Advances in next-generation sequencing have revolutionized genomics and metagenomics of bacterial pathogens by increasing throughput exponentially over first-generation Sanger sequencing. Short reads with a low error rate of <0.1% make them well-suited to high-throughput genomics and metagenomics, allowing them to become the most dominant technology. However, using short reads alone cannot resolve repeated sequences longer than the reads short-read sequencing can span and thus may fail to assemble mobile genetic elements and genomic duplications. Long-read sequencing has become a popular tool for obtaining complete genomes of bacterial pathogens, although it is associated with higher error rates when compared to short reads. Shotgun metagenomics offers a potent method for distinguishing between various strains of bacterial pathogens within intricate food and environmental microbiota. With the swift progress in assembly algorithms for next-generation sequencing, it is crucial to pinpoint the most efficient assembly algorithm for metagenomic identification of bacterial pathogens.
Our objective is to harness state-of-the-art long-read assembly algorithms for long reads and hybrid assembly algorithms for short and long reads to improve the genomic and metagenomic analyses of bacterial pathogens. Additionally, we seek to enhance the genomic and metagenomic analysis of bacterial pathogens by polishing and refining the assemblies of long reads with short reads.
We have harnessed long-read assembly, hybrid assembly, and polishing algorithms to improve the genomic analyses of bacterial pathogens. Meanwhile, we have employed short- and long-read assembly algorithms to enhance the identification of bacterial pathogens in a metagenomic context. In some instances, the extracted sequences from long-read metagenome assemblies produced near-complete metagenome-assembled genomes and provided the locations and structures of genes and mobile genetic elements, shedding light on the advantage of using long reads for metagenome assembly. This project marks the initial phase in implementing shotgun metagenomics in conjunction with state-of-the-art bioinformatic algorithms to enhance pathogen identification.
1. Chen, Z., & Meng, J. (2022). Critical assessment of short-read assemblers for the metagenomic identification of foodborne and waterborne pathogens using simulated bacterial communities. Microorganisms, 10(12), 2416.
2. Chen, Z., Erickson, D. L., & Meng, J. (2021). Polishing the Oxford Nanopore long-read assemblies of bacterial pathogens with Illumina short reads to improve genomic analyses. Genomics, 113(3), 1366-1377.
3. Chen, Z., Erickson, D. L., & Meng, J. (2020). Benchmarking long-read assemblers for genomic analyses of bacterial pathogens using Oxford Nanopore sequencing. International Journal of Molecular Sciences, 21(23), 9161.
4. Chen, Z., Erickson, D. L., & Meng, J. (2020). Benchmarking hybrid assembly approaches for genomic analyses of bacterial pathogens using Illumina and Oxford Nanopore sequencing. BMC Genomics, 21(1), 1-21.
5. Kwon, H. J., Chen, Z., Evans, P., Meng, J., & Chen, Y. (2020). Characterization of mobile genetic elements using long-read sequencing for tracking Listeria monocytogenes from food processing environments. Pathogens, 9(10), 822.
6. Chen, Z., Kuang, D., Xu, X., González-Escalona, N., Erickson, D. L., Brown, E., & Meng, J. (2020). Genomic analyses of multidrug-resistant Salmonella Indiana, Typhimurium, and Enteritidis isolates using MinION and MiSeq sequencing technologies. PloS ONE, 15(7), e0235641.
Poster Presentations in Scientific Meetings
1. Chen, Z., Meng, J. Benchmarking short-read assemblers for the metagenomic identification of bacterial pathogens using simulated bacterial communities. International Association for Food Protection Annual Meeting, Pittsburgh, PA, 08/2022.
2. Kwon, H.J., Chen, Z., Meng, J, Evans, P. Identification of mobile genetic elements and evolutionary analysis based on long-read sequencing of Listeria monocytogenes in the food processing environment. International Association for Food Protection Annual Meeting, Cleveland, OH, 10/2020.