Characterizing the composition of the airway microbiota of patients with COPD in a rural setting in Uganda using shotgun metagenomics, a case control study

Abstract

Introduction: Diverse airway microbiota play an important role in the development and integrity of the immune system that limits growth of pathogenic microorganisms and clearing bacterial infections. Community shifts from mixed species composition to high proportions of pathogenic respiratory bacteria (Streptococcus pneumonia, Haemophilus influenza or Moraxella catarrhalis) in the airway microbiota have been linked to accelerate chronic obstructive pulmonary disease severity with an increase in symptoms that present clinically as exacerbations. Studies assessing this association have been restricted to western COPD cohorts and primarily based on 16S rRNA sequencing approach. Such data currently lacking in sub-Saharan Africa, particularly Uganda. Understanding the airway microbiota associated with COPD in Ugandan patients may be important in guiding local effective clinical interventions. Methods: This study was nested in the Lung microbiome study (LMB) conducted in Nakaseke district, Uganda, whose main aim was to assess the composition of the HIV-COPD lung microbiota in Ugandan COPD-HIV cohort. We employed shotgun metagenomics sequencing to compare the airway microbiota of 9 COPD patients Vs 9 healthy controls randomly sampled from the LMB study participants. Shotgun metagenomics allows for community structure characterisation and gene function profiling at a far greater resolution than amplicon 16S rRNA sequencing. Novaseq 6000 S4 PE150 sequencing platform was used to generate a mean 37 million reads per sample. Results: Following stringent quality control, resultant average 1.2 million reads per sample yielded 437 taxonomic operating units (OTUs) dominated by Bacteria which accounted for 100% with 8 phyla, 27 genera and 137 different species observed in all samples. Both alpha and beta diversity measures showed non-significant microbial taxonomic diversity difference between the two sample groups. We also noticed slightly lower microbial diversity at genus and species level in COPD samples compared to controls, with provotella dominating the microbiota from both groups. Species like prevotella melaninogenica were observed to increase in abundance with increase in COPD GOLD stages. Antimicrobial resistance gene analysis detected 47 genes dominated by fluoroquinolone, macrolide, tetracycline and beta-lactamase. Functional diversity analysis showed a non-significant difference both by alpha (Shannon) and beta (CAP) diversity measures. We also noticed a positive association between sequencing depth and Shannon diversity index with maximum diversity detection at 20 million reads and more per sample. Conclusion: To the best of our knowledge, Prevotella melaninogenica has not been associated with COPD in earlier studies, a longitudinal cohort with a bigger sample size could inform its role in COPD progression. Characterizing COPD microbiota and determining its resistome using metagenomics analysis has a potential to inform effective treatment of COPD especially managing exacerbations using antibiotics. Data generated by this study agrees with previous studies that there are differences in microbial composition between the African COPD cohorts and the widely studied western COPD cohorts.