scholarly journals Discovering Novel Antimicrobial Peptides in Generative Adversarial Network

2021 ◽  
Author(s):  
Tzu-Tang Lin ◽  
Li-Yen Yang ◽  
Ching-Tien Wang ◽  
Ga-Wen Lai ◽  
Chi-Fong Ko ◽  
...  
Keyword(s):  
Antimicrobial Peptides ◽  
Antibacterial Activities ◽  
Resistant Bacteria ◽  
Antibacterial Effects ◽  
Generative Adversarial Network ◽  
Antibiotic Resistant ◽  
Adversarial Network ◽  
Carbapenem Resistant ◽  
Disk Diffusion Testing

Due to the growing number of clinical antibiotic resistance cases in recent years, novel antimicrobial peptides (AMPs) can become ideal for next-generation antibiotics. This study trained a deep convolutional generative adversarial network (GAN) with known AMPs to generate novel AMP candidates. The quality of the GAN-designed peptides was evaluated in silico, and eight of them named GAN-pep 1~8 were chosen to be synthesized for further experiments. Disk diffusion testing and minimum inhibitory concentration (MIC) determination were used to determine the antibacterial effects of the synthesized GAN-designed peptides. Seven out of the eight synthesized GAN-designed peptides showed antibacterial activities. Additionally, GAN-pep 3 and GAN-pep 8 had a broad spectrum of antibacterial effects. Both of them were also effective against antibiotic-resistant bacteria strains such as methicillin-resistant Staphylococcus aureus (S. aureus) and carbapenem-resistant Pseudomonas aeruginosa (P. aeruginosa). GAN-pep 3, the most promising GAN-designed peptide candidate, had low MICs against all the tested bacteria.

scholarly journals Boosting Synergistic Effects of Short Antimicrobial Peptides With Conventional Antibiotics Against Resistant Bacteria

2021 ◽  
Vol 12 ◽  
Author(s):  
Chih-Lung Wu ◽  
Kuang-Li Peng ◽  
Bak-Sau Yip ◽  
Ya-Han Chih ◽  
Jya-Wei Cheng
Keyword(s):  
Antimicrobial Peptides ◽  
Synergistic Effects ◽  
Antibacterial Activities ◽  
Resistant Bacteria ◽  
Bacterial Strains ◽  
Antibiotic Resistant ◽  
C Terminus ◽  
Global Spread ◽  
Synergistic Mechanism ◽  
Conventional Antibiotics

The global spread of antibiotic-resistant infections has meant that there is an urgent need to develop new antimicrobial alternatives. In this study, we developed a strategy to boost and/or synergize the activity of conventional antibiotics by combination with antimicrobial peptides tagged with the bulky non-natural amino acid β-naphthylalanine (Nal) to their N- or C-terminus. A checkerboard method was used to evaluate synergistic effects of the parent peptide and the Nal-tagged peptides. Moreover, boron-dipyrro-methene labeled vancomycin was used to characterize the synergistic mechanism of action between the peptides and vancomycin on the bacterial strains. These Nal-tagged antimicrobial peptides also reduced the antibiotic-induced release of lipopolysaccharide from Gram-negative bacteria by more than 99.95%. Our results demonstrate that Nal-tagged peptides could help in developing antimicrobial peptides that not only have enhanced antibacterial activities but also increase the synergistic effects with conventional antibiotics against antibiotic-resistant bacteria.

Medicinal Plants: Antibacterial Effects and Chemical Composition of Essential Oil of Foeniculum vulgare

2017 ◽  
Vol 8 (01) ◽  
Author(s):  
Azadeh Foroughi ◽  
Pouya Pournaghi ◽  
Fariba Najafi ◽  
Akram Zangeneh ◽  
Mohammad Mahdi Zangeneh ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Medicinal Plants ◽  
Essential Oil ◽  
Antibacterial Properties ◽  
Screen Test ◽  
Antibacterial Activities ◽  
Gas Chromatography Mass Spectrometry ◽  
Resistant Bacteria ◽  
Antibacterial Effects ◽  
Foeniculum Vulgare

Medicinal plants are considered modern resources for producing agents that could act as alternatives to antibiotics in demeanor of antibiotic-resistant bacteria. The aim of the study was to evaluate the chemical composition and antibacterial activities of essential oil of Foeniculum vulgare (FV) against Pseudomonas aeruginosa and Bacillus subtilis. Gas chromatography mass spectrometry was done to specify chemical composion. As a screen test to detect antibacterial properties of the essential oil, agar disk and agar well diffusion methods were employed. Macrobroth tube test was performed to determinate MIC. The results indicated that the most substance found in FV essential oil was Trans-anethole (47.41 %), also the essential oil of FV with 0.007 g/ml concentration has prevented P. aeruginosa and with 0.002 g/ml concentration has prevented B. subtilis from the growth. Thus, the research represents the antibacterial effects of the medical herb on test P. aeruginosa and B. subtilis. We believe that the article provide support to the antibacterial properties of the essential oil. The results indicate the fact that the essential oil from the plant can be useful as medicinal or preservatives composition.

Optimizing the quality of Fourier single-pixel imaging via generative adversarial network

Optik ◽  
2021 ◽  
Vol 227 ◽  
pp. 166060
Author(s):  
Yangdi Hu ◽  
Zhengdong Cheng ◽  
Xiaochun Fan ◽  
Zhenyu Liang ◽  
Xiang Zhai
Keyword(s):  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Single Pixel

scholarly journals Prevalence of Antibiotic-Resistant Bacteria ESKAPE among Healthy People Estimated by Monitoring of Municipal Wastewater

Antibiotics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 495
Author(s):  
Masateru Nishiyama ◽  
Susan Praise ◽  
Keiichi Tsurumaki ◽  
Hiroaki Baba ◽  
Hajime Kanamori ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
General Population ◽  
Municipal Wastewater ◽  
Treatment Plant ◽  
Multidrug Resistant ◽  
Resistant Bacteria ◽  
Municipal Wastewater Treatment ◽  
Antibiotic Resistant ◽  
Carbapenem Resistant ◽  
Wastewater Samples

There is increasing attention toward factors that potentially contribute to antibiotic resistance (AR), as well as an interest in exploring the emergence and occurrence of antibiotic resistance bacteria (ARB). We monitored six ARBs that cause hospital outbreaks in wastewater influent to highlight the presence of these ARBs in the general population. We analyzed wastewater samples from a municipal wastewater treatment plant (MWWTP) and hospital wastewater (HW) for six species of ARB: Carbapenem-resistant Enterobacteria (CARBA), extended-spectrum β-lactamase producing Enterobacteria (ESBL), multidrug-resistant Acinetobacter (MDRA), multidrug-resistant Pseudomonas aeruginosa (MDRP), methicillin-resistant Staphylococcus aureus (MRSA), and vancomycin-resistant Enterococci (VRE). We registered a high percentage of ARBs in MWWTP samples (>66%) for all ARBs except for MDRP, indicating a high prevalence in the population. Percentages in HW samples were low (<78%), and no VRE was detected throughout the study. CARBA and ESBL were detected in all wastewater samples, whereas MDRA and MRSA had a high abundance. This result demonstrated the functionality of using raw wastewater at MWWTP to monitor the presence and extent of ARB in healthy populations. This kind of surveillance will contribute to strengthening the efforts toward reducing ARBs through the detection of ARBs to which the general population is exposed.

scholarly journals Machine Learning for Dissimulating Reality

Proceedings ◽  
2021 ◽  
Vol 77 (1) ◽  
pp. 17
Author(s):  
Andrea Giussani
Keyword(s):  
Machine Learning ◽  
Language Processing ◽  
Huge Amount ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Technological Advances ◽  
Textual Data ◽  
Musical Scores ◽  
Mathematical Formulas

In the last decade, advances in statistical modeling and computer science have boosted the production of machine-produced contents in different fields: from language to image generation, the quality of the generated outputs is remarkably high, sometimes better than those produced by a human being. Modern technological advances such as OpenAI’s GPT-2 (and recently GPT-3) permit automated systems to dramatically alter reality with synthetic outputs so that humans are not able to distinguish the real copy from its counteracts. An example is given by an article entirely written by GPT-2, but many other examples exist. In the field of computer vision, Nvidia’s Generative Adversarial Network, commonly known as StyleGAN (Karras et al. 2018), has become the de facto reference point for the production of a huge amount of fake human face portraits; additionally, recent algorithms were developed to create both musical scores and mathematical formulas. This presentation aims to stimulate participants on the state-of-the-art results in this field: we will cover both GANs and language modeling with recent applications. The novelty here is that we apply a transformer-based machine learning technique, namely RoBerta (Liu et al. 2019), to the detection of human-produced versus machine-produced text concerning fake news detection. RoBerta is a recent algorithm that is based on the well-known Bidirectional Encoder Representations from Transformers algorithm, known as BERT (Devlin et al. 2018); this is a bi-directional transformer used for natural language processing developed by Google and pre-trained over a huge amount of unlabeled textual data to learn embeddings. We will then use these representations as an input of our classifier to detect real vs. machine-produced text. The application is demonstrated in the presentation.

Towards Accuracy Enhancement of Age Group Classification Using Generative Adversarial Networks

2021 ◽  
pp. 1-17
Author(s):  
Khaled ELKarazle ◽  
Valliappan Raman ◽  
Patrick Then
Keyword(s):  
Age Estimation ◽  
Super Resolution ◽  
Generative Adversarial Networks ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Adversarial Networks ◽  
Original Dataset ◽  
Age Group Classification ◽  
Facial Images

Age estimation models can be employed in many applications, including soft biometrics, content access control, targeted advertising, and many more. However, as some facial images are taken in unrestrained conditions, the quality relegates, which results in the loss of several essential ageing features. This study investigates how introducing a new layer of data processing based on a super-resolution generative adversarial network (SRGAN) model can influence the accuracy of age estimation by enhancing the quality of both the training and testing samples. Additionally, we introduce a novel convolutional neural network (CNN) classifier to distinguish between several age classes. We train one of our classifiers on a reconstructed version of the original dataset and compare its performance with an identical classifier trained on the original version of the same dataset. Our findings reveal that the classifier which trains on the reconstructed dataset produces better classification accuracy, opening the door for more research into building data-centric machine learning systems.

Aminoglycoside antibiotic resistance conferred by Hpa2 of MDR Acinetobacter baumannii: an unusual adaptation of a common histone acetyltransferase

2019 ◽  
Vol 476 (5) ◽  
pp. 795-808 ◽  
Author(s):  
Jyoti Singh Tomar ◽  
Rama Krishna Peddinti ◽  
Ramakrishna V. Hosur
Keyword(s):  
Acinetobacter Baumannii ◽  
Histone Acetyltransferase ◽  
Hydrophobic Interactions ◽  
Aminoglycoside Antibiotic ◽  
Aminoglycoside Antibiotics ◽  
Titration Calorimetry ◽  
Resistant Bacteria ◽  
Antibiotic Resistant ◽  
Carbapenem Resistant ◽  
Eskape Pathogens

AbstractAntibiotic-resistant bacteria pose the greatest threat to human health. Among the list of such bacteria released by WHO, carbapenem-resistant Acinetobacter baumannii, for which almost no treatment exists, tops the list. A. baumannii is one of the most troublesome ESKAPE pathogens and mechanisms that have facilitated its rise as a successful pathogen are not well studied. Efforts in this direction have resulted in the identification of Hpa2-Ab, an uncharacterized histone acetyltransferase enzyme of GNAT superfamily. Here, we show that Hpa2-Ab confers resistance against aminoglycoside antibiotics using Escherichia coli DH5α strains in which Hpa2 gene is expressed. Resistivity for aminoglycoside antibiotics is demonstrated with the help of CLSI-2010 and KB tests. Isothermal titration calorimetry, MALDI and acetylation assays indicate that conferred resistance is an outcome of evolved antibiotic acetylation capacity in this. Hpa2 is known to acetylate nuclear molecules; however, here it is found to cross its boundary and participate in other functions. An array of biochemical and biophysical techniques were also used to study this protein, which demonstrates that Hpa2-Ab is intrinsically oligomeric in nature, exists primarily as a dimer and its interface is mainly stabilized by hydrophobic interactions. Our work demonstrates an evolved survival strategy by A. baumannii and provides insights into the mechanism that facilitates it to rise as a successful pathogen.

scholarly journals Hypochlorite-Activated Fluorescence Emission and Antibacterial Activities of Imidazole Derivatives for Biological Applications

2021 ◽  
Vol 9 ◽  
Author(s):  
Thanh Chung Pham ◽  
Van-Nghia Nguyen ◽  
Yeonghwan Choi ◽  
Dongwon Kim ◽  
Ok-Sang Jung ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Staphylococcus Aureus ◽  
Stokes Shift ◽  
Fluorescence Emission ◽  
Antibacterial Activities ◽  
Resistant Bacteria ◽  
Antibiotic Resistant ◽  
Fluorogenic Probe ◽  
High Fluorescence

The ability to detect hypochlorite (HOCl/ClO−) in vivo is of great importance to identify and visualize infection. Here, we report the use of imidazoline-2-thione (R1SR2) probes, which act to both sense ClO− and kill bacteria. The N2C=S moieties can recognize ClO− among various typical reactive oxygen species (ROS) and turn into imidazolium moieties (R1IR2) via desulfurization. This was observed through UV–vis absorption and fluorescence emission spectroscopy, with a high fluorescence emission quantum yield (ՓF = 43–99%) and large Stokes shift (∆v∼115 nm). Furthermore, the DIM probe, which was prepared by treating the DSM probe with ClO−, also displayed antibacterial efficacy toward not only Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) but also methicillin-resistant Staphylococcus aureus (MRSA) and extended-spectrum ß-lactamase–producing Escherichia coli (ESBL-EC), that is, antibiotic-resistant bacteria. These results suggest that the DSM probe has great potential to carry out the dual roles of a fluorogenic probe and killer of bacteria.

scholarly journals The Antibacterial Potential of Honeydew Honey Produced by Stingless Bee (Heterotrigona itama) against Antibiotic Resistant Bacteria

Antibiotics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 871
Author(s):  
Wen-Jie Ng ◽  
Nam-Weng Sit ◽  
Peter Aun-Chuan Ooi ◽  
Kah-Yaw Ee ◽  
Tuck-Meng Lim
Keyword(s):  
Honey Bee ◽  
Pathogenic Bacteria ◽  
Apis Cerana ◽  
Stingless Bee ◽  
Morphological Alteration ◽  
Resistant Bacteria ◽  
Antibacterial Effects ◽  
Electron Microscopic ◽  
Antibiotic Resistant ◽  
E Coli

Scientific studies about the antibacterial effects of honeydew honey produced by the stingless bee are very limited. In this study, the antibacterial activities of 46 blossom and honeydew honeys produced by both honey bees and stingless bees were evaluated and compared. All bacterial isolates showed varying degrees of susceptibility to blossom and honeydew honeys produced by the honey bee (Apis cerana) and stingless bee (Heterotrigona itama and Geniotrigona thoracica) in agar-well diffusion. All stingless bee honeys managed to inhibit all the isolates but only four out of 23 honey bee honeys achieved that. In comparison with Staphylococcus aureus, Escherichia coli was found to be more susceptible to the antibacterial effects of honey. Bactericidal effects of stingless bee honeys on E. coli were determined with the measurement of endotoxins released due to cell lysis. Based on the outcomes, the greatest antibacterial effects were observed in honeydew honey produced by H. itama. Scanning electron microscopic images revealed the morphological alteration and destruction of E. coli due to the action of this honey. The combination of this honey with antibiotics showed synergistic inhibitory effects on E. coli clinical isolates. This study revealed that honeydew honey produced by H. itama stingless bee has promising antibacterial activity against pathogenic bacteria, including antibiotic resistant strains.

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