DNA extraction protocol impacts ocular surface microbiome profile

HIF‑1 and macrophage activation signalling pathways are potential biomarkers of invasive aspergillosis

Invasive aspergillosis (IA) is a severe disease, the pathogenesis of which remains unclear. The present study aimed to determine the molecular mechanism of IA and to identify potential biomarkers using bioinformatics analysis. The GSE78000 dataset, which includes data from patients with IA and healthy individuals, was downloaded from Gene Expression Omnibus. Differentially expressed genes (DEGs) between the IA and control groups were identified with the 'affy' package in R software. The Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) databases were then used to analyse the function and pathway enrichment of DEGs. The protein-protein interaction network was analysed with the Search Tool for the Retrieval of Interacting Genes (STRING) website. In addition, DEGs were confirmed using reverse transcription-quantitative PCR and western blotting in samples with IA (n=6) and control samples (n=6) collected from the Department of Respiratory and Critical Care Medicine of the First Affiliated Hospital of Henan University of Science and Technology (Luoyang, China). The present study identified 735 DEGs, including 312 upregulated and 423 downregulated genes. Through GO and KEGG analyses of the DEGs, macrophage activation and hypoxia-inducible factor 1 (HIF-1) signalling pathways were revealed to be significantly upregulated and downregulated, respectively, in patients with IA compared with that of the healthy individuals. Subsequently, correlation analysis of macrophage activation and HIF-1 signalling pathways was revealed using correlation as a distance metric for hierarchical clustering correlation analysis. However, there was no protein-protein interaction between the macrophage activity regulation and HIF-1 signalling pathways based on STRING analysis. In summary, the present study identified candidate genes and associated molecules that may be associated to IA and revealed potential biomarkers and therapeutic targets for IA.

Role of the ocular surface microbiome in allergic eye diseases

PURPOSE OF REVIEW

The purpose of this review is to provide an update on emerging literature on the role of the ocular surface microbiome (OSM) in allergic eye diseases.

RECENT FINDINGS

Findings in the literature suggest that the ocular surface microbiome plays a role in the pathophysiology and course of allergic disease of the ocular surface.

SUMMARY

Knowledge regarding the role of the ocular surface microbiome in allergic disease is important to guide development of targets for future therapeutic interventions.

Challenges and insights in the exploration of the low abundance human ocular surface microbiome

Purpose

The low microbial abundance on the ocular surface results in challenges in the characterization of its microbiome. The purpose of this study was to reveal factors introducing bias in the pipeline from sample collection to data analysis of low-abundant microbiomes.

Methods

Lower conjunctiva and lower lid swabs were collected from six participants using either standard cotton or flocked nylon swabs. Microbial DNA was isolated with two different kits (with or without prior host DNA depletion and mechanical lysis), followed by whole-metagenome shotgun sequencing with a high sequencing depth set at 60 million reads per sample. The relative microbial compositions were generated using the two different tools MetaPhlan3 and Kraken2.

Results

The total amount of extracted DNA was increased by using nylon flocked swabs on the lower conjunctiva. In total, 269 microbial species were detected. The most abundant bacterial phyla were Actinobacteria, Firmicutes and Proteobacteria. Depending on the DNA extraction kit and tool used for profiling, the microbial composition and the relative abundance of viruses varied.

Conclusion

The microbial composition on the ocular surface is not dependent on the swab type, but on the DNA extraction method and profiling tool. These factors have to be considered in further studies about the ocular surface microbiome and other sparsely colonized microbiomes in order to improve data reproducibility. Understanding challenges and biases in the characterization of the ocular surface microbiome may set the basis for microbiome-altering interventions for treatment of ocular surface associated diseases.