Following drug uptake and reactions inside Escherichia coli cells by Raman microspectroscopy

Classification and prediction of Klebsiella pneumoniae strains with different MLST allelic profiles via SERS spectral analysis

The Gram-negative non-motile Klebsiella pneuomoniae is currently a major cause of hospital-acquired (HA) and community-acquired (CA) infections, leading to great public health concern globally, while rapid identification and accurate tracing of the pathogenic bacterium is essential in facilitating monitoring and controlling of K. pneumoniae outbreak and dissemination. Multi-locus sequence typing (MLST) is a commonly used typing approach with low cost that is able to distinguish bacterial isolates based on the allelic profiles of several housekeeping genes, despite low resolution and labor intensity of the method. Core-genome MLST scheme (cgMLST) is recently proposed to sub-type and monitor outbreaks of bacterial strains with high resolution and reliability, which uses hundreds or thousands of genes conserved in all or most members of the species. However, the method is complex and requires whole genome sequencing of bacterial strains with high costs. Therefore, it is urgently needed to develop novel methods with high resolution and low cost for bacterial typing. Surface enhanced Raman spectroscopy (SERS) is a rapid, sensitive and cheap method for bacterial identification. Previous studies confirmed that classification and prediction of bacterial strains via SERS spectral analysis correlated well with MLST typing results. However, there is currently no similar comparative analysis in K. pneumoniae strains. In this pilot study, 16 K. pneumoniae strains with different sequencing typings (STs) were selected and a phylogenetic tree was constructed based on core genome analysis. SERS spectra (N = 45/each strain) were generated for all the K. pneumoniae strains, which were then comparatively classified and predicted via six representative machine learning (ML) algorithms. According to the results, SERS technique coupled with the ML algorithm support vector machine (SVM) could achieve the highest accuracy (5-Fold Cross Validation = 100%) in terms of differentiating and predicting all the K. pneumoniae strains that were consistent to corresponding MLSTs. In sum, we show in this pilot study that the SERS-SVM based method is able to accurately predict K. pneumoniae MLST types, which has the application potential in clinical settings for tracing dissemination and controlling outbreak of K. pneumoniae in hospitals and communities with low costs and high rapidity.

An Outer Membrane Vesicle-Based Permeation Assay (OMPA) for Assessing Bacterial Bioavailability

When searching for new antibiotics against Gram-negative bacterial infections, a better understanding of the permeability across the cell envelope and tools to discriminate high from low bacterial bioavailability compounds are urgently needed. Inspired by the phospholipid vesicle-based permeation assay (PVPA), which is designed to predict non-facilitated permeation across phospholipid membranes, outer membrane vesicles (OMVs) of Escherichia coli either enriched or deficient of porins are employed to coat filter supports for predicting drug uptake across the complex cell envelope. OMVs and the obtained in vitro model are structurally and functionally characterized using cryo-TEM, SEM, CLSM, SAXS, and light scattering techniques. In vitro permeability, obtained from the membrane model for a set of nine antibiotics, correlates with reported in bacterio accumulation data and allows to discriminate high from low accumulating antibiotics. In contrast, the correlation of the same data set generated by liposome-based comparator membranes is poor. This better correlation of the OMV-derived membranes points to the importance of hydrophilic membrane components, such as lipopolysaccharides and porins, since those features are lacking in liposomal comparator membranes. This approach can offer in the future a high throughput screening tool with high predictive capacity or can help to identify compound- and bacteria-specific passive uptake pathways.

Visualizing and quantifying antimicrobial drug distribution in tissue

The biodistribution and pharmacokinetics of drugs are vital to the mechanistic understanding of their efficacy. Measuring antimicrobial drug efficacy has been challenging as plasma drug concentration is used as a surrogate for tissue drug concentration, yet typically does not reflect that at the intended site(s) of action. Utilizing an image-guided approach, it is feasible to accurately quantify the biodistribution and pharmacokinetics within the desired site(s) of action. We outline imaging modalities used in visualizing drug distribution with examples ranging from in vitro cellular drug uptake to clinical treatment of microbial infections. The imaging modalities of interest are: radio-labeling, magnetic resonance, mass spectrometry imaging, computed tomography, fluorescence, and Raman spectroscopy. We outline the progress, limitations, and future outlook for each methodology. Further advances in these optical approaches would benefit patients and researchers alike, as non-invasive imaging could yield more profound insights with a lower clinical burden than invasive measurement approaches used today.

Resonance Raman Spectra for the In Situ Identification of Bacteria Strains and Their Inactivation Mechanism

The resonance Raman spectra of bacterial carotenoids have been employed to identify bacterial strains and their intensity changes as a function of ultraviolet (UV) radiation dose have been used to differentiate between live and dead bacteria. In addition, the resonance-enhanced Raman spectra enabled us to detect bacteria in water at much lower concentrations (∼10⁸ cells/mL) than normally detected spectroscopically. A handheld spectrometer capable of recording resonance Raman spectra in situ was designed, constructed, and was used to record the spectra. In addition to bacteria, the method presented in this paper may also be used to identify fungi, viruses, and plants, in situ, and detect infections within a very short period of time.

Nanotargeting of Resistant Infections with a Special Emphasis on the Biofilm Landscape

Bacterial resistance to antimicrobial compounds is a growing concern in medical and public health circles. Overcoming the adaptable and duplicative resistance mechanisms of bacteria requires chemistry-based approaches. Engineered nanoparticles (NPs) now offer unique advantages toward this effort. However, most in situ infections (in humans) occur as attached biofilms enveloped in a protective surrounding matrix of extracellular polymers, where survival of microbial cells is enhanced. This presents special considerations in the design and deployment of antimicrobials. Here, we review recent efforts to combat resistant bacterial strains using NPs and, then, explore how NP surfaces may be specifically engineered to enhance the potency and delivery of antimicrobial compounds. Special NP-engineering challenges in the design of NPs must be overcome to penetrate the inherent protective barriers of the biofilm and to successfully deliver antimicrobials to bacterial cells. Future challenges are discussed in the development of new antibiotics and their mechanisms of action and targeted delivery via NPs.

Mastering the Gram-negative bacterial barrier - Chemical approaches to increase bacterial bioavailability of antibiotics

To win the battle against resistant, pathogenic bacteria, novel classes of anti-infectives and targets are urgently needed. Bacterial uptake, distribution, metabolic and efflux pathways of antibiotics in Gram-negative bacteria determine what we here refer to as bacterial bioavailability. Understanding these mechanisms from a chemical perspective is essential for anti-infective activity and hence, drug discovery as well as drug delivery. A systematic and critical discussion of in bacterio, in vitro and in silico assays reveals that a sufficiently accurate holistic approach is still missing. We expect new findings based on Gram-negative bacterial bioavailability to guide future anti-infective research.

Defining new chemical space for drug penetration into Gram-negative bacteria

We live in the era of antibiotic resistance, and this problem will progressively worsen if no new solutions emerge. In particular, Gram-negative pathogens present both biological and chemical challenges that hinder the discovery of new antibacterial drugs. First, these bacteria are protected from a variety of structurally diverse drugs by a low-permeability barrier composed of two membranes with distinct permeability properties, in addition to active drug efflux, making this cell envelope impermeable to most compounds. Second, chemical libraries currently used in drug discovery contain few compounds that can penetrate Gram-negative bacteria. As a result of these challenges, intensive screening campaigns have led to few successes, highlighting the need for new approaches to identify regions of chemical space that are specifically relevant to antibacterial drug discovery. Herein we provide an overview of emerging insights into this problem and outline a general approach to addressing it using prospective analysis of chemical libraries for the ability of compounds to accumulate in Gram-negative bacteria. The overall goal is to develop robust cheminformatic tools to predict Gram-negative permeation and efflux, which can then be used to guide medicinal chemistry campaigns and the design of antibacterial discovery libraries.

Stability of β-lactam antibiotics in bacterial growth media

Laboratory assays such as MIC tests assume that antibiotic molecules are stable in the chosen growth medium-but rapid degradation has been observed for antibiotics including β-lactams under some conditions in aqueous solution. Degradation rates in bacterial growth medium are less well known. Here, we develop a 'delay time bioassay' that provides a simple way to estimate antibiotic stability in bacterial growth media, using only a plate reader and without the need to measure the antibiotic concentration directly. We use the bioassay to measure degradation half-lives of the β-lactam antibiotics mecillinam, aztreonam and cefotaxime in widely-used bacterial growth media based on MOPS and Luria-Bertani (LB) broth. We find that mecillinam degradation can occur rapidly, with a half-life as short as 2 hours in MOPS medium at 37°C and pH 7.4, and 4-5 hours in LB, but that adjusting the pH and temperature can increase its stability to a half-life around 6 hours without excessively perturbing growth. Aztreonam and cefotaxime were found to have half-lives longer than 6 hours in MOPS medium at 37°C and pH 7.4, but still shorter than the timescale of a typical minimum inhibitory concentration (MIC) assay. Taken together, our results suggest that care is needed in interpreting MIC tests and other laboratory growth assays for β-lactam antibiotics, since there may be significant degradation of the antibiotic during the assay.

Biochemical characterization of pathogenic bacterial species using Raman spectroscopy and discrimination model based on selected spectral features

This study aimed to evaluate the differences in the Raman spectra of nine clinical species of bacteria isolated from infections (three Gram-positive and six Gram-negative species), correlating the spectra with the chemical composition of each species and to develop a classification model through discriminant analysis to categorize each bacterial strain using the peaks with the most significant differences. Bacteria were cultured in Mueller Hinton agar and a sample of biomass was harvested and placed in an aluminum sample holder. A total of 475 spectra from 115 different strains were obtained through a dispersive Raman spectrometer (830 nm) with exposure time of 50 s. The intensities of the peaks were evaluated by one-way analysis of variance (ANOVA) and the peaks with significant differences were related to the differences in the biochemical composition of the strains. Discriminant analysis based on quadratic distance applied to the peaks with the most significant differences and partial least squares applied to the whole spectrum showed 89.5% and 90.1% of global accuracy, respectively, for classification of the spectra in all the groups. Raman spectroscopy could be a promising technique to identify spectral differences related to the biochemical content of pathogenic microorganisms and to provide a faster diagnosis of infectious diseases.

Membrane damage mechanism contributes to inhibition of trans-cinnamaldehyde on Penicillium italicum using Surface-Enhanced Raman Spectroscopy (SERS)

The antifungal mechanism of essential oils against fungi remains in the shallow study. In this paper, antifungal mechanism of trans-cinnamaldehyde against Penicillium italicum was explored. Trans-cinnamaldehyde exhibited strong mycelial growth inhibition against Penicillium italicum, with minimum inhibitory concentration of 0.313 μg/mL. Conventional analytical tests showed that trans-cinnamaldehyde changed the cell membrane permeability, which led to the leakage of some materials. Meanwhile, the membrane integrity and cell wall integrity also changed. Surface-enhanced Raman spectroscopy, an ultrasensitive and fingerprint method, was served as a bran-new method to study the antifungal mechanism. Characteristic peaks of supernatant obviously changed at 734, 1244, 1330, 1338 and 1466 cm^-1. The Raman intensity represented a strong correlation with results from conventional methods, which made SERS an alternative to study antifungal process. All evidences implied that trans-cinnamaldehyde exerts its antifungal capacity against Penicillium italicum via membrane damage mechanism.

Measuring Drug-Induced Changes in Metabolite Populations of Live Bacteria: Real Time Analysis by Raman Spectroscopy

Raman difference spectroscopy is shown to provide a wealth of molecular detail on changes within bacterial cells caused by infusion of antibiotics or hydrogen peroxide. Escherichia coli strains paired with chloramphenicol, dihydrofolate reductase propargyl-based inhibitors, meropenem, or hydrogen peroxide provide details of the depletion of protein and nucleic acid populations in real time. Additionally, other reproducible Raman features appear and are attributed to changes in cell metabolite populations. An initial candidate for one of the metabolites involves population increases of citrate, an intermediate within the tricarboxyclic acid cycle. This is supported by the observation that a strain of E. coli without the ability to synthesize citrate, gltA, lacks an intense feature in the Raman difference spectrum that has been ascribed to citrate. The methodology for obtaining the Raman data involves infusing the drug into live cells, then washing, freezing, and finally lyophilizing the cells. The freeze-dried cells are then examined under a Raman microscope. The difference spectra [cells treated with drug] - [cells without treatment] are time-dependent and can yield population kinetics for intracellular species in vivo. There is a strong resemblance between the Raman difference spectra of E. coli cells treated with meropenem and those treated with hydrogen peroxide.

Antibacterial Drug Discovery: Some Assembly Required

Our limited understanding of the molecular basis for compound entry into and efflux out of Gram-negative bacteria is now recognized as a key bottleneck for the rational discovery of novel antibacterial compounds. Traditional, large-scale biochemical or target-agnostic phenotypic antibacterial screening efforts have, as a result, not been very fruitful. A main driver of this knowledge gap has been the historical lack of predictive cellular assays, tools, and models that provide structure-activity relationships to inform optimization of compound accumulation. A variety of recent approaches has recently been described to address this conundrum. This Perspective explores these approaches and considers ways in which their integration could successfully redirect antibacterial drug discovery efforts.

A Critical Review on Ultrasensitive, Spectroscopic-based Methods for High-throughput Monitoring of Bacteria during Infection Treatment

The world is in the midst of a pre-emptive public health emergency, one that is just as dramatic as the global aggressive viruses-related crises (Ebola, Zika, or SARS), but not as visible. The "superbugs" and their antimicrobial resistance do not cause much public alarm or awareness, but provoke financial losses of $100 trillion annually (WHO, http://www.who.int/mediacentre/commentaries/superbugs-action-now/en/ ). This status quo review offers an overview of ultrasensitive methods for high-throughput monitoring of bacteria during infection treatment, the effects of antibiotics on bacteria at single-cell level and the challenges we will face in their detection due to the extraordinary capability of these "superbugs" to gain and constantly improve multiresistance to antibiotics. A special emphasis is put on the ultrasensitive spectroscopic-based analysis techniques, using nanotechnology or not necessarily, that are more and more promising alternatives to conventional culture-based ones. The particular case of Mycobacteria detection is discussed based on recent reported work.

Imaging drug uptake by bioorthogonal stimulated Raman scattering microscopy

Stimulated Raman scattering (SRS) microscopy in tandem with bioorthogonal Raman labelling enables intracellular drug concentrations, distribution and therapeutic response to be measured in living cells.

Stimulated Raman scattering (SRS) microscopy in tandem with bioorthogonal Raman labelling strategies is set to revolutionise the direct visualisation of intracellular drug uptake. Rational evaluation of a series of Raman-active labels has allowed the identification of highly active labels which have minimal perturbation on the biological efficacy of the parent drug. Drug uptake has been correlated with markers of cellular composition and cell cycle status, and mapped across intracellular structures using dual-colour and multi-modal imaging. The minimal phototoxicity and low photobleaching associated with SRS microscopy has enabled real-time imaging in live cells. These studies demonstrate the potential for SRS microscopy in the drug development process.

Single-cell level methods for studying the effect of antibiotics on bacteria during infection

Considerable evidence about phenotypic heterogeneity among bacteria during infection has accumulated during recent years. This heterogeneity has to be considered if the mechanisms of infection and antibiotic action are to be understood, so we need to implement existing and find novel methods to monitor the effects of antibiotics on bacteria at the single-cell level. This review provides an overview of methods by which this aim can be achieved. Fluorescence label-based methods and Raman scattering as a label-free approach are discussed in particular detail. Other label-free methods that can provide single-cell level information, such as impedance spectroscopy and surface plasmon resonance, are briefly summarized. The advantages and disadvantages of these different methods are discussed in light of a challenging in vivo environment.

Stimulated Raman scattering microscopy: an emerging tool for drug discovery

Optical microscopy techniques have emerged as a cornerstone of biomedical research, capable of probing the cellular functions of a vast range of substrates, whilst being minimally invasive to the cells or tissues of interest. Incorporating biological imaging into the early stages of the drug discovery process can provide invaluable information about drug activity within complex disease models. Spontaneous Raman spectroscopy has been widely used as a platform for the study of cells and their components based on chemical composition; but slow acquisition rates, poor resolution and a lack of sensitivity have hampered further development. A new generation of stimulated Raman techniques is emerging which allows the imaging of cells, tissues and organisms at faster acquisition speeds, and with greater resolution and sensitivity than previously possible. This review focuses on the development of stimulated Raman scattering (SRS), and covers the use of bioorthogonal tags to enhance sample detection, and recent applications of both spontaneous Raman and SRS as novel imaging platforms to facilitate the drug discovery process.

Exposing a β-Lactamase "Twist": the Mechanistic Basis for the High Level of Ceftazidime Resistance in the C69F Variant of the Burkholderia pseudomallei PenI β-Lactamase

Around the world, Burkholderia spp. are emerging as pathogens highly resistant to β-lactam antibiotics, especially ceftazidime. Clinical variants of Burkholderia pseudomallei possessing the class A β-lactamase PenI with substitutions at positions C69 and P167 are known to demonstrate ceftazidime resistance. However, the biochemical basis for ceftazidime resistance in class A β-lactamases in B. pseudomallei is largely undefined. Here, we performed site saturation mutagenesis of the C69 position and investigated the kinetic properties of the C69F variant of PenI from B. pseudomallei that results in a high level of ceftazidime resistance (2 to 64 mg/liter) when expressed in Escherichia coli. Surprisingly, quantitative immunoblotting showed that the steady-state protein levels of the C69F variant β-lactamase were ∼4-fold lower than those of wild-type PenI (0.76 fg of protein/cell versus 4.1 fg of protein/cell, respectively). However, growth in the presence of ceftazidime increases the relative amount of the C69F variant to greater than wild-type PenI levels. The C69F variant exhibits a branched kinetic mechanism for ceftazidime hydrolysis, suggesting there are two different conformations of the enzyme. When incubated with an anti-PenI antibody, one conformation of the C69F variant rapidly hydrolyzes ceftazidime and most likely contributes to the higher levels of ceftazidime resistance observed in cell-based assays. Molecular dynamics simulations suggest that the electrostatic characteristics of the oxyanion hole are altered in the C69F variant. When ceftazidime was positioned in the active site, the C69F variant is predicted to form a greater number of hydrogen-bonding interactions than PenI with ceftazidime. In conclusion, we propose "a new twist" for enhanced ceftazidime resistance mediated by the C69F variant of the PenI β-lactamase based on conformational changes in the C69F variant. Our findings explain the biochemical basis of ceftazidime resistance in B. pseudomallei, a pathogen of considerable importance, and suggest that the full repertoire of conformational states of a β-lactamase profoundly affects β-lactam resistance.

New techniques in antibiotic discovery and resistance: Raman spectroscopy

Raman spectroscopy can play a role in both antibiotic discovery and understanding the molecular basis of resistance. A major challenge in drug development is to measure the population of the drug molecules inside a cell line and to follow the chemistry of their reactions with intracellular targets. Recently, a protocol based on Raman microscopy has been developed that achieves these goals. Drug candidates are soaked into live bacterial cells and subsequently the cells are frozen and freeze-dried. The samples yield exemplary (nonresonance) Raman data that provide a measure of the number of drug molecules within each cell, as well as details of drug-target interactions. Results are discussed for two classes of compounds inhibiting either β-lactamase or dihydrofolate reductase enzymes in a number of Gram-positive or Gram-negative cell lines. The advantages of the present protocol are that it does not use labels and it can measure the kinetics of cell-compound uptake on the time scale of minutes. Spectroscopic interpretation is supported by in vitro Raman experiments. Studying drug-target interactions in aqueous solution and in single crystals can provide molecular level insights into drug-target interactions, which, in turn, provide the underpinnings of our understanding of data from bacterial cells. Thus, the applicability of X-ray crystallographic-derived data to in-cell chemistry can be tested.