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Acute kidney injury (AKI) has been noticed after both COVID-19 vaccination and infection, affecting risk-benefit evaluations and vaccine hesitancy. We conducted a large-scale N3C cohort study to compare AKI incidence following COVID-19 vaccination and infection. Participants from December 2020 to August 2023 were divided into two groups based on their initially observed COVID-19 antigen exposure: COVID-19 vaccination group (n = 2,953,219) and COVID-19 infection group (n = 3,616,802). AKI was defined by diagnostic codes and serum creatinine changes within a 30 day follow-up window after exposure. The absolute risk of AKI was 0.66% in the vaccination group versus 4.88% in the infection group. After adjusting for various confounders, COVID-19 infection was associated with a significantly higher risk of AKI than COVID-19 vaccination (aHR = 10.31, P < 0.001). Our study reveals that COVID-19 vaccination is associated with a significant lower AKI risk compared to COVID-19 infection. [ABSTRACT FROM AUTHOR]

Bacterial integrative and conjugative elements (ICEs) are highly modular mobile genetic elements critical to the horizontal transfer of antibiotic resistance and virulence factor genes. To better understand and analyze the ongoing increase of ICEs, we developed an Integrative and Conjugative Element Ontology (ICEO) to represent the gene components, functional modules, and other information of experimentally verified ICEs. ICEO is aligned with the upper-level Basic Formal Ontology and reuses existing reliable ontologies. There are 31,081 terms, including 26,814 classes from 14 ontologies and 4128 ICEO-specific classes, representing the information of 271 known experimentally verified ICEs from 235 bacterial strains in ICEO currently and 311 predicted ICEs of 272 completely sequenced Klebsiella pneumoniae strains. Three ICEO use cases were illustrated to investigate complex joins of ICEs and their harboring antibiotic resistance or virulence factor genes by using SPARQL or DL query. ICEO has been approved as an Open Biomedical Ontology library ontology. It may be dedicated to facilitating systematical ICE knowledge representation, integration, and computer-assisted queries. [ABSTRACT FROM AUTHOR]

The presence of SARS-CoV-2 mutants, including the emerging variant B.1.1.7, has raised great concerns in terms of pathogenesis, transmission, and immune escape. Characterizing SARS-CoV-2 mutations, evolution, and effects on infectivity and pathogenicity is crucial to the design of antibody therapies and surveillance strategies. Here, we analyzed 454,443 SARS-CoV-2 spike genes/proteins and 14,427 whole-genome sequences. We demonstrated that the early variant B.1.1.7 may not have evolved spontaneously in the United Kingdom or within human populations. Our extensive analyses suggested that Canidae, Mustelidae or Felidae, especially the Canidae family (for example, dog) could be a possible host of the direct progenitor of variant B.1.1.7. An alternative hypothesis is that the variant was simply yet to be sampled. Notably, the SARS-CoV-2 whole-genome represents a large number of potential co-mutations. In addition, we used an experimental SARS-CoV-2 reporter replicon system to introduce the dominant co-mutations NSP12_c14408t, 5′UTR_c241t, and NSP3_c3037t into the viral genome, and to monitor the effect of the mutations on viral replication. Our experimental results demonstrated that the co-mutations significantly attenuated the viral replication. The study provides valuable clues for discovering the transmission chains of variant B.1.1.7 and understanding the evolutionary process of SARS-CoV-2. [ABSTRACT FROM AUTHOR]

Research on drugs against SARS-CoV-2 (cause of COVID-19) has been one of the major world concerns at present. There have been abundant research data and findings in this field. The interference of drugs on gene expression in cell lines, drug-target, protein-virus receptor networks, and immune cell infiltration of the host may provide useful information for anti-SARS-CoV-2 drug research. To simplify the complex bioinformatics analysis and facilitate the evaluation of the latest research data, we developed OmiczViz (http://medcode.link/omicsviz), a web tool that has integrated drug-cell line interference data, virus-host protein–protein interactions, and drug-target interactions. To demonstrate the usages of OmiczViz, we analyzed the gene expression data from cell lines treated with chloroquine and ruxolitinib, the drug-target protein networks of 48 anti-coronavirus drugs and drugs bound with ACE2, and the profiles of immune cell infiltration between different COVID-19 patient groups. Our research shows that chloroquine had a regulatory role of the immune response in renal cell line but not in lung cell line. The anti-coronavirus drug-target network analysis suggested that antihistamine of promethaziney and dietary supplement of Zinc might be beneficial when used jointly with antiviral drugs. The immune infiltration analysis indicated that both the COVID-19 patients admitted to the ICU and the elderly with infection showed immune exhaustion status, yet with different molecular mechanisms. The interactive graphic interface of OmiczViz also makes it easier to analyze newly discovered and user-uploaded data, leading to an in-depth understanding of existing findings and an expansion of existing knowledge of SARS-CoV-2. Collectively, OmicsViz is web program that promotes the research on medical agents against SARS-CoV-2 and supports the evaluation of the latest research findings. [ABSTRACT FROM AUTHOR]

Our systematic literature collection and annotation identified 106 chemical drugs and 31 antibodies effective against the infection of at least one human coronavirus (including SARS-CoV, SAR-CoV-2, and MERS-CoV) in vitro or in vivo in an experimental or clinical setting. A total of 163 drug protein targets were identified, and 125 biological processes involving the drug targets were significantly enriched based on a Gene Ontology (GO) enrichment analysis. The Coronavirus Infectious Disease Ontology (CIDO) was used as an ontological platform to represent the anti-coronaviral drugs, chemical compounds, drug targets, biological processes, viruses, and the relations among these entities. In addition to new term generation, CIDO also adopted various terms from existing ontologies and developed new relations and axioms to semantically represent our annotated knowledge. The CIDO knowledgebase was systematically analyzed for scientific insights. To support rational drug design, a "Host-coronavirus interaction (HCI) checkpoint cocktail" strategy was proposed to interrupt the important checkpoints in the dynamic HCI network, and ontologies would greatly support the design process with interoperable knowledge representation and reasoning. [ABSTRACT FROM AUTHOR]

The Coronavirus Infectious Disease Ontology (CIDO) is a community-based ontology that supports coronavirus disease knowledge and data standardization, integration, sharing, and analysis. [ABSTRACT FROM AUTHOR]

Introduction: A translational bioinformatics challenge exists in connecting population and individual clinical phenotypes in various formats to biological mechanisms. The Medical Dictionary for Regulatory Activities (MedDRA(®)) is the default dictionary for adverse event (AE) reporting in the US Food and Drug Administration Adverse Event Reporting System (FAERS). The ontology of adverse events (OAE) represents AEs as pathological processes occurring after drug exposures.Objectives: The aim of this work was to establish a semantic framework to link biological mechanisms to phenotypes of AEs by combining OAE with MedDRA(®) in FAERS data analysis. We investigated the AEs associated with tyrosine kinase inhibitors (TKIs) and monoclonal antibodies (mAbs) targeting tyrosine kinases. The five selected TKIs/mAbs (i.e., dasatinib, imatinib, lapatinib, cetuximab, and trastuzumab) are known to induce impaired ventricular function (non-QT) cardiotoxicity.Results: Statistical analysis of FAERS data identified 1053 distinct MedDRA(®) terms significantly associated with TKIs/mAbs, where 884 did not have corresponding OAE terms. We manually annotated these terms, added them to OAE by the standard OAE development strategy, and mapped them to MedDRA(®). The data integration to provide insights into molecular mechanisms of drug-associated AEs was performed by including linkages in OAE for all related AE terms to MedDRA(®) and the existing ontologies, including the human phenotype ontology (HP), Uber anatomy ontology (UBERON), and gene ontology (GO). Sixteen AEs were shared by all five TKIs/mAbs, and each of 17 cardiotoxicity AEs was associated with at least one TKI/mAb. As an example, we analyzed "cardiac failure" using the relations established in OAE with other ontologies and demonstrated that one of the biological processes associated with cardiac failure maps to the genes associated with heart contraction.Conclusion: By expanding the existing OAE ontological design, our TKI use case demonstrated that the combination of OAE and MedDRA(®) provides a semantic framework to link clinical phenotypes of adverse drug events to biological mechanisms. [ABSTRACT FROM AUTHOR]

The response regulator OtpR is critical for the growth, morphology and virulence of Brucella melitensis. Compared to its wild type strain 16 M, B. melitensis 16 MΔotpR mutant has decreased tolerance to acid stress. To analyze the genes regulated by OtpR under acid stress, we performed RNA-seq whole transcriptome analysis of 16 MΔotpR and 16 M. In total, 501 differentially expressed genes were identified, including 390 down-regulated and 111 up-regulated genes. Among these genes, 209 were associated with bacterial metabolism, including 54 genes involving carbohydrate metabolism, 13 genes associated with nitrogen metabolism, and seven genes associated with iron metabolism. The 16 MΔotpR also decreased capacity to utilize different carbon sources and to tolerate iron limitation in culture experiments. Notably, OtpR regulated many Brucella virulence factors essential for B. melitensis intracellular survival. For instance, the virB operon encoding type IV secretion system was significantly down-regulated, and 36 known transcriptional regulators (e.g., vjbR and blxR) were differentially expressed in 16 MΔotpR. Selected RNA-seq results were experimentally confirmed by RT-PCR and RT-qPCR. Overall, these results deciphered differential phenomena associated with virulence, environmental stresses and cell morphology in 16 MΔotpR and 16 M, which provided important information for understanding the detailed OtpR-regulated interaction networks and Brucella pathogenesis. [ABSTRACT FROM AUTHOR]