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Cited by 358

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A genome-scale analysis for identification of genes required for growth or survival of Haemophilus influenzae

Open access
Akerley, Brian J., Rubin, Eric J., Novick, Veronica L., Amaya, Kensey, Judson, Nicholas, Mekalanos, John J.·2002·Proceedings of the National Academy of Sciences

Abstract

A high-density transposon mutagenesis strategy was applied to the Haemophilus influenzae genome to identify genes required for growth or viability. This analysis detected putative essential roles for the products of 259 ORFs of unknown function. Comparisons between complete genomes defined a subset of these proteins in H. influenzae having homologs in Mycobacterium tuberculosis that are absent in Saccharomyces cerevisiae , a distribution pattern that favors their use in development of antimicrobial therapeutics. Three genes within this set are essential for viability in other bacteria. Interfacing the set of essential gene products in H. influenzae with the distribution of homologs in other microorganisms can detect components of unrecognized cellular pathways essential in diverse bacteria. This genome-scale phenotypic analysis identifies potential roles for a large set of genes of unknown function.

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Metadata

Authors
Akerley, B. J., Rubin, E. J., Novick, V. L., Amaya, K., Judson, N., & Mekalanos, J. J.
Venue
Proceedings of the National Academy of Sciences
Published
2002-01-22
Volume
99
Issue
2
Pages
966-971
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W1974299093
Cited by
358
References
1
FWCI
15.84
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: A genome-scale analysis for identification of genes required for growth or survival of Haemophilus influenzae. https://app.cochat.ai/papers/10.1073/pnas.012602299
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Akerley, B. J., Rubin, E. J., Novick, V. L., Amaya, K., Judson, N., & Mekalanos, J. J. (2002). A genome-scale analysis for identification of genes required for growth or survival of Haemophilus influenzae. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.012602299

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.