Open questions in the social lives of viruses

Phage therapy for Klebsiella pneumoniae: Understanding bacteria-phage interactions for therapeutic innovations

Klebsiella pneumoniae (KP) is a Gram-negative bacterium that commonly resides in the human gastrointestinal tract and can also act as an opportunistic pathogen and cause extra-intestinal infections. KP poses a global health threat because it causes both hospital- and community-acquired infections in immune-competent and immunocompromised hosts. These infections can be multidrug-resistant and/or hypervirulent, making KP infections difficult to treat and deadly. In the absence of effective treatments for recalcitrant KP infections, bacteriophage (phage) therapy is gaining attention as a promising alternative. In this review, we evaluate KP epidemiology and epitope diversity, discuss interactions between KP-targeting phages and their bacterial hosts from an eco-evolutionary perspective, and summarize recent efforts in phage therapy for treating KP infections. We also discuss novel approaches, including genetic engineering and machine learning, as initial steps toward developing KP-targeting phage therapy as a precision medicine approach for an emerging and dangerous pathogen.

Exploiting social traits for clinical applications in bacteria and viruses

Despite generating a great deal of interest in the form of review papers, progress in exploiting social dynamics for treatment strategies against bacterial infection has made limited progress since it was suggested twenty years ago. In contrast, anti-viral strategies based on social interactions are entering clinical trial stage. We explore possible reasons for this difference and highlight areas where the two fields of research may learn from one another.

Baculovirus Genetic Diversity and Population Structure

Baculoviruses can naturally regulate lepidopteran populations and are used as biological insecticides. The genetic diversity of these viruses affects their survival and efficacy in pest control. For nucleopolyhedroviruses, occlusion-derived virions and the occlusion body facilitate the transmission of groups of genomes, whereas this is not the case for granuloviruses. We review the evidence for baculovirus genetic diversity in the environment, in the host insect, and in occlusion bodies and virions. Coinfection allows defective genotypes to persist through complementation and results in the pseudotyping of virus progeny that can influence their transmissibility and insecticidal properties. Genetic diversity has marked implications for the development of pest resistance to virus insecticides. We conclude that future research is warranted on the physical segregation of genomes during virus replication and on the independent action of virions during infection. We also identify opportunities for studies on the transmission of genetic diversity and host resistance to viruses.

Deciphering mixed infections by plant RNA virus and reconstructing complete genomes simultaneously present within-host

Local co-circulation of multiple phylogenetic lineages is particularly likely for rapidly evolving pathogens in the current context of globalisation. When different phylogenetic lineages co-occur in the same fields, they may be simultaneously present in the same host plant (i.e. mixed infection), with potentially important consequences for disease outcome. This is the case in Burkina Faso for the rice yellow mottle virus (RYMV), which is endemic to Africa and a major constraint on rice production. We aimed to decipher the distinct RYMV isolates that simultaneously infect a single rice plant and to sequence their genomes. To this end, we tested different sequencing strategies, and we finally combined direct cDNA ONT (Oxford Nanopore Technology) sequencing with the bioinformatics tool RVhaplo. This method was validated by the successful reconstruction of two viral genomes that were less than a hundred nucleotides apart (out of a genome of 4450nt length, i.e. 2-3%), and present in artificial mixes at a ratio of up to a 99/1. We then used this method to subsequently analyze mixed infections from field samples, revealing up to three RYMV isolates within one single rice plant sample from Burkina Faso. In most cases, the complete genome sequences were obtained, which is particularly important for a better estimation of viral diversity and the detection of recombination events. The method described thus allows to identify various haplotypes of RYMV simultaneously infecting a single rice plant, obtaining their full-length sequences, as well as a rough estimate of relative frequencies within the sample. It is efficient, cost-effective, as well as portable, so that it could further be implemented where RYMV is endemic. Prospects include unravelling mixed infections with other RNA viruses that threaten crop production worldwide.

Navigating a Fine Balance: Point-Mutant Cheater Viruses Disrupt the Viral Replication Cycle

Cheater viruses cannot replicate on their own yet replicate faster than the wild type (WT) when the 2 viruses coinfect the same cell. Cheaters must possess dual genetic features: a defect, which leads to their inability to infect cells on their own, and a selective advantage over WT during coinfection. Previously, we have discovered 2 point-mutant cheaters of the MS2 bacteriophage. Here, we set out to discover the possible repertoire of cheater MS2 viruses by performing experimental evolution at a very high multiplicity of infection. Our results revealed a third point-mutant cheater that arose in 8 biological replicas. Each of the 3 primary cheaters disrupts the fine balance necessary for phage replication, in different ways that create a defect + advantage. We found that over time, the point-mutant cheaters accumulate additional secondary mutations, which alter other stages of the viral replication cycle, complementing the disruptions created by the original cheater. Intriguingly, cheater and secondary mutations almost always reside in very close proximity on the genome. This region encodes for multiple functions: overlapping reading frames as well as overlapping RNA structures critical for transitioning from one stage to another in the viral replication cycle. This region of overlap explains the dual functions of cheaters, as one mutation can have pleiotropic effects. Overall, these findings underscore how viruses, whose dense genomes often have overlapping functions, can easily evolve point-mutant cheaters, and how cheaters can evolve to alter the intricate balance of the viral replication cycle.

Municipal secondary-treated effluent data seem to be a suitable source of information for human viral trends

Employing a long-time series of municipal wastewater samples collected in 2020, the present study aims to confirm whether the appearance of SARS-CoV-2 influences the environmental load and behaviour of both JC Virus and Norovirus, determine the ability of the selected wastewater treatment plant (WWTP) to remove viral genomes, and assess if secondary-treated effluent data is somehow related to the incidence of the viral diseases reported by the local hospital. From the 11 raw influent and 52 secondary-treated effluent samples tested, JC Virus data present an occurrence frequency of 100 %, showing two different abundance patterns along the year, before and after the appearance of SARS-CoV-2. The constant detection of JC nucleic acids in wastewater reinforces the idea that urine is responsible for transmitting this virus. The Norovirus genogroup (G) II was detected more frequently than GI, both in influents and effluents, and their characteristic incidence peaks were not observed in late 2020. Regarding SARS-CoV-2 RNA, it appeared only in 5.8 % of the effluents, possibly due to the iron dosing used by the WWTP to reduce both phosphorus and organic matter concentrations in order to meet the requirements of European legislation, and/or the pre-filtration laboratory step which neglected the possibility of viral association with the solid fraction. The results suggest a poor performance of the WWTP, since Log removal values below 1.8 were determined. We were able to trace the development of local Norovirus outbreaks in the effluent samples to some extent, suggesting that secondary-treated effluents may be used to monitor human viruses by following viral nucleic acid levels.

Phage against the Machine: The SIE-ence of Superinfection Exclusion

Prophages can alter their bacterial hosts to prevent other phages from infecting the same cell, a mechanism known as superinfection exclusion (SIE). Such alterations are facilitated by phage interactions with critical bacterial components involved in motility, adhesion, biofilm production, conjugation, antimicrobial resistance, and immune evasion. Therefore, the impact of SIE extends beyond the immediate defense against superinfection, influencing the overall fitness and virulence of the bacteria. Evaluating the interactions between phages and their bacterial targets is critical for leading phage therapy candidates like Pseudomonas aeruginosa, a Gram-negative bacterium responsible for persistent and antibiotic-resistant opportunistic infections. However, comprehensive literature on the mechanisms underlying SIE remains scarce. Here, we provide a compilation of well-characterized and potential mechanisms employed by Pseudomonas phages to establish SIE. We hypothesize that the fitness costs imposed by SIE affect bacterial virulence, highlighting the potential role of this mechanism in the management of bacterial infections.

Influenza A defective viral genome production is altered by metabolites, metabolic signaling molecules, and cyanobacteria extracts

RNA virus infections are composed of a diverse mix of viral genomes that arise from low fidelity in replication within cells. The interactions between "defective" and full-length viral genomes have been shown to shape pathogenesis, leading to intense research into employing these to develop novel antivirals. In particular, Influenza A defective viral genomes (DVGs) have been associated with milder clinical outcomes. Yet, the full potential of DVGs as broad-spectrum antivirals remains untapped due to the unknown mechanisms of their de novo production. Much of the research into the factors affecting defective viral genome production has focused on the virus, while the role of the host has been neglected. We recently showed that altering host cell metabolism away from pro-growth pathways using alpelisib increased the production of Influenza A defective viral genomes. To uncover other drugs that could induce infections to create more DVGs, we subjected active influenza infections of the two circulating human subtypes (A/H1N1 & A/H3N2) to a screen of metabolites, metabolic signaling molecules, and cyanobacteria-derived biologics, after which we quantified the defective viral genomes (specifically deletion-containing viral genomes, DelVGs) and total viral genomes using third generation long-read sequencing. Here we show that metabolites and signaling molecules of host cell central carbon metabolism can significantly alter DelVG production early in Influenza A infection. Adenosine, emerged as a potent inducer of defective viral genomes, significantly amplifying DelVG production across both subtypes. Insulin had similar effects, albeit subtype-specific, predominantly enhancing polymerase segment DVGs in TX12 infections. Tricarboxylic Acid (TCA) cycle inhibitors 4-octyl itaconate and UK5099, along with the purine analog favipiravir, increased total viral genome production across subtypes. Cyanobacterial extracts primarily affected DVG and total viral genome production in TX12, with a specific, almost complete shutdown of influenza antigenic segments. These results underscore the influence of host metabolic pathways on DVG production and suggest new avenues for antiviral intervention, including PI3K-AKT and Ras-MAPK signaling pathways, TCA cycle metabolism, purine-pyrimidine metabolism, polymerase inhibition, and cyanotherapeutic approaches. More broadly, our findings suggest that the social interactions observed between defective and full-length viral genomes, depend not only on the viral actors, but can be altered by the stage provided by the host. Our study advances our fundamental understanding of DVG production mechanisms and highlights the potential of targeting host metabolism to develop broad-spectrum influenza therapeutics.

Influenza A defective viral genomes and non-infectious particles are increased by host PI3K inhibition via anti-cancer drug alpelisib

RNA viruses produce abundant defective viral genomes during replication, setting the stage for interactions between viral genomes that alter the course of pathogenesis. Harnessing these interactions to develop antivirals has become a recent goal of intense research focus. Despite decades of research, the mechanisms that regulate the production and interactions of Influenza A defective viral genomes are still unclear. The role of the host is essentially unexplored; specifically, it remains unknown whether host metabolism can influence the formation of defective viral genomes and the particles that house them. To address this question, we manipulated host cell anabolic signaling activity and monitored the production of defective viral genomes and particles by A/H1N1 and A/H3N2 strains, using a combination of single-cell immunofluorescence quantification, third-generation long-read sequencing, and the cluster-forming assay, a method we developed to titer defective and fully-infectious particles simultaneously. Here we show that alpelisib (Piqray), a highly selective inhibitor of mammalian Class 1a phosphoinositide-3 kinase (PI3K) receptors, significantly changed the proportion of defective particles and viral genomes (specifically deletion-containing viral genomes) in a strain-specific manner, under conditions that minimize multiple cycles of replication. Alpelisib pre-treatment of cells led to an increase in defective particles in the A/H3N2 strain, while the A/H1N1 strain showed a decrease in total viral particles. In the same infections, we found that defective viral genomes of polymerase and antigenic segments increased in the A/H1N1 strain, while the total particles decreased suggesting defective interference. We also found that the average deletion size in polymerase complex viral genomes increased in both the A/H3N2 and A/H1N1 strains. The A/H1N1 strain, additionally showed a dose-dependent increase in total number of defective viral genomes. In sum, we provide evidence that host cell metabolism can increase the production of defective viral genomes and particles at an early stage of infection, shifting the makeup of the infection and potential interactions among virions. Given that Influenza A defective viral genomes can inhibit pathogenesis, our study presents a new line of investigation into metabolic states associated with less severe flu infection and the potential induction of these states with metabolic drugs.

Fractal networks: Topology, dimension, and complexity

Over the past two decades, the study of self-similarity and fractality in discrete structures, particularly complex networks, has gained momentum. This surge of interest is fueled by the theoretical developments within the theory of complex networks and the practical demands of real-world applications. Nonetheless, translating the principles of fractal geometry from the domain of general topology, dealing with continuous or infinite objects, to finite structures in a mathematically rigorous way poses a formidable challenge. In this paper, we overview such a theory that allows to identify and analyze fractal networks through the innate methodologies of graph theory and combinatorics. It establishes the direct graph-theoretical analogs of topological (Lebesgue) and fractal (Hausdorff) dimensions in a way that naturally links them to combinatorial parameters that have been studied within the realm of graph theory for decades. This allows to demonstrate that the self-similarity in networks is defined by the patterns of intersection among densely connected network communities. Moreover, the theory bridges discrete and continuous definitions by demonstrating how the combinatorial characterization of Lebesgue dimension via graph representation by its subsets (subgraphs/communities) extends to general topological spaces. Using this framework, we rigorously define fractal networks and connect their properties with established combinatorial concepts, such as graph colorings and descriptive complexity. The theoretical framework surveyed here sets a foundation for applications to real-life networks and future studies of fractal characteristics of complex networks using combinatorial methods and algorithms.

The social lives of viruses and other mobile genetic elements: a commentary on Leeks et al. 2023

Illustration of life-histories of phages and plasmids through horizontal and vertical transmission (see Figure 1 for more information).