BIT 295 MRA Isolate 106: Pseudarthrobacter Oxydans
Aditya Chadha, Carlos C. Goller, Carly Sjogren, Rom Stanek, Sophie Goeuriot
Generated December 5, 2022

A Detailed Anaylsis of Arthrobactor

Abstract

Arthrobactor is a bacteria that commonly resides in soil, plants, and wastewater (Gobbetti 2014). A species of arthrobacter known as Arthrobacter citreus can be used for polyamide waste (Baxi 2019). The goal here is to determine if this species of arthrobacter can be useful in e-waste recycling.

Introduction

Arthrobactor is a bacteria that commonly resides in soil, plants, and wastewater (Gobbetti 2014). It is commonly used in the agricultural industry for degrading pesticides which will detox the soil and allow wildlife not to be harmed by said pesticides. The sample that is being tested came from an acid drain from a mine. The test sample was able to live and thrive in a metal ridden environment which could lead it to having some genes that could aid in e-waste recycling. A species of arthrobacter known as Arthrobacter citreus can be used for polyamide waste (Baxi 2019). Polyamide is used in fishing nets and industrial applications and the waste generated by this impacts ocean environments and ecosystems (Rietzler et all... 2021). Based on the resilience of arthrobacter as a genus, the hopes for this sample to aid in e-waste recycling are high.

Authors URL Link
M. Gobbetti, C.G. Rizzello Link
Nandita N. Baxi, Shweta Patel,Dipeksha Hansoti Link
Microbe Wiki Link
Barbara Rietzler,Avinash P. Manian,Dorian Rhomberg,Thomas Bechtold,Tung Pham Link

Keywords

  • Electronic Waste/E-waste recycling
  • Arthrobactor
  • Potential Use

Table of Contents

  1. Background and Experimental Methods
  2. Import and annotation
  3. QC, Assembly, and Annotation
  4. Taxonomic Classification
  5. Metabolic Modeling and Flux Balance Analysis
  6. References

Narritive Authors

  • Aditya Chadha
  • Sophie Goeuriot
  • Rom Stanek

Background and Experimental Methods

Background

The bacteria was collected from an acid waste drain from a mine by Dr. Jason Whitham and Dr. Amy Grunden. These were then transported to NC State to be analyzed and sequenced to see if they had any potential in eliminating electronic waste.

Process

Plate streaking- To start the process of sequencing, the bacteria was grown in trypic soy broth and plate streaked the bacteria onto plates to facilitate growth of colonies. This was to ensure we had enough bacteria to test with just in case a sample failed.

Biolog plates

After the bacteria grew, our team swabbed the bacteria and put it through a Turbidimeter at a T percent of 95. This was to ensure the concentration of bacteria in our test sample is high enough to be sequenced. Lastly we pipetted this test sample into a biolog plate with different growth indicators in each well. These were left to grow for 7 days in a 28°C controlled environment.

Genomic Isolation

The next step is Genomic Isolation in preparation for Nanopore sequencing. In this, our team ran the sample through bacterial lysis to break open the bacterial cells in order to purify the sample. Then we bound the gDNA and eluted it to fully purify the sample.

Checking bacteria

After isolating and purifying the sample, our team ran the sample through a Nanodrop and Qubit to determine the concentration of the sample in ng/uL.

Reading the genome

Lastly our team ran the sample through Nanopore sequencing to determine relevant genes that could be helpful for e-waste recycling. The library prepartion protocol specifications and the flow cell are as follows below. The genomone algorithm was used in annotating the DNA sample.

  • -ONT Rapid Barcoding Kit (RBK004)
  • ONT Flow Cell Priming Kit (EXP-FLP002)
  • MinION FLO-MIN106 R9.4.1 flow cells
  • Sequencing auxiliary kit EXP-AUX001
  • 1.5 mL Eppendorf DNA LoBind tubes
  • 0.2 mL thin-walled PCR tubes
  • Nuclease-free water (e.g., ThermoFisher, cat # AM9937)
  • Freshly prepared 70% ethanol in nuclease-free water
  • Qubit™ Assay Tubes (ThermoFisher Q32856)
  • Qubit dsDNA HS Assay Kit (ThermoFisher Q32851)
  • 10 mM Tris-HCl pH 8.0 with 50 mM NaCl

Statistics

  • Total read length- 4539679 basepairs
  • Mean read length- 15564.6534 basepairs
  • Number of reads-361,021
  • Type of read- Signle End
  • First sequencing of the genome so there is not an accession number
    • Oulier Read Length (kb) Aggreated Reads (Mb)
    176-432 70.71
    432-688 4.16
    688-904 0.93
Issues
  • There was no size selection of the Dna, our team used all available data.
  • There was little quaility control over sample reads.
  • The sample DNA was ligated with barcode 2 at random points in the sample due to the amount of DNA the sample contatined.

QC, Assembly, and Annotation

Process

The reads were not heavliy quaility controled. The genome was assembled by Dr. Goller and Dr. Sjoren after the read data was taken from the flow cell. There were muliple files generated into 9 different contigs seperated by the chosen barcode labeled barcode 2. Dr. Goller took all the files and reordered them based on basepairs and labeled them 1-9. These were then uploaded and the genome was assembled by RASTtk - v1.073. The final genome coverage is 5201919 basepairs. The GC content of the genome is 65.54% based on the number of G and C pairs in the sequence and the N50 value is 4539679 basepairs. The end of the reads were determined with the ligation of barcode 2 on the sample.

Assemble Reads with Unicycler - v0.4.8
Assemble reads using the Unicycler assembler.
This app produced errors.
No output found.

Taxonomic Identification

Genus and Species

The sample tested has a Genus named Pseudarthrobacter and species Oxydans.

Annotate Genome/Assembly with RASTtk - v1.073
Annotate or re-annotate genome/assembly using RASTtk (Rapid Annotations using Subsystems Technology toolkit).
This app completed without errors in 6m 14s.
Objects
Created Object Name Type Description
RASTtk-isolate106 Genome RAST re-annotated genome
Report
Summary
The RAST algorithm was applied to annotating a genome sequence comprised of 9 contigs containing 5201919 nucleotides. No initial gene calls were provided. Standard features were called using: glimmer3; prodigal. A scan was conducted for the following additional feature types: rRNA; tRNA; selenoproteins; pyrrolysoproteins; repeat regions; crispr. The genome features were functionally annotated using the following algorithm(s): Kmers V2; Kmers V1; protein similarity. In addition to the remaining original 0 coding features and 0 non-coding features, 6921 new features were called, of which 150 are non-coding. Output genome has the following feature types: Coding gene 6771 Non-coding repeat 89 Non-coding rna 61 The number of distinct functions can exceed the number of genes because some genes have multiple functions.
Links
Classify Microbes with GTDB-Tk - v1.7.0
Obtain objective taxonomic assignments for bacterial and archaeal genomes based on the Genome Taxonomy Database (GTDB) ver R06-RS202
This app completed without errors in 27m 50s.
Report
Links

References

  1. Assemble Reads with Unicycler - v0.4.8
  2. RASTtk - v1.073
  3. GTDB-Tk - v1.7.0

Apps

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  2. Assemble Reads with Unicycler - v0.4.8
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  3. Classify Microbes with GTDB-Tk - v1.7.0
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    • Rinke C, Chuvochina M, Mussig AJ, Chaumeil PA, Dav n AA, Waite DW, Whitman WB, Parks DH, and Hugenholtz P. A standardized archaeal taxonomy for the Genome Taxonomy Database. Nat Microbiol. 2021 Jul;6(7):946-959. DOI:10.1038/s41564-021-00918-8
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