Cell-Type-Specific Gene Regulatory Networks of Pro-Inflammatory and Pro-Resolving Lipid Mediator Biosynthesis in the Immune System.

Lipid mediators are important regulators in inflammatory responses, and their biosynthetic pathways are targeted by commonly used anti-inflammatory drugs. Switching from pro-inflammatory lipid mediators (PIMs) to specialized pro-resolving (SPMs) is a critical step toward acute inflammation resolution and preventing chronic inflammation. Although the biosynthetic pathways and enzymes for PIMs and SPMs have now been largely identified, the actual transcriptional profiles underlying the immune cell type-specific transcriptional profiles of these mediators are still unknown. Using the Atlas of Inflammation Resolution, we created a large network of gene regulatory interactions linked to the biosynthesis of SPMs and PIMs. By mapping single-cell sequencing data, we identified cell type-specific gene regulatory networks of the lipid mediator biosynthesis. Using machine learning approaches combined with network features, we identified cell clusters of similar transcriptional regulation and demonstrated how specific immune cell activation affects PIM and SPM profiles. We found substantial differences in regulatory networks in related cells, accounting for network-based preprocessing in functional single-cell analyses. Our results not only provide further insight into the gene regulation of lipid mediators in the immune response but also shed light on the contribution of selected cell types in their biosynthesis.

COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms.

We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.

The Response and Tolerability of a Novel Cold Atmospheric Plasma Wound Dressing for the Healing of Split Skin Graft Donor Sites: A Controlled Pilot Study.

INTRODUCTION: Cold atmospheric plasma (CAP) has positive effects on wound healing and antimicrobial properties. However, an ongoing challenge is the development of specific modes of application for different clinical indications. OBJECTIVES: We investigated in a prospective pilot study the response and tolerability of a newly developed CAP wound dressing for the acute healing of split skin graft donor sites compared to conventional therapy. METHODS: We applied both treatments to each patient (n = 10) for 7 days and measured 4 parameters of wound healing every other day (i.e., 1,440 measurements) using a hyperspectral imaging camera. Additionally, we evaluated the clinical appearance and pain levels reported by the patients. RESULTS: The CAP wound dressing was superior to the control (p < 0.001) in the improvement of 3 wound parameters, that is, deep tissue oxygen saturation, hemoglobin distribution, and tissue water distribution. CAP was well tolerated, and pain levels were lower in CAP-treated wound areas. CONCLUSION: CAP wound dressing is a promising new tool for acute wound healing.

NaviCenta - The disease map for placental research.

The placenta remains the key organ to pregnancy complications, such as preeclampsia, contrarily the pathophysiology underlying the placental dysfunctions remains elusive. Here, we present our Disease Map "NaviCenta", which is an online resource based on the interactions between tissues, cellular compartments, and molecules that mediate disease-related processes in the placenta. We built cellular and molecular interaction networks based upon manual curation and annotation of publicly available information in the scientific literature, pathways resources, and Omics data. NaviCenta (Navigate the plaCenta) serves as an open access, spatio-temporal, multi-scale knowledge base, and analytical tool for enhanced interpretation and hypothesis testing on various placental disease phenotypes.

Network analyses reveal new insights into the effect of multicomponent Tr14 compared to single-component diclofenac in an acute inflammation model.

BACKGROUND: Modifying the acute inflammatory response has wide clinical benefits. Current options include non-steroidal anti-inflammatory drugs (NSAIDs) and therapies that may resolve inflammation. Acute inflammation involves multiple cell types and various processes. We, therefore, investigated whether an immunomodulatory drug that acts simultaneously at multiple sites shows greater potential to resolve acute inflammation more effectively and with fewer side effects than a common anti-inflammatory drug developed as a small molecule for a single target. In this work, we used time-series gene expression profiles from a wound healing mouse model to compare the effects of Traumeel (Tr14), a multicomponent natural product, to diclofenac, a single component NSAID on inflammation resolution. RESULTS: We advance previous studies by mapping the data onto the "Atlas of Inflammation Resolution", followed by in silico simulations and network analysis. We found that Tr14 acts primarily on the late phase of acute inflammation (during resolution) compared to diclofenac, which suppresses acute inflammation immediately after injury. CONCLUSIONS: Our results provide new insights how network pharmacology of multicomponent drugs may support inflammation resolution in inflammatory conditions.

Network- and enrichment-based inference of phenotypes and targets from large-scale disease maps.

Complex diseases are inherently multifaceted, and the associated data are often heterogeneous, making linking interactions across genes, metabolites, RNA, proteins, cellular functions, and clinically relevant phenotypes a high-priority challenge. Disease maps have emerged as knowledge bases that capture molecular interactions, disease-related processes, and disease phenotypes with standardized representations in large-scale molecular interaction maps. Various tools are available for disease map analysis, but an intuitive solution to perform in silico experiments on the maps in a wide range of contexts and analyze high-dimensional data is currently missing. To this end, we introduce a two-dimensional enrichment analysis (2DEA) approach to infer downstream and upstream elements through the statistical association of network topology parameters and fold changes from molecular perturbations. We implemented our approach in a plugin suite for the MINERVA platform, providing an environment where experimental data can be mapped onto a disease map and predict potential regulatory interactions through an intuitive graphical user interface. We show several workflows using this approach and analyze two RNA-seq datasets in the Atlas of Inflammation Resolution (AIR) to identify enriched downstream processes and upstream transcription factors. Our work improves the usability of disease maps and increases their functionality by facilitating multi-omics data integration and exploration.

In silico investigation of molecular networks linking gastrointestinal diseases, malnutrition, and sarcopenia.

Malnutrition (MN) is a common primary or secondary complication in gastrointestinal diseases. The patient's nutritional status also influences muscle mass and function, which can be impaired up to the degree of sarcopenia. The molecular interactions in diseases leading to sarcopenia are complex and multifaceted, affecting muscle physiology, the intestine (nutrition), and the liver at different levels. Although extensive knowledge of individual molecular factors is available, their regulatory interplay is not yet fully understood. A comprehensive overall picture of pathological mechanisms and resulting phenotypes is lacking. In silico approaches that convert existing knowledge into computationally readable formats can help unravel mechanisms, underlying such complex molecular processes. From public literature, we manually compiled experimental evidence for molecular interactions involved in the development of sarcopenia into a knowledge base, referred to as the Sarcopenia Map. We integrated two diseases, namely liver cirrhosis (LC), and intestinal dysfunction, by considering their effects on nutrition and blood secretome. We demonstrate the performance of our model by successfully simulating the impact of changing dietary frequency, glycogen storage capacity, and disease severity on the carbohydrate and muscle systems. We present the Sarcopenia Map as a publicly available, open-source, and interactive online resource, that links gastrointestinal diseases, MN, and sarcopenia. The map provides tools that allow users to explore the information on the map and perform in silico simulations.

WITHDRAWN: The Atlas of Inflammation Resolution (AIR).

The Publisher regrets that this article is an accidental duplication of an article that has already been published, https://doi.org/10.1016/j.mam.2020.100894. The duplicate article has therefore been withdrawn. The full Elsevier Policy on Article Withdrawal can be found at https://www.elsevier.com/about/our-business/policies/article-withdrawal.

The Atlas of Inflammation Resolution (AIR).

Acute inflammation is a protective reaction by the immune system in response to invading pathogens or tissue damage. Ideally, the response should be localized, self-limited, and returning to homeostasis. If not resolved, acute inflammation can result in organ pathologies leading to chronic inflammatory phenotypes. Acute inflammation and inflammation resolution are complex coordinated processes, involving a number of cell types, interacting in space and time. The biomolecular complexity and the fact that several biomedical fields are involved, make a multi- and interdisciplinary approach necessary. The Atlas of Inflammation Resolution (AIR) is a web-based resource capturing an essential part of the state-of-the-art in acute inflammation and inflammation resolution research. The AIR provides an interface for users to search thousands of interactions, arranged in inter-connected multi-layers of process diagrams, covering a wide range of clinically relevant phenotypes. By mapping experimental data onto the AIR, it can be used to elucidate drug action as well as molecular mechanisms underlying different disease phenotypes. For the visualization and exploration of information, the AIR uses the Minerva platform, which is a well-established tool for the presentation of disease maps. The molecular details of the AIR are encoded using international standards. The AIR was created as a freely accessible resource, supporting research and education in the fields of acute inflammation and inflammation resolution. The AIR connects research communities, facilitates clinical decision making, and supports research scientists in the formulation and validation of hypotheses. The AIR is accessible through https://air.bio.informatik.uni-rostock.de.

(Re-)programming of subtype specific cardiomyocytes.

Adult cardiomyocytes (CMs) possess a highly restricted intrinsic regenerative potential - a major barrier to the effective treatment of a range of chronic degenerative cardiac disorders characterized by cellular loss and/or irreversible dysfunction and which underlies the majority of deaths in developed countries. Both stem cell programming and direct cell reprogramming hold promise as novel, potentially curative approaches to address this therapeutic challenge. The advent of induced pluripotent stem cells (iPSCs) has introduced a second pluripotent stem cell source besides embryonic stem cells (ESCs), enabling even autologous cardiomyocyte production. In addition, the recent achievement of directly reprogramming somatic cells into cardiomyocytes is likely to become of great importance. In either case, different clinical scenarios will require the generation of highly pure, specific cardiac cellular-subtypes. In this review, we discuss these themes as related to the cardiovascular stem cell and programming field, including a focus on the emergent topic of pacemaker cell generation for the development of biological pacemakers and in vitro drug testing.