Tatsuya Shirai

Introduction. Human bocavirus 1 (HBoV1) is a member of Bocaparvovirus primate1 and is associated with paediatric respiratory infections. Although genetic grouping has been described, it remains unclear whether temporal genetic changes occur among clinically circulating HBoV1 strains. Hypothesis/Gap Statement. HBoV1 shows limited genetic diversity, but temporal genetic changes may occur in circulating strains. Aim. To investigate whether temporal genetic changes are present in HBoV1 isolates collected in Fukushima, Japan, between 2018 and 2024. Methodology. Nasopharyngeal swabs were collected from paediatric inpatients with acute respiratory infections. Thirty-two HBoV1 isolates were obtained using air–liquid interface cultures of human bronchial/tracheal epithelial cells. Nearly complete genomes were sequenced by next-generation sequencing and analysed together with additional reference sequences (total n =100, including outgroups) using phylogenetic and time-scaled methods. Results. Phylogenetic analyses classified the 32 Fukushima isolates into Group 1 ( n =12) and Group 2 ( n =20). Group 2 predominated in 2018, Group 1 from 2019 to 2021 and Group 2 again from 2022 to 2024, indicating temporal shifts in circulating strains. The average number of nucleotide differences among HBoV1 genomes was 13.9 (maximum 55), with Groups 1 and 2 diverging around 2004–2005. Divergence was concentrated in the VP genes, and synonymous substitutions within VP genes overlapped the ORFx reading frame, leading to distinct amino acid differences in ORFx. Conclusion. Clinically circulating HBoV1 undergoes temporal genetic change, with group differentiation determined primarily by VP genes and uniquely by ORFx at the amino acid level. These findings suggest a potential biological role for ORFx in the HBoV1 life cycle. Understanding these temporal genetic shifts is important for enhancing the accuracy of molecular surveillance tools, particularly for distinguishing genetically diverse HBoV1 strains.

Human parainfluenza virus type 2 (HPIV2) is a clinically significant respiratory pathogen, which highlights the necessity of studies on its molecular evolution. This study investigated the evolutionary dynamics, phylodynamics, and structural characteristics of the HPIV2 fusion (F) gene using a comprehensive dataset spanning multiple decades and geographic regions. Phylogenetic analyses revealed two distinct clusters of HPIV2 F gene sequences, which were estimated to have diverged from a common ancestor approximately a century ago. Cluster 1 demonstrated a higher evolutionary rate and genetic diversity compared to the more stable cluster 2. Bayesian Skyline Plot analyses indicated a significant increase in the effective population size of the F gene between 2005 and 2015; potentially linked to enhanced diagnostic and surveillance capabilities. Structural modeling identified conserved conformational epitopes predominantly in the apex and stalk regions of the F protein. These findings underscore the evolutionary constraints and antigenic landscape of the HPIV2 F protein.

Human sapovirus (HuSaV) is a significant cause of gastroenteritis. This study aims to analyze the evolutionary dynamics of the RNA-dependent RNA polymerase (RdRp) and capsid (VP1) genes of the HuSaV GI.1 and GI.2 genotypes between 1976 and 2020. Using bioinformatics tools such as the Bayesian phylogenetics software BEAST 2 package (v.2.7.6), we constructed time-scale evolutionary trees based on the gene sequences. Most of the recent common ancestors (MRCAs) of the RdRp region and VP1 gene in the present HuSaV GI.1 diverged around 1930 and 1933, respectively. The trees of the HuSaV GI.1 RdRp region and VP1 gene were divided into two clusters. Further, the MRCAs of the RdRp region and VP1 gene in HuSaV GI.2 diverged in 1960 and 1943, respectively. The evolutionary rates were higher for VP1 gene in HuSaV GI.1 than that in HuSaV GI.2, furthermore, were higher in GI.1 Cluster B than GI.1 Cluster A. In addition, a steep increase was observed in the time-scaled genome population size of the HuSaV GI.1 Cluster B. These results indicate that the HuSaV GI.1 Cluster B may be evolving more actively than other genotypes. The conformational B-cell epitopes were predicted with a higher probability in RdRp for GI.1 and in VP1 for GI.2, respectively. These results suggest that the RdRp region and VP1 gene in HuSaV GI.1 and GI.2 evolved uniquely. These findings suggest unique evolutionary patterns in the RdRp region and VP1 gene of HuSaV GI.1 and GI.2, emphasizing the need for a ‘One Health’ approach to better understand and combat this pathogen.

To better understand the molecular genetics of the Shiga toxin type 2 subunit A gene (stx2A gene), we collected many subtypes of stx2A genes and performed detailed molecular evolutionary analyses of the gene. To achieve the aim of the study, we used several bioinformatics technologies, including time-scaled phylogenetic analyses, phylogenetic distance analyses, phylodynamics analyses, selective pressure analyses, and conformational epitope analyses. A time-scaled phylogeny showed that the common ancestor of the stx2A gene dated back to around 18,600 years ago. After that, the gene diverged into two major lineages (Lineage 1 and 2). Lineage 1 comprised the stx2a–2d subtypes, while Lineage 2 comprised the stx2e, 2g, 2h, and 2o subtypes. The evolutionary rates of the genes were relatively fast. Phylogenetic distances showed that the Lineage 2 strains had a wider genetic divergence than Lineage 1. Phylodynamics also indicated that the population size of the stx2A gene increased after the 1930s and spread globally. Moreover, negative selection sites were identified in the Stx2A proteins, and these sites were diffusely distributed throughout the protein. Two negative selection sites were located adjacent to an active site of the common Stx2A protein. Many conformational epitopes were also estimated in these proteins, while no conformational epitope was found adjacent to the active site. The results suggest that the stx2A gene has uniquely evolved and diverged over an extremely long time, resulting in many subtypes. The dominance of the strains belonging to Lineage 1 suggests that differences in virulence may be involved in the prosperity of the offspring. Furthermore, some subtypes of Stx2A proteins may be able to induce effective neutralizing antibodies against the proteins in humans.

The identification of pathogens associated with respiratory symptoms other than the novel coronavirus disease 2019 (COVID-19) can be challenging. However, the diagnosis of pathogens is crucial for assessing the clinical outcome of patients. We comprehensively profiled pathogens causing non-COVID-19 respiratory symptoms during the 7th prevalent period in Gunma, Japan, using deep sequencing combined with a next-generation sequencer (NGS) and advanced bioinformatics technologies. The study included nasopharyngeal swabs from 40 patients who tested negative for severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) using immuno-chromatography and/or quantitative reverse transcription polymerase chain reaction (qRT-PCR) methods. Comprehensive pathogen sequencing was conducted through deep sequencing using NGS. Additionally, short reads obtained from NGS were analyzed for comprehensive pathogen estimation using MePIC (Metagenomic Pathogen Identification Pipeline for Clinical Specimens) and/or VirusTap. The results revealed the presence of various pathogens, including respiratory viruses and bacteria, in the present subjects. Notably, human adenovirus (HAdV) was the most frequently detected virus in 16 of the 40 cases (40.0%), followed by coryneforms, which were the most frequently detected bacteria in 21 of the 40 cases (52.5%). Seasonal human coronaviruses (NL63 type, 229E type, HKU1 type, and OC43 type), human bocaviruses, and human herpesviruses (human herpesvirus types 1–7) were not detected. Moreover, multiple pathogens were detected in 50% of the subjects. These results suggest that various respiratory pathogens may be associated with non-COVID-19 patients during the 7th prevalent period in Gunma Prefecture, Japan. Consequently, for an accurate diagnosis of pathogens causing respiratory infections, detailed pathogen analyses may be necessary. Furthermore, it is possible that various pathogens, excluding SARS-CoV-2, may be linked to fever and/or respiratory infections even during the COVID-19 pandemic.

Despite the increasing evidence of the clinical impact of Pseudomonas-derived cephalosporinase (PDC) sequence polymorphisms, the molecular evolution of its encoding gene, bla_PDC, remains elusive. To elucidate this, we performed a comprehensive evolutionary analysis of bla_PDC. A Bayesian Markov Chain Monte Carlo phylogenetic tree revealed that a common ancestor of bla_PDC diverged approximately 4660 years ago, leading to the formation of eight clonal variants (clusters A–H). The phylogenetic distances within clusters A to G were short, whereas those within cluster H were relatively long. Two positive selection sites and many negative selection sites were estimated. Two PDC active sites overlapped with negative selection sites. In docking simulation models based on samples selected from clusters A and H, piperacillin was bound to the serine and the threonine residues of the PDC active sites, with the same binding mode for both models. These results suggest that, in P. aeruginosa, bla_PDC is highly conserved, and PDC exhibits similar antibiotic resistance functionality regardless of its genotype.

While the aetiology of asthma is unclear, the onset and/or exacerbation of asthma may be associated with respiratory infections. Virus-induced asthma is also known as virus-associated/triggered asthma, and the reported main causative agent is rhinovirus (RV). Understanding the relationship between viral infections and asthma may overcome the gaps in deferential immunity between viral infections and allergies. Moreover, understanding the complicated cytokine networks involved in RV infection may be necessary. Therefore, the complexity of RV-induced asthma is not only owing to the response of airway and immune cells against viral infection, but also to allergic immune responses caused by the wide variety of cytokines produced by these cells. To better understand RV-induced asthma, it is necessary to elucidate the nature RV infections and the corresponding host defence mechanisms. In this review, we attempt to organise the complexity of RV-induced asthma to make it easily understandable for readers.

Molecular interactions between respiratory syncytial virus (RSV) fusion protein (F protein) and the cellular receptor Toll-like receptor 4 (TLR4) and myeloid differentiation factor-2 (MD-2) protein complex are unknown. Thus, to reveal the detailed molecular interactions between them, in silico analyses were performed using various bioinformatics techniques. The present simulation data showed that the neutralizing antibody (NT-Ab) binding sites in both prefusion and postfusion proteins at sites II and IV were involved in the interactions between them and the TLR4 molecule. Moreover, the binding affinity between postfusion proteins and the TLR4/MD-2 complex was higher than that between prefusion proteins and the TLR4/MD-2 complex. This increased binding affinity due to conformational changes in the F protein may be able to form syncytium in RSV-infected cells. These results may contribute to better understand the infectivity and pathogenicity (syncytium formation) of RSV.

DNA gyrase plays important roles in genome replication in various bacteria, including Pseudomonasaeruginosa. The gyrA gene encodes the gyrase subunit A protein (GyrA). Mutations in GyrA are associated with resistance to quinolone-based antibiotics. We performed a detailed molecular evolutionary analyses of the gyrA gene and associated resistance to the quinolone drug, ciprofloxacin, using bioinformatics techniques. We produced an evolutionary phylogenetic tree using the Bayesian Markov Chain Monte Carlo (MCMC) method. This tree indicated that a common ancestor of the gene was present over 760 years ago, and the offspring formed multiple clusters. Quinolone drug-resistance-associated amino-acid substitutions in GyrA, including T83I and D87N, emerged after the drug was used clinically. These substitutions appeared to be positive selection sites. The molecular affinity between ciprofloxacin and the GyrA protein containing T83I and/or D87N decreased significantly compared to that between the drug and GyrA protein, with no substitutions. The rate of evolution of the gene before quinolone drugs were first used in the clinic, in 1962, was significantly lower than that after the drug was used. These results suggest that the gyrA gene evolved to permit the bacterium to overcome quinolone treatment.

There are currently no antiviral agents for human metapneumovirus (HMPV), respiratory syncytial virus (RSV), mumps virus (MuV), or measles virus (MeV). Favipiravir has been developed as an anti-influenza agent, and this agent may be effective against these viruses in vitro. However, the molecular mechanisms through which the agent affects virus replication remain to be fully elucidated. Thus, to clarify the detailed molecular interactions between favipiravir and the RNA-dependent RNA polymerase (RdRp) of HMPV, RSV, MuV, MeV, and influenza virus, we performed in silico studies using authentic bioinformatics technologies. As a result, we found that the active form of favipiravir (favipiravir ribofuranosyl-5′-triphosphate [F-RTP]) can bind to the RdRp active sites of HMPV, RSV, MuV, and MeV. The aspartic acid residue of RdRp active sites was involved in the interaction. Moreover, F-RTP was incorporated into the growing viral RNA chain in the presence of nucleotide triphosphate and magnesium ions. The results suggested that favipiravir shows two distinct mechanisms in various viruses: RdRp active site inhibition and/or genome replication inhibition.