Worldwide clustering and infection cycles as universal features of multiscale stochastic processes in the SARS-CoV-2 pandemic

Predicting the evolution of the current epidemic depends significantly on understanding the nature of the underlying stochastic processes. To unravel the global features of these processes, we analyse the world data of SARS-CoV-2 infection events, scrutinising two eight-month periods associated with the epidemic's outbreak and initial immunisation phase. Based on the correlation-network mapping, K-means clustering, and multifractal time series analysis, our results reveal universal patterns, suggesting potential predominant drivers of the pandemic. More precisely, the Laplacian eigenvectors localisation has revealed robust communities of different countries and regions that then cluster according to similar shapes of infection fluctuations. Apart from quantitative measures, the immunisation phase differs significantly from the epidemic outbreak by the countries and regions constituting each cluster. While the similarity grouping possesses some regional components, the appearance of large clusters spanning different geographic locations is persevering. Furthermore, cyclic trends are characteristic of the identified clusters, dominating large temporal fluctuations of infection evolution, which are prominent in the immunisation phase. Meanwhile, persistent fluctuations around the local trend occur in intervals smaller than 14 days. These results provide a basis for further research into the interplay between biological and social factors as the primary cause of infection cycles and a better understanding of the impact of socio-economical and environmental factors at different phases of the pandemic.

Worldwide clustering and infection cycles as universal features of multiscale stochastic processes in the SARS-CoV-2 pandemic

Predicting the evolution of the current epidemic depends significantly on understanding the nature of the underlying stochastic processes. To unravel the global features of these processes, we analyse the world data of SARS-CoV-2 infection events, scrutinising two eight-month periods associated with the epidemic’s outbreak and initial immunisation phase. Based on the correlation-network mapping, K-means clustering, and multifractal time series analysis, our results reveal universal patterns, suggesting potential predominant drivers of the pandemic. More precisely, the Laplacian eigenvectors localisation has revealed robust communities of different countries and regions that then cluster according to similar shapes of infection fluctuations. Apart from quantitative measures, the immunisation phase differs significantly from the epidemic outbreak by the countries and regions constituting each cluster. While the similarity grouping possesses some regional components, the appearance of large clusters spanning different geographic locations is persevering. Furthermore, cyclic trends are characteristic of the identified clusters, dominating large temporal fluctuations of infection evolution, which are prominent in the immunisation phase. Meanwhile, persistent fluctuations around the local trend occur in intervals smaller than 14 days. These results provide a basis for further research into the interplay between biological and social factors as the primary cause of infection cycles and a better understanding of the impact of socio-economical and environmental factors at different phases of the pandemic.

Analysis of Infection Time Courses Shows CII Levels Determine the Frequency of Lysogeny in Phage 186

Engineered phage with properties optimised for the treatment of bacterial infections hold great promise, but require careful characterisation by a number of approaches. Phage–bacteria infection time courses, where populations of bacteriophage and bacteria are mixed and followed over many infection cycles, can be used to deduce properties of phage infection at the individual cell level. Here, we apply this approach to analysis of infection of Escherichia coli by the temperate bacteriophage 186 and explore which properties of the infection process can be reliably inferred. By applying established modelling methods to such data, we extract the frequency at which phage 186 chooses the lysogenic pathway after infection, and show that lysogenisation increases in a graded manner with increased expression of the lysogenic establishment factor CII. The data also suggest that, like phage λ, the rate of lysogeny of phage 186 increases with multiple infections.

EXPERIENCE WITH THE USE OF ALUVIA IN THE TREATMENT OF PATIENTS WITH MODERATE COVID-19

В настоящее время этиологическое лечение корона вирусной инфекции COVID-19 SARS CoV-2 не выявлено. Было исследовано влияние различных групп противовирусных препаратов на коронавирус. В ряде стран активно применялся лекарственный препарат Алувиа против коронавируса (комбинированный лопинавир и ритонавир). В данной научной работе представлены результаты применения высоко активных антиретро вирусных препаратов при коронавирусной инфекции.Лопинавир - ингибитор протеаз ВИЧ-1 и ВИЧ-2 - предотвращает расщепление gagpol-полипротеина, приводя к продукции незрелого неинфекционного вируса. Ритонавир - пептидомиметический ингибитор ВИЧ-1 и ВИЧ-2 аспартил протеаз. Торможение ВИЧ-протеазы делает этот фермент неспособным к обработке предшественника gag pol полипротеина, что приводит к образованию морфологически незрелых ВИЧ частиц, не способных к инициированию новых циклов инфицирования. [1] Currently, no etiological treatment of COVID-19 SARS CoV-2 coronavirus infection has been identified. The influence of various antiviral drug groups on the coronavirus was studied. One of them is the drug lopinavir \\ritonavir. This scientific paper presents an analysis of the experience of using highly active antiretroviral drugs in coronavirus infection. Lopinaviran inhibitor of HIV-1 and HIV - 2 proteases prevents the cleavage of gagpolpolyprotein, leading to the production of an immature noninfectious virus.Ritonavir is a peptidomimetic inhibitor of HIV-1 and HIV-2 aspartyl proteases. Inhibition of HIV protease makes this enzyme unable to process the gag pol precursor polyprotein, which leads to the formation of morphologically immature HIV particles that are not able to initiate new infection cycles. [1]

How to Train Your Phage: The Recent Efforts in Phage Training

Control of pathogenic bacteria by deliberate application of predatory phages has potential as a powerful therapy against antibiotic-resistant bacteria. The key advantages of phage biocontrol over antibacterial chemotherapy are: (1) an ability to self-propagate inside host bacteria, (2) targeted predation of specific species or strains of bacteria, (3) adaptive molecular machinery to overcome resistance in target bacteria. However, realizing the potential of phage biocontrol is dependent on harnessing or adapting these responses, as many phage species switch between lytic infection cycles (resulting in lysis) and lysogenic infection cycles (resulting in genomic integration) that increase the likelihood of survival of the phage in response to external stress or host depletion. Similarly, host range will need to be optimized to make phage therapy medically viable whilst avoiding the potential for deleteriously disturbing the commensal microbiota. Phage training is a new approach to produce efficient phages by capitalizing on the evolved response of wild-type phages to bacterial resistance. Here we will review recent studies reporting successful trials of training different strains of phages to switch into lytic replication mode, overcome bacterial resistance, and increase their host range. This review will also highlight the current knowledge of phage training and future implications in phage applications and phage therapy and summarize the recent pipeline of the magistral preparation to produce a customized phage for clinical trials and medical applications.

Dual RNA-seq analysis of in vitro infection multiplicity and RNA depletion methods in Chlamydia-infected epithelial cells

Dual RNA-seq experiments examining viral and bacterial pathogens are increasing, but vary considerably in their experimental designs, such as infection rates and RNA depletion methods. Here, we have applied dual RNA-seq to Chlamydia trachomatis infected epithelial cells to examine transcriptomic responses from both organisms. We compared two time points post infection (1 and 24 h), three multiplicity of infection (MOI) ratios (0.1, 1 and 10) and two RNA depletion methods (rRNA and polyA). Capture of bacterial-specific RNA were greatest when combining rRNA and polyA depletion, and when using a higher MOI. However, under these conditions, host RNA capture was negatively impacted. Although it is tempting to use high infection rates, the implications on host cell survival, the potential reduced length of infection cycles and real world applicability should be considered. This data highlights the delicate nature of balancing host–pathogen RNA capture and will assist future transcriptomic-based studies to achieve more specific and relevant infection-related biological insights.

Role of Virally Encoded Circular RNAs in the Pathogenicity of Human Oncogenic Viruses

Human oncogenic viruses are a group of important pathogens that etiologically contribute to at least 12% of total cancer cases in the world. As an emerging class of non-linear regulatory RNA molecules, circular RNAs (circRNAs) have gained increasing attention as a crucial player in the regulation of signaling pathways involved in viral infection and oncogenesis. With the assistance of current circRNA enrichment and detection technologies, numerous novel virally-encoded circRNAs (vcircRNAs) have been identified in the human oncogenic viruses, initiating an exciting new era of vcircRNA research. In this review, we discuss the current understanding of the roles of vcircRNAs in the respective viral infection cycles and in virus-associated pathogenesis.

Manipulating vector transmission reveals local processes in bacterial communities of bats

Infectious diseases result from multiple interactions among microbes and hosts, but community ecology approaches are rarely applied. Manipulation of vector populations provides a unique opportunity to test the importance of vectors in infection cycles while also observing changes in pathogen community diversity and species interactions. Yet for many vector-borne infections in wildlife, a biological vector has not been experimentally verified and few manipulative studies have been performed. Using a captive colony of fruit bats in Ghana, we observed changes in the community of Bartonella bacteria over time after the decline and subsequent reintroduction of bat flies. With reduced transmission, community changes were attributed to ecological drift and potential selection through interspecies competition mediated by host immunity. This work demonstrated that forces maintaining diversity in communities of free-living macroorganisms act in similar ways in communities of symbiotic microorganisms, both within and among hosts. Additionally, this study is the first to experimentally test the role of bat flies as vectors of Bartonella species.

Theoretical Studies of the Acid-Base Equilibria in a Model Active Site of the Human 20S Proteasome

The 20S Proteasome is a macromolecule responsible for the chemical step in the ubiquitin-proteasome system of degrading unnecessary and unused proteins of the cell. It plays a central role both in the rapid growth of cancer cells as well as in viral infection cycles. Herein, we present a computational study of the acid-base equilibria in an active site of the human proteasome, an aspect which is often neglected despite the crucial role protons play in the catalysis. As example substrates, we take the inhibition by epoxy and boronic acid containing warheads. We have combined cluster quantum mechanical calculations, replica exchange molecular dynamics and Bayesian optimization of non-bonded potential terms in the inhibitors. In relation to the latter, we propose an easily scalable approach to the reevaluation of non-bonded potentials making use of QM/MM dynamics information. Our results show that coupled acid-base equilibria need to be considered when modeling the inhibition mechanism. The coupling between a neighboring lysine and the reacting threonine is not affected by the presence of the inhibitor.

Theoretical Studies of the Acid-Base Equilibria in a Model Active Site of the Human 20S Proteasome

The 20S Proteasome is a macromolecule responsible for the chemical step in the ubiquitin-proteasome system of degrading unnecessary and unused proteins of the cell. It plays a central role both in the rapid growth of cancer cells as well as in viral infection cycles. Herein, we present a computational study of the acid-base equilibria in an active site of the human proteasome, an aspect which is often neglected despite the crucial role protons play in the catalysis. As example substrates, we take the inhibition by epoxy and boronic acid containing warheads. We have combined cluster quantum mechanical calculations, replica exchange molecular dynamics and Bayesian optimization of non-bonded potential terms in the inhibitors. In relation to the latter, we propose an easily scalable approach to the reevaluation of non-bonded potentials making use of QM/MM dynamics information. Our results show that coupled acid-base equilibria need to be considered when modeling the inhibition mechanism. The coupling between a neighboring lysine and the reacting threonine is not affected by the presence of the inhibitor.