Journal of Microbiology

Journal Articles

Different Adaption Strategies of Abundant and Rare Microbial Communities in Sediment and Water of East Dongting Lake: Yabing Gu, Junsheng Li, Zhenghua Liu, Min Zhang, Zhaoyue Yang, Huaqun Yin, Liyuan Chai, Delong Meng, Nengwen Xiao; J. Microbiol. 2024;62(10):829-843. Published online October 22, 2024; DOI: https://doi.org/10.1007/s12275-024-00171-8

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Abstract: The dynamics of aquatic microbes is of great importance for comprehending the acclimatisation and evolution of microorganisms in lake ecology. However, little is known about the adaption strategies of microbial communities in East Dongting Lake, which had special and complexity geographical characteristics. A semi-enclosed lake area (A) and a waterway connected to Yangtze River (B) both existed in the lake zone. Here, we investigated bacterial and fungal community diversity, community network and community assembly processes in sediment and water. The results indicated that the proportion of OTU numbers and their relative abundance for rare and abundant taxa were different obviously between sediment and water, but not between bacteria and fungi. However, abundant subcommunities dominated the shifts of bacterial community diversity and structure in A region, while rare subcommunities for fungal community diversity. Compared to fungal community, bacterial network was more compact and more key stones were identified as rare taxa. In addition, stochastic processes (dispersal limitation) drove the community assembly of abundant and rare subcommunities, but the effects of deterministic processes (including variable and heterogeneous selections) affected more on rare rather than abundant taxa. Partial Mantel test further indicated that the effect of environmental factors was a stronger force in shaping abundant bacterial subcommunities (TOC, NH₄⁺-N, TN, and ORP) and rare fungal subcommunities (ORP). Environmental factors explained more of the variation in bacterial community structure than that in fungal community structure, although they had additional effects on fungal community diversity and community assembly. Moreover, bacterial community affected the fungal community as a biotic factor in water. This research provided new insights into better understanding of microbial communities in the complex environment of the East Dongting Lake.

LAMMER Kinase Governs the Expression and Cellular Localization of Gas2, a Key Regulator of Flocculation in Schizosaccharomyces pombe: Won-Hwa Kang , Yoon-Dong Park , Joo-Yeon Lim , Hee-Moon Park; J. Microbiol. 2024;62(1):21-31. Published online January 5, 2024; DOI: https://doi.org/10.1007/s12275-023-00097-7

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Abstract: It was reported that LAMMER kinase in Schizosaccharomyces pombe plays an important role in cation-dependent and galactose-specific flocculation. Analogous to other flocculating yeasts, when cell wall extracts of the Δlkh1 strain were treated to the wild-type strain, it displayed flocculation. Gas2, a 1,3-β-glucanosyl transferase, was isolated from the EDTA-extracted cell-surface proteins in the Δlkh1 strain. While disruption of the gas2+ gene was not lethal and reduced the flocculation activity of the Δlkh1 strain, the expression of a secreted form of Gas2, in which the GPI anchor addition sequences had been removed, conferred the ability to flocculate upon the WT strain. The Gas2-mediated flocculation was strongly inhibited by galactose but not by glucose. Immunostaining analysis showed that the cell surface localization of Gas2 was crucial for the flocculation of fission yeast. In addition, we identified the regulation of mbx2+ expression by Lkh1 using RT-qPCR. Taken together, we found that Lkh1 induces asexual flocculation by regulating not only the localization of Gas2 but also the transcription of gas2+ through Mbx2.

Antiviral Activity Against SARS‑CoV‑2 Variants Using in Silico and in Vitro Approaches: Hee-Jung Lee , Hanul Choi , Aleksandra Nowakowska , Lin-Woo Kang , Minjee Kim , Young Bong Kim; J. Microbiol. 2023;61(7):703-711. Published online June 26, 2023; DOI: https://doi.org/10.1007/s12275-023-00062-4

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Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emergence in 2019 led to global health crises and the persistent risk of viral mutations. To combat SARS-CoV-2 variants, researchers have explored new approaches to identifying potential targets for coronaviruses. This study aimed to identify SARS-CoV-2 inhibitors using drug repurposing. In silico studies and network pharmacology were conducted to validate targets and coronavirus-associated diseases to select potential candidates, and in vitro assays were performed to evaluate the antiviral effects of the candidate drugs to elucidate the mechanisms of the viruses at the molecular level and determine the effective antiviral drugs for them. Plaque and cytopathic effect reduction were evaluated, and real-time quantitative reverse transcription was used to evaluate the antiviral activity of the candidate drugs against SARS-CoV-2 variants in vitro. Finally, a comparison was made between the molecular docking binding affinities of fenofibrate and remdesivir (positive control) to conventional and identified targets validated from protein–protein interaction (PPI). Seven candidate drugs were obtained based on the biological targets of the coronavirus, and potential targets were identified by constructing complex disease targets and PPI networks. Among the candidates, fenofibrate exhibited the strongest inhibition effect 1 h after Vero E6 cell infection with SARS-CoV-2 variants. This study identified potential targets for coronavirus disease (COVID-19) and SARS-CoV-2 and suggested fenofibrate as a potential therapy for COVID-19.

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Distinctive Combinations of RBD Mutations Contribute to Antibody Evasion in the Case of the SARS-CoV-2 Beta Variant
Tae-Hun Kim, Sojung Bae, Sunggeun Goo, Jinjong Myoung
Journal of Microbiology and Biotechnology.2023; 33(12): 1587. CrossRef

Prevalence and characteristics of the mcr-1 gene in retail meat samples in Zhejiang Province, China: Biao Tang , Jiang Chang , Yi Luo , Han Jiang , Canying Liu , Xingning Xiao , Xiaofeng Ji , Hua Yang; J. Microbiol. 2022;60(6):610-619. Published online March 31, 2022; DOI: https://doi.org/10.1007/s12275-022-1597-y

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Abstract

Considering the serious threat to food safety and public health posed by pathogens with colistin resistance, colistin was banned as a growth promoter in 2017 in China. In recent years, the resistance rate of Escherichia coli isolated from animal intestines or feces to colistin has decreased. However, the prevalence and characteristics of the mcr-1 gene in retail meat have not been well explored. Herein, 106 mcr-1-negative and 16 mcr- 1-positive E. coli isolates were randomly recovered from 120 retail meat samples and screened using colistin. The 106 E. coli isolates showed maximum resistance to sulfafurazole (73.58%) and tetracycline (62.26%) but susceptibility to colistin (0.00%). All 16 mcr-1-positive E. coli isolates showed resistance to colistin, were extended spectrum beta-lactamase (ESBL)-positive and exhibited complex multidrug resistance (MDR). For these 16 isolates, 17 plasmid replicons and 42 antibiotic resistance genes were identified, and at least 7 antibiotic resistance genes were found in each isolate. Acquired disinfectant resistance genes were identified in 75.00% (12/16) of the isolates. Furthermore, comparative genomic and phylogenetic analysis
results
indicated that these 16 mcr-1-positive E. coli isolates and the most prevalent mcr-1-harboring IncI2 plasmid in this study were closely related to other previously reported mcr-1-positive E. coli isolates and the IncI2 plasmid, respectively, showing their wide distribution. Taken together, our findings showed that retail meat products were a crucial reservoir of mcr-1 during the colistin ban period and should be continuously monitored.

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Regression models from portable NIR spectra for predicting the carcass traits and meat quality of beef cattle
Nathália Veloso Trópia, Rizielly Saraiva Reis Vilela, Flávia Adriane de Sales Silva, Dhones Rodrigues Andrade, Adailton Camêlo Costa, Fernando Alerrandro Andrade Cidrini, Jardeson de Souza Pinheiro, Pauliane Pucetti, Mario Luiz Chizzotti, Sebastião de Cam
PLOS ONE.2024; 19(5): e0303946. CrossRef
IncHI1 plasmids mediated the tet(X4) gene spread in Enterobacteriaceae in porcine
Jiangang Ma, Juan Wang, Hua Yang, Mengru Su, Ruichao Li, Li Bai, Jie Feng, Yuting Huang, Zengqi Yang, Biao Tang
Frontiers in Microbiology.2023;[Epub] CrossRef
Prevalence and molecular characteristics of polymyxin-resistant Enterobacterales in a Chinese tertiary teaching hospital
Chenlu Xiao, Xuming Li, Lianjiang Huang, Huiluo Cao, Lizhong Han, Yuxing Ni, Han Xia, Zhitao Yang
Frontiers in Cellular and Infection Microbiology.2023;[Epub] CrossRef
Farm to table: colistin resistance hitchhiking through food
Absar Talat, Carla Miranda, Patrícia Poeta, Asad U. Khan
Archives of Microbiology.2023;[Epub] CrossRef
Detection of mcr-1-harbouring Escherichia coli by quantum dot labelling of synthetic small peptides mimicking lipopolysaccharide receptors
Chenghao Wang, Biao Tang, Jiusheng Wu, Xi Jin, Shuwen Ke, Hua Yang, Yuehuan Liu
International Journal of Antimicrobial Agents.2023; 62(3): 106898. CrossRef
Genomic characterization of multidrug-resistance gene cfr in Escherichia coli recovered from food animals in Eastern China
Biao Tang, Juan Ni, Jiahui Lin, Yangying Sun, Hui Lin, Yuehong Wu, Hua Yang, Min Yue
Frontiers in Microbiology.2022;[Epub] CrossRef
Antimicrobial resistance and genomic characterization of Escherichia coli from pigs and chickens in Zhejiang, China
Wei Zhou, Rumeng Lin, Zhijin Zhou, Jiangang Ma, Hui Lin, Xue Zheng, Jingge Wang, Jing Wu, Yuzhi Dong, Han Jiang, Hua Yang, Zhangnv Yang, Biao Tang, Min Yue
Frontiers in Microbiology.2022;[Epub] CrossRef
The Occurrence and Genomic Characteristics of mcr-1-Harboring Salmonella from Retail Meats and Eggs in Qingdao, China
Changan Li, Xiulei Gu, Liping Zhang, Yuqing Liu, Yan Li, Ming Zou, Baotao Liu
Foods.2022; 11(23): 3854. CrossRef

Regulator of ribonuclease activity modulates the pathogenicity of Vibrio vulnificus: Jaejin Lee , Eunkyoung Shin , Jaeyeong Park , Minho Lee , Kangseok Lee; J. Microbiol. 2021;59(12):1133-1141. Published online November 9, 2021; DOI: https://doi.org/10.1007/s12275-021-1518-5

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Abstract

RraA, a protein regulator of RNase E activity, plays a unique role in modulating the mRNA abundance in Escherichia coli. The marine pathogenic bacterium Vibrio vulnificus also possesses homologs of RNase E (VvRNase E) and RraA (VvRraA1 and VvRraA2). However, their physiological roles have not yet been investigated. In this study, we demonstrated that VvRraA1 expression levels affect the pathogenicity of V. vulnificus. Compared to the wild-type strain, the VvrraA1-deleted strain (ΔVvrraA1) showed decreased motility, invasiveness, biofilm formation ability as well as virulence in mice; these phenotypic changes of ΔVvrraA1 were restored by the exogenous expression of VvrraA1. Transcriptomic analysis indicated that VvRraA1 expression levels affect the abundance of a large number of mRNA species. Among them, the halflives of mRNA species encoding virulence factors (e.g., smcR and htpG) that have been previously shown to affect VvrraA1 expression-dependent phenotypes were positively correlated with VvrraA1 expression levels. These findings suggest that VvRraA1 modulates the pathogenicity of V. vulnificus by regulating the abundance of a subset of mRNA species.

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Identification of the global regulatory roles of RraA via the integrative transcriptome and proteome in Vibrio alginolyticus
Huizhen Chen, Qian Gao, Bing Liu, Ying Zhang, Jianxiang Fang, Songbiao Wang, Youqi Chen, Chang Chen, Nicolas E. Buchler
mSphere.2024;[Epub] CrossRef
Comparative Transcriptomic Analysis of Flagellar-Associated Genes in Salmonella Typhimurium and Its rnc Mutant
Seungmok Han, Ji-Won Byun, Minho Lee
Journal of Microbiology.2024; 62(1): 33. CrossRef
Eco-Evolutionary Drivers of Vibrio parahaemolyticus Sequence Type 3 Expansion: Retrospective Machine Learning Approach
Amy Marie Campbell, Chris Hauton, Ronny van Aerle, Jaime Martinez-Urtaza
JMIR Bioinformatics and Biotechnology.2024; 5: e62747. CrossRef
Relaxed Cleavage Specificity of Hyperactive Variants of Escherichia coli RNase E on RNA I
Dayeong Bae, Hana Hyeon, Eunkyoung Shin, Ji-Hyun Yeom, Kangseok Lee
Journal of Microbiology.2023; 61(2): 211. CrossRef
Regulator of RNase E activity modulates the pathogenicity of Salmonella Typhimurium
Jaejin Lee, Eunkyoung Shin, Ji-Hyun Yeom, Jaeyoung Park, Sunwoo Kim, Minho Lee, Kangseok Lee
Microbial Pathogenesis.2022; 165: 105460. CrossRef

Characterization of staphylococcal endolysin LysSAP33 possessing untypical domain composition: Jun-Hyeok Yu , Do-Won Park , Jeong-A Lim , Jong-Hyun Park; J. Microbiol. 2021;59(9):840-847. Published online August 12, 2021; DOI: https://doi.org/10.1007/s12275-021-1242-1

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Abstract

Endolysin, a peptidoglycan hydrolase derived from bacteriophage, has been suggested as an alternative antimicrobial agent. Many endolysins on staphylococcal phages have been identified and applied extensively against Staphylococcus spp. Among them, LysK-like endolysin, a well-studied staphylococcal endolysin, accounts for most of the identified endolysins. However, relatively little interest has been paid to LysKunlike endolysin and a few of them has been characterized. An endolysin LysSAP33 encoded on bacteriophage SAP33 shared low homology with LysK-like endolysin in sequence by 41% and domain composition (CHAP-unknown CBD). A green fluorescence assay using a fusion protein for Lys- SAP33_CBD indicated that the CBD domain (157-251 aa) was bound to the peptidoglycan of S. aureus. The deletion of LysSAP33_CBD at the C-terminal region resulted in a significant decrease in lytic activity and efficacy. Compared to LysK-like endolysin, LysSAP33 retained its lytic activity in a broader range of temperature, pH, and NaCl concentrations. In addition, it showed a higher activity against biofilms than LysK-like endolysin. This study could be a helpful tool to develop our understanding of staphylococcal endolysins not belonging to LysK-like endolysins and a potential biocontrol agent against biofilms.

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Phage-Derived Endolysins Against Resistant Staphylococcus spp.: A Review of Features, Antibacterial Activities, and Recent Applications
Mina Golban, Javad Charostad, Hossein Kazemian, Hamid Heidari
Infectious Diseases and Therapy.2024;[Epub] CrossRef
Molecular Machinery of the Triad Holin, Endolysin, and Spanin: Key Players Orchestrating Bacteriophage-Induced Cell Lysis and their Therapeutic Applications
Safia Samir
Protein & Peptide Letters.2024; 31(2): 85. CrossRef
A Novel Truncated CHAP Modular Endolysin, CHAPSAP26-161, That Lyses Staphylococcus aureus, Acinetobacter baumannii, and Clostridioides difficile, and Exhibits Therapeutic Effects in a Mouse Model of A. baumannii Infection
Yoon-Jung Choi, Shukho Kim, Ram Hari Dahal, Jungmin Kim
Journal of Microbiology and Biotechnology.2024; 34(8): 1718. CrossRef
Therapeutic potential of bacteriophage endolysins for infections caused by Gram-positive bacteria
He Liu, Zhen Hu, Mengyang Li, Yi Yang, Shuguang Lu, Xiancai Rao
Journal of Biomedical Science.2023;[Epub] CrossRef
Endolysin, a Promising Solution against Antimicrobial Resistance
Mujeeb ur Rahman, Weixiao Wang, Qingqing Sun, Junaid Ali Shah, Chao Li, Yanmei Sun, Yuanrui Li, Bailing Zhang, Wei Chen, Shiwei Wang
Antibiotics.2021; 10(11): 1277. CrossRef

Lysobacter arenosi sp. nov. and Lysobacter solisilvae sp. nov. isolated from soil: Kyeong Ryeol Kim† , Kyung Hyun Kim† , Shehzad Abid Khan , Hyung Min Kim , Dong Min Han , Che Ok Jeon; J. Microbiol. 2021;59(8):709-718. Published online June 1, 2021; DOI: https://doi.org/10.1007/s12275-021-1156-y

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Abstract

Two Gram-stain negative, yellow-pigmented, and mesophilic bacteria, designated strains R7T and R19T, were isolated from sandy and forest soil, South Korea, respectively. Both strains were non-motile rods showing catalase- and oxidase-positive activities. Both strains were shown to grow at 10–37°C and pH 6.0–9.0, and in the presence of 0–1.5% (w/v) NaCl. Strain R7T contained iso-C14:0, iso-C15:0, iso-C16:0, and summed feature 9 (comprising C16:0 10-methyl and/or iso-C17:1 ω9c), whereas strain R19T contained iso-C11:0 3-OH, C16:1 ω7c alcohol, iso-C11:0, iso-C15:0, iso-C16:0, and summed feature 9 (comprising C16:0 10-methyl and/or iso-C17:1 ω9c) as major cellular fatty acids (> 5%). Both strains contained ubiquinone- 8 as the sole isoprenoid quinone and phosphatidylglycerol, phosphatidylethanolamine, and an unidentified phospholipid as the major polar lipids. The DNA G + C contents of strains R7T and R19T calculated from their genomes were 66.9 mol% and 68.9 mol%, respectively. Strains R7T and R19T were most closely related to Lysobacter panacisoli C8-1T and Lysobacter niabensis GH34-4T with 98.7% and 97.8% 16S rRNA sequence similarities, respectively. Phylogenetic analyses based on 16S rRNA gene sequences showed that strains R7T and R19T formed distinct phylogenetic lineages within the genus Lysobacter. Based on phenotypic, chemotaxonomic, and molecular features, strains R7T and R19T represent novel species of the genus Lysobacter, for which the names Lysobacter arenosi sp. nov. and Lysobacter solisilvae sp. nov. are proposed. The type strains of L. arenosi and L. solisilvae are R7T (= KACC 21663T = JCM 34257T) and R19T (= KACC 21767T = JCM 34258T), respectively.

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Luteimonas flava sp. nov. and Aquilutibacter rugosus gen. nov., sp. nov., isolated from freshwater environments in China and re-examining the taxonomic status of genera Luteimonas and Lysobacter
Huibin Lu, Li Chen, Yujing Wang, Peng Xing, Qinglong Wu
International Journal of Systematic and Evolutionary Microbiology .2024;[Epub] CrossRef
Saline soil improvement promotes the transformation of microbial salt tolerance mechanisms and microbial-plant-animal ecological interactions
Keyu Yao, Guanghao Wang, Wen Zhang, Qiang Liu, Jian Hu, Mao Ye, Xin Jiang
Journal of Environmental Management.2024; 372: 123360. CrossRef
Optimal Irrigation and Fertilization Enhanced Tomato Yield and Water and Nitrogen Productivities by Increasing Rhizosphere Microbial Nitrogen Fixation
Hongfei Niu, Tieliang Wang, Yongjiang Dai, Mingze Yao, Bo Li, Jiaqi Zheng, Lizhen Mao, Mingyu Zhao, Zhanyang Xu, Feng Zhang
Agronomy.2024; 14(9): 2111. CrossRef
Short-term effect of reclaimed wastewater quality gradient on soil microbiome during irrigation
V. Moulia, N. Ait-Mouheb, G. Lesage, J. Hamelin, N. Wéry, V. Bru-Adan, L. Kechichian, M. Heran
Science of The Total Environment.2023; 901: 166028. CrossRef
Dyadobacter pollutisoli sp. nov., isolated from plastic waste landfill soil
Kyeong Ryeol Kim, Jeong Min Kim, Jae Kyeong Lee, Dong Min Han, Lujiang Hao, Che Ok Jeon
International Journal of Systematic and Evolutionary Microbiology .2023;[Epub] CrossRef
Physiological and genomic analyses of cobalamin (vitamin B12)-auxotrophy of Lysobacter auxotrophicus sp. nov., a methionine-auxotrophic chitinolytic bacterium isolated from chitin-treated soil
Akihiro Saito, Hideo Dohra, Moriyuki Hamada, Ryota Moriuchi, Yohei Kotsuchibashi, Koji Mori
International Journal of Systematic and Evolutionary Microbiology .2023;[Epub] CrossRef
Nitratireductor rhodophyticola sp. nov., isolated from marine red algae
Kyung Hyun Kim, Sylvia Kristyanto, Hyung Min Kim, Kyeong Ryeol Kim, Che Ok Jeon
International Journal of Systematic and Evolutionary Microbiology .2022;[Epub] CrossRef
Description of Corynebacterium poyangense sp. nov., isolated from the feces of the greater white-fronted geese (Anser albifrons)
Qian Liu, Guoying Fan, Kui Wu, Xiangning Bai, Xi Yang, Wentao Song, Shengen Chen, Yanwen Xiong, Haiying Chen
Journal of Microbiology.2022; 60(7): 668. CrossRef
Lysobacter ciconiae sp. nov., and Lysobacter avium sp. nov., isolated from the faeces of an Oriental stork
So-Yeon Lee, Pil Soo Kim, Hojun Sung, Dong-Wook Hyun, Jin-Woo Bae
Journal of Microbiology.2022; 60(5): 469. CrossRef
Isolation and characterization of tick-borne Roseomonas haemaphysalidis sp. nov. and rodent-borne Roseomonas marmotae sp. nov.
Wentao Zhu, Juan Zhou, Shan Lu, Jing Yang, Xin-He Lai, Dong Jin, Ji Pu, Yuyuan Huang, Liyun Liu, Zhenjun Li, Jianguo Xu
Journal of Microbiology.2022; 60(2): 137. CrossRef
Rhodococcus oxybenzonivorans sp. nov., a benzophenone-3-degrading bacterium, isolated from stream sediment
Ju Hye Baek, Woonhee Baek, Sang Eun Jeong, Sung Chul Lee, Hyun Mi Jin, Che Ok Jeon
International Journal of Systematic and Evolutionary Microbiology.2022;[Epub] CrossRef

Ganoderma boninense mycelia for phytochemicals and secondary metabolites with antibacterial activity: Syahriel Abdullah , Se-Eun Jang , Min-Kyu Kwak , KhimPhin Chong; J. Microbiol. 2020;58(12):1054-1064. Published online December 2, 2020; DOI: https://doi.org/10.1007/s12275-020-0208-z

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Abstract

Antiplasmodial nortriterpenes with 3,4-seco-27-norlanostane skeletons, almost entirely obtained from fruiting bodies, represent the main evidential source for bioactive secondary metabolites derived from a relatively unexplored phytopathogenic fungus, Ganoderma boninense. Currently lacking is convincing evidence for antimicrobial secondary metabolites in this pathogen, excluding that obtained from commonly observed phytochemicals in the plants. Herein, we aimed to demonstrate an efficient analytical approach for the production of antibacterial secondary metabolites using the mycelial extract of G. boninense. Three experimental cultures were prepared from fruiting bodies (GBFB), mycelium cultured on potato dextrose agar (PDA) media (GBMA), and liquid broth (GBMB). Through solvent extraction, culture type-dependent phytochemical distributions were diversely exhibited. Water-extracted GBMB produced the highest yield (31.21 ± 0.61%, p < 0.05), but both GBFB and GBMA elicited remarkably higher yields than GBMB when polar-organic solvent extraction was employed. Greater quantities of phytochemicals were also obtained from GBFB and GBMA, in sharp contrast to those gleaned from GBMB. However, the highest antibacterial activity was observed in chloroform-extracted GBMA against all tested bacteria. From liquid-liquid extractions (LLE), it was seen that mycelia extraction with combined chloroform-methanol-water at a ratio of 1:1:1 was superior at detecting antibacterial activities with the most significant quantities of antibacterial compounds. The data demonstrate a novel means of assessing antibacterial compounds with mycelia by LLE which avoids the shortcomings of standardized
method
ologies. Additionally, the antibacterial extract from the mycelia demonstrate that previously unknown bioactive secondary metabolites of the less studied subsets of Ganoderma may serve as active and potent antimicrobial compounds.

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Medium composition optimization and characterization of polysaccharides extracted from Ganoderma boninense along with antioxidant activity
Qian-Zhu Li, Chuan Xiong, Wei Chee Wong, Li-Wei Zhou
International Journal of Biological Macromolecules.2024; 260: 129528. CrossRef
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Oluwatosin Temilade Adu, Yougasphree Naidoo, Johnson Lin, Depika Dwarka, John Mellem, Hosakatte Niranjana Murthy, Yaser Hassan Dewir
Plants.2023; 12(4): 769. CrossRef
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Shao-Jun Tang, Chen-Xia Shao, Yi Yang, Rui Ren, Lei Jin, Dan Hu, Shen-Lian Wu, Pin Lei, Yue-Lin He, Jun Xu
Journal of Ethnopharmacology.2023; 311: 116407. CrossRef
Impacts of Plant-derived Secondary Metabolites for Improving Flora in Type 2 Diabetes
Lin Zehao Li, Yan Yan, Qinghe Song, Zhibin Wang, Wei Zhang, Yanli Hou, Xiandang Zhang
Current Diabetes Reviews.2023;[Epub] CrossRef
Bioactive Compounds of Ganoderma boninense Inhibited Methicillin-Resistant Staphylococcus aureus Growth by Affecting Their Cell Membrane Permeability and Integrity
Yow-San Chan, Khim-Phin Chong
Molecules.2022; 27(3): 838. CrossRef
Natural Products Targeting Liver X Receptors or Farnesoid X Receptor
Jianglian She, Tanwei Gu, Xiaoyan Pang, Yonghong Liu, Lan Tang, Xuefeng Zhou
Frontiers in Pharmacology.2022;[Epub] CrossRef
Biophysical characterization of antibacterial compounds derived from pathogenic fungi Ganoderma boninense
Syahriel Abdullah, Yoon Sin Oh, Min-Kyu Kwak, KhimPhin Chong
Journal of Microbiology.2021; 59(2): 164. CrossRef
Enhanced Accumulation of Betulinic Acid in Transgenic Hairy Roots of Senna obtusifolia Growing in the Sprinkle Bioreactor and Evaluation of Their Biological Properties in Various Biological Models
Tomasz Kowalczyk, Przemysław Sitarek, Monika Toma, Patricia Rijo, Eva Domínguez‐Martín, Irene Falcó, Gloria Sánchez, Tomasz Śliwiński
Chemistry & Biodiversity.2021;[Epub] CrossRef

Review

[MINIREVIEW]Bacterial bug-out bags: outer membrane vesicles and their proteins and functions: Kesavan Dineshkumar , Vasudevan Aparna , Liang Wu , Jie Wan , Mohamod Hamed Abdelaziz , Zhaoliang Su , Shengjun Wang , Huaxi Xu; J. Microbiol. 2020;58(7):531-542. Published online June 10, 2020; DOI: https://doi.org/10.1007/s12275-020-0026-3

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Abstract

Among the major bacterial secretions, outer membrane vesicles (OMVs) are significant and highly functional. The proteins and other biomolecules identified within OMVs provide new insights into the possible functions of OMVs in bacteria. OMVs are rich in proteins, nucleic acids, toxins and virulence factors that play a critical role in bacteria-host interactions. In this review, we discuss some proteins with multifunctional features from bacterial OMVs and their role involving the mechanisms of bacterial survival and defence. Proteins with moonlighting activities in OMVs are discussed based on their functions in bacteria. OMVs harbour many other proteins that are important, such as proteins involved in virulence, defence, and competition. Overall, OMVs are a power-packed aid for bacteria, harbouring many defensive and moonlighting proteins and acting as a survival kit in
case
of an emergency or as a defence weapon. In summary, OMVs can be defined as bug-out bags for bacterial defence and, therefore, survival.

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Teresa Faddetta, Giovanni Renzone, Alberto Vassallo, Emilio Rimini, Giorgio Nasillo, Gianpiero Buscarino, Simonpietro Agnello, Mariano Licciardi, Luigi Botta, Andrea Scaloni, Antonio Palumbo Piccionello, Anna Maria Puglia, Giuseppe Gallo, Gladys Alexandre
Applied and Environmental Microbiology.2022;[Epub] CrossRef
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Shiana Malhotra, Zarinah M. Amin, Garima Dobhal, Sophie Cottam, Thomas Nann, Renee V. Goreham
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Enis Kostallari, Shantha Valainathan, Louise Biquard, Vijay H. Shah, Pierre-Emmanuel Rautou
Advanced Drug Delivery Reviews.2021; 175: 113816. CrossRef

Journal Articles

Machine learning methods for microbiome studies: Junghyun Namkung; J. Microbiol. 2020;58(3):206-216. Published online February 27, 2020; DOI: https://doi.org/10.1007/s12275-020-0066-8

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Abstract

Researches on the microbiome have been actively conducted worldwide and the results have shown human gut bacterial environment significantly impacts on immune system, psychological conditions, cancers, obesity, and metabolic diseases. Thanks to the development of sequencing technology, microbiome studies with large number of samples are eligible on an acceptable cost nowadays. Large samples allow analysis of more sophisticated modeling using machine learning approaches to study relationships between microbiome and various traits. This article provides an overview of machine learning methods for non-data scientists interested in the association analysis of microbiomes and host phenotypes. Once genomic feature of microbiome is determined, various analysis
methods
can be used to explore the relationship between microbiome and host phenotypes that include penalized regression, support vector machine (SVM), random forest, and artificial neural network (ANN). Deep neural network methods are also touched. Analysis procedure from environment setup to extract analysis results are presented with Python programming language.

Citations

Citations to this article as recorded by

Association of body index with fecal microbiome in children cohorts with ethnic–geographic factor interaction: accurately using a Bayesian zero-inflated negative binomial regression model
Jian Huang, Yanzhuan Lu, Fengwei Tian, Yongqing Ni, Cheng Gao, Dong Chen, Luciana Damascena Silva
mSystems.2024;[Epub] CrossRef
Characteristics of gut microbiota of premature infants in the early postnatal period and their relationship with intraventricular hemorrhage
Yunlong Zhao, Shan Li, Rui Zhang, Xin Zhang, Qiuyue Shen, Xingyun Zhang, Tian Tian, Xinlin Hou
BMC Microbiology.2024;[Epub] CrossRef
Development and application of a machine learning-based predictive model for obstructive sleep apnea screening
Kang Liu, Shi Geng, Ping Shen, Lei Zhao, Peng Zhou, Wen Liu
Frontiers in Big Data.2024;[Epub] CrossRef
Methodology for biomarker discovery with reproducibility in microbiome data using machine learning
David Rojas-Velazquez, Sarah Kidwai, Aletta D. Kraneveld, Alberto Tonda, Daniel Oberski, Johan Garssen, Alejandro Lopez-Rincon
BMC Bioinformatics.2024;[Epub] CrossRef
mi-Mic: a novel multi-layer statistical test for microbiota-disease associations
Oshrit Shtossel, Shani Finkelstein, Yoram Louzoun
Genome Biology.2024;[Epub] CrossRef
Understanding Nanoscale Interactions between Minerals and Microbes: Opportunities for Green Remediation of Contaminated Sites
Tianchi Cao, Yaqi Liu, Cheng Gao, Yuxin Yuan, Wei Chen, Tong Zhang
Environmental Science & Technology.2024; 58(32): 14078. CrossRef
Harnessing of Artificial Intelligence for the Diagnosis and Prevention of Hospital-Acquired Infections: A Systematic Review
Buket Baddal, Ferdiye Taner, Dilber Uzun Ozsahin
Diagnostics.2024; 14(5): 484. CrossRef
A longitudinal study of the gut microbiota during the first three years of life: Links with problem behavior and executive functions at preschool age
Yvonne Willemsen, Yangwenshan Ou, Clara Belzer, Alejandro Arias Vásquez, Hauke Smidt, Roseriet Beijers, Carolina de Weerth
Development and Psychopathology.2024; 36(4): 2032. CrossRef
Baseline gut microbiota diversity and composition and albendazole efficacy in hookworm-infected individuals
Javier Gandasegui, Pedro E. Fleitas, Paula Petrone, Berta Grau-Pujol, Valdemiro Novela, Elisa Rubio, Osvaldo Muchisse, Anélsio Cossa, José Carlos Jamine, Charfudin Sacoor, Eric A. T. Brienen, Lisette van Lieshout, José Muñoz, Climent Casals-Pascual
Parasites & Vectors.2024;[Epub] CrossRef
Gut bacteriome and mood disorders in women with PCOS
S Lee, M V Tejesvi, E Hurskainen, O Aasmets, J Plaza-Díaz, S Franks, L Morin-Papunen, J S Tapanainen, T S Ruuska, S Altmäe, E Org, A Salumets, R K Arffman, T T Piltonen
Human Reproduction.2024; 39(6): 1291. CrossRef
DeepGum: Deep feature transfer for gut microbiome analysis using bottleneck models
U. Gülfem Elgün Çiftcioğlu, O. Ufuk Nalbanoglu
Biomedical Signal Processing and Control.2024; 91: 105984. CrossRef
Harnessing meta-omics to unveil and mitigate methane emissions in ruminants: Integrative approaches and future directions
Yuchao Zhao, Jian Tan, Luoyun Fang, Linshu Jiang
Science of The Total Environment.2024; 951: 175732. CrossRef
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Sihai Zhang, Xuemei Han, Yangchun Zhu, Xiangfeng Tan
Forests.2023; 14(11): 2134. CrossRef
Soterobionts: disease-preventing microorganisms and proposed strategies to facilitate their discovery
Mengcen Wang, Tomislav Cernava
Current Opinion in Microbiology.2023; 75: 102349. CrossRef
Microbial biomarkers of tree water status for next‐generation biomonitoring of forest ecosystems
Marine C. Cambon, Marine Trillat, Isabelle Lesur‐Kupin, Régis Burlett, Emilie Chancerel, Erwan Guichoux, Lucie Piouceau, Bastien Castagneyrol, Grégoire Le Provost, Stéphane Robin, Yves Ritter, Inge Van Halder, Sylvain Delzon, David A. Bohan, Corinne Vache
Molecular Ecology.2023; 32(22): 5944. CrossRef
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Taejung Chung, Runan Yan, Daniel L. Weller, Jasna Kovac, Jeffrey A. Gralnick
Microbiology Spectrum.2023;[Epub] CrossRef
The gut microbiota as a potential biomarker for methamphetamine use disorder: evidence from two independent datasets
Linzi Liu, Zijing Deng, Wen Liu, Ruina Liu, Tao Ma, Yifang Zhou, Enhui Wang, Yanqing Tang
Frontiers in Cellular and Infection Microbiology.2023;[Epub] CrossRef
Machine Learning Algorithms Applied to Predict Autism Spectrum Disorder Based on Gut Microbiome Composition
Juan M. Olaguez-Gonzalez, Isaac Chairez, Luz Breton-Deval, Mariel Alfaro-Ponce
Biomedicines.2023; 11(10): 2633. CrossRef
Predicting Personalized Responses to Dietary Fiber Interventions: Opportunities for Modulation of the Gut Microbiome to Improve Health
Car Reen Kok, Devin Rose, Robert Hutkins
Annual Review of Food Science and Technology.2023; 14(1): 157. CrossRef
Machine learning: a powerful tool for identifying key microbial agents associated with specific cancer types
Jia Feng, Kailan Yang, Xuexue Liu, Min Song, Ping Zhan, Mi Zhang, Jinsong Chen, Jinbo Liu
PeerJ.2023; 11: e16304. CrossRef
Artificial Intelligence: A Promising Tool in Exploring the Phytomicrobiome in Managing Disease and Promoting Plant Health
Liang Zhao, Sean Walkowiak, Wannakuwattewaduge Gerard Dilantha Fernando
Plants.2023; 12(9): 1852. CrossRef
Impact of Aging Microbiome on Metabolic Profile of Natural Aging Huangjiu through Machine Learning
Huakun Yu, Shuangping Liu, Zhilei Zhou, Hongyuan Zhao, Yuezheng Xu, Jian Mao
Foods.2023; 12(4): 906. CrossRef
An Intelligent and Optimal Deep-Learning Approach in Sensor-Based Networks for Detecting Microbes
S. Remya, T. Anjali
IEEE Sensors Journal.2023; 23(17): 19367. CrossRef
Machine learning-guided determination of Acinetobacter density in waterbodies receiving municipal and hospital wastewater effluents
Temitope C. Ekundayo, Mary A. Adewoyin, Oluwatosin A. Ijabadeniyi, Etinosa O. Igbinosa, Anthony I. Okoh
Scientific Reports.2023;[Epub] CrossRef
A Microbial-Based Approach to Mental Health: The Potential of Probiotics in the Treatment of Depression
Dinyadarshini Johnson, Vengadesh Letchumanan, Chern Choong Thum, Sivakumar Thurairajasingam, Learn-Han Lee
Nutrients.2023; 15(6): 1382. CrossRef
Exploring the role of gut microbiota in advancing personalized medicine
Gouxin Huang, Raees Khan, Yilin Zheng, Ping-Chin Lee, Qingnan Li, Imran Khan
Frontiers in Microbiology.2023;[Epub] CrossRef
Using machine learning models to predict the effects of seasonal fluxes on Plesiomonas shigelloides population density
Temitope C. Ekundayo, Oluwatosin A. Ijabadeniyi, Etinosa O. Igbinosa, Anthony I. Okoh
Environmental Pollution.2023; 317: 120734. CrossRef
Next-Generation Sequencing for the Detection of Microbial Agents in Avian Clinical Samples
Claudio L. Afonso, Anna M. Afonso
Veterinary Sciences.2023; 10(12): 690. CrossRef
Classification of Microbiome Data from Type 2 Diabetes Mellitus Individuals with Deep Learning Image Recognition
Juliane Pfeil, Julienne Siptroth, Heike Pospisil, Marcus Frohme, Frank T. Hufert, Olga Moskalenko, Murad Yateem, Alina Nechyporenko
Big Data and Cognitive Computing.2023; 7(1): 51. CrossRef
EnsDeepDP: An Ensemble Deep Learning Approach for Disease Prediction Through Metagenomics
Yang Shen, Jinlin Zhu, Zhaohong Deng, Wenwei Lu, Hongchao Wang
IEEE/ACM Transactions on Computational Biology and Bioinformatics.2023; 20(2): 986. CrossRef
Classifying asthma control using salivary and fecal bacterial microbiome in children with moderate‐to‐severe asthma
Jelle M. Blankestijn, Alejandro Lopez‐Rincon, Anne H. Neerincx, Susanne J. H. Vijverberg, Simone Hashimoto, Mario Gorenjak, Olaia Sardón Prado, Paula Corcuera‐Elosegui, Javier Korta‐Murua, Maria Pino‐Yanes, Uroš Potočnik, Corinna Bang, Andre Franke, Chris
Pediatric Allergy and Immunology.2023;[Epub] CrossRef
A new approach of microbiome monitoring in the built environment: feasibility analysis of condensation capture
Jarrad T. Hampton-Marcell, Aritra Ghosh, Mohamad Jafari Gukeh, Constantine M. Megaridis
Microbiome.2023;[Epub] CrossRef
Artificial network inference analysis reveals the impact of biostimulant on bacterial communities in fumigated soil for potato production against common scab
Honoré Tekeu, Thomas Jeanne, Joël D’Astous-Pagé, Richard Hogue
Frontiers in Soil Science.2023;[Epub] CrossRef
Discriminative Machine Learning Analysis for Skin Microbiome: Observing Biomarkers in Patients with Seborrheic Dermatitis
H.E.C. van der Wall, R.J. Doll, G.J.P. van Westen, T. Niemeyer-van der Kolk, G. Feiss, H. Pinckaers, M.B.A. van Doorn, T. Nijsten, M.G.H. Sanders, A.F. Cohen, J. Burggraaf, R. Rissmann, L.M. Pardo
Journal of Artificial Intelligence for Medical Sciences.2022; 3(1-2): 1. CrossRef
Microbial Forensics: A Present to Future Perspective on Genomic Targets, Bioinformatic Challenges, and Applications
Rachel Shadoff, Mary Anne Panoyan, Nicole Novroski
Forensic Genomics.2022; 2(2): 42. CrossRef
Robust host source tracking building on the divergent and non-stochastic assembly of gut microbiomes in wild and farmed large yellow croaker
Jun Zhu, Hao Li, Ze Zhou Jing, Wei Zheng, Yuan Rong Luo, Shi Xi Chen, Feng Guo
Microbiome.2022;[Epub] CrossRef
Machine learning on the road to unlocking microbiota’s potential for boosting immune checkpoint therapy
Szymon Wojciechowski, Monika Majchrzak-Górecka, Paweł Biernat, Krzysztof Odrzywołek, Łukasz Pruss, Konrad Zych, Jan Majta, Kaja Milanowska-Zabel
International Journal of Medical Microbiology.2022; 312(7): 151560. CrossRef
Machine Learning in Nutrition Research
Daniel Kirk, Esther Kok, Michele Tufano, Bedir Tekinerdogan, Edith J M Feskens, Guido Camps
Advances in Nutrition.2022; 13(6): 2573. CrossRef
The diagnostic potential and barriers of microbiome based therapeutics
Animesh Acharjee, Utpreksha Singh, Saptamita Paul Choudhury, Georgios V. Gkoutos
Diagnosis.2022; 9(4): 411. CrossRef
Microbiome-based personalized nutrition as a result of the 4.0 technological revolution: A mini literature review
Neslihan Yeşilyurt, Birsen Yılmaz, Duygu Ağagündüz, Raffaele Capasso
Process Biochemistry.2022; 121: 257. CrossRef
Fecal Microbiota Transplants for Inflammatory Bowel Disease Treatment: Synthetic- and Engineered Communities-Based Microbiota Transplants Are the Future
Raees Khan, Nazish Roy, Hussain Ali, Muhammad Naeem, Eiji Sakai
Gastroenterology Research and Practice.2022; 2022: 1. CrossRef
Utilizing stability criteria in choosing feature selection methods yields reproducible results in microbiome data
Lingjing Jiang, Niina Haiminen, Anna‐Paola Carrieri, Shi Huang, Yoshiki Vázquez‐Baeza, Laxmi Parida, Ho‐Cheol Kim, Austin D. Swafford, Rob Knight, Loki Natarajan
Biometrics.2022; 78(3): 1155. CrossRef
New-Generation Sequencing Technology in Diagnosis of Fungal Plant Pathogens: A Dream Comes True?
Maria Aragona, Anita Haegi, Maria Teresa Valente, Luca Riccioni, Laura Orzali, Salvatore Vitale, Laura Luongo, Alessandro Infantino
Journal of Fungi.2022; 8(7): 737. CrossRef
Machine learning to predict dynamic changes of pathogenic Vibrio spp. abundance on microplastics in marine environment
Jiawen Jiang, Hua Zhou, Ting Zhang, Chuanyi Yao, Delin Du, Liang Zhao, Wenfang Cai, Liming Che, Zhikai Cao, Xue E Wu
Environmental Pollution.2022; 305: 119257. CrossRef
MicrobioSee: A Web-Based Visualization Toolkit for Multi-Omics of Microbiology
JinHui Li, Yimeng Sang, Sen Zeng, Shuming Mo, Zufan Zhang, Sheng He, Xinying Li, Guijiao Su, Jianping Liao, Chengjian Jiang
Frontiers in Genetics.2022;[Epub] CrossRef
Multi-Omics Strategies for Investigating the Microbiome in Toxicology Research
Ethan W Morgan, Gary H Perdew, Andrew D Patterson
Toxicological Sciences.2022; 187(2): 189. CrossRef
Noninvasive early diagnosis of intestinal diseases based on artificial intelligence in genomics and microbiome
Weitong Zhang, Xingjian Chen, Ka‐Chun Wong
Journal of Gastroenterology and Hepatology.2021; 36(4): 823. CrossRef
Harnessing machine learning for development of microbiome therapeutics
Laura E. McCoubrey, Moe Elbadawi, Mine Orlu, Simon Gaisford, Abdul W. Basit
Gut Microbes.2021;[Epub] CrossRef
Mild Cystic Fibrosis Lung Disease Is Associated with Bacterial Community Stability
Thomas H. Hampton, Devin Thomas, Christopher van der Gast, George A. O’Toole, Bruce A. Stanton, Amanda G. Oglesby
Microbiology Spectrum.2021;[Epub] CrossRef
Feature Extension of Gut Microbiome Data for Deep Neural Network-Based Colorectal Cancer Classification
Mwenge Mulenga, Sameem Abdul Kareem, Aznul Qalid Md Sabri, Manjeevan Seera, Suresh Govind, Chandramathi Samudi, Saharuddin Bin Mohamad
IEEE Access.2021; 9: 23565. CrossRef
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Astghik Z. Pepoyan, Elya S. Pepoyan, Lilit Galstyan, Natalya A. Harutyunyan, Vardan V. Tsaturyan, Tamas Torok, Alexey M. Ermakov, Igor V. Popov, Richard Weeks, Michael L. Chikindas
Probiotics and Antimicrobial Proteins.2021; 13(5): 1306. CrossRef
Deep convolutional neural network: a novel approach for the detection of Aspergillus fungi via stereomicroscopy
Haozhong Ma, Jinshan Yang, Xiaolu Chen, Xinyu Jiang, Yimin Su, Shanlei Qiao, Guowei Zhong
Journal of Microbiology.2021; 59(6): 563. CrossRef
Key Technologies for Progressing Discovery of Microbiome-Based Medicines
Remy B. Young, Vanessa R. Marcelino, Michelle Chonwerawong, Emily L. Gulliver, Samuel C. Forster
Frontiers in Microbiology.2021;[Epub] CrossRef
Statistical and Machine Learning Techniques in Human Microbiome Studies: Contemporary Challenges and Solutions
Isabel Moreno-Indias, Leo Lahti, Miroslava Nedyalkova, Ilze Elbere, Gennady Roshchupkin, Muhamed Adilovic, Onder Aydemir, Burcu Bakir-Gungor, Enrique Carrillo-de Santa Pau, Domenica D’Elia, Mahesh S. Desai, Laurent Falquet, Aycan Gundogdu, Karel Hron, Tho
Frontiers in Microbiology.2021;[Epub] CrossRef
The potential for mitigation of methane emissions in ruminants through the application of metagenomics, metabolomics, and other -OMICS technologies
Victoria Asselstine, Stephanie Lam, Filippo Miglior, Luiz F Brito, Hannah Sweett, Leluo Guan, Sinead M Waters, Graham Plastow, Angela Cánovas
Journal of Animal Science.2021;[Epub] CrossRef
Omics-based microbiome analysis in microbial ecology: from sequences to information
Jang-Cheon Cho
Journal of Microbiology.2021; 59(3): 229. CrossRef
kernInt: A Kernel Framework for Integrating Supervised and Unsupervised Analyses in Spatio-Temporal Metagenomic Datasets
Elies Ramon, Lluís Belanche-Muñoz, Francesc Molist, Raquel Quintanilla, Miguel Perez-Enciso, Yuliaxis Ramayo-Caldas
Frontiers in Microbiology.2021;[Epub] CrossRef
Integrating Systems and Synthetic Biology to Understand and Engineer Microbiomes
Patrick A. Leggieri, Yiyi Liu, Madeline Hayes, Bryce Connors, Susanna Seppälä, Michelle A. O'Malley, Ophelia S. Venturelli
Annual Review of Biomedical Engineering.2021; 23(1): 169. CrossRef
Towards multi-label classification: Next step of machine learning for microbiome research
Shunyao Wu, Yuzhu Chen, Zhiruo Li, Jian Li, Fengyang Zhao, Xiaoquan Su
Computational and Structural Biotechnology Journal.2021; 19: 2742. CrossRef
User guides for biologists to learn computational methods
Dokyun Na
Journal of Microbiology.2020; 58(3): 173. CrossRef
Catalyzing Holistic Agriculture Innovation Through Industrial Biotechnology
Larry P. Walker, Douglas Buhler
Industrial Biotechnology.2020; 16(4): 189. CrossRef

Zur-regulated lipoprotein A contributes to the fitness of Acinetobacter baumannii: Eun Kyung Lee , Chul Hee Choi , Man Hwan Oh; J. Microbiol. 2020;58(1):67-77. Published online January 2, 2020; DOI: https://doi.org/10.1007/s12275-020-9531-7

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Abstract

Acinetobacter baumannii is a notorious nosocomial pathogen that commonly infects severely ill patients. Zinc (Zn) is essential to survive and adapt to different environment and host niches in A. baumannii. Of the Zinc uptake regulator (Zur)-regulated genes in A. baumannii, the A1S_3412 gene encoding a Zur-regulated lipoprotein A (ZrlA) is critical for cell envelope integrity and overcoming antibiotic exposure. This study investigated whether ZrlA contributes to the fitness of A. baumannii in vitro and in vivo using the wildtype A. baumannii ATCC 17978, ΔzrlA mutant, and zrlAcomplemented strains. The ΔzrlA mutant showed reduced biofilm formation, surface motility, and adherence to and invasion of epithelial cells compared to the wild-type strain. In a mouse pneumonia model, the ΔzrlA mutant showed significantly lower bacterial numbers in the blood than the wildtype strain. These virulence traits were restored in the zrlAcomplemented strain. Under static conditions, the expression of csuCDE, which are involved in the chaperone-usher pili assembly system, was significantly lower in the ΔzrlA mutant than in the wild-type strain. Moreover, the expression of the bfmR/S genes, which regulate the CsuA/BABCDE system, was significantly lower in the ΔzrlA mutant under static conditions than in the wild-type strain. Our results indicate that the zrlA gene plays a role in the fitness of A. baumannii by regulating the BfmR/S two-component system and subsequently the CsuA/BABCDE chaperone-usher pili assembly system, suggesting it as a potential target for anti-virulence strategies against A. baumannii.

Citations

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Estabraq Ali Maklef, Amal A. Kareem, Susan F. K. Al-Sudani
Medical Journal of Babylon.2024; 21(Suppl 2): S258. CrossRef
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Massimiliano Lucidi, Daniela Visaggio, Antonella Migliaccio, Giulia Capecchi, Paolo Visca, Francesco Imperi, Raffaele Zarrilli
Virulence.2024;[Epub] CrossRef
Characterization of the Zinc Uptake Repressor (Zur) from Acinetobacter baumannii
Minyong Kim, My Tra Le, Lixin Fan, Courtney Campbell, Sambuddha Sen, Daiana A. Capdevila, Timothy L. Stemmler, David P. Giedroc
Biochemistry.2024; 63(5): 660. CrossRef
Acinetobacter Metabolism in Infection and Antimicrobial Resistance
Xiaomei Ren, Lauren D. Palmer, Karen M. Ottemann
Infection and Immunity.2023;[Epub] CrossRef
A response regulator controls Acinetobacter baumannii virulence by acting as an indole receptor
Binbin Cui, Quan Guo, Xia Li, Shihao Song, Mingfang Wang, Gerun Wang, Aixin Yan, Jianuan Zhou, Yinyue Deng, Marenda Wilson-Pham
PNAS Nexus.2023;[Epub] CrossRef
The role of quorum sensing, biofilm formation, and iron acquisition as key virulence mechanisms in Acinetobacter baumannii and the corresponding anti-virulence strategies
Soffi Kei Kei Law, Hock Siew Tan
Microbiological Research.2022; 260: 127032. CrossRef
Carboxy-Terminal Processing Protease Controls Production of Outer Membrane Vesicles and Biofilm in Acinetobacter baumannii
Rakesh Roy, Ren-In You, Chan-Hua Chang, Chiou-Ying Yang, Nien-Tsung Lin
Microorganisms.2021; 9(6): 1336. CrossRef
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Kyeongmin Kim, Maidul Islam, Hye-won Jung, Daejin Lim, Kwangsoo Kim, Sung-Gwon Lee, Chungoo Park, Je Chul Lee, Minsang Shin
Virulence.2021; 12(1): 2122. CrossRef
COG0523 proteins: a functionally diverse family of transition metal-regulated G3E P-loop GTP hydrolases from bacteria to man
Katherine A Edmonds, Matthew R Jordan, David P Giedroc
Metallomics.2021;[Epub] CrossRef
The role of Zur-regulated lipoprotein A in bacterial morphology, antimicrobial susceptibility, and production of outer membrane vesicles in Acinetobacter baumannii
Nayeong Kim, Hyo Jeong Kim, Man Hwan Oh, Se Yeon Kim, Mi Hyun Kim, Joo Hee Son, Seung Il Kim, Minsang Shin, Yoo Chul Lee, Je Chul Lee
BMC Microbiology.2021;[Epub] CrossRef
Insights Into Mechanisms of Biofilm Formation in Acinetobacter baumannii and Implications for Uropathogenesis
Jennifer M. Colquhoun, Philip N. Rather
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Structure of bacterial and eukaryote communities reflect in situ controls on community assembly in a high-alpine lake: Eli Michael S. Gendron , John L. Darcy , Katherinia Hell , Steven K. Schmidt; J. Microbiol. 2019;57(10):852-864. Published online August 3, 2019; DOI: https://doi.org/10.1007/s12275-019-8668-8

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Abstract

Recent work suggests that microbial community composition in high-elevation lakes is significantly influenced by microbes entering from upstream terrestrial and aquatic habitats. To test this idea, we conducted 18S and 16S rDNA surveys of microbial communities in a high-alpine lake in the Colorado Rocky Mountains. We compared the microbial community of the lake to water entering the lake and to uphill soils that drain into the lake. Utilizing hydrological and abiotic data, we identified potential factors controlling microbial diversity and community composition. Results show a diverse community entering the lake at the inlet with a strong resemblance to uphill terrestrial and aquatic communities. In contrast, the lake communities (water column and outlet) showed significantly lower diversity and were significantly different from the inlet communities. Assumptions of neutral community assembly poorly predicted community differences between the inlet and lake, whereas “variable selection” and “dispersal limitation” were predicted to dominate. Similarly, the lake communities were correlated with discharge rate, indicating that longer hydraulic residence times limit dispersal, allowing selective pressures within the lake to structure communities. Sulfate and inorganic nitrogen and phosphorus concentrations correlated with community composition, indicating “bottom up” controls on lake community assembly. Furthermore, bacterial community composition was correlated with both zooplankton density and eukaryotic community composition, indicating biotic controls such as “top-down” interactions also contribute to community assembly in the lake. Taken together, these community analyses suggest that deterministic biotic and abiotic selection within the lake coupled with dispersal limitation structures the microbial communities in Green Lake 4.

Citations

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Unraveling the distribution pattern and driving forces of soil microorganisms under geographic barriers
Gu Rao, Wen-Long Song, Shu-Zhen Yan, Shuang-Lin Chen, John R. Spear
Applied and Environmental Microbiology.2024;[Epub] CrossRef
The nature of microbial diversity and assembly in the Nebraska Sandhills depends on organismal identity and habitat type
Kaitlin Gattoni, Eli M. S. Gendron, J. Parr McQueen, Kirsten Powers, Thomas O. Powers, Mary J. Harner, Jessica R. Corman, Dorota L. Porazinska
Community Ecology.2024;[Epub] CrossRef
Lakes-scale pattern of eukaryotic phytoplankton diversity and assembly process shaped by electrical conductivity in central Qinghai-Tibet Plateau
Huan Zhu, Xiong Xiong, Benwen Liu, Guoxiang Liu
FEMS Microbiology Ecology.2024;[Epub] CrossRef
Free-Living and Particle-Associated Microbial Communities of Lake Baikal Differ by Season and Nutrient Intake
Maria Bashenkhaeva, Yelena Yeletskaya, Irina Tomberg, Artyom Marchenkov, Lubov Titova, Yuri Galachyants
Diversity.2023; 15(4): 572. CrossRef
Conservation tillage and moderate nitrogen application changed the composition, assembly pattern and interaction network of abundant and rare microbial community on straw surface
Houping Zhang, Yuanpeng Zhu, Chaoyang Yu, Yuze Li, Mei Long, Wei Li, Yuncheng Liao, Weiyan Wang, Xiaoxia Wen
Applied Soil Ecology.2023; 191: 105060. CrossRef
Sediment sulfate content determines assembly processes and network stability of bacteria communities of coastal land-based shrimp aquaculture ponds
Lianzuan Wu, Ping Yang, Linhai Zhang, Liangjuan Luo, Yan Hong, Wanyi Zhu, Lidi Zheng, Guanghui Zhao, Chuan Tong, Josep Peñuelas
Aquaculture.2023; 563: 738953. CrossRef
Microbial predators form a new supergroup of eukaryotes
Denis V. Tikhonenkov, Kirill V. Mikhailov, Ryan M. R. Gawryluk, Artem O. Belyaev, Varsha Mathur, Sergey A. Karpov, Dmitry G. Zagumyonnyi, Anastasia S. Borodina, Kristina I. Prokina, Alexander P. Mylnikov, Vladimir V. Aleoshin, Patrick J. Keeling
Nature.2022; 612(7941): 714. CrossRef
Crossing Treeline: Bacterioplankton Communities of Alpine and Subalpine Rocky Mountain Lakes
Kim Vincent, Hannah Holland-Moritz, Adam J. Solon, Eli M. S. Gendron, Steven K. Schmidt
Frontiers in Microbiology.2022;[Epub] CrossRef
Community Assembly and Co-occurrence Patterns Underlying the Core and Satellite Bacterial Sub-communities in the Tibetan Lakes
Qi Yan, Jianming Deng, Feng Wang, Yongqin Liu, Keshao Liu
Frontiers in Microbiology.2021;[Epub] CrossRef
Microbial community and abiotic effects on aquatic bacterial communities in north temperate lakes
Javad Sadeghi, Subba Rao Chaganti, Abdolrazagh Hashemi Shahraki, Daniel D. Heath
Science of The Total Environment.2021; 781: 146771. CrossRef
Evidence for phosphorus limitation in high-elevation unvegetated soils, Niwot Ridge, Colorado
Clifton P. Bueno de Mesquita, Laurel M. Brigham, Pacifica Sommers, Dorota L. Porazinska, Emily C. Farrer, John L. Darcy, Katharine N. Suding, Steven K. Schmidt
Biogeochemistry.2020; 147(1): 1. CrossRef

Assembly mechanisms of soil bacterial communities in subalpine coniferous forests on the Loess Plateau, China: Pengyu Zhao , Jinxian Liu , Tong Jia , Zhengming Luo , Cui Li , Baofeng Chai; J. Microbiol. 2019;57(6):461-469. Published online May 27, 2019; DOI: https://doi.org/10.1007/s12275-019-8373-7

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Abstract

Microbial community assembly is affected by trade-offs between deterministic and stochastic processes. However, the mechanisms underlying the relative influences of the two processes remain elusive. This knowledge gap limits our ability to understand the effects of community assembly processes on microbial community structures and functions. To better understand community assembly mechanisms, the community dynamics of bacterial ecological groups were investigated based on niche breadths in 23 soil plots from subalpine coniferous forests on the Loess Plateau in Shanxi, China. Here, the overall community was divided into the ecological groups that corresponded to habitat generalists, ‘other taxa’ and specialists. Redundancy analysis based on Bray-Curtis distances (db-RDA) and multiple regression tree (MRT) analysis indicated that soil organic carbon (SOC) was a general descriptor that encompassed the environmental gradients by which the communities responded to, because it can explain more significant variations in community diversity patterns. The three ecological groups exhibited different niche optima and degrees of specialization (i.e., niche breadths) along the SOC gradient, suggesting the presence of a gradient in tolerance for environmental heterogeneity. The inferred community assembly processes varied along the SOC gradient, wherein a transition was observed from homogenizing dispersal to variable selection that reflects increasing deterministic processes. Moreover, the ecological groups were inferred to perform different community functions that varied with community composition, structure. In conclusion, these results contribute to our understanding of the trade-offs between community assembly mechanisms and the responses of community structure and function to environmental gradients.

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Crystal structure and modeling of the tetrahedral intermediate state of methylmalonate-semialdehyde dehydrogenase (MMSDH) from Oceanimonas doudoroffii: Hackwon Do , Chang Woo Lee , Sung Gu Lee , Hara Kang , Chul Min Park , Hak Jun Kim , Hyun Park , HaJeung Park , Jun Hyuck Lee; J. Microbiol. 2016;54(2):114-121. Published online February 2, 2016; DOI: https://doi.org/10.1007/s12275-016-5549-2

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Abstract

The gene product of dddC (Uniprot code G5CZI2), from the Gram-negative marine bacterium Oceanimonas doudoroffii, is a methylmalonate-semialdehyde dehydrogenase (OdoMMSDH) enzyme. MMSDH is a member of the aldehyde dehydrogenase superfamily, and it catalyzes the NADdependent decarboxylation of methylmalonate semialdehyde to propionyl-CoA. We determined the crystal structure of OdoMMSDH at 2.9 Å resolution. Among the twelve molecules in the asymmetric unit, six subunits complexed with NAD, which was carried along the protein purification steps. OdoMMSDH exists as a stable homodimer in solution; each subunit consists of three distinct domains: an NAD-binding domain, a catalytic domain, and an oligomerization domain. Computational modeling studies of the OdoMMSDH structure revealed key residues important for substrate recognition and tetrahedral intermediate stabilization. Two basic residues (Arg103 and Arg279) and six hydrophobic residues (Phe150, Met153, Val154, Trp157, Met281, and Phe449) were found to be important for tetrahedral intermediate binding. Modeling data also suggested that the backbone amide of Cys280 and the side chain amine of Asn149 function as the oxyanion hole during the enzymatic reaction. Our results provide useful insights into the substrate recognition site residues and catalytic mechanism of OdoMMSDH.

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Abstract

An endophyte (PC27-5) was isolated from stem tissue of Western hemlock (Tsuga heterophylla) in a Pacific Northwest temperate rainforest. Phylogenetic analyses, based on ITS- 5.8S rDNA and 18S rDNA sequence data, combined with cultural and morphological analysis showed that endophyte PC27-5 exhibited all characteristics of a fungus identical to Coniochaeta velutina. Furthermore, wide spectrum antimycotics were produced by this endophyte that were active against such plant pathogens as Sclerotinia sclerotiorum, Pythium ultimum, and Verticillium dahliae and lethal to Phythophthora cinnamomi, Pythium ultimum, and Phytophthora palmivora in plate tests. The bioactive components were purified through organic solvent extraction, followed by silica column chromatography, and finally preparative HPLC. The minimum inhibitory concentration of the active fraction to Pythium ultimum, which was gained from preparative HPLC, was 11 ?/ml. UPLC-HRMS analysis showed there were two similar components in the antimycotic fraction. Their molecular formulae were established as C30H22O11 (compound I) and C30H22O10 (compound II) respectively, and preliminary spectral results indicate that they are anthroquinone glycosides. Other non ?biologically active compounds were identified in culture fluids of this fungus by spectral means as emodin and chrysophanol - anthroquinone derivatives. This is the first report that Coniochaeta velutina as an endophyte produces bioactive antifungal components.

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