Pregled bibliografske jedinice broj: 696452
Signatures of conformational stability and oxidation resistance in proteomes of pathogenic bacteria
Signatures of conformational stability and oxidation resistance in proteomes of pathogenic bacteria // Cell Reports, 7 (2014), 5; 1393-1400 doi:10.1016/j.celrep.2014.04.057 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 696452 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Signatures of conformational stability and oxidation resistance in proteomes of pathogenic bacteria
Autori
Vidović, Anita ; Supek, Fran ; Nikolić, Andrea ; Kriško, Anita
Izvornik
Cell Reports (2211-1247) 7
(2014), 5;
1393-1400
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
protein oxidation resistance; conformational stability; protein carbonylation; machine learning; pathogens; comparative genomics
Sažetak
Protein oxidation is known to compromise vital cellular functions. Therefore, invading pathogenic bacteria must resist damage inflicted by host defenses via reactive oxygen species. Using comparative genomics and experimental approaches, we provide multiple lines of evidence that proteins from pathogenic bacteria have acquired resistance to oxidative stress by an increased conformational stability. Representative pathogens exhibited higher survival upon HSP90 inhibition and a less oxidation-prone proteome. A proteome signature of the 46 pathogenic bacteria encompasses 14 physicochemical features related to increasing protein conformational stability. By purifying ten representative proteins, we demonstrate in vitro that proteins with a pathogen-like signature are more resistant to oxidative stress as a consequence of their increased conformational stability. A compositional signature of the pathogens' proteomes allowed the design of protein fragments more resilient to both unfolding and carbonylation, validating the relationship between conformational stability and oxidability with implications for synthetic biology and antimicrobial strategies.
Izvorni jezik
Engleski
Znanstvena područja
Biologija, Biotehnologija
POVEZANOST RADA
Projekti:
098-0000000-3168 - Strojno učenje prediktivnih modela u računalnoj biologiji (Šmuc, Tomislav, MZOS ) ( CroRIS)
Ustanove:
Institut "Ruđer Bošković", Zagreb,
Mediteranski institut za istraživanje života
Poveznice na cjeloviti tekst rada:
Pristup cjelovitom tekstu rada doi www.cell.com www.sciencedirect.comCitiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus
- MEDLINE