Learning from –omics strategies applied to uncover Haemophilus influenzae host-pathogen interactions: Current status and perspectives
Haemophilus influenzae has contributed to key bacterial genome sequencing hallmarks, as being not only the first bacterium to be genome-sequenced, but also starring the first genome-wide analysis of chromosomes directly transformed with DNA from a divergent genotype, and pioneering Tn-seq methodologies. Over the years, the phenomenal and constantly evolving development of –omic technologies applied to a whole range of biological questions of clinical relevance in the H. influenzae-host interplay, has greatly moved forward our understanding of this human-adapted pathogen, responsible for multiple acute and chronic infections of the respiratory tract. In this way, essential genes, virulence factors, pathoadaptive traits, and multi-layer gene expression regulatory networks with both genomic and epigenomic complexity levels are being elucidated. Likewise, the unstoppable increasing whole genome sequencing information underpinning H. influenzae great genomic plasticity, mainly when referring to non-capsulated strains, poses major challenges to understand the genomic basis of clinically relevant phenotypes and even more, to clearly highlight potential targets of clinical interest for diagnostic, therapeutic or vaccine development. We review here how genomic, transcriptomic, proteomic and metabolomic-based approaches are great contributors to our current understanding of the interactions between H. influenzae and the human airways, and point possible strategies to maximize their usefulness in the context of biomedical research and clinical needs on this human-adapted bacterial pathogen.
Main Authors: | López-López, Nahikari, Gil-Campillo, Celia, Díez-Martínez, Roberto, Garmendia, Juncal |
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Other Authors: | Diputación Foral de Navarra |
Format: | artículo de revisión biblioteca |
Published: |
Elsevier
2021
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Subjects: | Haemophilus influenzae, Airway infection, Genome, Transcriptomes, Methylome, Proteome, Metabolome, Tn-seq, |
Online Access: | http://hdl.handle.net/10261/261533 http://dx.doi.org/10.13039/501100011033 http://dx.doi.org/10.13039/501100004587 http://dx.doi.org/10.13039/501100007509 |
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