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Systems Bioinformatics: increasing precision of computational diagnostics and therapeutics through network-based approaches.

ABSTRACT: Systems Bioinformatics is a relatively new approach, which lies in the intersection of systems biology and classical bioinformatics. It focuses on integrating information across different levels using a bottom-up approach as in systems biology with a data-driven top-down approach as in bioinformatics. The advent of omics technologies has provided the stepping-stone for the emergence of Systems Bioinformatics. These technologies provide a spectrum of information ranging from genomics, transcriptomics and proteomics to epigenomics, pharmacogenomics, metagenomics and metabolomics. Systems Bioinformatics is the framework in which systems approaches are applied to such data, setting the level of resolution as well as the boundary of the system of interest and studying the emerging properties of the system as a whole rather than the sum of the properties derived from the system's individual components. A key approach in Systems Bioinformatics is the construction of multiple networks representing each level of the omics spectrum and their integration in a layered network that exchanges information within and between layers. Here, we provide evidence on how Systems Bioinformatics enhances computational therapeutics and diagnostics, hence paving the way to precision medicine. The aim of this review is to familiarize the reader with the emerging field of Systems Bioinformatics and to provide a comprehensive overview of its current state-of-the-art methods and technologies. Moreover, we provide examples of success stories and case studies that utilize such methods and tools to significantly advance research in the fields of systems biology and systems medicine.

SUBMITTER: Oulas A

PROVIDER: S-EPMC6585387 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Systems Bioinformatics: increasing precision of computational diagnostics and therapeutics through network-based approaches.

Oulas Anastasis A Minadakis George G Zachariou Margarita M Sokratous Kleitos K Bourdakou Marilena M MM Spyrou George M GM

Briefings in bioinformatics 20190501 3

Systems Bioinformatics is a relatively new approach, which lies in the intersection of systems biology and classical bioinformatics. It focuses on integrating information across different levels using a bottom-up approach as in systems biology with a data-driven top-down approach as in bioinformatics. The advent of omics technologies has provided the stepping-stone for the emergence of Systems Bioinformatics. These technologies provide a spectrum of information ranging from genomics, transcripto ...[more]

PMID: 29186305

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Project description:The novel coronavirus pneumonia (COVID-19) is a highly infectious acute respiratory disease caused by Severe Acute Respiratory Syndrome-Related Coronavirus (SARS-CoV-2) (Prec Clin Med 2020;3:9–13, Lancet 2020;395:497–506, N. Engl J Med 2020a;382:1199–207, Nature 2020;579:270–3). SARS-CoV-2 surveillance is essential to controlling widespread transmission. However, there are several challenges associated with the diagnostic of the COVID-19 during the current outbreak (Liu and Li (2019), Nature 2020;579:265–9, N. Engl J Med 2020;382:727–33). Firstly, the high number of cases overwhelms diagnostic test capacity and proposes the need for a rapid solution for sample processing (Science 2018;360:444–8). Secondly, SARS-CoV-2 is closely related to other important coronavirus species and subspecies, so detection assays can give false-positive results if they are not efficiently specific to SARS-CoV-2. Thirdly, patients with suspected SARS-CoV-2 infection sometimes have a different respiratory viral infection or co-infections with SARS-CoV-2 and other respiratory viruses (MedRxiv 2020a;1–18). Confirmation of the COVID-19 is performed mainly by virus isolation followed by RT-PCR and sequencing (N. Engl J Med 2020;382:727–33, MedRxiv 2020a, Turkish J Biol 2020;44:192–202). The emergence and outbreak of the novel coronavirus highlighted the urgent need for new therapeutic technologies that are fast, precise, stable, easy to manufacture, and target-specific for surveillance and treatment. Molecular biology tools that include gene-editing approaches such as CRISPR-Cas12/13-based SHERLOCK, DETECTR, CARVER and PAC-MAN, antisense oligonucleotides, antisense peptide nucleic acids, ribozymes, aptamers, and RNAi silencing approaches produced with cutting-edge scientific advances compared to conventional diagnostic or treatment methods could be vital in COVID-19 and other future outbreaks. Thus, in this review, we will discuss potent the molecular biology approaches that can revolutionize diagnostic of viral infections and therapies to fight COVID-19 in a highly specific, stable, and efficient way. Highlights SARS-CoV-2 is an RNA virus that could be targeted and diagnosed with novel CRISPR approaches. ASO therapy targeting transcript encoding a viral protein or genomic RNA itself could be developed as a response to the SARS-CoV-2 pandemic. Antisense peptide nucleic acids, which have significant potential as antiviral agents, are important therapeutic candidates that can target SARS-CoV-2 RNA with high hybridization affinity and stability. Although ribozyme and aptamer technologies are relatively older than other gene-editing technologies, they are still strong candidates in the fight against the COVID-19 pandemic due to their high specificities and low toxicities, besides that aptamers are highly reproducible. siRNAs that target structural or non-structural proteins of SARS-CoV-2, could inhibit assembly and replication of SARS-CoV-2.

Project description:BackgroundType 1 diabetes mellitus (T1DM), an autoimmune disease with a genetic tendency, has an increasing prevalence. Long non-coding RNA (lncRNA) and circular RNA (circRNA) are receiving increasing attention in disease pathogenesis. However, their roles in T1DM are poorly understood. The present study aimed at identifying signature lncRNAs and circRNAs and investigating their roles in T1DM using the competing endogenous RNA (ceRNA) network analysis.MethodsThe T1DM expression profile was downloaded from Gene Expression Omnibus (GEO) database to identify the differentially expressed circRNAs, lncRNAs, and mRNAs. The biological functions of these differentially expressed circRNAs, lncRNAs, and mRNAs were analyzed by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Targeting relationships of circRNA-miRNA, lncRNA-miRNA, and miRNA-mRNA were predicted, and the circRNA-lncRNA-miRNA-mRNA ceRNA regulatory network was established. Finally, qRT-PCR was applied to identify the effect of hsa_circ_0002202 inhibition on the IFN-I induced macrophage inflammation.ResultsA total of 178 circRNAs, 404 lncRNAs, and 73 mRNAs were identified to be abnormally expressed in T1DM samples. Functional enrichment analysis results indicated that the differentially expressed genes were mainly enriched in extracellular matrix components and macrophage activation. CeRNA regulatory network showed that circRNAs and lncRNAs regulate mRNAs through integrate multiple miRNAs. In addition, in vitro experiments showed that hsa_circ_0002202 inhibition suppressed the type I interferon (IFN-I)-induced macrophage inflammation.ConclusionIn the present study, the circRNA-lncRNA-miRNA-mRNA ceRNA regulatory network in T1DM was established for the first time. We also found that hsa_circ_0002202 inhibition suppressed the IFN-I-induced macrophage inflammation. Our study may lay a foundation for future studies on the ceRNA regulatory network in T1DM.

Dataset Information

Systems Bioinformatics: increasing precision of computational diagnostics and therapeutics through network-based approaches.

Publications

Systems Bioinformatics: increasing precision of computational diagnostics and therapeutics through network-based approaches.

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