Potential of FTIR-Spectroscopy for Drugs Screening against Helicobacter pylori

Bridging the gap between target-based and phenotypic-based drug discovery

INTRODUCTION

The unparalleled progress in science of the last decades has brought a better understanding of the molecular mechanisms of diseases. This promoted drug discovery processes based on a target approach. However, despite the high promises associated, a critical decrease in the number of first-in-class drugs has been observed.

AREAS COVERED

This review analyses the challenges, advances, and opportunities associated with the main strategies of the drug discovery process, i.e. based on a rational target approach and on an empirical phenotypic approach. This review also evaluates how the gap between these two crossroads can be bridged toward a more efficient drug discovery process.

EXPERT OPINION

The critical lack of knowledge of the complex biological networks is leading to targets not relevant for the clinical context or to drugs that present undesired adverse effects. The phenotypic systems designed by considering available molecular mechanisms can mitigate these knowledge gaps. Associated with the expansion of the chemical space and other technologies, these designs can lead to more efficient drug discoveries. Technological and scientific knowledge should also be applied to identify, as early as possible, both drug targets and mechanisms of action, leading to a more efficient drug discovery pipeline.

Enhancing Bioactive Compound Classification through the Synergy of Fourier-Transform Infrared Spectroscopy and Advanced Machine Learning Methods

Bacterial infections and resistance to antibiotic drugs represent the highest challenges to public health. The search for new and promising compounds with anti-bacterial activity is a very urgent matter. To promote the development of platforms enabling the discovery of compounds with anti-bacterial activity, Fourier-Transform Mid-Infrared (FT-MIR) spectroscopy coupled with machine learning algorithms was used to predict the impact of compounds extracted from Cynara cardunculus against Escherichia coli. According to the plant tissues (seeds, dry and fresh leaves, and flowers) and the solvents used (ethanol, methanol, acetone, ethyl acetate, and water), compounds with different compositions concerning the phenol content and antioxidant and antimicrobial activities were obtained. A principal component analysis of the spectra allowed us to discriminate compounds that inhibited E. coli growth according to the conventional assay. The supervised classification models enabled the prediction of the compounds' impact on E. coli growth, showing the following values for accuracy: 94% for partial least squares-discriminant analysis; 89% for support vector machine; 72% for k-nearest neighbors; and 100% for a backpropagation network. According to the results, the integration of FT-MIR spectroscopy with machine learning presents a high potential to promote the discovery of new compounds with antibacterial activity, thereby streamlining the drug exploratory process.

Recognition of breast cancer subtypes using FTIR hyperspectral data

Fourier-transform infrared spectroscopy (FTIR) is a powerful, non-destructive, highly sensitive and a promising analytical technique to provide spectrochemical signatures of biological samples, where markers like carbohydrates, proteins, and phosphate groups of DNA can be recognized in biological micro-environment. However, method of measurements of large cells need an excessive time to achieve high quality images, making its clinical use difficult due to speed of data-acquisition and lack of optimized computational procedures. To address such challenges, Machine Learning (ML) based technologies can assist to assess an accurate prognostication of breast cancer (BC) subtypes with high performance. Here, we applied FTIR spectroscopy to identify breast cancer subtypes in order to differentiate between luminal (BT474) and non-luminal (SKBR3) molecular subtypes. For this reason, we tested multivariate classification technique to extract feature information employing three-dimension (3D)-discriminant analysis approach based on 3D-principle component analysis-linear discriminant analysis (3D-PCA-LDA) and 3D-principal component analysis-quadratic discriminant analysis (3D-PCA-QDA), showing an improvement in sensitivity (98%), specificity (94%) and accuracy (98%) parameters compared to conventional unfolded methods. Our results evidence that 3D-PCA-LDA and 3D-PCA-QDA are potential tools for discriminant analysis of hyperspectral dataset to obtain superior classification assessment.

Milk phospholipids protect Bifidobacterium longum subsp. infantis during in vitro digestion and enhance polysaccharide production

Bifidobacterium longum subsp. infantis is associated with the gut microbiota of breast-fed infants. Bifidobacterium infantis promotes intestinal barrier and immune function through several proposed mechanisms, including interactions between their surface polysaccharides, the host, and other gut microorganisms. Dairy foods and ingredients are some of the most conspicuous food-based niches for this species and may provide benefits for their delivery and efficacy in the gut. Milk phospholipid (MPL)-rich ingredients have been increasingly recognized for their versatile benefits to health, including interactions with the gut microbiota and intestinal cells. Therefore, our objective was to investigate the capacity for MPL to promote survival of B. infantis during simulated digestion and to modulate bacterial polysaccharide production. To achieve these aims, B. infantis was incubated with or without 0.5% MPL in de Man, Rogosa, and Sharpe (MRS) media at 37°C under anaerobiosis. Survival across the oral, gastric, and intestinal phases using in vitro digestion was measured using plate count, along with adhesion to goblet-like intestinal cells. MPL increased B. infantis survival at the end of the intestinal phase by at least 7% and decreased adhesion to intestinal cells. The bacterial surface characteristics, which may contribute to these effects, were assessed by ζ-potential, changes in surface proteins using comparative proteomics, and production of bound polysaccharides. MPL decreased the surface charge of the bifidobacteria from -17 to -24 mV and increased a 50 kDa protein (3-fold) that appears to be involved in protection from stress. The production of bound polysaccharides was measured using FTIR, HPLC, and TEM imaging. These techniques all suggest an increase in bound polysaccharide production at least 1.7-fold in the presence of MPL. Our results show that MPL treatment increases B. infantis survival during simulated digestion, induces a stress resistance surface protein, and yields greater bound polysaccharide production, suggesting its use as a functional ingredient to enhance probiotic and postbiotic effects.

Epigenetic and Drug Response Modulation of Epigalocaten-In-3-Gallate in Staphylococcus aureus with Divergent Resistance Phenotypes

Healthcare-associated methicillin-resistant Staphylococcus aureus infections represent extremely high morbidity and mortality rates worldwide. We aimed to assess the antimicrobial potential and synergistic effect between Epigalocatenin-3-gallate (EGCG) and different antibiotics in S. aureus strains with divergent resistance phenotypes. EGCG exposure effects in epigenetic and drug resistance key modulators were also evaluated. S. aureus strains (n = 32) were isolated from infected patients in a Lisbon hospital. The identification of the S. aureus resistance phenotype was performed through automatized methods. The antibiotic synergistic assay was performed through disk diffusion according to EUCAST guidelines with co-exposure to EGCG (250, 100, 50 and 25 µg/mL). The bacteria’s molecular profile was assessed through FTIR spectroscopy. The transcriptional expression of OrfX, SpdC and WalKR was performed by using qRT-PCR. FTIR-spectroscopy analysis enabled the clear discrimination of MRSA/MSSA strains and the EGCG exposure effect in the bacteria’s molecular profiles. Divergent resistant phenotypes were associated with divergent transcriptional expression of the epigenetic modulator OrfX, particularly in MRSA strains, as well as the key drug response modulators SpdC and WalKR. These results clearly demonstrate that EGCG exposure alters the expression patterns of key epigenetic and drug response genes with associated divergent-resistant profiles, which supports its potential for antimicrobial treatment and/or therapeutic adjuvant against antibiotic-resistant microorganisms.

A Bioluminescence-Based Drug Screen Identifies Activities of Fexinidazole and Its Metabolites against Helicobacter pylori

Helicobacter pylori is responsible for a wide range of gastric diseases, including gastric cancer and gastritis. With half of the world’s population infected by H. pylori and the current standard of care associated with suboptimal outcomes, a search for more effective drugs is critical. To facilitate drug screening for H. pylori, we developed a microtiter plate-based compound screening method that is faster and can screen multiple compounds. We identified activities of fexinidazole and its sulfoxide and sulfone metabolites against H. pylori. Both fexinidazole and its metabolites exhibited equipotency against SS1, 60190, and G27 strains, which were about 3–6-fold more potent than the currently used metronidazole. We also determined the minimal inhibitory concentration (MIC) of metronidazole, fexinidazole, and its metabolites against these strains by a traditional agar plate-based method. While MIC values of fexinidazole and metronidazole were similar against all the strains, both sulfoxide and sulfone showed lower MIC values than metronidazole against SS1 and 60190. Given the recent FDA approval of fexinidazole, our data on the in vitro antibacterial activities of fexinidazole and its metabolites support further evaluation of this drug with the goal of producing an alternative nitro-based antimicrobial with good safety profiles for the treatment of H. pylori infection.

Antimicrobial evaluation of the Cynara cardunculus extract in Helicobacter pylori cells using mid-infrared spectroscopy and chemometric methods

AIMS

The treatment effectiveness of gastric diseases caused by the bacteria Helicobacter pylori is failing due to high resistance to some antibiotics. Consequently, it is urgent to develop an accurate methodology to screen new antimicrobial agents.

METHODS AND RESULTS

A preliminary assay, using both therapeutic-based antibiotics (clarithromycin and metronidazole), was conducted to optimize experimental conditions in terms of the sensibility of the Fourier Transform Mid-Infrared spectroscopy (MIR-FTIR) associated with chemometric methods. Principal component analysis was applied to understand how the Cynara extract concentration acts differentially against H. pylori bacteria. The partial least squares model, characterized by R² = 0.98, and root mean square error cross-validation, 0.011, was developed for the spectral regions (3600 - 2500 cm^-1 , and 2000 - 698 cm^-1 ).

CONCLUSIONS

MIR-FTIR spectroscopy associated with chemometric methods can be considered a suitable approach to discover and analyze the promissory antimicrobial agents based on the biomolecular changes observed according to the Cynara extract.

SIGNIFICANCE AND IMPACT OF THE STUDY

MIR-FTIR spectroscopy and chemometric methods allowed to register the biomolecular changes due to the potential antimicrobial drugs at reduced concentrations comparatively to the conventional assay based on an agar-dilution method, being considered a useful approach to develop a platform to discover new bioactive molecules, allowing to reduce time and costs related to the exploratory step.

Using least angular regression to model the antibacterial potential of metronidazole complexes

Imidazole has anti-inflammatory, antituberculotic, antimicrobial, antimycotic, antiviral, and antitumor properties in the human body, to name a few. Metronidazole [1-(2-Hydroxyethyl)-2-methyl-5-nitroimidazole] is a widely used antiprotozoan and antibacterial medication. Using fourier transform infrared spectroscopy, the current study models the antibacterial activity of already synthesised Metronidazole (MTZ) complexes (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$MTZ-Benz$$\end{document}MTZ-Benz, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$MTZ-Benz-Cu$$\end{document}MTZ-Benz-Cu, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$MTZ-Benz-Cu-Cl_2CHCOOH$$\end{document}MTZ-Benz-Cu-Cl2CHCOOH, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$MTZ$$\end{document}MTZ, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$MTZ-Cu$$\end{document}MTZ-Cu, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$MTZ-Cu-Cl_2CHCOOH$$\end{document}MTZ-Cu-Cl2CHCOOH, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$MTZ-Benz-Ag$$\end{document}MTZ-Benz-Ag, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$MTZ-Benz-Ag-Cl_2CHCOOH$$\end{document}MTZ-Benz-Ag-Cl2CHCOOH, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$MTZ-Ag$$\end{document}MTZ-Ag and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$MTZ-Ag-Cl_2CHCOOH$$\end{document}MTZ-Ag-Cl2CHCOOH) against E. coli, B. bronceptica, S. epidermidis, B. pumilus and S. aureus. To characterise the Metronidazole complexes for antibacterial activity against 05 microbes, the least angular regression and least absolute shrinkage selection operators were used. Asymmetric Least Squares was used to correct the spectrum baseline. Least angular regression outperforms cross-validated root mean square error in the fitted models. Using Least angular regression, influential wavelengths that explain the variation in antibacterial activity of Metronidazole complexes were identified and mapped against functional groups.