Detection of Antimicrobial Resistance-Related Changes in Biochemical Composition of Staphylococcus aureus by Means of Atomic Force Microscopy-Infrared Spectroscopy

Identification of coumarin - benzimidazole hybrids as potential antibacterial agents: Synthesis, in vitro and in vivo biological assessment, and ADMET prediction

The direct-linked coumarin-benzimidazole hybrids, featuring aryl and n-butyl substituents at the N1-position of benzimidazole were synthesized through a Knoevenagel condensation reaction. This reaction involved the condensation of 1,2-diaminobenzene derivatives with coumarin-3-carboxylic acids in the presence of polyphosphoric acid (PPA) at 154 °C. The in vitro antibacterial potency of the hybrid molecules against different gram-positive and gram-negative bacterial strains led to the identification of the hybrids 6m and 6p with a MIC value of 6.25 μg/mL against a gram-negative bacterium, Klebsiella pneumonia ATCC 27736. Cell viability studies on THP-1 cells demonstrated that the compounds 6m and 6p were non-toxic at a concentration of 50 µM. Furthermore, in vivo efficacy studies using a murine neutropenic thigh infection model revealed that both compounds significantly reduced bacterial (Klebsiella pneumonia ATCC 27736) counts (more than 2 log) compared to the control group. Additionally, both compounds exhibited favorable physicochemical properties and drug-likeness characteristics. Consequently, these compounds hold promise as lead candidates for further development of effective antibacterial drugs.

An optical photothermal infrared investigation of lymph nodal metastases of oral squamous cell carcinoma

In this study, optical photothermal infrared (O-PTIR) spectroscopy combined with machine learning algorithms were used to evaluate 46 tissue cores of surgically resected cervical lymph nodes, some of which harboured oral squamous cell carcinoma nodal metastasis. The ratios obtained between O-PTIR chemical images at 1252 cm-1 and 1285 cm-1 were able to reveal morphological details from tissue samples that are comparable to the information achieved by a pathologist's interpretation of optical microscopy of haematoxylin and eosin (H&E) stained samples. Additionally, when used as input data for a hybrid convolutional neural network (CNN) and random forest (RF) analyses, these yielded sensitivities, specificities and precision of 98.6 ± 0.3%, 92 ± 4% and 94 ± 5%, respectively, and an area under receiver operator characteristic (AUC) of 94 ± 2%. Our findings show the potential of O-PTIR technology as a tool to study cancer on tissue samples.

An end-to-end approach for single-cell infrared absorption spectroscopy of bacterial inclusion bodies: from AFM-IR measurement to data interpretation of large sample sets

BACKGROUND

Inclusion bodies (IBs) are well-known subcellular structures in bacteria where protein aggregates are collected. Various methods have probed their structure, but single-cell spectroscopy remains challenging. Atomic Force Microscopy-based Infrared Spectroscopy (AFM-IR) is a novel technology with high potential for the characterisation of biomaterials such as IBs.

RESULTS

We present a detailed investigation using AFM-IR, revealing the substructure of IBs and their variation at the single-cell level, including a rigorous optimisation of data collection parameters and addressing issues such as laser power, pulse frequency, and sample drift. An analysis pipeline was developed tailored to AFM-IR image data, allowing high-throughput, label-free imaging of more than 3500 IBs in 12,000 bacterial cells. We examined IBs generated in Escherichia coli under different stress conditions. Dimensionality reduction analysis of the resulting spectra suggested distinct clustering of stress conditions, aligning with the nature and severity of the applied stresses. Correlation analyses revealed intricate relationships between the physical and morphological properties of IBs.

CONCLUSIONS

Our study highlights the power and limitations of AFM-IR, revealing structural heterogeneity within and between IBs. We show that it is possible to perform quantitative analyses of AFM-IR maps over a large collection of different samples and determine how to control for various technical artefacts.

Surface-enhanced Raman spectroscopy for comparison of biochemical profile of bacteriophage sensitive and resistant methicillin-resistant Staphylococcus aureus (MRSA) strains

Methicillin-resistant Staphylococcus aureus (MRSA) is gram positive bacteria and leading cause of a wide variety of diseases. It is a common cause of hospitalized and community-acquired infections. Development of increasing antibiotic-resistance by methicillin-resistant S. aureus (MRSA) strains demand to develop alternate novel therapies. Bacteriophages are now widely used as antibacterial therapies against antibiotic-resistant gram-positive pathogens. So, there is an urgent need to find fast detection techniques to point out phage susceptible and resistant strains of methicillin-resistant S. aureus (MRSA) bacteria. Samples of two separate strains of bacteria, S. aureus, in form of pellets and supernatant, were used for this purpose. Strain-I was resistant to phage, while the other (strain-II) was sensitive. Surface Enhanced Raman Spectroscopy (SERS) has detected significant biochemical changes in these bacterial strains of pellets and supernatants in the form of SERS spectral features. The protein portion of these two types of strains of methicillin-resistant S. aureus (MRSA) in their relevant pellets and supernatants is major distinguishing biomolecule as shown by their representative SERS spectral features. In addition, multivariate data analysis techniques such as principal component analysis (PCA) and a partial least squares-discriminant analysis (PLS-DA) were found to be helpful in identifying and characterizing various strains of S. aureus which are sensitive and resistant to bacteriophage with 100% specificity, 100% accuracy, and 99.8% sensitivity in case of SERS spectral data sets of bacterial cell pellets. Moreover, in case of supernatant samples, the results of PLS-DA model including 95.5% specificity, 96% sensitivity, and 96.5% accuracy are obtained.

Antimicrobial susceptibility testing using infrared attenuated total reflection (IR-ATR) spectroscopy to monitor metabolic activity

Fast and accurate detection of antimicrobial resistance in pathogens remains a challenge, and with the increase in antimicrobial resistance due to mis- and overuse of antibiotics, it has become an urgent public health problem. We demonstrate how infrared attenuated total reflection (IR-ATR) can be used as a simple method for assessment of bacterial susceptibility to antibiotics. This is achieved by monitoring the metabolic activities of bacterial cells via nutrient consumption and using this as an indicator of bacterial viability. Principal component analysis of the obtained spectra provides a tool for fast and simple discrimination of antimicrobial resistance in the acquired data. We demonstrate this concept using four bacterial strains and four different antibiotics, showing that the change in glucose concentration in the growth medium after 2 h, as monitored by IR-ATR, can be used as a spectroscopic diagnostic technique, to reduce detection time and to improve quality in the assessment of antimicrobial resistance in pathogens.

Photoinduced force microscopy as a novel method for the study of microbial nanostructures

A detailed comparison of the capabilities of electron microscopy and nano-infrared (IR) microscopy for imaging microbial nanostructures has been carried out for the first time. The surface sensitivity, chemical specificity, and non-destructive nature of spectroscopic mapping is shown to offer significant advantages over transmission electron microscopy (TEM) for the study of biological samples. As well as yielding important topographical information, the distribution of amides, lipids, and carbohydrates across cross-sections of bacterial (Escherichia coli, Staphylococcus aureus) and fungal (Candida albicans) cells was demonstrated using PiFM. The unique information derived from this new mode of spectroscopic mapping of the surface chemistry and biology of microbial cell walls and membranes, may provide new insights into fungal/bacterial cell function as well as having potential use in determining mechanisms of antimicrobial resistance, especially those targeting the cell wall.

Spectroscopic Identification of Bacteria Resistance to Antibiotics by Means of Absorption of Specific Biochemical Groups and Special Machine Learning Algorithm

FTIR (Fourier transform infrared spectroscopy) is one analytical technique of the absorption of infrared radiation. FTIR can also be used as a tool to characterize profiles of biomolecules in bacterial cells, which can be useful in differentiating different bacteria. Considering that different bacterial species have different molecular compositions, it will then result in unique FTIR spectra for each species and even bacterial strains. Having this important tool, here, we have developed a methodology aimed at refining the analysis and classification of the FTIR absorption spectra obtained from samples of Staphylococcus aureus, with the implementation of machine learning algorithms. In the first stage, the system conforming to four specified species groups, Control, Amoxicillin induced (AMO), Gentamicin induced (GEN), and Erythromycin induced (ERY), was analyzed. Then, in the second stage, five hidden samples were identified and correctly classified as with/without resistance to induced antibiotics. The total analyses were performed in three windows, Carbohydrates, Fatty Acids, and Proteins, of five hundred spectra. The protocol for acquiring the spectral data from the antibiotic-resistant bacteria via FTIR spectroscopy developed by Soares et al. was implemented here due to demonstrating high accuracy and sensitivity. The present study focuses on the prediction of antibiotic-induced samples through the implementation of the hierarchical cluster analysis (HCA), principal component analysis (PCA) algorithm, and calculation of confusion matrices (CMs) applied to the FTIR absorption spectra data. The data analysis process developed here has the main objective of obtaining knowledge about the intrinsic behavior of S. aureus samples within the analysis regions of the FTIR absorption spectra. The results yielded values with 0.7 to 1 accuracy and high values of sensitivity and specificity for the species identification in the CM calculations. Such results provide important information on antibiotic resistance in samples of S. aureus bacteria for potential application in the detection of antibiotic resistance in clinical use.

High-Throughput Antimicrobial Susceptibility Testing of Escherichia coli by Wide-Field Mid-Infrared Photothermal Imaging of Protein Synthesis

Antimicrobial resistance poses great threats to global health and economics. Current gold-standard antimicrobial susceptibility testing (AST) requires extensive culture time (36-72 h) to determine susceptibility. There is an urgent need for rapid AST methods to slow down antimicrobial resistance. Here, we present a rapid AST method based on wide-field mid-infrared photothermal imaging of protein synthesis from ¹³C-glucose in Escherichia coli. Our wide-field approach achieved metabolic imaging for hundreds of bacteria at the single-cell resolution within seconds. The perturbed microbial protein synthesis can be probed within 1 h after antibiotic treatment in E. coli cells. The susceptibility of antibiotics with various mechanisms of action has been probed through monitoring protein synthesis, which promises great potential of the proposed platform toward clinical translation.

Electrochemical Quantification of Tobramycin Retention in Pseudomonas aeruginosa as Antimicrobial Susceptibility Indicator

The emergence and spread of bacterial resistance to antibiotics has developed into one of the most challenging threats to public health. Antibiotic susceptibility tests (ASTs) for bacterial infections are now essential, because they provide guidance for physicians in the selection of antibiotics, to which bacteria will respond. Most current AST methods require long periods of time, because of bacterial growth and incubation, leading to a prolonged and overuse of broad-spectrum antibiotics. Thus, there is a growing demand for methods and technologies that enable rapid antibiotic susceptibility assessment. Due to advantages related to cost-effectiveness, rapid response time and high sensitivity, electrochemical detection methods are promising analytical tools that can successfully quantify antibiotic uptake and retention in clinically relevant bacterial strains. This study presents the electroanalytical quantification of tobramycin (TOB) retention in susceptible and resistant bacterial strains of Pseudomonas aeruginosa. The electrochemical behavior of TOB was characterized by voltammetry, identifying redox potentials, the current dependence on pH conditions, and the detection limit at unmodified glassy carbon electrodes. The presented methodology was able to distinguish between susceptible and resistant bacterial strains, and is also capable of identifying varying degrees of resistance against TOB. The presented approach detects the immediate interaction of bacteria with an antibiotic, without the need of complex and cost-intense equipment related to genomic testing methods.

Determination of Klebsiella pneumoniae Susceptibility to Antibiotics Using Infrared Microscopy

Klebsiella pneumoniae (K. pneumoniae) is one of the most aggressive multidrug-resistant bacteria associated with human infections, resulting in high mortality and morbidity. We obtained 1190 K. pneumoniae isolates from different patients with urinary tract infections. The isolates were measured to determine their susceptibility regarding nine specific antibiotics. This study's primary goal is to evaluate the potential of infrared spectroscopy in tandem with machine learning to assess the susceptibility of K. pneumoniae within approximately 20 min following the first culture. Our results confirm that it was possible to classify the isolates into sensitive and resistant with a success rate higher than 80% for the tested antibiotics. These results prove the promising potential of infrared spectroscopy as a powerful method for a K. pneumoniae susceptibility test.

Atomic force microscopy and surface plasmon resonance for real-time single-cell monitoring of bacteriophage-mediated lysis of bacteria

The growing incidence of multidrug-resistant bacterial strains presents a major challenge in modern medicine. Antibiotic resistance is often exhibited by Staphylococcus aureus, which causes severe infections in human and animal hosts and leads to significant economic losses. Antimicrobial agents with enzymatic activity (enzybiotics) and phage therapy represent promising and effective alternatives to classic antibiotics. However, new tools are needed to study phage-bacteria interactions and bacterial lysis with high resolution and in real-time. Here, we introduce a method for studying the lysis of S. aureus at the single-cell level in real-time using atomic force microscopy (AFM) in liquid. We demonstrate the ability of the method to monitor the effect of the enzyme lysostaphin on S. aureus and the lytic action of the Podoviridae phage P68. AFM allowed the topographic and biomechanical properties of individual bacterial cells to be monitored at high resolution over the course of their lysis, under near-physiological conditions. Changes in the stiffness of S. aureus cells during lysis were studied by analyzing force-distance curves to determine Young's modulus. This allowed observing a progressive decline in cellular stiffness corresponding to the disintegration of the cell envelope. The AFM experiments were complemented by surface plasmon resonance (SPR) experiments that provided information on the kinetics of phage-bacterium binding and the subsequent lytic processes. This approach forms the foundation of an innovative framework for studying the lysis of individual bacteria that may facilitate the further development of phage therapy.

Infrared Spectroscopy of Blood

The magnitude of infectious diseases in the twenty-first century created an urgent need for point-of-care diagnostics. Critical shortages in reagents and testing kits have had a large impact on the ability to test patients with a suspected parasitic, bacteria, fungal, and viral infections. New point-of-care tests need to be highly sensitive, specific, and easy to use and provide results in rapid time. Infrared spectroscopy, coupled to multivariate and machine learning algorithms, has the potential to meet this unmet demand requiring minimal sample preparation to detect both pathogenic infectious agents and chronic disease markers in blood. This focal point article will highlight the application of Fourier transform infrared spectroscopy to detect disease markers in blood focusing principally on parasites, bacteria, viruses, cancer markers, and important analytes indicative of disease. Methodologies and state-of-the-art approaches will be reported and potential confounding variables in blood analysis identified. The article provides an up to date review of the literature on blood diagnosis using infrared spectroscopy highlighting the recent advances in this burgeoning field.

Rapid detection of Klebsiella pneumoniae producing extended spectrum β lactamase enzymes by infrared microspectroscopy and machine learning algorithms

Antimicrobial drugs have played an indispensable role in decreasing morbidity and mortality associated with infectious diseases. However, the resistance of bacteria to a broad spectrum of commonly-used antibiotics has grown to the point of being a global health-care problem. One of the most important classes of multi-drug resistant bacteria is Extended Spectrum Beta-Lactamase-producing (ESBL+) bacteria. This increase in bacterial resistance to antibiotics is mainly due to the long time (about 48 h) that it takes to obtain lab results of detecting ESBL-producing bacteria. Thus, rapid detection of ESBL+ bacteria is highly important for efficient treatment of bacterial infections. In this study, we evaluated the potential of infrared microspectroscopy in tandem with machine learning algorithms for rapid detection of ESBL-producing Klebsiella pneumoniae (K. pneumoniae) obtained from samples of patients with urinary tract infections. 285 ESBL+ and 365 ESBL-K. pneumoniae samples, gathered from cultured colonies, were examined. Our results show that it is possible to determine that K. pneumoniae is ESBL+ with ∼89% accuracy, ∼88% sensitivity and ∼89% specificity, in a time span of ∼20 minutes following the initial culture.

Rapid Methods for Antimicrobial Resistance Diagnostics

Antimicrobial resistance (AMR) is one of the most challenging threats in public health; thus, there is a growing demand for methods and technologies that enable rapid antimicrobial susceptibility testing (AST). The conventional methods and technologies addressing AMR diagnostics and AST employed in clinical microbiology are tedious, with high turnaround times (TAT), and are usually expensive. As a result, empirical antimicrobial therapies are prescribed leading to AMR spread, which in turn causes higher mortality rates and increased healthcare costs. This review describes the developments in current cutting-edge methods and technologies, organized by key enabling research domains, towards fighting the looming AMR menace by employing recent advances in AMR diagnostic tools. First, we summarize the conventional methods addressing AMR detection, surveillance, and AST. Thereafter, we examine more recent non-conventional methods and the advancements in each field, including whole genome sequencing (WGS), matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) spectrometry, Fourier transform infrared (FTIR) spectroscopy, and microfluidics technology. Following, we provide examples of commercially available diagnostic platforms for AST. Finally, perspectives on the implementation of emerging concepts towards developing paradigm-changing technologies and methodologies for AMR diagnostics are discussed.

Imaging Isotopically Labeled Bacteria at the Single-Cell Level Using High-Resolution Optical Infrared Photothermal Spectroscopy

We report that the cellular uptake of stable isotope-labeled compounds by bacteria can be probed at the single-cell level using infrared spectroscopy, and this monitors the chemical vibrations affected by the incorporation of "heavy" atoms by cells and thus can be used to understand microbial systems. This presents a significant advancement as most studies have focused on evaluating communities of cells due to the poor spatial resolution achieved by classical infrared microspectrometers, and to date, there is no study evaluating the incorporation of labeled compounds by bacteria at single-cell levels using infrared spectroscopy. The development of new technologies and instrumentations that provide information on the metabolic activity of a single bacterium is critical as this will allow for a better understanding of the interactions between microorganisms as well as the function of individual members and their interactions in different microbial communities. Thus, the present study demonstrates the ability of a novel far-field infrared imaging technique, optical photothermal infrared (O-PTIR) spectroscopy, as a tool to monitor the uptake of ¹³C-glucose and ¹⁵N-ammonium chloride by Escherichia coli bacteria at single-cell levels using spectral signatures recorded via single-point and imaging modes. An additional novelty is that imaging was achieved using six vibrational bands in the amide I and II regions, which were analyzed with chemometrics by employing partial least squares-discriminant analysis to predict ¹³C/¹²C and ¹⁵N/¹⁴N simultaneously.

Vibrational Spectroscopy as a Sensitive Probe for the Chemistry of Intra-Phase Bacterial Growth

Bacterial growth in batch cultures occurs in four phases (lag, exponential/log, stationary and death phase) that differ distinctly in number of different bacteria, biochemistry and physiology. Knowledge regarding the growth phase and its kinetics is essential for bacterial research, especially in taxonomic identification and monitoring drug interactions. However, the conventional methods by which to assess microbial growth are based only on cell counting or optical density, without any insight into the biochemistry of cells or processes. Both Raman and Fourier transform infrared (FTIR) spectroscopy have shown potential to determine the chemical changes occurring between different bacterial growth phases. Here, we extend the application of spectroscopy and for the first time combine both Raman and FTIR microscopy in a multimodal approach to detect changes in the chemical compositions of bacteria within the same phase (intra-phase). We found a number of spectral markers associated with nucleic acids (IR: 964, 1082, 1215 cm⁻¹; RS: 785, 1483 cm⁻¹), carbohydrates (IR: 1035 cm⁻¹; RS: 1047 cm⁻¹) and proteins (1394 cm⁻¹, amide II) reflecting not only inter-, but also intra-phase changes in bacterial chemistry. Principal component analysis performed simultaneously on FTIR and Raman spectra enabled a clear-cut, time-dependent discrimination between intra-lag phase bacteria probed every 30 min. This demonstrates the unique capability of multimodal vibrational spectroscopy to probe the chemistry of bacterial growth even at the intra-phase level, which is particularly important for the lag phase, where low bacterial numbers limit conventional analytical approaches.

Molecular characterization of methicillin-resistant Staphylococcus aureus clinical strains from the endotracheal tubes of patients with nosocomial pneumonia

BACKGROUND

Among all cases of nosocomial pneumonia, Staphylococcus aureus is the second most prevalent pathogen (17.8%). In Europe, 29.9% of the isolates are oxacillin-resistant. The changing epidemiology of methicillin-resistant Staphylococcus aureus (MRSA) nosocomial infections and the decreasing susceptibility to first-line antibiotics leave clinicians with few therapeutic options. The objective of our study was to determine the antimicrobial susceptibility, the associated molecular mechanisms of resistance and the epidemiological relatedness of MRSA strains isolated from the endotracheal tubes (ETT) of intubated critically ill patients in the intensive care unit (ICU) with nosocomial pneumonia caused by Staphylococcus aureus.

METHODS

The antimicrobial susceptibility to vancomycin, linezolid, ciprofloxacin, clindamycin, erythromycin, chloramphenicol, fusidic acid, gentamicin, quinupristin-dalfopristin, rifampicin, sulfamethoxazole/trimethoprim, and tetracycline were measured. Resistance mechanisms were then analyzed by polymerase chain reaction and sequencing. Molecular epidemiology was carried out by multi-locus sequence typing.

RESULTS

S. aureus isolates were resistant to ciprofloxacin, erythromycin, gentamicin, tetracycline, clindamycin, and fusidic acid. The most frequent mutations in quinolone-resistant S. aureus strains were S84L in the gyrA gene, V511A in the gyrB gene, S144P in the grlA gene, and K401R/E in the grlB gene. Strains resistant to erythromycin carried the ermC, ermA, and msrA genes; the same ermC and ermA genes were detected in strains resistant to clindamycin. The aac(6')-aph(2″) gene was related to gentamicin resistance, while resistance to tetracycline was related to tetK (efflux pump). The fusB gene was detected in the strain resistant to fusidic acid. The most frequent sequence types were ST22, ST8, and ST217, which were distributed in four clonal complexes (CC5, CC22, CC45, and CC59).

CONCLUSIONS

High levels of resistance to second-line antimicrobials threatens the treatment of nosocomial respiratory infections due to methicillin-resistant S. aureus with decreased susceptibility to linezolid and vancomycin. The wide genotypic diversity found reinforces the central role of ICU infection control in preventing nosocomial transmission.