The virome composition of respiratory tract changes in school-aged children with Mycoplasma pneumoniae infection

doi:10.21203/rs.3.rs-5317334/v1

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Research Article

The virome composition of respiratory tract changes in school-aged children with Mycoplasma pneumoniae infection

https://doi.org/10.21203/rs.3.rs-5317334/v1

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Background

Mycoplasma pneumoniae (MP) is a common pathogen for respiratory infections in children. Previous studies have reported respiratory tract microbial disturbances associated with MP infection (MPI); however, since the COVID-19 pandemic, respiratory virome data in school-aged children with MPI remains insufficient. This study aims to explore the changes in the respiratory virome caused by MPI after the COVID-19 pandemic to enrich local epidemiological data.

Methods

Clinical samples from 70 children with MPI (70 throat swab samples and 70 bronchoalveolar lavage fluid (BALF) samples) and 78 healthy controls (78 throat swab samples) were analyzed using viral metagenomics. Virus reads were calculated and normalized using MEGAN.6, followed by statistical analysis.

Results

Principal Coordinate Analysis (PCoA) showed that viral community diversity is a significant difference between disease cohorts and healthy controls. After MPI, the number of virus species in the upper respiratory tract (URT) increased obviously, and the abundance of families Poxviridae, Retroviridae, and Iridoviridae, which infect vertebrates, rose evidently, particularly the species BeAn 58085 virus (BAV). Meanwhile, phage alterations in the disease cohorts were predominantly characterized by increased Myoviridae and Ackermannviridae families and decreased Siphoviridae and Salasmaviridae families (p < 0.01). In addition, some new viruses, such as rhinovirus, respirovirus, dependoparvovirus, and a novel gemykibvirus, were also detected in the BALF of the disease cohort.

Conclusions

This cross-sectional research highlighted the respiratory virome characteristics of school-aged children with MPI after the COVID-19 outbreak and provided important epidemiological information. Further investigation into the impact of various microorganisms on diseases will aid in developing clinical treatment strategies.

school-aged children

respiratory infection

Mycoplasma pneumoniae

viral metagenomics

respiratory virome

Acute respiratory infections (ARIs), as a global health problem closely linked to high morbidity and mortality, have become the fourth leading cause of death in the world[1], especially acute lower respiratory infections (ALRIs), which have become the leading cause of hospitalization and death in young children [2, 3]. Following the ongoing public health challenges posed by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) that emerged in late 2019 [4], further efforts should be invested to elucidate the unique epidemiological characteristics and potential pathogenic factors of each regional or large-scale ARI event.

Since mid-2023, the atypical rise of MPI in Jiangsu Province (China) has gradually shown the trend of large-scale epidemics, and the outbreak peak was reached in October of the same year. Mycoplasma pneumoniae, an atypical bacterium, is one of the primary pathogens causing community-acquired pneumonia (CAP) and can cause severe respiratory infections in children [5, 6]. Clinical symptoms include fever, cough (dry or productive), sore throat, headache, and other common respiratory symptoms [7]. In severe cases, it can develop into lung abscess, bronchiectasis, pleural effusion, bronchiolitis obliterans, and respiratory distress syndrome [8]. The pathogenic mechanism of MP is a complex process because the main adhesins (P1 and P30) and accessory proteins (P90 and P40) in MP bind respiratory epithelial cells, either directly or indirectly, leading to host cell metabolism and structural changes, causing severe host damage [9–11]. He et al. demonstrated that standard antigenic components between MP and host cells can evade the host immune surveillance system and thus achieve long-term infection [12]. MP can also cause multi-system immune damage to the host, which may further increase the risk of disease and co-infection [13, 14]. Li et al. reported that the co-infection rate of MP and adenovirus (ADV) was as high as 92.3% (84/91) in bronchoalveolar lavage fluid (BALF) in 91 pediatric severe community-acquired pneumonia (SCAP) patients [15]. Similarly, Gao et al. found that children with MP and ADV infections had more severe clinical symptoms, as shown by a longer duration of fever and hospitalization, a higher proportion of dyspnea, and oxygen treatment [16].

Previous research has shown that MPI may induce dysregulation of the respiratory microbiota. Firmicutes and Bacteroidetes phyla were most common in healthy lungs[17], whereas in MPI, Tenericutes abundance was significantly increased, exceeding 65% of the entire microbiota [18]. One study reported that compared with healthy controls, microbial diversity in the oropharyngeal and nasopharyngeal regions decreased in MPI, with significant enrichment of streptococcus in the oropharyngeal and Staphylococcus in the nasopharyngeal area [19]. Dai et al. found that the lung microbial community was more similar to that in the nasopharyngeal under MPI conditions and that Mycoplasma dominated the BALF microbiota, while its abundance was lower in URT [20]. However, bacterial dysbiosis, including richness and diversity, cannot effectively explain virome changes in disease status [21]. At present, many studies have scrutinized the respiratory viral community. However, the primary focus is on discovering novel viruses or the absence of corresponding control groups and distinct pathological states [22, 23], which still possess some limitations in elucidating the potential pathogenic causes of diseases. Over the past few years, the implementation of non-pharmaceutical interventions (NPIs) has effectively reduced the spread of SARS-CoV-2 during COVID-19 epidemic [24]. However, protective measures inevitably affect the development of children's immune systems, especially those of current school age (> 6 years). An epidemiological survey showed that school-aged children (aged 6–11) were more likely to develop severe conditions [25], possibly due to the relatively immature immune system and a more complex social environment. The host immune response was confirmed to be closely related to the severity of MPI [26, 27]. The respiratory microbiota is an essential factor in regulating and shaping the pulmonary immune response, and slight variations in this composition may obviously impact host immunity. At the same time, microbe-microbe interactions can also significantly affect the process of respiratory diseases [28, 29].

This study used viral metagenomics to analyze the viral composition and respiratory tract differences in school-aged children with MPI. It identified potential pathogens and provided clues as to whether a co-infection in the current MP epidemic was possible. This study will not only enrich local epidemiological data but also contribute to providing empirical treatment strategies for these infections.

2.1. Participants and sample collection

From July to September 2023, a total of 140 clinical specimens (70 throat swab specimens and 70 BALF specimens) from 70 school-aged children clinically diagnosed with MPI were collected, and 78 throat swab specimens from healthy school-aged children without clinical symptoms were used as controls in Wuxi city, Jiangsu Province. The inclusion criteria for the disease group were children aged 6–12 years with fever, cough, runny nose, and other obvious respiratory symptoms, positive for mycoplasma pneumoniae and negative for other clinical routine diagnostic tests, including respiratory viruses (influenza A virus, influenza B virus, human parainfluenza virus, adenovirus, respiratory syncytial virus), bacteria, chlamydia. The inclusion criteria for healthy children were 6–12 years old, without clinical symptoms, and adverse clinical respiratory routine tests as controls.

All samples were collected by professional clinicians, stored in sterile centrifuge tubes or sputum collectors, and then transported by cold chain. Throat swab samples were vigorously vortexed in 1 mL Dulbecco's phosphate-buffered saline (DPBS) for 10 min before being freeze-thawed three times in dry ice. After centrifugation (10 min, 15,000g, 4 ℃), each sample's supernatants were collected in a new 1.5 mL centrifuge tube and stored at -80 ℃. After filtration through sterile gauze, BALF samples were centrifuged at 400g for 10 min at 4 ℃, and then the supernatant was transferred to a high-speed centrifuge tube. After centrifugation (10 min, 15000g, 4 ℃), the supernatant was discarded, and 1 mL of DPBS was added to resuspend the precipitate and store it at -80 ℃.

2.2. Viral nucleic acid extraction and library construction

The 218 supernatants were randomly and evenly combined into 15 sample pools (500 µL/pool) according to the health status and sample type. Eukaryotic and some bacterial cell-sized particles were removed from each sample pool using a 0.45 µm filter (5 min, 8,000g, 4 ℃), and DNase (Turbo DNase from Thermo Fisher; Baseline-ZERO from Epicentre; benzonase from Novagen) and RNase (Promega, Madison, WI, USA) kits were used to digest unprotected nucleic acid in filtrates at 37 ℃ for 60 min. QIAamp viral RNA Minikit (Qiagen, HQ, Germany) was used to extract the remaining viral nucleic acids according to the manufacturer’s protocol.

The enriched viral RNA from the respective pools was subjected to reverse transcription reactions using Super-Script IV Reverse Transcriptase (Invitrogen, CA, USA) and six-base random primers, and then double-strand DNA synthesis using Klenow fragment polymerase (New England Biolabs, Ipswich, MA, USA). Using the Nextera XT DNA Sample Preparation Kit (Illumina, CA, USA), 15 libraries were constructed and sequenced on the Miseq Illumina platform with 250 bases paired-ends with dual barcoding for each sample library.

2.3. Bioinformatics analysis

The 250-bp paired-end reads with barcodes generated by the MiSeq platform were trimmed using Illumina’s vendor software. Data was processed using an in-house analysis pipeline running on a 32-node Linux cluster, and reads were treated as duplicates if bases 5 to 55 were identical, with only one random copy of duplicates kept. The Phred quality score of 10 as the threshold was used to trim tails with low sequencing quality, and adaptors were trimmed using the default parameters of VecScreen in the National Center for Biotechnology Information (NCBI) (http://www.ncbi.nlm.nih.gov/tools/vecscreen/). Bacterial nucleotide sequences were mapped from the BLAST NT database and subtracted, and cleaned reads were de-novo assembled by SOAPdenovo2 (version r240) with a K-mer size of 63 with default settings. Contigs and singlets were then aligned to an in-house viral proteome database using BLASTx (https://ftp.ncbi.nih.gov/refseq/release/viral/) with an E-value cutoff of < 10^− 5. Candidate viral hits were then compared to an in-house non-virus non-redundant (NVNR) database (based on annotation taxonomy excluding viruses) with an E-value cutoff of < 10^− 5 to eliminate false-positive viral hits. MEGAN (v6.22.2) was used to assign each sequence present in metagenomic data to different taxa using the NCBI taxonomic database.

2.4. Viral sequences extension and annotation

The generated individual viral contig was used as a reference to obtain a longer contig or nearly complete genome using the Low Sensitivity/Fastest parameter in Geneious Prime v2020.0.5, and then predicted putative viral open reading frames (ORFs) with self-defined parameters (genetic code: Standard; minimum size: 200–1000; start codons: ATG), and the predicted ORFs were further compared against the NCBI database using BLASTp.

2.5. Phylogenetic analysis

Detailed methods were described in the previous research [30, 31]. Roughly as follows, the amino acid (aa) sequences of viral reference strains were downloaded from the NCBI GenBank database, and sequence alignment was performed using Cluster X with the default parameters in MEGA (v10.1.8). For MrBayes analysis, “lset nst = 6 rates = invgamma” were used for phylogenetic analysis based on nucleotide sequences, which set the evolutionary model to the GTR substitution model with gamma-distributed rate variation across sites and a proportion of invariable sites ("GTR + I+Г"), while “prset aamodelpr = mixed” were set for the phylogenetic analysis using aa sequences, which allows the program to utilize the 10 built-in aa models, and the number of generations was increased to one million until the standard deviation of split frequencies is below 0.01, sampled every 50 generations, and the first 25% of Markov chain Monte Carlo (MCMC) samples were discarded as burn-in. Meanwhile, all Bayesian inference trees were further validated using the maximum likelihood trees constructed by the MEGA X64.

2.6 Statistical analysis

The virus composition analyses were normalized using MEGAN.6, and the viral community analyses were compared by the R v4.3.1 package (vegan, ggpubr, ggsignif, dplyr, and ggplot2). The Kruskal-Wallis test compared the alpha diversity. The Mann-Whitney U test was used to compare groups. Statistical Analysis of Metagenomic Profiles (STAMP) analysis was constructed by the R v4.3.1 package (tidyverse and boot), and the Wilcoxon test was calculated to compare groups. P < 0.05 was considered statistically significant.

2.7. Nucleotide sequence accession number

The raw sequence reads generated in the study are available at the China National Center for Bioinformation (CNCB) database under the BioProject accession PRJCA027224 (https://ngdc.cncb.ac.cn/gsub/), and the Biosample accession can be found in Supplementary Table. S1. All viral sequences identified in this study were deposited in the CNCB database (https://ngdc.cncb.ac.cn/genbase/), and the accession numbers were provided in the Supplementary Table. S2.

3.1 Overview of viral metagenomic

Fifteen libraries were divided into three cohorts according to participants' health status and sample types, including Healthy Control (5 libraries, WXN1-WXN5, HC), MP-infected throat swab (5 libraries, WXD1-WXD5, MT), and MP-infected BALF (5 libraries, WXD1-WXD5, MB).

After next-generation sequencing with the Illumina Miseq platform, the 15 libraries generated 193,279,390 raw sequence reads. With an E-value cutoff of < 10^− 5, 762,858 sequences demonstrated significant sequence identities for known viruses using MEGAN.6 (18,874 − 134,174 reads per library), most of which were assigned to phage sequences, mainly belonging to Siphoviridae, Myoviridae, Podoviridae, and Autographiviridae. Besides, 301,576 sequences from the following families of viruses that could infect vertebrates were detected, including Poxviridae, Picornaviridae, Retroviridae, Coronaviridae, Anelloviridae, and Paramyxoviridae, among others. Of these, Poxviridae and Picornaviridae accounted for the majority of the viruses observed infecting vertebrates in this study. Detailed information on each library can be found in the Supplementary Table. S3.

3.2 Diversity analysis of viral communities

Virus reads were calculated and normalized using MEGAN.6, followed by composition analysis. The flattening of each library curve in the Rarefaction Curve indicates that the biodiversity of community predictions can be made within the range of sequencing depth (Figure. 1A). Assessing alpha diversity using Shannon, Simpson, and ACE indices to reflect virus diversity and richness. The results showed significant differences in alpha diversity among the three cohorts (Figure. 1B). The Shannon and Simpson indices decreased slightly in the MT cohort compared to the HC cohort. The differences were significant in the MB cohort (p < 0.001), while the ACE index increased significantly in the MT cohort (p < 0.05). These results indicated that MP infection resulted in changes in viral community composition, including diversity and richness. On the other hand, the above results also revealed apparent differences in the composition of upper and lower respiratory virus communities (MT vs. MB).

We further explored whether the overall viral phenotype differed among the three groups. PCoA was performed using the Bray Curtis distance matrix to compare differences in community composition (Figure. 1C), and the results showed that viral signatures among the three groups were significantly distinct (ANOSIM: R = 0.928, P < 0.01). The difference in virus community structure among the three groups was significant, and the five libraries in each group could be effectively clustered, indicating that the difference within each group was slight and the sampling was reasonable. Meanwhile, the Partial Least Squares Discrimination Analysis (PLS-DA) model showed a similar result (Figure. 1D).

3.3 Composition of the viral communities

Viral reads were analyzed at the family and species levels to reveal community composition. At the family level, viral reads in the three cohorts were classified into 81 known viral families, which contain 24 viral families that can infect vertebrates, including 12 RNA virus families and 12 DNA virus families (Figure. 2A). Among the viral reads that infect vertebrates, Picornaviridae (70.41%), Coronaviridae (7.67%), and Picobirnaviridae (7.06%) showed a relatively high proportion in the HC cohort. However, Picornaviridae (39.01%, 20.06%), Poxviridae (31.19%, 45.81%), and Retroviridae (9.28%, 10.35%) were the main viruses in the MT and MB cohorts, respectively. Notably, the composition of viral communities in the URT was significantly altered following MPI (HC vs. MT), with a significant increase in the proportion of Poxviridae (4.35% vs. 31.19%) and Retroviridae (2.00% vs. 9.28%). In addition, Adenoviridae, Pneumoviridae, Caliciviridae, Arenaviridae, and Bornaviridae were only detected in the disease cohort. At the species level, 1554 species were identified in virus reads across all cohorts. The MT cohort contained the most virus species, with 408 viruses unique to this group, while only 248 viruses were unique to the HC group (Figure. 2B). This indicates that Mycoplasma pneumoniae infection had a significant impact on the respiratory virus community.

3.4 Differences in virus communities

In the HC and MT cohorts, 6 viral families displayed significant differences in abundance. The families Herpesviridae, Iridoviridae, Parvoviridae, Poxviridae, and Retroviridae were significantly higher than the HC cohort in the MT cohort. At the same time, the number of Picobirnaviridae was clearly lower than the HC cohort (Figure. 3A). In the state of MPI, 5 viral families were significantly different between the upper and lower respiratory tracts (MT vs. MB), and viral reads in the families of Herpesviridae, Iridoviridae, Poxviridae, and Retroviridae showed visibly higher abundance in the MB cohort compared to the MT cohort (Figure. 3B). Although the abundance of Anelloviridae was overtly increased in the disease group, it did not show a statistical difference. At the genus level, Enterovirus read abundance was higher in the upper respiratory tract virus community of the healthy control group. In contrast, abundance of the genus unclassified Chordopoxvirinae and Enterovirus was the main domain in the infection cohort (Figure. 3C).

In addition, phage, as the main component of the viral community, also changed significantly after infection with MP. Phage Siphoviridae, Salasmaviridae, and Microviridae showed an obvious lower abundance in the MT cohort compared to HC, while Ackermannviridae and Myoviridae were significantly more abundant. Meanwhile, the abundance of phage reads in the LRT (23,115 reads, MB) was obviously lower than that in the URT (99,290 reads, MT). Phage Myoviridae, Microviridae, and Autographiviridae showed significant differences (Figure. 3D).

Subsequently, STAMP was used to investigate further differences in the relative abundance of viral reads at the species level. The results showed that 13 virus species were significantly different between the HC and MT cohorts (Figure. 4A), most of which (Mouse mammary tumor virus, Bovine retrovirus CH15, Feline leukemia virus, Harvey murine sarcoma virus, Reticuloendotheliosis virus, Baboon endogenous virus, and Atlantic salmon swim bladder sarcoma virus) belonged to the family Retroviridae. In the MT and MB cohorts (Figure. 4B), there were 15 distinct virus species, most of which (Murmansk microtuspox virus, NY_014 poxvirus, Mule deerpox virus, Squirrelpox virus, Eptesipox virus, and Anomala cuprea entomopoxvirus) belonged to the family Poxviridae.

3.5. Analysis of new viruses

Ultimately, to compensate for the lack of conventional clinical methods, this study utilized viral metagenomic technology to examine possible vertebrate viruses in all libraries and obtained seven relatively complete virus sequences.

Sequence reads corresponding to the family Picornaviridae were identified from all libraries. Four nearly complete genomes of the virus were obtained and named WX/HC1/Picor2023 (mean coverage: 26.1), WX/HC2/Picor2023 (mean coverage: 37.7), WX/BALF8/Picor2023 (mean coverage: 44.4), and WX/BALF10/Picor2023 (mean coverage: 155.1), respectively (Figure. S1A). Phylogenetic analysis was performed based on VP1 nucleotide (nt) sequences, including reference sequences from the genus Enterovirus [32]. The results showed that WX/HC2/Picor2023, WX/BALF8/Picor2023, and WX/BALF10/Picor2023 clustered significantly with the species Rhinovirus A forming a clade, while WX/HC1/Picor2023 clustered with the species Enterovirus A forming a clade (Figure. S1B). Sequence analysis showed that WX/HC1/Picor2023 shared the 97.7% nt sequence identity with Coxsackievirus A6 strain (OR394975), WX/HC2/Picor2023 shared 97.0% with Rhinovirus A21 strain (OL638406), WX/BALF8/Picor2023 shared 97.1% with Rhinovirus A21 strain (MZ835609), and WX/BALF10/Picor2023 shared 98.8% with Rhinovirus A54 strain (MZ540950).

One nearly complete respirovirus was discovered in library ^#WXD10 and named WX/BALF10/Param2023 (mean coverage: 55.6). The genome was 15,492 bp and contained a complete coding sequence (CDS), including N, P, M, F, HN, and L (Fig. S2A). Phylogenetic analysis based on N protein and L protein construction showed that WX/BALF10/Param2023 belonged to a member of the species Human respirovirus 3 and shared 99.6% nt sequence identity with Human respirovirus 3 isolated NICU/BJ/CHN/2022 (OQ785280) (Figure. S2B).

A nearly complete genome of the family Parvoviridae was detected in library ^#WXD8 and named WX/BALF8/Parv2023 (mean coverage: 21.6). The virus was 4,529 bp in length and contained two complete ORFs encoding a nonstructural protein (NS1, 648aa) and a structural protein (VP1, 726aa), respectively. Phylogenetic analysis was performed based on VP1 aa sequences, including reference sequences from the genus Dependoparvovirus, and results showed that WX/BALF8/Parv2023 was clustered with avian adeno-associated viruses (MT138226, MT138246, MT138249) but formed a separate branch (Figure. S3A). According to the International Committee on Taxonomy of Viruses (ICTV) classification criteria for species in the family Parvoviridae, viruses within a species usually encode NS1 protein that exhibits > 85% aa sequence identity. Analysis of the NS1 aa sequence showed that the virus shared the identity of 91.5–93.7% with the above three virus strains. On the basis of the above evidence, WX/BALF8/Parv2023 belongs to a member of the genus Dependoparvovirus.

A complete genome of Genomoviridae was obtained from library ^#WXD10 and named WX/BALF10/Genom2023 (mean coverage: 8.9). The virus was 2150 bp in length, and the genome organization was typical of the family Genomoviridae. WX/BALF10/Genom2023 was examined for genetic relationships with family references using the replication-associated protein. The phylogenetic tree showed that the virus detected in the study was clustered significantly with the genus Gemykibvirus (Figure. S3B). Further analysis showed that WX/BALF10/Genom2023 shared only 57.4% and 50.2% genome-wide identity with closely related faecal-associated gemycircularvirus 9 (NC_025731) and human gemycircularvirus GeTz1 (NC_038497). According to the 78% genome-wide pairwise identity as a species demarcation threshold [33], WX/BALF10/Genom2023 is a new member of the genus Gemykibvirus.

The respiratory tract, as the channel of communication between the human body and the external environment, is also the main route for the invasion of many pathogens. Previous studies have shown that changes in respiratory microecology can affect host respiratory health and the development of disease processes [34, 35]. In this study, respiratory virome in school-aged children with MPI and healthy controls were compared, and the difference between upper and lower respiratory virome in MPI was further explored.

Special bacterial communities that colonize the respiratory tract are thought to play a major role in maintaining human health [36]. For most pathogens, colonization on the surface of the respiratory tract is a necessary precondition for infection, and the "colonization resistance" effect generated by the resident microbiota may be important for maintaining respiratory health [37]. In addition, the respiratory microbiota also plays an essential role in the formation of local immunity [38]. The complex pathogenic mechanism of MP often leads to varying degrees of respiratory system damage. MP interacts with the host bronchial epithelium through adhesion proteins, inducing intracellular metabolism and ultrastructural changes in infected cells, leading to the destruction of the integrity of the airway lumen surface membranes and further affecting the self-purification ability of the respiratory tract, which may provide a prerequisite for other pathogens to invade the host [11]. A report of pathogen detection using the TaqMan Array Card (TAC) in MP-infected patients found that at least one other bacterial or viral codetection was identified in 59.8% (125/209) patients, and bacterial and viral codetection was found in 19% (34/209) patients, and was observed only in pediatric patients [13]. Moreover, several studies have demonstrated that MPI can also cause an imbalance in the respiratory microbiota [18, 20]. As shown in our study, the relative abundance of many viruses increases significantly in the disease state, such as Anelloviridae, Iridoviridae, Poxviridae, Coronaviridae, Paramyxoviridae, and Retroviridae. In a previous study investigating unexplained acute respiratory infections, Mao et al. found that Picornaviridae, Parvoviridae, Paramyxoviridae, Coronaviridae, and Anelloviridae were the top five virus families with the highest relative abundance in the URT [22]. Our results have partially overlapped with theirs. Due to the lack of a healthy control group, their results do not reflect changes in the viral community under disease status. As we observed in this study, the family Picornaviridae in the healthy state still has a high proportion, indicating that it may be a resident virus in the respiratory tract. The recently discovered Anelloviridae has been confirmed as a wildly prevalent family of viruses throughout the respiratory tract [39]. However, the relative abundance of Anelloviridae is clearly increasing under MPI, a trend consistent with previous research results [22, 40].Several studies have shown that anellovirus can be used as a potential clinical biomarker for immune function; as observed in organ transplant patients, blood levels of anellovirus increase with immunosuppressive therapy, before the onset of acute organ rejection showed a relative decline. Changes in anellovirus levels may indicate the body's immune status[41]. It is suggested that Anelloviridae replication may have a potential role in disease progression, and the underlying mechanism remains to be explored.

As major members of the virome, phages are generally thought to maintain microbiota homeostasis by regulating and modifying bacterial colonies [42]. In this study, DNA phages of Caudovirales were dominated by the bacteriophage component and mainly concentrated in the URT, which also reflected the relatively clean environment of the LRT. The MP infection caused changes in the phage community. The phage Siphoviridae was the dominant virus in the healthy state, while the abundance of Myoviridae increased significantly and became dominant after MPI. Intriguingly, one study reported that pathogen-induced inflammation catalyzes phage induction and transfer during infection[43], and immune activity and phage-killing effects are synergistic in combating bacterial infection [44]. Given recent evidence, we propose a conjecture as to whether MPI leads to changes in the phage community by destabilizing the microbiota or whether infection catalyzes phage induction and promotes rebalancing of dysregulated microbiota. Therefore, exploring phage-microbiota and phage-immune system interactions may have important biological implications and broaden the horizons of clinical therapeutics.

It is worth noting that a large number of poxviridae reads were observed in the respiratory tract of MPI patients in this study, particularly the BAV. BAV has been characterized and recommended to belong to the genus Orthopoxvirus. The genus belongs to double-stranded DNA (dsDNA) viruses and are zoonotic pathogen [45]. In a study of the lung microbiome of COPD patients in Tshwane, South Africa, the team reported a high abundance of BAV in all sputum samples in the study [46], consistent with what was observed in the disease cohort in our study. Several immature theories point to possible reasons for the high abundance of BAV. First, BAV was an ancient virus that had become part of the human genome over time [47]. Second, the virus is a DNA artifact of the smallpox vaccine received years earlier because BAV has a high degree of homology with the vaccinia virus (used for smallpox vaccination) [45]. Finally, participants were infected with the virus via environmental exposure [48]. However, even if the above theories can explain the existence of BAV in humans, the potential significance and mechanism of the apparently elevated abundance of BAV in disease states have yet to be elucidated. To the best of our knowledge, this is the first cross-sectional study to report the differential performance of BAV in the human respiratory tract.

Conventional clinical methods, including microbial culture, serology tests, and nucleic acid amplification technology (NAAT), for the detection of respiratory pathogens still have certain limitations. Microbial culture not only takes a long time due to its characteristics but is also susceptible to antimicrobial therapy, especially for viruses. Serology tests are often subject to thresholds and population variations, such as antibodies that persist long after infection has cleared in young children [49]. Although NAAT is highly sensitive and specific, it requires effective prediction of the pathogen. Meanwhile, pulmonary infection, due to its universality, complexity, and heterogeneity in clinical diagnosis, is unclear in about 19–62% of aetiology. Using unbiased viral metagenomics techniques, we investigated viral community composition under MPI. As expected, some common ARI viruses were detected in the disease group, such as Adenoviridae, Paramyxoviridae, and Pneumoviridae. It is worth noting that the inclusion criteria for the disease group in this study already excluded subjects who tested positive for routine clinical respiratory viruses. Obviously, conventional methods still have a certain degree of missed detection. A retrospective study of pneumonia infection showed that the positive rate of metagenomic next-generation sequencing (mNGS) for virus detection was as high as 92.31% compared to conventional methods (7.69%) [50]. Therefore, for each regional or large-scale outbreak of infectious disease, comprehensive testing is needed to explore the potential causes of the epidemic trend. At the same time, with cost reduction and process simplification, mNGS technology is expected to become a conventional clinical method for microbial detection and diagnosis.

Several limitations of this study should also be considered. First, the inevitable loss of nucleic acid fragments in the library enrichment process has led to the inability to obtain complete genetic information for some viruses, such as Coronaviridae and Anelloviridae. Subsequent studies can obtain more complete sequencing information by optimizing the experimental process. Second, MP was not sequenced to compare the effect of resistance gene mutation on changes in respiratory viral communities. Further research is needed to investigate the effect of this aspect. Third, as an invasive procedure, BALF collection is relatively limited and requires future large-scale cohort studies to validate the findings of this study.

This cross-sectional research highlighted the respiratory virome characteristics of school-aged children with MPI after the COVID-19 outbreak, with obvious increases in Poxviridae, Retroviridae, Iridoviridae families, and the phages Siphoviridae and Ackermannviridae. Further investigation into the differentially altered viral communities may help to develop new clinical treatment strategies

ADV

Adenovirus

ALRIs

Acute lower respiratory infections

ARIs

Acute respiratory infections

BAV

BeAn 58085 virus

BALF

Bronchoalveolar lavage fluid

CAP

Community-acquired pneumonia

CDS

Complete coding sequence

CNCB

China National Center for Bioinformation

DPBS

Dulbecco’s phosphate-buffered saline

Healthy Control

LRT

Lower respiratory tract

MP-infected BALF

MCMC

Markov chain Monte Carlo

Mycoplasma pneumoniae

MPI

Mycoplasma pneumoniae infection

MP-infected throat swab

NAAT

Nucleic acid amplification technology

NCBI

National Center for Biotechnology Information

NPIs

Non-pharmaceutical interventions

NVNR

Non-virus non-redundant

ORFs

Open reading frames

PCoA

Principal Coordinate Analysis

PLS-DA

Partial Least Squares Discrimination Analysis

SARS-CoV-2

Severe Acute Respiratory Syndrome Coronavirus 2

SCAP

Severe community acquired pneumonia

STAMP

Statistical Analysis of Metagenomic Profiles

TAC

TaqMan Array Card

URT

Upper respiratory tract

Conflicts of Interest

No potential conflict of interest was reported by the author(s).

Ethics statements

Sample collection and all experiments in the present were performed with Ethical Approval given by the Ethics Committee of The Affiliated Yixing People’s Hospital.

Funding

This research was supported by National Natural Science Foundation of China No. 32201990; Natural Science Foundation of Jiangsu Province of China No. BK20210461; Scientific Research Program of Wuxi Health Commission No. Q202342; Hospital-level project of Northern Jiangsu People's Hospital No. SBQN22013.

Author Contribution

Conceptualization: Y.J, Y.M.H., and D.Q.Z. Methodology: D.Q.Z., B.D., T.Z., X.J., Q.Y.L., and C.Y.Q. Investigation: D.Q.Z., Y.J., Y.M.H., and C.Y.Q. Funding acquisition: D.Q.Z, X.J, and Y.M.H. Writing–original draft: D.Q.Z, and Y.C. Writing–review and editing: D.Q.Z, Y.J, Y.M.H, and C.Y.Q.

Acknowledgement

We thank Prof. Shixing Yang and Prof. Wen Zhang for their guidance on this research.

Data Availability

All datasets are available in the CNCB database. A list of repository names and accession ID can be found in the supplementary material.

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No competing interests reported.

FigureS1.jpg
Figure. S1. Genome organization and phylogenetic analysis of enterovirus. (A) The s genomic organization of these viruses was identified in this study. The blue line represents the GC content and the green line represents the AT content. (B) Phylogenetic analysis based on VP1 aa sequences of the four viruses identified in this study, reference strains of 11 Enterovirus species and 3 Rhinovirus species. The viruses identified in this study were marked with a red font.
FigureS2.jpg
Figure. S2. Genome organization and phylogenetic analysis of the respirovirus. (A) Genomic structure of WX/BALF10/Param2023. The blue line represents the GC content and the green line represents the AT content. (B-C) Phylogenetic analysis of N protein (B) and L protein (C) from WX/BALF10/Param2023, and the subfamily Feraresvirinae. The virus detected in this study was highlighted using the red font.
FigureS3.jpg
Figure. S3. The phylogenetic analysis of parvovirus and Gemykibivirus.(A) Phylogenetic tree constructed based on VP1 amino acid sequences of members of the genus Dependoparvovirus. (B) Phylogenetic analysis based on Rep amino acid sequences of members of the family Genomoviridae. The virus detected in this study was highlighted using the red font.
SupplementaryTableS1.docx
Table. S1. Detailed information of 15 libraries constructed in this study.
SupplementaryTableS2.docx
Table. S2. Detailed information of viral sequences identified in this study.
SupplementaryTableS3.xlsx
Table. S3. The number of viral reads and contigs in each library.

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The virome composition of respiratory tract changes in school-aged children with Mycoplasma pneumoniae infection

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Abstract

Background

Methods

Results

Conclusions

Figures

1. Introduction

2. Materials and methods

2.1. Participants and sample collection

2.2. Viral nucleic acid extraction and library construction

2.3. Bioinformatics analysis

2.4. Viral sequences extension and annotation

2.5. Phylogenetic analysis

2.6 Statistical analysis

2.7. Nucleotide sequence accession number

3. Result

3.1 Overview of viral metagenomic

3.2 Diversity analysis of viral communities

3.3 Composition of the viral communities

3.4 Differences in virus communities

3.5. Analysis of new viruses

4. Discussion

Conclusions

Abbreviations

Declarations

Conflicts of Interest

Ethics statements

Funding

Author Contribution

Acknowledgement

Data Availability

References

Additional Declarations

Supplementary Files

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