Influence of microbiome species in hard-to-heal wounds on
disease severity and treatment duration

J 2015

Influence of microbiome species in hard-to-heal wounds on disease severity and treatment duration

CHUDOBOVA, Dagmar, Kristyna CIHALOVA, Roman GURAN, Simona DOSTALOVA, Kristyna SMERKOVA et. al.

Základní údaje

Originální název

Influence of microbiome species in hard-to-heal wounds on disease severity and treatment duration

Autoři

CHUDOBOVA, Dagmar (203 Česká republika), Kristyna CIHALOVA (203 Česká republika), Roman GURAN (203 Česká republika), Simona DOSTALOVA (203 Česká republika), Kristyna SMERKOVA (203 Česká republika), Radek VESELÝ (203 Česká republika, domácí), Jaromír GUMULEC (203 Česká republika, domácí), Michal MASAŘÍK (203 Česká republika, garant, domácí), Zbynek HEGER (203 Česká republika), Vojtech ADAM (203 Česká republika) a Rene KIZEK (203 Česká republika)

Vydání

Brazilian Journal of Infectious Diseases, Rio de Janeiro, Elsevier Brazil, 2015, 1413-8670

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

30300 3.3 Health sciences

Stát vydavatele

Brazílie

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 1.412

Kód RIV

RIV/00216224:14110/15:00084692

Organizační jednotka

Lékařská fakulta

DOI

http://dx.doi.org/10.1016/j.bjid.2015.08.013

UT WoS

000365871300008

Klíčová slova anglicky

Bacterial strains; MALDI-TOF; Sequencing; Superficial wounds

Štítky

EL OK

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 29. 1. 2016 15:27, Ing. Mgr. Věra Pospíšilíková

Anotace

V originále

Background Infections, mostly those associated with colonization of wound by different pathogenic microorganisms, are one of the most serious health complications during a medical treatment. Therefore, this study is focused on the isolation, characterization, and identification of microorganisms prevalent in superficial wounds of patients (n = 50) presenting with bacterial infection. Methods After successful cultivation, bacteria were processed and analyzed. Initially the identification of the strains was performed through matrix-assisted laser desorption/ionization time-of-flight mass spectrometry based on comparison of protein profiles (2–30 kDa) with database. Subsequently, bacterial strains from infected wounds were identified by both matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and sequencing of 16S rRNA gene 108. Results The most prevalent species was Staphylococcus aureus (70%), and out of those 11% turned out to be methicillin-resistant (mecA positive). Identified strains were compared with patients’ diagnoses using the method of artificial neuronal network to assess the association between severity of infection and wound microbiome species composition. Artificial neuronal network was subsequently used to predict patients’ prognosis (n = 9) with 85% success. Conclusions In all of 50 patients tested bacterial infections were identified. Based on the proposed artificial neuronal network we were able to predict the severity of the infection and length of the treatment.

Návaznosti

ED1.1.00/02.0068, projekt VaV

Název: CEITEC - central european institute of technology

Citovat

CHUDOBOVA, Dagmar, Kristyna CIHALOVA, Roman GURAN, Simona DOSTALOVA, Kristyna SMERKOVA, Radek VESELÝ, Jaromír GUMULEC, Michal MASAŘÍK, Zbynek HEGER, Vojtech ADAM a Rene KIZEK. Influence of microbiome species in hard-to-heal wounds on disease severity and treatment duration. Brazilian Journal of Infectious Diseases. Rio de Janeiro: Elsevier Brazil, 2015, roč. 19, č. 6, s. 604-613. ISSN 1413-8670. Dostupné z: https://dx.doi.org/10.1016/j.bjid.2015.08.013.

@article{1317093,
   author = {Chudobova, Dagmar and Cihalova, Kristyna and Guran, Roman and Dostalova, Simona and Smerkova, Kristyna and Veselý, Radek and Gumulec, Jaromír and Masařík, Michal and Heger, Zbynek and Adam, Vojtech and Kizek, Rene},
   article_location = {Rio de Janeiro},
   article_number = {6},
   doi = {http://dx.doi.org/10.1016/j.bjid.2015.08.013},
   keywords = {Bacterial strains; MALDI-TOF; Sequencing; Superficial wounds},
   language = {eng},
   issn = {1413-8670},
   journal = {Brazilian Journal of Infectious Diseases},
   title = {Influence of microbiome species in hard-to-heal wounds on disease severity and treatment duration},
   url = {http://dx.doi.org/10.1016/j.bjid.2015.08.013},
   volume = {19},
   year = {2015}
}

TY  - JOUR
ID  - 1317093
AU  - Chudobova, Dagmar - Cihalova, Kristyna - Guran, Roman - Dostalova, Simona - Smerkova, Kristyna - Veselý, Radek - Gumulec, Jaromír - Masařík, Michal - Heger, Zbynek - Adam, Vojtech - Kizek, Rene
PY  - 2015
TI  - Influence of microbiome species in hard-to-heal wounds on disease severity and treatment duration
JF  - Brazilian Journal of Infectious Diseases
VL  - 19
IS  - 6
SP  - 604-613
EP  - 604-613
PB  - Elsevier Brazil
SN  - 14138670
KW  - Bacterial strains
KW  - MALDI-TOF
KW  - Sequencing
KW  - Superficial wounds
UR  - http://dx.doi.org/10.1016/j.bjid.2015.08.013
N2  - Background Infections, mostly those associated with colonization of wound by different pathogenic microorganisms, are one of the most serious health complications during a medical treatment. Therefore, this study is focused on the isolation, characterization, and identification of microorganisms prevalent in superficial wounds of patients (n = 50) presenting with bacterial infection. Methods After successful cultivation, bacteria were processed and analyzed. Initially the identification of the strains was performed through matrix-assisted laser desorption/ionization time-of-flight mass spectrometry based on comparison of protein profiles (2–30 kDa) with database. Subsequently, bacterial strains from infected wounds were identified by both matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and sequencing of 16S rRNA gene 108. Results The most prevalent species was Staphylococcus aureus (70%), and out of those 11% turned out to be methicillin-resistant (mecA positive). Identified strains were compared with patients’ diagnoses using the method of artificial neuronal network to assess the association between severity of infection and wound microbiome species composition. Artificial neuronal network was subsequently used to predict patients’ prognosis (n = 9) with 85% success. Conclusions In all of 50 patients tested bacterial infections were identified. Based on the proposed artificial neuronal network we were able to predict the severity of the infection and length of the treatment.
ER  -

CHUDOBOVA, Dagmar, Kristyna CIHALOVA, Roman GURAN, Simona DOSTALOVA, Kristyna SMERKOVA, Radek VESELÝ, Jaromír GUMULEC, Michal MASAŘÍK, Zbynek HEGER, Vojtech ADAM a Rene KIZEK. Influence of microbiome species in hard-to-heal wounds on disease severity and treatment duration. \textit{Brazilian Journal of Infectious Diseases}. Rio de Janeiro: Elsevier Brazil, 2015, roč.~19, č.~6, s.~604-613. ISSN~1413-8670. Dostupné z: https://dx.doi.org/10.1016/j.bjid.2015.08.013.

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