***Title of the dataset / Data underlying the publication: ‘Effects of E. coli Nissle 1917 on the Porcine Gut Microbiota and Immune System in Early Life’***

***Creators***
Mirelle Geervliet 1,†, Hugo de Vries 2,3,†, Christine A. Jansen 1,4, Victor P.M.G. Rutten 4,5, Hubèrt van Hees 6, Caifang Wen 3, 
Kerstin Skovgaard 7, Giacomo Antonello 8, Huub F.J. Savelkoul 1, Hauke Smidt 3, Edwin Tijhaar 1,†, and Jerry M. Wells2,†,*

1	Cell Biology and Immunology Group, Wageningen University & Research, Wageningen, The Netherlands; mirelle.geervliet@wur.nl; huub.savelkoul@wur.nl; edwin.tijhaar@wur.nl; christine.jansen@wur.nl 
2	Host-Microbe Interactomics Group, Wageningen University & Research, Wageningen, The Netherlands; jerry.wells@wur.nl
3	Laboratory of Microbiology, Wageningen University & Research, Wageningen, The Netherlands; hugo.devries@wur.nl; caifang.wen@wur.nl; hauke.smidt@wur.nl 
4	Department of Biomolecular Health Sciences, Division of Infectious Diseases and Immunology, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands; v.rutten@uu.nl 
5	Department of Veterinary Tropical Diseases, Faculty of Veterinary Science, University of Pretoria, Pretoria, South Africa; v.rutten@uu.nl 
6	Research and Development, Trouw Nutrition, Amersfoort, The Netherlands; hubert.van.hees@trouwnutrition.com
7       Department of Biotechnology and Biomedicine, Technical University of Denmark, Lyngby, Denmark; kesk@dtu.dk
8       Department of Cellular, Computational and Integrative Biology, University of Trento, Trento, Italy; giacomo.antonello@unitn.it

* Correspondence: jerry.wells@wur.nl

† These authors have contributed equally to this work and share first or last authorship.

***Related publication***
Title: Effects of E. coli Nissle 1917 on the Porcine Gut Microbiota and Immune System in Early Life
DOI: 10.3389/fcimb.2022.842437
Received: December 23th, 2021; Accepted: February 1st, 2022; Published: 2022

***General Introduction***
This README file corresponds to the data corresponding to Figure 7 of the manuscript.
This dataset contains data collected during an in vivo experiment with pigs at the Wageningen University as part of the PhD Thesis Projects of Mirelle Geervliet and Hugo de Vries (first authors of the manuscript). 
This research project was made possible by The Netherlands Organisation for Scientific Research and Vereniging Diervoeders Nederland (VDN).

***Purpose of analysis***
To validate the EcN-specific ASV in the NGS dataset using an EcN-specific qPCR analysis

***Methodological information***
For qPCR data, A qPCR with primers specific to EcN (Table 1) was used to determine the relative abundance of EcN in fecal samples. All qPCR analyses were performed in triplicate in a reaction volume of 10 µL, 
using Hard-Shell® 384-Well PCR plates (Bio-Rad). The reaction mixture contained 2x iQ SybrGreen Supermix (Bio-Rad Laboratories B.V.), 200 nM of each primer (Table 1), and 2 µL of the DNA template (1ng/µL). 
The amplification program consisted of an initial denaturation at 94°C for 10 min followed by 39 cycles of 94°C for 20s, 60°C for 30s, and 72°C for 30s using a CFX384TM thermocycler (Bio-Rad Laboratories B.V.). 

For NGS data, DNA was extracted from faecal samples, then PCR amplification was carried out with barcoded primers directed to the V4 region 
of the bacterial and archaeal 16 S rRNA gene. Samples were sent for Illumina HiSeq sequencing after which amplicon sequence data were processed and analysed using NG-Tax 2.0 and annotated using the SILVA 132 database.
Resulting data was imported into R-studio together with a metadata file to perform analyses and generate figures.

***Data specific information***
In folder 'Figure S2', two subfolders can be found namely:

1. Unprocessed_Figure:
This folder contains a PDF file with the figure as generated by R. 
This PDF file was used to create final Figure S2. 

2. Final_Figure:
This folder contains the final figure as presented in the manuscript. 
The final figure is prepared in Adoble Illustrator. 

Raw_data:
In the folder "EcN-specific_qPCR_original_datafiles", raw data of the qPCR can be found. Additionally, an excel file that includes the plate setup and data processing can be found. A second excel file named "samples_for_qpcr_11-nov-20",
was used to maintain the connection of sample numbering 1-40 to the original master sample numbers.

R script: 
R script can be found under the following folder: Data_analyses_in_R_Studio
This folder also contains the data files used in the subfolder 'input_data'. This includes the metadata file that also contains a column with results from the EcN-specific qPCR, this was used to bring the qPCR and NGS data into one file.
