Back to Basics: A Simplified Improvement to Multiple Displacement Amplification for Microbial Single-Cell Genomics

Abstract

Microbial single-cell genomics (SCG) provides access to the genomes of rare and uncultured microorganisms and is a complementary method to metagenomics. Due to the femtogram-levels of DNA in a single microbial cell, sequencing the genome requires whole genome amplification (WGA) as a preliminary step. However, the most common WGA method, multiple displacement amplification (MDA), is known to be costly and biased against specific genomic regions, preventing high-throughput applications and resulting in uneven genome coverage. Thus, obtaining high-quality genomes from many taxa, especially minority members of microbial communities, becomes difficult. Here, we present a volume reduction approach that significantly reduces costs while improving genome coverage and uniformity of DNA amplification products in standard 384-well plates. Our results demonstrate that further volume reduction in specialized and complex setups (e.g., microfluidic chips) is likely unnecessary to obtain higher-quality microbial genomes. This volume reduction method makes SCG more feasible for future studies, thus helping to broaden our knowledge on the diversity and function of understudied and uncharacterized microorganisms in the environment.

Improved single-cell genome amplification by a high-efficiency phi29 DNA polymerase

“…Ethidium monoazide, ultravioletfree light-emitting diode lamp and trehalose can remove contaminants from host DNA, laboratory environments, tools and reagents (Takahashi et al, 2014). Smaller WGA volume can increase the concentration of the template and lessen the chance of background contamination amplification (Sobol and Kaster, 2023). There are several microbial single-cell genomics volume reduction methods including microfluidic devices (Ruan et al, 2020), nanowells (Goldstein et al, 2017), planar surfaces (Rezaei et al, 2021), and hydrogels (Xu et al, 2016), which significantly reduce amplification bias and increase assembly coverage up to almost 90% (Sobol and Kaster, 2023).…”

“…Smaller WGA volume can increase the concentration of the template and lessen the chance of background contamination amplification (Sobol and Kaster, 2023). There are several microbial single-cell genomics volume reduction methods including microfluidic devices (Ruan et al, 2020), nanowells (Goldstein et al, 2017), planar surfaces (Rezaei et al, 2021), and hydrogels (Xu et al, 2016), which significantly reduce amplification bias and increase assembly coverage up to almost 90% (Sobol and Kaster, 2023). Moreover, since elevated reaction temperature reduced the influence on amplification bias, MDA reaction was reported to perform better when amplification temperature increased (Henry and Romesberg, 2005).…”

Comparative single-cell genomics of Atribacterota JS1 in the Japan Trench hadal sedimentary biosphere

“…Notably, bacterial lineages detected only through MAG tended to have a higher guanine-cytosine (GC) content (average of 61%). Although the concentration of amplified DNA was sufficient in the single-cell library preparation step, GC-rich templates of the bacterial genome were less amplified by the multiple displacement amplification reaction, resulting in the generation of low-quality SAGs ( 34 ). Nevertheless, major bacterial classes in the 16S rRNA gene amplicon-based community composition, including JS1, Bacteroidia, Gammaproteobacteria, Dehalococcoidia, and Desulfobacteria, were also detected in the SAG-based community composition, suggesting that a single cell-based approach has the potential to characterize the microbial communities of dominant populations ( Fig.…”

Targeted Cell Labeling and Sorting of Prokaryotes for Cultivation and Omics Approaches

“…Moreover, SCG requires amplification of DNA since a single cell only contains femtograms of nucleic acids, which is too little to be directly used in sequencing. Multiple displacement amplification (MDA) is the most common method used; however, it suffers from random biases as well as biases against high GC regions and chimera formation, which often results in incomplete genomes [Parras-Moltó et al, 2018;Tu et al, 2021;Lawrence et al, 2022;Sobol and Kaster, 2023]. This is why standard SCG and metagenomics can become very expensive in regard to time and cost when one is interested in a specific organism with a certain taxonomy or metabolism, and especially when looking for minority members of microbial communities.…”