Graph databases in systems biology: a systematic review.

Graph databases are becoming increasingly popular across scientific disciplines, being highly suitable for storing and connecting complex heterogeneous data. In systems biology, they are used as a backend solution for biological data repositories, ontologies, networks, pathways, and knowledge graph databases. In this review, we analyse all publications using or mentioning graph databases retrieved from PubMed and PubMed Central full-text search, focusing on the top 16 available graph databases, Publications are categorized according to their domain and application, focusing on pathway and network biology and relevant ontologies and tools.

MeDaX: A Knowledge Graph on FHIR.

In Germany, the standard format for exchange of clinical care data for research is HL7 FHIR. Graph databases (GDBs), well suited for integrating complex and heterogeneous data from diverse sources, are currently gaining traction in the medical field. They provide a versatile framework for data analysis which is generally challenging for raw FHIR-formatted data.

[Interoperability Working Group: core dataset and information systems for data integration and data exchange in the Medical Informatics Initiative].

The interoperability Working Group of the Medical Informatics Initiative (MII) is the platform for the coordination of overarching procedures, data structures, and interfaces between the data integration centers (DIC) of the university hospitals and national and international interoperability committees. The goal is the joint content-related and technical design of a distributed infrastructure for the secondary use of healthcare data that can be used via the Research Data Portal for Health. Important general conditions are data privacy and IT security for the use of health data in biomedical research.

The MeDaX Knowledge Graph Prototype.

Data sharing is sustainable for several reasons, including minimising economical and human costs or maximising knowledge gain. Still, reuse of biomedical (research) data is often hampered by the diverse technical, juridical, and scientific requirements for biomedical data handling and specifically sharing. We are building a toolbox for automated generation of knowledge graphs (KGs) from diverse sources, for data enrichment, and for data analysis.

Control of COVID-19 Outbreaks under Stochastic Community Dynamics, Bimodality, or Limited Vaccination.

Reaching population immunity against COVID-19 is proving difficult even in countries with high vaccination levels. Thus, it is critical to identify limits of control and effective measures against future outbreaks. The effects of nonpharmaceutical interventions (NPIs) and vaccination strategies are analyzed with a detailed community-specific agent-based model (ABM).

Loss of hepatic Mboat7 leads to liver fibrosis.

Objective: The rs641738C>T variant located near the membrane-bound O-acyltransferase domain containing 7 (MBOAT7) locus is associated with fibrosis in liver diseases, including non-alcoholic fatty liver disease (NAFLD), alcohol-related liver disease, hepatitis B and C. We aim to understand the mechanism by which the rs641738C>T variant contributes to pathogenesis of NAFLD.

Design: Mice with hepatocyte-specific deletion of MBOAT7 (Mboat7) were generated and livers were characterised by histology, flow cytometry, qPCR, RNA sequencing and lipidomics.

Publisher Correction: MEMOTE for standardized genome-scale metabolic model testing.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Monitoring cytochrome P450 activity in living hepatocytes by chromogenic substrates in response to drug treatment or during cell maturation.

The metabolic activity of hepatocytes is a central prerequisite for drug activity and a key element in drug-drug interaction. This central role in metabolism largely depends on the activity of the cytochrome P450 (CYP450) enzyme family, which is not only dependent on liver cell maturation but is also controlled in response to drug and chemical exposure. Here, we report the use of VividDye fluorogenic CYP450 substrates to directly measure and continuously monitor metabolic activity in living hepatocytes.

Integration of multi-omics data of a genome-reduced bacterium: Prevalence of post-transcriptional regulation and its correlation with protein abundances.

We developed a comprehensive resource for the genome-reduced bacterium Mycoplasma pneumoniae comprising 1748 consistently generated '-omics' data sets, and used it to quantify the power of antisense non-coding RNAs (ncRNAs), lysine acetylation, and protein phosphorylation in predicting protein abundance (11%, 24% and 8%, respectively). These factors taken together are four times more predictive of the proteome abundance than of mRNA abundance. In bacteria, post-translational modifications (PTMs) and ncRNA transcription were both found to increase with decreasing genomic GC-content and genome size.

Defining a minimal cell: essentiality of small ORFs and ncRNAs in a genome-reduced bacterium.

Identifying all essential genomic components is critical for the assembly of minimal artificial life. In the genome-reduced bacterium Mycoplasma pneumoniae, we found that small ORFs (smORFs; < 100 residues), accounting for 10% of all ORFs, are the most frequently essential genomic components (53%), followed by conventional ORFs (49%). Essentiality of smORFs may be explained by their function as members of protein and/or DNA/RNA complexes.

MyMpn: a database for the systems biology model organism Mycoplasma pneumoniae.

MyMpn (http://mympn.crg.eu) is an online resource devoted to studying the human pathogen Mycoplasma pneumoniae, a minimal bacterium causing lower respiratory tract infections.

Bridging the gaps in systems biology.

Systems biology aims at creating mathematical models, i.e., computational reconstructions of biological systems and processes that will result in a new level of understanding-the elucidation of the basic and presumably conserved "design" and "engineering" principles of biomolecular systems.

Large-scale metabolome analysis and quantitative integration with genomics and proteomics data in Mycoplasma pneumoniae.

Systems metabolomics, the identification and quantification of cellular metabolites and their integration with genomics and proteomics data, promises valuable functional insights into cellular biology. However, technical constraints, sample complexity issues and the lack of suitable complementary quantitative data sets prevented accomplishing such studies in the past. Here, we present an integrative metabolomics study of the genome-reduced bacterium Mycoplasma pneumoniae.

Dissecting the energy metabolism in Mycoplasma pneumoniae through genome-scale metabolic modeling.

Mycoplasma pneumoniae, a threatening pathogen with a minimal genome, is a model organism for bacterial systems biology for which substantial experimental information is available. With the goal of understanding the complex interactions underlying its metabolism, we analyzed and characterized the metabolic network of M. pneumoniae in great detail, integrating data from different omics analyses under a range of conditions into a constraint-based model backbone.

Impact of genome reduction on bacterial metabolism and its regulation.

To understand basic principles of bacterial metabolism organization and regulation, but also the impact of genome size, we systematically studied one of the smallest bacteria, Mycoplasma pneumoniae. A manually curated metabolic network of 189 reactions catalyzed by 129 enzymes allowed the design of a defined, minimal medium with 19 essential nutrients. More than 1300 growth curves were recorded in the presence of various nutrient concentrations.