Metadata: 
In this folder are the data to reproduce all figures & data analysis.


1. About the Dataset

Creator(s): Daniel James [1], https://orcid.org/0009-0006-4263-9445

1 = University of Reading. 

Title: Data for investigating the effects of high-protein diets on microbiota, gut barrier function, and mucosal immunity, with a focus on potential sex-dependent differences. 

Organisation: University of Reading

Rights-holder: University of Reading

Publication year: 2024

Description:
The data was produced from conducting a feeding trial using male and female 21-day-old piglets as models for humans, comparing high protein (28% dietary protein) and standard protein (18% dietary protein) diets for 4 weeks. The differences in protein intake came from soya, pea, whey and fish proteins. At day 0, faecal microbiota, size, weight, and blood were recorded or taken. At the end of the feeding period (day 56), faeces, urine and colon tissue samples were taken for analysis. Each week the length of the piglets was measured, and every half-week the weight was measured. The data includes microbiota compositions, urinary metabolite concentrations, quantified protein expression of gut barrier function proteins and mucosal immune system associated protein. The code used for the statistical analysis of the data is also included. 

Cite as: Daniel James (2024): Data for investigating the effects of high-protein diets on microbiota, gut barrier function, and mucosal immunity, with a focus on potential sex-dependent differences. University of Reading. Dataset. https://doi.org/10.17864/1947.001381 

Related publication: High-protein diets increase microbiota associated para-cresol production in the colon and reduce gut barrier function in a sex-dependent manner.

Contact: Daniel James; d.james3@pgr.reading.ac.uk.

Acknowledgements: Associate professor Marie Lewis for supervising the project.


2. Terms of Use

Copyright 2024 University of Reading. This dataset is licensed under a Creative Commons Attribution 4.0 International Licence: https://creativecommons.org/licenses/by/4.0/


3. Project and Funding Information

Title of the project: Diet and Chronic Disease: mechanistic studies on the impact of dietary protein on gut barrier function and the microbiota. PhD project.

Dates: 09/2020-12/2024

Funding organisation: BBSRC Case Studentship co-funded by Feed and Food Innovations Ltd.

Grant no: BB/T008776/1


4. Contents

File name: _Highprotein_pigtrial_data_code.zip

Upon opening the data folder there are several folders:

1) Demultiplexed sequencing data: This contains the raw data files that can be used in QIIME2 pipeline for ASV identification.

2) Metadata file used for analyses: This contains the file that was used as the metadata file in all analyses.

3) QIIME2 code: This contains the steps conducted to produce our ASV data using the demultiplexed data inputs in QIIME2. It also contains the steps used for PIcrust2, to output KEGG, KO and MetaCyc information.

4) R code_bioinformatics: Here is the code we used to produce the differential abundance analyses in ASVs and functional pathways. Along with correlation analyses between microbiota and metabolites.

5) R code_metabolites_size: This is the R code that we used for statistical analyses of length, weight, urinary metabolites, and plasma LPS and IL-6 concentrations.

6) Raw data_metabolites_size_bacterial counts: This contains multiple files of raw data collected during the trial, including KEGG, KOs, Metacyc, expression of immune associated proteins in the MLN, ASV abundance data used in differential abundance analysis, the protein expression of gut barrier proteins E-cadherin and ZO-1 and the SPSS input table used to model the statistics from protein expression in SPSS. 


5. Methods:

The different conditions include:

High protein (HP); pigs consuming 28% dietary protein.
Standard protein (SP); pigs consuming 18% dietary protein.
females consuming high protein (HP/F); 
males consuming high protein (HP/M);
females consuming standard protein (SP/F);
males consuming standard protein (SP/M);

The data collection outcomes and methods were as follows:


Ammonia (mM) in urine: as measured by ELISA (Sigma-Aldrich Co Ltd, AA0100). 

Phenolics (mM)
phenol, indole, p-cresol: as measured in urine by SPME-GCMS (Agilent 110PAL injection system mounted on an Agilent 7890 GC connected to a 5975 mass selective detector (MSD). The SPME fibre stationary phase was composed of 75um divinylbenzene/Carboxen).

Bacteria composition of faecal samples: 16S rRNA sequencing (V4 and V5 regions) of extracted DNA.

Barrier and immunity protein expression: ZO-1, E-cadherin, CD45, CD172a, MHCII, MIL11; four-colour fluorescence immunohistology.  

Barrier and immunity protein expression:
ZO-1, E-cadherin, CD45, CD172a, MHCII, MIL11; four-colour fluorescence immunohistology