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Phenotype and Multi-Omics Comparison of Staphylococcus and Streptococcus Uncovers Pathogenic Traits and Predicts Zoonotic Potential Niels A

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Phenotype and Multi-Omics Comparison of Staphylococcus and Streptococcus Uncovers Pathogenic Traits and Predicts Zoonotic Potential Niels A Zondervan et al. BMC Genomics (2021) 22:102 https://doi.org/10.1186/s12864-021-07388-6 RESEARCH ARTICLE Open Access Phenotype and multi-omics comparison of Staphylococcus and Streptococcus uncovers pathogenic traits and predicts zoonotic potential Niels A. Zondervan1, Vitor A. P. Martins dos Santos1,2, Maria Suarez-Diez1† and Edoardo Saccenti1*† 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: Staphylococcus, Streptococcus, Multi-omics, Comparison, Pathogenic, Traits, Prediction, Phenotype, Host-trophism, Zoonotic Background Few comparative genomic studies have been performed Species from the genera Staphylococcus and Streptococ- to analyse the evolution and the pathogenesis of Staphylo- cus are mostly commensals that live as part of the coccus and Streptococcus species: the comparisons of the ge- microbiota of various animals and humans [1]. Some of nomes of 11 Staphylococcus species determined that them are opportunistic pathogens, displaying a patho- horizontal gene transfer of virulence factors is an important genic phenotype when the immune system of the host is factor in adaptation of S. aureus to humans [6]; another compromised or the epithelial barrier is damaged [2–5]. study showed that protein domain based metabolic diver- sity among Streptococcus species could be used to identify differences in the metabolism of the highly pathogenic sero- * Correspondence: [email protected] type 2 S. suis compared to other Streptococci [7]. Another †Maria Suarez-Diez and Edoardo Saccenti these authors jointly supervised study confirmed these results and showed that metabolic this work. capability predicted using genome scale models (GEMs) 1Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Stippeneng 4, 6708WE Wageningen, Netherlands Full list of author information is available at the end of the article © The Author(s). 2021, corrected publication 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/ licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1. 0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Zondervan et al. BMC Genomics (2021) 22:102 Page 2 of 21 couldbeusedtoidentifyStreptococcus strain specific bio- pathogenic phenotypes. We compared the clustering of markers and metabolic determinants of virulence [8]. Staphylococcus and Streptococcus genomes based on pro- Protein domains and protein-domain architectures teins selected using on Gene Ontology (GO) terms asso- have been shown to be a fast and efficient method to de- ciated with clinical phenotypes such drug resistance, fine groups of functionally equivalent proteins that were pathogenesis, and tissue and host tropism. Furthermore, used for comparative genomic studies [9, 10], including we used the functional grouping of proteins to predict Staphylococcus and Streptococcus [11–13]. However, at zoonotic potential of S. suis and S. agalactiae, that is the best of our knowledge, no work exists focusing on their ability to infect multiple hosts including humans. similarities and differences within and between Staphylo- Finally, we compared S. aureus and S. pyogenes to iden- coccus and Streptococcus genomes. tify the genomic basis for their shared ability to cause se- In this study we performed a comparative analysis of vere bacterial infections like necrotizing fasciitis. Our 235 and 315 fully sequenced Staphylococci and Strepto- results are compared throughout the paper with findings cocci genomes by annotating their proteins based on from literature. their domain content. We integrated this protein anno- tation with genome-scale metabolic-modelling predic- tions, transcriptomic and transposon-mutagenesis data Results sets to study gene essentiality and persistence. All anno- Pan- and core genome analysis tation used in this paper as well as GO information is The size of the pan- and core genomes of Staphylococcus based on genomics annotation from databases based and Streptococcus was determined based on protein do- mainly on bacterial genomics studies. In this paper we main content (Fig. 1). The pangenome contains all pro- compare within and between Staphylococcus and teins present in the analysed genomes. The core genome Streptococcus species with the objective to identify both contains only proteins that are present in all genomes difference and similarities in genomic properties as well and represents their genomic essence [14]. The ratio of as in specific combinations of genes that give rise to the sizes of the core- and pan genome are 0.22 (557/ Fig. 1 Mean observed and estimated size of the pan- and core genome. The shadowed area shows variation over 10 times sampling Zondervan et al. BMC Genomics (2021) 22:102 Page 3 of 21 2563) for Staphylococcus and 0.17 (458/2725) for Table 1 Persistence of Staphylococcus (Staph.) and Streptococcus Streptococcus. (Strep.) for all proteins, proteins associated to Genome A Heaps’ regression model was used to estimate the Metabolic model (GEM) essential genes and experimentally closedness of the pangenome [15]. The closedness of the (EXP) determined essential genes pangenome represents how much the addition of more Group Avg persistence Staph. Avg persistence Strep. genome sequences is expected to increase the number of All 0.60 ± 0.44 (N = 2655) 0.42 ± 0.42 (N = 3047) proteins in the pangenome. For both Staphylococcus GEM-essential 0.94 ± 0.14 (N = 153) 0.98 ± 0.09 (N = 225) α α ( = 1.10 ± 0.02) and Streptococcus ( = 1.12 ± 0.01) the Exp-Essential 0.97 ± 0.03 (N = 411) 0.97 ± 0.12 (N = 254) pangenome was found to be closed (i.e few new genes EXP&GEM-Essential 0.94 ± 0.01 (N = 46) 0.98 ± 0.00 (N = 113) are added as news strains are discovered/sequenced). Additional plots of the estimated pan- and core genomes size and the Heaps’ regression model can be found in Variability of gene expression and gene essentiality supplementary material (see Additional file 5). Essentiality and domain persistence information for Staphylococcus was combined with the variability of transcription (measured by log2 fold changes). The vari- Protein persistence and essentiality ability in expression for experimentally determined es- Persistence of proteins over all Staphylococcus and all sential and non-essential genes as well as for persistent Streptococcus species was calculated. Protein persistence and non-persistent genes were compared (Fig. 3). The data was combined with model predictions of essentiality fold change transcription levels of experimentally deter- and experimentally determined essentiality data.Experi- mined essential genes are significantly less variable than mentally determined essentiality (labelled as EXP) is avail- the transcription levels of non-essential genes (Student’s − able for growth on rich media resembling in vivo t-test, p-value = 5 × 10 14) as well as for persistent genes conditions. GEMs predictions were made using minimal (Student’s t-test, p-value = 0.000124)). media conditions for all combinations of carbon, nitrogen, sulphur, and phosphorus sources. Simulations on rich Functional analysis of pathogenesis and pathogenicity media conditions were therefore indirectly performed For this analysis, we filtered proteins from Staphylococ- since all rich media compounds are present in the models cus and Streptococcus on their association to 17 genome as exchange reactions and all combinations of these ex- ontology (GO) biological process terms associated
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