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RISS 인기검색어
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- 저자 : Shahbaz Raza (검색결과 3 건)
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Microbial source tracking using metagenomics and other new technologies
Raza Shahbaz,Kim Jungman,Sadowsky Michael J.,Unno Tatsuya 한국미생물학회 2021 The journal of microbiology Vol.59 No.3
The environment is under siege from a variety of pollution sources. Fecal pollution is especially harmful as it disperses pathogenic bacteria into waterways. Unraveling origins of mixed sources of fecal bacteria is difficult and microbial source tracking (MST) in complex environments is still a daunting task. Despite the challenges, the need for answers far outweighs the difficulties experienced. Advancements in qPCR and next generation sequencing (NGS) technologies have shifted the traditional culture-based MST approaches towards culture independent technologies, where communitybased MST is becoming a method of choice. Metagenomic tools may be useful to overcome some of the limitations of community-based MST methods as they can give deep insight into identifying host specific fecal markers and their association with different environments. Adoption of machine learning (ML) algorithms, along with the metagenomic based MST approaches, will also provide a statistically robust and automated platform. To compliment that, ML-based approaches provide accurate optimization of resources. With the successful application of ML based models in disease prediction, outbreak investigation and medicine prescription, it would be possible that these methods would serve as a better surrogate of traditional MST approaches in future.
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Nguyen Son Giang,Raza Shahbaz,Ta Loan Thi,Le Lan-Anh Thi,Ho Cuong Tu,Unno Tatsuya 한국응용생명화학회 2022 Applied Biological Chemistry (Appl Biol Chem) Vol.65 No.2
In this study, we use high-throughput sequencing-based metagenomic methods to investigate the differences in seasonal structures of the bacterial community and the abundance and diversity of antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs) in both shrimp ponds and river water samples downstream of the Day River, Ninh Binh, Vietnam. The structure of the central bacterial community, ARGs, and MGEs was found to be regardless of the seasons and locations. The predominant phyla found in all samples was Proteobacteria, Bacteroidetes, and Actinobacteria. Multi-drug resistance (MDR) genes and transposases are the most dominant ARG types and MGEs, respectively. Our data showed a higher abundance of bacterial communities, ARGs, and MGEs in the river water during the rainy season. There is a significant correlation between the abundance of ARGs, MGEs, and environmental factors. Our results indicate that water environments containing ARGs/MGEs carrying bacteria pose a risk to shrimp and human health, especially during the rainfall-polluted water season.
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Comparison of de‑novo assembly tools for plasmid metagenome analysis
Sachin Kumar Gupta,Shahbaz Raza,Tatsuya Unno 한국유전학회 2019 Genes & Genomics Vol.41 No.9
Background With the advent of next-generation sequencing techniques, culture-independent metagenome approaches have now made it possible to predict possible presence of genes in the environmental bacteria most of which may be non-cultivable. Short reads obtained from the deep sequencing can be assembled into long contigs some of which include plasmids. Plasmids are the circular double stranded DNA in bacteria and known as one of the major carriers of antibiotic resistance genes. Objective Metagenomic analyses, especially focused on plasmids, could help us predict dissemination mechanisms of antibiotic resistance genes in the environment. However, with the availability of a myriad of metagenomic assemblers, the selection of the most appropriate metagenome assembler for the plasmid metagenome study might be challenging. Therefore, in this study, we compared five open source assemblers to suggest most effective way of plasmid metagenome analysis. Methods IDBA-UD, MEGAHIT, SPAdes, SOAPdenovo2, and Velvet are compared for conducting plasmid metagenome analyses using two water samples. Results Our results clearly showed that abundance and types of antibiotic resistance genes on plasmids varied depending on the selection of assembly tools. IDBA-UD and MEGAHIT demonstrated the overall best assembly statistics with high N50 values with higher portion of longer contigs. Conclusion These two assemblers also detected more diverse plasmids. Among the two, MEGAHIT showed more memory efficient assembly, therefore we suggest that the use of MEGAHIT for plasmid metagenome analysis may offer more diverse plasmids with less computer resource required. Here, we also summarized a fundamental plasmid metagenome work flow, especially for antibiotic resistance gene investigation.
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