Abstract
Proteomics is particularly suitable for characterising human pathogens with high life cycle complexity, such as fungi. Protein content and expression levels may be affected by growth states and life cycle morphs and correlate to species and strain variation. Identification and typing of fungi by conventional methods are often difficult, time-consuming and frequently, for unusual species, inconclusive. Proteomic phenotypes from MALDI-TOF MS were employed as analytical and typing expression profiling of yeast, yeast-like species and strain variants in order to achieve a microbial proteomics population study. Spectra from 303 clinical isolates were generated and processed by standard pattern matching with a MALDI-TOF Biotyper (MT). Identifications (IDs) were compared to a reference biochemical-based system (Vitek-2) and, when discordant, MT IDs were verified with genotyping IDs, obtained by sequencing the 25-28S rRNA hypervariable D2 region. Spectra were converted into virtual gel-like formats, and hierarchical clustering analysis was performed for 274 Candida profiles to investigate species and strain typing correlation. MT provided 257/303 IDs consistent with Vitek-2 ones. However, amongst 26/303 discordant MT IDs, only 5 appeared "true". No MT identification was achieved for 20/303 isolates for incompleteness of database species variants. Candida spectra clustering agreed with identified species and topology of Candida albicans and Candida parapsilosis specific dendrograms. MT IDs show a high analytical performance and profiling heterogeneity which seems to complement or even outclass existing typing tools. This variability reflects the high biological complexity of yeasts and may be properly exploited to provide epidemiological tracing and infection dispersion patterns.
| Original language | English |
|---|---|
| Pages (from-to) | 620-629 |
| Number of pages | 10 |
| Journal | Molecular BioSystems |
| Volume | 7 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - Mar 1 2011 |
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ASJC Scopus subject areas
- Biotechnology
- Molecular Biology
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MALDI-TOF mass spectrometry proteomic phenotyping of clinically relevant fungi. / Putignani, Lorenza; Del Chierico, Federica; Onori, Manuela; Mancinelli, Livia; Argentieri, Marta; Bernaschi, Paola; Coltella, Luana; Lucignano, Barbara; Pansani, Laura; Ranno, Stefania; Russo, Cristina; Urbani, Andrea; Federici, Giorgio; Menichella, Donato.
In: Molecular BioSystems, Vol. 7, No. 3, 01.03.2011, p. 620-629.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - MALDI-TOF mass spectrometry proteomic phenotyping of clinically relevant fungi
AU - Putignani, Lorenza
AU - Del Chierico, Federica
AU - Onori, Manuela
AU - Mancinelli, Livia
AU - Argentieri, Marta
AU - Bernaschi, Paola
AU - Coltella, Luana
AU - Lucignano, Barbara
AU - Pansani, Laura
AU - Ranno, Stefania
AU - Russo, Cristina
AU - Urbani, Andrea
AU - Federici, Giorgio
AU - Menichella, Donato
PY - 2011/3/1
Y1 - 2011/3/1
N2 - Proteomics is particularly suitable for characterising human pathogens with high life cycle complexity, such as fungi. Protein content and expression levels may be affected by growth states and life cycle morphs and correlate to species and strain variation. Identification and typing of fungi by conventional methods are often difficult, time-consuming and frequently, for unusual species, inconclusive. Proteomic phenotypes from MALDI-TOF MS were employed as analytical and typing expression profiling of yeast, yeast-like species and strain variants in order to achieve a microbial proteomics population study. Spectra from 303 clinical isolates were generated and processed by standard pattern matching with a MALDI-TOF Biotyper (MT). Identifications (IDs) were compared to a reference biochemical-based system (Vitek-2) and, when discordant, MT IDs were verified with genotyping IDs, obtained by sequencing the 25-28S rRNA hypervariable D2 region. Spectra were converted into virtual gel-like formats, and hierarchical clustering analysis was performed for 274 Candida profiles to investigate species and strain typing correlation. MT provided 257/303 IDs consistent with Vitek-2 ones. However, amongst 26/303 discordant MT IDs, only 5 appeared "true". No MT identification was achieved for 20/303 isolates for incompleteness of database species variants. Candida spectra clustering agreed with identified species and topology of Candida albicans and Candida parapsilosis specific dendrograms. MT IDs show a high analytical performance and profiling heterogeneity which seems to complement or even outclass existing typing tools. This variability reflects the high biological complexity of yeasts and may be properly exploited to provide epidemiological tracing and infection dispersion patterns.
AB - Proteomics is particularly suitable for characterising human pathogens with high life cycle complexity, such as fungi. Protein content and expression levels may be affected by growth states and life cycle morphs and correlate to species and strain variation. Identification and typing of fungi by conventional methods are often difficult, time-consuming and frequently, for unusual species, inconclusive. Proteomic phenotypes from MALDI-TOF MS were employed as analytical and typing expression profiling of yeast, yeast-like species and strain variants in order to achieve a microbial proteomics population study. Spectra from 303 clinical isolates were generated and processed by standard pattern matching with a MALDI-TOF Biotyper (MT). Identifications (IDs) were compared to a reference biochemical-based system (Vitek-2) and, when discordant, MT IDs were verified with genotyping IDs, obtained by sequencing the 25-28S rRNA hypervariable D2 region. Spectra were converted into virtual gel-like formats, and hierarchical clustering analysis was performed for 274 Candida profiles to investigate species and strain typing correlation. MT provided 257/303 IDs consistent with Vitek-2 ones. However, amongst 26/303 discordant MT IDs, only 5 appeared "true". No MT identification was achieved for 20/303 isolates for incompleteness of database species variants. Candida spectra clustering agreed with identified species and topology of Candida albicans and Candida parapsilosis specific dendrograms. MT IDs show a high analytical performance and profiling heterogeneity which seems to complement or even outclass existing typing tools. This variability reflects the high biological complexity of yeasts and may be properly exploited to provide epidemiological tracing and infection dispersion patterns.
UR - http://www.scopus.com/inward/record.url?scp=79951619802&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79951619802&partnerID=8YFLogxK
U2 - 10.1039/c0mb00138d
DO - 10.1039/c0mb00138d
M3 - Article
C2 - 20967323
AN - SCOPUS:79951619802
VL - 7
SP - 620
EP - 629
JO - Molecular BioSystems
JF - Molecular BioSystems
SN - 1742-206X
IS - 3
ER -