Metabolic alterations induced by attenuated Zika virus in glioblastoma cells

Unraveling the Metabolic Alterations Induced by Zika Infection in Prostate Epithelial (PNT1a) and Adenocarcinoma (PC-3) Cell Lines

The outbreak of Zika virus infection in 2016 led to the identification of its presence in several types of biofluids, including semen. Later discoveries associated Zika infection with sexual transmission and persistent replication in cells of the male reproductive tract. Prostate epithelial and carcinoma cells are favorable to virus replication, with studies pointing to transcriptomics alterations of immune and inflammation genes upon persistence. However, metabolome alterations promoted by the Zika virus in prostate cells are unknown. Given its chronic effects and oncolytic potential, we aim to investigate the metabolic alterations induced by the Zika virus in prostate epithelial (PNT1a) and adenocarcinoma (PC-3) cells using an untargeted metabolomics approach and high-resolution mass spectrometry. PNT1a cells were viable up to 15 days post ZIKV infection, in contrast to its antiproliferative effect in the PC-3 cell lineage. Remarkable alterations in the PNT1a cell metabolism were observed upon infection, especially regarding glycerolipids, fatty acids, and acylcarnitines, which could be related to viral cellular resource exploitation, in addition to the over-time increase in oxidative stress metabolites associated with carcinogenesis. The upregulation of FA20:5 at 5 dpi in PC-3 cells corroborates the antiproliferative effect observed since this metabolite was previously reported to induce PC-3 cell death. Overall, Zika virus promotes extensive lipid alterations on both PNT1a and PC-3 cells, promoting different outcomes based on the cellular metabolic state.

Metabolomic Profiling of Plasma Reveals Differential Disease Severity Markers in COVID-19 Patients

The severity, disabilities, and lethality caused by the coronavirus 2019 (COVID-19) disease have dumbfounded the entire world on an unprecedented scale. The multifactorial aspect of the infection has generated interest in understanding the clinical history of COVID-19, particularly the classification of severity and early prediction on prognosis. Metabolomics is a powerful tool for identifying metabolite signatures when profiling parasitic, metabolic, and microbial diseases. This study undertook a metabolomic approach to identify potential metabolic signatures to discriminate severe COVID-19 from non-severe COVID-19. The secondary aim was to determine whether the clinical and laboratory data from the severe and non-severe COVID-19 patients were compatible with the metabolomic findings. Metabolomic analysis of samples revealed that 43 metabolites from 9 classes indicated COVID-19 severity: 29 metabolites for non-severe and 14 metabolites for severe disease. The metabolites from porphyrin and purine pathways were significantly elevated in the severe disease group, suggesting that they could be potential prognostic biomarkers. Elevated levels of the cholesteryl ester CE (18:3) in non-severe patients matched the significantly different blood cholesterol components (total cholesterol and HDL, both p < 0.001) that were detected. Pathway analysis identified 8 metabolomic pathways associated with the 43 discriminating metabolites. Metabolomic pathway analysis revealed that COVID-19 affected glycerophospholipid and porphyrin metabolism but significantly affected the glycerophospholipid and linoleic acid metabolism pathways (p = 0.025 and p = 0.035, respectively). Our results indicate that these metabolomics-based markers could have prognostic and diagnostic potential when managing and understanding the evolution of COVID-19.

Cytopathic Effect (CPE )-Based Drug Screening Assay for SARS-CoV-2

Identification of an effective antiviral for the treatment of COVID-19 is considered one of the holy grails in the bid to end the pandemic. However, the novelty of SARS-CoV-2, along with the little knowledge available about its infection characteristics at the beginning of this pandemic, challenges the scientific world on how one may be able to promptly identify promising drug candidates from a myriad of compound libraries. Here, we describe a cytopathic effect (CPE)-based drug screening assay for SARS-CoV-2 which allows for rapid assessment of drug compound libraries through pre- or posttreatment drug screening procedures and evaluation using a light microscope. By comparing the virus-induced CPE of the drug-treated cells against the vehicle and drug controls, potent drug candidates can be quickly identified for further downstream studies.

Novel modulators of p53-signaling encoded by unknown genes of emerging viruses

The p53 transcription factor plays a key role both in cancer and in the cell-intrinsic response to infections. The ORFEOME project hypothesized that novel p53-virus interactions reside in hitherto uncharacterized, unknown, or hypothetical open reading frames (orfs) of human viruses. Hence, 172 orfs of unknown function from the emerging viruses SARS-Coronavirus, MERS-Coronavirus, influenza, Ebola, Zika (ZIKV), Chikungunya and Kaposi Sarcoma-associated herpesvirus (KSHV) were de novo synthesized, validated and tested in a functional screen of p53 signaling. This screen revealed novel mechanisms of p53 virus interactions and two viral proteins KSHV orf10 and ZIKV NS2A binding to p53. Originally identified as the target of small DNA tumor viruses, these experiments reinforce the notion that all viruses, including RNA viruses, interfere with p53 functions. These results validate this resource for analogous systems biology approaches to identify functional properties of uncharacterized viral proteins, long non-coding RNAs and micro RNAs.

New viruses are constantly emerging. The ORFEOME project was based on the hypothesis that every virus, regardless of its molecular makeup and biology should encode functions that intersect the p53 signaling network, since p53 guards the cell from genomic insults, of which depositing a foreign, viral nucleic acid is one. The result of the ORFEOME screen of proteins without any known function, of predicted open reading frames and of suspected non-coding RNAs is the identification of two viral proteins that interact with p53. The first one, orf10, is encoded by Kaposi Sarcoma-associated herpesvirus and the second one, NS2A, is encoded by the Zika virus.

Molecular signatures associated with prostate cancer cell line (PC-3) exposure to inactivated Zika virus

The recent outbreak of Zika virus (ZIKV) infection associated with microcephaly cases has elicited much research on the mechanisms involved in ZIKV-host cell interactions. It has been described that Zika virus impairs cell growth, raising a hypothesis about its oncolytic potential against cancer cells. ZIKV tumor cell growth inhibition was later confirmed for glioblastoma. It was also demonstrated that an inactivated ZIKV prototype (ZVp) based on bacterial outer membrane vesicles has antiproliferative activity upon other cancer cell lines, such as PC-3 prostate cancer cell. This study aims at understanding the pathways that might be involved with the antiproliferative effect of Zika virus against prostate cancer cells. A metabolomic approach based on high-resolution mass spectrometry analysis led to the identification of 21 statistically relevant markers of PC-3 cells treated with ZVp. The markers were associated with metabolic alterations that trigger lipid remodeling, endoplasmic reticulum stress, inflammatory mediators, as well as disrupted porphyrin and folate metabolism. These findings highlight molecular signatures of ZVp-induced response that may be involved on cellular pathways triggered by its antiproliferative effect. To our knowledge, this is the first reported metabolomic assessment of ZIKV effect on prostate cancer cells, a promising topic for further research.