Characterization of the Ocular Surface Microbiome in Keratitis Patients after Repeated Ophthalmic Antibiotic Exposure

ABSTRACT In human medicine, antibiotics have been widely used to treat microbial infections. The extensive use of antibiotics is a leading cause of antibiotic resistance. Currently, the influence of the use of antibiotics on the ocular surface microbiome in the course of keratitis treatment remains to be explored in depth. We performed metagenomic analyses in a cohort of 26 healthy controls (HCs), 28 keratitis patients (KPs) who received antibiotics [KP (abx+) group], and 12 KPs who were antibiotic naive [KP (abx−) group]. We identified that the dissimilarities in microbial community structure (Bray-Curtis and Jaccard analyses) between the KP (abx+) group and the HC group were greater than those between the KP (abx−) group and the HC group. Pseudomonas lactis, P. aeruginosa, Pseudomonas sp. FDAARGOS_380, Pseudomonas sp. J380, Corynebacterium simulans, Streptococcus pyogenes, Finegoldia magna, and Aspergillus oryzae had no statistically significant differences between the KP (abx+) and KP (abx−) groups but did have statistically significant differences between the KP (abx+) and HC groups and between the KP (abx−) and HC groups. Among them, Pseudomonas lactis, P. aeruginosa, Pseudomonas sp. FDAARGOS_380, and Pseudomonas sp. J380 were identified as possible hosts carrying multidrug-resistant genes. The total abundance and number of antibiotic resistance genes (ARGs) were greater in the KP (abx+) group than in the HC and KP (abx−) groups. The functional profile analysis of ocular surface microbiota revealed that pathogenesis-related functional pathways and virulence functions were enriched in KPs. In conclusion, our results show that empirical antibiotic treatment in KPs leads to increases in the antibiotic resistance of ocular surface microbiota. IMPORTANCE Treatment for keratitis is based on appropriate antimicrobial therapy. A direct correlation between antibiotic use and the extent of antibiotic resistance has been reported. Therefore, knowledge of the antibiotic resistance patterns of ocular surface microbial flora in KPs is important for clinical treatment. To the best of our knowledge, this is the first study to use metagenomic approaches to investigate the associations between ophthalmic antibiotic use and the ocular surface microbiome of KPs. Monitoring the microbiota and antibiotic resistome profiles for the ocular surface has huge potential to help ophthalmologists choose the appropriate antibiotics and will thereby improve the efficacy of treatment regimens, which has important implications for reducing the development of antibiotic resistance of the ocular surface to a certain extent. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Yutong Kang [verfasserIn] Leihao Tian [verfasserIn] Xiaobin Gu [verfasserIn] Yiju Chen [verfasserIn] Xueli Ma [verfasserIn] Shudan Lin [verfasserIn] Zhenjun Li [verfasserIn] Yongliang Lou [verfasserIn] Meiqin Zheng [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	keratitis antibiotic exposure metagenomic analysis ocular surface microbiome

Übergeordnetes Werk:	In: Microbiology Spectrum - American Society for Microbiology, 2022, 10(2022), 2
Übergeordnetes Werk:	volume:10 ; year:2022 ; number:2

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1128/spectrum.02162-21

Katalog-ID:	DOAJ033512655

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allfields	10.1128/spectrum.02162-21 doi (DE-627)DOAJ033512655 (DE-599)DOAJ8e0bbda925314f9fb68f21b19ed87ec8 DE-627 ger DE-627 rakwb eng QR1-502 Yutong Kang verfasserin aut Characterization of the Ocular Surface Microbiome in Keratitis Patients after Repeated Ophthalmic Antibiotic Exposure 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier ABSTRACT In human medicine, antibiotics have been widely used to treat microbial infections. The extensive use of antibiotics is a leading cause of antibiotic resistance. Currently, the influence of the use of antibiotics on the ocular surface microbiome in the course of keratitis treatment remains to be explored in depth. We performed metagenomic analyses in a cohort of 26 healthy controls (HCs), 28 keratitis patients (KPs) who received antibiotics [KP (abx+) group], and 12 KPs who were antibiotic naive [KP (abx−) group]. We identified that the dissimilarities in microbial community structure (Bray-Curtis and Jaccard analyses) between the KP (abx+) group and the HC group were greater than those between the KP (abx−) group and the HC group. Pseudomonas lactis, P. aeruginosa, Pseudomonas sp. FDAARGOS_380, Pseudomonas sp. J380, Corynebacterium simulans, Streptococcus pyogenes, Finegoldia magna, and Aspergillus oryzae had no statistically significant differences between the KP (abx+) and KP (abx−) groups but did have statistically significant differences between the KP (abx+) and HC groups and between the KP (abx−) and HC groups. Among them, Pseudomonas lactis, P. aeruginosa, Pseudomonas sp. FDAARGOS_380, and Pseudomonas sp. J380 were identified as possible hosts carrying multidrug-resistant genes. The total abundance and number of antibiotic resistance genes (ARGs) were greater in the KP (abx+) group than in the HC and KP (abx−) groups. The functional profile analysis of ocular surface microbiota revealed that pathogenesis-related functional pathways and virulence functions were enriched in KPs. In conclusion, our results show that empirical antibiotic treatment in KPs leads to increases in the antibiotic resistance of ocular surface microbiota. IMPORTANCE Treatment for keratitis is based on appropriate antimicrobial therapy. A direct correlation between antibiotic use and the extent of antibiotic resistance has been reported. Therefore, knowledge of the antibiotic resistance patterns of ocular surface microbial flora in KPs is important for clinical treatment. To the best of our knowledge, this is the first study to use metagenomic approaches to investigate the associations between ophthalmic antibiotic use and the ocular surface microbiome of KPs. Monitoring the microbiota and antibiotic resistome profiles for the ocular surface has huge potential to help ophthalmologists choose the appropriate antibiotics and will thereby improve the efficacy of treatment regimens, which has important implications for reducing the development of antibiotic resistance of the ocular surface to a certain extent. keratitis antibiotic exposure metagenomic analysis ocular surface microbiome Microbiology Leihao Tian verfasserin aut Xiaobin Gu verfasserin aut Yiju Chen verfasserin aut Xueli Ma verfasserin aut Shudan Lin verfasserin aut Zhenjun Li verfasserin aut Yongliang Lou verfasserin aut Meiqin Zheng verfasserin aut In Microbiology Spectrum American Society for Microbiology, 2022 10(2022), 2 (DE-627)816693293 (DE-600)2807133-5 21650497 nnns volume:10 year:2022 number:2 https://doi.org/10.1128/spectrum.02162-21 kostenfrei https://doaj.org/article/8e0bbda925314f9fb68f21b19ed87ec8 kostenfrei https://journals.asm.org/doi/10.1128/spectrum.02162-21 kostenfrei https://doaj.org/toc/2165-0497 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_252 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2022 2
spelling	10.1128/spectrum.02162-21 doi (DE-627)DOAJ033512655 (DE-599)DOAJ8e0bbda925314f9fb68f21b19ed87ec8 DE-627 ger DE-627 rakwb eng QR1-502 Yutong Kang verfasserin aut Characterization of the Ocular Surface Microbiome in Keratitis Patients after Repeated Ophthalmic Antibiotic Exposure 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier ABSTRACT In human medicine, antibiotics have been widely used to treat microbial infections. The extensive use of antibiotics is a leading cause of antibiotic resistance. Currently, the influence of the use of antibiotics on the ocular surface microbiome in the course of keratitis treatment remains to be explored in depth. We performed metagenomic analyses in a cohort of 26 healthy controls (HCs), 28 keratitis patients (KPs) who received antibiotics [KP (abx+) group], and 12 KPs who were antibiotic naive [KP (abx−) group]. We identified that the dissimilarities in microbial community structure (Bray-Curtis and Jaccard analyses) between the KP (abx+) group and the HC group were greater than those between the KP (abx−) group and the HC group. Pseudomonas lactis, P. aeruginosa, Pseudomonas sp. FDAARGOS_380, Pseudomonas sp. J380, Corynebacterium simulans, Streptococcus pyogenes, Finegoldia magna, and Aspergillus oryzae had no statistically significant differences between the KP (abx+) and KP (abx−) groups but did have statistically significant differences between the KP (abx+) and HC groups and between the KP (abx−) and HC groups. Among them, Pseudomonas lactis, P. aeruginosa, Pseudomonas sp. FDAARGOS_380, and Pseudomonas sp. J380 were identified as possible hosts carrying multidrug-resistant genes. The total abundance and number of antibiotic resistance genes (ARGs) were greater in the KP (abx+) group than in the HC and KP (abx−) groups. The functional profile analysis of ocular surface microbiota revealed that pathogenesis-related functional pathways and virulence functions were enriched in KPs. In conclusion, our results show that empirical antibiotic treatment in KPs leads to increases in the antibiotic resistance of ocular surface microbiota. IMPORTANCE Treatment for keratitis is based on appropriate antimicrobial therapy. A direct correlation between antibiotic use and the extent of antibiotic resistance has been reported. Therefore, knowledge of the antibiotic resistance patterns of ocular surface microbial flora in KPs is important for clinical treatment. To the best of our knowledge, this is the first study to use metagenomic approaches to investigate the associations between ophthalmic antibiotic use and the ocular surface microbiome of KPs. Monitoring the microbiota and antibiotic resistome profiles for the ocular surface has huge potential to help ophthalmologists choose the appropriate antibiotics and will thereby improve the efficacy of treatment regimens, which has important implications for reducing the development of antibiotic resistance of the ocular surface to a certain extent. keratitis antibiotic exposure metagenomic analysis ocular surface microbiome Microbiology Leihao Tian verfasserin aut Xiaobin Gu verfasserin aut Yiju Chen verfasserin aut Xueli Ma verfasserin aut Shudan Lin verfasserin aut Zhenjun Li verfasserin aut Yongliang Lou verfasserin aut Meiqin Zheng verfasserin aut In Microbiology Spectrum American Society for Microbiology, 2022 10(2022), 2 (DE-627)816693293 (DE-600)2807133-5 21650497 nnns volume:10 year:2022 number:2 https://doi.org/10.1128/spectrum.02162-21 kostenfrei https://doaj.org/article/8e0bbda925314f9fb68f21b19ed87ec8 kostenfrei https://journals.asm.org/doi/10.1128/spectrum.02162-21 kostenfrei https://doaj.org/toc/2165-0497 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_252 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2022 2
allfields_unstemmed	10.1128/spectrum.02162-21 doi (DE-627)DOAJ033512655 (DE-599)DOAJ8e0bbda925314f9fb68f21b19ed87ec8 DE-627 ger DE-627 rakwb eng QR1-502 Yutong Kang verfasserin aut Characterization of the Ocular Surface Microbiome in Keratitis Patients after Repeated Ophthalmic Antibiotic Exposure 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier ABSTRACT In human medicine, antibiotics have been widely used to treat microbial infections. The extensive use of antibiotics is a leading cause of antibiotic resistance. Currently, the influence of the use of antibiotics on the ocular surface microbiome in the course of keratitis treatment remains to be explored in depth. We performed metagenomic analyses in a cohort of 26 healthy controls (HCs), 28 keratitis patients (KPs) who received antibiotics [KP (abx+) group], and 12 KPs who were antibiotic naive [KP (abx−) group]. We identified that the dissimilarities in microbial community structure (Bray-Curtis and Jaccard analyses) between the KP (abx+) group and the HC group were greater than those between the KP (abx−) group and the HC group. Pseudomonas lactis, P. aeruginosa, Pseudomonas sp. FDAARGOS_380, Pseudomonas sp. J380, Corynebacterium simulans, Streptococcus pyogenes, Finegoldia magna, and Aspergillus oryzae had no statistically significant differences between the KP (abx+) and KP (abx−) groups but did have statistically significant differences between the KP (abx+) and HC groups and between the KP (abx−) and HC groups. Among them, Pseudomonas lactis, P. aeruginosa, Pseudomonas sp. FDAARGOS_380, and Pseudomonas sp. J380 were identified as possible hosts carrying multidrug-resistant genes. The total abundance and number of antibiotic resistance genes (ARGs) were greater in the KP (abx+) group than in the HC and KP (abx−) groups. The functional profile analysis of ocular surface microbiota revealed that pathogenesis-related functional pathways and virulence functions were enriched in KPs. In conclusion, our results show that empirical antibiotic treatment in KPs leads to increases in the antibiotic resistance of ocular surface microbiota. IMPORTANCE Treatment for keratitis is based on appropriate antimicrobial therapy. A direct correlation between antibiotic use and the extent of antibiotic resistance has been reported. Therefore, knowledge of the antibiotic resistance patterns of ocular surface microbial flora in KPs is important for clinical treatment. To the best of our knowledge, this is the first study to use metagenomic approaches to investigate the associations between ophthalmic antibiotic use and the ocular surface microbiome of KPs. Monitoring the microbiota and antibiotic resistome profiles for the ocular surface has huge potential to help ophthalmologists choose the appropriate antibiotics and will thereby improve the efficacy of treatment regimens, which has important implications for reducing the development of antibiotic resistance of the ocular surface to a certain extent. keratitis antibiotic exposure metagenomic analysis ocular surface microbiome Microbiology Leihao Tian verfasserin aut Xiaobin Gu verfasserin aut Yiju Chen verfasserin aut Xueli Ma verfasserin aut Shudan Lin verfasserin aut Zhenjun Li verfasserin aut Yongliang Lou verfasserin aut Meiqin Zheng verfasserin aut In Microbiology Spectrum American Society for Microbiology, 2022 10(2022), 2 (DE-627)816693293 (DE-600)2807133-5 21650497 nnns volume:10 year:2022 number:2 https://doi.org/10.1128/spectrum.02162-21 kostenfrei https://doaj.org/article/8e0bbda925314f9fb68f21b19ed87ec8 kostenfrei https://journals.asm.org/doi/10.1128/spectrum.02162-21 kostenfrei https://doaj.org/toc/2165-0497 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_252 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2022 2
allfieldsGer	10.1128/spectrum.02162-21 doi (DE-627)DOAJ033512655 (DE-599)DOAJ8e0bbda925314f9fb68f21b19ed87ec8 DE-627 ger DE-627 rakwb eng QR1-502 Yutong Kang verfasserin aut Characterization of the Ocular Surface Microbiome in Keratitis Patients after Repeated Ophthalmic Antibiotic Exposure 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier ABSTRACT In human medicine, antibiotics have been widely used to treat microbial infections. The extensive use of antibiotics is a leading cause of antibiotic resistance. Currently, the influence of the use of antibiotics on the ocular surface microbiome in the course of keratitis treatment remains to be explored in depth. We performed metagenomic analyses in a cohort of 26 healthy controls (HCs), 28 keratitis patients (KPs) who received antibiotics [KP (abx+) group], and 12 KPs who were antibiotic naive [KP (abx−) group]. We identified that the dissimilarities in microbial community structure (Bray-Curtis and Jaccard analyses) between the KP (abx+) group and the HC group were greater than those between the KP (abx−) group and the HC group. Pseudomonas lactis, P. aeruginosa, Pseudomonas sp. FDAARGOS_380, Pseudomonas sp. J380, Corynebacterium simulans, Streptococcus pyogenes, Finegoldia magna, and Aspergillus oryzae had no statistically significant differences between the KP (abx+) and KP (abx−) groups but did have statistically significant differences between the KP (abx+) and HC groups and between the KP (abx−) and HC groups. Among them, Pseudomonas lactis, P. aeruginosa, Pseudomonas sp. FDAARGOS_380, and Pseudomonas sp. J380 were identified as possible hosts carrying multidrug-resistant genes. The total abundance and number of antibiotic resistance genes (ARGs) were greater in the KP (abx+) group than in the HC and KP (abx−) groups. The functional profile analysis of ocular surface microbiota revealed that pathogenesis-related functional pathways and virulence functions were enriched in KPs. In conclusion, our results show that empirical antibiotic treatment in KPs leads to increases in the antibiotic resistance of ocular surface microbiota. IMPORTANCE Treatment for keratitis is based on appropriate antimicrobial therapy. A direct correlation between antibiotic use and the extent of antibiotic resistance has been reported. Therefore, knowledge of the antibiotic resistance patterns of ocular surface microbial flora in KPs is important for clinical treatment. To the best of our knowledge, this is the first study to use metagenomic approaches to investigate the associations between ophthalmic antibiotic use and the ocular surface microbiome of KPs. Monitoring the microbiota and antibiotic resistome profiles for the ocular surface has huge potential to help ophthalmologists choose the appropriate antibiotics and will thereby improve the efficacy of treatment regimens, which has important implications for reducing the development of antibiotic resistance of the ocular surface to a certain extent. keratitis antibiotic exposure metagenomic analysis ocular surface microbiome Microbiology Leihao Tian verfasserin aut Xiaobin Gu verfasserin aut Yiju Chen verfasserin aut Xueli Ma verfasserin aut Shudan Lin verfasserin aut Zhenjun Li verfasserin aut Yongliang Lou verfasserin aut Meiqin Zheng verfasserin aut In Microbiology Spectrum American Society for Microbiology, 2022 10(2022), 2 (DE-627)816693293 (DE-600)2807133-5 21650497 nnns volume:10 year:2022 number:2 https://doi.org/10.1128/spectrum.02162-21 kostenfrei https://doaj.org/article/8e0bbda925314f9fb68f21b19ed87ec8 kostenfrei https://journals.asm.org/doi/10.1128/spectrum.02162-21 kostenfrei https://doaj.org/toc/2165-0497 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_252 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2022 2
allfieldsSound	10.1128/spectrum.02162-21 doi (DE-627)DOAJ033512655 (DE-599)DOAJ8e0bbda925314f9fb68f21b19ed87ec8 DE-627 ger DE-627 rakwb eng QR1-502 Yutong Kang verfasserin aut Characterization of the Ocular Surface Microbiome in Keratitis Patients after Repeated Ophthalmic Antibiotic Exposure 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier ABSTRACT In human medicine, antibiotics have been widely used to treat microbial infections. The extensive use of antibiotics is a leading cause of antibiotic resistance. Currently, the influence of the use of antibiotics on the ocular surface microbiome in the course of keratitis treatment remains to be explored in depth. We performed metagenomic analyses in a cohort of 26 healthy controls (HCs), 28 keratitis patients (KPs) who received antibiotics [KP (abx+) group], and 12 KPs who were antibiotic naive [KP (abx−) group]. We identified that the dissimilarities in microbial community structure (Bray-Curtis and Jaccard analyses) between the KP (abx+) group and the HC group were greater than those between the KP (abx−) group and the HC group. Pseudomonas lactis, P. aeruginosa, Pseudomonas sp. FDAARGOS_380, Pseudomonas sp. J380, Corynebacterium simulans, Streptococcus pyogenes, Finegoldia magna, and Aspergillus oryzae had no statistically significant differences between the KP (abx+) and KP (abx−) groups but did have statistically significant differences between the KP (abx+) and HC groups and between the KP (abx−) and HC groups. Among them, Pseudomonas lactis, P. aeruginosa, Pseudomonas sp. FDAARGOS_380, and Pseudomonas sp. J380 were identified as possible hosts carrying multidrug-resistant genes. The total abundance and number of antibiotic resistance genes (ARGs) were greater in the KP (abx+) group than in the HC and KP (abx−) groups. The functional profile analysis of ocular surface microbiota revealed that pathogenesis-related functional pathways and virulence functions were enriched in KPs. In conclusion, our results show that empirical antibiotic treatment in KPs leads to increases in the antibiotic resistance of ocular surface microbiota. IMPORTANCE Treatment for keratitis is based on appropriate antimicrobial therapy. A direct correlation between antibiotic use and the extent of antibiotic resistance has been reported. Therefore, knowledge of the antibiotic resistance patterns of ocular surface microbial flora in KPs is important for clinical treatment. To the best of our knowledge, this is the first study to use metagenomic approaches to investigate the associations between ophthalmic antibiotic use and the ocular surface microbiome of KPs. Monitoring the microbiota and antibiotic resistome profiles for the ocular surface has huge potential to help ophthalmologists choose the appropriate antibiotics and will thereby improve the efficacy of treatment regimens, which has important implications for reducing the development of antibiotic resistance of the ocular surface to a certain extent. keratitis antibiotic exposure metagenomic analysis ocular surface microbiome Microbiology Leihao Tian verfasserin aut Xiaobin Gu verfasserin aut Yiju Chen verfasserin aut Xueli Ma verfasserin aut Shudan Lin verfasserin aut Zhenjun Li verfasserin aut Yongliang Lou verfasserin aut Meiqin Zheng verfasserin aut In Microbiology Spectrum American Society for Microbiology, 2022 10(2022), 2 (DE-627)816693293 (DE-600)2807133-5 21650497 nnns volume:10 year:2022 number:2 https://doi.org/10.1128/spectrum.02162-21 kostenfrei https://doaj.org/article/8e0bbda925314f9fb68f21b19ed87ec8 kostenfrei https://journals.asm.org/doi/10.1128/spectrum.02162-21 kostenfrei https://doaj.org/toc/2165-0497 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_252 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2022 2
language	English
source	In Microbiology Spectrum 10(2022), 2 volume:10 year:2022 number:2
sourceStr	In Microbiology Spectrum 10(2022), 2 volume:10 year:2022 number:2
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	keratitis antibiotic exposure metagenomic analysis ocular surface microbiome Microbiology
isfreeaccess_bool	true
container_title	Microbiology Spectrum
authorswithroles_txt_mv	Yutong Kang @@aut@@ Leihao Tian @@aut@@ Xiaobin Gu @@aut@@ Yiju Chen @@aut@@ Xueli Ma @@aut@@ Shudan Lin @@aut@@ Zhenjun Li @@aut@@ Yongliang Lou @@aut@@ Meiqin Zheng @@aut@@
publishDateDaySort_date	2022-01-01T00:00:00Z
hierarchy_top_id	816693293
id	DOAJ033512655
language_de	englisch
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callnumber-first	Q - Science
author	Yutong Kang
spellingShingle	Yutong Kang misc QR1-502 misc keratitis misc antibiotic exposure misc metagenomic analysis misc ocular surface microbiome misc Microbiology Characterization of the Ocular Surface Microbiome in Keratitis Patients after Repeated Ophthalmic Antibiotic Exposure
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topic_title	QR1-502 Characterization of the Ocular Surface Microbiome in Keratitis Patients after Repeated Ophthalmic Antibiotic Exposure keratitis antibiotic exposure metagenomic analysis ocular surface microbiome
topic	misc QR1-502 misc keratitis misc antibiotic exposure misc metagenomic analysis misc ocular surface microbiome misc Microbiology
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title	Characterization of the Ocular Surface Microbiome in Keratitis Patients after Repeated Ophthalmic Antibiotic Exposure
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title_full	Characterization of the Ocular Surface Microbiome in Keratitis Patients after Repeated Ophthalmic Antibiotic Exposure
author_sort	Yutong Kang
journal	Microbiology Spectrum
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author_browse	Yutong Kang Leihao Tian Xiaobin Gu Yiju Chen Xueli Ma Shudan Lin Zhenjun Li Yongliang Lou Meiqin Zheng
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doi_str_mv	10.1128/spectrum.02162-21
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title_sort	characterization of the ocular surface microbiome in keratitis patients after repeated ophthalmic antibiotic exposure
callnumber	QR1-502
title_auth	Characterization of the Ocular Surface Microbiome in Keratitis Patients after Repeated Ophthalmic Antibiotic Exposure
abstract	ABSTRACT In human medicine, antibiotics have been widely used to treat microbial infections. The extensive use of antibiotics is a leading cause of antibiotic resistance. Currently, the influence of the use of antibiotics on the ocular surface microbiome in the course of keratitis treatment remains to be explored in depth. We performed metagenomic analyses in a cohort of 26 healthy controls (HCs), 28 keratitis patients (KPs) who received antibiotics [KP (abx+) group], and 12 KPs who were antibiotic naive [KP (abx−) group]. We identified that the dissimilarities in microbial community structure (Bray-Curtis and Jaccard analyses) between the KP (abx+) group and the HC group were greater than those between the KP (abx−) group and the HC group. Pseudomonas lactis, P. aeruginosa, Pseudomonas sp. FDAARGOS_380, Pseudomonas sp. J380, Corynebacterium simulans, Streptococcus pyogenes, Finegoldia magna, and Aspergillus oryzae had no statistically significant differences between the KP (abx+) and KP (abx−) groups but did have statistically significant differences between the KP (abx+) and HC groups and between the KP (abx−) and HC groups. Among them, Pseudomonas lactis, P. aeruginosa, Pseudomonas sp. FDAARGOS_380, and Pseudomonas sp. J380 were identified as possible hosts carrying multidrug-resistant genes. The total abundance and number of antibiotic resistance genes (ARGs) were greater in the KP (abx+) group than in the HC and KP (abx−) groups. The functional profile analysis of ocular surface microbiota revealed that pathogenesis-related functional pathways and virulence functions were enriched in KPs. In conclusion, our results show that empirical antibiotic treatment in KPs leads to increases in the antibiotic resistance of ocular surface microbiota. IMPORTANCE Treatment for keratitis is based on appropriate antimicrobial therapy. A direct correlation between antibiotic use and the extent of antibiotic resistance has been reported. Therefore, knowledge of the antibiotic resistance patterns of ocular surface microbial flora in KPs is important for clinical treatment. To the best of our knowledge, this is the first study to use metagenomic approaches to investigate the associations between ophthalmic antibiotic use and the ocular surface microbiome of KPs. Monitoring the microbiota and antibiotic resistome profiles for the ocular surface has huge potential to help ophthalmologists choose the appropriate antibiotics and will thereby improve the efficacy of treatment regimens, which has important implications for reducing the development of antibiotic resistance of the ocular surface to a certain extent.
abstractGer	ABSTRACT In human medicine, antibiotics have been widely used to treat microbial infections. The extensive use of antibiotics is a leading cause of antibiotic resistance. Currently, the influence of the use of antibiotics on the ocular surface microbiome in the course of keratitis treatment remains to be explored in depth. We performed metagenomic analyses in a cohort of 26 healthy controls (HCs), 28 keratitis patients (KPs) who received antibiotics [KP (abx+) group], and 12 KPs who were antibiotic naive [KP (abx−) group]. We identified that the dissimilarities in microbial community structure (Bray-Curtis and Jaccard analyses) between the KP (abx+) group and the HC group were greater than those between the KP (abx−) group and the HC group. Pseudomonas lactis, P. aeruginosa, Pseudomonas sp. FDAARGOS_380, Pseudomonas sp. J380, Corynebacterium simulans, Streptococcus pyogenes, Finegoldia magna, and Aspergillus oryzae had no statistically significant differences between the KP (abx+) and KP (abx−) groups but did have statistically significant differences between the KP (abx+) and HC groups and between the KP (abx−) and HC groups. Among them, Pseudomonas lactis, P. aeruginosa, Pseudomonas sp. FDAARGOS_380, and Pseudomonas sp. J380 were identified as possible hosts carrying multidrug-resistant genes. The total abundance and number of antibiotic resistance genes (ARGs) were greater in the KP (abx+) group than in the HC and KP (abx−) groups. The functional profile analysis of ocular surface microbiota revealed that pathogenesis-related functional pathways and virulence functions were enriched in KPs. In conclusion, our results show that empirical antibiotic treatment in KPs leads to increases in the antibiotic resistance of ocular surface microbiota. IMPORTANCE Treatment for keratitis is based on appropriate antimicrobial therapy. A direct correlation between antibiotic use and the extent of antibiotic resistance has been reported. Therefore, knowledge of the antibiotic resistance patterns of ocular surface microbial flora in KPs is important for clinical treatment. To the best of our knowledge, this is the first study to use metagenomic approaches to investigate the associations between ophthalmic antibiotic use and the ocular surface microbiome of KPs. Monitoring the microbiota and antibiotic resistome profiles for the ocular surface has huge potential to help ophthalmologists choose the appropriate antibiotics and will thereby improve the efficacy of treatment regimens, which has important implications for reducing the development of antibiotic resistance of the ocular surface to a certain extent.
abstract_unstemmed	ABSTRACT In human medicine, antibiotics have been widely used to treat microbial infections. The extensive use of antibiotics is a leading cause of antibiotic resistance. Currently, the influence of the use of antibiotics on the ocular surface microbiome in the course of keratitis treatment remains to be explored in depth. We performed metagenomic analyses in a cohort of 26 healthy controls (HCs), 28 keratitis patients (KPs) who received antibiotics [KP (abx+) group], and 12 KPs who were antibiotic naive [KP (abx−) group]. We identified that the dissimilarities in microbial community structure (Bray-Curtis and Jaccard analyses) between the KP (abx+) group and the HC group were greater than those between the KP (abx−) group and the HC group. Pseudomonas lactis, P. aeruginosa, Pseudomonas sp. FDAARGOS_380, Pseudomonas sp. J380, Corynebacterium simulans, Streptococcus pyogenes, Finegoldia magna, and Aspergillus oryzae had no statistically significant differences between the KP (abx+) and KP (abx−) groups but did have statistically significant differences between the KP (abx+) and HC groups and between the KP (abx−) and HC groups. Among them, Pseudomonas lactis, P. aeruginosa, Pseudomonas sp. FDAARGOS_380, and Pseudomonas sp. J380 were identified as possible hosts carrying multidrug-resistant genes. The total abundance and number of antibiotic resistance genes (ARGs) were greater in the KP (abx+) group than in the HC and KP (abx−) groups. The functional profile analysis of ocular surface microbiota revealed that pathogenesis-related functional pathways and virulence functions were enriched in KPs. In conclusion, our results show that empirical antibiotic treatment in KPs leads to increases in the antibiotic resistance of ocular surface microbiota. IMPORTANCE Treatment for keratitis is based on appropriate antimicrobial therapy. A direct correlation between antibiotic use and the extent of antibiotic resistance has been reported. Therefore, knowledge of the antibiotic resistance patterns of ocular surface microbial flora in KPs is important for clinical treatment. To the best of our knowledge, this is the first study to use metagenomic approaches to investigate the associations between ophthalmic antibiotic use and the ocular surface microbiome of KPs. Monitoring the microbiota and antibiotic resistome profiles for the ocular surface has huge potential to help ophthalmologists choose the appropriate antibiotics and will thereby improve the efficacy of treatment regimens, which has important implications for reducing the development of antibiotic resistance of the ocular surface to a certain extent.
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title_short	Characterization of the Ocular Surface Microbiome in Keratitis Patients after Repeated Ophthalmic Antibiotic Exposure
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