Effect of different modes of viral spread on the dynamics of multiply infected cells in human immunodeficiency virus infection

Infection of individual cells with more than one HIV particle is an important feature of HIV replication, which may contribute to HIV pathogenesis via the occurrence of recombination, viral complementation and other outcomes that influence HIV replication and evolutionary dynamics. A previous mathematical model of co-infection has shown that the number of cells infected with i viruses correlates with the ith power of the singly infected cell population, and this has partly been observed in experiments. This model, however, assumed that virus spread from cell to cell occurs only via free virus particles, and that viruses and cells mix perfectly. Here, we introduce a cellular automaton model that takes into account different modes of virus spread among cells, including cell to cell transmission via the virological synapse, and spatially constrained virus spread. In these scenarios, it is found that the number of multiply infected cells correlates linearly with the number of singly infected cells, meaning that co-infection plays a greater role at lower virus loads. The model further indicates that current experimental systems that are used to study co-infection dynamics fail to reflect the true dynamics of multiply infected cells under these specific assumptions, and that new experimental techniques need to be designed to distinguish between the different assumptions.     

Uncovering the Rab5‐Independent Autophagic Trafficking of Influenza A Virus by Quantum‐Dot‐Based Single‐Virus Tracking

Autophagy is closely related to virus‐induced disease and a comprehensive understanding of the autophagy‐associated infection process of virus will be significant for developing more effective antiviral strategies. However, many critical issues and the underlying mechanism of autophagy in virus entry still need further investigation. Here, this study unveils the involvement of autophagy in influenza A virus entry. The quantum‐dot‐based single‐virus tracking technique assists in real‐time, prolonged, and multicolor visualization of the transport process of individual viruses and provides unambiguous dissection of the autophagic trafficking of viruses. These results reveal that roughly one‐fifth of viruses are ferried into cells for infection by autophagic machineries, while the remaining are not. A comprehensive overview of the endocytic‐ and autophagic‐trafficking process indicates two distinct trafficking pathway of viruses, either dependent on Rab5‐positive endosomes or autophagosomes, with striking similarities. Expressing dominant‐negative mutant of Rab5 suggests that the autophagic trafficking of viruses is independent on Rab5. The present study provides dynamic, precise, and mechanistic insights into the involvement of autophagy in virus entry, which contributes to a better understanding of the relationship between autophagy and virus entry. The quantum‐dot‐based single‐virus tracking is proven to hold promise for autophagy‐related fundamental research.     

Exploring Sialic Acid Receptors‐Related Infection Behavior of Avian Influenza Virus in Human Bronchial Epithelial Cells by Single‐Particle Tracking

Human respiratory tract epithelial cells are the portals of human infection with influenza viruses. However, the infection pathway of individual avian influenza viruses in human respiratory cells remains poorly reported so far. The single‐particle tracking technique (SPT) is a powerful tool for studying the transport mechanism of biomolecules in live cells. In this work, we use quantum dots to label avian influenza H9N2 virus and elaborate on the infection mechanism of the virus in human bronchial epithelial (HBE) cells using a three‐dimensional SPT technique. We have found that the H9N2 virus can infect HBE cells directly and the virus infection follows an actin filament‐ and microtubule‐dependent process with a three‐stage pattern. The transport behaviors show a high degree of consistency between the sialic acid receptors and the influenza virus. Real‐time SPT provides dynamic evidence of the sialic acid receptors‐related infection behavior of the avian influenza virus in live cells. The study of the influence of sialic acid receptors on virus infection may contribute to a better understanding of the cross‐species transmission of the avian influenza virus.     

Functionalized Fullerene for Inhibition of SARS-CoV-2 Variants

As virus outbreaks continue to pose a challenge, a nonspecific viral inhibitor can provide significant benefits, especially against respiratory viruses. Polyglycerol sulfates recently emerge as promising agents that mediate interactions between cells and viruses through electrostatics, leading to virus inhibition. Similarly, hydrophobic C₆₀ fullerene can prevent virus infection via interactions with hydrophobic cavities of surface proteins. Here, two strategies are combined to inhibit infection of SARS-CoV-2 variants in vitro. Effective inhibitory concentrations in the millimolar range highlight the significance of bare fullerene's hydrophobic moiety and electrostatic interactions of polysulfates with surface proteins of SARS-CoV-2. Furthermore, microscale thermophoresis measurements support that fullerene linear polyglycerol sulfates interact with the SARS-CoV-2 virus via its spike protein, and highlight importance of electrostatic interactions within it. All-atom molecular dynamics simulations reveal that the fullerene binding site is situated close to the receptor binding domain, within 4 nm of polyglycerol sulfate binding sites, feasibly allowing both portions of the material to interact simultaneously.     

Within-host viral dynamics of dengue serotype 1 infection

Dengue, the most common mosquito-borne viral infection of humans, is endemic across much of the world, including much of tropical Asia and is increasing in its geographical range. Here, we present a mathematical model of dengue virus dynamics within infected individuals, detailing the interaction between virus and a simple immune response. We fit this model to measurements of plasma viral titre from cases of primary and secondary DENV 1 infection in Vietnam. We show that variation in model parameters governing the immune response is sufficient to create the observed variation in virus dynamics between individuals. Estimating model parameter values, we find parameter differences between primary and secondary cases consistent with the theory of antibody-dependent enhancement (namely enhanced rates of viral entry to target cells in secondary cases). Finally, we use our model to examine the potential impact of an antiviral drug on the within-host dynamics of dengue. We conclude that the impact of antiviral therapy on virus dynamics is likely to be limited if therapy is only started at the onset of symptoms, owing to the typically late stage of viral pathogenesis reached by the time symptoms are manifested and thus treatment is started.     

Bioinspired Artificial Tobacco Mosaic Virus with Combined Oncolytic Properties to Completely Destroy Multidrug-Resistant Cancer

Although biomimetic virus-like strategies have been widely used in antitumor applications, construction of uniquely shaped virus-like agents and optimization of their specific morphological features to achieve diverse antitumor functions are worthwhile pursuits. Here, a novel strategy to construct an artificial tobacco mosaic virus (ATMV) that closely mimics the structure of the rod-like tobacco mosaic virus (TMV) is developed. The supramolecular array is self-assembled from small, repeated subunits of tailor-made capsid-mimicking dendrons onto RGD-modified single-walled carbon nanotube to construct the ATMVs with high structural stability. The ATMVs are tactfully designed with shielding, targeting, and arming approaches, including shielding the viruses against premature elimination, selectively targeting tumor tissue, and arming the viruses with oncolytic abilities. The elongated particles are concealed in blood until they arrived at a tumor site, then they induce robust composite oncolytic processes including cytomembrane penetration, endoplasmic reticulum disruption to cause Ca²⁺ release, chemotherapeutic delivery, and photothermal therapy. Excitingly, the ATMVs not only lyse primary infected cells, but permeate adjacent cells for secondary infection, spreading cell-to-cell and continuing to induce lysis even deep in solid tumors. This work inspires a uniquely shaped virus-like agent with tactically optimized oncolytic functions that completely defeated large drug-resistant colon tumor (LoVo/Adr, ≈500 mm³).     

Mechanistic movement models reveal ecological drivers of tick-borne pathogen spread

Identifying ecological drivers of tick-borne pathogen spread has great value for tick-borne disease management. However, theoretical investigations into the consequences of host movement behaviour on pathogen spread dynamics in heterogeneous landscapes remain limited because spatially explicit epidemiological models that incorporate more realistic mechanisms governing host movement are rare. We built a mechanistic movement model to investigate how the interplay between multiple ecological drivers affects the risk of tick-borne pathogen spread across heterogeneous landscapes. We used the model to generate simulations of tick dispersal by migratory birds and terrestrial hosts across theoretical landscapes varying in resource aggregation, and we performed a sensitivity analysis to explore the impacts of different parameters on the infected tick spread rate, tick infection prevalence and infected tick density. Our findings highlight the importance of host movement and tick population dynamics in explaining the infected tick spread rate into new regions. Tick infection prevalence and infected tick density were driven by predictors related to the infection process and tick population dynamics, respectively. Our results suggest that control strategies aiming to reduce tick burden on tick reproduction hosts and encounter rate between immature ticks and pathogen amplification hosts will be most effective at reducing tick-borne disease risk.     

An avian influenza model with latency and vaccination

Avian influenza, caused by influenza A viruses, has received worldwide attention in recent years. The viruses can spread from birds to humans as well as transmit among human hosts. In this study, we formulate a mathematical model for avian influenza that includes bird-human interaction and that incorporates the effects of infection latency and human vaccination. We investigate the essential dynamics of the model through an equilibrium analysis. Meanwhile, we explore effective vaccination strategy to control avian influenza outbreaks using optimal control theory. Our results indicate that strategically deployed human vaccination can significantly reduce the numbers of exposed and infectious people.     

Systems engineering medicine: engineering the inflammation response to infectious and traumatic challenges

The complexity of the systemic inflammatory response and the lack of a treatment breakthrough in the treatment of pathogenic infection demand that advanced tools be brought to bear in the treatment of severe sepsis and trauma. Systems medicine, the translational science counterpart to basic science''s systems biology, is the interface at which these tools may be constructed. Rapid initial strides in improving sepsis treatment are possible through the use of phenomenological modelling and optimization tools for process understanding and device design. Higher impact, and more generalizable, treatment designs are based on mechanistic understanding developed through the use of physiologically based models, characterization of population variability, and the use of control-theoretic systems engineering concepts. In this review we introduce acute inflammation and sepsis as an example of just one area that is currently underserved by the systems medicine community, and, therefore, an area in which contributions of all types can be made.     

Modelling immune response to BK virus infection and donor kidney in renal transplant recipients

In this paper, we develop and validate with bootstrapping techniques a mechanistic mathematical model of immune response to both BK virus infection and a donor kidney based on known and hypothesized mechanisms in the literature. The model presented does not capture all the details of the immune response but possesses key features that describe a very complex immunological process. We then estimate model parameters using a least squares approach with a typical set of available clinical data. Sensitivity analysis combined with asymptotic theory is used to determine the number of parameters that can be reliably estimated given the limited number of observations.     

Social encounter networks: collective properties and disease transmission

A fundamental challenge of modern infectious disease epidemiology is to quantify the networks of social and physical contacts through which transmission can occur. Understanding the collective properties of these interactions is critical for both accurate prediction of the spread of infection and determining optimal control measures. However, even the basic properties of such networks are poorly quantified, forcing predictions to be made based on strong assumptions concerning network structure. Here, we report on the results of a large-scale survey of social encounters mainly conducted in Great Britain. First, we characterize the distribution of contacts, which possesses a lognormal body and a power-law tail with an exponent of −2.45; we provide a plausible mechanistic model that captures this form. Analysis of the high level of local clustering of contacts reveals additional structure within the network, implying that social contacts are degree assortative. Finally, we describe the epidemiological implications of this local network structure: these contradict the usual predictions from networks with heavy-tailed degree distributions and contain public-health messages about control. Our findings help us to determine the types of realistic network structure that should be assumed in future population level studies of infection transmission, leading to better interpretations of epidemiological data and more appropriate policy decisions.     

Modelling the effects of past and future climate on the risk of bluetongue emergence in Europe

Vector-borne diseases are among those most sensitive to climate because the ecology of vectors and the development rate of pathogens within them are highly dependent on environmental conditions. Bluetongue (BT), a recently emerged arboviral disease of ruminants in Europe, is often cited as an illustration of climate''s impact on disease emergence, although no study has yet tested this association. Here, we develop a framework to quantitatively evaluate the effects of climate on BT''s emergence in Europe by integrating high-resolution climate observations and model simulations within a mechanistic model of BT transmission risk. We demonstrate that a climate-driven model explains, in both space and time, many aspects of BT''s recent emergence and spread, including the 2006 BT outbreak in northwest Europe which occurred in the year of highest projected risk since at least 1960. Furthermore, the model provides mechanistic insight into BT''s emergence, suggesting that the drivers of emergence across Europe differ between the South and the North. Driven by simulated future climate from an ensemble of 11 regional climate models, the model projects increase in the future risk of BT emergence across most of Europe with uncertainty in rate but not in trend. The framework described here is adaptable and applicable to other diseases, where the link between climate and disease transmission risk can be quantified, permitting the evaluation of scale and uncertainty in climate change''s impact on the future of such diseases.     

Single passage in mouse organs enhances the survival and spread of Salmonella enterica

Intravenous inoculation of Salmonella enterica serovar Typhimurium into mice is a prime experimental model of invasive salmonellosis. The use of wild-type isogenic tagged strains (WITS) in this system has revealed that bacteria undergo independent bottlenecks in the liver and spleen before establishing a systemic infection. We recently showed that those bacteria that survived the bottleneck exhibited enhanced growth when transferred to naive mice. In this study, we set out to disentangle the components of this in vivo adaptation by inoculating mice with WITS grown either in vitro or in vivo. We developed an original method to estimate the replication and killing rates of bacteria from experimental data, which involved solving the probability-generating function of a non-homogeneous birth–death–immigration process. This revealed a low initial mortality in bacteria obtained from a donor animal. Next, an analysis of WITS distributions in the livers and spleens of recipient animals indicated that in vivo-passaged bacteria started spreading between organs earlier than in vitro-grown bacteria. These results further our understanding of the influence of passage in a host on the fitness and virulence of Salmonella enterica and represent an advance in the power of investigation on the patterns and mechanisms of host–pathogen interactions.     

Profiling of cucumber mosaic virus responsive mRNAs in tomato using micro paraflo microfluidics microarrays

Cucumber mosaic virus (CMV) is widely spread worldwide, causing typical systemic mosaic and other symptoms in tomato (Solanum lycopersicum). Host responses to CMV and molecular mechanisms associated with the development of disease symptoms caused by this virus in tomato are largely unexplored. To investigate plant responses activated during this interaction, we used microarray analysis to monitor changes in host gene expression during disease development. Compared with genes from mock-inoculated control plants, seedlings to adults, 214 of the 3313 tomato genes represented on the array were differentially expressed in CMV-infected plants. Functional classification of CMV-responsive genes revealed that CMV activated typical basal defense responses in the host during the infection process, including induction of defense-related genes, production and scavenging of free oxygen radicals, and hormone synthesis. CMV infection also suppressed a subset of host genes involved in photosynthesis and metabolism. Our results indicate that a wide range of genes play an important role in regulation of the tomato susceptibility response to CMV.     

Time variation in the probability of failing to detect a case of polymerase chain reaction testing for SARS-CoV-2 as estimated from a viral dynamics model

Viral tests including polymerase chain reaction (PCR) tests are recommended to diagnose COVID-19 infection during the acute phase of infection. A test should have high sensitivity; however, the sensitivity of the PCR test is highly influenced by viral load, which changes over time. Because it is difficult to collect data before the onset of symptoms, the current literature on the sensitivity of the PCR test before symptom onset is limited. In this study, we used a viral dynamics model to track the probability of failing to detect a case of PCR testing over time, including the presymptomatic period. The model was parametrized by using longitudinal viral load data collected from 30 hospitalized patients. The probability of failing to detect a case decreased toward symptom onset, and the lowest probability was observed 2 days after symptom onset and increased afterwards. The probability on the day of symptom onset was 1.0% (95% CI: 0.5 to 1.9) and that 2 days before symptom onset was 60.2% (95% CI: 57.1 to 63.2). Our study suggests that the diagnosis of COVID-19 by PCR testing should be done carefully, especially when the test is performed before or way after symptom onset. Further study is needed of patient groups with potentially different viral dynamics, such as asymptomatic cases.     

Single‐Particle Tracking Reveals the Sequential Entry Process of the Bunyavirus Severe Fever with Thrombocytopenia Syndrome Virus

The Bunyavirales is one of the largest groups of RNA viruses, which encompasses many strains that are highly pathogenic to animals and humans. Severe fever with thrombocytopenia syndrome virus (SFTSV) is an emerging tick‐borne bunyavirus that causes severe disease in humans, with a high fatality rate of up to 30%. To date, the entry process of bunyavirus infection remains obscure. Here, using quantum dot (QD)‐based single‐particle tracking and multicolor imaging, the dynamic molecular process of SFTSV entry and penetration is systematically dissected. The results show that internalization of SFTSV into host cells is initiated by recruiting clathrin onto the cell membrane for the formation of clathrin‐coated pits and further pinching off from the plasma membrane to form discrete vesicles. These vesicular carriers further deliver virions to Rab5+ early endosomes, and then to Rab7+ late endosomes. The intracellular transport of virion‐carrying endocytic vesicles is dependent first on actin filaments at the cell periphery, and then on microtubules toward the cell interior. The final fusion events occur at ≈15–60 min post‐entry, and are triggered by the acidic environment at ≈pH5.6 within the late endosomes. These results reveal the multistep SFTSV entry process and the dynamic virus–host interactions involved.     

Disease induced dynamics in host–parasitoid systems: chaos and coexistence

All animals and plants are, to some extent, susceptible to disease caused by varying combinations of parasites, viruses and bacteria. In this paper, we present a mathematical model of interactions between a host, two parasitoids and a pathogen which shows that the presence of an infection can preserve and promote diversity in such multi-species systems. Initially, we use a system of ordinary differential equations to investigate interactions between two species of parasitoids, a host and a host infection. We show that the presence of all four species is necessary for the system as a whole to persist, and that in particular, the presence of the pathogen is necessary for the coexistence of the two parasitoid species. The inclusion of infection induces a wide range of dynamics, including chaos, and these dynamics are robust for a wide range of parameter values. We then extend the model to include spatial effects by introducing random motility (diffusion) of all three species and examine the subsequent spatio-temporal dynamics, including travelling waves and other more complicated heterogeneous behaviour. The computational simulation results of the model suggest that infection in the hosts can blunt the effects of competition between parasitoids, allowing the weaker competitor to survive. Regardless of the nature of the stability of the coexistent steady state of the system, there is an initial period of transient dynamics, the length of which can be extended by an appropriate choice of initial conditions. The existence of these transient dynamics suggests that systems subject to regular restoration to a starting state, such as agro-ecosystems, may be kept in a continual state of dynamic transience, and this has implications for the use of natural enemies to control insect pests, the preservation of biodiversity in farmland habitats and the more general dynamics of disease processes.     

Modelling the spread of infectious salmon anaemia among salmon farms based on seaway distances between farms and genetic relationships between infectious salmon anaemia virus isolates

Infectious salmon anaemia (ISA) is an important infectious disease in Atlantic salmon farming causing recurrent epidemic outbreaks worldwide. The focus of this paper is on tracing the spread of ISA among Norwegian salmon farms. To trace transmission pathways for the ISA virus (ISAV), we use phylogenetic relationships between virus isolates in combination with space–time data on disease occurrences. The rate of ISA infection of salmon farms is modelled stochastically, where seaway distances between farms and genetic distances between ISAV isolates from infected farms play prominent roles. The model was fitted to data covering all cohorts of farmed salmon and the history of all farms with ISA between 2003 and summer 2009. Both seaway and genetic distances were significantly associated with the rate of ISA infection. The fitted model predicts that the risk of infection from a neighbourhood infectious farm decreases with increasing seaway distance between the two farms. Furthermore, for a given infected farm with a given ISAV genotype, the source of infection is significantly more likely to be ISAV of a small genetic distance than of moderate or large genetic distances. Nearly half of the farms with ISA in the investigated period are predicted to have been infected by an infectious farm in their neighbourhood, whereas the remaining half of the infected farms had unknown sources. For many of the neighbourhood infected farms, it was possible to point out one or a few infectious farms as the most probable sources of infection. This makes it possible to map probable infection pathways.