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Detection of growth- and metabolism-altering interactions within a defined microbiota

Jupyter Notebook 99.73% Python 0.27%

asf_interactions's Introduction

asf_interactions

This git repository accompanies the paper "Metabolic mechanisms of interaction within a defined gut microbiota", available on bioRxiv here.

In this study, we profiled the growth and metabolism of 6 bacterial strains from the altered Schaedler flora (ASF), a group of bacteria used to standardize the mouse microbiota in breeding facilities. We grew each of the 6 strains in monoculture and co-culture, profiling growth interactions using probe-based qPCR and metabolic behavior using 1H-NMR spectroscopy-based metabolomics. We developed an applied a Constant Yield Expectation (ConYE, pronounced "Kanye") model, which we used in conjunction with genome scale metabolic network reconstructions to dissect metabolic cross-feeding.

This repository contains all data, models, and analyses associated with the study. We are currently uploading raw NMR spectra to MetaboLights (a MS/NMR metabolomics database) and prepping a Jupyter notebook to demonstrate loading/manipulating the processed data for "data mutualists" (less tastefully known as "data parasites") to re-use. Within our paper, we focus our genome-scale metabolic network analysis on a single strain, but we provide network reconstructions for 7 of the ASF strains here,constructed using the same methods.

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asf_interactions's Issues

Add final publication figures

Update the repository with vector art version of the final publication images.

Change all figure references to "strain" from "species"

Make this consistent with the text of the manuscript, where we refer to the ASF members as strains rather than species.

Replot qPCR figure with clip_on=False

Replot the qPCR figure with clop_on=False to get the entire symbol within each subplot frame for the monoculture abundance data.

submit NMR spectra to MetaboLights

Add guide for "data parasites"

Add a folder with preprocessed, neatly organized data tables. Write a jupyter notebook guide to explain the data and simple ways to explore it/transform it.

Finalize figure 1

Finalize figure 1 by cleaning up box scatters for overall abundance.

Determine normality and adjust tests as needed

Finalize normality tests and the corresponding downstream statistical test for DNA abundance and metabolite abundance.

Edit Figure 4

Change references to "CRAM" to "ConYE"

Add detail to cartoon for clarity and guided interpretation based on potential observed and predicted outcomes

Rearrange labels on triangle key so that it doesn't seem as if the p value is directly derived from ConYE, rather ConYE is the system for generating expected values.

Add subpanel labels for A,B, and C in Figure 5

Each row should be labelled as a subpanel.

Transfer expectation model to this repository

Transfer the co-culture metabolome expectation model to this repository and decide on select figures to include for figure 3 in the manuscript.

Edit Figure 5

Rename CRAM to ConYE, and add descriptive column labels to indicate where the volcano plots are from, and that the middle column describes "actual behavior"

Share axes on Fig 1B

For figure 1B (in vitro total growth by OD), share the Y axis so they can have a shared label to save space for manuscript.

Clean up experimental condition labels in subplots of Figure 7D

Use full metabolite names

GENRE-based inference on cross-feeding

Implement GENRE-based inference of cross-fed metabolites using our previously-generated ensembles. Use an ensemble of 100 GENREs for each species. Explore using micom rather than current scripts.

Use consistent statistical threshold value when graphically representing rejection of null hypothesis

Add colorscale to abundance summary triangle plot

Add HPC code used for gapfilling

Update readme with directory organization and file summaries

Fix Figure 4D typo

Figure 4D has ASF360 labelled twice on the x axis for Lactose; the second label should be replaced with ASF356

Clean PCA notebook

The analysis and figures are finished, but some commenting needs to be removed/improved and linting needs to be performed.

Increase point size in Figure 4 and 6 volcano plots

Add primer design scripts to this repository

Add the primer design scripts, and verify the location and identity of target genes.

Generate volcano plots and summary metrics for CRAM model

Transfer over the plotting scripts for CRAM results into a new notebook and decide on which figures will go into figure 3 for the manuscript. Standardize the CRAM output and count metabolites categorically based on the monoculture differential abundance results (e.g. consumed by one species, produced by one species, etc.).