A computational knowledge-base elucidates the response of Staphylococcus aureus to different media types Article Swipe
Yara Seif
,
Jonathan M. Monk
,
Nathan Mih
,
Hannah Tsunemoto
,
Saugat Poudel
,
Cristal Zúñiga
,
Jared T. Broddrick
,
Karsten Zengler
,
Bernhard Ø. Palsson
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1371/journal.pcbi.1006644
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1371/journal.pcbi.1006644
S. aureus is classified as a serious threat pathogen and is a priority that guides the discovery and development of new antibiotics. Despite growing knowledge of S. aureus metabolic capabilities, our understanding of its systems-level responses to different media types remains incomplete. Here, we develop a manually reconstructed genome-scale model (GEM-PRO) of metabolism with 3D protein structures for S. aureus USA300 str. JE2 containing 854 genes, 1,440 reactions, 1,327 metabolites and 673 3-dimensional protein structures. Computations were in 85% agreement with gene essentiality data from random barcode transposon site sequencing (RB-TnSeq) and 68% agreement with experimental physiological data. Comparisons of computational predictions with experimental observations highlight: 1) cases of non-essential biomass precursors; 2) metabolic genes subject to transcriptional regulation involved in Staphyloxanthin biosynthesis; 3) the essentiality of purine and amino acid biosynthesis in synthetic physiological media; and 4) a switch to aerobic fermentation upon exposure to extracellular glucose elucidated as a result of integrating time-course of quantitative exo-metabolomics data. An up-to-date GEM-PRO thus serves as a knowledge-based platform to elucidate S. aureus' metabolic response to its environment.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1371/journal.pcbi.1006644
- OA Status
- gold
- Cited By
- 60
- References
- 98
- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
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- OpenAlex ID
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https://openalex.org/W2910511306Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1371/journal.pcbi.1006644Digital Object Identifier
- Title
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A computational knowledge-base elucidates the response of Staphylococcus aureus to different media typesWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2019Year of publication
- Publication date
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2019-01-09Full publication date if available
- Authors
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Yara Seif, Jonathan M. Monk, Nathan Mih, Hannah Tsunemoto, Saugat Poudel, Cristal Zúñiga, Jared T. Broddrick, Karsten Zengler, Bernhard Ø. PalssonList of authors in order
- Landing page
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https://doi.org/10.1371/journal.pcbi.1006644Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1371/journal.pcbi.1006644Direct OA link when available
- Concepts
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Staphylococcus aureus, Transposable element, Biology, Computational biology, Gene, Genome, Metabolomics, Metabolic pathway, Genetics, Biochemistry, Bacteria, BioinformaticsTop concepts (fields/topics) attached by OpenAlex
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60Total citation count in OpenAlex
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2025: 5, 2024: 12, 2023: 11, 2022: 10, 2021: 9Per-year citation counts (last 5 years)
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98Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.data. | 97, 158 |
| abstract_inverted_index.genes | 114 |
| abstract_inverted_index.media | 38 |
| abstract_inverted_index.model | 49 |
| abstract_inverted_index.types | 39 |
| abstract_inverted_index.USA300 | 60 |
| abstract_inverted_index.aureus | 1, 27, 59 |
| abstract_inverted_index.genes, | 65 |
| abstract_inverted_index.guides | 14 |
| abstract_inverted_index.media; | 135 |
| abstract_inverted_index.purine | 127 |
| abstract_inverted_index.random | 85 |
| abstract_inverted_index.result | 151 |
| abstract_inverted_index.serves | 163 |
| abstract_inverted_index.switch | 139 |
| abstract_inverted_index.threat | 7 |
| abstract_inverted_index.Despite | 22 |
| abstract_inverted_index.GEM-PRO | 161 |
| abstract_inverted_index.aerobic | 141 |
| abstract_inverted_index.aureus' | 171 |
| abstract_inverted_index.barcode | 86 |
| abstract_inverted_index.biomass | 110 |
| abstract_inverted_index.develop | 44 |
| abstract_inverted_index.glucose | 147 |
| abstract_inverted_index.growing | 23 |
| abstract_inverted_index.protein | 55, 73 |
| abstract_inverted_index.remains | 40 |
| abstract_inverted_index.serious | 6 |
| abstract_inverted_index.subject | 115 |
| abstract_inverted_index.exposure | 144 |
| abstract_inverted_index.involved | 119 |
| abstract_inverted_index.manually | 46 |
| abstract_inverted_index.pathogen | 8 |
| abstract_inverted_index.platform | 167 |
| abstract_inverted_index.priority | 12 |
| abstract_inverted_index.response | 173 |
| abstract_inverted_index.(GEM-PRO) | 50 |
| abstract_inverted_index.agreement | 79, 93 |
| abstract_inverted_index.different | 37 |
| abstract_inverted_index.discovery | 16 |
| abstract_inverted_index.elucidate | 169 |
| abstract_inverted_index.knowledge | 24 |
| abstract_inverted_index.metabolic | 28, 113, 172 |
| abstract_inverted_index.responses | 35 |
| abstract_inverted_index.synthetic | 133 |
| abstract_inverted_index.(RB-TnSeq) | 90 |
| abstract_inverted_index.classified | 3 |
| abstract_inverted_index.containing | 63 |
| abstract_inverted_index.elucidated | 148 |
| abstract_inverted_index.highlight: | 105 |
| abstract_inverted_index.metabolism | 52 |
| abstract_inverted_index.reactions, | 67 |
| abstract_inverted_index.regulation | 118 |
| abstract_inverted_index.sequencing | 89 |
| abstract_inverted_index.structures | 56 |
| abstract_inverted_index.transposon | 87 |
| abstract_inverted_index.up-to-date | 160 |
| abstract_inverted_index.Comparisons | 98 |
| abstract_inverted_index.development | 18 |
| abstract_inverted_index.incomplete. | 41 |
| abstract_inverted_index.integrating | 153 |
| abstract_inverted_index.metabolites | 69 |
| abstract_inverted_index.precursors; | 111 |
| abstract_inverted_index.predictions | 101 |
| abstract_inverted_index.structures. | 74 |
| abstract_inverted_index.time-course | 154 |
| abstract_inverted_index.Computations | 75 |
| abstract_inverted_index.antibiotics. | 21 |
| abstract_inverted_index.biosynthesis | 131 |
| abstract_inverted_index.environment. | 176 |
| abstract_inverted_index.essentiality | 82, 125 |
| abstract_inverted_index.experimental | 95, 103 |
| abstract_inverted_index.fermentation | 142 |
| abstract_inverted_index.genome-scale | 48 |
| abstract_inverted_index.observations | 104 |
| abstract_inverted_index.quantitative | 156 |
| abstract_inverted_index.3-dimensional | 72 |
| abstract_inverted_index.biosynthesis; | 122 |
| abstract_inverted_index.capabilities, | 29 |
| abstract_inverted_index.computational | 100 |
| abstract_inverted_index.extracellular | 146 |
| abstract_inverted_index.non-essential | 109 |
| abstract_inverted_index.physiological | 96, 134 |
| abstract_inverted_index.reconstructed | 47 |
| abstract_inverted_index.systems-level | 34 |
| abstract_inverted_index.understanding | 31 |
| abstract_inverted_index.Staphyloxanthin | 121 |
| abstract_inverted_index.knowledge-based | 166 |
| abstract_inverted_index.transcriptional | 117 |
| abstract_inverted_index.exo-metabolomics | 157 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 98 |
| corresponding_author_ids | https://openalex.org/A5090688831, https://openalex.org/A5090742414, https://openalex.org/A5088968927, https://openalex.org/A5018695597, https://openalex.org/A5084064381, https://openalex.org/A5042162895, https://openalex.org/A5023323263, https://openalex.org/A5051097609, https://openalex.org/A5072461088 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 9 |
| corresponding_institution_ids | https://openalex.org/I36258959 |
| citation_normalized_percentile.value | 0.91467631 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |