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Predicting quorum sensing peptides using stacked generalization ensemble with gradient boosting based feature selection
Muthusaravanan Sivaramakrishnan , Rahul Suresh , Kannapiran Ponraj
J. Microbiol. 2022;60(7):756-765.   Published online June 22, 2022
DOI: https://doi.org/10.1007/s12275-022-2044-9
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  • 8 Web of Science
  • 7 Crossref
AbstractAbstract PDF
Bacteria exist in natural environments for most of their life as complex, heterogeneous, and multicellular aggregates. Under these circumstances, critical cell functions are controlled by several signaling molecules known as quorum sensing (QS) molecules. In Gram-positive bacteria, peptides are deployed as QS molecules. The development of antibodies against such QS molecules has been identified as a promising therapeutic intervention for bacterial control. Hence, the identification of QS peptides has received considerable attention. Availability of a fast and reliable predictive model to effectively identify QS peptides can help the existing high throughput experiments. In this study, a stacked generalization ensemble model with Gradient Boosting Machine (GBM)-based feature selection, namely EnsembleQS was developed to predict QS peptides with high accuracy. On selected GBM features (791D), the EnsembleQS outperformed finely tuned baseline classifiers and demonstrated robust performance, indicating the superiority of the model. The accuracy of EnsembleQS is 4% higher than those resulting from ensemble model on hybrid dataset. When evaluating an independent data set of 40 QS peptides, the EnsembleQS model showed an accuracy of 93.4% with Matthew’s Correlation Coefficient (MCC) and area under the ROC curve (AUC) values 􀁇􀁇of 0.91 and 0.951, respectively. These
results
suggest that EnsembleQS will be a useful computational framework for predicting QS peptides and will efficiently support proteomics research. The source code and all datasets used in this study are publicly available at https:// github.com/proteinexplorers/EnsembleQS.

Citations

Citations to this article as recorded by  
  • IQSPred-PLM: An Interpretable Quorum Sensing Peptides Prediction Model Based on Protein Language Model
    Yusen Su, Qingyang Guo, Taigang Liu
    Interdisciplinary Sciences: Computational Life Sciences.2025;[Epub]     CrossRef
  • Kernelized Fuzzy System for Predicting Therapeutic Peptides via Deep Stacked Encoder
    Xiaoyi Guo, Yijie Ding, Quan Zou
    IEEE Transactions on Computational Biology and Bioinformatics.2025; 22(4): 1494.     CrossRef
  • Revolutionizing physics: a comprehensive survey of machine learning applications
    Rahul Suresh, Hardik Bishnoi, Artem V. Kuklin, Atharva Parikh, Maxim Molokeev, R. Harinarayanan, Sarvesh Gharat, P. Hiba
    Frontiers in Physics.2024;[Epub]     CrossRef
  • DeepQSP: Identification of Quorum Sensing Peptides Through Neural Network Model
    Md. Ashikur Rahman, Md. Mamun Ali, Kawsar Ahmed, Imran Mahmud, Francis M. Bui, Li Chen, Santosh Kumar, Mohammad Ali Moni
    Results in Engineering.2024; 24: 102878.     CrossRef
  • Computational tools for exploring peptide-membrane interactions in gram-positive bacteria
    Shreya Kumar, Rex Devasahayam Arokia Balaya, Saptami Kanekar, Rajesh Raju, Thottethodi Subrahmanya Keshava Prasad, Richard K. Kandasamy
    Computational and Structural Biotechnology Journal.2023; 21: 1995.     CrossRef
  • DeepTPpred: A Deep Learning Approach With Matrix Factorization for Predicting Therapeutic Peptides by Integrating Length Information
    Zhen Cui, Si-Guo Wang, Ying He, Zhan-Heng Chen, Qin-Hu Zhang
    IEEE Journal of Biomedical and Health Informatics.2023; 27(9): 4611.     CrossRef
  • PSRQSP: An effective approach for the interpretable prediction of quorum sensing peptide using propensity score representation learning
    Phasit Charoenkwan, Pramote Chumnanpuen, Nalini Schaduangrat, Changmin Oh, Balachandran Manavalan, Watshara Shoombuatong
    Computers in Biology and Medicine.2023; 158: 106784.     CrossRef
Research Support, Non-U.S. Gov'ts
Providencia Isolates Carrying blaPER-1 and blaVIM-2 Genes: Biofilm-Forming Capacity and Biofilm Inhibitory Concentrations for Carbapenem Antibiotics
Jungmin Kim , Shukho Kim , Hee Woo Lee , Sung Min Kim , Sung Yong Seol
J. Microbiol. 2011;49(3):512-515.   Published online June 30, 2011
DOI: https://doi.org/10.1007/s12275-011-1221-z
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AbstractAbstract PDF
Multidrug-resistant clinical isolates of Providencia carrying blaPER-1 and blaVIM-2 were evaluated for the abilities to form biofilm and high biofilm forming capacity was demonstrated in them. Minimum biofilm inhibitory concentrations (MBICs), minimum biofilm eradication concentrations (MBECs), and minimum inhibitory concentrations (MICs) for imipenem and meropenem were also determined. In all tested strains, the MBICs were higher than the MICs for both drugs. Interestingly, the MBICs and the MBEC50 for meropenem were lower than those for imipenem in the isolates producing high amounts of biofilm, suggesting that meropenem is superior to imipenem in the growth inhibition and eradication of biofilm forming Providencia strains.
Acinetobacter baumannii Biofilms: Variations Among Strains and Correlations with Other Cell Properties
Christin N. McQueary , Luis A. Actis
J. Microbiol. 2011;49(2):243-250.   Published online May 3, 2011
DOI: https://doi.org/10.1007/s12275-011-0343-7
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  • 62 Scopus
AbstractAbstract PDF
Acinetobacter baumannii is an opportunistic pathogen that causes serious infections in humans by colonizing and persisting on surfaces normally found in hospital settings. The capacity of this pathogen to persist in these settings could be due to its ability to form biofilms on inanimate surfaces. This report shows that although the ATCC 19606T type strain and 8 different clinical isolates form biofilms, there are significant variations in the cell density and microscopic structures of these cell aggregates, with 3 of the isolates forming pellicles floating on the surface of stagnant broth cultures. PCR indicated that, like ATCC 19606T, all 8 clinical isolates harbor all the genetic components of the CsuA/BABCDE chaperone-usher pili assembly system, which is needed for biofilm formation on plastic. Pili detection in cells of all strains examined supports the presence and function of a pilus assembly system. However, only one of them produced the putative ATCC 19606T CsuA/B pilin subunit protein. Hydrophobicity tests and motility assays also showed significant variations among all tested strains and did not result in direct correlations between the biofilm phenotype and cell properties that could affect biofilm formation on abiotic surfaces. This lack of correlation among these 3 phenotypes may reflect some of the variations already reported with this pathogen, which may pose a challenge in the treatment of the infections this pathogen causes in humans using biofilm formation on abiotic surfaces as a target.
Inhibitory Effect of Lactobacillus reuteri on Periodontopathic and Cariogenic Bacteria
Mi-Sun Kang , Jong-Suk Oh , Hyun-Chul Lee , Hoi-Soon Lim , Seok-Woo Lee , Kyu-Ho Yang , Nam-Ki Choi , Seon-Mi Kim
J. Microbiol. 2011;49(2):193-199.   Published online May 3, 2011
DOI: https://doi.org/10.1007/s12275-011-0252-9
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  • 71 Crossref
AbstractAbstract PDF
The interaction between Lactobacillus reuteri, a probiotic bacterium, and oral pathogenic bacteria have not been studied adequately. This study examined the effects of L. reuteri on the proliferation of periodontopathic bacteria including Aggregatibacter actinomycetemcomitans, Fusobacterium nucleatum, Porphyromonas gingivalis, and Tannerella forsythia, and on the formation of Streptococcus mutans biofilms. Human-derived L. reuteri strains (KCTC 3594 and KCTC 3678) and rat-derived L. reuteri KCTC 3679 were used. All strains exhibited significant inhibitory effects on the growth of periodontopathic bacteria and the formation of S. mutans biofilms. These antibacterial activities of L. reuteri were attributed to the production of organic acids, hydrogen peroxide, and a bacteriocin-like compound. Reuterin, an antimicrobial factor, was produced only by L. reuteri KCTC 3594. In addition, L. reuteri inhibited the production of methyl mercaptan by F. nucleatum and P. gingivalis. Overall, these results suggest that L. reuteri may be useful as a probiotic agent for improving oral health.

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Journal Article
Screening-Level Assays for Potentially Human-Infectious Environmental Legionella spp.
Helen Y. Buse , Abby Brehm , Jorge W. Santo Domingo , Nicholas J. Ashbolt
J. Microbiol. 2011;49(2):200-207.   Published online May 3, 2011
DOI: https://doi.org/10.1007/s12275-011-0233-z
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AbstractAbstract PDF
In spite of the fact that various Legionella species are isolated from nonclinical water settings, there is no standard method to determine whether environmental legionellae may be infectious to humans. Here we provide a screening-level approach based on an in vivo murine (A/J mouse) model and three in vitro proliferation assays using Acanthamoeba polyphaga, and THP-1 human and J774 murine macrophage cell lines to identify potentially human-infectious legionellae. As an initial demonstration the infectivity potential of three clinical (Legionella pneumophila, L. longbeacheae, and L. micdadei) and three environmental (L. dumoffii, L. maceachernii, and L. sainthelensi) legionellae were evaluated. A/J mice were intranasally infected and by 6 h post infection (p.i.), there were significant bacterial titers in the lungs. L. pneumophila, L. dumoffii, and L. micdadei densities were higher than L. longbeacheae, L. maceacherni, and L. sainthelensi at 24 h p.i. However, only L. pneumophila and L. micdadei persisted in the lungs after 48 h, indicating that the other isolates were rapidly cleared. Results from the in vitro assays showed that only L. pneumophila significantly multiplied within A. polyphaga, THP-1 and J774 cells after 72 h, but lysis of any of the in vitro hosts also flagged the strains for potential concern (e.g. L. dumoffii and L. micdadei). The results demonstrate the value of using multiple approaches to assess the potential level of pathogenicity of Legionella strains isolated from different environmental matrices.

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Research Support, Non-U.S. Gov't
Antibacterial Characteristics of Curcuma xanthorrhiza Extract on Streptococcus mutans Biofilm
Jung-Eun Kim , Hee-Eun Kim , Jae-Kwan Hwang , Ho-Jeong Lee , Ho-Keun Kwon , Baek-Il Kim
J. Microbiol. 2008;46(2):228-232.   Published online June 11, 2008
DOI: https://doi.org/10.1007/s12275-007-0167-7
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AbstractAbstract PDF
This study evaluated the antibacterial effects of a natural Curcuma xanthorrhiza extract (Xan) on a Streptococcus mutans biofilm by examining the bactericidal activity, inhibition of acidogenesis and morphological alteration. Xan was obtained from the roots of a medicinal plant in Indonesia, which has shown selective <br><br>antibacterial effects on planktonic S. mutans. S. mutans biofilms were formed on slide glass over a 72 h period and treated with the following compounds for 5, 30, and 60 min: saline, 1% DMSO, 2 mg/ml chlorhexidine (CHX), and 0.1 mg/ml Xan. The Xan group exposed for 5 and 30 min showed significantly fewer colony forming units (CFU, 57.6 and 97.3%, respectively) than those exposed to 1% DMSO, the negative control group (P<0.05). These CFU were similar in number to those slides exposed to CHX, the positive control group. Xan showed similar bactericidal effect to that of CHX but the dose of Xan was one twentieth that of CHX. In addition, the biofilms treated with Xan and CHX maintained a neutral pH for 4 h, which indicates that Xan and CHX inhibit acid production. Scanning electron microscopy showed morphological changes in the cell wall and membrane of the Xan-treated biofilms; an uneven surface and a deformation in contour. Overall, natural Xan has strong bactericidal activity, inhibitory effects on acidogenesis, and alters the microstructure of S. mutans biofilm. In conclusion, Xan has potential in anti-S. mutans therapy for the prevention of dental caries.

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