TY - JOUR
T1 - Use of a regression model to study host-genomic determinants of phage susceptibility in MRSA
AU - Zschach, Henrike
AU - Larsen, Mette V.
AU - Hasman, Henrik
AU - Westh, Henrik
AU - Nielsen, Morten
AU - Międzybrodzki, Ryszard
AU - Jónczyk-Matysiak, Ewa
AU - Weber-Dąbrowska, Beata
AU - Górski, Andrzej
PY - 2018
Y1 - 2018
N2 - Staphylococcus aureus is a major agent of nosocomial infections. Especially in methicillinresistant strains, conventional treatment options are limited and expensive, which has fueled a growing interest in phage therapy approaches. We have tested the susceptibility of 207 clinical S. aureus strains to 12 (nine monovalent) different therapeutic phage preparations and subsequently employed linear regression models to estimate the influence of individual host gene families on resistance to phages. Specifically, we used a two-step regression model setup with a preselection step based on gene family enrichment. We show that our models are robust and capture the data’s underlying signal by comparing their performance to that of models build on randomized data. In doing so, we have identified 167 gene families that govern phage resistance in our strain set and performed functional analysis on them. This revealed genes of possible prophage or mobile genetic element origin, along with genes involved in restriction-modification and transcription regulators, though the majority were genes of unknown function. This study is a step in the direction of understanding the intricate host-phage relationship in this important pathogen with the outlook to targeted phage therapy applications.
AB - Staphylococcus aureus is a major agent of nosocomial infections. Especially in methicillinresistant strains, conventional treatment options are limited and expensive, which has fueled a growing interest in phage therapy approaches. We have tested the susceptibility of 207 clinical S. aureus strains to 12 (nine monovalent) different therapeutic phage preparations and subsequently employed linear regression models to estimate the influence of individual host gene families on resistance to phages. Specifically, we used a two-step regression model setup with a preselection step based on gene family enrichment. We show that our models are robust and capture the data’s underlying signal by comparing their performance to that of models build on randomized data. In doing so, we have identified 167 gene families that govern phage resistance in our strain set and performed functional analysis on them. This revealed genes of possible prophage or mobile genetic element origin, along with genes involved in restriction-modification and transcription regulators, though the majority were genes of unknown function. This study is a step in the direction of understanding the intricate host-phage relationship in this important pathogen with the outlook to targeted phage therapy applications.
KW - Bacterial phage resistance
KW - MRSA
KW - Phage therapy
KW - Regression modeling
U2 - 10.3390/antibiotics7010009
DO - 10.3390/antibiotics7010009
M3 - Journal article
C2 - 29382143
AN - SCOPUS:85041359959
SN - 2079-6382
VL - 7
JO - Antibiotics
JF - Antibiotics
IS - 1
M1 - 9
ER -