Purpose

To investigate the ocular surface microbiome of patients with unilateral or asymmetric glaucoma being treated with topical ophthalmic medications in one eye and to determine whether microbial community changes were related to measures of ocular surface disease.

Methods

V3-V4 16S rRNA sequencing was conducted on ocular surface swabs collected from both eyes of 17 subjects: 10 patients with asymmetric/unilateral glaucoma using topical glaucoma therapy on only one eye and seven age-matched, healthy controls with no history of ocular disease or eyedrop use. Samples were categorized into three groups: patients' glaucomatous eye treated with eyedrops, patients' contralateral eye without eyedrops, and healthy control eyes. Comparisons were made for microbial diversity and composition, with differences in composition tested for association with ocular surface disease measures including tear meniscus height, tear break-up time, and Dry Eye Questionnaire.

Results

Samples obtained from the patients' treated and untreated eyes both had significantly greater alpha-diversity and relative abundance of gram-negative organisms compared to healthy controls. The microbial composition of patient eyes was associated with decreased tear meniscus height and tear break-up time, whereas metagenomic predictions, based on 16S rRNA data, suggested increased synthesis of lipopolysaccharide.

Conclusions

The ocular surface microbiome of patients taking unilateral preserved glaucoma drops is characterized by a highly diverse array of gram-negative bacteria that is significantly different from the predominantly gram-positive microbes detected on healthy control eyes. These compositional differences were associated with decreased tear film measures and distinct inferred protein synthesis pathways, suggesting a potential link between microbial alterations and ocular surface inflammation.

Sequencing-based approaches for the analysis of microbial communities are susceptible to contamination, which could mask biological signals or generate artifactual ones. Methods for in silico decontamination using controls are routinely used, but do not make optimal use of information shared across samples and cannot handle taxa that only partially originate in contamination or leakage of biological material into controls. Here we present Source tracking for Contamination Removal in microBiomes (SCRuB), a probabilistic in silico decontamination method that incorporates shared information across multiple samples and controls to precisely identify and remove contamination. We validate the accuracy of SCRuB in multiple data-driven simulations and experiments, including induced contamination, and demonstrate that it outperforms state-of-the-art methods by an average of 15-20 times. We showcase the robustness of SCRuB across multiple ecosystems, data types and sequencing depths. Demonstrating its applicability to microbiome research, SCRuB facilitates improved predictions of host phenotypes, most notably the prediction of treatment response in melanoma patients using decontaminated tumor microbiome data.

In vitro evolution of drug resistance is a powerful approach for identifying antimalarial targets, however, key obstacles to eliciting resistance are the parasite inoculum size and mutation rate. Here we sought to increase parasite genetic diversity to potentiate resistance selections by editing catalytic residues of Plasmodium falciparum DNA polymerase δ. Mutation accumulation assays reveal a ~5-8 fold elevation in the mutation rate, with an increase of 13-28 fold in drug-pressured lines. Upon challenge with the spiroindolone PfATP4-inhibitor KAE609, high-level resistance is obtained more rapidly and at lower inocula than wild-type parasites. Selections also yield mutants with resistance to an irresistible compound, MMV665794 that failed to yield resistance with other strains. We validate mutations in a previously uncharacterised gene, PF3D7_1359900, which we term quinoxaline resistance protein (QRP1), as causal for resistance to MMV665794 and a panel of quinoxaline analogues. The increased genetic repertoire available to this mutator parasite can be leveraged to drive P. falciparum resistome discovery.