Kinetics of coinfection with influenza A virus and Streptococcus pneumoniae

Estimating the distribution of parameters in differential equations with repeated cross-sectional data

Differential equations are pivotal in modeling and understanding the dynamics of various systems, as they offer insights into their future states through parameter estimation fitted to time series data. In fields such as economy, politics, and biology, the observation data points in the time series are often independently obtained (i.e., Repeated Cross-Sectional (RCS) data). RCS data showed that traditional methods for parameter estimation in differential equations, such as using mean values of RCS data over time, Gaussian Process-based trajectory generation, and Bayesian-based methods, have limitations in estimating the shape of parameter distributions, leading to a significant loss of data information. To address this issue, this study proposes a novel method called Estimation of Parameter Distribution (EPD) that provides accurate distribution of parameters without loss of data information. EPD operates in three main steps: generating synthetic time trajectories by randomly selecting observed values at each time point, estimating parameters of a differential equation that minimizes the discrepancy between these trajectories and the true solution of the equation, and selecting the parameters depending on the scale of discrepancy. We then evaluated the performance of EPD across several models, including exponential growth, logistic population models, and target cell-limited models with delayed virus production, thereby demonstrating the ability of the proposed method in capturing the shape of parameter distributions. Furthermore, we applied EPD to real-world datasets, capturing various shapes of parameter distributions over a normal distribution. These results address the heterogeneity within systems, marking a substantial progression in accurately modeling systems using RCS data. Therefore, EPD marks a significant advancement in accurately modeling systems with RCS data, realizing a deeper understanding of system dynamics and parameter variability.

A systematic review and guide for using multi-response statistical models in co-infection research

The simultaneous infection of organisms with two or more co-occurring pathogens, otherwise known as co-infections, concomitant infections or multiple infections, plays a significant role in the dynamics and consequences of infectious diseases in both humans and animals. To understand co-infections, ecologists and epidemiologists rely on models capable of accommodating multiple response variables. However, given the diversity of available approaches, choosing a model that is suitable for drawing meaningful conclusions from observational data is not a straightforward task. To provide clearer guidance for statistical model use in co-infection research, we conducted a systematic review to (i) understand the breadth of study goals and host-pathogen systems being pursued with multi-response models and (ii) determine the degree of crossover of knowledge among disciplines. In total, we identified 69 peer-reviewed primary studies that jointly measured infection patterns with two or more pathogens of humans or animals in natural environments. We found stark divisions in research objectives and methods among different disciplines, suggesting that cross-disciplinary insights into co-infection patterns and processes for different human and animal contexts are currently limited. Citation network analysis also revealed limited knowledge exchange between ecology and epidemiology. These findings collectively highlight the need for greater interdisciplinary collaboration for improving disease management.

Impact of pneumococcal conjugate vaccine 13 introduction on severe lower respiratory tract infections associated with respiratory syncytial virus or influenza virus in hospitalized children in Ulaanbaatar, Mongolia

Objectives

Limited data indicate a beneficial effect of pneumococcal conjugate vaccines (PCVs) on respiratory syncytial virus (RSV) and influenza infections in young children. We evaluated the impact of 13-valent PCV (PCV13) introduction on the incidence of severe lower respiratory tract infections (LRTIs) associated with RSV or influenza in hospitalized children.

Methods

Our study was restricted to children aged <2 years with arterial oxygen saturation <93% and children with radiologically confirmed pneumonia nested in a pneumonia surveillance project in four districts of Ulaanbaatar city, Mongolia. We tested nasopharyngeal swabs collected on admission for RSV and influenza using quantitative reverse transcription-polymerase chain reaction. The impact of PCV13 on the incidence of LRTI outcomes associated with RSV or with influenza for the period April 2015-March 2020 was estimated. Incidence rate ratios comparing pre- and post-vaccine periods were estimated for each outcome for each district using negative binomial models and for all districts combined with a mixed-effects negative binomial model. Adjusted models accounted for seasonality. Sensitivity analyses were conducted to assess the robustness of our findings.

Results

Among 5577 tested cases, the adjusted incidence rate ratios showed a trend toward a reduction in RSV-associated outcomes: all LRTIs (0.77, 95% confidence interval [CI] 0.44-1.36), severe LRTIs (0.88, 95% CI 0.48-1.62), very severe LRTIs (0.76, 95% CI 0.42-1.38), and radiologically confirmed pneumonia (0.66, 95% CI 0.32-1.38) but inconsistent trends in outcomes associated with influenza.

Conclusions

No significant reductions were observed in any outcomes associated with RSV and influenza after PCV introduction.

Mathematical Modeling Suggests That Monocyte Activity May Drive Sex Disparities during Influenza Infection

In humans, females of reproductive age often experience a more severe disease during influenza A virus infection, which may be due to differences in their innate immune response. Sex-specific outcomes to influenza infection have been recapitulated in mice, enabling researchers to study viral and immune dynamics in vivo in order to identify immune mechanisms that are differently regulated between the sexes. This study is based on the hypothesis that sex-specific outcomes emerge due to differences in the rates/speeds that select immune components respond. Using publicly available sex-specific murine data, we utilized dynamic mathematical models of the innate immune response to identify candidate mechanisms that may lead to increased disease severity in female mice. We implemented a large computational screen using the Bayesian information criterion (BIC), wherein the goodness of fit of the competing model scenarios is balanced against complexity (i.e., the number of parameters). Our results suggest that having sex-specific rates for proinflammatory monocyte induction by interferon and monocyte inhibition of virus replication provides the simplest (lowest BIC) explanation for the difference observed in the male and female immune responses. Markov-chain Monte Carlo (MCMC) analysis and global sensitivity analysis of the top performing scenario were performed to provide rigorous estimates of the sex-specific parameter distributions and to provide insight into which parameters most affect innate immune responses. Simulations using the top-performing model suggest that monocyte activity could be a key target to reduce influenza disease severity in females. Overall, our Bayesian statistical and dynamic modeling approach suggests that monocyte activity and induction parameters are sex-specific and may explain sex-differences in influenza disease immune dynamics.

Respiratory Syncytial Virus and Influenza Infections in Children in Ulaanbaatar, Mongolia, 2015-2021

BACKGROUND

Data available for RSV and influenza infections among children < 2 years in Mongolia are limited. We present data from four districts of Ulaanbaatar from April 2015 to June 2021.

METHODS

This study was nested in an enhanced surveillance project evaluating pneumococcal conjugate vaccine (PCV13) impact on the incidence of hospitalized lower respiratory tract infections (LRTIs). Our study was restricted to children aged < 2 years with arterial O2 saturation < 93% and children with radiological pneumonia. Nasopharyngeal (NP) swabs collected at admission were tested for RSV and influenza using qRT-PCR. NP swabs of all patients with radiological pneumonia and of a subset of randomly selected NP swabs were tested for S. pneumoniae (S.p.) by qPCR and for serotypes by culture and DNA microarray.

RESULTS

Among 5705 patients, 2113 (37.0%) and 386 (6.8%) had RSV and influenza infections, respectively. Children aged 2-6 months had a higher percentage of very severe RSV infection compared to those older than 6 months (42.2% versus 31.4%, p-value Fisher's exact = 0.001). S.p. carriage was detected in 1073/2281 (47.0%) patients. Among S.p. carriage cases, 363/1073 (33.8%) had S.p. and RSV codetection, and 82/1073 (7.6%) had S.p. and influenza codetection. S.p. codetection with RSV/influenza was not associated with more severe LRTIs, compared to only RSV/influenza cases.

CONCLUSION

In Mongolia, RSV is an important pathogen causing more severe LRTI in children under 6 months of age. Codetection of RSV or influenza virus and S.p. was not associated with increased severity.

A review of the influence of environmental pollutants (microplastics, pesticides, antibiotics, air pollutants, viruses, bacteria) on animal viruses

Microorganisms, especially viruses, cause disease in both humans and animals. Environmental chemical pollutants including microplastics, pesticides, antibiotics sand air pollutants arisen from human activities affect both animal and human health. This review assesses the impact of chemical and biological contaminants (virus and bacteria) on viruses including its life cycle, survival, mutations, loads and titers, shedding, transmission, infection, re-assortment, interference, abundance, viral transfer between cells, and the susceptibility of the host to viruses. It summarizes the sources of environmental contaminants, interactions between contaminants and viruses, and methods used to mitigate such interactions. Overall, this review provides a perspective of environmentally co-occurring contaminants on animal viruses that would be useful for future research on virus-animal-human-ecosystem harmony studies to safeguard human and animal health.

A bacterial vesicle-based pneumococcal vaccine against influenza-mediated secondary Streptococcus pneumoniae pulmonary infection

Streptococcus pneumoniae (Spn) is a common pathogen causing a secondary bacterial infection following influenza, which leads to severe morbidity and mortality during seasonal and pandemic influenza. Therefore, there is an urgent need to develop bacterial vaccines that prevent severe post-influenza bacterial pneumonia. Here, an improved Yersinia pseudotuberculosis strain (designated as YptbS46) possessing an Asd+ plasmid pSMV92 could synthesize high amounts of the Spn pneumococcal surface protein A (PspA) antigen and monophosphoryl lipid A as an adjuvant. The recombinant strain produced outer membrane vesicles (OMVs) enclosing a high amount of PspA protein (designated as OMV-PspA). A prime-boost intramuscular immunization with OMV-PspA induced both memory adaptive and innate immune responses in vaccinated mice, reduced the viral and bacterial burden, and provided complete protection against influenza-mediated secondary Spn infection. Also, the OMV-PspA immunization afforded significant cross-protection against the secondary Spn A66.1 infection and long-term protection against the secondary Spn D39 challenge. Our study implies that an OMV vaccine delivering Spn antigens can be a new promising pneumococcal vaccine candidate.

H9N2 Avian Influenza Virus Downregulates FcRY Expression in Chicken Macrophage Cell Line HD11 by Activating the JNK MAPK Pathway

The H9N2 avian influenza virus causes reduced production performance and immunosuppression in chickens. The chicken yolk sac immunoglobulins (IgY) receptor (FcRY) transports from the yolk into the embryo, providing offspring with passive immunity to infection against common poultry pathogens. FcRY is expressed in many tissues/organs of the chicken; however, there are no reports investigating FcRY expression in chicken macrophage cells, and how H9N2-infected HD11 cells (a chicken macrophage-like cell line) regulate FcRY expression remains uninvestigated. This study used the H9N2 virus as a model pathogen to explore the regulation of FcRY expression in avian macrophages. FcRY was highly expressed in HD11 cells, as shown by reverse transcription polymerase chain reactions, and indirect immunofluorescence indicated that FcRY was widely expressed in HD11 cells. HD11 cells infected with live H9N2 virus exhibited downregulated FcRY expression. Transfection of eukaryotic expression plasmids encoding each viral protein of H9N2 into HD11 cells revealed that nonstructural protein (NS1) and matrix protein (M1) downregulated FcRY expression. In addition, the use of a c-jun N-terminal kinase (JNK) activator inhibited the expression of FcRY, while a JNK inhibitor antagonized the downregulation of FcRY expression by live H9N2 virus, NS1 and M1 proteins. Finally, a dual luciferase reporter system showed that both the M1 protein and the transcription factor c-jun inhibited FcRY expression at the transcriptional level. Taken together, the transcription factor c-jun was a negative regulator of FcRY, while the live H9N2 virus, NS1, and M1 proteins downregulated the FcRY expression through activating the JNK signaling pathway. This provides an experimental basis for a novel mechanism of immunosuppression in the H9N2 avian influenza virus.

The Increase in Invasive Bacterial Infections With Respiratory Transmission in Germany, 2022/2023

BACKGROUND

In late 2022, health care institutions in Germany reported an unusual number of severe, invasive bacterial infections in association with a high incidence of viral respiratory infections.

METHODS

We analyzed routine data on invasive infections due to Haemophilus influenzae, Neisseria meningitidis, Staphylococcus aureus, Streptococcus pneumoniae, and Streptococcus pyogenes (2017-2023) from a voluntary, laboratory-based surveillance system involving continuously participating facilities providing diagnostic routine data that cover approximately one-third of the German population.

RESULTS

In the first quarter (Q1) of 2023, the number of invasive S. pyogenes isolates rose by 142% (n = 837 vs. mean Q1/2017-2019 = 346, 95% CI [258; 434]), while the number of H. influenzae isolates rose by 90% (n = 209 in Q1/2023 vs. mean Q1/2017-2019 = 110, 95% CI [79; 142]), compared to pre-pandemic seasonal peak values. The number of invasive S. pneumoniae isolates was high in two quarters (n = 1732 in Q4/2022 und Q1/2023). Adults aged 55 and older and children younger than 5 years were most affected by invasive H. influenzae, S. pneumoniae, and S. pyogenes infections. N. meningitidis was most commonly found in children under age 5.

CONCLUSION

The reason for the marked rise in invasive bacterial infections may be an increased circulation of respiratory pathogens and elevated susceptibility in the population after relaxation of the measures taken to prevent COVID-19 infection. Coinfections with respiratory viruses may have reinforced this effect. We recommend continuous surveillance, preventive measures such as raising awareness about invasive bacterial diseases, and vaccination as recommended by the German Standing Committee on Vaccinations (STIKO).

Virome Data Explorer: A web resource to longitudinally explore respiratory viral infections, their interactions with other pathogens and host transcriptomic changes in over 100 people

Viral respiratory infections are an important public health concern due to their prevalence, transmissibility, and potential to cause serious disease. Disease severity is the product of several factors beyond the presence of the infectious agent, including specific host immune responses, host genetic makeup, and bacterial coinfections. To understand these interactions within natural infections, we designed a longitudinal cohort study actively surveilling respiratory viruses over the course of 19 months (2016 to 2018) in a diverse cohort in New York City. We integrated the molecular characterization of 800+ nasopharyngeal samples with clinical data from 104 participants. Transcriptomic data enabled the identification of respiratory pathogens in nasopharyngeal samples, the characterization of markers of immune response, the identification of signatures associated with symptom severity, individual viruses, and bacterial coinfections. Specific results include a rapid restoration of baseline conditions after infection, significant transcriptomic differences between symptomatic and asymptomatic infections, and qualitatively similar responses across different viruses. We created an interactive computational resource (Virome Data Explorer) to facilitate access to the data and visualization of analytical results.

Mathematical Modeling of the Lethal Synergism of Coinfecting Pathogens in Respiratory Viral Infections: A Review

Influenza A virus (IAV) infections represent a substantial global health challenge and are often accompanied by coinfections involving secondary viruses or bacteria, resulting in increased morbidity and mortality. The clinical impact of coinfections remains poorly understood, with conflicting findings regarding fatality. Isolating the impact of each pathogen and mechanisms of pathogen synergy during coinfections is challenging and further complicated by host and pathogen variability and experimental conditions. Factors such as cytokine dysregulation, immune cell function alterations, mucociliary dysfunction, and changes to the respiratory tract epithelium have been identified as contributors to increased lethality. The relative significance of these factors depends on variables such as pathogen types, infection timing, sequence, and inoculum size. Mathematical biological modeling can play a pivotal role in shedding light on the mechanisms of coinfections. Mathematical modeling enables the quantification of aspects of the intra-host immune response that are difficult to assess experimentally. In this narrative review, we highlight important mechanisms of IAV coinfection with bacterial and viral pathogens and survey mathematical models of coinfection and the insights gained from them. We discuss current challenges and limitations facing coinfection modeling, as well as current trends and future directions toward a complete understanding of coinfection using mathematical modeling and computer simulation.

IL-17RA promotes pathologic epithelial inflammation in a mouse model of upper respiratory influenza infection

The upper respiratory tract (nasopharynx or NP) is the first site of influenza replication, allowing the virus to disseminate to the lower respiratory tract or promoting community transmission. The host response in the NP regulates an intricate balance between viral control and tissue pathology. The hyper-inflammatory responses promote epithelial injury, allowing for increased viral dissemination and susceptibility to secondary bacterial infections. However, the pathologic contributors to influenza upper respiratory tissue pathology are incompletely understood. In this study, we investigated the role of interleukin IL-17 recetor A (IL-17RA) as a modulator of influenza host response and inflammation in the upper respiratory tract. We used a combined experimental approach involving IL-17RA-/- mice and an air-liquid interface (ALI) epithelial culture model to investigate the role of IL-17 response in epithelial inflammation, barrier function, and tissue pathology. Our data show that IL-17RA-/- mice exhibited significantly reduced neutrophilia, epithelial injury, and viral load. The reduced NP inflammation and epithelial injury in IL-17RA-/- mice correlated with increased resistance against co-infection by Streptococcus pneumoniae (Spn). IL-17A treatment, while potentiating the apoptosis of IAV-infected epithelial cells, caused bystander cell death and disrupted the barrier function in ALI epithelial model, supporting the in vivo findings.

A cooperativity between virus and bacteria during respiratory infections

Respiratory tract infections remain the leading cause of morbidity and mortality worldwide. The burden is further increased by polymicrobial infection or viral and bacterial co-infection, often exacerbating the existing condition. Way back in 1918, high morbidity due to secondary pneumonia caused by bacterial infection was known, and a similar phenomenon was observed during the recent COVID-19 pandemic in which secondary bacterial infection worsens the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) condition. It has been observed that viruses paved the way for subsequent bacterial infection; similarly, bacteria have also been found to aid in viral infection. Viruses elevate bacterial infection by impairing the host's immune response, disrupting epithelial barrier integrity, expression of surface receptors and adhesion proteins, direct binding of virus to bacteria, altering nutritional immunity, and effecting the bacterial biofilm. Similarly, the bacteria enhance viral infection by altering the host's immune response, up-regulation of adhesion proteins, and activation of viral proteins. During co-infection, respiratory bacterial and viral pathogens were found to adapt and co-exist in the airways of their survival and to benefit from each other, i.e., there is a cooperative existence between the two. This review comprehensively reviews the mechanisms involved in the synergistic/cooperativity relationship between viruses and bacteria and their interaction in clinically relevant respiratory infections.

Immune predisposition drives susceptibility to pneumococcal pneumonia after mild influenza A virus infection in mice

Introduction

A frequent sequela of influenza A virus (IAV) infection is secondary bacterial pneumonia. Therefore, it is clinically important to understand the genetic predisposition to IAV and bacterial coinfection.

Methods

BALB/c and C57BL/6 (B6) mice were infected with high or low-pathogenic IAV and Streptococcus pneumoniae (SPn). The contribution of cellular and molecular immune factors to the resistance/susceptibility of BALB/c and B6 mice were dissected in nonlethal and lethal IAV/SPn coinfection models.

Results

Low-virulent IAV X31 (H3N2) rendered B6 mice extremely susceptible to SPn superinfection, while BALB/c mice remained unaffected. X31 infection alone barely induces IFN-γresponse in two strains of mice; however, SPn superinfection significantly enhances IFN-γ production in the susceptible B6 mice. As a result, IFN-γ signaling inhibits neutrophil recruitment and bacterial clearance, leading to lethal X31/SPn coinfection in B6 mice. Conversely, the diminished IFN-γ and competent neutrophil responses enable BALB/c mice highly resistant to X31/SPn coinfection.

Discussion

The results establish that type 1 immune predisposition plays a key role in lethal susceptibility of B6 mice to pneumococcal pneumonia after mild IAV infection.

Stimulation of lipopolysaccharide from Pseudomonas aeruginosa following H9N2 IAV infection exacerbates inflammatory responses of alveolar macrophages and decreases virus replication

H9N2 IAV infection contributed to P. aeruginosa coinfection, causing severe hemorrhagic pneumonia in mink. In this study, the in vitro alveolar macrophage models were developed to investigate the innate immune responses to P. aeruginosa LPS stimulation following H9N2 IAV infection, using MH-S cells. The cytokine levels, apoptosis levels and the viral nucleic acid levels were detected and analyzed. As a result, the levels of IFN-α, IL-1β, TNF-α, and IL-10 in MH-S cells with P. aeruginosa LPS stimulation following H9N2 IAV infection were significantly higher than those in MH-S cells with single H9N2 IAV infection and single LPS stimulation (P < 0.05), exacerbating inflammatory responses. LPS stimulation aggravated the apoptosis of MH-S cells with H9N2 IAV infection. Interestingly, LPS stimulation influences H9N2 IAV replication and indirectly reduced H9N2 IAV replications in in vitro AMs. It implied that LPS should play an important role in the pathogenesis of H9N2 IAV and P. aeruginosa coinfection.

A target-cell limited model can reproduce influenza infection dynamics in hosts with differing immune responses

We consider a hierarchy of ordinary differential equation models that describe the within-host viral kinetics of influenza infections: the IR model explicitly accounts for an immune response to the virus, while the simpler, target-cell limited TEIV and TV models do not. We show that when the IR model is fitted to pooled experimental murine data of the viral load, fraction of dead cells, and immune response levels, its parameters values can be determined. However, if, as is common, only viral load data are available, we can estimate parameters of the TEIV and TV models but not the IR model. These results are substantiated by a structural and practical identifiability analysis. We then use the IR model to generate synthetic data representing infections in hosts whose immune responses differ. We fit the TV model to these synthetic datasets and show that it can reproduce the characteristic exponential increase and decay of viral load generated by the IR model. Furthermore, the values of the fitted parameters of the TV model can be mapped from the immune response parameters in the IR model. We conclude that, if only viral load data are available, a simple target-cell limited model can reproduce influenza infection dynamics and distinguish between hosts with differing immune responses.

Dissecting Phenotype from Genotype with Clinical Isolates of SARS-CoV-2 First Wave Variants

The emergence and availability of closely related clinical isolates of SARS-CoV-2 offers a unique opportunity to identify novel nonsynonymous mutations that may impact phenotype. Global sequencing efforts show that SARS-CoV-2 variants have emerged and then been replaced since the beginning of the pandemic, yet we have limited information regarding the breadth of variant-specific host responses. Using primary cell cultures and the K18-hACE2 mouse, we investigated the replication, innate immune response, and pathology of closely related, clinical variants circulating during the first wave of the pandemic. Mathematical modeling of the lung viral replication of four clinical isolates showed a dichotomy between two B.1. isolates with significantly faster and slower infected cell clearance rates, respectively. While isolates induced several common immune host responses to infection, one B.1 isolate was unique in the promotion of eosinophil-associated proteins IL-5 and CCL11. Moreover, its mortality rate was significantly slower. Lung microscopic histopathology suggested further phenotypic divergence among the five isolates showing three distinct sets of phenotypes: (i) consolidation, alveolar hemorrhage, and inflammation, (ii) interstitial inflammation/septal thickening and peribronchiolar/perivascular lymphoid cells, and (iii) consolidation, alveolar involvement, and endothelial hypertrophy/margination. Together these findings show divergence in the phenotypic outcomes of these clinical isolates and reveal the potential importance of nonsynonymous mutations in nsp2 and ORF8.

Influenza A virus modulation of Streptococcus pneumoniae infection using ex vivo transcriptomics in a human primary lung epithelial cell model reveals differential host glycoconjugate uptake and metabolism

Background

Streptococcus pneumoniae (Spn) is typically an asymptomatic colonizer of the nasopharynx but it also causes pneumonia and disseminated disease affecting various host anatomical sites. Transition from colonization to invasive disease is not well understood. Studies have shown that such a transition can occur as result of influenza A virus coinfection.

Methods

We investigated the pneumococcal (serotype 19F, strain EF3030) and host transcriptomes with and without influenza A virus (A/California/07 2009 pH1N1) infection at this transition. This was done using primary, differentiated Human Bronchial Epithelial Cells (nHBEC) in a transwell monolayer model at an Air-Liquid Interface (ALI), with multispecies deep RNA-seq.

Results

Distinct pneumococcal gene expression profiles were observed in the presence and absence of influenza. Influenza coinfection allowed for significantly greater pneumococcal growth and triggered the differential expression of bacterial genes corresponding to multiple metabolic pathways; in totality suggesting a fundamentally altered bacterial metabolic state and greater nutrient availability when coinfecting with influenza. Surprisingly, nHBEC transcriptomes were only modestly perturbed by infection with EF3030 alone in comparison to that resulting from Influenza A infection or coinfection, which had drastic alterations in thousands of genes. Influenza infected host transcriptomes suggest significant loss of ciliary function in host nHBEC cells.

Conclusions

Influenza A virus infection of nHBEC promotes pneumococcal infection. One reason for this is an altered metabolic state by the bacterium, presumably due to host components made available as result of viral infection. Influenza infection had a far greater impact on the host response than did bacterial infection alone, and this included down regulation of genes involved in expressing cilia. We conclude that influenza infection promotes a pneumococcal metabolic shift allowing for transition from colonization to disseminated disease.

Synergistic Protection against Secondary Pneumococcal Infection by Human Monoclonal Antibodies Targeting Distinct Epitopes

Streptococcus pneumoniae persists as a leading cause of bacterial pneumonia despite the widespread use of polysaccharide-based vaccines. The limited serotype coverage of current vaccines has led to increased incidence of nonvaccine serotypes, as well as an increase in antibiotic resistance among these serotypes. Pneumococcal infection often follows a primary viral infection such as influenza virus, which hinders host defense and results in bacterial spread to the lungs. We previously isolated human monoclonal Abs (mAbs) against the conserved surface Ag pneumococcal histidine triad protein D (PhtD), and we demonstrated that mAbs to this Ag are protective against lethal pneumococcal challenge prophylactically and therapeutically. In this study, we elucidated the mechanism of protection of a protective anti-pneumococcal human mAb, PhtD3, which is mediated by the presence of complement and macrophages in a mouse model of pneumococcal infection. Treatment with mAb PhtD3 reduced blood and lung bacterial burden in mice, and mAb PhtD3 is able to bind to bacteria in the presence of the capsular polysaccharide, indicating exposure of surface PhtD on encapsulated bacteria. In a mouse model of secondary pneumococcal infection, protection mediated by mAb PhtD3 and another mAb targeting a different epitope, PhtD7, was reduced; however, robust protection was restored by combining mAb PhtD3 with mAb PhtD7, indicating a synergistic effect. Overall, these studies provide new insights into anti-pneumococcal mAb protection and demonstrate, to our knowledge, for the first time, that mAbs to pneumococcal surface proteins can protect against secondary pneumococcal infection in the mouse model.

Predicting Influenza A Virus Infection in the Lung from Hematological Data with Machine Learning

The tracking of pathogen burden and host responses with minimally invasive methods during respiratory infections is central for monitoring disease development and guiding treatment decisions. Utilizing a standardized murine model of respiratory influenza A virus (IAV) infection, we developed and tested different supervised machine learning models to predict viral burden and immune response markers, i.e., cytokines and leukocytes in the lung, from hematological data. We performed independently in vivo infection experiments to acquire extensive data for training and testing of the models. We show here that lung viral load, neutrophil counts, cytokines (such as gamma interferon [IFN-γ] and interleukin 6 [IL-6]), and other lung infection markers can be predicted from hematological data. Furthermore, feature analysis of the models showed that blood granulocytes and platelets play a crucial role in prediction and are highly involved in the immune response against IAV. The proposed in silico tools pave the path toward improved tracking and monitoring of influenza virus infections and possibly other respiratory infections based on minimally invasively obtained hematological parameters. IMPORTANCE During the course of respiratory infections such as influenza, we do have a very limited view of immunological indicators to objectively and quantitatively evaluate the outcome of a host. Methods for monitoring immunological markers in a host's lungs are invasive and expensive, and some of them are not feasible to perform. Using machine learning algorithms, we show for the first time that minimally invasively acquired hematological parameters can be used to infer lung viral burden, leukocytes, and cytokines following influenza virus infection in mice. The potential of the framework proposed here consists of a new qualitative vision of the disease processes in the lung compartment as a noninvasive tool.

Gut microbial community supplementation and reduction modulates African armyworm susceptibility to a baculovirus

Gut microbiota stimulates the immune system and inhibits pathogens, and thus, it is critical for disease prevention. Probiotics represent an effective alternative to antibiotics used for the therapy and prevention of bacterial diseases. Probiotic bacteria are commonly used in vertebrates, although their use in invertebrates is still rare. We manipulated the gut microbiome of the African Armyworm (Spodoptera exempta Walker) using antibiotics and field-collected frass, in an attempt to understand the interactions of the gut microbiome with the nucleopolyhedrovirus, SpexNPV. We found that S. exempta individuals with supplemented gut microbiome were significantly more resistant to SpexNPV, relative to those with a typical laboratory gut microbiome. Illumina MiSeq sequencing revealed the bacterial phyla in the S. exempta gut belonged to 28 different classes. Individuals with an increased abundance of Lactobacillales had a higher probability of surviving viral infection. In contrast, there was an increased abundance of Enterobacteriales and Pseudomonadales in individuals dying from viral infection, corresponding with decreased abundance of these two Orders in surviving caterpillars, suggesting a potential role for them in modulating the interaction between the host and its pathogen. These results have important implications for laboratory studies testing biopesticides.

Gastrointestinal helminths increase Bordetella bronchiseptica shedding and host variation in supershedding

Co-infected hosts, individuals that carry more than one infectious agent at any one time, have been suggested to facilitate pathogen transmission, including the emergence of supershedding events. However, how the host immune response mediates the interactions between co-infecting pathogens and how these affect the dynamics of shedding remains largely unclear. We used laboratory experiments and a modeling approach to examine temporal changes in the shedding of the respiratory bacterium Bordetella bronchiseptica in rabbits with one or two gastrointestinal helminth species. Experimental data showed that rabbits co-infected with one or both helminths shed significantly more B. bronchiseptica, by direct contact with an agar petri dish, than rabbits with bacteria alone. Co-infected hosts generated supershedding events of higher intensity and more frequently than hosts with no helminths. To explain this variation in shedding an infection-immune model was developed and fitted to rabbits of each group. Simulations suggested that differences in the magnitude and duration of shedding could be explained by the effect of the two helminths on the relative contribution of neutrophils and specific IgA and IgG to B. bronchiseptica neutralization in the respiratory tract. However, the interactions between infection and immune response at the scale of analysis that we used could not capture the rapid variation in the intensity of shedding of every rabbit. We suggest that fast and local changes at the level of respiratory tissue probably played a more important role. This study indicates that co-infected hosts are important source of variation in shedding, and provides a quantitative explanation into the role of helminths to the dynamics of respiratory bacterial infections.

The Influence of Influenza Virus Infections in Patients with Chronic Obstructive Pulmonary Disease

Introduction

Chronic obstructive pulmonary disease (COPD) is a common disease and is preventable and treatable. A previous study showed that influenza virus infections were also associated with the risk of acute exacerbation in patients with COPD, and other studies showed that the influenza virus might increase the risk of stroke. However, studies on the influence of influenza infection among COPD patients are limited. In this study, we review the role of influenza infection in contributing to mortality, pneumonia, respiratory failure, COPD acute exacerbation, and ischemic stroke among COPD patients.

Materials and Methods

We performed a population-based cohort study of COPD patients using data from Taiwan between January 1, 2011, and December 31, 2019. We excluded patients with lung cancer, lung transplantation and asthma. We also excluded patients who lacked COPD medication prescriptions and those treated with anti-influenza drugs without flu diagnosis records. Patients with missing or incomplete data were also excluded from the study cohort.

Results

After 1:1 matching by age, sex, COPD duration, diagnosed years and comorbidities, we enrolled 10,855 cases and controls for further analysis. The risks of pneumonia, respiratory failure, COPD acute exacerbation, and ischemic stroke were 1.770 (95% CI=1.638–1.860; P<0.0001), 1.097 (95% CI=1.008–1.194; P=0.0319), 1.338 (95% CI=1.248–1.435; P<0.0001), and 1.134 (95% CI=1.039–1.239, P=0.0051), respectively, in the influenza infection group compared with COPD patients without influenza infection.

Conclusion

Influenza infections are linked to an increased risk of ischemic stroke, pneumonia, respiratory failure, and COPD acute exacerbation among COPD patients. In conclusion, patients with COPD need to be closely monitored after having an influenza infection.

Increased virus dissemination leads to enhanced lung injury but not inflammation during influenza-associated secondary bacterial infection

Secondary bacterial infections increase influenza-related morbidity and mortality, particularly if acquired after 5-7 d from the viral onset. Synergistic host responses and direct pathogen-pathogen interactions are thought to lead to a state of hyperinflammation, but the kinetics of the lung pathology have not yet been detailed, and identifying the contribution of different mechanisms to disease is difficult because these may change over time. To address this gap, we examined host-pathogen and lung pathology dynamics following a secondary bacterial infection initiated at different time points after influenza within a murine model. We then used a mathematical approach to quantify the increased virus dissemination in the lung, coinfection time-dependent bacterial kinetics, and virus-mediated and postbacterial depletion of alveolar macrophages. The data showed that viral loads increase regardless of coinfection timing, which our mathematical model predicted and histomorphometry data confirmed was due to a robust increase in the number of infected cells. Bacterial loads were dependent on the time of coinfection and corresponded to the level of IAV-induced alveolar macrophage depletion. Our mathematical model suggested that the additional depletion of these cells following the bacterial invasion was mediated primarily by the virus. Contrary to current belief, inflammation was not enhanced and did not correlate with neutrophilia. The enhanced disease severity was correlated to inflammation, but this was due to a nonlinearity in this correlation. This study highlights the importance of dissecting nonlinearities during complex infections and demonstrated the increased dissemination of virus within the lung during bacterial coinfection and simultaneous modulation of immune responses during influenza-associated bacterial pneumonia.

Type I IFN Signaling Is Essential for Preventing IFN-γ Hyperproduction and Subsequent Deterioration of Antibacterial Immunity during Postinfluenza Pneumococcal Infection

Postinfluenza bacterial pneumonia is a significant cause of hospitalization and death in humans. The mechanisms underlying this viral and bacterial synergy remain incompletely understood. Recent evidence indicates that influenza-induced IFNs, particularly type I IFN (IFN-I) and IFN-γ, suppress antibacterial defenses. In this study, we have investigated the relative importance and interplay of IFN-I and IFN-γ pathways in influenza-induced susceptibility to Streptococcus pneumoniae infection. Using gene-deficient mouse models, as well as in vivo blocking Abs, we show that both IFN-I and IFN-γ signaling pathways contribute to the initial suppression of antibacterial immunity; however, IFN-γ plays a dominant role in the disease deterioration, in association with increased TNF-α production and alveolar macrophage (AM) depletion. We have previously shown that IFN-γ impairs AM antibacterial function and thereby acute bacterial clearance. The findings in this study indicate that IFN-γ signaling also impairs AM viability and αβ T cell recruitment during the progression of influenza/S. pneumoniae coinfection. Macrophages insensitive to IFN-γ mice express a dominant-negative mutant IFN-γR in mononuclear phagocytes. Interestingly, macrophages insensitive to IFN-γ mice exhibited significantly improved recovery and survival from coinfection, despite delayed bacterial clearance. Importantly, we demonstrate that IFN-I receptor signaling is essential for preventing IFN-γ hyperproduction and animal death during the progression of postinfluenza pneumococcal pneumonia.

The Contribution of Viral Proteins to the Synergy of Influenza and Bacterial Co-Infection

A severe course of acute respiratory disease caused by influenza A virus (IAV) infection is often linked with subsequent bacterial superinfection, which is difficult to cure. Thus, synergistic influenza-bacterial co-infection represents a serious medical problem. The pathogenic changes in the infected host are accelerated as a consequence of IAV infection, reflecting its impact on the host immune response. IAV infection triggers a complex process linked with the blocking of innate and adaptive immune mechanisms required for effective antiviral defense. Such disbalance of the immune system allows for easier initiation of bacterial superinfection. Therefore, many new studies have emerged that aim to explain why viral-bacterial co-infection can lead to severe respiratory disease with possible fatal outcomes. In this review, we discuss the key role of several IAV proteins-namely, PB1-F2, hemagglutinin (HA), neuraminidase (NA), and NS1-known to play a role in modulating the immune defense of the host, which consequently escalates the development of secondary bacterial infection, most often caused by Streptococcus pneumoniae. Understanding the mechanisms leading to pathological disorders caused by bacterial superinfection after the previous viral infection is important for the development of more effective means of prevention; for example, by vaccination or through therapy using antiviral drugs targeted at critical viral proteins.

Time-Dependent Increase in Susceptibility and Severity of Secondary Bacterial Infections During SARS-CoV-2

Secondary bacterial infections can exacerbate SARS-CoV-2 infection, but their prevalence and impact remain poorly understood. Here, we established that a mild to moderate infection with the SARS-CoV-2 USA-WA1/2020 strain increased the risk of pneumococcal (type 2 strain D39) coinfection in a time-dependent, but sex-independent, manner in the transgenic K18-hACE2 mouse model of COVID-19. Bacterial coinfection increased lethality when the bacteria was initiated at 5 or 7 d post-virus infection (pvi) but not at 3 d pvi. Bacterial outgrowth was accompanied by neutrophilia in the groups coinfected at 7 d pvi and reductions in B cells, T cells, IL-6, IL-15, IL-18, and LIF were present in groups coinfected at 5 d pvi. However, viral burden, lung pathology, cytokines, chemokines, and immune cell activation were largely unchanged after bacterial coinfection. Examining surviving animals more than a week after infection resolution suggested that immune cell activation remained high and was exacerbated in the lungs of coinfected animals compared with SARS-CoV-2 infection alone. These data suggest that SARS-CoV-2 increases susceptibility and pathogenicity to bacterial coinfection, and further studies are needed to understand and combat disease associated with bacterial pneumonia in COVID-19 patients.

Voyich J. Examining the Executioners, Influenza Associated Secondary Bacterial Pneumonia

Influenza infections typically present mild to moderate morbidities in immunocompetent host and are often resolved within 14 days of infection onset. Death from influenza infection alone is uncommon; however, antecedent influenza infection often leads to an increased susceptibility to secondary bacterial pneumonia. Bacterial pneumonia following viral infection exhibits mortality rates greater than 10-fold of those of influenza alone. Furthermore, bacterial pneumonia has been identified as the major contributor to mortality during each of the previous four influenza pandemics. Streptococcus pneumoniae, Staphylococcus aureus, Haemophilus influenzae, and Streptococcus pyogenes are the most prevalent participants in this pathology. Of note, these lung pathogens are frequently found as commensals of the upper respiratory tract. Herein we describe influenza-induced host-changes that lead to increased susceptibility to bacterial pneumonia, review virulence strategies employed by the most prevalent secondary bacterial pneumonia species, and highlight recent findings of bacterial sensing and responding to the influenza infected environment.

Mathematical Modeling Finds Disparate Interferon Production Rates Drive Strain-Specific Immunodynamics during Deadly Influenza Infection

The timing and magnitude of the immune response (i.e., the immunodynamics) associated with the early innate immune response to viral infection display distinct trends across influenza A virus subtypes in vivo. Evidence shows that the timing of the type-I interferon response and the overall magnitude of immune cell infiltration are both correlated with more severe outcomes. However, the mechanisms driving the distinct immunodynamics between infections of different virus strains (strain-specific immunodynamics) remain unclear. Here, computational modeling and strain-specific immunologic data are used to identify the immune interactions that differ in mice infected with low-pathogenic H1N1 or high-pathogenic H5N1 influenza viruses. Computational exploration of free parameters between strains suggests that the production rate of interferon is the major driver of strain-specific immune responses observed in vivo, and points towards the relationship between the viral load and lung epithelial interferon production as the main source of variance between infection outcomes. A greater understanding of the contributors to strain-specific immunodynamics can be utilized in future efforts aimed at treatment development to improve clinical outcomes of high-pathogenic viral strains.

Time-Dependent Increase in Susceptibility and Severity of Secondary Bacterial Infection during SARS-CoV-2 Infection

Secondary bacterial infections can exacerbate SARS-CoV-2 infection, but their prevalence and impact remain poorly understood. Here, we established that a mild to moderate SARS-CoV-2 infection increased the risk of pneumococcal coinfection in a time-dependent, but sexindependent, manner in the transgenic K18-hACE mouse model of COVID-19. Bacterial coinfection was not established at 3 d post-virus, but increased lethality was observed when the bacteria was initiated at 5 or 7 d post-virus infection (pvi). Bacterial outgrowth was accompanied by neutrophilia in the groups coinfected at 7 d pvi and reductions in B cells, T cells, IL-6, IL-15, IL-18, and LIF were present in groups coinfected at 5 d pvi. However, viral burden, lung pathology, cytokines, chemokines, and immune cell activation were largely unchanged after bacterial coinfection. Examining surviving animals more than a week after infection resolution suggested that immune cell activation remained high and was exacerbated in the lungs of coinfected animals compared with SARS-CoV-2 infection alone. These data suggest that SARS-CoV-2 increases susceptibility and pathogenicity to bacterial coinfection, and further studies are needed to understand and combat disease associated with bacterial pneumonia in COVID-19 patients.

Pandemic Influenza Infection Promotes Streptococcus pneumoniae Infiltration, Necrotic Damage, and Proteomic Remodeling in the Heart

For over a century, it has been reported that primary influenza infection promotes the development of a lethal form of bacterial pulmonary disease. More recently, pneumonia events caused by both viruses and bacteria have been directly associated with cardiac damage. Importantly, it is not known whether viral-bacterial synergy extends to extrapulmonary organs such as the heart. Using label-free quantitative proteomics and molecular approaches, we report that primary infection with pandemic influenza A virus leads to increased Streptococcus pneumoniae translocation to the myocardium, leading to general biological alterations. We also observed that each infection alone led to proteomic changes in the heart, and these were exacerbated in the secondary bacterial infection (SBI) model. Gene ontology analysis of significantly upregulated proteins showed increased innate immune activity, oxidative processes, and changes to ion homeostasis during SBI. Immunoblots confirmed increased complement and antioxidant activity in addition to increased expression of angiotensin-converting enzyme 2. Using an in vitro model of sequential infection in human cardiomyocytes, we observed that influenza enhances S. pneumoniae cytotoxicity by promoting oxidative stress enhancing bacterial toxin-induced necrotic cell death. Influenza infection was found to increase receptors that promote bacterial adhesion, such as polymeric immunoglobulin receptor and fibronectin leucine-rich transmembrane protein 1 in cardiomyocytes. Finally, mice deficient in programmed necrosis (i.e., necroptosis) showed enhanced innate immune responses, decreased virus-associated pathways, and promotion of mitochondrial function upon SBI. The presented results provide the first in vivo evidence that influenza infection promotes S. pneumoniae infiltration, necrotic damage, and proteomic remodeling of the heart. IMPORTANCE Adverse cardiac events are a common complication of viral and bacterial pneumonia. For over a century, it has been recognized that influenza infection promotes severe forms of pulmonary disease mainly caused by the bacterium Streptococcus pneumoniae. The extrapulmonary effects of secondary bacterial infections to influenza virus are not known. In the present study, we used a combination of quantitative proteomics and molecular approaches to assess the underlying mechanisms of how influenza infection promotes bacteria-driven cardiac damage and proteome remodeling. We further observed that programmed necrosis (i.e., necroptosis) inhibition leads to reduced damage and proteome changes associated with health.

Pathogenesis of Respiratory Viral and Fungal Coinfections

Individuals suffering from severe viral respiratory tract infections have recently emerged as "at risk" groups for developing invasive fungal infections. Influenza virus is one of the most common causes of acute lower respiratory tract infections worldwide. Fungal infections complicating influenza pneumonia are associated with increased disease severity and mortality, with invasive pulmonary aspergillosis being the most common manifestation. Strikingly, similar observations have been made during the current coronavirus disease 2019 (COVID-19) pandemic. The copathogenesis of respiratory viral and fungal coinfections is complex and involves a dynamic interplay between the host immune defenses and the virulence of the microbes involved that often results in failure to return to homeostasis. In this review, we discuss the main mechanisms underlying susceptibility to invasive fungal disease following respiratory viral infections. A comprehensive understanding of these interactions will aid the development of therapeutic modalities against newly identified targets to prevent and treat these emerging coinfections.

Klebsiella pneumoniae infection following H9N2 influenza A virus infection contributes to the development of pneumonia in mice

In this study, whether H9N2 influenza A virus (IAV) infection contributed to secondary Klebsiella pneumoniae infection was investigated. From post-infection onwards, clinical symptoms were monitored, examined and recorded daily for 11 days. As a result, no clinical signs were observed in the mice infected with single H9N2 IAV, implying that H9N2 IAV was less pathogenic to mice. Compared to single K. pneumonia infection, K. pneumoniae infection following H9N2 IAV infection exacerbates lung histopathological lesions and apoptosis, resulting in more severe diseases. Lung index of the mice with H9N2 IAV and K. pneumoniae co-infection was significantly higher than those in the other groups. Bacterial loads in the tissues in H9N2 IAV and K. pneumoniae co-infection group were significantly higher than those in the single K. pneumoniae infection group at 7 dpi. It demonstrated that prior H9N2 IAV infection contributed to K. pneumonia proliferation and delayed bacterial clearance in mice. Secondary K. pneumoniae infection influences seroconversion of anti-H9N2 antibody titers and the cytokine profiles. The findings demonstrated that H9N2 IAV infection facilitated secondary K. pneumonia infection, causing severe the diseases in mice.

Molecular detection of respiratory pathogens in community-acquired pneumonia involving adults

BACKGROUND

Community-acquired pneumonia (CAP) causes substantial morbidity and mortality in adults worldwide. The etiology of CAP often remains uncertain, and therapy is empirical. Thus, there is still room for improvement in the diagnosis of pneumonia.

METHODS

Adults aged >20 years who presented at the outpatient or emergency departments of Linkou and Keelung Chang Gung Memorial Hospital with CAP were prospectively included between November 2016 and December 2018. We collected respiratory specimens for culture and molecular testing and calculated the incidence rates of CAP according to pathogens.

RESULTS

Of 212 hospitalized adult patients with CAP, 69.3% were male, and the median age of the patients was 67.8 years. Bacterial pathogens were detected in 106 (50%) patients, viruses in 77 (36.3%), and fungal pathogens in 1 patient (0.5%). The overall detection rate (culture and molecular testing method) was 70.7% (n = 150). Traditional microbial culture yielded positive results in 36.7% (n = 78), molecular testing in 61.3% (n = 130). The most common pathogens were influenza (16.1%), followed by Klebsiella pneumoniae (14.1%), Pseudomonas aeruginosa (13.6%), human rhinovirus (11.8%), and Streptococcus pneumoniae (9.9%). Multiple pathogen co-infections accounted for 28.7% (n = 61), of which co-infection with K. pneumoniae and human rhinovirus comprised the largest proportion.

CONCLUSIONS

Molecular diagnostic testing could detect 23.6% more pathogens than traditional culture techniques. However, despite the current diagnostic tests, there is still the possibility that no pathogen was detected.

Quantifying dose-, strain-, and tissue-specific kinetics of parainfluenza virus infection

Human parainfluenza viruses (HPIVs) are a leading cause of acute respiratory infection hospitalization in children, yet little is known about how dose, strain, tissue tropism, and individual heterogeneity affects the processes driving growth and clearance kinetics. Longitudinal measurements are possible by using reporter Sendai viruses, the murine counterpart of HPIV 1, that express luciferase, where the insertion location yields a wild-type (rSeV-luc(M-F*)) or attenuated (rSeV-luc(P-M)) phenotype. Bioluminescence from individual animals suggests that there is a rapid increase in expression followed by a peak, biphasic clearance, and resolution. However, these kinetics vary between individuals and with dose, strain, and whether the infection was initiated in the upper and/or lower respiratory tract. To quantify the differences, we translated the bioluminescence measurements from the nasopharynx, trachea, and lung into viral loads and used a mathematical model together a nonlinear mixed effects approach to define the mechanisms distinguishing each scenario. The results confirmed a higher rate of virus production with the rSeV-luc(M-F*) virus compared to its attenuated counterpart, and suggested that low doses result in disproportionately fewer infected cells. The analyses indicated faster infectivity and infected cell clearance rates in the lung and that higher viral doses, and concomitantly higher infected cell numbers, resulted in more rapid clearance. This parameter was also highly variable amongst individuals, which was particularly evident during infection in the lung. These critical differences provide important insight into distinct HPIV dynamics, and show how bioluminescence data can be combined with quantitative analyses to dissect host-, virus-, and dose-dependent effects.

Human parainfluenza viruses (HPIVs) cause acute respiratory infections and can lead to the hospitalization of children. HPIV infection severity may vary due to dose, strain, patient, and whether the infection initiates within the upper or lower respiratory tract. There is a need to determine how the rates of virus spread and clearance change in different infection scenarios in order to better understand varying clinical manifestations. The significance of our research is in identifying the dominant mechanisms driving strain-, dose-, and tissue-specific HPIV infection kinetics, and in pairing bioluminescence data with quantitative analyses to determine how the same virus can yield patient-specific outcomes. This work enhances our understanding of HPIV infection and broadens our knowledge viral dynamics in the upper and lower respiratory tracts.

Dynamically linking influenza virus infection kinetics, lung injury, inflammation, and disease severity

Influenza viruses cause a significant amount of morbidity and mortality. Understanding host immune control efficacy and how different factors influence lung injury and disease severity are critical. We established and validated dynamical connections between viral loads, infected cells, CD8⁺ T cells, lung injury, inflammation, and disease severity using an integrative mathematical model-experiment exchange. Our results showed that the dynamics of inflammation and virus-inflicted lung injury are distinct and nonlinearly related to disease severity, and that these two pathologic measurements can be independently predicted using the model-derived infected cell dynamics. Our findings further indicated that the relative CD8⁺ T cell dynamics paralleled the percent of the lung that had resolved with the rate of CD8⁺ T cell-mediated clearance rapidly accelerating by over 48,000 times in 2 days. This complimented our analyses showing a negative correlation between the efficacy of innate and adaptive immune-mediated infected cell clearance, and that infection duration was driven by CD8⁺ T cell magnitude rather than efficacy and could be significantly prolonged if the ratio of CD8⁺ T cells to infected cells was sufficiently low. These links between important pathogen kinetics and host pathology enhance our ability to forecast disease progression, potential complications, and therapeutic efficacy.

Microbial co-infections in COVID-19: Associated microbiota and underlying mechanisms of pathogenesis

The novel coronavirus infectious disease-2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has traumatized the whole world with the ongoing devastating pandemic. A plethora of microbial domains including viruses (other than SARS-CoV-2), bacteria, archaea and fungi have evolved together, and interact in complex molecular pathogenesis along with SARS-CoV-2. However, the involvement of other microbial co-pathogens and underlying molecular mechanisms leading to extortionate ailment in critically ill COVID-19 patients has yet not been extensively reviewed. Although, the incidence of co-infections could be up to 94.2% in laboratory-confirmed COVID-19 cases, the fate of co-infections among SARS-CoV-2 infected hosts often depends on the balance between the host's protective immunity and immunopathology. Predominantly identified co-pathogens of SARS-CoV-2 are bacteria such as Streptococcus pneumoniae, Staphylococcus aureus, Klebsiella pneumoniae, Haemophilus influenzae, Mycoplasma pneumoniae, Acinetobacter baumannii, Legionella pneumophila and Clamydia pneumoniae followed by viruses including influenza, coronavirus, rhinovirus/enterovirus, parainfluenza, metapneumovirus, influenza B virus, and human immunodeficiency virus. The cross-talk between co-pathogens (especially lung microbiomes), SARS-CoV-2 and host is an important factor that ultimately increases the difficulty of diagnosis, treatment, and prognosis of COVID-19. Simultaneously, co-infecting microbiotas may use new strategies to escape host defense mechanisms by altering both innate and adaptive immune responses to further aggravate SARS-CoV-2 pathogenesis. Better understanding of co-infections in COVID-19 is critical for the effective patient management, treatment and containment of SARS-CoV-2. This review therefore necessitates the comprehensive investigation of commonly reported microbial co-pathogens amid COVID-19, their transmission pattern along with the possible mechanism of co-infections and outcomes. Thus, identifying the possible co-pathogens and their underlying molecular mechanisms during SARS-CoV-2 pathogenesis may shed light in developing diagnostics, appropriate curative and preventive interventions for suspected SARS-CoV-2 respiratory infections in the current pandemic.

Babaodan controls excessive immune responses and may represent a cytokine-targeted agent suitable for COVID-19 treatment

It has become evident that the actions of pro-inflammatory cytokines and/or the development of a cytokine storm are responsible for the occurrence of severe COVID-19 during SARS-CoV-2 infection. Although immunomodulatory mechanisms vary among viruses, the activation of multiple TLRs that occurs primarily through the recruitment of adapter proteins such as MyD88 and TRIF contributes to the induction of a cytokine storm. Based on this, controlling the robust production of pro-inflammatory cytokines by macrophages may be applicable as a cellular approach to investigate potential cytokine-targeted therapies against COVID-19. In the current study, we utilized TLR2/MyD88 and TLR3/TRIF co-activated macrophages and evaluated the anti-cytokine storm effect of the traditional Chinese medicine (TCM) formula Babaodan (BBD). An RNA-seq-based transcriptomic approach was used to determine the molecular mode of action. Additionally, we evaluated the anti-inflammatory activity of BBD in vivo using a mouse model of post-viral bacterial infection-induced pneumonia and seven severely ill COVID-19 patients. Our study reveals the protective role of BBD against excessive immune responses in macrophages, where the underlying mechanisms involve the inhibition of the NF-κB and MAPK signaling pathways. In vivo, BBD significantly inhibited the release of IL-6, thus resulting in increased survival rates in mice. Based on limited data, we demonstrated that severely ill COVID-19 patients benefited from BBD treatment due to a reduction in the overproduction of IL-6. In conclusion, our study indicated that BBD controls excessive immune responses and may thus represent a cytokine-targeted agent that could be considered to treating COVID-19.

Dynamic Pneumococcal Genetic Adaptations Support Bacterial Growth and Inflammation during Coinfection with Influenza

Streptococcus pneumoniae (pneumococcus) is one of the primary bacterial pathogens that complicates influenza virus infections. These bacterial coinfections increase influenza-associated morbidity and mortality through a number of immunological and viral-mediated mechanisms, but the specific bacterial genes that contribute to postinfluenza pathogenicity are not known. Here, we used genome-wide transposon mutagenesis (Tn-Seq) to reveal bacterial genes that confer improved fitness in influenza virus-infected hosts. The majority of the 32 genes identified are involved in bacterial metabolism, including nucleotide biosynthesis, amino acid biosynthesis, protein translation, and membrane transport. We generated mutants with single-gene deletions (SGD) of five of the genes identified, SPD1414, SPD2047 (cbiO1), SPD0058 (purD), SPD1098, and SPD0822 (proB), to investigate their effects on in vivo fitness, disease severity, and host immune responses. The growth of the SGD mutants was slightly attenuated in vitro and in vivo, but each still grew to high titers in the lungs of mock- and influenza virus-infected hosts. Despite high bacterial loads, mortality was significantly reduced or delayed with all SGD mutants. Time-dependent reductions in pulmonary neutrophils, inflammatory macrophages, and select proinflammatory cytokines and chemokines were also observed. Immunohistochemical staining further revealed altered neutrophil distribution with reduced degeneration in the lungs of influenza virus-SGD mutant-coinfected animals. These studies demonstrate a critical role for specific bacterial genes and for bacterial metabolism in driving virulence and modulating immune function during influenza-associated bacterial pneumonia.

Human TRIM14 protects transgenic mice from influenza A viral infection without activation of other innate immunity pathways

TRIM14 is an important component of innate immunity that defends organism from various viruses. It was shown that TRIM14 restricted influenza A virus (IAV) infection in cell cultures in an interferon-independent manner. However, it remained unclear whether TRIM14 affects IAV reproduction and immune system responses upon IAV infection in vivo. In order to investigate the effects of TRIM14 at the organismal level we generated transgenic mice overexpressing human TRIM14 gene. We found that IAV reproduction was strongly inhibited in lungs of transgenic mice, resulting in the increased survival of transgenic animals. Strikingly, upon IAV infection, the transcription of genes encoding interferons, IL-6, IL-1β, and TNFα was notably weaker in lungs of transgenic animals than that in control mice, thus indicating the absence of significant induction of interferon and inflammatory responses. In spleen of transgenic mice, where TRIM14 was unexpectedly downregulated, upon IAV infection the transcription of genes encoding interferons was oppositely increased. Therefore, we demonstrated the key role of TRIM14 in anti-IAV protection in the model organism that is realized without noticeable activation of other innate immune system pathways.

Virus-Induced Changes of the Respiratory Tract Environment Promote Secondary Infections With Streptococcus pneumoniae

Secondary bacterial infections enhance the disease burden of influenza infections substantially. Streptococcus pneumoniae (the pneumococcus) plays a major role in the synergism between bacterial and viral pathogens, which is based on complex interactions between the pathogen and the host immune response. Here, we discuss mechanisms that drive the pathogenesis of a secondary pneumococcal infection after an influenza infection with a focus on how pneumococci senses and adapts to the influenza-modified environment. We briefly summarize what is known regarding secondary bacterial infection in relation to COVID-19 and highlight the need to improve our current strategies to prevent and treat viral bacterial coinfections.

Streptococcus pneumoniae serotype 22F infection in respiratory syncytial virus infected neonatal lambs enhances morbidity

Respiratory syncytial virus (RSV) is the primary cause of viral bronchiolitis resulting in hospitalization and a frequent cause of secondary respiratory bacterial infection, especially by Streptococcus pneumoniae (Spn) in infants. While murine studies have demonstrated enhanced morbidity during a viral/bacterial co-infection, human meta-studies have conflicting results. Moreover, little knowledge about the pathogenesis of emerging Spn serotype 22F, especially the co-pathologies between RSV and Spn, is known. Here, colostrum-deprived neonate lambs were divided into four groups. Two of the groups were nebulized with RSV M37, and the other two groups were mock nebulized. At day three post-RSV infection, one RSV group (RSV/Spn) and one mock-nebulized group (Spn only) were inoculated with Spn intratracheally. At day six post-RSV infection, bacterial/viral loads were assessed along with histopathology and correlated with clinical symptoms. Lambs dually infected with RSV/Spn trended with higher RSV titers, but lower Spn. Additionally, lung lesions were observed to be more frequent in the RSV/Spn group characterized by increased interalveolar wall thickness accompanied by neutrophil and lymphocyte infiltration and higher myeloperoxidase. Despite lower Spn in lungs, co-infected lambs had more significant morbidity and histopathology, which correlated with a different cytokine response. Thus, enhanced disease severity during dual infection may be due to lesion development and altered immune responses rather than bacterial counts.

Pneumococcal carriage in children with COVID-19

Background: SARS-CoV-2 is the new virus, and Streptococcus pneumoniae is one of the most important pathogens affecting humans. However, we do not yet know whether these microorganisms interact. Thus, we aimed to evaluate the relationship between Streptococcus pneumoniae and SARS-CoV-2 in pediatric patients.Methods: This study was conducted retrospectively by means of medical records of pediatric patients who were tested for SARS-CoV-2 between March 11 and June 04, 2020, in the University of Health Sciences, Ankara Educating and Training Hospital and Hacettepe University Faculty of Medicine.Results: We evaluated 829 pediatric patients for S. pneumoniae and SARS-CoV-2 from their nasopharyngeal specimen. Of 115 children positive for SARS-CoV-2, 32.2% had a positive S. pneumoniae test, whereas of 714 children negative for SARS-CoV-2, 14.1% had a positive S. pneumoniae test (p < .01). We compared patients with positive vs. negative SARS-CoV-2 tests according to S. pneumoniae positivity There were no statistically significant differences in terms of gender, underlying disease, fever, cough, leukocytosis, lymphopenia, increased CRP, increased procalcitonin, findings of chest x-ray, severity of disease, and treatment.Conclusion: The nasopharyngeal S. pneumoniae carriage rate in patients with COVID-19 was higher than in non-infected children, while S. pneumoniae carriage did not affect the course of COVID-19 disease. Pneumococcal vaccination is significant, such that we do not know the outcomes of increased pneumococcal carriage for the upcoming months of pandemic.

Exacerbation of disease by intranasal liquid administration following influenza virus infection in mice

Although numerous studies have clarified the synergistic pathogenesis in mouse models of influenza A virus (IAV)-associated dual infections, fewer studies have investigated the influence of intranasal liquid administration on the disease. This study explored the effects of intranasal PBS administration in mouse models of mimic IAV dual infection and the infectious dose of IAV that caused equivalent pathogenesis in different dual infection models. Weights, survival rates, virus loads, lung indexes and lung pathology were compared. We demonstrated that intranasal PBS administration following H1N1 or H3N2 infection increased weight loss, mortality, virus replication and lung damage. No difference was observed if the order was reversed or PBS was given simultaneously with IAV. To induce equivalent virulence, a 20-fold difference in the infectious dose was needed when the H3N2-PBS superinfection and H3N2-PBS coinfection or PBS-H3N2 superinfection groups were compared. Our study demonstrated that the unfavourable effect of intranasal liquid administration should not be neglected and that both the strain and infectious dose of IAV should be considered to avoid an illusion of synergistic pathogenicity when establishing IAV-associated dual infection model. A 20-fold lower dose than that of coinfection may be a better choice for secondary infection following IAV.

Molecular pathogenesis of secondary bacterial infection associated to viral infections including SARS-CoV-2

Secondary bacterial infections are commonly associated with prior or concomitant respiratory viral infections. Viral infections damage respiratory airways and simultaneously defects both innate and acquired immune response that provides a favorable environment for bacterial growth, adherence, and facilitates invasion into healthy sites of the respiratory tract. Understanding the molecular mechanism of viral-induced secondary bacterial infections will provide us a chance to develop novel and effective therapeutic approaches for disease prevention. The present study describes details about the secondary bacterial infection during viral infections and their immunological changes.The outcome of discussion avails an opportunity to understand possible secondary bacterial infections associated with novel SARS-CoV-2, presently causing pandemic outbreak COVID-19.

Leveraging Computational Modeling to Understand Infectious Diseases

Purpose of Review

Computational and mathematical modeling have become a critical part of understanding in-host infectious disease dynamics and predicting effective treatments. In this review, we discuss recent findings pertaining to the biological mechanisms underlying infectious diseases, including etiology, pathogenesis, and the cellular interactions with infectious agents. We present advances in modeling techniques that have led to fundamental disease discoveries and impacted clinical translation.

Recent Findings

Combining mechanistic models and machine learning algorithms has led to improvements in the treatment of Shigella and tuberculosis through the development of novel compounds. Modeling of the epidemic dynamics of malaria at the within-host and between-host level has afforded the development of more effective vaccination and antimalarial therapies. Similarly, in-host and host-host models have supported the development of new HIV treatment modalities and an improved understanding of the immune involvement in influenza. In addition, large-scale transmission models of SARS-CoV-2 have furthered the understanding of coronavirus disease and allowed for rapid policy implementations on travel restrictions and contract tracing apps.

Summary

Computational modeling is now more than ever at the forefront of infectious disease research due to the COVID-19 pandemic. This review highlights how infectious diseases can be better understood by connecting scientists from medicine and molecular biology with those in computer science and applied mathematics.

Effect of Vitamin A Deficiency in Dysregulating Immune Responses to Influenza Virus and Increasing Mortality Rates After Bacterial Coinfections

BACKGROUND

Secondary bacterial coinfections are ranked as a leading cause of hospitalization and morbid conditions associated with influenza. Because vitamin A deficiency (VAD) and insufficiency are frequent in both developed and developing countries, we asked how VAD influences coinfection severity.

METHODS

VAD and control mice were infected with influenza virus for evaluation of inflammatory cytokines, cellular immune responses, and viral clearance. Influenza-infected mice were coinfected with Streptococcus pneumoniae to study weight loss and survival.

RESULTS

Naive VAD mouse lungs exhibited dysregulated immune function. Neutrophils were enhanced in frequency and there was a significant reduction in RANTES (regulated on activation of normal T cells expressed and secreted), a chemokine instrumental in T-cell homing and recruitment. After influenza virus infection, VAD mice experienced failures in CD4+ T-cell recruitment and B-cell organization into lymphoid structures in the lung. VAD mice exhibited higher viral titers than controls and slow viral clearance. There were elevated levels of inflammatory cytokines and innate cell subsets in the lungs. However, arginase, a marker of alternatively activated M2 macrophages, was rare. When influenza-infected VAD animals were exposed to bacteria, they experienced a 100% mortality rate.

CONCLUSION

Data showed that VAD dysregulated the immune response. Consequently, secondary bacterial infections were 100% lethal in influenza-infected VAD mice.

Modelling within-host macrophage dynamics in influenza virus infection

Human respiratory disease associated with influenza virus infection is of significant public health concern. Macrophages, as part of the front line of host innate cellular defence, have been shown to play an important role in controlling viral replication. However, fatal outcomes of infection, as evidenced in patients infected with highly pathogenic viral strains, are often associated with prompt activation and excessive accumulation of macrophages. Activated macrophages can produce a large amount of pro-inflammatory cytokines, which leads to severe symptoms and at times death. However, the mechanism for rapid activation and excessive accumulation of macrophages during infection remains unclear. It has been suggested that the phenomena may arise from complex interactions between macrophages and influenza virus. In this work, we develop a novel mathematical model to study the relationship between the level of macrophage activation and the level of viral load in influenza infection. Our model combines a dynamic model of viral infection, a dynamic model of macrophages and the essential interactions between the virus and macrophages. Our model predicts that the level of macrophage activation can be negatively correlated with the level of viral load when viral infectivity is sufficiently high. We further identify that temporary depletion of resting macrophages in response to viral infection is a major driver in our model for the negative relationship between the level of macrophage activation and viral load, providing new insight into the mechanisms that regulate macrophage activation. Our model serves as a framework to study the complex dynamics of virus-macrophage interactions and provides a mechanistic explanation for existing experimental observations, contributing to an enhanced understanding of the role of macrophages in influenza viral infection.

Influenza Infection Induces Alveolar Macrophage Dysfunction and Thereby Enables Noninvasive Streptococcus pneumoniae to Cause Deadly Pneumonia

Secondary Streptococcus pneumoniae infection is a significant cause of morbidity and mortality during influenza epidemics and pandemics. Multiple pathogenic mechanisms, such as lung epithelial damage and dysregulation of neutrophils and alveolar macrophages (AMs), have been suggested to contribute to the severity of disease. However, the fundamental reasons for influenza-induced susceptibility to secondary bacterial pneumonia remain unclear. In this study, we revisited these controversies over key pathogenic mechanisms in a lethal model of secondary bacterial pneumonia with an S. pneumoniae strain that is innocuous to mice in the absence of influenza infection. Using a series of in vivo models, we demonstrate that rather than a systemic suppression of immune responses or neutrophil function, influenza infection activates IFN-γR signaling and abrogates AM-dependent bacteria clearance and thereby causes extreme susceptibility to pneumococcal infection. Importantly, using mice carrying conditional knockout of Ifngr1 gene in different myeloid cell subsets, we demonstrate that influenza-induced IFN-γR signaling in AMs impairs their antibacterial function, thereby enabling otherwise noninvasive S. pneumoniae to cause deadly pneumonia.