A phenotypic screening bioassay forEscherichia colistress and antibiotic responses based on Fourier‐transform infrared (FTIR) spectroscopy and multivariate analysis

Abstract

Aims To develop and optimize a Fourier‐transform infrared spectroscopy (FTIRS) phenotypic screening bioassay for stress responses, regarding the effect of nutrient content, bacterial growth phase and stress agent exposure time. Methods and Results A high‐throughput FTIRS bioassay was developed to distinguish the stress responses of Escherichia coli to sodium hydroxide, hydrochloric acid, sodium chloride, sodium hypochlorite and ethanol. Principal component analysis and hierarchical clustering were used to quantify the effect of each parameter on bioassay performance, namely its reproducibility and metabolic resolution. Bioassay performance varied greatly, ranging from poor to very good. Spectra were partitioned into biologically relevant regions to evaluate their contributions to bioassay performance, but further improvements were not observed. Bioassay optimization was validated against empirical parameters, which confirmed a closer representation of known mechanisms on the antibiotic‐induced stress responses. Conclusions The optimized bioassay used standard nutrient content, cells in the late‐stationary growth phase and a one‐shift exposure duration. Only the optimized bioassay adequately and reproducibly distinguished the E. coli stress and antibiotic responses. The absence of performance improvements using partitioned spectra indicated that stress responses are imprinted on the whole‐spectra metabolic signature. Significance and Impact of the Study Highly optimized FTIRS bioassay parameters are vital in capturing whole‐spectra metabolic signatures that can be used for satisfactory and reproducible phenotypic screening of stress and antibiotic responses.

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

“…For example, the bands of ≈1084 and ≈1245 cm −1 are usually attributed to symmetric and antisymmetric vibrations of phosphate bonds, respectively, which are present in diverse molecules such as DNA, RNA, phospholipids, and phosphorylated proteins [28,30]. Principal component analysis (PCA) is the most frequently used qualitative multivariate data analysis technique, as it allows for dimension reduction while enabling a search for data patterns, whereas other methods such as hierarchical clustering analysis (HCA) and supervised discriminant analysis (DA) [31,32], allow for the quantitative analysis and the development of prediction models, respectively.…”

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

“…FTIRS has been shown to detect antibiotic‐induced profiles that elucidate their MOA (Huleihel et al, 2009; Ribeiro da Cunha et al, 2019, 2020; Xuan Nguyen et al, 2017). In addition to the prediction of both known and simulated novel MOA, we have shown that FTIRS can be used to estimate potency and to probe the gray chemical matter (Ribeiro da Cunha et al, 2021).…”

“…Fourier‐transform infrared (FTIR) spectroscopy (FTIRS) is a technique with such characteristics that reflects the vibrational energy of molecular bonds after their interaction with infrared radiation, thereby revealing the atoms participating in said bonds, which in turn conveys the molecular composition of biological samples regarding nucleic acids, proteins, carbohydrates, lipids, phospholipids, among others (Ribeiro da Cunha et al, 2020). FTIRS conveys the molecular composition of samples with sufficient detail that it is suitable for metabolic fingerprinting in general (Goodacre et al, 2004), and specifically for identifying antibiotic‐induced profiles (Huleihel et al, 2009; Ribeiro da Cunha et al, 2019, 2020; Xuan Nguyen et al, 2017). Recently, FTIRS has also been shown to be sufficiently sensitive for screening animal DNA polymorphism (Gomes Rios et al, 2021) as well as for detecting single mtDNA deletions, which can enable the diagnosis of mitochondrial myopathy in clinical practice (Gervasoni et al, 2020).…”

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

“…They have been utilized to uncover the antimicrobial properties of novel extracts [19], differentiate the effects of various surfactants on E. coli cells [20], compare how E. coli responds to diverse stress conditions [21], and develop bioassays for toxicity testing in yeasts [22], among other applications. Compared to various omics techniques, FTIR spectroscopy offers valuable insights with less data intensity and minimal impact on metabolic sensitivity [23]. This underscores its significance and potential for further advancements in research across different fields.…”