Metagenomic analysis of microbiological changes on the ocular surface of diabetic children and adolescents with a dry eye

From BugSigDB
Needs review
study design
Citation
PMID PubMed identifier for scientific articles.
DOI Digital object identifier for electronic documents.
URI
Authors
Chen Z, Xiao Y, Jia Y, Lin Q, Qian Y, Cui L, Xiang Z, Li M, Yang C, Zou H
Journal
BMC microbiology
Year
2023
Keywords:
Children and adolescents, Diabetes mellitus, Dry eye, Metagenome, Microecology, Ocular surface
BACKGROUND: Microbiome changes on the ocular surface may cause dry eyes. A metagenome assay was used to compare the microbiome composition and function of the ocular surface between diabetic children and adolescents with dry eye, diabetic children and adolescents without dry eye, and normal children. MATERIALS AND METHODS: Twenty children and adolescents aged 8 to 16 with diabetes were selected from the Shanghai Children and Adolescent Diabetes Eye Study. Ten healthy children and adolescents belonging to the same age group were selected from the outpatient clinic during the same period. The participants were classified into the dry eye group (DM-DE group, n = 10), the non-dry eye group (DM-NDE group, n = 10) and the normal group (NDM group, n = 10). A conjunctival sac swab was collected for metagenomic sequencing, and the relationship between the microbiome composition and functional gene differences on the ocular surface with dry eye was studied. RESULTS: The classification composition and metabolic function of the microorganisms on the ocular surface of children in the 3 groups were analyzed. It was found that children's ocular microbiota was composed of bacteria, viruses and fungi. There were significant differences in α diversity and β diversity of microbial composition of ocular surface between DM-DE group and NDM group(P<0.05). There were significant differences in α and β diversity of metabolic pathways between the two groups(P<0.05). The functional pathways of ocular surface microorganisms in diabetic children with dry eyes were mainly derived from human disease, antibiotic resistance genes, carbohydrate, coenzyme and lipid transport and metabolism-related functional genes; In normal children, the functional pathways were mainly derived from replication, recombination, repair, signal transduction and defense-related functional genes. CONCLUSION: The DM-DE group have unique microbial composition and functional metabolic pathways. The dominant species and unique metabolic pathways of the ocular surface in the DM-DE group may be involved in the pathogenesis of dry eye in diabetic children.

Experiment 1


Needs review

Curated date: 2023/11/11

Curator: Mary Bearkland

Revision editor(s): Mary Bearkland

Subjects

Location of subjects
China
Host species Species from which microbiome was sampled. Contact us to have more species added.
Homo sapiens
Body site Anatomical site where microbial samples were extracted from according to the Uber Anatomy Ontology
Conjunctival sac Conjunctiva serous sac,Subbrillar sac,Conjunctival sac
Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology
dry eye syndrome dry eye,Dry Eye Syndrome,dry eye syndrome,Dry Eye Syndromes,dry eye(s),eye(s), dry,KCS,Keraconjunctivitis sicca,Keratoconjunctivitis Sicca,Keratoconjunctivitis sicca,keratoconjunctivitis sicca,Keratoconjunctivitis sicca (disorder),sicca, keratoconjunctivitis,Tear film insufficiency,tear film insufficiency
Group 0 name Corresponds to the control (unexposed) group for case-control studies
Normal healthy (NDM) children
Group 1 name Corresponds to the case (exposed) group for case-control studies
Diabetic children with Dry Eye Disease
Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
Children aged 8-16 with Diabetes and Dry Eye Disease
Group 0 sample size Number of subjects in the control (unexposed) group
18
Group 1 sample size Number of subjects in the case (exposed) group
15

Lab analysis

Sequencing type
WMS
16S variable region One or more hypervariable region(s) of the bacterial 16S gene
Not specified
Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance
Illumina

Statistical Analysis

Data transformation Data transformation applied to microbial abundance measurements prior to differential abundance testing (if any).
relative abundances
Statistical test
LEfSe
Significance threshold p-value or FDR threshold used for differential abundance testing (if any)
0.05
Matched on Factors on which subjects have been matched on in a case-control study
age, body mass index, sex

Alpha Diversity

Chao1 Abundance-based estimator of species richness
decreased
Richness Number of species
decreased

Signature 1

Needs review

Curated date: 2023/11/11

Curator: Mary Bearkland

Revision editor(s): Mary Bearkland

Source: Figure 3g and text

Description: Fig 3g: Species composition with significant difference at the species level between the NDM and DM-DE groups (top 20)

Abundance in Group 1: decreased abundance in Diabetic children with Dry Eye Disease

NCBI Quality ControlLinks
Staphylococcus aureus
Mycobacteroides abscessus
Paenibacillus odorifer
Vibrio agarivorans
Streptococcus gordonii
Novosphingobium nitrogenifigens
Novosphingobium sp. Fuku2-ISO-50

Revision editor(s): Mary Bearkland

Signature 2

Needs review

Curated date: 2023/11/11

Curator: Mary Bearkland

Revision editor(s): Mary Bearkland

Source: Figure 3g

Description: Figure 3g Species composition with significant difference at the species level between the NDM and DM-DE groups (top 20)

Abundance in Group 1: increased abundance in Diabetic children with Dry Eye Disease

NCBI Quality ControlLinks
Vibrio vulnificus
Salmonella enterica
Enterobacter mori
Cordyceps militaris
Leuconostoc sp. DORA_2

Revision editor(s): Mary Bearkland

Experiment 2


Needs review

Curated date: 2023/11/18

Curator: Mary Bearkland

Revision editor(s): Mary Bearkland

Differences from previous experiment shown

Subjects

Lab analysis

Statistical Analysis

Statistical test
ANOSIM

Alpha Diversity

Chao1 Abundance-based estimator of species richness
decreased
Richness Number of species
decreased

Signature 1

Needs review

Curated date: 2023/11/18

Curator: Mary Bearkland

Revision editor(s): Mary Bearkland

Source: Text on page 5

Description: At the phylum level, the abundance of Apicomplexa, Actinobacteria, Chlamydiae and Ascomycota in the DM-DE group was significantly higher than that in the NDM group. The abundance of Firmicutes and Proteobacteria in the NDM group was significantly higher than that in the DM-DE group. At the genus level, the abundance of Plasmodium, Mycobacterium, Escherichia, Vibrio, Leuconostoc, Chlamydia and Enterobacter in the DM-DE group was significantly higher than that in the NDM group. The abundance of Enterococcus, Streptococcus, Staphylococcus and Acinetobacter in the NDM group was significantly higher than that in the DM-DE group. At the species level, the abundance of P. ovale, E. coli, S. enterica, M. leprae, L. sp. DORA_2 and C. trachomatis in the DM-DE group were significantly higher than those in the NDM group. The abundance of E. faecalis, S. pneumoniae, S. aureus and A. johnsonii in the NDM group was significantly higher than that in the DM-DE group.

Abundance in Group 1: increased abundance in Diabetic children with Dry Eye Disease

NCBI Quality ControlLinks
Actinomycetota
Apicomplexa
Ascomycota
Chlamydia
Chlamydia trachomatis
Chlamydiota
Enterobacter
Escherichia
Escherichia coli
Leuconostoc
Mycobacterium
Mycobacterium leprae
Plasmodium (Plasmodium)
Plasmodium ovale
Salmonella enterica
Vibrio
Leuconostoc sp. DORA_2

Revision editor(s): Mary Bearkland

Signature 2

Needs review

Curated date: 2023/11/18

Curator: Mary Bearkland

Revision editor(s): Mary Bearkland

Source: Text on page 5

Description: At the phylum level, the abundance of Apicomplexa, Actinobacteria, Chlamydiae and Ascomycota in the DM-DE group was significantly higher than that in the NDM group. The abundance of Firmicutes and Proteobacteria in the NDM group was significantly higher than that in the DM-DE group. At the genus level, the abundance of Plasmodium, Mycobacterium, Escherichia, Vibrio, Leuconostoc, Chlamydia and Enterobacter in the DM-DE group was significantly higher than that in the NDM group. The abundance of Enterococcus, Streptococcus, Staphylococcus and Acinetobacter in the NDM group was significantly higher than that in the DM-DE group. At the species level, the abundance of P. ovale, E. coli, S. enterica, M. leprae, L. sp. DORA_2 and C. trachomatis in the DM-DE group were significantly higher than those in the NDM group. The abundance of E. faecalis, S. pneumoniae, S. aureus and A. johnsonii in the NDM group was significantly higher than that in the DM-DE group.

Abundance in Group 1: decreased abundance in Diabetic children with Dry Eye Disease

NCBI Quality ControlLinks
Pseudomonadota
Bacillota
Enterococcus
Streptococcus
Staphylococcus
Acinetobacter
Enterococcus faecalis
Streptococcus pneumoniae
Staphylococcus aureus
Acinetobacter johnsonii

Revision editor(s): Mary Bearkland