Antibiotic Susceptibility Determination within One Cell Cycle at Single-Bacterium Level by Stimulated Raman Metabolic Imaging

Seeing is Believing: Developing Multimodal Metabolic Insights at the Molecular Level

This outlook explores how two different molecular imaging approaches might be combined to gain insight into dynamic, subcellular metabolic processes. Specifically, we discuss how matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) and stimulated Raman scattering (SRS) microscopy, which have significantly pushed the boundaries of imaging metabolic and metabolomic analyses in their own right, could be combined to create comprehensive molecular images. We first briefly summarize the recent advances for each technique. We then explore how one might overcome the inherent limitations of each individual method, by envisioning orthogonal and interchangeable workflows. Additionally, we delve into the potential benefits of adopting a complementary approach that combines both MSI and SRS spectro-microscopy for informing on specific chemical structures through functional-group-specific targets. Ultimately, by integrating the strengths of both imaging modalities, researchers can achieve a more comprehensive understanding of biological and chemical systems, enabling precise metabolic investigations. This synergistic approach holds substantial promise to expand our toolkit for studying metabolites in complex environments.

Biomedical applications, perspectives and tag design concepts in the cell - silent Raman window

Spectroscopic studies increasingly employ Raman tags exhibiting a signal in the cell - silent region of the Raman spectrum (1800-2800 cm-1), where bands arising from biological molecules are inherently absent. Raman tags bearing functional groups which contain a triple bond, such as alkyne and nitrile or a carbon-deuterium bond, have a distinct vibrational frequency in this region. Due to the lack of spectral background and cell-associated bands in the specific area, the implementation of those tags can help overcome the inherently poor signal-to-noise ratio and presence of overlapping Raman bands in measurements of biological samples. The cell - silent Raman tags allow for bioorthogonal imaging of biomolecules with improved chemical contrast and they have found application in analyte detection and monitoring, biomarker profiling and live cell imaging. This review focuses on the potential of the cell - silent Raman region, reporting on the tags employed for biomedical applications using variants of Raman spectroscopy.

A multimodal nonlinear optical microscopy study of the responses of Pseudomonas aeruginosa to blue light and antibiotic treatment

Pseudomonas aeruginosa (P. aeruginosa) is a multidrug-resistant human pathogen involved in numerous infections. Understanding the response of P. aeruginosa to various treatments is critical to developing new ways for the antimicrobial susceptibly test and more effective treatment methods. Conventional antimicrobial susceptibility tests lack molecular information at the single bacterium level. In this study, we used label-free multimodal nonlinear optical microscopy to identify an autofluorescence signal from pyoverdine, a siderophore of the bacteria, for quantification of P. aeruginosa responses to antibiotics and blue light treatment. We also discovered that the bleaching of the pyoverdine autofluorescence signals is correlated with the inactivation of P. aeruginosa and is perhaps one of the mechanisms involved in the blue light inactivation of P. aeruginosa.

Metabolism-Triggered Plasmonic Nanosensor for Bacterial Detection and Antimicrobial Susceptibility Testing of Clinical Isolates

Antimicrobial resistance (AMR) is predicted to become the leading cause of death worldwide in the coming decades. Rapid and on-site antibiotic susceptibility testing (AST) is crucial for guiding appropriate antibiotic choices to combat AMR. With this in mind, we have designed a simple and efficient plasmonic nanosensor consisting of Cu2+ and cysteine-modified AuNP (Au/Cys) that utilizes the metabolic activity of bacteria toward Cu2+ for bacterial detection and AST. When Cu2+ is present, it induces the aggregation of Au/Cys. However, in the presence of bacteria, Cu2+ is metabolized to varying extents, resulting in distinct levels of aggregation. Moreover, the metabolic activity of bacteria can be influenced by their antibiotic susceptibility, allowing us to differentiate between susceptible and resistant strains through direct color changes from the Cu2+-Au/Cys platform over approximately 3 h. These color changes can be easily detected using naked-eye observation, smartphone analysis, or absorption readout. We have validated the platform using four clinical isolates and six types of antibiotics, demonstrating a clinical sensitivity and specificity of 95.8%. Given its simplicity, low cost, high speed, and high accuracy, the plasmonic nanosensor holds great potential for point-of-care detection of antibiotic susceptibility across various settings.

Simultaneous bond-selective deuterium-based isotopic labeling sensing with disposable ultra-miniature CARS fiber probe

Deuterium-based isotopic labeling is an important technique for tracking cellular metabolism with the Raman signals analysis of low-wavenumber (LW) C-D bonds and high-wavenumber (HW) C-H bonds. We propose and demonstrate a disposable ultra-miniature fiber probe to detect LW and HW coherent anti-Stokes Raman scattering (CARS) spectra for deuterated compounds simultaneously and bond-selectively sensing. The 10.78 µm diameter disposable fiber probe, comprised of focusing taper as fiber probe head and time-domain walk-off eliminating fiber section with designed length, realizes wide-frequency-interval dual Stokes pulse delivering and focusing. The fiber probe enables quantitative concentration determination with resolution down to 11 mM. The chemical vibration modes of LW region C-D bonds and HW region C-H bonds of the mixture samples of organic compounds and their deuterated counterparts in a simulated cell are simultaneously excited and characterized. The CARS disposable fiber probe introduces a promising handle for in vivo biochemical detection based on isotopic labeling sensing.

The Parkinson's drug entacapone disrupts gut microbiome homeostasis via iron sequestration

Increasing evidence shows that many human-targeted drugs alter the gut microbiome, leading to implications for host health. However, much less is known about the mechanisms by which drugs target the microbiome and how drugs affect microbial function. Here we combined quantitative microbiome profiling, long-read metagenomics, stable isotope probing and single cell chemical imaging to investigate the impact of two widely prescribed nervous system targeted drugs on the gut microbiome. Ex vivo supplementation of physiologically relevant concentrations of entacapone or loxapine succinate to faecal samples significantly impacted the abundance of up to one third of the microbial species present. Importantly, we demonstrate that the impact of these drugs on microbial metabolism is much more pronounced than their impact on abundances, with low concentrations of drugs reducing the activity, but not the abundance of key microbiome members like Bacteroides, Ruminococcus or Clostridium species. We further demonstrate that entacapone impacts the microbiome due to its ability to complex and deplete available iron, and that microbial growth can be rescued by replenishing levels of microbiota-accessible iron. Remarkably, entacapone-induced iron starvation selected for iron-scavenging organisms carrying antimicrobial resistance and virulence genes. Collectively, our study unveils the impact of two under-investigated drugs on whole microbiomes and identifies metal sequestration as a mechanism of drug-induced microbiome disturbance.

Rapid Mycobacterium abscessus antimicrobial susceptibility testing based on antibiotic treatment response mapping via Raman Microspectroscopy

OBJECTIVES

Antimicrobial susceptibility tests (ASTs) are pivotal tools for detecting and combating infections caused by multidrug-resistant rapidly growing mycobacteria (RGM) but are time-consuming and labor-intensive.

DESIGN

We used a Mycobacterium abscessus-based RGM model to develop a rapid (24-h) AST from the beginning of the strain culture, the Clinical Antimicrobials Susceptibility Test Ramanometry for RGM (CAST-R-RGM). The ASTs obtained for 21 clarithromycin (CLA)-treated and 18 linezolid (LZD)-treated RGM isolates.

RESULTS

CAST-R-RGM employs D2O-probed Raman microspectroscopy to monitor RGM metabolic activity, while also revealing bacterial antimicrobial drug resistance mechanisms. The results of clarithromycin (CLA)-treated and linezolid (LZD)-treated RGM isolates exhibited 90% and 83% categorical agreement, respectively, with conventional AST results of the same isolates. Furthermore, comparisons of time- and concentration-dependent Raman results between CLA- and LZD-treated RGM strains revealed distinct metabolic profiles after 48-h and 72-h drug treatments, despite similar profiles obtained for both drugs after 24-h treatments.

CONCLUSIONS

Ultimately, the rapid, accurate, and low-cost CAST-R-RGM assay offers advantages over conventional culture-based ASTs that warrant its use as a tool for improving patient treatment outcomes and revealing bacterial drug resistance mechanisms.

Rapid Antifungal Susceptibility Testing Based on Single-Cell Metabolism Analysis Using Stimulated Raman Scattering Imaging

Rapid antifungal susceptibility testing (AFST) is urgently needed in clinics to treat invasive fungal infections with the appropriate antifungal drugs and to slow the emergence of antifungal resistance. However, current AFST methods are time-consuming (24-48 h) due to the slow growth of fungal cells and the methods not being able to work directly for clinical samples. Here, we demonstrate rapid AFST by measuring the metabolism in single fungal cells using stimulated Raman scattering imaging and deuterium probing. Distinct metabolic responses were observed in Candida albicans to different classes of antifungal drugs: while the metabolism was inhibited by amphotericin B, it was stimulated by azoles (fluconazole and voriconazole) and micafungin. Accordingly, we propose metabolism change as a biomarker for rapid AFST. The results were obtained in 4 h with 100% categorical agreement with the gold standard broth microdilution test. In addition, a protocol was developed for direct AFST from positive blood cultures. This method overcomes the limitation of slow growth in conventional methods and has the potential for the rapid diagnosis of candidemia and other clinical fungal infections.

High-throughput single-cell sorting by stimulated Raman-activated cell ejection

Single-cell sorting is essential to explore cellular heterogeneity in biology and medicine. Recently developed Raman-activated cell sorting (RACS) circumvents the limitations of fluorescence-activated cell sorting, such as the cytotoxicity of labels. However, the sorting throughputs of all forms of RACS are limited by the intrinsically small cross-section of spontaneous Raman scattering. Here, we report a stimulated Raman-activated cell ejection (S-RACE) platform that enables high-throughput single-cell sorting based on high-resolution multi-channel stimulated Raman chemical imaging, in situ image decomposition, and laser-induced cell ejection. The performance of this platform was illustrated by sorting a mixture of 1 μm polymer beads, where 95% yield, 98% purity, and 14 events per second throughput were achieved. Notably, our platform allows live cell ejection, allowing for the growth of single colonies of bacteria and fungi after sorting. To further illustrate the chemical selectivity, lipid-rich Rhodotorula glutinis cells were successfully sorted from a mixture with Saccharomyces cerevisiae, confirmed by downstream quantitative PCR. Furthermore, by integrating a closed-loop feedback control circuit into the system, we realized real-time single-cell imaging and sorting, and applied this method to precisely eject regions of interest from a rat brain tissue section. The reported S-RACE platform opens exciting opportunities for a wide range of single-cell applications in biology and medicine.

Single-cell scattering and auto-fluorescence-based fast antibiotic susceptibility testing for gram-negative and gram-positive bacteria

In this study, we assess the scattering of light and auto-fluorescence from single bacterial cells to address the challenge of fast (<2 h), label-free phenotypic antimicrobial susceptibility testing (AST). Label-free flow cytometry is used for monitoring both the respiration-related auto-fluorescence in two different fluorescence channels corresponding to FAD and NADH, and the morphological and structural information contained in the light scattered by individual bacteria during incubation with or without antibiotic. Large multi-parameter data are analyzed using dimensionality reduction methods, based either on a combination of 2D binning and Principal Component Analysis, or with a one-class Support Vector Machine approach, with the objective to predict the Susceptible or Resistant phenotype of the strain. For the first time, both Escherichia coli (Gram-negative) and Staphylococcus epidermidis (Gram-positive) isolates were tested with a label-free approach, and, in the presence of two groups of bactericidal antibiotic molecules, aminoglycosides and beta-lactams. Our results support the feasibility of label-free AST in less than 2 h and suggest that single cell auto-fluorescence adds value to the Susceptible/Resistant phenotyping over single-cell scattering alone, in particular for the mecA+ Staphylococcus (i.e., resistant) strains treated with oxacillin.

Antibiotic resistance mechanism and diagnosis of common foodborne pathogens based on genotypic and phenotypic biomarkers

The emergence of antibiotic-resistant bacteria due to the overuse or inappropriate use of antibiotics has become a significant public health concern. The agri-food chain, which serves as a vital link between the environment, food, and human, contributes to the large-scale dissemination of antibiotic resistance, posing a concern to both food safety and human health. Identification and evaluation of antibiotic resistance of foodborne bacteria is a crucial priority to avoid antibiotic abuse and ensure food safety. However, the conventional approach for detecting antibiotic resistance heavily relies on culture-based methods, which are laborious and time-consuming. Therefore, there is an urgent need to develop accurate and rapid tools for diagnosing antibiotic resistance in foodborne pathogens. This review aims to provide an overview of the mechanisms of antibiotic resistance at both phenotypic and genetic levels, with a focus on identifying potential biomarkers for diagnosing antibiotic resistance in foodborne pathogens. Furthermore, an overview of advances in the strategies based on the potential biomarkers (antibiotic resistance genes, antibiotic resistance-associated mutations, antibiotic resistance phenotypes) for antibiotic resistance analysis of foodborne pathogens is systematically exhibited. This work aims to provide guidance for the advancement of efficient and accurate diagnostic techniques for antibiotic resistance analysis in the food industry.

Stimulated Raman Scattering Imaging Sheds New Light on Lipid Droplet Biology

A lipid droplet (LD) is a dynamic organelle closely associated with cellular functions and energy homeostasis. Dysregulated LD biology underlies an increasing number of human diseases, including metabolic disease, cancer, and neurodegenerative disorder. Commonly used lipid staining and analytical tools have difficulty providing the information regarding LD distribution and composition at the same time. To address this problem, stimulated Raman scattering (SRS) microscopy uses the intrinsic chemical contrast of biomolecules to achieve both direct visualization of LD dynamics and quantitative analysis of LD composition with high molecular selectivity at the subcellular level. Recent developments of Raman tags have further enhanced sensitivity and specificity of SRS imaging without perturbing molecular activity. With these advantages, SRS microscopy has offered great promise for deciphering LD metabolism in single live cells. This article overviews and discusses the latest applications of SRS microscopy as an emerging platform to dissect LD biology in health and disease.

Antibiotic Resistance Diagnosis in ESKAPE Pathogens-A Review on Proteomic Perspective

Antibiotic resistance has emerged as an imminent pandemic. Rapid diagnostic assays distinguish bacterial infections from other diseases and aid antimicrobial stewardship, therapy optimization, and epidemiological surveillance. Traditional methods typically have longer turn-around times for definitive results. On the other hand, proteomic studies have progressed constantly and improved both in qualitative and quantitative analysis. With a wide range of data sets made available in the public domain, the ability to interpret the data has considerably reduced the error rates. This review gives an insight on state-of-the-art proteomic techniques in diagnosing antibiotic resistance in ESKAPE pathogens with a future outlook for evading the "imminent pandemic".

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.

Mid-Infrared Photothermal-Fluorescence In Situ Hybridization for Functional Analysis and Genetic Identification of Single Cells

Simultaneous identification and metabolic analysis of microbes with single-cell resolution and high throughput are necessary to answer the question of "who eats what, when, and where" in complex microbial communities. Here, we present a mid-infrared photothermal-fluorescence in situ hybridization (MIP-FISH) platform that enables direct bridging of genotype and phenotype. Through multiple improvements of MIP imaging, the sensitive detection of isotopically labeled compounds incorporated into proteins of individual bacterial cells became possible, while simultaneous detection of FISH labeling with rRNA-targeted probes enabled the identification of the analyzed cells. In proof-of-concept experiments, we showed that the clear spectral red shift in the protein amide I region due to incorporation of ¹³C atoms originating from ¹³C-labeled glucose can be exploited by MIP-FISH to discriminate and identify ¹³C-labeled bacterial cells within a complex human gut microbiome sample. The presented methods open new opportunities for single-cell structure-function analyses for microbiology.

Antibiotic Susceptibility Testing with Raman Biosensing

Antibiotics guard us against bacterial infections and are among the most commonly used medicines. The immediate consequence of their large-scale production and prescription is the development of antibiotic resistance. Therefore, rapid detection of antibiotic susceptibility is required for efficient antimicrobial therapy. One of the promising methods for rapid antibiotic susceptibility testing is Raman spectroscopy. Raman spectroscopy combines fast and contactless acquisition of spectra with good selectivity towards bacterial cells. The antibiotic-induced changes in bacterial cell physiology are detected as distinct features in Raman spectra and can be associated with antibiotic susceptibility. Therefore, the Raman-based approach may be beneficial in designing therapy against multidrug-resistant infections. The surface-enhanced Raman spectroscopy (SERS) and resonance Raman spectroscopy (RRS) additionally provide excellent sensitivity. In this review, we present an analysis of the Raman spectroscopy-based optical biosensing approaches aimed at antibiotic susceptibility testing.

Raman Spectroscopy for Chemical Biology Research

In chemical biology research, various fluorescent probes have been developed and used to visualize target proteins or molecules in living cells and tissues, yet there are limitations to this technology, such as the limited number of colors that can be detected simultaneously. Recently, Raman spectroscopy has been applied in chemical biology to overcome such limitations. Raman spectroscopy detects the molecular vibrations reflecting the structures and chemical conditions of molecules in a sample and was originally used to directly visualize the chemical responses of endogenous molecules. However, our initial research to develop "Raman tags" opens a new avenue for the application of Raman spectroscopy in chemical biology. In this Perspective, we first introduce the label-free Raman imaging of biomolecules, illustrating the biological applications of Raman spectroscopy. Next, we highlight the application of Raman imaging of small molecules using Raman tags for chemical biology research. Finally, we discuss the development and potential of Raman probes, which represent the next-generation probes in chemical biology.

Combinatorial screening SlipChip for rapid phenotypic antimicrobial susceptibility testing

Antimicrobial resistance (AMR) by bacteria is a serious global threat, and a rapid, high-throughput, and easy-to-use phenotypic antimicrobial susceptibility testing (AST) method is essential for making timely treatment decisions and controlling the spread of antibiotic resistant micro-organisms. Traditional culture-based methods are time-consuming, and their capability to screen against a large number of different conditions is limited; meanwhile genotypic based methods, including sequencing and PCR based methods, are constrained by rarely identified resistance genes and complicated resistance mechanisms. Here, a combinatorial-screening SlipChip (cs-SlipChip) containing 192 nanoliter-sized compartments is developed which can perform high-throughput phenotypic AST within three hours by monitoring the bacterial growth within nanoliter-sized droplets with bright-field imaging and analyzing the changes in bacterial number and morphology. The minimum inhibitory concentration (MIC) of Escherichia coli ATCC 25922 against four antibiotics (ampicillin, ciprofloxacin, ceftazidime, and nitrofurantoin) can be measured in one chip within 3 hours. Furthermore, five antibiotic-resistant E. coli strains were isolated from patients diagnosed with urinary tract infections (UTIs), and an individual isolate was tested using four antibiotics and eleven antibiotic combinations simultaneously with three different concentrations of each. The results from the cs-SlipChip agree with those of a VITEK 2 automated system. This cs-SlipChip provides a practical high-throughput and rapid phenotypic method for AST and can also be used to screen different chemicals and antibiotic combinations for the treatment of multiple antibiotic-resistant bacteria.

Microfluidics for antibiotic susceptibility testing

The rise of antibiotic resistance is a threat to global health. Rapid and comprehensive analysis of infectious strains is critical to reducing the global use of antibiotics, as informed antibiotic use could slow down the emergence of resistant strains worldwide. Multiple platforms for antibiotic susceptibility testing (AST) have been developed with the use of microfluidic solutions. Here we describe microfluidic systems that have been proposed to aid AST. We identify the key contributions in overcoming outstanding challenges associated with the required degree of multiplexing, reduction of detection time, scalability, ease of use, and capacity for commercialization. We introduce the reader to microfluidics in general, and we analyze the challenges and opportunities related to the field of microfluidic AST.

Rapid, automated, and reliable antimicrobial susceptibility test from positive blood culture by CAST-R

Antimicrobial susceptibility tests (ASTs) are pivotal in combating multidrug resistant pathogens, yet they can be time-consuming, labor-intensive, and unstable. Using the AST of tigecycline for sepsis as the main model, here we establish an automated system of Clinical Antimicrobials Susceptibility Test Ramanometry (CAST-R), based on D2O-probed Raman microspectroscopy. Featuring a liquid robot for sample pretreatment and a machine learning-based control scheme for data acquisition and quality control, the 3-h, automated CAST-R process accelerates AST by >10-fold, processes 96 paralleled antibiotic-exposure reactions, and produces high-quality Raman spectra. The Expedited Minimal Inhibitory Concentration via Metabolic Activity is proposed as a quantitative and broadly applicable parameter for metabolism-based AST, which shows 99% essential agreement and 93% categorical agreement with the broth microdilution method (BMD) when tested on 100 Acinetobacter baumannii isolates. Further tests on 26 clinically positive blood samples for eight antimicrobials, including tigecycline, meropenem, ceftazidime, ampicillin/sulbactam, oxacillin, clindamycin, vancomycin, and levofloxacin reveal 93% categorical agreement with BMD-based results. The automation, speed, reliability, and general applicability of CAST-R suggest its potential utility for guiding the clinical administration of antimicrobials.

Compound Raman microscopy for rapid diagnosis and antimicrobial susceptibility testing of pathogenic bacteria in urine

Rapid identification and antimicrobial susceptibility testing (AST) of bacteria are key interventions to curb the spread and emergence of antimicrobial resistance. The current gold standard identification and AST methods provide comprehensive diagnostic information but often take 3 to 5 days. Here, a compound Raman microscopy (CRM), which integrates Raman spectroscopy and stimulated Raman scattering microscopy in one system, is presented and demonstrated for rapid identification and AST of pathogens in urine. We generated an extensive bacterial Raman spectral dataset and applied deep learning to identify common clinical bacterial pathogens. In addition, we employed stimulated Raman scattering microscopy to quantify bacterial metabolic activity to determine their antimicrobial susceptibility. For proof-of-concept, we demonstrated an integrated assay to diagnose urinary tract infection pathogens, S. aureus and E. coli. Notably, the CRM system has the unique ability to provide Gram-staining classification and AST results within ~3 h directly from urine samples and shows great potential for clinical applications.

Quantitative Stimulated Raman Scattering Microscopy: Promises and Pitfalls

Since its first demonstration, stimulated Raman scattering (SRS) microscopy has become a powerful chemical imaging tool that shows promise in numerous biological and biomedical applications. The spectroscopic capability of SRS enables identification and tracking of specific molecules or classes of molecules, often without labeling. SRS microscopy also has the hallmark advantage of signal strength that is directly proportional to molecular concentration, allowing for in situ quantitative analysis of chemical composition of heterogeneous samples with submicron spatial resolution and subminute temporal resolution. However, it is important to recognize that quantification through SRS microscopy requires assumptions regarding both system and sample. Such assumptions are often taken axiomatically, which may lead to erroneous conclusions without proper validation. In this review, we focus on the tacitly accepted, yet complex, quantitative aspect of SRS microscopy. We discuss the various approaches to quantitative analysis, examples of such approaches, challenges in different systems, and potential solutions. Through our examination of published literature, we conclude that a scrupulous approach to experimental design can further expand the powerful and incisive quantitative capabilities of SRS microscopy.

Single Cell Raman Spectroscopy Deuterium Isotope Probing for Rapid Antimicrobial Susceptibility Test of Elizabethkingia spp

Nosocomial infection by multi-drug resistance Elizabethkingia spp. is an emerging concern with severe clinical consequences, particularly in immunocompromised individuals and infants. Efficient control of this infection requires quick and reliable methods to determine the appropriate drugs for treatment. In this study, a total of 31 Elizabethkingia spp., including two standard strains (ATCC 13253 and FMS-007) and 29 clinical isolates obtained from hospitals in China were subjected to single cell Raman spectroscopy analysis coupled with deuterium probing (single cell Raman-DIP). The results demonstrated that single cell Raman-DIP could determine antimicrobial susceptibility of Elizabethkingia spp. in 4 h, only one third of the time required by standard broth microdilution method. The method could be integrated into current clinical protocol for sepsis and halve the report time. The study also confirmed that minocycline and levofloxacin are the first-line antimicrobials for Elizabethkingia spp. infection.

Metabolism-Triggered Colorimetric Sensor Array for Fingerprinting and Antibiotic Susceptibility Testing of Bacteria

The rapid identification and antibiotic susceptibility testing (AST) of bacteria would help us to accurately identify the infectious sources as well as guide the use of antibiotics, which are crucial for improving the survival rate and antimicrobial resistance. Herein, a colorimetric sensor array for bacteria fingerprinting was constructed with d-amino acid (d-AA)-modified gold nanoparticles (AuNPs) as probes (Au/d-AA). Bacteria can metabolize the d-AA, triggering the aggregation of AuNPs. Making use of different metabolic capabilities of bacteria toward different d-AA, eight kinds of bacteria including antibiotic-resistant bacteria and strains of the same bacterial species are successfully differentiated via learning the response patterns. Meanwhile, the sensor array also performs well in quantitative analysis of single bacterium and differentiation of bacteria mixtures. More interestingly, a rapid colorimetric AST approach has been developed based on the Au/d-AA nanoprobes by monitoring the d-AA metabolic activity of bacteria toward various antibiotic treatments. In this regard, the outlined work here would promote clinical practicability and facilitate antibiotic stewardship.

d-Amino Acid-Based Metabolic Labeling Enables a Fast Antibiotic Susceptibility Test of Both Isolated Bacteria and Bronchoalveolar Lavage Fluid

The threat of multidrug-resistant bacteria has escalated rapidly, increasing the demand for accurate antibiotic susceptibility tests (ASTs). Traditional bacterial growth yield-based ASTs often take overnight to report, delaying the timely guidance of antibiotic use. Here, a fluorescent d-amino acid (FDAA) labeling-based AST (FaAST) is reported, which can quickly provide accurate minimum inhibitory concentrations (MICs). The FDAA-labeling signals that reflect the bacterial metabolic status underlie the flow cytometry-based strategy for MIC determination. Resistant bacteria show a reluctant decline in FDAA-labeling (inhibited metabolism) after treatment with the corresponding antibiotics, whereas susceptible bacteria demonstrate quick responses to low doses of drugs. The MICs are determined based on the changing trends in labeling. After testing 23 clinical isolates and laboratory strains of the most critical drug-resistant bacteria against a panel of representative antibiotics, FaAST shows a high susceptibility category with an accuracy of 98.13%. Moreover, FaAST can also make quick and accurate diagnosis against bronchoalveolar lavage fluids collected from hospital-acquired pneumonia patients, saving 2-4 days in guiding antibiotic use for this life-threatening infection. Thus, the speed, accuracy, and broad applicability of FaAST will be valuable in informing antibiotic decisions when treating critical infections caused by drug-resistant bacteria.

A Review of Raman-Based Technologies for Bacterial Identification and Antimicrobial Susceptibility Testing

Antimicrobial resistance (AMR) is a global medical threat that seriously endangers human health. Rapid bacterial identification and antimicrobial susceptibility testing (AST) are key interventions to combat the spread and emergence of AMR. Although current clinical bacterial identification and AST provide comprehensive information, they are labor-intensive, complex, inaccurate, and slow (requiring several days, depending on the growth of pathogenic bacteria). Recently, Raman-based identification and AST technologies have played an increasingly important role in fighting AMR. This review summarizes major Raman-based techniques for bacterial identification and AST, including spontaneous Raman scattering, surface-enhanced Raman scattering (SERS), and coherent Raman scattering (CRS) imaging. Then, we discuss recent developments in rapid identification and AST methods based on Raman technology. Finally, we highlight the major challenges and potential future efforts to improve clinical outcomes through rapid bacterial identification and AST.

A rapid procedure for bacterial identification and antimicrobial susceptibility testing directly from positive blood cultures

There is an urgent need to develop a rapid procedure that can rapidly identify and obtain antimicrobial susceptibility testing (AST) results directly from positive blood cultures. Here, we report a semi-automatic bacterial diagnosis procedure, which includes (1) a bacterial concentration process to isolate bacteria from a positive blood culture bottle (PBCB), (2) an identification process using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS), and (3) a rapid AST process based on stimulated Raman scattering imaging of deuterium oxide (D₂O) incorporation in bacteria. A total of 105 samples were tested for bacterial identification, and a bacterial identification accuracy of 92.3% was achieved. AST takes about 2.5 h after identification. This semi-automatic procedure only takes 3.5 h, which is demonstrated to be the fastest process to obtain identification and AST results starting from PBCBs.

Shot-noise limited tunable dual-vibrational frequency stimulated Raman scattering microscopy

We present a shot-noise limited SRS implementation providing a >200 mW per excitation wavelength that is optimized for addressing two molecular vibrations simultaneously. As the key to producing a 3 ps laser of different colors out of a single fs-laser (15 nm FWHM), we use ultra-steep angle-tunable optical filters to extract 2 narrow-band Stokes laser beams (1-2 nm & 1-2 ps), which are separated by 100 cm^-1. The center part of the fs-laser is frequency doubled to pump an optical parametric oscillator (OPO). The temporal width of the OPO's output (1 ps) is matched to the Stokes beams and can be tuned from 650-980 nm to address simultaneously two Raman shifts separated by 100 cm^-1 that are located between 500 cm^-1 and 5000 cm^-1. We demonstrate background-free SRS imaging of C-D labeled biological samples (bacteria and Drosophila). Furthermore, high quality virtual stimulated Raman histology imaging of a brain adenocarcinoma is shown for pixel dwell times of 16 µs.

Rapid identification of the resistance of urinary tract pathogenic bacteria using deep learning-based spectroscopic analysis

The resistance of urinary tract pathogenic bacteria to various antibiotics is increasing, which requires the rapid detection of infectious pathogens for accurate and timely antibiotic treatment. Here, we propose a rapid diagnosis strategy for the antibiotic resistance of bacteria in urinary tract infections (UTIs) based on surface-enhanced Raman scattering (SERS) using a positively charged gold nanoparticle planar solid SERS substrate. Then, an intelligent identification model for SERS spectra based on the deep learning technique is constructed to realize the rapid, ultrasensitive, and non-labeled detection of pathogenic bacteria. A total of 54,000 SERS spectra were collected from 18 isolates belonging to 6 species of common UTI bacteria in this work to realize identification of bacterial species, antibiotic sensitivity, and multidrug resistance (MDR) via convolutional neural networks (CNN). This method significantly simplify the Raman data processing processes without background removing and smoothing, however, achieving 96% above classification accuracy, which was significantly greater than the 85% accuracy of the traditional multivariate statistical analysis algorithm principal component analysis combined with the K-nearest neighbor (PCA-KNN). This work clearly elucidated the potential of combining SERS and deep learning technique to realize culture-free identification of pathogenic bacteria and their associated antibiotic sensitivity.

Raman Stable Isotope Probing of Bacteria in Visible and Deep UV-Ranges

Raman stable isotope probing (Raman-SIP) is an excellent technique that can be used to access the overall metabolism of microorganisms. Recent studies have mainly used an excitation wavelength in the visible range to characterize isotopically labeled bacteria. In this work, we used UV resonance Raman spectroscopy (UVRR) to evaluate the spectral red-shifts caused by the uptake of isotopes (¹³C, ¹⁵N, ²H(D) and ¹⁸O) in E. coli cells. Moreover, we present a new approach based on the extraction of labeled DNA in combination with UVRR to identify metabolically active cells. The proof-of-principle study on E. coli revealed heterogeneities in the Raman features of both the bacterial cells and the extracted DNA after labeling with ¹³C, ¹⁵N, and D. The wavelength of choice for studying ¹⁸O- and deuterium-labeled cells is 532 nm is, while ¹³C-labeled cells can be investigated with visible and deep UV wavelengths. However, ¹⁵N-labeled cells are best studied at the excitation wavelength of 244 nm since nucleic acids are in resonance at this wavelength. These results highlight the potential of the presented approach to identify active bacterial cells. This work can serve as a basis for the development of new techniques for the rapid and efficient detection of active bacteria cells without the need for a cultivation step.

In Vitro Anticancer Drug Sensitivity Sensing through Single-Cell Raman Spectroscopy

Traditional in vitro anticancer drug sensitivity testing at the population level suffers from lengthy procedures and high false positive rates. To overcome these defects, we built a confocal Raman microscopy sensing system and proposed a single-cell approach via Raman-deuterium isotope probing (Raman-DIP) as a rapid and reliable in vitro drug efficacy evaluation method. Raman-DIP detected the incorporation of deuterium into the cell, which correlated with the metabolic activity of the cell. The human non-small cell lung cancer cell line HCC827 and human breast cancer cell line MCF-7 were tested against eight different anticancer drugs. The metabolic activity of cancer cells could be detected as early as 12 h, independent of cell growth. Incubation of cells in 30% heavy water (D₂O) did not show any negative effect on cell viability. Compared with traditional methods, Raman-DIP could accurately determine the drug effect, meanwhile, it could reduce the testing period from 72–144 h to 48 h. Moreover, the heterogeneity of cells responding to anticancer drugs was observed at the single-cell level. This proof-of-concept study demonstrated the potential of Raman-DIP to be a reliable tool for cancer drug discovery and drug susceptibility testing.

The Role of Raman Spectroscopy Within Quantitative Metabolomics

Ninety-four years have passed since the discovery of the Raman effect, and there are currently more than 25 different types of Raman-based techniques. The past two decades have witnessed the blossoming of Raman spectroscopy as a powerful physicochemical technique with broad applications within the life sciences. In this review, we critique the use of Raman spectroscopy as a tool for quantitative metabolomics. We overview recent developments of Raman spectroscopy for identification and quantification of disease biomarkers in liquid biopsies, with a focus on the recent advances within surface-enhanced Raman scattering-based methods. Ultimately, we discuss the applications of imaging modalities based on Raman scattering as label-free methods to study the abundance and distribution of biomolecules in cells and tissues, including mammalian, algal, and bacterial cells.

Recent developments in Raman spectral analysis of microbial single cells: Techniques and applications

The conventional microbial cell analyses are mostly population-averaged methods that conceal the characteristics of single-cell in the community. Single-cell analysis can provide information on the functional and structural variation of each cell, resulting in the elimination of long and tedious microbial cultivation techniques. Raman spectroscopy is a label-free, noninvasive, and in-vivo method ideal for single-cell measurement to obtain spatially resolved chemical information. In the current review, recent developments in Raman spectroscopic techniques for microbial characterization at the single-cell level are presented, focusing on Raman imaging of single cells to study the intracellular distribution of different components. The review also discusses the limitation and challenges of each technique and put forward some future outlook for improving Raman spectroscopy-based techniques for single-cell analysis. Raman spectroscopic methods at the single-cell level have potential in precision measurements, metabolic analysis, antibiotic susceptibility testing, resuscitation capability, and correlating phenotypic information to genomics for cells, the integration of Raman spectroscopy with other techniques such as microfluidics, stable isotope probing (SIP), and atomic force microscope can further improve the resolution and provide extensive information. Future focuses should be given to advance algorithms for data analysis, standardized reference libraries, and automated cell isolation techniques in future.

Coherent Raman scattering microscopy for chemical imaging of biological systems

Coherent Raman scattering (CRS) processes, including both the coherent anti-Stokes Raman scattering and stimulated Raman scattering, have been utilized in state-of-the-art microscopy platforms for chemical imaging of biological samples. The key advantage of CRS microscopy over fluorescence microscopy is label-free, which is an attractive characteristic for modern biological and medical sciences. Besides, CRS has other advantages such as higher selectivity to metabolites, no photobleaching, and narrow peak width. These features have brought fast-growing attention to CRS microscopy in biological research. In this review article, we will first briefly introduce the history of CRS microscopy, and then explain the theoretical background of the CRS processes in detail using the classical approach. Next, we will cover major instrumentation techniques of CRS microscopy. Finally, we will enumerate examples of recent applications of CRS imaging in biological and medical sciences.

Campylobacter jejuni Antimicrobial Resistance Profiles and Mechanisms Determined Using a Raman Spectroscopy-Based Metabolomic Approach

Rapid identification of antimicrobial resistance (AMR) profiles and mechanisms is critical for clinical management and drug development. However, the current AMR detection approaches take up to 48 h to obtain a result. Here, we demonstrate a Raman spectroscopy-based metabolomic approach to rapidly determine the AMR profile of Campylobacter jejuni, a major cause of foodborne gastroenteritis worldwide. C. jejuni isolates with susceptible and resistant traits to ampicillin and tetracycline were subjected to different antibiotic concentrations for 5 h, followed by Raman spectral collection and chemometric analysis (i.e., second-derivative transformation analysis, hierarchical clustering analysis [HCA], and principal-component analysis [PCA]). The MICs obtained by Raman-2nd derivative transformation agreed with the reference agar dilution method for all isolates. The AMR profile of C. jejuni was accurately classified by Raman-HCA after treating bacteria with antibiotics at clinical susceptible and resistant breakpoints. According to PCA loading plots, susceptible and resistant strains showed different Raman metabolomic patterns for antibiotics. Ampicillin-resistant isolates had distinctive Raman signatures of peptidoglycan, which is related to cell wall synthesis. The ratio of saturated to unsaturated fatty acids in the lipid membrane layer of ampicillin-resistant isolates was higher than in susceptible ones, indicating more rigid envelope structure under ampicillin treatment. In comparison, tetracycline-resistant isolates exhibited prominent Raman spectral features associated with proteins and nucleic acids, demonstrating more active protein synthesis than susceptible strains with the presence of tetracycline. Taken together, Raman spectroscopy is a powerful metabolic fingerprinting technique for simultaneously revealing the AMR profiles and mechanisms of foodborne pathogens. IMPORTANCE Metabolism plays the central role in bacteria to mediate the early response against antibiotics and demonstrate antimicrobial resistance (AMR). Understanding the whole-cell metabolite profiles gives rise to a more complete AMR mechanism insight. In this study, we have applied Raman spectroscopy and chemometrics to achieve a rapid, accurate, and easy-to-operate investigation of bacterial AMR profiles and mechanisms. Raman spectroscopy reduced the analysis time by an order of magnitude to obtain the same results achieved through traditional culture-based antimicrobial susceptibility approaches. It offers great benefits as a high-throughput screening method in food chain surveillance and clinical diagnostics. Meanwhile, the AMR mechanisms toward two representative antibiotic classes, namely, ampicillin and tetracycline, were revealed by Raman spectroscopy at the metabolome level. This approach is based on bacterial phenotypic responses to antibiotics, providing information complementary to that obtained by conventional genetic methods such as genome sequencing. The knowledge obtained from Raman metabolomic data can be used in drug discovery and pathogen intervention.

Rapid antimicrobial susceptibility testing by stimulated Raman scattering metabolic imaging and morphological deformation of bacteria

Methods for rapid antimicrobial susceptibility testing (AST) are urgently needed to address the emergence and spread of antimicrobial resistance. Here, we report a new method based on stimulated Raman scattering (SRS) microscopy, which measures both the metabolic activity and the morphological deformation of bacteria to determine the antimicrobial susceptibility of β-lactam antibiotics rapidly. In this approach, we quantify single bacteria's metabolic activity by the carbon-deuterium (C-D) bond concentrations in bacteria after D₂O incubation. In the meantime, bacterial morphological deformation caused by β-lactam antibiotics is also measured. With these two quantifiable markers, we develop an evaluation method to perform AST of cefotaxime on 103 E. coli strains. Our method achieved a 93.2% categorical agreement and a 93.2% essential agreement with the standard reference method.

Antimicrobial Susceptibility Testing in a Rapid Single Test via an Egg-like Multivolume Microchamber-Based Microfluidic Platform

Fast determination of antimicrobial agents' effectiveness (susceptibility/resistance pattern) is an essential diagnostic step for treating bacterial infections and stopping world-wide outbreaks. Here, we report an egg-like multivolume microchamber-based microfluidic (EL-MVM²) platform, which is used to produce a wide range of gradient-based antibiotic concentrations quickly (∼10 min). The EL-MVM² platform works based upon testing a bacterial suspension in multivolume microchambers (microchamber sizes that range from a volume of 12.56 to 153.86 nL). Antibiotic molecules from a stock solution diffuse into the microchambers of various volumes at the same loading rate, leading to different concentrations among the microchambers. Therefore, we can quickly and easily produce a robust antibiotic gradient-based concentration profile. The EL-MVM² platform's diffusion (loading) pattern was investigated for different antibiotic drugs using both computational fluid dynamics simulations and experimental approaches. With an easy-to-follow protocol for sample loading and operation, the EL-MVM² platform was also found to be of high precision with respect to predicting the susceptibility/resistance outcome (>97%; surpassing the FDA-approval criterion for technology-based antimicrobial susceptibility testing instruments). These features indicate that the EL-MVM² is an effective, time-saving, and precise alternative to conventional antibiotic susceptibility testing platforms currently being used in clinical diagnostics and point-of-care settings.

Bond-selective imaging by optically sensing the mid-infrared photothermal effect

Mid-infrared (IR) spectroscopic imaging using inherent vibrational contrast has been broadly used as a powerful analytical tool for sample identification and characterization. However, the low spatial resolution and large water absorption associated with the long IR wavelengths hinder its applications to study subcellular features in living systems. Recently developed mid-infrared photothermal (MIP) microscopy overcomes these limitations by probing the IR absorption-induced photothermal effect using a visible light. MIP microscopy yields submicrometer spatial resolution with high spectral fidelity and reduced water background. In this review, we categorize different photothermal contrast mechanisms and discuss instrumentations for scanning and widefield MIP microscope configurations. We highlight a broad range of applications from life science to materials. We further provide future perspective and potential venues in MIP microscopy field.

Unveiling Cancer Metabolism through Spontaneous and Coherent Raman Spectroscopy and Stable Isotope Probing

Metabolic reprogramming is a common hallmark in cancer. The high complexity and heterogeneity in cancer render it challenging for scientists to study cancer metabolism. Despite the recent advances in single-cell metabolomics based on mass spectrometry, the analysis of metabolites is still a destructive process, thus limiting in vivo investigations. Being label-free and nonperturbative, Raman spectroscopy offers intrinsic information for elucidating active biochemical processes at subcellular level. This review summarizes recent applications of Raman-based techniques, including spontaneous Raman spectroscopy and imaging, coherent Raman imaging, and Raman-stable isotope probing, in contribution to the molecular understanding of the complex biological processes in the disease. In addition, this review discusses possible future directions of Raman-based technologies in cancer research.

Development of a Fast Raman-Assisted Antibiotic Susceptibility Test (FRAST) for the Antibiotic Resistance Analysis of Clinical Urine and Blood Samples

Human health is at great risk due to the spreading of antimicrobial resistance (AMR). The lengthy procedure of conventional antimicrobial susceptibility testing (AST) usually requires a few days. We developed a fast Raman-assisted antibiotic susceptibility test (FRAST), which detects single bacterial metabolic activity in the presence of antibiotics, using Raman single-cell spectroscopy. It was found that single-cell Raman spectra (SCRS) would show a clear and distinguishable Raman band at the "silent zone" (2000-2300 cm^-1), due to the active incorporation of deuterium from heavy water (D₂O) by antibiotic-resistant bacteria. This pilot study has compared the FRAST and the conventional AST for six clinical standard quality controls (four Gram-negative and two Gram-positive bacteria strains) in response to 38 antibiotics. In total, 3200 treatments have been carried out and approximately 64 000 SCRS have been acquired for FRAST analysis. The result showed an overall agreement of 88.0% between the FRAST and the conventional AST assay. The gram-staining classification based on the linear discriminant analysis (LDA) model of SCRS was developed, seamlessly coupling with the FRAST to further reduce the turnaround time. We applied the FRAST to real clinical analysis for nine urinary infectious samples and three sepsis samples. The results were consistent with MALDI-TOF identification and the conventional AST. Under the optimal conditions, the "sample to report" of the FRAST could be reduced to 3 h for urine samples and 21 h for sepsis samples. The FRAST provides fast and reliable susceptibility tests, which could speed up microbiological analysis for clinical practice and facilitate antibiotic stewardship.

Recent Development of Rapid Antimicrobial Susceptibility Testing Methods through Metabolic Profiling of Bacteria

Due to the inappropriate use and overuse of antibiotics, the emergence and spread of antibiotic-resistant bacteria are increasing and have become a major threat to human health. A key factor in the treatment of bacterial infections and slowing down the emergence of antibiotic resistance is to perform antimicrobial susceptibility testing (AST) of infecting bacteria rapidly to prescribe appropriate drugs and reduce the use of broad-spectrum antibiotics. Current phenotypic AST methods based on the detection of bacterial growth are generally reliable but are too slow. There is an urgent need for new methods that can perform AST rapidly. Bacterial metabolism is a fast process, as bacterial cells double about every 20 to 30 min for fast-growing species. Moreover, bacterial metabolism has shown to be related to drug resistance, so a comparison of differences in microbial metabolic processes in the presence or absence of antimicrobials provides an alternative approach to traditional culture for faster AST. In this review, we summarize recent developments in rapid AST methods through metabolic profiling of bacteria under antibiotic treatment.

Biological small-molecule assays using gradient-based microfluidics

Studying the potency of small-molecules on eukaryotic and prokaryotic cells using conventional biological settings requires time-consuming procedures and large volumes of expensive small-molecules. Microfluidics could significantly expedite these assays by enabling operation in high-throughput and (semi)automated modes. Here, we introduce a microfluidics platform based on multi-volume microchamber arrays that can produce a wide range of small-molecule concentrations with a desired gradient-based profile for rapid and precise biological testing within a single device with minimal hands-on time. The concept behind this device is based on introducing the same amount of a small-molecule into microchambers of different volumes to spontaneously generate a gradient concentration profile via diffusion. This design enables to obtain an unprecedented concentration range (e.g., three orders of magnitude) that can be easily adjusted, allowing us to pinpoint the precise effect of small-molecules on pre-loaded prokaryotic and eukaryotic cells. We also propose a comprehensive relationship for determining the loading time (the only required parameter for implementing this platform) in order to study the effects of any small-molecule on a biological species in a desired test. We demonstrate the versatility of this microfluidics platform by conducting two small-molecule assays-antimicrobial resistance and sugar-phosphate toxicity for both eukaryotic and prokaryotic biological systems.

Klebsiella pneumoniae: Prevalence, Reservoirs, Antimicrobial Resistance, Pathogenicity, and Infection: A Hitherto Unrecognized Zoonotic Bacterium

Klebsiella pneumoniae is considered an opportunistic pathogen, constituting an ongoing health concern for immunocompromised patients, the elderly, and neonates. Reports on the isolation of K. pneumoniae from other sources are increasing, many of which express multidrug-resistant (MDR) phenotypes. Three phylogroups were identified based on nucleotide differences. Niche environments, including plants, animals, and humans appear to be colonized by different phylogroups, among which KpI (K. pneumoniae) is commonly associated with human infection. Infections with K. pneumoniae can be transmitted through contaminated food or water and can be associated with community-acquired infections or between persons and animals involved in hospital-acquired infections. Increasing reports are describing detections along the food chain, suggesting the possibility exists that this could be a hitherto unexplored reservoir for this opportunistic bacterial pathogen. Expression of MDR phenotypes elaborated by these bacteria is due to the nature of various plasmids carrying antimicrobial resistance (AMR)-encoding genes, and is a challenge to animal, environmental, and human health alike. Raman spectroscopy has the potential to provide for the rapid identification and screening of antimicrobial susceptibility of Klebsiella isolates. Moreover, hypervirulent isolates linked with extraintestinal infections express phenotypes that may support their niche adaptation. In this review, the prevalence, reservoirs, AMR, Raman spectroscopy detection, and pathogenicity of K. pneumoniae are summarized and various extraintestinal infection pathways are further narrated to extend our understanding of its adaptation and survival ability in reservoirs, and associated disease risks.