Rapid, user-friendly, cost-effective DNA and library Preparation methods for whole-genome sequencing of bacteria with varying cell wall composition and GC content using minimal DNA on the illumina platform
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Updated: May 10, 2025

Automated Gel Size Selection to Improve the Quality of Next-generation Sequencing Libraries Prepared from Environmental Water Samples
Published on: April 17, 2015
Bertrand Bearzatto1, Jean-François Durant1, Jérôme Ambroise1
1Centre for Applied Molecular Technologies (CTMA), Institute of Experimental and Clinical Research (IREC), Université catholique de Louvain (UCLouvain), Avenue Hippocrate 54/B1.54.01, Woluwe-Saint-Lambert, 1200, Belgium.
Background:
Whole-genome sequencing using high-throughput sequencing is essential for identifying and characterising chromosomes and plasmids in nosocomial and environmental bacterial pathogens, including those with bioterrorism potential. To expedite outbreaks investigations, including accidental or intentional bacterial release, without compromising sequencing quality, we evaluated a more time-efficient, user-friendly, and cost-effective approach, using minimal DNA (~ 1 ng) from a single bacterial colony. Four DNA extraction methods were compared: the automated nucleic acid extractor (EZ1 Advanced, Qiagen) with or without DNA purification using AMPure® beads (EZ1 vs. EZ1-AMP), and two rapid and inexpensive methods: heat shock lysis (HS), and glass bead disruption (GBD). Additionally, we evaluated four library preparation kits: Illumina DNA Prep (DN), Illumina Nextera XT (XT), Roche KAPA HyperPlus (KP), and NEBNext® Ultra™ II FS DNA Library Prep Kit (NN).
Results:
Whole-genome sequencing performance was evaluated on Bacillus cereus (B. cereus), Staphylococcus epidermidis (S. epidermidis), and Enterobacter cloacae (E. cloacae) ATCC strains. Key performance indicators included sequencing depth evenness across chromosome and plasmids (accounting for GC bias), genome assembly quality measured by contig number, N50, genome fraction, and percentage of mismatches. Key performance indicators confirmed that DNA and library preparation methods significantly influenced WGS quality. GBD enabled efficient sequencing across all three bacterial species, while HS proved inadequate for spore-forming bacteria B. cereus. DN, KP, and NN produced high-quality results with low GC bias, whereas XT exhibited significant GC bias and lower quality for bacteria with low GC content.
Conclusions:
This study highlights the importance of selecting suitable DNA and sequencing library preparation methods based on bacterial cell wall composition and GC content for optimal HTS outcomes.
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