Título : Beyond the identifiable proteome: Delving into the proteomics of polymyxin-resistant and non-resistant Acinetobacter baumannii from Brazilian hospitals
Autor(es) : Dal Lin, Amanda
de S. da G. Fischer, Juliana
DM Santos, Marlon
Camillo-Andrade, Amanda Caroline
Ulrich Kurt, Louise
Souza, Tatiana A.C.B.
Lyrio Lajas, Ana Beatriz
Rivera, Bernardina
Portela, María Magdalena
Durán, Rosario
Távora Mira, Marcelo
Pillonetto, Marcelo
C Carvalho, Paulo
Fecha de publicación : 23-sep-2023
Tipo de publicación: Artículo
Versión: Publicado
Publicado por: Elsevier
Publicado en: Journal of Proteomics
Areas del conocimiento : Ciencias Naturales y Exactas
Ciencias Biológicas
Bioquímica y Biología Molecular
Otros descriptores : Bacteria
Proteómica
Resumen : This work discloses a unique, comprehensive proteomic dataset of Acinetobacter baumannii strains, both resistant and non-resistant to polymyxin B, isolated in Brazil generated using Orbitrap Fusion Lumos. From nearly 4 million tandem mass spectra, the software DiagnoMass produced 240,685 quality-filtered mass spectral clusters, of which PatternLab for proteomics identified 44,553 peptides mapping to 3479 proteins. Crucially, DiagnoMass shortlisted 3550 and 1408 unique mass spectral clusters for the resistant and non-resistant strains, respectively, with only about a third with sequences (and PTMs) identified by PatternLab. Further open-search attempts via FragPipe yielded an additional ~20% identifications, suggesting the remaining unidentified spectra likely arise from complex combinations of post-translational modifications and amino-acid substitutions. This highlights the untapped potential of the dataset for future discoveries, particularly given the importance of PTMs, which remain elusive to nucleotide sequencing approaches but are crucial for understanding biological mechanisms. Our innovative approach extends beyond the identifications that are typically subjected to the bias of a search engine; we discern which spectral clusters are differential and subject them to increased scrutiny, akin to spectral library matching by comparing captured spectra to themselves. Our analysis reveals adaptations in the resistant strain, including enhanced detoxification, altered protein synthesis, and metabolic adjustments. Significance: We present comprehensive proteomic profiles of non-resistant and resistant Acinetobacter baumannii from Brazilian Hospitals strains, and highlight the presence of discriminative and yet unidentified mass spectral clusters. Our work emphasizes the importance of exploring this overlooked data, as it could hold the key to understanding the complex dynamics of antibiotic resistance. This approach not only informs antimicrobial stewardship efforts but also paves the way for the development of innovative diagnostic tools. Thus, our findings have profound implications for the field, as far as methods for providing a new perspective on diagnosing antibiotic resistance as well as classifying proteomes in general.
URI / Handle: https://hdl.handle.net/20.500.12381/3555
DOI: https://doi.org/10.1016/j.jprot.2023.105012
Citación : Dal Lin Amanda , Juliana de S. da G. Fischer, Marlon D.M. Santos, Amanda Caroline Camillo-Andrade, Louise Ulrich Kurt, Tatiana A.C.B. Souza, Ana Beatriz Lyrio Lajas, Bernardina Rivera, Magdalena Portela, Rosario Duran, Marcelo Távora Mira, Marcelo Pillonetto, Paulo Costa Carvalho, Beyond the identifiable proteome: Delving into the proteomics of polymyxin-resistant and non-resistant Acinetobacter baumannii from Brazilian hospitals, Journal of Proteomics, Volume 289, 2023, 105012, ISSN 1874-3919, https://doi.org/10.1016/j.jprot.2023.105012.
Institución responsable del proyecto: Laboratory for Structural and Computational Proteomics, Carlos Chagas Institute, Fiocruz – Parana, Brazil
Laboratorio Experimental Multiuso, Pontifícia Universidade Catolica do Parana, Brazil
Analytical Biochemistry and Proteomics Unit, Institut Pasteur de Montevideo/IIBCE, Montevideo, Uruguay
Laboratorio Central do Estado do Parana, Brazil
Financiadores: Agencia Nacional de Investigación e Innovación
Fundaçao Araucaria
CNPq
CAPES
Identificador ANII: FSS_X_2022_1_173332.
Nivel de Acceso: Acceso embargado
Fin del embargo: 2024-10-30
Licencia CC: Reconocimiento-NoComercial 4.0 Internacional. (CC BY-NC)
Aparece en las colecciones: Institut Pasteur de Montevideo

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