Characterization of gastric cells infection by diverse Helicobacter pylori strains through Fourier-transform infrared spectroscopy

A new methodology for a rapid and high-throughput comparison of molecular profiles and biological activity of phytoextracts

To robustly discover and explore phytocompounds, it is necessary to evaluate the interrelationships between the plant species, plant tissue, and the extraction process on the extract composition and to predict its cytotoxicity. The present work evaluated how Fourier Transform InfraRed spectroscopy can acquire the molecular profile of aqueous and ethanol-based extracts obtained from leaves, seeds, and flowers of Cynara Cardunculus, and ethanol-based extracts from Matricaria chamomilla flowers, as well the impact of these extracts on the viability of mammalian cells. The extract molecular profile enabled to predict the extraction yield, and how the plant species, plant tissue, and extraction process affected the extract's relative composition. The molecular profile obtained from the culture media of cells exposed to extracts enabled to capture its impact on cells metabolism, at a higher sensitivity than the conventional assay used to determine the cell viability. Furthermore, it was possible to detect specific impacts on the cell's metabolism according to plant species, plant tissue, and extraction process. Since spectra were acquired on small volumes of samples (25 µL), after a simple dehydration step, and based on a plate with 96 wells, the method can be applied in a rapid, simple, high-throughput, and economic mode, consequently promoting the discovery of phytocompounds.

Plasma versus Serum Analysis by FTIR Spectroscopy to Capture the Human Physiological State

Fourier Transform InfraRed spectroscopy of serum and plasma has been highly explored for medical diagnosis, due to its general simplicity, and high sensitivity and specificity. To evaluate the plasma and serum molecular fingerprint, as obtained by FTIR spectroscopy, to acquire the system metabolic state, serum and plasma spectra were compared to characterize the metabolic state of 30 human volunteers, between 90 days consumption of green tea extract rich in Epigallocatechin-3-gallate (EGCG). Both plasma and serum spectra enabled the high impact of EGCG consumption on the biofluid spectra to be observed, as analyzed by the spectra principal component analysis, hierarchical-cluster analysis, and univariate data analysis. Plasma spectra resulted in the prediction of EGCG consumption with a slightly higher specificity, accuracy, and precision, also pointing to a higher number of significant spectral bands that were different between the 90 days period. Despite this, the lipid regions of the serum spectra were more affected by EGCG consumption than the corresponding plasma spectra. Therefore, in general, if no specific compound analysis is highlighted, plasma is in general the advised biofluid to capture by FTIR spectroscopy the general metabolic state. If the lipid content of the biofluid is relevant, serum spectra could present some advantages over plasma spectra.

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.

A pH-Responsive Persistent Luminescence Nanozyme for Selective Imaging and Killing of Helicobacter pylori and Common Resistant Bacteria

Helicobacter pylori (H. pylori) infection is implicated in the etiology of many diseases. H. pylori eradication by antibiotic therapy is limited by the extreme acidic environment in the stomach, the undesired side effect of intestinal commensal bacteria, and the development of drug resistance. Here, we report a pH-responsive persistent luminescence (PL) nanozyme (MSPLNP-Au-CB) for in vivo imaging and inactivation of H. pylori. This PL nanozyme is composed of mesoporous silica (MS)-coated persistent luminescence nanoparticles (MSPLNP), Au nanoparticles (AuNP), and chitosan-benzeneboronic acid (CB), taking advantage of the long PL of PLNP to realize autofluorescence-free imaging, the pH-activated oxidase- and peroxidase-like nanozyme activity of AuNP, and the bacterial binding capacity of CB. The MSPLNP-Au-CB nanozyme can resist the corrosion of gastric acid and exhibit pH-activated dual nanozyme activity to catalyze bactericidal reactive oxygen species generation. This multifunctional nanozyme enables targeted imaging and activated deactivation of H. pylori under extreme gastric acid conditions as well as methicillin-resistant Staphylococcus aureus in common slightly acidic environments, while it has no side effects on the commensal bacteria and normal cells in normal physiological environments. This work provides a promising PL nanozyme platform for bioimaging and therapy of bacterial infection under harsh conditions.

Fast identification of off-target liabilities in early antibiotic discovery with Fourier-transform infrared spectroscopy

Structural modifications of known antibiotic scaffolds have kept the upper hand on resistance, but we are on the verge of not having antibiotics for many common infections. Mechanism-based discovery assays reveal novelty, exclude off-target liabilities, and guide lead optimization. For that, we developed a fast and automatable protocol using high-throughput Fourier-transform infrared spectroscopy (FTIRS). Metabolic fingerprints of Staphylococcus aureus and Escherichia coli exposed to 35 compounds, dissolved in dimethyl sulfoxide (DMSO) or water, were acquired. Our data analysis pipeline identified biomarkers of off-target effects, optimized spectral preprocessing, and identified the top-performing machine learning algorithms for off-target liabilities and mechanism of action (MOA) identification. Spectral bands with known biochemical associations more often yielded more significant biomarkers of off-target liabilities when bacteria were exposed to compounds dissolved in water than DMSO. Highly discriminative models distinguished compounds with predominant off-target effects from antibiotics with well-defined MOA (AUROC > 0.87, AUPR > 0.79, F1 > 0.81), and from the latter predicted their MOA (AUROC > 0.88, AUPR > 0.70, F1 > 0.70). The compound solvent did not affect predictive models. FTIRS is fast, simple, inexpensive, automatable, and highly effective at predicting MOA and off-target liabilities. As such, FTIRS mechanism-based screening assays can be applied for hit discovery and to guide lead optimization during the early stages of antibiotic discovery.

A new method to predict genotoxic effects based on serum molecular profile

It is critical to develop new methods to assess genotoxic effects in human biomonitoring since the conventional methods are usually laborious, time-consuming, and expensive. It is aimed to evaluate if the analysis of a drop of serum by Fourier Transform Infrared spectroscopy, allow to assess genotoxic effects in occupational exposure to cytostatic drugs in hospital professionals, as obtained by the lymphocyte cytokinesis-block micronucleus assay. It was considered peripheral blood from hospital professionals exposed to cytostatic drugs (n = 22) and from a non-exposed group (n = 36). It was observed that workers occupationally exposed presented a higher number of micronuclei (p < 0.05) in lymphocytes, in relation to the non-exposed group. The serum Fourier Transform Infrared spectra from exposed workers presented diverse different peaks (p < 0.01) in relation to the non-exposed group. The hierarchical cluster analysis of serum spectra separated serum samples of the exposed group from the non-exposed group with 61% sensitivity and 88% specificity. A support vector machine model of serum spectra enables to predict exposure with high accuracy (0.91), precision (0.89), sensitivity (0.86), F1 score (0.87) and AUC (0.96). Therefore, Fourier Transform Infrared spectroscopic analysis of a drop of serum enabled to predict in a rapid and simple mode the genotoxic effects of cytostatic drugs. The method presents therefore potential for high-dimension screening of exposure of genotoxic substances, due to its simplicity and rapid setup mode.

Technologies for High-Throughput Identification of Antibiotic Mechanism of Action

There are two main strategies for antibiotic discovery: target-based and phenotypic screening. The latter has been much more successful in delivering first-in-class antibiotics, despite the major bottleneck of delayed Mechanism-of-Action (MOA) identification. Although finding new antimicrobial compounds is a very challenging task, identifying their MOA has proven equally challenging. MOA identification is important because it is a great facilitator of lead optimization and improves the chances of commercialization. Moreover, the ability to rapidly detect MOA could enable a shift from an activity-based discovery paradigm towards a mechanism-based approach. This would allow to probe the grey chemical matter, an underexplored source of structural novelty. In this study we review techniques with throughput suitable to screen large libraries and sufficient sensitivity to distinguish MOA. In particular, the techniques used in chemical genetics (e.g., based on overexpression and knockout/knockdown collections), promoter-reporter libraries, transcriptomics (e.g., using microarrays and RNA sequencing), proteomics (e.g., either gel-based or gel-free techniques), metabolomics (e.g., resourcing to nuclear magnetic resonance or mass spectrometry techniques), bacterial cytological profiling, and vibrational spectroscopy (e.g., Fourier-transform infrared or Raman scattering spectroscopy) were discussed. Ultimately, new and reinvigorated phenotypic assays bring renewed hope in the discovery of a new generation of antibiotics.

FTIR microspectroscopic investigation of Lactobacillus paracasei apoptosis induced by cisplatin

Recent studies have shown that bacteria can also undergo apoptosis, which has gradually attracted researchers' attention. Cisplatin is a first-line drug to treat several cancers, but it can damage beneficial bacteria. Hence it is very important to explore the damage mechanism of cisplatin on beneficial bacteria. In this study, Lactobacillus paracasei, one kind of beneficial bacteria, was used as the model to investigate cisplatin damage. Conventional detection showed that cisplatin induced the apoptosis of Lactobacillus paracasei. Then Fourier transform infrared (FTIR) microspectroscopy was used to detect biomacromolecular changes in Lactobacillus paracasei apoptosis, and the following results were obtained: ① Second derivative IR spectra showed the changes of DNA, proteins, polysaccharides and lipids; ② Peak-area ratios suggested the changes of the protein and lipid structure and the decrease of DNA content; ③ Principal component analysis (PCA) further revealed significant changes in the DNA and protein content/structure. This study may have a new insight into the adverse reaction mechanism of cisplatin on Lactobacillus, moreover, it suggests that FTIR microspectroscopy may be a useful supplementary tool for investigating bacterial apoptosis.

Poly-3-hydroxybutyrate synthesis by different Azospirillum brasilense strains under varying nitrogen deficiency: A comparative in-situ FTIR spectroscopic analysis

Monitoring of poly-3-hydroxybutyrate accumulation and changes in its relative contents in biomass of the plant-growth-promoting bacteria Azospirillum brasilense (strains Sp7, Cd and Sp245) was performed during aerobic cultivation for 1 to 8 days at various initial concentrations of bound nitrogen (0.1 to 0.5 g∙L^-1 NH₄Cl) in the culture medium using in-situ transmission FTIR spectroscopy. A methodology has been proposed based on calculating band areas in FTIR spectra (instead of band intensities commonly used earlier) for determining relative contents of PHB in dry bacterial biomass, using the ester ν(C=O) band as a PHB marker (in the region 1750-1720 cm^-1) and amide II band of cellular proteins (at ca. 1540 cm^-1). Differences in PHB accumulation levels and their changes in the course of cultivation under various trophic stress for the three strains are discussed in relation to their different ecological niches which they occupy in the rhizosphere.

Fourier Transform Infrared (FTIR) Spectroscopic Analyses of Microbiological Samples and Biogenic Selenium Nanoparticles of Microbial Origin: Sample Preparation Effects

To demonstrate the importance of sample preparation used in Fourier transform infrared (FTIR) spectroscopy of microbiological materials, bacterial biomass samples with and without grinding and after different drying periods (1.5-23 h at 45 °C), as well as biogenic selenium nanoparticles (SeNPs; without washing and after one to three washing steps) were comparatively studied by transmission FTIR spectroscopy. For preparing bacterial biomass samples, Azospirillum brasilense Sp7 and A. baldaniorum Sp245 (earlier known as A. brasilense Sp245) were used. The SeNPs were obtained using A. brasilense Sp7 incubated with selenite. Grinding of the biomass samples was shown to result in slight downshifting of the bands related to cellular poly-3-hydroxybutyrate (PHB) present in the samples in small amounts (under ~10%), reflecting its partial crystallisation. Drying for 23 h was shown to give more reproducible FTIR spectra of bacterial samples. SeNPs were shown to contain capping layers of proteins, polysaccharides and lipids. The as-prepared SeNPs contained significant amounts of carboxylated components in their bioorganic capping, which appeared to be weakly bound and were largely removed after washing. Spectroscopic characteristics and changes induced by various sample preparation steps are discussed with regard to optimising sample treatment procedures for FTIR spectroscopic analyses of microbiological specimens.

Simultaneous elucidation of antibiotic mechanism of action and potency with high-throughput Fourier-transform infrared (FTIR) spectroscopy and machine learning

The low rate of discovery and rapid spread of resistant pathogens have made antibiotic discovery a worldwide priority. In cell-based screening, the mechanism of action (MOA) is identified after antimicrobial activity. This increases rediscovery, impairs low potency candidate detection, and does not guide lead optimization. In this study, high-throughput Fourier-transform infrared (FTIR) spectroscopy was used to discriminate the MOA of 14 antibiotics at pathway, class, and individual antibiotic level. For that, the optimal combinations and parametrizations of spectral preprocessing were selected with cross-validated partial least squares discriminant analysis, to which various machine learning algorithms were applied. This coherently resulted in very good accuracies, independently of the algorithms, and at all levels of MOA. Particularly, an ensemble of subspace discriminants predicted the known pathway (98.6%), antibiotic classes (100%), and individual antibiotics (97.8%) with exceptional accuracy, and similar results were obtained for simulated novel MOA. Even at very low concentrations (1 μg/mL) and growth inhibition (15%), over 70% pathway and class accuracy was achieved, suggesting FTIR spectroscopy can probe the grey chemical matter. Prediction of inhibitory effect was also examined, for which a squared exponential Gaussian process regression yielded a root mean square error of 0.33 and a R² of 0.92, indicating that metabolic alterations leading to growth inhibition are intrinsically reflected on FTIR spectra beyond cell density. KEY POINTS: • Antibiotic MOA and potency estimated with high-throughput FTIR spectroscopy • Sub-inhibitory MOA identification suggests ability to explore grey chemical matter • Data analysis optimization improved MOA identification at antibiotic level by 38.

Potential of FTIR-Spectroscopy for Drugs Screening against Helicobacter pylori

Helicobacter pylori colonizes the human stomach of half of the world's population. The infection if not treated, persists through life, leading to chronic gastric inflammation, that may progress to severe diseases as peptic ulcer, gastric adenocarcinoma, and mucosa-associated lymphoid tissue lymphoma. The first line of treatment, based on 7 to 21 days of two antibiotics associated with a proton pump inhibitor, is, however, already failing most due to patient non-compliance that leads to antibiotic resistance. It is, therefore, urgent to screen for new and more efficient antimicrobials against this bacterium. In this work, Fourier Transform Infrared (FTIR) spectroscopy was evaluated to screen new drugs against H. pylori, in rapid (between 1 to 6 h), and high-throughput mode and based on a microliter volume processes in relation to the agar dilution method. The reference H. pylori strains 26,695 and J99, were evaluated against a peptide-based antimicrobial and the clinical antibiotic clarithromycin, respectively. After optimization of the assay conditions, as the composition of the incubation mixture, the time of incubation, and spectral pre-processing, it was possible to reproducibly observe the effect of the drug on the bacterial molecular fingerprint as pointed by the spectra principal component analysis. The spectra, obtained from both reference strains, after its incubation with drugs concentrations lower than the MIC, presented peak ratios statistically different (p < 0.05) in relation to the bacteria incubated with drugs concentrations equal or higher to the MIC. It was possible to develop a partial least square regression model, enabling to predict from spectra of both bacteria strains, the drug concentration on the assay, with a high correlation coefficient between predicted and experimental data (0.91) and root square error of 40% of the minimum inhibitory concentration. All this points to the high potential of the technique for drug screening against this fastidious growth bacterium.

A Simple, Label-Free, and High-Throughput Method to Evaluate the Epigallocatechin-3-Gallate Impact in Plasma Molecular Profile

Epigallocatechin-3-gallate (EGCG), the major catechin present in green tea, presents diverse appealing biological activities, such as antioxidative, anti-inflammatory, antimicrobial, and antiviral activities, among others. The present work evaluated the impact in the molecular profile of human plasma from daily consumption of 225 mg of EGCG for 90 days. Plasma from peripheral blood was collected from 30 healthy human volunteers and analyzed by high-throughput Fourier transform infrared spectroscopy. To capture the biochemical information while minimizing the interference of physical phenomena, several combinations of spectra pre-processing methods were evaluated by principal component analysis. The pre-processing method that led to the best class separation, that is, between the plasma spectral data collected at the beginning and after the 90 days, was a combination of atmospheric correction with a second derivative spectra. A hierarchical cluster analysis of second derivative spectra also highlighted the fact that plasma acquired before EGCG consumption presented a distinct molecular profile after the 90 days of EGCG consumption. It was also possible by partial least squares regression discriminant analysis to correctly predict all unlabeled plasma samples (not used for model construction) at both timeframes. We observed that the similarity in composition among the plasma samples was higher in samples collected after EGCG consumption when compared with the samples taken prior to EGCG consumption. Diverse negative peaks of the normalized second derivative spectra, associated with lipid and protein regions, were significantly affected (p < 0.001) by EGCG consumption, according to the impact of EGCG consumption on the patients’ blood, low density and high density lipoproteins ratio. In conclusion, a single bolus dose of 225 mg of EGCG, ingested throughout a period of 90 days, drastically affected plasma molecular composition in all participants, which raises awareness regarding prolonged human exposure to EGCG. Because the analysis was conducted in a high-throughput, label-free, and economic analysis, it could be applied to high-dimension molecular epidemiological studies to further promote the understanding of the effect of bio-compound consumption mode and frequency.

Metabolic Fingerprinting with Fourier-Transform Infrared (FTIR) Spectroscopy: Towards a High-Throughput Screening Assay for Antibiotic Discovery and Mechanism-of-Action Elucidation

The discovery of antibiotics has been slowing to a halt. Phenotypic screening is once again at the forefront of antibiotic discovery, yet Mechanism-Of-Action (MOA) identification is still a major bottleneck. As such, methods capable of MOA elucidation coupled with the high-throughput screening of whole cells are required now more than ever, for which Fourier-Transform Infrared (FTIR) spectroscopy is a promising metabolic fingerprinting technique. A high-throughput whole-cell FTIR spectroscopy-based bioassay was developed to reveal the metabolic fingerprint induced by 15 antibiotics on the Escherichia coli metabolism. Cells were briefly exposed to four times the minimum inhibitory concentration and spectra were quickly acquired in the high-throughput mode. After preprocessing optimization, a partial least squares discriminant analysis and principal component analysis were conducted. The metabolic fingerprints obtained with FTIR spectroscopy were sufficiently specific to allow a clear distinction between different antibiotics, across three independent cultures, with either analysis algorithm. These fingerprints were coherent with the known MOA of all the antibiotics tested, which include examples that target the protein, DNA, RNA, and cell wall biosynthesis. Because FTIR spectroscopy acquires a holistic fingerprint of the effect of antibiotics on the cellular metabolism, it holds great potential to be used for high-throughput screening in antibiotic discovery and possibly towards a better understanding of the MOA of current antibiotics.