DNA viruses and cancer: insights from evolutionary biology

The human adenovirus PI3K-Akt activator E4orf1 is targeted by the tumor suppressor p53

Human adenoviruses (HAdV) are classified as DNA tumor viruses due to their potential to mediate oncogenic transformation in non-permissive mammalian cells and certain human stem cells. To achieve transformation, the viral early proteins of the E1 and E4 regions must block apoptosis and activate proliferation: the former predominantly through modulating the cellular tumor suppressor p53 and the latter by activating cellular pro-survival and pro-metabolism protein cascades, such as the phosphoinositide 3-kinase (PI3K-Akt) pathway, which is activated by HAdV E4orf1. Focusing on HAdV-C5, we show that E4orf1 is necessary and sufficient to stimulate Akt activation through phosphorylation in H1299 cells, which is not only hindered but repressed during HAdV-C5 infection with a loss of E4orf1 function in p53-positive A549 cells. Contrary to other research, E4orf1 localized not only in the common, cytoplasmic PI3K-Akt-containing compartment, but also in distinct nuclear aggregates. We identified a novel inhibitory mechanism, where p53 selectively targeted E4orf1 to destabilize it, also stalling E4orf1-dependent Akt phosphorylation. Co-IP and immunofluorescence studies showed that p53 and E4orf1 interact, and since p53 is bound by the HAdV-C5 E3 ubiquitin ligase complex, we also identified E4orf1 as a novel factor interacting with E1B-55K and E4orf6 during infection; overexpression of E4orf1 led to less-efficient E3 ubiquitin ligase-mediated proteasomal degradation of p53. We hypothesize that p53 specifically subverts the pro-survival function of E4orf1-mediated PI3K-Akt activation to protect the cell from metabolic hyper-activation or even transformation.IMPORTANCEHuman adenoviruses (HAdV) are nearly ubiquitous pathogens comprising numerous subtypes that infect various tissues and organs. Among many encoded proteins that facilitate viral replication and subversion of host cellular processes, the viral E4orf1 protein has emerged as an intriguing yet under-investigated player in the complex interplay between the virus and its host. Nonetheless, E4orf1 has gained attention as a metabolism activator and oncogenic agent, while recent research is showing that E4orf1 may play a more important role in modulating the cellular pathways such as phosphoinositide 3-kinase-Akt-mTOR. Our study reveals a novel and general impact of E4orf1 on host mechanisms, providing a novel basis for innovative antiviral strategies in future therapeutic settings. Ongoing investigations of the cellular pathways modulated by HAdV are of great interest, particularly since adenovirus-based vectors actually serve as vaccine or gene vectors. HAdV constitute an ideal model system to analyze the underlying molecular principles of virus-induced tumorigenesis.

Linear and non-linear dynamics of the epidemics: System identification based parametric prediction models for the pandemic outbreaks

Coronavirus disease 2019 (COVID-19) has endured constituting formidable economic, social, educational, and phycological challenges for the societies. Moreover, during pandemic outbreaks, the hospitals are overwhelmed with patients requiring more intensive care units and intubation equipment. Therein, to cope with these urgent healthcare demands, the state authorities seek ways to develop policies based on the estimated future casualties. These policies are mainly non-pharmacological policies including the restrictions, curfews, closures, and lockdowns. In this paper, we construct three model structures of the SpInItIbD-N (suspicious Sp, infected In, intensive care It, intubated Ib, and dead D together with the non-pharmacological policies N) holding two key targets. The first one is to predict the future COVID-19 casualties including the intensive care and intubated ones, which directly determine the need for urgent healthcare facilities, and the second one is to analyse the linear and non-linear dynamics of the COVID-19 pandemic under the non-pharmacological policies. In this respect, we have modified the non-pharmacological policies and incorporated them within the models whose parameters are learned from the available data. The trained models with the data released by the Turkish Health Ministry confirmed that the linear SpInItIbD-N model yields more accurate results under the imposed non-pharmacological policies. It is important to note that the non-pharmacological policies have a damping effect on the pandemic casualties and this can dominate the non-linear dynamics. Herein, a model without pharmacological or non-pharmacological policies might have more dominant non-linear dynamics. In addition, the paper considers two machine learning approaches to optimize the unknown parameters of the constructed models. The results show that the recursive neural network has superior performance for learning nonlinear dynamics. However, the batch least squares outperforms in the presence of linear dynamics and stochastic data. The estimated future pandemic casualties with the linear SpInItIbD-N model confirm that the suspicious, infected, and dead casualties converge to zero from 200000, 1400, 200 casualties, respectively. The convergences occur in 120 days under the current conditions.

Viral and cellular oncogenes promote immune evasion

Thirteen percent of cancers worldwide are associated with viral infections. While many human oncogenic viruses are widely endemic, very few infected individuals develop cancer. This raises the question why oncogenic viruses encode viral oncogenes if they can replicate and spread between human hosts without causing cancer. Interestingly, viral infection triggers innate immune signaling pathways that in turn activate tumor suppressors such as p53, suggesting that tumor suppressors may have evolved not primarily to prevent cancer, but to thwart viral infection. Here, we summarize and compare several major immune evasion strategies used by viral and non-viral cancers, with a focus on oncogenes that play dual roles in promoting tumorigenicity and immune evasion. By highlighting important and illustrative examples of how oncogenic viruses evade the immune system, we aim to shed light on how non-viral cancers avoid immune detection. Further study and understanding of how viral and non-viral oncogenes impact immune function could lead to improved strategies to combine molecular therapies targeting oncoproteins in combination with immunomodulators.

Interrelationship between daily COVID-19 cases and average temperature as well as relative humidity in Germany

COVID-19 pandemic continues to obstruct social lives and the world economy other than questioning the healthcare capacity of many countries. Weather components recently came to notice as the northern hemisphere was hit by escalated incidence in winter. This study investigated the association between COVID-19 cases and two components, average temperature and relative humidity, in the 16 states of Germany. Three main approaches were carried out in this study, namely temporal correlation, spatial auto-correlation, and clustering-integrated panel regression. It is claimed that the daily COVID-19 cases correlate negatively with the average temperature and positively with the average relative humidity. To extract the spatial auto-correlation, both global Moran's [Formula: see text] and global Geary's [Formula: see text] were used whereby no significant difference in the results was observed. It is evident that randomness overwhelms the spatial pattern in all the states for most of the observations, except in recent observations where either local clusters or dispersion occurred. This is further supported by Moran's scatter plot, where states' dynamics to and fro cold and hot spots are identified, rendering a traveling-related early warning system. A random-effects model was used in the sense of case-weather regression including incidence clustering. Our task is to perceive which ranges of the incidence that are well predicted by the existing weather components rather than seeing which ranges of the weather components predicting the incidence. The proposed clustering-integrated model associated with optimal barriers articulates the data well whereby weather components outperform lag incidence cases in the prediction. Practical implications based on marginal effects follow posterior to model diagnostics.

Demystifying therapeutic potential of medicinal plants against chikungunya virus

Viral infections are posing a great threat to humanity for the last few years. Among these, Chikungunya which is a mosquito-borne viral infection has produced enormous epidemics around the world after been rebounded. Although this infection shows a low mortality rate, patients suffer from fever, arthralgia, and maculopapular rashes, which reduce the quality of life for several weeks to years. The currently available treatments only provide symptomatic relief based on analgesics, antipyretics, and anti-inflammatory drugs which are nonspecific without satisfactory results. Medicinal plants are a widely accepted source of new molecules for the treatment of infectious diseases including viral infections. The scientific reports, primarily focusing on the anti-chikungunya activity of plant extracts, natural origin pure compounds, and their synthetic analog published from 2011 to 2021, were selected from PubMed, Google Scholar, and Scopus by using related keywords like anti-chikungunya plants, natural antivirals for Chikungunya. The present review decodes scientific reports on medicinal plants against chikungunya virus (CHIKV) infection and demystifies the potential phytoconstituents which reveals that the screening of flavonoids containing plants and phytochemicals showing efficacy against other arbovirus infections, may prove as a potential lead for drug development against CHIKV. The present article also outlines pathogenesis, clinical aspects, molecular virology, and diagnostic approaches of CHIKV infection.

Gut eukaryotic virome in colorectal carcinogenesis: Is that a trigger?

The human gut microbiota is composed of bacteria and viruses that might be associated with colorectal cancer (CRC) onset and progression. Indeed, although viral infections have been reported to be the primary trigger in many diseases, the role of eukaryotic viruses populating the gut mucosa during early colorectal carcinogenesis is underinvestigated. Human eukaryotic viruses in the gut were found to induce alterations of the immune homeostasis so that some viral-dependent mechanisms likely able to induce DNA alterations in the bowel wall have been proposed, although no demonstration is available yet. However, thanks to the latest advancements in computational biology and the implementation of the bioinformatic pipelines, the option of establishing a direct causative link between intestinal virome and CRC will be possible soon, hopefully paving the way to innovative therapeutic strategies blocking or reverting the CRC pathogenesis.