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A Repository for an Alternative Pipeline as used in RNA-seq and Tn-seq reveal fitness determinants of vancomycin-resistant Enterococcus faecium during growth in human serum* for the sake of differential expression and other analysis (Zhang, 2017).
Home :Introduction and overview of investigation and pipeline
Methods and Intermediate Results :Explanation of settings used at each step of analysis and interpretation of intermediate results
Questions Regarding Analysis Tools :Questions from lab manual answered
Results and Discussion :Explanation of final tools and outcomes followed by a more in-depth discussion of results
References :Sources cited in text
E. faecium are a common commensal bacteria as part of the human microbiome. As with everything, there can be such a thing as having too many E. faecium bacteria. The human body helps to keep the populations of bacteria within the gut microbiome in check, but in individuals with compromised immune systems the population of E. faecium can go un-managed and grow out of control. When this happens, E. faecium becomes pathogenic to the host as it uses up resources and makes its way to sterile locations within the human body. Normally, when a person becomes septic, antibiotics are given to kill off the pathogen.
Vancomycin is a common antibiotic that is given to fight off gram-positive bacteria. Vancomycin disrupts the formation of the peptidoglycan wall by preventing the formation of crosslinks between peptidoglycan layers. This makes it an ideal antibiotic as it will not effect the human host as human cells do not have peptidoglycan in their cells. While it is an ideal antibiotic, it has been used so often that finding vancomycin restistant Enterococci (VRE) has become quite common. This is more-so becoming the case for antibiotics in general as they are overused and abused.
Zhang and his team looked to study the essential genes in vancomycin resistant Enterococci faecium to find the genes that are required for growth in human serum. The study compares E. faecium E745 grown in brain-heart infusion (BHI) medium to E. faecium E745 grown in human serum. The BHI medium is nutrient rich and therefore is not a very restrictive environment to grow E. faecium while human serum is not a nutrient rich medium and therefore is more demanding of the bacteria. By seeing the what is more highly expressed in E. faecium grown in human serum than in BHI, the team was able to find the genes essential for growth in human serum (Zhang, 2017).
- Genome assembly of Pac-Bio DNA reads using Canu
- Vizualization of Illumina DNA sequences with FastQC
- Trimming of Illumina reads using Trimmomatic
- Mapping Illumina reads to Pac-Bio Assembly:
4.1 Using BWA-MEM to map
4.2 Converting SAM files to BAM using SAMtools
4.3 Creating a combined genome assembly from mapping using Pilon
4.4 QUAST - Annotation of the combined assembly:
5.1 Using Prokka for structural and functional annotation
5.2 Using eggNog-Mapper for functional annotation
5.3 Artemis ART and ACT used for Visualization and Synteny - RNA Mapping:
6.1 For serum RNA using BWA-MEM and converted to to BAM using SAMtools 6.2 For BHI RNA using BWA-MEM and converted to to BAM using SAMtools - Counting RNA reads:
7.1 Converting .gbk to .gtf with gbk2gtf.py
7.2 Counting serum RNA reads using HTseq-count
7.3 Counting BHI RNA reads using HTseq-count - Differential expression using DEseq2
- Interpretation and Other Analysis**
**See Results and Discussion page for the interpretation of DEseq2 and other analysis results.
The following schemas contain the workflow of analysis of E.faecium sequencing data to look at the fitness determinants of VRE growth in human serum. These steps are explained in more depth in the Methods and Intermediate Results and Results and Discussion pages.
Genome Assembly and Annotation was finished by 12.04.2019, Comparative genomics was finished by 25.04.2019, and RNA mapping was finished by 07.05.2019
fig.1 Key for diagrams below
fig.2 Initial steps part 1
Genome assembly and annotation
fig.3 Continuation of genome analysis
This schema continues from fig.1 so show steps with RNA