Fig 1.
Overview of the different steps in sampling, extraction, cDNA synthesis, library building, sequencing and bioinformatics used in our protocol for the detection and quantification of human viral pathogens from airplane toilet waste.
Fig 2.
Heatmap of the top 50 most abundant viruses in the airplane toilet waste.
Read number values were converted to Viral Reads Per Million (VRPM) and log 10 transformed. Hierarchical clustering was done on the airplane samples and colored by region. The putative viral host is marked in the left column. In some cases the host is debated, and these are discussed more in the Discussion and Strengths and Limitations sections.
Fig 3.
Principal component analysis (PCA) of the airplane sewage viral community composition.
Log10 transformed viral reads per million (VRPM) values for the 12 most abundant virus families were used as input. The individual samples are colored according to their assigned region.
Fig 4.
Viral species richness of the samples grouped according to their city of departure.
Statistical analysis was done on region level, using Anova to test for significance (p<0.05) followed by pairwise t-tests with Bonferroni correction for multiple testing. ** = p<0.01.
Fig 5.
Enteric viruses detected in the sewage from the 19 airplanes.
The airplane samples are grouped according to their departing city (n = 1–3). The y-axis was log-transformed viral reads per million (VRPM). For the statistical analysis, the cities were grouped according to their assigned region, and tested for significance using the Kruskal-Wallis rank sum test. If significant, the pairwise significance was determined using the Wilcoxon test with Bonferroni correction for multiple testing. * = p-Wilcoxon < 0.05, ** = p-Wilcoxon < 0.01, † = p-Kruskal-Wallis < 0.05.