Team II Webserver Group

Introduction

Background And Goal

We got our raw data from Dr. David S. Weiss' lab (ARC, Division of Infectious Diseases). They provided us with a sample ID numbers and we downloaded 258 pair-end raw reads sequences of Klebsiella spp,sequenced by illumina MiSeq. from NCBI SRA database. The goal of the class was to provide an insight on the major issue of antibiotic resistance. Klebsiella is a genus of nonmotile, Gram-negative, oxidase-negative, rod-shaped bacteria with a prominent polysaccharide-based capsule. Klebsiella species are found everywhere in nature. The members of the genus Klebsiella are a part of the human and animal's normal flora in the nose, mouth and intestines. The species of Klebsiella are all gram-negative and non-motile. Some of Klebsiella types are: K.granulomatis, K. oxytoca, K. michiganensis and K. pneumoniae (type-species: K. p. subsp. ozaenae, K. p. subsp. pneumoniae, K. p. subsp. rhinoscleromatis). Our job as the web server team was to provide the following:-

1. An easy-to-use tool to help distinguish between Klebsiella phenotypes, by implementing the work of the comparative genomics group.

2. A robust and easy-to-use web-based de-novo assembly tool.

3. A feature to visualize and download the results of the 258 genomes.

Here, we build a web server that ideally predicts a phenotype based on the genetic information it is given.

Goal

The web server should provide the following:

1. An easy-to-use tool to help distinguish between Klebsiella phenotypes, by implementing the work of the comparative genomics group.

2. A robust and easy-to-use web-based de-novo assembly tool.

3. A feature to visualize and download the results of the 258 genomes.

Design Principles

1. Minimal

2. Mobile Friendly

3. Short Load Time

4. Contrasting Colors

Functionalities Offered

Genome Assembly

Users will have the option of uploading either an assembled genome or short-reads from NGS methods. If short-reads are provided, a de novo assembly will be performed using the assembler Skesa. The resulting assembly will be available for download and will be used for downstream processes.

Strain and Species Identification

Strain identification is performed using k-mer based approaches in StrainSeeker. Each user-provided input sample is reduced to a pool of unique k-mers that is compared to k-mer pools from samples in the NCBI sequence database. The observed and expected k-mer pool overlaps between user-provided samples and NCBI-samples are used to taxonomically place samples with unknown strain identity.

Antibiotic-resistance Profiling

Each user-provided sample will be compared to the Comprehensive Antibiotic Resistance Database (CARD) using the toolkit RGI. RGI discovers high-confidence homologues of known antibiotic-resistance genes using Diamond homology searches. RGI also incorporates SNP models to predict genetic variants that are likely to confer new antibiotic resistances. The entire antibiotic profile of each strain is visualized in a wheel-chart (provided by RGI) that allows the user to explore result by drug class, mechanism of resistance, and antibiotic target.

Virulence Factor Profiling

Each user-provided sample will be blasted against the Virulence Factor Database (VFDB) to identify homologues of known virulence factors. A non-redundant blast output (outfmt 6) will be provided for download by the user.

Tools

Skesa

Skesa is the most recent tool in our list and is currently used by NCBI. Information about the algorithm is currently unavailable. . De novo sequencing refers to sequencing a novel genome where there is no reference sequence available for alignment. Sequence reads are assembled as contigs, and the coverage quality of de novo sequence data depends on the size and continuity of the contigs (ie, the number of gaps in the data).

To compare the performance of the above tools, we use Quast.

StrainSeeker

StrainSeeker is a program for detecting bacterial strains from raw sequencing reads. Compared to other similar programs, it offers the following advantages:

1. Fully customizable database - use your own strains of interest or download our database

2. Detect novel strains that are related to strains in the database

3. Quickly handle large amounts of data

4. Results given all the way down to the strain level!

Input

Fastq or Fasta sample

Output tree

RGI

Open Reading Frame (ORF) prediction using Prodigal, homolog detection using Diamond, and Strict significance based on CARD curated bitscore cut-offs. Addition of rRNA mutation and efflux over-expression models. Hits of 95% identity or better are automatically listed as Strict. All results organized by revised ARO classification: AMR Gene Family, Drug Class, and Resistance Mechanism. Support added for low quality/coverage assemblies, metagenomic merged reads, small plasmids or assembly contigs.

VFDB

The virulence factor database (VFDB) is dedicated to providing up-to-date knowledge of virulence factors (VFs) of various bacterial pathogens.

1. Blastn against VFDB

2. Remove redundant matches, output list of unique VF homologues -Accession numbers, blast scores, positions in query

Our Web Page

Home Page

Basic Layout

Assembly Page

Batch mode

Downloads Page