Phenotype and multi-omics comparison of Staphylococcus and Streptococcus uncovers pathogenic traits and predicts zoonotic potential

Abstract

Background: Staphylococcus and Streptococcus species can cause many different diseases, ranging from mild skin infections to life-threatening necrotizing fasciitis. Both genera consist of commensal species that colonize the skin and nose of humans and animals, and of which some can display a pathogenic phenotype.

Results: We compared 235 Staphylococcus and 315 Streptococcus genomes based on their protein domain content. We show the relationships between protein persistence and essentiality by integrating essentiality predictions from two metabolic models and essentiality measurements from six large-scale transposon mutagenesis experiments. We identified clusters of strains within species based on proteins associated to similar biological processes. We built Random Forest classifiers that predicted the zoonotic potential. Furthermore, we identified shared attributes between of Staphylococcus aureus and Streptococcus pyogenes that allow them to cause necrotizing fasciitis.

Conclusions: Differences observed in clustering of strains based on functional groups of proteins correlate with phenotypes such as host tropism, capability to infect multiple hosts and drug resistance. Our method provides a solid basis towards large-scale prediction of phenotypes based on genomic information.

Keywords: Comparison; Host-trophism; Multi-omics; Pathogenic; Phenotype; Prediction; Staphylococcus; Streptococcus; Traits; Zoonotic.

Fig. 1

Mean observed and estimated size of the pan- and core genome. The shadowed area shows variation over 10 times sampling

Fig. 2

Protein persistence. a Staphylococcus, b Streptococcus. Group labels: All = all proteins, GEM = in silico predicted to be essential using a Genome Scale Metabolic model, Exp-Essential = experimentally determined to be essential. Combined group strains

Fig. 3

a Transcriptional variability of essential and non-essential genes in Staphylococcus. Box plots show Variability values for both groups. Difference between mean values is significant (p-val < 0.01). b Transcriptional variability of persistent and non-persistent genes (genes with persistence lower or higher than 0.95, respectively). Box plots show Variability values for both groups. Difference between mean values is significant (p-val < 0.01)

Fig. 4

a Heatmaps of the correlation between Staphylococcus functional trees, b Heatmaps of the correlation between Streptococcus functional trees

Fig. 5

a PCA based on all proteins in Staphylococcus and Streptococcus. b PCA based on proteins association to ‘response to drug’ (GO:0042493). c PCA based on proteins associated to ‘pathogenesis’ (GO:009405). Fraction of variance explained by each PC is indicated in the axis

Fig. 6

PCA plot of Streptococcus strains based on all proteins (a), proteins filtered on ‘modification of morphology or physiology of other organism’ (b) and proteins filtered on ‘pathogenesis’ (c). S. suis serotypes are shown in the label, genomes from species mentioned in literature as having zoonotic capabilities are marked with a triangle and the isolation host is marked in the label with D = dog, F = fish, H = human, P = pig, T = toad. Genomes predicted in this study to have zoonotic potential are coloured red while strains in the cluster predicted not to have zoonotic potential are coloured blue. Fraction of variance explained by each PC is indicated in the axis

Fig. 7

t-SNE plots of Streptococcus strains based on proteins all proteins (a), proteins filtered on ‘biological adhesion’ (b) and ‘pathogenesis’ (c). t-SNE is a technique for dimensional reduction and visualization, so that similar objects appear as nearby objects in the two-dimensional plots here presented. S. suis serotypes are shown in the label, genomes from species mentioned in literature as having zoonotic capabilities are marked with a triangle and the isolation host is marked in the label with D = dog, F = fish, H = human, P = pig, T = toad. Genomes predicted in this study to be part of the zoonotic potential cluster are coloured red while strains in the cluster predicted not to have zoonotic potential are coloured blue. Fraction of variance explained by each PC is indicated in the axis

Fig. 8

Protein feature contribution to predict the class ‘non-zoonotic’ and ‘zoonotic’ as well as the overall importance of the protein feature for classification. a The five most important ‘modification of morphology or physiology of other organism’ proteins used to classify S. suis. b The five most important ‘pathogenesis’ proteins used to classify S. suis. c The five most important ‘biological adhesion’ proteins used to classify S. agalactiae. d The five most important ‘pathogenesis’ proteins used to classify S. agalactiae