The DOI matches its Crossref record; 103 of the 104 references it cites were found in a registry or an index.
Comparative genome-scale modelling of Staphylococcus aureus strains identifies strain-specific metabolic capabilities linked to pathogenicity
Open accessAbstract
Staphylococcus aureus is a preeminent bacterial pathogen capable of colonizing diverse ecological niches within its human host. We describe here the pangenome of S. aureus based on analysis of genome sequences from 64 strains of S. aureus spanning a range of ecological niches, host types, and antibiotic resistance profiles. Based on this set, S. aureus is expected to have an open pangenome composed of 7,411 genes and a core genome composed of 1,441 genes. Metabolism was highly conserved in this core genome; however, differences were identified in amino acid and nucleotide biosynthesis pathways between the strains. Genome-scale models (GEMs) of metabolism were constructed for the 64 strains of S. aureus These GEMs enabled a systems approach to characterizing the core metabolic and panmetabolic capabilities of the S. aureus species. All models were predicted to be auxotrophic for the vitamins niacin (vitamin B3) and thiamin (vitamin B1), whereas strain-specific auxotrophies were predicted for riboflavin (vitamin B2), guanosine, leucine, methionine, and cysteine, among others. GEMs were used to systematically analyze growth capabilities in more than 300 different growth-supporting environments. The results identified metabolic capabilities linked to pathogenic traits and virulence acquisitions. Such traits can be used to differentiate strains responsible for mild vs. severe infections and preference for hosts (e.g., animals vs. humans). Genome-scale analysis of multiple strains of a species can thus be used to identify metabolic determinants of virulence and increase our understanding of why certain strains of this deadly pathogen have spread rapidly throughout the world.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“For example, Bosi et al [24], included information from all the aforementioned databases to reconstruct 64 models of Staphylococcus aureus.”
From Traceability, reproducibility and wiki-exploration for “à-la-carte” reconstructions of genome-scale metabolic models (2018) · cites this paper as [24]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
KEGG: Kyoto Encyclopedia of Genes and Genomes
Kanehisa, M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.27 · Cited by 37,077
KEGG: Kyoto Encyclopedia of Genes and Genomes
Ogata, H., Goto, S., Sato, K., Fujibuchi, W., Bono, H., & Kanehisa, M. (1999) · Nucleic Acids Research · doi:10.1093/nar/27.1.29 · Cited by 31,232
Construction of Escherichia coli K‐12 in‐frame, single‐gene knockout mutants: the Keio collection
Baba, T., Ara, T., Hasegawa, M., Takai, Y., Okumura, Y., Baba, M., Datsenko, K. A., Tomita, M., Wanner, B. L., & Mori, H. (2006) · Molecular Systems Biology · doi:10.1038/msb4100050 · Cited by 7,858
KEGG for integration and interpretation of large-scale molecular data sets
Kanehisa, M., Goto, S., Sato, Y., Furumichi, M., & Tanabe, M. (2012) · Nucleic Acids Research · doi:10.1093/nar/gkr988 · Cited by 4,848
The COG database: an updated version includes eukaryotes
Tatusov, R. L., Fedorova, N. D., Jackson, J. D., Jacobs, A. R., Kiryutin, B., Koonin, E. V., Krylov, D. M., Mazumder, R., Mekhedov, S., Nikolskaya, A. N., et al. (2003) · BMC Bioinformatics · doi:10.1186/1471-2105-4-41 · Cited by 4,470
What is flux balance analysis?
Orth, J. D., Thiele, I., & Palsson, B. Ø. (2010) · Nature Biotechnology · doi:10.1038/nbt.1614 · Cited by 3,903
Self-citationKlevens, R. M. (2007) · JAMA · doi:10.1001/jama.298.15.1763 · Cited by 3,726
Caspi, R., Billington, R., Ferrer, L., Foerster, H., Fulcher, C. A., Keseler, I. M., Kothari, A., Krummenacker, M., Latendresse, M., Mueller, L. A., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1164 · Cited by 3,395
Multiple Sequence Alignment Using ClustalW and ClustalX
Thompson, J., Gibson, T. J., & Higgins, D. G. (2002) · Current Protocols in Bioinformatics · doi:10.1002/0471250953.bi0203s00 · Cited by 2,989
Waves of resistance: Staphylococcus aureus in the antibiotic era
Chambers, H. F., & DeLeo, F. R. (2009) · Nature Reviews Microbiology · doi:10.1038/nrmicro2200 · Cited by 2,718
Research works printed but not linked: 1
- 10.1111/j.1574-6968.1992.tb05089.x · DOI
Cited by
Sorted by citations
Items 201–271 of 271
Pan-genomics of food pathogens and its applications
Facimoto, C. T., Balbo, L. C., Chideroli, R. T., & Pereira, U. D. P. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-817076-2.00007-x
Ghafoor, R. T. A., & Yassin, A. P. H. A. L. (2020) · European Journal of Molecular & Clinical Medicine
CASTLE: A database of synthetic lethal sets predicted from genome-scale metabolic networksPreprint
Senthamizhan, V., Subramaniam, S., Raghavan, A., & Raman, K. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.02.08.430024
Caetano, A. C. B. (2018) · LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)
Research Progress on the Correlation between Skin Microbiome and Pathogenesis of Psoriasis
边, 慧. (2022) · Advances in Clinical Medicine · doi:10.12677/acm.2022.122182
(2023) · doi:10.1101/2023.07.26.550757
Self-citationHachem, A. A., Filkins, L., Kidane, Y. H., Raj, P., Tareen, N. G., Arana, C. A., Muthukrishnan, G., & Copley, L. A. (2023) · PLoS ONE · doi:10.1371/journal.pone.0288758
Poudel, S., Hyun, J., Hefner, Y., Monk, J., Nizet, V., & Palsson, B. O. (2025) · eLife · doi:10.7554/elife.90668
Self-citationWei, C. R., Basharat, Z., & Adhikari, P. (2025) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2025.110882
Unraveling the Genomic Landscape of Staphylococcus aureus in Hospital Settings of East AfricaPreprint
Olweny, G., Mboowa, G., Kayongo, A., Kidenya, B. R., & Kateete, D. P. (2025) · Research Square · doi:10.21203/rs.3.rs-6846109/v1
Lazzari, G., Felis, G. E., Salvetti, E., Calgaro, M., Cesare, F. D., Teusink, B., & Vitulo, N. (2025) · mSystems · doi:10.1128/msystems.01007-25
Smith, J. T., Eckhardt, E. M., Hansel, N. B., Eliato, T. R., Martin, I. W., & Andam, C. P. (2021) · Figshare · doi:10.6084/m9.figshare.14821181
Zondervan, N. A., dos Santos, V. A. P. M., Diez, M. S., & Saccenti, E. (2021) · Figshare · doi:10.6084/m9.figshare.13719106
Zondervan, N. A., dos Santos, V. A. P. M., Diez, M. S., & Saccenti, E. (2021) · Figshare · doi:10.6084/m9.figshare.13719076
Hof, M. V. ‘., Mohite, O. S., Monk, J. M., Weber, T., Palsson, B. O., & Sommer, M. O. A. (2024) · Figshare · doi:10.6084/m9.figshare.26558360
Self-citationHof, M. V. ‘., Mohite, O. S., Monk, J. M., Weber, T., Palsson, B. O., & Sommer, M. O. A. (2024) · Figshare · doi:10.6084/m9.figshare.26558342
Self-citationSmith, J. T., Eckhardt, E. M., Hansel, N. B., Eliato, T. R., Martin, I. W., & Andam, C. P. (2021) · Figshare · doi:10.6084/m9.figshare.14821202
Hof, M. V. ‘., Mohite, O. S., Monk, J. M., Weber, T., Palsson, B. O., & Sommer, M. O. A. (2024) · Figshare · doi:10.6084/m9.figshare.26558351
Self-citationZondervan, N. A., dos Santos, V. A. P. M., Diez, M. S., & Saccenti, E. (2021) · Figshare · doi:10.6084/m9.figshare.13719112
Hof, M. V. ‘., Mohite, O. S., Monk, J. M., Weber, T., Palsson, B. O., & Sommer, M. O. A. (2024) · Figshare · doi:10.6084/m9.figshare.26558366
Self-citationSmith, J. T., Eckhardt, E. M., Hansel, N. B., Eliato, T. R., Martin, I. W., & Andam, C. P. (2021) · Figshare · doi:10.6084/m9.figshare.14821196
Hof, M. V. ‘., Mohite, O. S., Monk, J. M., Weber, T., Palsson, B. Ø., & Sommer, M. O. A. (2024) · Figshare · doi:10.6084/m9.figshare.26558336
Self-citationHof, M. V. ‘., Mohite, O. S., Monk, J. M., Weber, T., Palsson, B. O., & Sommer, M. O. A. (2024) · Figshare · doi:10.6084/m9.figshare.26558354
Self-citationHof, M. V. ‘., Mohite, O. S., Monk, J. M., Weber, T., Palsson, B. O., & Sommer, M. O. A. (2024) · Figshare · doi:10.6084/m9.figshare.26558363
Self-citationZondervan, N. A., dos Santos, V. A. P. M., Diez, M. S., & Saccenti, E. (2021) · Figshare · doi:10.6084/m9.figshare.13719115
Hof, M. V. ‘., Mohite, O. S., Monk, J. M., Weber, T., Palsson, B. O., & Sommer, M. O. A. (2024) · Figshare · doi:10.6084/m9.figshare.26558348
Self-citationZondervan, N. A., dos Santos, V. A. P. M., Diez, M. S., & Saccenti, E. (2021) · Figshare · doi:10.6084/m9.figshare.13719079
Zondervan, N. A., dos Santos, V. A. P. M., Diez, M. S., & Saccenti, E. (2021) · Figshare · doi:10.6084/m9.figshare.13719085
Hof, M. V. ‘., Mohite, O. S., Monk, J. M., Weber, T., Palsson, B. O., & Sommer, M. O. A. (2024) · Figshare · doi:10.6084/m9.figshare.26558357
Self-citationKim, E., Jung, H.-I., Park, S. H., Kim, H.-Y., & Kim, S. (2024) · Figshare · doi:10.6084/m9.figshare.26574412
Zondervan, N. A., dos Santos, V. A. P. M., Diez, M. S., & Saccenti, E. (2021) · Figshare · doi:10.6084/m9.figshare.13719118
Zondervan, N. A., dos Santos, V. A. P. M., Diez, M. S., & Saccenti, E. (2021) · Figshare · doi:10.6084/m9.figshare.13719088
Zondervan, N. A., dos Santos, V. A. P. M., Diez, M. S., & Saccenti, E. (2021) · Figshare · doi:10.6084/m9.figshare.13719109
Smith, J. T., Eckhardt, E. M., Hansel, N. B., Eliato, T. R., Martin, I. W., & Andam, C. P. (2021) · Figshare · doi:10.6084/m9.figshare.14821190
Hof, M. V. ‘., Mohite, O. S., Monk, J. M., Weber, T., Palsson, B. O., & Sommer, M. O. A. (2024) · Figshare · doi:10.6084/m9.figshare.26558345
Self-citationHuber‐Ruano, I., Calvo, E., Mayneris‐Perxachs, J., Rodríguez-Peña, M.-M., Ceperuelo‐Mallafré, V., Cedó, L., Núñez‐Roa, C., Miró, J., Arnoriaga‐Rodríguez, M., Balvay, A., et al. (2022) · Figshare · doi:10.6084/m9.figshare.20624955
Hof, M. V. ‘., Mohite, O. S., Monk, J. M., Weber, T., Palsson, B. O., & Sommer, M. O. A. (2024) · Figshare · doi:10.6084/m9.figshare.26558339
Self-citationKim, S. J., Shin, Y., Lee, S., Kim, J., Jang, J., Kim, J., & Lee, W. (2026) · mSystems · doi:10.1128/msystems.01396-25
Real-time genomics to decipher atypical bacteria in clinical microbiology
Mlaga, K. D. (2017) · theses.fr (ABES) · doi:10.70675/c62b198fz520bz433az8b20zd67be9ef537c
Staphylococcus aureus Regulatory RNAs Driving Fitness upon Antibiotic Exposure
Liu, W. (2018) · theses.fr (ABES) · doi:10.70675/1ab43e4bz428bz410ez90c9z8b5f463c1e38
Morgene, M. F. (2018) · theses.fr (ABES) · doi:10.70675/b0196800za02fz441eza108z5f55bfa12952
da Luz, B. S. R. (2022) · theses.fr (ABES) · doi:10.70675/2e2fa4bfz4a44z4eb8za456z56828affa1d9
Jasem, K. (2026) · Microbiology Independent Research Journal (MIR Journal) · doi:10.18527/20261313646
Cross Kingdom Metabolic Engineering Paradigm Elevating Sustainable Protein Production
Du, Y., Pi, C., Hong, K., Gao, L., & Wu, X. (2026) · Advanced Science · doi:10.1002/advs.202517703
Sidarous, L. R., Ibrahim, M. S., Elhadidy, M., Abouelfetouh, A. A. Y., Saif, N. A., Aboelnaga, N., Shehat, M. G., Youssef, M., & Badr, E. (2026) · Interdisciplinary Sciences Computational Life Sciences · doi:10.1007/s12539-026-00855-2
Singh, S., & Kumar, P. (2026) · Computational Biology and Chemistry · doi:10.1016/j.compbiolchem.2026.109359
Muzahid, N. H., Patel, A., Raymond, M., Egidi, T., Nguyen, N., & Zúñiga, C. (2026) · Infection and Immunity · doi:10.1128/iai.00435-26
Jo, M.-W., Jung, S.-H., Shin, J.-I., & Chung, Y. (2026) · Genomics & Informatics · doi:10.1186/s44342-026-00086-3
Metadata
- Authors
- Bosi, E., Monk, J. M., Aziz, R. K., Fondi, M., Nizet, V., & Palsson, B. Ø.
- Affiliations
- University of Florence (IT)
- University of California San Diego (US)
- Cairo University (EG)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2016-06-10
- Volume
- 113
- Issue
- 26
- Pages
- E3801-9
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC4932939
- OpenAlex
- W2419335772
- Cited by
- 266
- References
- 104
- Citations by year
- 2026: 12 · 2025: 16 · 2024: 20 · 2023: 19 · 2022: 28 · 2021: 47 · 2020: 41 · 2019: 42 · 2018: 22 · 2017: 17 · 2016: 2
- FWCI
- 14.37
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- CINECA IRIS Institutial Research Information System (University of Genoa) (submittedVersion)
- Funders
- NIH (1R01GM057089)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
- Health Sciences › Medicine › Infectious Diseases › Antimicrobial Resistance in Staphylococcus
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Bacterial Genetics and Biotechnology
- Keywords
- Staphylococcus aureus, pan-genome, genome-scale metabolic models, auxotrophy, amino acid biosynthesis, nucleotide synthesis, host preference, ecological niche, antibiotic resistance, core genome, pathogenicity
- MeSH terms
- Models, Molecular, Species Specificity, Staphylococcus aureus, Genome, Bacterial, Virulence Factors
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review