Journal of Microbiology

Journal Articles

Delineating the Acquired Genetic Diversity and Multidrug Resistance in Alcaligenes from Poultry Farms and Nearby Soil.: Abhilash Bhattacharjee, Anil Kumar Singh; J. Microbiol. 2024;62(7):511-523. Published online June 21, 2024; DOI: https://doi.org/10.1007/s12275-024-00129-w

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Abstract: Alcaligenes faecalis is one of the most important and clinically significant environmental pathogens, increasing in importance due to its isolation from soil and nosocomial environments. The Gram-negative soil bacterium is associated with skin endocarditis, bacteremia, dysentery, meningitis, endophthalmitis, urinary tract infections, and pneumonia in patients. With emerging antibiotic resistance in A. faecalis, it has become crucial to understand the origin of such resistance genes within this clinically significant environmental and gut bacterium. In this research, we studied the impact of antibiotic overuse in poultry and its effect on developing resistance in A. faecalis. We sampled soil and faecal materials from five poultry farms, performed whole genome sequencing & analysis and identified four strains of A. faecalis. Furthermore, we characterized the genes in the genomic islands of A. faecalis isolates. We found four multidrug-resistant A. faecalis strains that showed resistance against vancomycin (MIC >1000 μg/ml), ceftazidime (50 μg/ml), colistin (50 μg/ml) and ciprofloxacin (50 μg/ml). From whole genome comparative analysis, we found more than 180 resistance genes compared to the reference sequence. Parts of our assembled contigs were found to be similar to different bacteria which included pbp1A and pbp2 imparting resistance to amoxicillin originally a part of Helicobacter and Bordetella pertussis. We also found the Mycobacterial insertion element IS6110 in the genomic islands of all four genomes. This prominent insertion element can be transferred and induce resistance to other bacterial genomes. The results thus are crucial in understanding the transfer of resistance genes in the environment and can help in developing regimes for antibiotic use in the food and poultry industry.

Heterologous Production and Structure Determination of a New Lanthipeptide Sinosporapeptin Using a Cryptic Gene Cluster in an Actinobacterium Sinosporangium siamense: Keita Saito , Keiichiro Mukai , Issara Kaweewan , Hiroyuki Nakagawa , Takeshi Hosaka , Shinya Kodani; J. Microbiol. 2023;61(6):641-648. Published online June 12, 2023; DOI: https://doi.org/10.1007/s12275-023-00059-z

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3 Citations

Abstract: Lipolanthine is a subclass of lanthipeptide that has the modification of lipid moiety at the N-terminus. A cryptic biosynthetic gene cluster comprising four genes (sinA, sinKC, sinD, and sinE) involved in the biosynthesis of lipolanthine was identified in the genome of an actinobacterium Sinosporangium siamense. Heterologous coexpression of a precursor peptide coding gene sinA and lanthipeptide synthetase coding gene sinKC in the host Escherichia coli strain BL21(DE3) resulted in the synthesis of a new lanthipeptide, sinosporapeptin. It contained unusual amino acids, including one labionin and two dehydrobutyrine residues, as determined using NMR and MS analyses. Another coexpression experiment with two additional genes of decarboxylase (sinD) and N-acetyl transferase (sinE) resulted in the production of a lipolanthine-like modified sinosporapeptin.

[PROTOCOL]Analyzing viral epitranscriptomes using nanopore direct RNA sequencing: Ari Hong , Dongwan Kim , V. Narry Kim , Hyeshik Chang; J. Microbiol. 2022;60(9):867-876. Published online August 24, 2022; DOI: https://doi.org/10.1007/s12275-022-2324-4

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6 Citations

Abstract: RNA modifications are a common occurrence across all domains of life. Several chemical modifications, including N6- methyladenosine, have also been found in viral transcripts and viral RNA genomes. Some of the modifications increase the viral replication efficiency while also helping the virus to evade the host immune system. Nonetheless, there are numerous examples in which the host's RNA modification enzymes function as antiviral factors. Although established methods like MeRIP-seq and miCLIP can provide a transcriptome- wide overview of how viral RNA is modified, it is difficult to distinguish between the complex overlapping viral transcript isoforms using the short read-based techniques. Nanopore direct RNA sequencing (DRS) provides both long reads and direct signal readings, which may carry information about the modifications. Here, we describe a refined protocol for analyzing the RNA modifications in viral transcriptomes using nanopore technology.

Review

Application of computational approaches to analyze metagenomic data: Ho-Jin Gwak , Seung Jae Lee , Mina Rho; J. Microbiol. 2021;59(3):233-241. Published online February 10, 2021; DOI: https://doi.org/10.1007/s12275-021-0632-8

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11 Citations

Abstract: Microorganisms play a vital role in living systems in numerous ways. In the soil or ocean environment, microbes are involved in diverse processes, such as carbon and nitrogen cycle, nutrient recycling, and energy acquisition. The relation between microbial dysbiosis and disease developments has been extensively studied. In particular, microbial communities in the human gut are associated with the pathophysiology of several chronic diseases such as inflammatory bowel disease and diabetes. Therefore, analyzing the distribution of microorganisms and their associations with the environment is a key step in understanding nature. With the advent of nextgeneration sequencing technology, a vast amount of metagenomic data on unculturable microbes in addition to culturable microbes has been produced. To reconstruct microbial genomes, several assembly algorithms have been developed by incorporating metagenomic features, such as uneven depth. Since it is difficult to reconstruct complete microbial genomes from metagenomic reads, contig binning approaches were suggested to collect contigs that originate from the same genome. To estimate the microbial composition in the environment, various methods have been developed to classify individual reads or contigs and profile bacterial proportions. Since microbial communities affect their hosts and environments through metabolites, metabolic profiles from metagenomic or metatranscriptomic data have been estimated. Here, we provide a comprehensive review of computational
methods
that can be applied to investigate microbiomes using metagenomic and metatranscriptomic sequencing data. The limitations of metagenomic studies and the key approaches to overcome such problems are discussed.

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