Investigation on the Pathological Mechanism of Frequent Exacerbators With Chronic Obstructive Pulmonary Disease Based on the Characteristics of Respiratory Flora

Detecting and quantifying Veillonella by real-time quantitative PCR and droplet digital PCR

Veillonella spp. are Gram-negative opportunistic pathogens present in the respiratory, digestive, and reproductive tracts of mammals. An abnormal increase in Veillonella relative abundance in the body is closely associated with periodontitis, inflammatory bowel disease, urinary tract infections, and many other diseases. We designed a pair of primers and a probe based on the 16S rRNA gene sequences of Veillonella and conducted real-time quantitative PCR (qPCR) and droplet digital PCR (ddPCR) to quantify the abundance of Veillonella in fecal samples. These two methods were tested for specificity and sensitivity using simulated clinical samples. The sensitivity of qPCR was 100 copies/μL, allowing for the accurate detection of a wide range of Veillonella concentrations from 103 to 108 CFU/mL. The sensitivity of ddPCR was 11.3 copies/μL, only allowing for the accurate detection of Veillonella concentrations from 101 to 104 CFU/mL because of the limited number of droplets generated by ddPCR. ddPCR is therefore more suitable for the detection of low-abundance Veillonella samples. To characterize the validity of the assay system, clinical samples from children with inflammatory bowel disease were collected and analyzed, and the results were verified using isolation methods. We conclude that molecular assays targeting the 16S rRNA gene provides an important tool for the rapid diagnosis of chronic and infectious diseases caused by Veillonella and also supports the isolation and identification of Veillonella for research purposes. KEY POINTS: • With suitable primer sets, the qPCR has a wider detection range than ddPCR. • ddPCR is suitable for the detection of low-abundance samples. • Methods successfully guided the isolation of Veillonella in clinical sample.

Human genetic associations of the airway microbiome in chronic obstructive pulmonary disease

Little is known about the relationships between human genetics and the airway microbiome. Deeply sequenced airway metagenomics, by simultaneously characterizing the microbiome and host genetics, provide a unique opportunity to assess the microbiome-host genetic associations. Here we performed a co-profiling of microbiome and host genetics with the identification of over 5 million single nucleotide polymorphisms (SNPs) through deep metagenomic sequencing in sputum of 99 chronic obstructive pulmonary disease (COPD) and 36 healthy individuals. Host genetic variation was the most significant factor associated with the microbiome except for geography and disease status, with its top 5 principal components accounting for 12.11% of the microbiome variability. Within COPD individuals, 113 SNPs mapped to candidate genes reported as genetically associated with COPD exhibited associations with 29 microbial species and 48 functional modules (P < 1 × 10-5), where Streptococcus salivarius exhibits the strongest association to SNP rs6917641 in TBC1D32 (P = 9.54 × 10-8). Integration of concurrent host transcriptomic data identified correlations between the expression of host genes and their genetically-linked microbiome features, including NUDT1, MAD1L1 and Veillonella parvula, TTLL9 and Stenotrophomonas maltophilia, and LTA4H and Haemophilus influenzae. Mendelian randomization analyses revealed a potential causal link between PARK7 expression and microbial type III secretion system, and a genetically-mediated association between COPD and increased relative abundance of airway Streptococcus intermedius. These results suggest a previously underappreciated role of host genetics in shaping the airway microbiome and provide fresh hypotheses for genetic-based host-microbiome interactions in COPD.