From hype to hope: Considerations in conducting robust microbiome science.

Microbiome science has been one of the most exciting and rapidly evolving research fields in the past two decades. Breakthroughs in technologies including DNA sequencing have meant that the trillions of microbes (particularly bacteria) inhabiting human biological niches (particularly the gut) can be profiled and analysed in exquisite detail. This microbiome profiling has profound impacts across many fields of research, especially biomedical science, with implications for how we understand and ultimately treat a wide range of human disorders. However, like many great scientific frontiers in human history, the pioneering nature of microbiome research comes with a multitude of challenges and potential pitfalls. These include the reproducibility and robustness of microbiome science, especially in its applications to human health outcomes. In this article, we address the enormous promise of microbiome science and its many challenges, proposing constructive solutions to enhance the reproducibility and robustness of research in this nascent field. The optimisation of microbiome science spans research design, implementation and analysis, and we discuss specific aspects such as the importance of ecological principals and functionality, challenges with microbiome-modulating therapies and the consideration of confounding, alternative options for microbiome sequencing, and the potential of machine learning and computational science to advance the field. The power of microbiome science promises to revolutionise our understanding of many diseases and provide new approaches to prevention, early diagnosis, and treatment.

Exploring the Complexity of the Human Respiratory Virome through an In Silico Analysis of Shotgun Metagenomic Data Retrieved from Public Repositories.

BACKGROUND: Respiratory viruses significantly impact global morbidity and mortality, causing more disease in humans than any other infectious agent. Beyond pathogens, various viruses and bacteria colonize the respiratory tract without causing disease, potentially influencing respiratory diseases' pathogenesis. Nevertheless, our understanding of respiratory microbiota is limited by technical constraints, predominantly focusing on bacteria and neglecting crucial populations like viruses. Despite recent efforts to improve our understanding of viral diversity in the human body, our knowledge of viral diversity associated with the human respiratory tract remains limited. METHODS: Following a comprehensive search in bibliographic and sequencing data repositories using keyword terms, we retrieved shotgun metagenomic data from public repositories (n = 85). After manual curation, sequencing data files from 43 studies were analyzed using EVEREST (pipEline for Viral assEmbly and chaRactEriSaTion). Complete and high-quality contigs were further assessed for genomic and taxonomic characterization. RESULTS: Viral contigs were obtained from 194 out of the 868 FASTQ files processed through EVEREST. Of the 1842 contigs that were quality assessed, 8% (n = 146) were classified as complete/high-quality genomes. Most of the identified viral contigs were taxonomically classified as bacteriophages, with taxonomic resolution ranging from the superkingdom level down to the species level. Captured contigs were spread across 25 putative families and varied between RNA and DNA viruses, including previously uncharacterized viral genomes. Of note, airway samples also contained virus(es) characteristic of the human gastrointestinal tract, which have not been previously described as part of the lung virome. Additionally, by performing a meta-analysis of the integrated datasets, ecological trends within viral populations linked to human disease states and their biogeographical distribution along the respiratory tract were observed. CONCLUSION: By leveraging publicly available repositories of shotgun metagenomic data, the present study provides new insights into viral genomes associated with specimens from the human respiratory tract across different disease spectra. Further studies are required to validate our findings and evaluate the potential impact of these viral communities on respiratory tract physiology.

Airway epithelium respiratory illnesses and allergy (AERIAL) birth cohort: study protocol.

Introduction: Recurrent wheezing disorders including asthma are complex and heterogeneous diseases that affect up to 30% of all children, contributing to a major burden on children, their families, and global healthcare systems. It is now recognized that a dysfunctional airway epithelium plays a central role in the pathogenesis of recurrent wheeze, although the underlying mechanisms are still not fully understood. This prospective birth cohort aims to bridge this knowledge gap by investigating the influence of intrinsic epithelial dysfunction on the risk for developing respiratory disorders and the modulation of this risk by maternal morbidities, in utero exposures, and respiratory exposures in the first year of life. Methods: The Airway Epithelium Respiratory Illnesses and Allergy (AERIAL) study is nested within the ORIGINS Project and will monitor 400 infants from birth to 5 years. The primary outcome of the AERIAL study will be the identification of epithelial endotypes and exposure variables that influence the development of recurrent wheezing, asthma, and allergic sensitisation. Nasal respiratory epithelium at birth to 6 weeks, 1, 3, and 5 years will be analysed by bulk RNA-seq and DNA methylation sequencing. Maternal morbidities and in utero exposures will be identified on maternal history and their effects measured through transcriptomic and epigenetic analyses of the amnion and newborn epithelium. Exposures within the first year of life will be identified based on infant medical history as well as on background and symptomatic nasal sampling for viral PCR and microbiome analysis. Daily temperatures and symptoms recorded in a study-specific Smartphone App will be used to identify symptomatic respiratory illnesses. Discussion: The AERIAL study will provide a comprehensive longitudinal assessment of factors influencing the association between epithelial dysfunction and respiratory morbidity in early life, and hopefully identify novel targets for diagnosis and early intervention.

An Analysis of the Gut Microbiota and Related Metabolites following PCSK9 Inhibition in Statin-Treated Patients with Elevated Levels of Lipoprotein(a).

BACKGROUND: Atherosclerotic cardiovascular disease (ASCVD) is a leading cause of global mortality, often associated with high blood levels of LDL cholesterol (LDL-c). Medications like statins and PCSK9 inhibitors, are used to manage LDL-c levels and reduce ASCVD risk. Recent findings connect the gut microbiota and its metabolites to ASCVD development. We showed that statins modulate the gut microbiota including the production of microbial metabolites involved in the regulation of cholesterol metabolism such as short chain fatty acids (SCFAs) and bile acids (BAs). Whether this pleiotropic effect of statins is associated with their antimicrobial properties or it is secondary to the modulation of cholesterol metabolism in the host is unknown. In this observational study, we evaluated whether alirocumab, a PCSK9 inhibitor administered subcutaneously, alters the stool-associated microbiota and the profiles of SCFAs and BAs. METHODS: We used stool and plasma collected from patients enrolled in a single-sequence study using alirocumab. Microbial DNA was extracted from stool, and the bacterial component of the gut microbiota profiled following an amplicon sequencing strategy targeting the V3-V4 region of the 16S rRNA gene. Bile acids and SCFAs were profiled and quantified in stool and plasma using mass spectrometry. RESULTS: Treatment with alirocumab did not alter bacterial alpha (Shannon index, p = 0.74) or beta diversity (PERMANOVA, p = 0.89) in feces. Similarly, circulating levels of SCFAs (mean difference (95% confidence interval (CI)), 8.12 [-7.15-23.36] µM, p = 0.25) and BAs (mean difference (95% CI), 0.04 [-0.11-0.19] log10(nmol mg-1 feces), p = 0.56) were equivalent regardless of PCSK9 inhibition. Alirocumab therapy was associated with increased concentration of BAs in feces (mean difference (95% CI), 0.20 [0.05-0.34] log10(nmol mg-1 feces), p = 0.01). CONCLUSION: In statin-treated patients, the use of alirocumab to inhibit PCSK9 leads to elevated levels of fecal BAs without altering the bacterial population of the gut microbiota. The association of alirocumab with increased fecal BA concentration suggests an additional mechanism for the cholesterol-lowering effect of PCSK9 inhibition.