Supplementary material
Creators: name: Henares, Desirée
name: Brotons, Pedro
name: de Sevilla, Mariona Fernandez
name: Fernandez-Lopez, Anna
name: Hernandez-Bou, Susanna
name: Perez-Arguello, Amaresh
name: Mira, Alex
name: Muñoz-Almagro, Carmen
name: Cabrera-Rubio, Raúl
Publisher: name: figshare
Year: 2021
Subjects: subject: 110309 Infectious Diseases
subject: FOS: Health sciences
subject: Microbiology
subject: FOS: Biological sciences
subject: Anesthesiology
subject: 110303 Clinical Microbiology
subject: FOS: Clinical medicine

description: <b>Supplementary material items from the article "Differential nasopharyngeal microbiota composition in children according to respiratory health status":<br></b><b><br></b><b>Metadata file in xlsx. (Spread Sheet 1) </b>A series of relevant epidemiological, clinical and microbiological data were recorded from each subject. Epidemiological variables such as weight at birth, delivery mode (vaginal or C-section), ethnicity (Caucasian or not), maternal breastfeeding fulfillment of World Health Organization (WHO) recommendations (duration ≥ 6 months), pneumococcal vaccination status (categorized into non-vaccinated children and children ≥1 dose of 7,10,13 Pneumococcal Conjugate Vaccines), exposure to crowding or parent’s educational level were obtained through personal interviews to parents or legal guardians. Clinical diagnosis, length of hospital stay, admission to Pediatric Intensive Care Unit (PICU), length of PICU stay, and evolution were collected from cases with IPD. Among microbiological variables, we determined for all subjects respiratory viral species present in the nasopharynx, nasopharyngeal bacterial microbiota, pneumococcal colonization status, pneumococcal nasopharyngeal load, invasiveness disease potential of nasopharyngeal pneumococcal serotypes and their inclusion in the PCV13 vaccines. Serotypes 1, 3, 4, 5, 7F, 8, 9A, 9V, 12F, 14, 18C, and 19A were considered as high invasive disease potential serotypes. <b>(Spread Sheet 2) </b>Complete list of all epidemiological, clinical and microbiological variables utilized for the study. It is indicated the code of the variable in the metadata and a detailed description of each variable and categories, if applicable.<br> <b>Fasta file containing the nucleotide sequences from each OTU detected in the study (n=726).</b> <br> <b>Dataset containing the absolute abundance of each OTU within each nasopharyngeal sample or negative control after removal of contaminant sequences (otu_table_clean.csv). </b>Samples are displayed in columns and taxa in rows. This table contains the sequence counts obtained after quality filtering and trimming of the sequences, removal of the chimeric sequences and removal of sequences considered as contaminants by the ratio described in the manuscript and by the use of Decontam package. Therefore, a total of 11,696,096 clean sequences were obtained from the 140 subjects included in the study, representing a median number of 73,553 sequences per sample. These sequences were assigned to 602 different OTUs. Regarding negative controls, a total 5122 sequences (median of 244 sequences per negative control) assigned to 77 OTUs were found in negative controls. However, these OTUs were mantained because were not considered contaminants, as they were overrepresented in samples. <br> <b>Datasets in csv format containing taxonomical annotations from all 726 OTUs detected in the present study (from domain up to species level).</b> The naïve Bayesian RDP classifier v2.12 taxonomically assigned OTUs from domain to genus, if achieving a minimum confidence threshold of 80%. Species level annotation was performed with SPINGO. This software was specifically created for high resolution assignment of sequences to species level by employing partial 16S rRNA gene sequences. kmer size and number of bootstrap runs were set to 8 and 100, respectively. Species taxonomic rank was accepted if confidence value for the assignment was &gt;75%. <br><br><b>Phylogenetic tree of the 726 OTUs detected. </b>The sequence aligner PyNAST v0.1 aligned the 16S rRNA gene sequences against a template alignment of full length 16S rRNA reference sequences from SILVA release 132. Qiime1 scripts were then utilized to filter the multiple sequence alignment by eliminating gaps found in all the sequences and by defining positions to include in the phylogenetic tree (Lane mask filtering), since highly variable regions are uninformative for tree building. The phylogenetic tree was constructed with Qiime by using the fastree method. <br> <b>Appendix S1.</b> <b>Additional methodology.</b> Appendix which includes a detailed description of the sequencing and bioinformatics procedures, treatment of negative controls and statistical analyses applied to the data. <br> <b>Appendix S2.</b> Full account of microbiota statistical analysis performed in R. (Note; some figures may be reordered in the final version of the manuscript) <br> p { margin-bottom: 0.25cm; line-height: 115%; background: transparent }a:link { color: #000080; so-language: zxx; text-decoration: underline }<br>