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.

Hidden diversity and potential ecological function of phosphorus acquisition genes in widespread terrestrial bacteriophages.

Phosphorus (P) limitation of ecosystem processes is widespread in terrestrial habitats. While a few auxiliary metabolic genes (AMGs) in bacteriophages from aquatic habitats are reported to have the potential to enhance P-acquisition ability of their hosts, little is known about the diversity and potential ecological function of P-acquisition genes encoded by terrestrial bacteriophages. Here, we analyze 333 soil metagenomes from five terrestrial habitat types across China and identify 75 viral operational taxonomic units (vOTUs) that encode 105 P-acquisition AMGs. These AMGs span 17 distinct functional genes involved in four primary processes of microbial P-acquisition. Among them, over 60% (11/17) have not been reported previously. We experimentally verify in-vitro enzymatic activities of two pyrophosphatases and one alkaline phosphatase encoded by P-acquisition vOTUs. Thirty-six percent of the 75 P-acquisition vOTUs are detectable in a published global topsoil metagenome dataset. Further analyses reveal that, under certain circumstances, the identified P-acquisition AMGs have a greater influence on soil P availability and are more dominant in soil metatranscriptomes than their corresponding bacterial genes. Overall, our results reinforce the necessity of incorporating viral contributions into biogeochemical P cycling.

Differential airway resistome and its correlations with clinical characteristics in Haemophilus- or Pseudomonas-predominant microbial subtypes of bronchiectasis.

The prevalence and clinical correlates of antibiotic resistance genes (ARGs) in bronchiectasis are not entirely clear. We aimed to profile the ARGs in sputum from adults with bronchiectasis, and explore the association with airway microbiome and disease severity and subtypes. In this longitudinal study, we prospectively collected 118 sputum samples from stable and exacerbation visits of 82 bronchiectasis patients and 19 healthy subjects. We profiled ARGs with shotgun metagenomic sequencing, and linked these to sputum microbiome and clinical characteristics, followed by validation in an international cohort. We compared ARG profiles in bronchiectasis according to disease severity, blood and sputum inflammatory subtypes. Unsupervised clustering revealed a Pseudomonas predominant subgroup (n = 16), Haemophilus predominant subgroup (n = 48), and balanced microbiome subgroup (N = 54). ARGs of multi-drug resistance were over-dominant in the Pseudomonas-predominant subgroup, while ARGs of beta-lactam resistance were most abundant in the Haemophilus-predominant subgroup. Pseudomonas-predominant subgroup yielded the highest ARG diversity and total abundance, while Haemophilus-predominant subgroup and balanced microbiota subgroup were lowest in ARG diversity and total abundance. PBP-1A, ksgA and emrB (multidrug) were most significantly enriched in Haemophilus-predominant subtype. ARGs generally correlated positively with Bronchiectasis Severity Index, fluoroquinolone use, and modified Reiff score. 68.6% of the ARG-clinical correlations could be validated in an independent international cohort. In conclusion, ARGs are differentially associated with the dominant microbiome and clinical characteristics in bronchiectasis.

The application of multi-omics in the respiratory microbiome: Progresses, challenges and promises.

The study of the respiratory microbiome has entered a multi-omic era. Through integrating different omic data types such as metagenome, metatranscriptome, metaproteome, metabolome, culturome and radiome surveyed from respiratory specimens, holistic insights can be gained on the lung microbiome and its interaction with host immunity and inflammation in respiratory diseases. The power of multi-omics have moved the field forward from associative assessment of microbiome alterations to causative understanding of the lung microbiome in the pathogenesis of chronic, acute and other types of respiratory diseases. However, the application of multi-omics in respiratory microbiome remains with unique challenges from sample processing, data integration, and downstream validation. In this review, we first introduce the respiratory sample types and omic data types applicable to studying the respiratory microbiome. We next describe approaches for multi-omic integration, focusing on dimensionality reduction, multi-omic association and prediction. We then summarize progresses in the application of multi-omics to studying the microbiome in respiratory diseases. We finally discuss current challenges and share our thoughts on future promises in the field.

The gut microbiome as a potential source of non-invasive biomarkers of chronic obstructive pulmonary disease.

Background: The link between gut microbial dysbiosis and the development of chronic obstructive pulmonary disease (COPD) is of considerable interest. However, little is known regarding the potential for the use of the fecal metagenome for the diagnosis of COPD. Methods: A total of 80 healthy controls, 31 patients with COPD severity stages I or II, and 49 patients with COPD severity stages III or IV fecal samples were subjected to metagenomic analysis. We characterized the gut microbiome, identified microbial taxonomic and functional markers, and constructed a COPD disease classifier using samples. Results: The fecal microbial diversity of patients with COPD stages I or II was higher than that of healthy controls, but lower in patients with COPD stages III or IV. Twenty-one, twenty-four, and eleven microbial species, including potential pathogens and pro-inflammatory bacteria, were significantly enriched or depleted in healthy controls, patients with COPD stages I or II, and patients with COPD stages III & IV. The KEGG orthology (KO) gene profiles derived demonstrated notable differences in gut microbial function among the three groups. Moreover, gut microbial taxonomic and functional markers could be used to differentiate patients with COPD from healthy controls, on the basis of areas under receiver operating characteristic curves (AUCs) of 0.8814 and 0.8479, respectively. Notably, the gut microbial taxonomic features differed between healthy individuals and patients in stages I-II COPD, which suggests the utility of fecal metagenomic biomarkers for the diagnosis of COPD (AUC = 0.9207). Conclusion: Gut microbiota-targeted biomarkers represent potential non-invasive tools for the diagnosis of COPD.

In situ enrichment of sulphate-reducing microbial communities with different carbon sources stimulating the acid mine drainage sediments.

The applications of sulphate-reducing microorganisms (SRMs) in acid mine drainage (AMD) treatment systems have received extensive attention due to their ability to reduce sulphate and stabilize metal(loid)s. Despite great phylogenetic diversity of SRMs, only a few have been used in AMD treatment bioreactors. In situ enrichment could be an efficient approach to select new effective SRMs for AMD treatment. Here, we performed in situ enrichment of SRMs in highly stratified AMD sediment cores using different kinds of carbon source mixture. The dsrAB (dissimilatory sulfite reductase) genes affiliated with nine phyla (two archaeal and seven bacterial phyla) and 26 genera were enriched. Remarkably, those genes affiliated with Aciduliprofundum and Vulcanisaeta were enriched in situ in AMD-related environments for the first time, and their relative abundances were negatively correlated with pH. Furthermore, 107 dsrAB-containing metagenome-assembled genomes (MAGs) were recovered from metagenomic datasets, with 14 phyla (two archaeal and 12 bacterial phyla) and 15 genera. The relative abundances of MAGs were positively correlated with total carbon and sulphate contents. Our findings expanded the diversity of SRMs that can be enriched in AMD sediment, and revealed the physiochemical properties that might affect the growth of SRMs, which provided guidance for AMD treatment bioreators.

Seasonal Dynamics of the Upper Respiratory Tract Microbiome in Chronic Obstructive Pulmonary Disease.

Introduction: Increasing evidence suggests that seasonal changes can trigger the alternation of airway microbiome. However, the dynamics of the upper airway bacterial ecology of chronic obstructive pulmonary disease (COPD) patients across different seasons remains unclear. Methods: In this study, we present a 16S ribosomal RNA survey of the airway microbiome on 72 swab samples collected in different months (March, May, July, September, and November) in 2019 from 18 COPD patients and from six resampled patients in November in 2020. Results: Our study uncovered a dynamic airway microbiota where changes appeared to be associated with seasonal alternation in COPD patients. Twelve clusters of temporal patterns were displayed by differential and clustering analysis along the time course, systematically revealing distinct microbial taxa that prefer to grow in cool and warm seasons, respectively. Moreover, the upper airway microbiome composition was relatively stable in the same season in different years. Discussion: Given the tight association between airway microbiome and COPD disease progression, this study can provide useful information for clinically understanding the seasonal trend of disease phenotypes in COPD patients.

The airway microbiome mediates the interaction between environmental exposure and respiratory health in humans.

Exposure to environmental pollution influences respiratory health. The role of the airway microbial ecosystem underlying the interaction of exposure and respiratory health remains unclear. Here, through a province-wide chronic obstructive pulmonary disease surveillance program, we conducted a population-based survey of bacterial (n = 1,651) and fungal (n = 719) taxa and metagenomes (n = 1,128) from induced sputum of 1,651 household members in Guangdong, China. We found that cigarette smoking and higher PM2.5 concentration were associated with lung function impairment through the mediation of bacterial and fungal communities, respectively, and that exposure was associated with an enhanced inter-kingdom microbial interaction resembling the pattern seen in chronic obstructive pulmonary disease. Enrichment of Neisseria was associated with a 2.25-fold increased risk of high respiratory symptom burden, coupled with an elevation in Aspergillus, in association with occupational pollution. We developed an individualized microbiome-based health index, which covaried with exposure, respiratory symptoms and diseases, with potential generalizability to global datasets. Our results may inform environmental risk prevention and guide interventions that harness airway microbiome.

Airway dysbiosis accelerates lung function decline in chronic obstructive pulmonary disease.

Progressive lung function decline is a hallmark of chronic obstructive pulmonary disease (COPD). Airway dysbiosis occurs in COPD, but whether it contributes to disease progression remains unknown. Here, we show, through a longitudinal analysis of two cohorts involving four UK centers, that baseline airway dysbiosis in COPD patients, characterized by the enrichment of opportunistic pathogenic taxa, associates with a rapid forced expiratory volume in 1 s (FEV1) decline over 2 years. Dysbiosis associates with exacerbation-related FEV1 fall and sudden FEV1 fall at stability, contributing to long-term FEV1 decline. A third cohort in China further validates the microbiota-FEV1-decline association. Human multi-omics and murine studies show that airway Staphylococcus aureus colonization promotes lung function decline through homocysteine, which elicits a neutrophil apoptosis-to-NETosis shift via the AKT1-S100A8/A9 axis. S. aureus depletion via bacteriophages restores lung function in emphysema mice, providing a fresh approach to slow COPD progression by targeting the airway microbiome.

Swine farm groundwater is a hidden hotspot for antibiotic-resistant pathogenic Acinetobacter.

Acinetobacter is present in the livestock environment, but little is known about their antibiotic resistance and pathogenic species in the farm groundwater. Here we investigated antibiotic resistance of Acinetobacter in the swine farm groundwater (JZPG) and residential groundwater (JZG) of a swine farming village, in comparison to a nearby (3.5 km) non-farming village (WTG) using metagenomic and culture-based approaches. Results showed that the abundance of antibiotic resistome in some JZG and all JZPG (~3.4 copies/16S rRNA gene) was higher than that in WTG (~0.7 copies/16S rRNA gene), indicating the influence of farming activities on both groundwater types. Acinetobacter accounted for ~95.7% of the bacteria in JZG and JZPG, but only ~8.0% in WTG. They were potential hosts of ~95.6% of the resistome in farm affected groundwater, which includes 99 ARG subtypes against 23 antibiotic classes. These ARGs were associated with diverse intrinsic and acquired resistance mechanisms, and the predominant ARGs were tetracyclines and fluoroquinolones resistance genes. Metagenomic binning analysis elucidated that non-baumannii Acinetobacter including A. oleivorans, A. beijerinckii, A. seifertii, A. bereziniae and A. modestus might pose environmental risks because of multidrug resistance, pathogenicity and massive existence in the groundwater. Antibiotic susceptibility tests showed that the isolated strains were resistant to multiple antibiotics including sulfamethoxazole (resistance ratio: 96.2%), levofloxacin (42.5%), gatifloxacin (39.0%), ciprofloxacin (32.6%), tetracycline (32.0%), doxycycline (29.0%) and ampicillin (12.0%) as well as last-resort polymyxin B (31.7%), colistin (24.1%) and tigecycline (4.1%). The findings highlight potential prevalence of groundwater-borne antibiotic-resistant pathogenic Acinetobacter in the livestock environment.

Phytostabilization mitigates antibiotic resistance gene enrichment in a copper mine tailings pond.

Mining-impacted environments are distributed globally and have become increasingly recognized as hotspots of antibiotic resistance genes (ARGs). However, there are currently no reports on treatment technologies to deal with such an important environmental problem. To narrow this knowledge gap, we implemented a phytostabilization project in an acidic copper mine tailings pond and employed metagenomics to explore ARG characteristics in the soil samples. Our results showed that phytostabilization decreased the total ARG abundance in 0-10 cm soil layer by 75 %, which was companied by a significant decrease in ARG mobility, and a significant increase in ARG diversity and microbial diversity. Phytostabilization was also found to drastically alter the ARG host composition and to significantly reduce the total abundance of virulence factor genes of ARG hosts. Soil nutrient status, heavy metal toxicity and SO42- concentration were important physicochemical factors to affect the total ARG abundance, while causal mediation analysis showed that their effects were largely mediated by the changes in ARG mobility and microbial diversity. The increase in ARG diversity associated with phytostabilization was mainly mediated by a small subgroup of ARG hosts, most of which could not be classified at the genus level and deserve further research in the future.

Functional Guilds, Community Assembly, and Co-occurrence Patterns of Fungi in Metalliferous Mine Tailings Ponds in Mainland China.

Metalliferous mine tailings ponds are generally characterized by low levels of nutrient elements, sustained acidic conditions, and high contents of toxic metals. They represent one kind of extreme environments that are believed to resemble the Earth's early environmental conditions. There is increasing evidence that the diversity of fungi inhabiting mine tailings ponds is much higher than previously thought. However, little is known about functional guilds, community assembly, and co-occurrence patterns of fungi in such habitats. As a first attempt to address this critical knowledge gap, we employed high-throughput sequencing to characterize fungal communities in 33 mine tailings ponds distributed across 18 provinces of mainland China. A total of 5842 fungal phylotypes were identified, with saprotrophic fungi being the major functional guild. The predictors of fungal diversity in whole community and sub-communities differed considerably. Community assembly of the whole fungal community and individual functional guilds were primarily governed by stochastic processes. Total soil nitrogen and total phosphorus mediated the balance between stochastic and deterministic processes of the fungal community assembly. Co-occurrence network analysis uncovered a high modularity of the whole fungal community. The observed main modules largely consisted of saprotrophic fungi as well as various phylotypes that could not be assigned to known functional guilds. The richness of core fungal phylotypes, occupying vital positions in co-occurrence network, was positively correlated with edaphic properties such as soil enzyme activity. This indicates the important roles of core fungal phylotypes in soil organic matter decomposition and nutrient cycling. These findings improve our understanding of fungal ecology of extreme environments.

Multi-omics analyses of airway host-microbe interactions in chronic obstructive pulmonary disease identify potential therapeutic interventions.

The mechanistic role of the airway microbiome in chronic obstructive pulmonary disease (COPD) remains largely unexplored. We present a landscape of airway microbe-host interactions in COPD through an in-depth profiling of the sputum metagenome, metabolome, host transcriptome and proteome from 99 patients with COPD and 36 healthy individuals in China. Multi-omics data were integrated using sequential mediation analysis, to assess in silico associations of the microbiome with two primary COPD inflammatory endotypes, neutrophilic or eosinophilic inflammation, mediated through microbial metabolic interaction with host gene expression. Hypotheses of microbiome-metabolite-host interaction were identified by leveraging microbial genetic information and established metabolite-human gene pairs. A prominent hypothesis for neutrophil-predominant COPD was altered tryptophan metabolism in airway lactobacilli associated with reduced indole-3-acetic acid (IAA), which was in turn linked to perturbed host interleukin-22 signalling and epithelial cell apoptosis pathways. In vivo and in vitro studies showed that airway microbiome-derived IAA mitigates neutrophilic inflammation, apoptosis, emphysema and lung function decline, via macrophage-epithelial cell cross-talk mediated by interleukin-22. Intranasal inoculation of two airway lactobacilli restored IAA and recapitulated its protective effects in mice. These findings provide the rationale for therapeutically targeting microbe-host interaction in COPD.

Gut Microbiome Signatures in the Progression of Hepatitis B Virus-Induced Liver Disease.

The gut microbiome is associated with hepatitis B virus (HBV)-induced liver disease, which progresses from chronic hepatitis B, to liver cirrhosis, and eventually to hepatocellular carcinoma. Studies have analyzed the gut microbiome at each stage of HBV-induced liver diseases, but a consensus has not been reached on the microbial signatures across these stages. Here, we conducted by a systematic meta-analysis of 486 fecal samples from publicly available 16S rRNA gene datasets across all disease stages, and validated the results by a gut microbiome characterization on an independent cohort of 15 controls, 23 chronic hepatitis B, 20 liver cirrhosis, and 22 hepatocellular carcinoma patients. The integrative analyses revealed 13 genera consistently altered at each of the disease stages both in public and validation datasets, suggesting highly robust microbiome signatures. Specifically, Colidextribacter and Monoglobus were enriched in healthy controls. An unclassified Lachnospiraceae genus was specifically elevated in chronic hepatitis B, whereas Bilophia was depleted. Prevotella and Oscillibacter were depleted in liver cirrhosis. And Coprococcus and Faecalibacterium were depleted in hepatocellular carcinoma. Classifiers established using these 13 genera showed diagnostic power across all disease stages in a cross-validation between public and validation datasets (AUC = 0.65-0.832). The identified microbial taxonomy serves as non-invasive biomarkers for monitoring the progression of HBV-induced liver disease, and may contribute to microbiome-based therapies.

Globally distributed mining-impacted environments are underexplored hotspots of multidrug resistance genes.

Mining is among the human activities with widest environmental impacts, and mining-impacted environments are characterized by high levels of metals that can co-select for antibiotic resistance genes (ARGs) in microorganisms. However, ARGs in mining-impacted environments are still poorly understood. Here, we conducted a comprehensive study of ARGs in such environments worldwide, taking advantage of 272 metagenomes generated from a global-scale data collection and two national sampling efforts in China. The average total abundance of the ARGs in globally distributed studied mine sites was 1572 times per gigabase, being rivaling that of urban sewage but much higher than that of freshwater sediments. Multidrug resistance genes accounted for 40% of the total ARG abundance, tended to co-occur with multimetal resistance genes, and were highly mobile (e.g. on average 16% occurring on plasmids). Among the 1848 high-quality metagenome-assembled genomes (MAGs), 85% carried at least one multidrug resistance gene plus one multimetal resistance gene. These high-quality ARG-carrying MAGs considerably expanded the phylogenetic diversity of ARG hosts, providing the first representatives of ARG-carrying MAGs for the Archaea domain and three bacterial phyla. Moreover, 54 high-quality ARG-carrying MAGs were identified as potential pathogens. Our findings suggest that mining-impacted environments worldwide are underexplored hotspots of multidrug resistance genes.

Inflammatory Endotype-Associated Airway Resistome in Chronic Obstructive Pulmonary Disease.

Antimicrobial resistance is a global concern in chronic respiratory diseases, including chronic obstructive pulmonary disease (COPD). The collection of antibiotic resistance genes or resistome in human airways may underlie the resistance. COPD is heterogeneous, and understanding the airway resistome in relation to patient phenotype and endotype may inform precision antibiotic therapy. Here, we characterized the airway resistome for 94 COPD participants at stable disease. Among all demographic and clinical factors, patient inflammatory endotype was associated with the airway resistome. There were distinct resistome profiles between patients with neutrophilic or eosinophilic inflammation, two primary inflammatory endotypes in COPD. For neutrophil-predominant COPD, the resistome was dominated by multidrug resistance genes. For eosinophil-predominant COPD, the resistome was diverse, with an increased portion of patients showing a macrolide-high resistome. The differential antimicrobial resistance pattern was validated by sputum culture and in vitro antimicrobial susceptibility testing. Ralstonia and Pseudomonas were the top contributors to the neutrophil-associated resistome, whereas Campylobacter and Aggregatibacter contributed most to the eosinophil-associated resistome. Multiomic analyses revealed specific host pathways and inflammatory mediators associated with the resistome. The arachidonic acid metabolic pathway and matrix metallopeptidase 8 (MMP-8) exhibited the strongest associations with the neutrophil-associated resistome, whereas the eosinophil chemotaxis pathway and interleukin-13 (IL-13) showed the greatest associations with the eosinophil-associated resistome. These results highlight a previously unrecognized link between inflammation and the airway resistome and suggest the need for considering patient inflammatory subtype in decision-making about antibiotic use in COPD and broader chronic respiratory diseases. IMPORTANCE Antibiotics are commonly prescribed for both acute and long-term prophylactic treatment in chronic airway disorders, such as chronic obstructive pulmonary disease (COPD), and the rapid growth of antibiotic resistance is alarming globally. The airway harbors a diverse collection of microorganisms known as microbiota, which serve as a reservoir for antibiotic resistance genes or the resistome. A comprehensive understanding of the airway resistome in relation to patient clinical and biological factors may help inform decisions to select appropriate antibiotics for clinical therapies. By deep multiomic profiling and in vitro phenotypic testing, we showed that inflammatory endotype, the underlying pattern of airway inflammation, was most strongly associated with the airway resistome in COPD patients. There were distinct resistome profiles between neutrophil-predominant and eosinophil-predominant COPD that were associated with different bacterial species, host pathways, and inflammatory markers, highlighting the need of considering patient inflammatory status in COPD antibiotic management.

A transcriptomic analysis based on aberrant methylation levels revealed potential novel therapeutic targets for nasopharyngeal carcinoma.

Background: This study aimed to identify potential novel therapeutic targets for nasopharyngeal carcinoma (NPC) by identifying aberrantly methylated-differentially expressed genes (DEGs) and pathways based on a comprehensive bioinformatics analysis. Methods: Eight gene expression data sets and 2 methylation microarray data sets that included NPC and control groups from the Gene Expression Omnibus were identified. Meta-analyses of the DEGs were performed using the online analysis database "NetworkAnalyst". Aberrantly methylated gene loci were obtained from the GEO2R. Aberrantly methylated DEGs were obtained from Venn diagrams. The enrichment analysis was carried out on the "Metascape" website, and the protein-protein interaction (PPI) network construction, network analysis, and visualization of the analysis results were carried out on the "String" website using "Cytoscape" software. Results: In total, 544 hypomethylation high-expression genes and 164 hypermethylation low-expression genes were obtained. The enrichment and PPI network analyses suggested that several pathways and hub genes with abnormal gene expression accompanied by methylation change, including inositol-trisphosphate 3-kinase B (ITPKB), G protein subunit beta 5 (GNB5), FYN proto-oncogene, Src family tyrosine kinase (FYN), LCK proto-oncogene, Src family tyrosine kinase (LCK), nuclear factor of activated T cells 1 (NFATC1), GNAS complex locus (GNAS), protein kinase C beta (PRKCB), zeta chain of T cell receptor associated protein kinase 70 (ZAP70), lysophosphatidic acid receptor 1 (LPAR1), protein kinase C epsilon (PRKCE), tumor protein p53 (TP53), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), fibronectin 1 (FN1), cyclin D1 (CCND1), vascular endothelial growth factor A (VEGFA), HRas proto-oncogene, GTPase (HRAS), signal transducer and activator of transcription 3 (STAT3), fibroblast growth factor 2 (FGF2), amyloid beta precursor protein (APP), and matrix metallopeptidase 2 (MMP2), may be related to the occurrence of nasopharyngeal carcinoma . Conclusions: The identification of novel and important pathways and hub genes and their roles in the occurrence and development of NPC will guide clinical research and the development of pharmaceutical targets.

Multi-omic meta-analysis identifies functional signatures of airway microbiome in chronic obstructive pulmonary disease.

The interaction between airway microbiome and host in chronic obstructive pulmonary disease (COPD) is poorly understood. Here we used a multi-omic meta-analysis approach to characterize the functional signature of airway microbiome in COPD. We retrieved all public COPD sputum microbiome datasets, totaling 1640 samples from 16S rRNA gene datasets and 26 samples from metagenomic datasets from across the world. We identified microbial taxonomic shifts using random effect meta-analysis and established a global classifier for COPD using 12 microbial genera. We inferred the metabolic potentials for the airway microbiome, established their molecular links to host targets, and explored their effects in a separate meta-analysis on 1340 public human airway transcriptome samples for COPD. 29.6% of differentially expressed human pathways were predicted to be targeted by microbiome metabolism. For inferred metabolite-host interactions, the flux of disease-modifying metabolites as predicted from host transcriptome was generally concordant with their predicted metabolic turnover in microbiome, suggesting a synergistic response between microbiome and host in COPD. The meta-analysis results were further validated by a pilot multi-omic study on 18 COPD patients and 10 controls, in which airway metagenome, metabolome, and host transcriptome were simultaneously characterized. 69.9% of the proposed "microbiome-metabolite-host" interaction links were validated in the independent multi-omic data. Butyrate, homocysteine, and palmitate were the microbial metabolites showing strongest interactions with COPD-associated host genes. Our meta-analysis uncovered functional properties of airway microbiome that interacted with COPD host gene signatures, and demonstrated the possibility of leveraging public multi-omic data to interrogate disease biology.

Expression of resistance genes instead of gene abundance are correlated with trace levels of antibiotics in urban surface waters.

In this study, antibiotic resistance to macrolide-lincosamide-streptogramin B (MLSB) antibiotics in total microbial community in surface water in a coastal urban city was measured using a modified fluorescence in situ hybridization (FISH) technique. This FISH technique quantified the rate of antibiotic resistance to MLSB antibiotics through targeting methylation site of A2058 of 23S rRNAs resulting from expressed erythromycin ribosome methylation (erm) genes. Correlations between the rates of MLSB resistance measured by FISH and macrolide concentrations was stronger than that between the relative abundance of erm genes and macrolide concentrations, especially in residential areas where the main detected antibiotics were macrolides. These results suggest that trace levels of antibiotics in environmental waters, which was as low as 40 ng L-1, may still play important roles in the development and spread of antibiotic resistance. Additionally, methylation as a result of erm gene expression, instead of erm gene abundance, was a better indicator of selective pressure of trace level macrolides. The rates of MLSB resistance varied significantly among land use types, suggesting that anthropogenic activities are important factors to select for erm gene expression in the environment. Microbial community analysis of representative surface water samples showed that relatively high rates of MLSB resistance were observed in Alphaproteobacteria (42%), Acidobacteria (36%), Bacteroidaceae (32%), Chloroflexi (27%), and Betaproteobacteria (20.2%).