This is Kathy Mou's lab notebook describing the comparative genomics project of commensal E. coli isolates and development of a pipeline to identify potential probiotic isolates that could be tested for competitive exclusion against STEC. /n 96 isolates (sorbitol-positive and sorbitol-negative) collected from FS19 STEC colonization study in dairy calves (Fecal and RAMS samples) were tested in this pipeline.
| File Name | Description |
|---|---|
| 00_Files.md | List of relevant files used and generated from analysis, locations of files on network drives or Ceres fsepru project folder |
| 00a_Metadata.md | Important metadata related to the project and files in 00_Files.md and Files directory |
| 01_Background.md | Notes taken from OSQR plan, references listed in OSQR that are related to this project |
| 02_Methods | Lists entries from OneNote FS19C lab notebook on practicing using tools (bbmap and spades) on 4 FS19C isolates' sequence data; entries from OneNote FS19C lab notebook of relevance, conda environments created for sequence analysis, description and scripts for each method; each individual method as its own step. |
| 03_Results.md | Notes to include in paper |
| 04_Introduction.md | Notes to include in paper |
| 05_Discussion.md | Notes to include in paper |
| 06_AuthorInfo.md | List of authors, contact info, contributions |
| BashScriptLesson.md | Contains the script for rename.contigs and the for-loop script rename_contigs.sh to run rename.contigs on all fasta files in a directory. This page also explains each step of rename_contigs and rename_contigs.sh |
| Notes.md | To-do list and other miscellaneous items |
| Files | Relevant data files or files in scripts |
| scripts | Scripts used in data analysis on HPC (Ceres) or locally (RStudio) |
- Assemble short read sequences (Illumina) with BBMap and spades.
- Determine how closely related isolates are using mash and visualize with MDS (in R).
- Fetch STEC genomes from NCBI (RefSeq).
- Run gifrop to 1) annotate with prokka and 2) conduct pan-genome analysis of commensal E. coli and STEC with roary.
- Run DRAM as a second method to annotate and distill carbon/sugar utilization pathways of interest that are in STEC and thus also in commensal E. coli. This tool is relatively new and was developed with the goal of finding metabolic networks in metagenomes (relevant to this project). The authors showed DRAM had higher resolution annotation than prokka, so we are trying it out. The tool also generates neat plots of metabolic pathways present/absent in isolates.
- Interproscan: GO term enrichment using roary output (and DRAM?) to identify carbon/sugar utilization pathways of interest present in STEC that are present in commensal E. coli.
- Identify candidate commensal E. coli for further study.