Data for: Human Gut Microbiota from Autism Spectrum Disorder Promote Behavioral Symptoms in Mice

Published: 30 May 2019 | Version 1 | DOI: 10.17632/ngzmj4zkms.1
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Description of this data

Raw data (excluding raw sequencing and metabolomic data) used to construct figures for manuscript. Data is predominantly in csv or tsv format. qza and qzv files are QIIME2 outputs and can be viewed at https://view.qiime2.org/ . mat files are mat lab datasets.

Human Gut Microbiota from Autism Spectrum Disorder Promote Behavioral Symptoms in Mice

Gil Sharon1,*, Nikki Jamie Cruz1, Dae-Wook Kang2,3,21, Michael J. Gandal4,5,6,7, Bo Wang1, Young-Mo Kim8, Erika M. Zink8, Cameron P. Casey8, Bryn C. Taylor9, Christianne J. Lane10, Lisa M. Bramer11, Nancy G. Isern8, David W. Hoyt8, Cecilia Noecker12, Michael J. Sweredoski1, Annie Moradian1, Elhanan Borenstein12,13,14,15,16, Janet K. Jansson8, Rob Knight17,18,19, Thomas O. Metz8, Carlos Lois1, Daniel H. Geschwind4,5,6, Rosa Krajmalnik-Brown2,3, and Sarkis K. Mazmanian1,20,*

Autism spectrum disorder (ASD) manifests as alterations in complex human behaviors including social communication and stereotypies. In addition to genetic risks, the gut microbiome differs between typically-developing (TD) and ASD individuals, though it remains unclear whether the microbiome contributes to symptoms. We transplanted gut microbiota from human donors with ASD and TD controls into germ-free mice, and reveal that colonization with ASD microbiota was sufficient to induce hallmark autistic behaviors. The brains of mice colonized with ASD microbiota display alternative splicing of ASD-relevant genes. Microbiome and metabolome profiles of mice harboring human microbiota predict that specific bacterial taxa and their metabolites modulate ASD behaviors. Indeed, treatment of an ASD mouse model with candidate microbial metabolites improves behavioral abnormalities and affects neuronal excitability in the brain. We propose that the gut microbiome modulates behaviors in mice via production of neuroactive metabolites, suggesting that gut-brain connections contribute to the pathophysiology of ASD.

Experiment data files

Steps to reproduce

The following python code can be used to unpack matlab data to a Pandas dataframe (Python 3):

import numpy as np
from scipy.io import loadmat # this is the SciPy module that loads mat-files
import pandas as pd

mat = loadmat('caImaging_taurine 5AV.mat') # load mat-file
mdata = mat['RawData'] # Data variable in mat file

# to get the data out of matlabs data structure, which is an array or arrays:
i,j = mdata.shape
AllCells = pd.DataFrame()
for column in range(j-1): # iterate over days
day = mdata[0,column+1].item()
group1_data = pd.DataFrame(np.transpose(mdata[1,column+1]))
group1_data['DIV'] = day
group1_data['Treatment'] = mdata[1,0].item()
group1_data['counter'] = range(1,len(group1_data)+1)
group2_data = pd.DataFrame(np.transpose(mdata[2,column+1]))
group2_data['DIV'] = day
group2_data['Treatment'] = mdata[2,0].item()
group2_data['counter'] = range(1,len(group2_data)+1)
group3_data = pd.DataFrame(np.transpose(mdata[3,column+1]))
group3_data['DIV'] = day
group3_data['Treatment'] = mdata[3,0].item()
group3_data['counter'] = range(1,len(group3_data)+1)

AllCells = pd.concat([AllCells, group1_data, group2_data, group3_data])
AllCells.set_index(['DIV','Treatment', 'counter'], inplace=True)
AllCells_stacked = AllCells.stack().reset_index()
AllCells_stacked.columns = ['DIV', 'Treatment','Cell#', 'Time', 'dF/F0']
AllCells_stacked = AllCells_stacked[AllCells_stacked['dF/F0'] >= 0]

Latest version

  • Version 1

    2019-05-30

    Published: 2019-05-30

    DOI: 10.17632/ngzmj4zkms.1

    Cite this dataset

    Sharon, Gil (2019), “Data for: Human Gut Microbiota from Autism Spectrum Disorder Promote Behavioral Symptoms in Mice”, Mendeley Data, v1 http://dx.doi.org/10.17632/ngzmj4zkms.1

Statistics

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Downloads: 419

Institutions

California Institute of Technology

Categories

Microbiome, Autism Spectrum Disorder, Expression Analysis, Mouse Study, Metabolome

Licence

CC BY 4.0 Learn more

The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International licence.

What does this mean?

This dataset is licensed under a Creative Commons Attribution 4.0 International licence. What does this mean? You can share, copy and modify this dataset so long as you give appropriate credit, provide a link to the CC BY license, and indicate if changes were made, but you may not do so in a way that suggests the rights holder has endorsed you or your use of the dataset. Note that further permission may be required for any content within the dataset that is identified as belonging to a third party.

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