotopes involved in processes as exotic as the r or rp processes.
Background: Intestinal perforation or leakage increases morbidity and mortality of surgical and endoscopic interventions. We identified criteria for use of full-covered, extractable self-expanding metal stents (cSEMS) vs. "Over the scope"-clips (OTSC) for leak closure.
Methods: Patients who underwent endoscopic treatment for postoperative leakage, endoscopic perforation, or spontaneous rupture of the upper gastrointestinal tract between 2006 and 2013 were identified at four tertiary endoscopic centers. Technical success, outcome (e.g. duration of hospitalization, in-hospital mortality), and complications were assessed and analyzed with respect to etiology, size and location of leakage.
Results: Of 106 patients (male: 75 (71%), female: 31 (29%); age (mean ± SD): 62.5 ± 1.3 years, 72 (69%) were treated by cSEMS and 34 (31%) by OTSC. For cSEMS vs. OTSC, mean treatment duration was 41.1 vs. 25 days, p<0.001, leakage size 10 (1-50) vs. 5 (1-30) mm (median (range)), and complications were observed in 68% vs. 8.8%, p<0.001, respectively. Clinical success for primary interventional treatment was observed in 29/72 (40%) vs. 24/34 (70%, p = 0.006), and clinical success at the end of follow-up was 46/72 (64%) vs. 29/34 (85%) for patients treated by cSEMS vs. OTSC; p = 0.04.
Conclusion: OTSC is preferred in small-sized lesions and in perforation caused by endoscopic interventions, cSEMS in patients with concomitant local infection or abscess. cSEMS is associated with a higher frequency of complications. Therefore, OTSC might be preferred if technically feasible. Indication criteria for cSEMS vs. OTSC vary and might impede design of randomized studies.
Aims: Averaged measurements, but not the progression based on multiple assessments of carotid intima-media thickness, (cIMT) are predictive of cardiovascular disease (CVD) events in individuals. Whether this is true for conventional risk factors is unclear.
Methods and results: An individual participant meta-analysis was used to associate the annualised progression of systolic blood pressure, total cholesterol, low-density lipoprotein cholesterol and high-density lipoprotein cholesterol with future cardiovascular disease risk in 13 prospective cohort studies of the PROG-IMT collaboration (n = 34,072). Follow-up data included information on a combined cardiovascular disease endpoint of myocardial infarction, stroke, or vascular death. In secondary analyses, annualised progression was replaced with average. Log hazard ratios per standard deviation difference were pooled across studies by a random effects meta-analysis. In primary analysis, the annualised progression of total cholesterol was marginally related to a higher cardiovascular disease risk (hazard ratio (HR) 1.04, 95% confidence interval (CI) 1.00 to 1.07). The annualised progression of systolic blood pressure, low-density lipoprotein cholesterol and high-density lipoprotein cholesterol was not associated with future cardiovascular disease risk. In secondary analysis, average systolic blood pressure (HR 1.20 95% CI 1.11 to 1.29) and low-density lipoprotein cholesterol (HR 1.09, 95% CI 1.02 to 1.16) were related to a greater, while high-density lipoprotein cholesterol (HR 0.92, 95% CI 0.88 to 0.97) was related to a lower risk of future cardiovascular disease events.
Conclusion: Averaged measurements of systolic blood pressure, low-density lipoprotein cholesterol and high-density lipoprotein cholesterol displayed significant linear relationships with the risk of future cardiovascular disease events. However, there was no clear association between the annualised progression of these conventional risk factors in individuals with the risk of future clinical endpoints.
Objective: Combination antiretroviral therapy (cART) has markedly increased survival and quality of life in people living with HIV. With the advent of new treatment options, including single-tablet regimens, durability and efficacy of first-line cART regimens are evolving.
Methods: We analyzed data from the prospective multicenter German Clinical Surveillance of HIV Disease (ClinSurv) cohort of the Robert-Koch Institute. Kaplan–Meier and Cox proportional hazards models were run to examine the factors associated with treatment modification. Recovery after treatment initiation was analyzed comparing pre-cART viral load and CD4+ T-cell counts with follow-up data.
Results: We included 8788 patients who initiated cART between 2005 and 2017. The sample population was predominantly male (n = 7040; 80.1%), of whom 4470 (63.5%) were reporting sex with men as the transmission risk factor. Overall, 4210 (47.9%) patients modified their first-line cART after a median time of 63 months (IQR 59–66). Regimens containing integrase strand transfer inhibitors (INSTI) were associated with significantly lower rates of treatment modification (adjusted hazard ratio 0.44; 95% CI 0.39–0.50) compared to protease inhibitor (PI)-based regimens. We found a decreased durability of first-line cART significantly associated with being female, a low CD4+ T-cell count, cART initiation in the later period (2011–2017), being on a multi-tablet regimen (MTR).
Conclusions: Drug class and MTRs are significantly associated with treatment modification. INSTI-based regimens showed to be superior compared to PI-based regimens in terms of durability.
Correction to: Infection (2020) 48:723–733 https://doi.org/10.1007/s15010-020-01469-6. The original version of this article unfortunately contained a mistake. In this article the authors Dirk Schürmann at affiliation Charité, University Medicine, Berlin, Olaf Degen at affiliation University Clinic Hamburg Eppendorf, Hamburg and Heinz-August Horst at affiliation University Hospital Schleswig–Holstein, Kiel, Germany were missing from the author list. The original article has been corrected.
Non-alcoholic steatohepatitis (NASH) - a hepatic manifestation of the metabolic syndrome - is a multifactorial disease with alarming global prevalence. It involves steatosis, inflammation and fibrosis in the liver, thus demanding multiple modes of action for robust therapeutic efficacy. Aiming to fuse complementary validated anti-NASH strategies in a single molecule, we have designed and systematically optimized a scaffold for triple activation of farnesoid X receptor (FXR), peroxisome proliferator-activated receptor (PPAR) α and PPARδ. Pilot profiling of the resulting triple modulator demonstrated target engagement in native cellular settings and in mice, rendering it a suitable tool to probe the triple modulator concept in vivo. In DIO NASH in mice, the triple agonist counteracted hepatic inflammation and reversed hepatic fibrosis highlighting the potential of designed polypharmacology in NASH.
This paper presents results from the "INUIT-JFJ/CLACE 2013" field campaign at the high alpine research station Jungfraujoch in January/February 2013. The chemical composition of ice particle residuals (IPR) in a size diameter range of 200–900 nm was measured in orographic, convective and non-convective clouds with a single particle mass spectrometer (ALABAMA) under ambient conditions characterized by temperatures between −28 and −4 °C and wind speed from 0.1 to 21 km h−1. Additionally, background aerosol particles in cloud free air were investigated. The IPR were sampled from mixed-phase clouds with two inlets which selectively extract small ice crystals in-cloud, namely the Counterflow Virtual Impactor (Ice-CVI) and the Ice Selective Inlet (ISI). The IPR as well as the aerosol particles were classified into seven different particle types: (1) black carbon, (2) organic carbon, (3) black carbon internally mixed with organic carbon, (4) minerals, (5) one particle group (termed "BioMinSal") that may contain biological particles, minerals, or salts, (6) industrial metals, and (7) lead containing particles. For any sampled particle population it was determined by means of single particle mass spectrometer how many of the analyzed particles belonged to each of these categories. Accordingly, between 20 and 30% of the IPR and roughly 42% of the background particles contained organic carbon. The measured fractions of minerals in the IPR composition varied from 6 to 33%, while the values for the "BioMinSal" group were between 15 and 29%. Four percent to 31% of the IPR contained organic carbon mixed with black carbon. Both inlets delivered similar results of the chemical composition and of the particle size distribution, although lead was found only in the IPR sampled by the Ice-CVI. The results show that the ice particle residual composition varies substantially between different cloud events, which indicates the influence of different meteorological conditions, such as origin of the air masses, temperature and wind speed.
In the present work, three different techniques are used to separate ice-nucleating particles (INP) and ice particle residuals (IPR) from non-ice-active particles: the Ice Selective Inlet (ISI) and the Ice Counterflow Virtual Impactor (Ice-CVI), which sample ice particles from mixed phase clouds and allow for the analysis of the residuals, as well as the combination of the Fast Ice Nucleus Chamber (FINCH) and the Ice Nuclei Pumped Virtual Impactor (IN-PCVI), which provides ice-activating conditions to aerosol particles and extracts the activated ones for analysis. The collected particles were analyzed by scanning electron microscopy and energy-dispersive X-ray microanalysis to determine their size, chemical composition and mixing state. Samples were taken during January/February 2013 at the High Alpine Research Station Jungfraujoch. All INP/IPR-separating techniques had considerable abundances (median 20–70%) of contamination artifacts (ISI: Si-O spheres, probably calibration aerosol; Ice-CVI: Al-O particles; FINCH + IN-PCVI: steel particles). Also, potential measurement artifacts (soluble material) occurred (median abundance < 20%). After removal of the contamination particles, silicates and Ca-rich particles, carbonaceous material and metal oxides were the major INP/IPR particle types separated by all three techniques. Minor types include soot and Pb-bearing particles. Sea-salt and sulfates were identified by all three methods as INP/IPR. Lead was identified in less than 10% of the INP/IPR. It was mainly present as an internal mixture with other particle types, but also external lead-rich particles were found. Most samples showed a maximum of the INP/IPR size distribution at 400 nm geometric diameter. In a few cases, a second super-micron maximum was identified. Soot/carbonaceous material and metal oxides were present mainly in the submicron range. ISI and FINCH yielded silicates and Ca-rich particles mainly with diameters above 1 μm, while the Ice-CVI also sampled many submicron particles. Probably owing to the different meteorological conditions, the INP/IPR composition was highly variable on a sample to sample basis. Thus, some part of the discrepancies between the different techniques may result from the (unavoidable) non-parallel sampling. The observed differences of the particles group abundances as well as the mixing state of INP/IPR point to the need of further studies to better understand the influence of the separating techniques on the INP/IPR chemical composition.
During January/February 2013, at the High Alpine Research Station Jungfraujoch a measurement campaign was carried out, which was centered on atmospheric ice-nucleating particles (INP) and ice particle residuals (IPR). Three different techniques for separation of INP and IPR from the non-ice-active particles are compared. The Ice Selective Inlet (ISI) and the Ice Counterflow Virtual Impactor (Ice-CVI) sample ice particles from mixed phase clouds and allow for the analysis of the residuals. The combination of the Fast Ice Nucleus Chamber (FINCH) and the Ice Nuclei Pumped Counterflow Virtual Impactor (IN-PCVI) provides ice-activating conditions to aerosol particles and extracts the activated INP for analysis.Collected particles were analyzed by scanning electron microscopy and energy-dispersive X-ray microanalysis to determine size, chemical composition and mixing state. All INP/IPR-separating techniques had considerable abundances (median 20 – 70 %) of instrumental contamination artifacts (ISI: Si-O spheres, probably calibration aerosol; Ice-CVI: Al-O particles; FINCH+IN-PCVI: steel particles). Also, potential sampling artifacts (e.g., pure soluble material) occurred with a median abundance of < 20 %. While these could be explained as IPR by ice break-up, for INP their IN-ability pathway is less clear. After removal of the contamination artifacts, silicates and Ca-rich particles, carbonaceous material and metal oxides were the major INP/IPR particle types separated by all three techniques. Soot was a minor contributor. Lead was detected in less than 10 % of the particles, of which the majority were internal mixtures with other particle types. Sea-salt and sulfates were identified by all three methods as INP/IPR. Most samples showed a maximum of the INP/IPR size distribution at 400 nm geometric diameter. In a few cases, a second super-micron maximum was identified. Soot/carbonaceous material and metal oxides were present mainly in the submicron range. ISI and FINCH yielded silicates and Ca-rich particles mainly with diameters above 1 μm, while the Ice-CVI also separated many submicron IPR. As strictly parallel sampling could not be performed, a part of the discrepancies between the different techniques may result from variations in meteorological conditions and subsequent INP/IPR composition. The observed differences in the particle group abundances as well as in the mixing state of INP/IPR express the need for further studies to better understand the influence of the separating techniques on the INP/IPR chemical
composition.
The production of Σ0 baryons in the nuclear reaction p (3.5 GeV) + Nb (corresponding to sNN=3.18 GeV) is studied with the detector set-up HADES at GSI, Darmstadt. Σ0s were identified via the decay Σ0→Λγ with subsequent decays Λ→pπ− in coincidence with a e+e− pair from either external (γ→e+e−) or internal (Dalitz decay γ⁎→e+e−) gamma conversions. The differential Σ0 cross section integrated over the detector acceptance, i.e. the rapidity interval 0.5<y<1.1, has been extracted as ΔσΣ0=2.3±(0.2)stat±(−0.6+0.6)sys±(0.2)norm mb, yielding the inclusive production cross section in full phase space σΣ0total=5.8±(0.5)stat±(−1.4+1.4)sys±(0.6)norm±(1.7)extrapol mb by averaging over different extrapolation methods. The Λall/Σ0 ratio within the HADES acceptance is equal to 2.3±(0.2)stat±(−0.6+0.6)sys. The obtained rapidity and momentum distributions are compared to transport model calculations. The Σ0 yield agrees with the statistical model of particle production in nuclear reactions. Keywords: Hyperons, Strangeness, Proton, Nucleus.
Infections of the central nervous system (CNS) are infrequently diagnosed in immunocompetent patients, but they do occur in a significant proportion of patients with hematological disorders. In particular, patients undergoing allogeneic hematopoietic stem-cell transplantation carry a high risk for CNS infections of up to 15%. Fungi and Toxoplasma gondii are the predominant causative agents. The diagnosis of CNS infections is based on neuroimaging, cerebrospinal fluid examination and biopsy of suspicious lesions in selected patients. However, identification of CNS infections in immunocompromised patients could represent a major challenge since metabolic disturbances, side-effects of antineoplastic or immunosuppressive drugs and CNS involvement of the underlying hematological disorder may mimic symptoms of a CNS infection. The prognosis of CNS infections is generally poor in these patients, albeit the introduction of novel substances (e.g. voriconazole) has improved the outcome in distinct patient subgroups. This guideline has been developed by the Infectious Diseases Working Party (AGIHO) of the German Society of Hematology and Medical Oncology (DGHO) with the contribution of a panel of 14 experts certified in internal medicine, hematology/oncology, infectious diseases, intensive care, neurology and neuroradiology. Grades of recommendation and levels of evidence were categorized by using novel criteria, as recently published by the European Society of Clinical Microbiology and Infectious Diseases.
Four different structural models, which all fit the same X-ray powder pattern, were obtained in the structure determination of 4,11-difluoroquinacridone (C20H10N2O2F2) from unindexed X-ray powder data by a global fit. The models differ in their lattice parameters, space groups, Z, Z′, molecular packing and hydrogen bond patterns. The molecules form a criss-cross pattern in models A and B, a layer structure built from chains in model C and a criss-cross arrangement of dimers in model D. Nevertheless, all models give a good Rietveld fit to the experimental powder pattern with acceptable R-values. All molecular geometries are reliable, except for model D, which is slightly distorted. All structures are crystallochemically plausible, concerning density, hydrogen bonds, intermolecular distances etc. All models passed the checkCIF test without major problems; only in model A a missed symmetry was detected. All structures could have probably been published, although 3 of the 4 structures were wrong. The investigation, which of the four structures is actually the correct one, was challenging. Six methods were used: (1) Rietveld refinements, (2) fit of the crystal structures to the pair distribution function (PDF) including the refinement of lattice parameters and atomic coordinates, (3) evaluation of the colour, (4) lattice-energy minimizations with force fields, (5) lattice-energy minimizations by two dispersion-corrected density functional theory methods, and (6) multinuclear CPMAS solid-state NMR spectroscopy (1H, 13C, 19F) including the comparison of calculated and experimental chemical shifts. All in all, model B (perhaps with some disorder) can probably be considered to be the correct one. This work shows that a structure determination from limited-quality powder data may result in totally different structural models, which all may be correct or wrong, even if they are chemically sensible and give a good Rietveld refinement. Additionally, the work is an excellent example that the refinement of an organic crystal structure can be successfully performed by a fit to the PDF, and the combination of computed and experimental solid-state NMR chemical shifts can provide further information for the selection of the most reliable structure among several possibilities.
Nuclear pore complexes (NPCs) mediate nucleocytoplasmic transport. Their intricate 120 MDa architecture remains incompletely understood. Here, we report a near-complete structural model of the human NPC scaffold with explicit membrane and in multiple conformational states. We combined AI-based structure prediction with in situ and in cellulo cryo-electron tomography and integrative modeling. We show that linker Nups spatially organize the scaffold within and across subcomplexes to establish the higher-order structure. Microsecond-long molecular dynamics simulations suggest that the scaffold is not required to stabilize the inner and outer nuclear membrane fusion, but rather widens the central pore. Our work exemplifies how AI-based modeling can be integrated with in situ structural biology to understand subcellular architecture across spatial organization levels.
Investigators in the cognitive neurosciences have turned to Big Data to address persistent replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. While there is tremendous potential to advance science through open data sharing, these efforts unveil a host of new questions about how to integrate data arising from distinct sources and instruments. We focus on the most frequently assessed area of cognition - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated raw data from 53 studies from around the world which measured at least one of three distinct verbal learning tasks, totaling N = 10,505 healthy and brain-injured individuals. A mega analysis was conducted using empirical bayes harmonization to isolate and remove site effects, followed by linear models which adjusted for common covariates. After corrections, a continuous item response theory (IRT) model estimated each individual subject’s latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance by 37% while preserving covariate effects. The effects of age, sex, and education on scores were found to be highly consistent across memory tests. IRT methods for equating scores across AVLTs agreed with held-out data of dually-administered tests, and these tools are made available for free online. This work demonstrates that large-scale data sharing and harmonization initiatives can offer opportunities to address reproducibility and integration challenges across the behavioral sciences.
n this paper we report on the investigation of baryonic resonance production in proton-proton collisions at the kinetic energies of 1.25 GeV and 3.5 GeV, based on data measured with HADES. Exclusive channels npπ+ and ppπ0 as well as ppe+e− were studied simultaneously in the framework of a one-boson exchange model. The resonance cross sections were determined from the one-pion channels for Δ(1232) and N(1440) (1.25 GeV) as well as further Δ and N* resonances up to 2 GeV/c2 for the 3.5 GeV data. The data at 1.25 GeV energy were also analysed within the framework of the partial wave analysis together with the set of several other measurements at lower energies. The obtained solutions provided the evolution of resonance production with the beam energy, showing a sizeable non-resonant contribution but with still dominating contribution of Δ(1232)P33. In the case of 3.5 GeV data, the study of the ppe+e− channel gave the insight on the Dalitz decays of the baryon resonances and, in particular, on the electromagnetic transition form-factors in the time-like region. We show that the assumption of a constant electromagnetic transition form-factors leads to underestimation of the yield in the dielectron invariant mass spectrum below the vector mesons pole. On the other hand, a comparison with various transport models shows the important role of intermediate ρ production, though with a large model dependency. The exclusive channels analysis done by the HADES collaboration provides new stringent restrictions on the parameterizations used in the models.
his contribution aims to give a basic overview of the latest results regarding the production of resonances in different collision systems. The results were extracted from experimental data collected with HADES that is a multipurpose detector located at the GSI Helmholtzzentrum, Darmstadt. The main points discussed here are: the properties of the strange resonances Λ(1405) and Σ(1385), the role of Δ’s as a source of pions in the final state, the production dynamics reflected in form of differential cross sections, and the role of the ϕ meson as a source for K− particles.
Understanding how epigenetic variation in non-coding regions is involved in distal gene-expression regulation is an important problem. Regulatory regions can be associated to genes using large-scale datasets of epigenetic and expression data. However, for regions of complex epigenomic signals and enhancers that regulate many genes, it is difficult to understand these associations. We present StitchIt, an approach to dissect epigenetic variation in a gene-specific manner for the detection of regulatory elements (REMs) without relying on peak calls in individual samples. StitchIt segments epigenetic signal tracks over many samples to generate the location and the target genes of a REM simultaneously. We show that this approach leads to a more accurate and refined REM detection compared to standard methods even on heterogeneous datasets, which are challenging to model. Also, StitchIt REMs are highly enriched in experimentally determined chromatin interactions and expression quantitative trait loci. We validated several newly predicted REMs using CRISPR-Cas9 experiments, thereby demonstrating the reliability of StitchIt. StitchIt is able to dissect regulation in superenhancers and predicts thousands of putative REMs that go unnoticed using peak-based approaches suggesting that a large part of the regulome might be uncharted water.
Understanding the complexity of transcriptional regulation is a major goal of computational biology. Because experimental linkage of regulatory sites to genes is challenging, computational methods considering epigenomics data have been proposed to create tissue-specific regulatory maps. However, we showed that these approaches are not well suited to account for the variations of the regulatory landscape between cell-types. To overcome these drawbacks, we developed a new method called STITCHIT, that identifies and links putative regulatory sites to genes. Within STITCHIT, we consider the chromatin accessibility signal of all samples jointly to identify regions exhibiting a signal variation related to the expression of a distinct gene. STITCHIT outperforms previous approaches in various validation experiments and was used with a genome-wide CRISPR-Cas9 screen to prioritize novel doxorubicin-resistance genes and their associated non-coding regulatory regions. We believe that our work paves the way for a more refined understanding of transcriptional regulation at the gene-level.
Die Fundmeldungen in Band 34 von Botanik und Naturschutz in Hessen stammen von: Dirk Bönsel, Martin De Jong, Klaus Dühr, Uta Engel, Benjamin Feller, Christian Feuring, Thomas Gregor, Arthur Händler, Karsten Horn, Diemut Klärner, Julia Kruse, Eric Martiné, Hasko Friedrich Nesemann, Kai Uwe Nierbauer, Uwe Raabe, Susanne Raehse, Felix Reischmann, Bernd Sauerwein, Petra Schmidt, Fabian Schrauth, Christof Nikolaus Schröder, Helmut Siebert, Michael Thieme, Otto Wacker und Rüdiger Wittig.
Genome-wide CRISPR screens are becoming more widespread and allow the simultaneous interrogation of thousands of genomic regions. Although recent progress has been made in the analysis of CRISPR screens, it is still an open problem how to interpret CRISPR mutations in non-coding regions of the genome. Most of the tools concentrate on the interpretation of mutations introduced in gene coding regions. We introduce a computational pipeline that uses epigenomic information about regulatory elements for the interpretation of CRISPR mutations in non-coding regions. We illustrate our approach on the analysis of a genome-wide CRISPR screen in hTERT-RPE-1 cells and reveal novel regulatory elements that mediate chemoresistance against doxorubicin in these cells. We infer links to established and to novel chemoresistance genes. Our approach is general and can be applied on any cell type and with different CRISPR enzymes.
Pseudomonas aeruginosa is a human pathogen that causes health-care associated blood stream infections (BSI). Although P. aeruginosa BSI are associated with high mortality rates, the clinical relevance of pathogen-derived prognostic biomarker to identify patients at risk for unfavorable outcome remains largely unexplored. We found novel pathogen-derived prognostic biomarker candidates by applying a multi-omics approach on a multicenter sepsis patient cohort. Multi-level Cox regression was used to investigate the relation between patient characteristics and pathogen features (2298 accessory genes, 1078 core protein levels, 107 parsimony-informative variations in reported virulence factors) with 30-day mortality. Our analysis revealed that presence of the helP gene encoding a putative DEAD-box helicase was independently associated with a fatal outcome (hazard ratio 2.01, p = 0.05). helP is located within a region related to the pathogenicity island PAPI-1 in close proximity to a pil gene cluster, which has been associated with horizontal gene transfer. Besides helP, elevated protein levels of the bacterial flagellum protein FliL (hazard ratio 3.44, p < 0.001) and of a bacterioferritin-like protein (hazard ratio 1.74, p = 0.003) increased the risk of death, while high protein levels of a putative aminotransferase were associated with an improved outcome (hazard ratio 0.12, p < 0.001). The prognostic potential of biomarker candidates and clinical factors was confirmed with different machine learning approaches using training and hold-out datasets. The helP genotype appeared the most attractive biomarker for clinical risk stratification due to its relevant predictive power and ease of detection.