Optimisation of methods for bacterial skin microbiome investigation: primer selection and comparison of the 454 versus MiSeq platform View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2017-01-21

AUTHORS

Madhura Castelino, Stephen Eyre, John Moat, Graeme Fox, Paul Martin, Pauline Ho, Mathew Upton, Anne Barton

ABSTRACT

BackgroundThe composition of the skin microbiome is predicted to play a role in the development of conditions such as atopic eczema and psoriasis. 16S rRNA gene sequencing allows the investigation of bacterial microbiota. A significant challenge in this field is development of cost effective high throughput methodologies for the robust interrogation of the skin microbiota, where biomass is low. Here we describe validation of methodologies for 16S rRNA (ribosomal ribonucleic acid) gene sequencing from the skin microbiome, using the Illumina MiSeq platform, the selection of primer to amplify regions for sequencing and we compare results with the current standard protocols..MethodsDNA was obtained from two low density mock communities of 11 diverse bacterial strains (with and without human DNA supplementation) and from swabs taken from the skin of healthy volunteers. This was amplified using primer pairs covering hypervariable regions of the 16S rRNA gene: primers 63F and 519R (V1-V3); and 347F and 803R (V3-V4). The resultant libraries were indexed for the MiSeq and Roche454 and sequenced. Both data sets were denoised, cleaned of chimeras and analysed using QIIME.ResultsThere was no significant difference in the diversity indices at the phylum and the genus level observed between the platforms. The capture of diversity using the low density mock community samples demonstrated that the primer pair spanning the V3-V4 hypervariable region had better capture when compared to the primer pair for the V1-V3 region and was robust to spiking with human DNA. The pilot data generated using the V3-V4 region from the skin of healthy volunteers was consistent with these results, even at the genus level (Staphylococcus, Propionibacterium, Corynebacterium, Paracoccus, Micrococcus, Enhydrobacter and Deinococcus identified at similar abundances on both platforms).ConclusionsThe results suggest that the bacterial community diversity captured using the V3-V4 16S rRNA hypervariable region from sequencing using the MiSeq platform is comparable to the Roche454 GS Junior platform. These findings provide evidence that the optimised method can be used in human clinical samples of low bacterial biomass such as the investigation of the skin microbiota. More... »

PAGES

23

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s12866-017-0927-4

DOI

http://dx.doi.org/10.1186/s12866-017-0927-4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1054049199

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/28109256


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38 schema:description BackgroundThe composition of the skin microbiome is predicted to play a role in the development of conditions such as atopic eczema and psoriasis. 16S rRNA gene sequencing allows the investigation of bacterial microbiota. A significant challenge in this field is development of cost effective high throughput methodologies for the robust interrogation of the skin microbiota, where biomass is low. Here we describe validation of methodologies for 16S rRNA (ribosomal ribonucleic acid) gene sequencing from the skin microbiome, using the Illumina MiSeq platform, the selection of primer to amplify regions for sequencing and we compare results with the current standard protocols..MethodsDNA was obtained from two low density mock communities of 11 diverse bacterial strains (with and without human DNA supplementation) and from swabs taken from the skin of healthy volunteers. This was amplified using primer pairs covering hypervariable regions of the 16S rRNA gene: primers 63F and 519R (V1-V3); and 347F and 803R (V3-V4). The resultant libraries were indexed for the MiSeq and Roche454 and sequenced. Both data sets were denoised, cleaned of chimeras and analysed using QIIME.ResultsThere was no significant difference in the diversity indices at the phylum and the genus level observed between the platforms. The capture of diversity using the low density mock community samples demonstrated that the primer pair spanning the V3-V4 hypervariable region had better capture when compared to the primer pair for the V1-V3 region and was robust to spiking with human DNA. The pilot data generated using the V3-V4 region from the skin of healthy volunteers was consistent with these results, even at the genus level (Staphylococcus, Propionibacterium, Corynebacterium, Paracoccus, Micrococcus, Enhydrobacter and Deinococcus identified at similar abundances on both platforms).ConclusionsThe results suggest that the bacterial community diversity captured using the V3-V4 16S rRNA hypervariable region from sequencing using the MiSeq platform is comparable to the Roche454 GS Junior platform. These findings provide evidence that the optimised method can be used in human clinical samples of low bacterial biomass such as the investigation of the skin microbiota.
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44 schema:keywords ConclusionsThe results
45 DNA
46 GS Junior platform
47 Illumina MiSeq platform
48 MethodsDNA
49 MiSeq
50 MiSeq platform
51 QIIME
52 ResultsThere
53 V1-V3 region
54 V3-V4 hypervariable region
55 V3-V4 region
56 atopic eczema
57 bacterial biomass
58 bacterial community diversity
59 bacterial microbiota
60 bacterial strains
61 better capture
62 biomass
63 capture
64 challenges
65 chimeras
66 clinical samples
67 community
68 community diversity
69 community sample
70 comparison
71 composition
72 conditions
73 current standard protocols
74 data
75 data sets
76 development
77 development of conditions
78 differences
79 diverse bacterial strains
80 diversity
81 diversity index
82 eczema
83 evidence
84 field
85 findings
86 gene sequencing
87 genes
88 genus level
89 healthy volunteers
90 high-throughput methodology
91 human DNA
92 human clinical samples
93 hypervariable region
94 index
95 interrogation
96 investigation
97 levels
98 library
99 low bacterial biomass
100 method
101 methodology
102 microbiome
103 microbiome investigations
104 microbiota
105 mock communities
106 mock community samples
107 optimization
108 optimization of methods
109 pairs
110 phyla
111 pilot data
112 platform
113 primer pairs
114 primer selection
115 primers
116 protocol
117 psoriasis
118 rRNA gene
119 rRNA gene sequencing
120 rRNA hypervariable regions
121 region
122 resultant library
123 results
124 robust interrogation
125 role
126 samples
127 selection
128 selection of primers
129 sequencing
130 set
131 significant challenge
132 significant differences
133 skin
134 skin microbiome
135 skin microbiota
136 standard protocol
137 strains
138 swabs
139 validation
140 validation of methodology
141 volunteers
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