Article Figures & Data
Figures
- FIG 1
Positions of primers UNI_ITS_fw and UNI_ITS_rv within the ribosomal locus of Escherichia coli K-12 strain MG1655.
- FIG 2
In silico evaluation of microbial ITS profiling performance and comparison respect to different hypervariable 16S rRNA gene regions. (a) Percentage of bacterial taxa correctly classified by ITS and 16S rRNA gene profiling methods with respect to expected taxonomic profiles of artificial data sets. (b) Taxonomic profiles observed using ITS and 16S rRNA gene profiling methods and their comparison with respect to expected taxonomic profiles of artificial data sets.
- FIG 3
Performance of microbial ITS profiling compared to 16S rRNA gene cataloguing and read-based classification of shotgun metagenomic data sets. (a) Average percentage of reads classified to the species level using ITS and 16S rRNA gene profiling for each matrix analyzed. Data obtained for each sample are reported in Data Set S4. (b) Average percentage of reads classified by 16S rRNA gene profiling as a genus also detected by microbial ITS profiling of the same read, for each matrix analyzed. Data obtained for each sample are reported in Data Set S4. (c) Percentage of reads classified at the species level based on read length.
Supplemental Material
DATA SET S1
UNI_ITS_fw/UNI_ITS_rv primers and UMID statistics. Download Data Set S1, XLSX file, 0.6 MB.
Copyright © 2020 Milani et al.
This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.
TABLE S1
Percentages of reads mapped to the SILVA SSU and LSU databases. Download Table S1, DOCX file, 0.02 MB.
Copyright © 2020 Milani et al.
This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.
TEXT S1
User manual for the analysis script available at http://probiogenomics.unipr.it/pbi/, discussion of the comparison between ITS profiling and shotgun metagenomics results, and detailed discussion of ITS profiling data obtained from the clinical test case encompassing colorectal cancer biopsy specimens. Download Text S1, DOCX file, 0.1 MB.
Copyright © 2020 Milani et al.
This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.
DATA SET S2
Results obtained from the analysis of artificial datasets. Download Data Set S2, XLSX file, 0.3 MB.
Copyright © 2020 Milani et al.
This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.
TABLE S2
Quality filtering table of samples analyzed in this study. Download Table S2, DOCX file, 0.03 MB.
Copyright © 2020 Milani et al.
This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.
DATA SET S3
Results obtained from analysis of the artificial community. Download Data Set S3, XLSX file, 0.01 MB.
Copyright © 2020 Milani et al.
This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.
DATA SET S4
Results obtained from the analysis of real biological samples. Download Data Set S4, XLSX file, 1.3 MB.
Copyright © 2020 Milani et al.
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FIG S1
Identification of microbial biomarkers of colorectal cancer based on species-level data. The graphical representation reports the bacterial species that, when detected in the mucosal samples analyzed, showed higher abundance in adenocarcinoma than in healthy mucosa of the same individual. Download FIG S1, PDF file, 0.2 MB.
Copyright © 2020 Milani et al.
This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.
DATA SET S5
Alignment file in Clustal format showing alignment of 100 16S rRNA gene sequences used to identify the optimal conserved region for primer design. Download Data Set S5, TXT file, 0.8 MB.
Copyright © 2020 Milani et al.
This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.
DATA SET S6
Alignment file in Clustal format showing alignment of 100 23S rRNA gene sequences used to identify the optimal conserved region for primer design. Download Data Set S6, TXT file, 1.1 MB.
Copyright © 2020 Milani et al.
This content is distributed under the terms of the Creative Commons Attribution 4.0 International license.
