Current and emerging techniques for antibiotic susceptibility tests

Unravelling AMR dynamics in the rumenofaecobiome: Insights, challenges and implications for One Health

Antimicrobial resistance (AMR) is a critical global threat to human, animal and environmental health, exacerbated by horizontal gene transfer (HGT) via mobile genetic elements. This poses significant challenges that have a negative impact on the sustainability of the One Health approach, hindering its long-term viability and effectiveness in addressing the interconnectedness of global health. Recent studies on livestock animals, specifically ruminants, indicate that culturable ruminal bacteria harbour AMR genes with the potential for HGT. However, these studies have focused predominantly on using the faecobiome as a proxy to the rumen microbiome or using easily isolated and culturable bacteria, overlooking the unculturable population. These unculturable microbial groups could have a profound influence on the rumen resistome and AMR dynamics within livestock ecosystems, potentially holding critical insights for advanced understanding of AMR in One Health. In order to address this gap, this review of current research on the burden of AMR in livestock was undertaken, and it is proposed that combined study of the rumen microbiome and faecobiome, termed the 'rumenofaecobiome', should be performed to enhance understanding of the risks of AMR in ruminant livestock. This review discusses the complexities of the rumen microbiome and the risks of AMR transmission in this microbiome in a One Health context. AMR transmission dynamics and methodologies for assessing the risks of AMR in livestock are summarized, and future considerations for researching the impact of AMR in the rumen microbiome and the implications within the One Health framework are discussed.

Microfluidic chip systems for color-based antimicrobial susceptibility test a review

Clinical bacteria pose a significant public health threat, underscoring the need for reliable and rapid diagnostic methods for early disease detection, which can facilitate patient recovery. Current diagnostic methods for rapid pathogen detection often take hours to days and require numerous reagents and lengthy protocols. Microfluidic chip system offers a promising solution for clinical microbiology detection by reducing detection time with minimal setup and providing a point-of-care solution for patients. These systems are also easier to handle and, with advancements in technology, offer more conclusive observations. This review focuses on recent developments in microfluidic chip-based systems that use colored fluorescent and non-fluorescent dyes for phenotypic tests in clinical pathogen detection. Recent advancements in non-conventional observation methods, such as smartphones and software combined with microscopy, are paving the way for microfluidic systems to revolutionize point-of-care devices. Significant challenges for these systems include antimicrobial susceptibility testing protocols, which depend on color formation, observation methods, and reducing detection time. In the future, working with live cultures remains a major hurdle in developing efficient and accurate microfluidic diagnostic systems for antimicrobial susceptibility testing.

Screening, characterization, and potential anti-hangover ability of selenium nanoparticle-enriched lactobacillus

This study aimed to develop a selenium nanoparticles (SeNPs)-enriched probiotic strain with potential anti-hangover effects. Pediococcus acidilactici JW-015 was screened for its high tolerance to inorganic selenium (up to 80 mM sodium selenite) and efficient synthesis of SeNPs, achieving a selenium accumulation concentration of 6974 ± 90.71 μg/g, with SeNPs accounting for 86.54% ± 2.48%. Safety and probiotic properties were evaluated, confirming that JW-015 is a safe probiotic strain and that selenium enrichment enhanced its probiotic properties. Furthermore, JW-015 demonstrated significant anti-hangover efficacy, with selenium enrichment improving the oxidative stress capacity, alcohol tolerance, alcohol degradation ability, and relevant enzyme activities (ADH and ALDH) of the strain. This study provides a promising bio-carrier for SeNPs transformation and expands the applications of selenium-enriched LAB.

Detection of antimicrobial resistance via state-of-the-art technologies versus conventional methods

Antimicrobial resistance (AMR) is recognized as one of the foremost global health challenges, complicating the treatment of infectious diseases and contributing to increased morbidity and mortality rates. Traditionally, microbiological culture and susceptibility testing methods, such as disk diffusion and minimum inhibitory concentration (MIC) assays, have been employed to identify AMR bacteria. However, these conventional techniques are often labor intensive and time consuming and lack the requisite sensitivity for the early detection of resistance. Recent advancements in molecular and genomic technologies-such as next-generation sequencing (NGS), matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS), lateral flow immunoassays (LFIAs), PCR-based diagnostic methods, and CRISPR-based diagnostics-have revolutionized the diagnosis of AMR. These innovative approaches provide increased sensitivity, reduced turnaround times, and the ability to identify genetic resistance mechanisms. This review seeks to examine the advantages and disadvantages of both emerging technologies and traditional methods for detecting AMR, emphasizing the potential benefits and limitations inherent to each. By understanding the strengths and limitations of these technologies, stakeholders, including researchers, healthcare professionals, regulatory agencies, health authorities, financial managers, and patients, can make informed decisions aimed at preventing the emergence and dissemination of antibiotic-resistant strains, thereby ultimately increasing patient safety.

Rapid antimicrobial susceptibility testing using carbon screen printed electrodes in a microfluidic device

The development of rapid, sensitive, and affordable antimicrobial susceptibility testing (AST) is essential for controlling antibiotic overuse, thereby creating a critical checkpoint for the emerging antimicrobial resistance threat. Here, we introduce a novel method of electrochemical monitoring of bacterial growth in a diluted low-conductivity nutrient medium for rapid susceptibility testing using impedance spectroscopy. The method works on the change in charge transfer resistance exhibited by bacteria in response to antibiotics. The proposed Electrochemical Microfluidic device (ε-µD) employs low-cost carbon screen-printed electrodes and uses a simple microfluidic geometry. We explored the utilisation of a diluted nutrient medium as an electrolyte since it provides a higher charge transfer baseline signal for better sensitivity and supports the growth of the bacteria required for detection. The method enables sensitive detection of bacteria even at a low density of 84/mm2 in three hours of incubation time. For proof of concept, bacteria such as Escherichia coli and Bacillus subtilis were used, and the efficacy of the ampicillin and tetracycline drugs were tested. The experiments were done with the spiked urine samples, which correlated well with the controlled sample. The proposed system enhances the accessibility and affordability of rapid susceptibility testing, enabling its widespread use.

Rapid Raman spectroscopy-based test for antimicrobial resistance

Antimicrobial resistance (AMR) is one of the top global health threats. In 2019, AMR was associated with 4.95 million deaths, of which 1.97 million were caused by drug-resistant infections directly. The main subset of AMR is antibiotic resistance, that is, the resistance of bacteria to antibiotic treatment. Traditional and most commonly used antibiotic susceptibility tests are based on the detection of bacterial growth and its inhibition in the presence of an antimicrobial. These tests typically take over 1-2 days to perform, so empirical therapy schemes are often administered before proper testing. Rapid tests for AMR are necessary to optimize the treatment of bacterial infection. Here, we combine the MTT test with Raman spectroscopy to provide a 1.5 h long test for minimal inhibitory concentration determination. Several Escherichia coli and Klebsiella pneumoniae strains were tested with three types of antibiotics, including ampicillin from penicillin family, kanamycin from aminoglycoside family and levofloxacin from fluoroquinolone family. The test provided the same minimal inhibitory concentrations as traditional Etest confirming its robustness.

Advancements of paper-based sensors for antibiotic-resistant bacterial species identification

Evolution of antimicrobial-resistant bacterial species is on a rise. This review aims to explore the diverse range of paper-based platforms designed to identify antimicrobial-resistant bacterial species. It highlights the most important targets used for sensor development and examines the applications of nanosized particles used in paper-based sensors. This review also discusses the advantages, limitations, and applicability of various targets and detection techniques for sensing drug-resistant bacterial species using paper-based platforms.

Rapid Antibiotic Susceptibility Determination by Fluorescence Lifetime Tracking of Bacterial Metabolism

To combat the rise of antibiotic-resistance in bacteria and the resulting effects on healthcare worldwide, new technologies are needed that can perform rapid antibiotic susceptibility testing (AST). Conventional clinical methods for AST rely on growth-based assays, which typically require long incubation times to obtain quantitative results, representing a major bottleneck in the determination of the optimal antibiotic regimen to treat patients. Here, we demonstrate a rapid AST method based on the metabolic activity measured by fluorescence lifetime imaging microscopy (FLIM). Using lab strains and clinical isolates of Escherichia coli with tetracycline-susceptible and resistant phenotypes as models, we demonstrate that changes in metabolic state associated with antibiotic susceptibility can be quantitatively tracked by FLIM. Our results show that the magnitude of metabolic perturbation resulting from antibiotic activity correlates with susceptibility evaluated by conventional metrics. Moreover, susceptible and resistant phenotypes can be differentiated in as short as 10 min after antibiotic exposure. This FLIM-AST (FAST) method can be applied to other antibiotics and provides insights into the nature of metabolic perturbations inside bacterial cells resulting from antibiotic exposure with single cell resolution.

Performance of the LifeScale automated rapid phenotypic antimicrobial susceptibility testing on Gram-negative rods directly from positive blood cultures

Rapid antimicrobial susceptibility testing (rAST) performed directly from blood cultures is essential to influencing the selection of appropriate antibiotics, preferably targeted therapy, for the treatment of bloodstream infections. Affinity Biosensors has developed the LifeScale, a phenotypic rAST system based on microfluidic sensors with a mechanical resonator that measures the mass of individual microbes. The combination of replication, biomass, and population profiling of individual microbes is analyzed to produce rAST results. The performance of the LifeScale was evaluated and compared to our current standard of care (SOC) antimicrobial susceptibility testing (AST) system under clinical conditions. The results indicated that the LifeScale is easy to use and provides rapid, reliable, and accurate AST results in less than 5 h directly from from positive blood cultures containing Gram-negative organisms listed in the current database. For all organism-antibiotic combinations involving polymicrobial cultures, LifeScale showed a resistant result when either mixed isolate was resistant. If these results prove to be robust on further testing, this may justify the reporting of rapid LifeScale results without the need for additional confirmatory testing.

IMPORTANCE

This is the first clinical-based study of a unique technology using microfluidic sensors to generate rapid antimicrobial susceptibility test results directly from blood cultures containing Gram-negative rods. The issue of polymicrobial cultures was also addressed in this study, which, to our knowledge, has not been addressed in publications of other rapid phenotypic AST systems. Overall, LifeScale results compared favorably with the SOC in terms of overall agreement, especially categorical agreement.

Rapid detection of antimicrobial susceptibility of the Bacteroides fragilis group by flow cytometry: A preliminary study

A total of nine Bacteroides fragilis group strains and B. fragilis ATCC 25285 were studied. Six antibiotics were used in the study. Broth dilution method was used for flow cytometry (FCM) analysis. Cell suspensions with antibiotics and antibiotic-free were stained with thiazole orange and propidium iodide (PI) to differentiate dead/live cells. The percentage of dead and live cells was calculated using FCM device. Cut-off values for antibiotics (26,7 %, 35,5 % and 30,2 % for meropenem, AMC and clindamycin, respectively) were calculated for dead/live cell differentiation. A common cut-off value was calculated for bactericidal and bacteriostatic (31,8 % and 25,7 % respectively). The PI staining ratios of the B. fragilis ATCC 25285 calculated in the MIC ranges for each antibiotic were under the cut-off values calculated with clinical isolates. The cut-off values we calculated are compatible with MBC rather than MIC values. The FCM method is one of the candidate methods for antimicrobial susceptibility testing.

Validating the utility of heavy water (Deuterium Oxide) as a potential Raman spectroscopic probe for identification of antibiotic resistance

The impact of microbial infections is increasing over time, and it is one of the major reasons for death in both developed and developing countries. colistin is considered as the antibiotic of last choice for infections brought by major multidrug-resistant (MDR), gram-negative bacteria such as Enterobacter species, Acinetobacter species, and Pseudomonas aeruginosa. Existing approaches to diagnose these resistant species are relatively slow and take up to 2 to 3 days. In this work, we propose a novel interdisciplinary method based on Raman spectroscopy and heavy water to identify colistin-resistant microbes. Our hypothesis is based on the fact that resistant bacteria will be metabolically active in the culture medium containing antibiotics and heavy water, and these bacteria will take up deuterium instead of hydrogen to newly synthesized lipids and proteins. This effect will generate a 'C - D' bond-specific Raman spectral marker. Successful identification of this band in the spectral profile can confirm the presence of colistin-resistant bacteria. We have validated the efficacy of this approach in identifying colistin-resistant bacteria spiked in artificial urine and have compared sensitivity at different bacterial concentrations. Overall findings suggest that heavy water can potentially serve as a suitable Raman probe for identifying metabolically active colistin-resistant bacteria via urine under clinically implementable time and can be used in clinical settings after validation.

Cell morphology as biomarker of carbapenem exposure

Characterizing the physiological response of bacterial cells to antibiotics is crucial for designing diagnostic techniques, treatment choices, and drug development. While bacterial cells at sublethal doses of antibiotics are commonly characterized, the impact of exposure to high concentrations of antibiotics on bacteria after long-term serial exposure and their effect on withdrawal need attention for further characterization. This study investigated the effect of increasing imipenem concentrations on carbapenem-susceptible (S) and carbapenem-resistant (R) E. coli on their growth adaptation and cell surface structure. We exposed the bacterial population to increasing imipenem concentrations through 30 exposure cycles. Cell morphology was observed using a 3D laser scanning confocal microscope (LSCM) and transmission electron microscope (TEM). Results showed that the exposure resulted in significant morphological changes in E. coli (S) cells, while minor changes were seen in E. coli (R) cells. The rod-shaped E. coli (S) gradually transformed into round shapes. Further, the exposed E. coli (S) cells' surface area-to-volume ratio (SA/V) was also significantly different from the control, which is non-exposed E. coli (S). Then, the exposed E. coli (S) cells were re-grown in antibiotic-free environment for 100 growth cycles to determine if the changes in cells were reversible. The results showed that their cell morphology remained round, showing that the cell morphology was not reversible. The morphological response of these cells to imipenem can assist in understanding the resistance mechanism in the context of diagnostics and antibacterial therapies.

Phosphorylation-amplified synchronized droplet microfluidics sensitizes bacterial growth kinetic real-time monitoring

The necessity for rapid and accurate bacterial growth monitoring is imperative across various domains, including healthcare and environmental safety. We introduce the self-synchronized droplet-amplified electrical screening cytometry (SYNC) system, a novel meld of droplet microfluidics and electrochemical amplification tailored for precise bacterial growth kinetic monitoring. SYNC encapsulates single bacteria in picolitre droplets, enabling real-time, fluorescence-free electrochemical monitoring. A specially devised phosphorylation-amplified culture medium translates bacterial metabolic activity into discernible electrical impedance changes. The dual-channel design and a rail-based structure in SYNC facilitate parallel screening and self-synchronization of droplets, addressing the limitations of conventional impedance cytometry. SYNC showcases a 5-fold enhancement in detection sensitivity and reduces 50% of the detection time compared to traditional approaches. Notably, SYNC is pioneering in providing exact initial bacterial concentrations, achieve to 104 bacteria/ml, a capability unmatched by existing real-time techniques measuring electrochemical variations. Along with its robust performance, this earmarks SYNC as a powerful tool for applications such as antibiotic susceptibility testing, food quality monitoring, and real-time water bacteria monitoring, paving the way for enhanced microbial process management and infection control.

Rapid determination of antibiotic susceptibility of clinical isolates of Escherichia coli by SYBR green I/Propidium iodide assay

Infections caused by pathogenic Escherichia coli are a serious threat to human health, while conventional antibiotic susceptibility tests (AST) have a long turn-around time, and rapid antibiotic susceptibility methods are urgently needed to save lives in the clinic, reduce antibiotic misuse and prevent emergence of antibiotic-resistant bacteria. We optimized and validated the feasibility of a novel rapid AST based on SYBR Green I and Propidium Iodide (SGPI-AST) for E. coli drug susceptibility test. A total of 112 clinical isolates of E. coli were collected and four antibiotics (ceftriaxone, cefoxitin, imipenem, meropenem) were selected for testing. Bacterial survival rate of E. coli was remarkably linearly correlated with S value at different OD600 values. After optimizing the antibiotic concentrations, the sensitivity and specificity of SGPI-AST reached 100%/100%, 97.8%/100%, 100%/100% and 98.4%/99% for ceftriaxone, cefoxitin, imipenem and meropenem, respectively, and the corresponding concordances of the SGPI-AST with conventional AST were 1.000, 0.980, 1.000 and 0.979, respectively. The SGPI-AST can rapidly and accurately determine the susceptibility of E. coli clinical isolates to multiple antibiotics in 60 min, and has the potential to be applied to guide the precise selection of antibiotics for clinical management of infections caused by pathogenic E. coli.

Rapid and Simple Morphological Assay for Determination of Susceptibility/Resistance to Combined Ciprofloxacin and Ampicillin, Independently, in Escherichia coli

Current antibiograms cannot discern the particular effect of a specific antibiotic when the bacteria are incubated with a mixture of antibiotics. To prove that this task is achievable, Escherichia coli strains were treated with ciprofloxacin for 45 min, immobilized on a slide and stained with SYBR Gold. In susceptible strains, the nucleoid relative surface started to decrease near the MIC, being progressively condensed as the dose increased. The shrinkage level correlated with the DNA fragmentation degree. Ciprofloxacin-resistant bacilli showed no change. Additionally, E. coli strains were incubated with ampicillin for 45 min and processed similarly. The ampicillin-susceptible strain revealed intercellular DNA fragments that increased with dose, unlike the resistant strain. Co-incubation with both antibiotics revealed that ampicillin did not modify the nucleoid condensation effect of ciprofloxacin, whereas the quinolone partially decreased the background of DNA fragments induced by ampicillin. Sixty clinical isolates, with different combinations of susceptibility-resistance to each antibiotic, were co-incubated with the EUCAST breakpoints of susceptibility of ciprofloxacin and ampicillin. The morphological assay correctly categorized all the strains for each antibiotic in 60 min, demonstrating the feasible independent evaluation of a mixture of quinolone and beta-lactam. The rapid phenotypic assay may shorten the incubation times and necessary microbial mass currently required for evaluation.

Recent Advances in Crimean-Congo Hemorrhagic Fever Virus Detection, Treatment, and Vaccination: Overview of Current Status and Challenges

Crimean-Congo hemorrhagic fever virus (CCHFV) is a tick-borne virus, and zoonosis, and affects large regions of Asia, Southwestern and Southeastern Europe, and Africa. CCHFV can produce symptoms, including no specific clinical symptoms, mild to severe clinical symptoms, or deadly infections. Virus isolation attempts, antigen-capture enzyme-linked immunosorbent assay (ELISA), and reverse transcription polymerase chain reaction (RT-PCR) are all possible diagnostic tests for CCHFV. Furthermore, an efficient, quick, and cheap technology, including biosensors, must be designed and developed to detect CCHFV. The goal of this article is to offer an overview of modern laboratory tests available as well as other innovative detection methods such as biosensors for CCHFV, as well as the benefits and limits of the assays. Furthermore, confirmed cases of CCHF are managed with symptomatic assistance and general supportive care. This study examined the various treatment modalities, as well as their respective limitations and developments, including immunotherapy and antivirals. Recent biotechnology advancements and the availability of suitable animal models have accelerated the development of CCHF vaccines by a substantial margin. We examined a range of potential vaccines for CCHF in this research, comprising nucleic acid, viral particles, inactivated, and multi-epitope vaccines, as well as the present obstacles and developments in this field. Thus, the purpose of this review is to present a comprehensive summary of the endeavors dedicated to advancing various diagnostic, therapeutic, and preventive strategies for CCHF infection in anticipation of forthcoming hazards.

Can flow cytometric measurements of reactive oxygen species levels determine minimal inhibitory concentrations and antibiotic susceptibility testing for Acinetobacter baumannii?

Current antimicrobial susceptibility testing (AST) requires 16-24 hours, delaying initiation of appropriate antibiotics. Hence, there is a need for rapid AST. This study aims to develop and evaluate the feasibility of a rapid flow cytometric AST assay to determine minimum inhibitory concentration (MIC) for carbapenem-resistant Acinetobacter baumannii (CRAB). Antibiotic exposure causes increased intracellular reactive oxygen species (ROS) in bacteria. We hypothesized that ROS can be used as a marker to determine MIC. We assessed three CRAB clinical isolates across fifteen antibiotics at various concentrations in a customized 96-well microtiter plate. The antibiotics assessed include amikacin, beta-lactams (ampicillin/sulbactam, aztreonam, cefepime, ceftolozane/tazobactam, doripenem, imipenem, meropenem, and piperacillin/tazobactam), levofloxacin, polymyxin B, rifampicin, trimethoprim/sulfamethoxazole, and tetracyclines (tigecycline and minocycline). These clinical CRAB isolates were assessed for ROS after antibiotic treatment. Increased ROS levels indicated by increased RedoxSensorTM Green (RSG) fluorescence intensity was assessed using flow cytometry (FCM). MIC was set as the lowest antibiotic concentration that gives a ≥1.5-fold increase in mode RSG fluorescence intensity (MICRSG). Accuracy of MICRSG was determined by comparing against microtiter broth dilution method performed under CLSI guidelines. ROS was deemed accurate in determining the MICs for β-lactams (83.3% accuracy) and trimethoprim/sulfamethoxazole (100% accuracy). In contrast, ROS is less accurate in determining MICs for levofloxacin (33.3% accuracy), rifampicin (0% accuracy), amikacin (33.3% accuracy), and tetracyclines (33.3% accuracy). Collectively, this study described an FCM-AST assay to determine antibiotic susceptibility of CRAB isolates within 5 hours, reducing turnaround time up to 19 hours.

Significant reduction of the culturing time required for bacterial identification and antibiotic susceptibility determination by infrared spectroscopy

Rapid testing of bacteria for antibiotic susceptibility is essential for effective treatment and curbing the emergence of multidrug-resistant bacteria. The misuse of antibiotics, coupled with the time-consuming classical testing methods, intensifies the threat of antibiotic resistance, a major global health concern. In this study, employing infrared spectroscopy-based machine learning techniques, we significantly shortened the time required for susceptibility testing to 10 hours, a significant improvement from the 24 hours in our previous studies as well as the conventional methods that typically take at least 48 hours. This remarkable reduction in turnaround time (from 48 hours to 10 hours), achieved by minimizing the culturing period, offers a game-changing advantage for clinical applications. Our study involves a dataset comprising 400 bacterial samples (200 E. coli, 100 Klebsiella pneumoniae, and 100 Pseudomonas aeruginosa) with an impressive 96% accuracy in the taxonomic classification at the species level and up to 82% accuracy in bacterial susceptibility to various antibiotics.

Unexpected decrease in necrotizing enterocolitis morbidity during the COVID-19 pandemic-A single-centre retrospective study

Background

The impact of the coronavirus disease 2019 (COVID-19) pandemic on neonatal necrotizing enterocolitis (NEC) is not well characterised. This cross-sectional study evaluated the potential effects of pandemic-related measures on NEC morbidity in premature infants in a neonatal ward during the COVID-19 pandemic.

Methods

This was a retrospective study conducted in a tertiary neonatal ward in eastern and central China over 6 consecutive years (2017, 2018, 2019, 2020, 2021 and 2022). The medical records of 189 premature infants with stage II or III NEC were reviewed for clinical manifestations and aetiologies. The data were analysed and compared between the prepandemic period (2017, 2018, and 2019) and the pandemic period (2020, 2021 and 2022).

Results

A total of 9,903 infants with gestational age (GA) < 37 weeks were enrolled, including 5,382 in the prepandemic period and 4,521 in the pandemic period. A reduction in stage II or III NEC morbidity was observed in infants with GA < 37 weeks, with an average annual morbidity of 2.29% (123/5,382) (95% CI, 1.89%-2.68%) in the prepandemic period and 1.46% (66/4,521) (95% CI, 1.11%-1.81%) in the pandemic period. NEC morbidity showed resurgent characteristics in 2021. When prepandemic coinfections were excluded, most cases of NEC with bloodstream infections in the prepandemic period were attributable to Gram-negative bacteria (27/32, 84.38%), mainly Klebsiella pneumoniae, while in the pandemic period they were attributable to Gram-positive bacteria (10/18, 55.56%), mainly Staphylococcus aureus. Antimicrobial susceptibility testing revealed that Klebsiella pneumoniae was 100% sensitive to meropenem, imipenem, ciprofloxacin and levofloxacin and 100% resistant to ampicillin. Staphylococcus capitis was 100% sensitive to vancomycin, linezolid, tetracycline, cotrimoxazole and cefoxitin and 100% resistant to penicillin and benzathine.

Conclusions

COVID-19 pandemic-related interventions can reduce the morbidity of NEC and change the pathogen spectrum in patients with bloodstream infections. We need to understand the exact factors leading to these changes.

Relative quantification of the recA gene for antimicrobial susceptibility testing in response to ciprofloxacin for pathogens of concern

Antimicrobial resistance (AR) is one of the greatest threats to global health and is associated with higher treatment costs, longer hospital stays, and increased mortality. Current gold standard antimicrobial susceptibility tests (AST) rely on organism growth rates that result in prolonged time-to-answer for slow growing organisms. Changes in the cellular transcriptome can be rapid in the presence of stressors such as antibiotic pressure, providing the opportunity to develop AST towards transcriptomic signatures. Here, we show that relative quantification of the recA gene is an indicator of pathogen susceptibly when select species are challenged with relevant concentrations of ciprofloxacin. We demonstrate that ciprofloxacin susceptible strains of Y. pestis and B. anthracis have significant increases in relative recA gene expression after 15 min of exposure while resistant strains show no significant differences. Building upon this data, we designed and optimized seven duplex RT-qPCR assays targeting the recA and 16S rRNA gene, response and housekeeping genes, respectively, for multiple biothreat and ESKAPE pathogens. Final evaluation of all seven duplex assays tested against 124 ciprofloxacin susceptible and resistant strains, including Tier 1 pathogens, demonstrated an overall categorical agreement compared to microbroth dilution of 97% using a defined cutoff. Testing pathogen strains commonly associated with urinary tract infections in contrived mock sample sets demonstrated an overall categorical agreement of 96%. These data indicate relative quantification of a single highly conserved gene accurately determines susceptibility for multiple bacterial species in response to ciprofloxacin.

Rapid and Accurate Antimicrobial Susceptibility Testing Using Label-Free Electrical Impedance-Based Microfluidic Platform

Antimicrobial resistance has become a serious threat to the global public health. Accurate and rapid antimicrobial susceptibility testing (AST) allows evidence-based prescribing of antibiotics to improve patient care and clinical outcomes. Current culture-based AST assays are inherently limited by the doubling time of bacterial reproduction, which require at least 24 h to have a decisive result. Herein, a label-free electrical impedance-based microfluidic platform designed to expedite and streamline AST procedure for clinical practice is presented. Following a 30-min exposure of bacterial samples to antibiotics, the presented high-throughput, single-bacterium level impedance characterization platform enables a rapid 2-min AST assay. The platform facilitates accurate analysis of individual bacterial viability, as indicated by changes in electrical characteristics, thereby enabling the determination of antimicrobial resistance. Moreover, the potential clinical applicability of this platform is demonstrated by testing different E. coli strains against five antibiotics, yielding 100% categorical agreements compared to standard culture methods.

Inoculum size-insensitive susceptibility determination of urine sample based on in-situ measurement of inducible enzyme activity after 20 min of antibiotic exposure

BACKGROUND

The empirical antibiotic therapies for bacterial infections cause the emergence and propagation of multi-drug resistant bacteria, which not only impair the effectiveness of existing antibiotics but also raise healthcare costs. To reduce the empirical treatments, rapid antimicrobial susceptibility testing (AST) of causative microorganisms in clinical samples should be conducted for prescribing evidence-based antibiotics. However, most of culture-based ASTs suffer from inoculum effect and lack differentiation of target pathogen and commensals, hampering their adoption for evidence-based antibiotic prescription. Therefore, rapid ASTs which can specifically determine pathogens' susceptibilities, regardless of the bacterial load in clinical samples, are in urgent need.

RESULTS

We present a pathogen-specific and inoculum size-insensitive AST to achieve the reliable susceptibility determination on Escherichia coli (E. coli) in urine samples. The developed AST is featured with an 1 h sample-to-result workflow in a filter, termed on-filter AST. The AST results can be obtained by using an inducible enzymatic assay to in-situ measure the cell response of E. coli collected from urine after 20 min of antibiotic exposure. The calculated detection limit of our AST (1.95 × 104 CFU/mL) is much lower than the diagnosis threshold of urinary tract infections. The specific expression of the inducible enzyme enables on-filter AST to correctly profile the susceptibilities of target pathogen to multi-type antibiotics without the interference from commensals. We performed the on-filter AST on 1 mL urine samples with bacterial loads varying from 105 CFU/mL to 107 CFU/mL and compared the results to that of standard method, demonstrating its insensitivity to inoculum size.

SIGNIFICANCE

The developed AST is demonstrated to be of high sensitivity, specificity, and insensitive to inoculum size. With further developments for additional bacteria and clinical validation, on-filter AST is promising as a rapid and reliable surrogate of culture-based AST to promote the evidence-based prescription at the first visit and minimize the emergency of new multi-drug resistant microorganisms.

Enzymatic Antimicrobial Susceptibility Testing with Bacteria Identification in 30 min

Rapid antimicrobial susceptibility testing (AST) with the ability of bacterial identification is urgently needed for evidence-based antibiotic prescription. Herein, we propose an enzymatic AST (enzyAST) that employs β-d-glucuronidase as a biomarker to identify pathogens and profile phenotypic susceptibilities simultaneously. EnzyAST enables to offer binary AST results within 30 min, much faster than standard methods (>16 h). The general applicability of enzyAST was verified by testing the susceptibility of two Escherichia coli strains to three antibiotics with different action mechanisms. The pilot study also shows that the minimal inhibitory concentrations can be determined by enzyAST with the statistical analysis of enzymatic activity of the bacteria population exposed to varying antibiotic concentrations. With further development of multiple bacteria and sample treatment, enzyAST could be able to evaluate the susceptibility of pathogens in clinical samples directly to facilitate the evidence-based therapy.

Accurate Prediction of Antimicrobial Susceptibility for Point-of-Care Testing of Urine in Less than 90 Minutes via iPRISM Cassettes

The extensive and improper use of antibiotics has led to a dramatic increase in the frequency of antibiotic resistance among human pathogens, complicating infectious disease treatments. In this work, a method for rapid antimicrobial susceptibility testing (AST) is presented using microstructured silicon diffraction gratings integrated into prototype devices, which enhance bacteria-surface interactions and promote bacterial colonization. The silicon microstructures act also as optical sensors for monitoring bacterial growth upon exposure to antibiotics in a real-time and label-free manner via intensity-based phase-shift reflectometric interference spectroscopic measurements (iPRISM). Rapid AST using clinical isolates of Escherichia coli (E. coli) from urine is established and the assay is applied directly on unprocessed urine samples from urinary tract infection patients. When coupled with a machine learning algorithm trained on clinical samples, the iPRISM AST is able to predict the resistance or susceptibility of a new clinical sample with an Area Under the Receiver Operating Characteristic curve (AUC) of ∼ 0.85 in 1 h, and AUC > 0.9 in 90 min, when compared to state-of-the-art automated AST methods used in the clinic while being an order of magnitude faster.

Current and Future Technologies for the Detection of Antibiotic-Resistant Bacteria

Antibiotic resistance is a global public health concern, posing a significant threat to the effectiveness of antibiotics in treating bacterial infections. The accurate and timely detection of antibiotic-resistant bacteria is crucial for implementing appropriate treatment strategies and preventing the spread of resistant strains. This manuscript provides an overview of the current and emerging technologies used for the detection of antibiotic-resistant bacteria. We discuss traditional culture-based methods, molecular techniques, and innovative approaches, highlighting their advantages, limitations, and potential future applications. By understanding the strengths and limitations of these technologies, researchers and healthcare professionals can make informed decisions in combating antibiotic resistance and improving patient outcomes.

Development of a Polymicrobial Checkerboard Assay as a Tool for Determining Combinatorial Antibiotic Effectiveness in Polymicrobial Communities

The checkerboard assay is a well-established tool used to determine the antimicrobial effects of two compounds in combination. Usually, data collected from the checkerboard assay use visible turbidity and optical density as a readout. While helpful in traditional checkerboard assays, these measurements become less useful in a polymicrobial context as they do not enable assessment of the drug effects on the individual members of the community. The methodology described herein allows for the determination of cell viability through selective and differential plating of each individual species in a community while retaining much of the high-throughput nature of a turbidity-based analysis and requiring no specialized equipment. This methodology further improves turbidity-based measurements by providing a distinction between bacteriostatic versus bactericidal concentrations of antibiotics. Herein, we use this method to demonstrate that the clinically used antibiotic combination of ceftazidime and gentamicin works synergistically against Pseudomonas aeruginosa in monoculture but antagonistically in a polymicrobial culture also containing Acinetobacter baumannii, Staphylococcus aureus, and Enterococcus faecalis, highlighting the fundamental importance of this methodology in improving clinical practices. We propose that this method could be implemented in clinical microbiology laboratories with minimal impact on the overall time for diagnosis.

A Review of Carbapenem Resistance in Enterobacterales and Its Detection Techniques

Infectious disease outbreaks have caused thousands of deaths and hospitalizations, along with severe negative global economic impacts. Among these, infections caused by antimicrobial-resistant microorganisms are a major growing concern. The misuse and overuse of antimicrobials have resulted in the emergence of antimicrobial resistance (AMR) worldwide. Carbapenem-resistant Enterobacterales (CRE) are among the bacteria that need urgent attention globally. The emergence and spread of carbapenem-resistant bacteria are mainly due to the rapid dissemination of genes that encode carbapenemases through horizontal gene transfer (HGT). The rapid dissemination enables the development of host colonization and infection cases in humans who do not use the antibiotic (carbapenem) or those who are hospitalized but interacting with environments and hosts colonized with carbapenemase-producing (CP) bacteria. There are continuing efforts to characterize and differentiate carbapenem-resistant bacteria from susceptible bacteria to allow for the appropriate diagnosis, treatment, prevention, and control of infections. This review presents an overview of the factors that cause the emergence of AMR, particularly CRE, where they have been reported, and then, it outlines carbapenemases and how they are disseminated through humans, the environment, and food systems. Then, current and emerging techniques for the detection and surveillance of AMR, primarily CRE, and gaps in detection technologies are presented. This review can assist in developing prevention and control measures to minimize the spread of carbapenem resistance in the human ecosystem, including hospitals, food supply chains, and water treatment facilities. Furthermore, the development of rapid and affordable detection techniques is helpful in controlling the negative impact of infections caused by AMR/CRE. Since delays in diagnostics and appropriate antibiotic treatment for such infections lead to increased mortality rates and hospital costs, it is, therefore, imperative that rapid tests be a priority.

Antibacterial effects of single phage and phage cocktail against multidrug-resistant Klebsiella pneumoniae isolated from diabetic foot ulcer

Diabetic foot ulcer (DFU) is associated with long-term hospitalization and amputation. Antibiotic resistance has made the infection eradication more difficult. Hence, seeking alternative therapies such as phage therapy seems necessary. Bacteriophages are viruses targeting specific bacterial species. Klebsiella pneumoniae (K. pneumoniae) is among causative agents of the DFU. In this study, the therapeutic effects of single phage and phage cocktail were investigated against multidrug-resistant (MDR) K. pneumonia isolated from DFU. Bacteriophages were isolated from animal feces and sewage samples, and were enriched and propagated using K. pneumoniae as the host. Thirty K. pneumoniae clinical isolates were collected from hospitalized patients with DFU. The antibiotic susceptibility pattern was determined using agar disk diffusion test. The phages' morphological traits were determined using transmission electron microscopy (TEM). The killing effect of isolated phages was assessed using plaque assay. Four phage types were isolated and recognized including KP1, KP2, KP3, and KP4. The bacterial rapid regrowth was observed following each single phage-host interaction, but not phage cocktail due to the evolution of mutant strains. Phage cocktail demonstrated significantly higher antibacterial activity than each single phage (p < 0.05) without any bacterial regrowth. The employment of phage cocktail was promising for the eradication of MDR-K. pneumoniae isolates. The development of phage therapy in particular, phage cocktail is promising as an efficient approach to eradicate MDR-K. pneumoniae isolated from DFU. The application of a specific phage cocktail can be investigated to try and achieve the eradication of various infections.

Direct single-cell antimicrobial susceptibility testing of Escherichia coli in urine using a ready-to-use 3D microwell array chip

Empirical antibiotic therapies are prescribed for treating uncomplicated urinary tract infections (UTIs) due to the long turnaround time of conventional antimicrobial susceptibility testing (AST), leading to the prevalence of multi-drug resistant pathogens. We present a ready-to-use 3D microwell array chip to directly conduct comprehensive AST of pathogenic agents in urine at the single-cell level. The developed device features a highly integrated 3D microwell array, offering a dynamic range from 10² to 10⁷ CFU mL^-1, and a capillary valve-based flow distributor for flow equidistribution in dispensing channels and uniform sample distribution. The chip with pre-loaded reagents and negative pressure inside only requires the user to initiate AST by loading samples (∼3 s) and can work independently. We demonstrate an accessible sample-to-result workflow, including syringe filter-based bacteria separation and rapid single-cell AST on chip, which enables us to bypass the time-consuming bacteria isolation and pre-culture, speeding up the AST in ∼3 h from 2 days of conventional methods. Moreover, the bacterial concentration and AST with minimum inhibitory concentrations can be assessed simultaneously to provide comprehensive information on infections. With further development for multiple antibiotic conditions, the Dsc-AST assay could contribute to timely prescription of targeted drugs for better patient outcomes and mitigation of the threat of drug-resistant bacteria.

The use of matrix-assisted laser desorption/ionization mass spectrometry in enzyme activity assays and its position in the context of other available methods

Activity assays are indispensable for studying biochemical properties of enzymes. The purposes of measuring activity are wide ranging from a simple detection of the presence of an enzyme to kinetic experiments evaluating the substrate specificity, reaction mechanisms, and susceptibility to inhibitors. Common activity assay methods include spectroscopy, electrochemical sensors, or liquid chromatography coupled with various detection techniques. This review focuses on the use of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) as a growing and modern alternative, which offers high speed of analysis, sensitivity, versatility, possibility of automation, and cost-effectiveness. It may reveal reaction intermediates, side products or measure more enzymes at once. The addition of an internal standard or calculating the ratios of the substrate and product peak intensities and areas overcome the inherent inhomogeneous distribution of analyte and matrix in the sample spot, which otherwise results in a poor reproducibility. Examples of the application of MALDI-TOF MS for assaying hydrolases (including peptidases and β-lactamases for antibiotic resistance tests) and other enzymes are provided. Concluding remarks summarize advantages and challenges coming from the present experience, and draw future perspectives such as a screening of large libraries of chemical compounds for their substrate or inhibitory properties towards enzymes.

Fiber-integrated cantilever-based nanomechanical biosensors as a tool for rapid antibiotic susceptibility testing

There is an urgent need for developing rapid and affordable antibiotic susceptibility testing (AST) technologies to inhibit the overuse of antibiotics. In this study, a novel microcantilever nanomechanical biosensor based on Fabry-Pérot interference demodulation was developed for AST. To construct the biosensor, a cantilever was integrated with the single mode fiber in order to form the Fabry-Pérot interferometer (FPI). After the attachment of bacteria on the cantilever, the fluctuations of cantilever caused by the bacterial movements were detected by monitoring the changes of resonance wavelength in the interference spectrum. We applied this methodology to Escherichia coli and Staphylococcus aureus, showing the amplitude of cantilever's fluctuations was positively related on the quantity of bacteria immobilized on the cantilever and associated with the bacterial metabolism. The response of bacteria to antibiotics was dependent on the types of bacteria, the types and concentrations of antibiotics. Moreover, the minimum inhibitory and bactericidal concentrations for Escherichia coli were obtained within 30 minutes, demonstrating the capacity of this method for rapid AST. Benefiting from the simplicity and portability of the optical fiber FPI-based nanomotion detection device, the developed nanomechanical biosensor in this study provides a promising technique for AST and a more rapid alternative for clinical laboratories.

Nanoparticle-Based Plasmonic Biosensor for the Unamplified Genomic Detection of Carbapenem-Resistant Bacteria

Antimicrobial resistance (AMR) is a global public health issue, and the rise of carbapenem-resistant bacteria needs attention. While progress is being made in the rapid detection of resistant bacteria, affordability and simplicity of detection still need to be addressed. This paper presents a nanoparticle-based plasmonic biosensor for detecting the carbapenemase-producing bacteria, particularly the beta-lactam Klebsiella pneumoniae carbapenemase (bla_KPC) gene. The biosensor used dextrin-coated gold nanoparticles (GNPs) and an oligonucleotide probe specific to bla_KPC to detect the target DNA in the sample within 30 min. The GNP-based plasmonic biosensor was tested in 47 bacterial isolates: 14 KPC-producing target bacteria and 33 non-target bacteria. The stability of GNPs, confirmed by the maintenance of their red appearance, indicated the presence of target DNA due to probe-binding and GNP protection. The absence of target DNA was indicated by the agglomeration of GNPs, corresponding to a color change from red to blue or purple. The plasmonic detection was quantified with absorbance spectra measurements. The biosensor successfully detected and differentiated the target from non-target samples with a detection limit of 2.5 ng/μL, equivalent to ~10³ CFU/mL. The diagnostic sensitivity and specificity were found to be 79% and 97%, respectively. The GNP plasmonic biosensor is simple, rapid, and cost-effective in detecting bla_KPC-positive bacteria.

Genomic Insights and Functional Analysis Reveal Plant Growth Promotion Traits of Paenibacillus mucilaginosus G78

Paenibacillus mucilaginosus has widely been reported as a plant growth-promoting rhizobacteria (PGPR). However, the important genomic insights into plant growth promotion in this species remain undescribed. In this study, the genome of P. mucilaginosus G78 was sequenced using Illumina NovaSeq PE150. It contains 8,576,872 bp with a GC content of 58.5%, and was taxonomically characterized. Additionally, a total of 7337 genes with 143 tRNAs, 41 rRNAs, and 5 ncRNAs were identified. This strain can prohibit the growth of the plant pathogen, but also has the capability to form biofilm, solubilize phosphate, and produce IAA. Twenty-six gene clusters encoding secondary metabolites were identified, and the genotypic characterization indirectly proved its resistant ability to ampicillin, bacitracin, polymyxin and chloramphenicol. The putative exopolysaccharide biosynthesis and biofilm formation gene clusters were explored. According to the genetic features, the potential monosaccharides of its exopolysaccharides for P. mucilaginosus G78 may include glucose, mannose, galactose, fucose, that can probably be acetylated and pyruvated. Conservation of the pelADEFG compared with other 40 Paenibacillus species suggests that Pel may be specific biofilm matrix component in P. mucilaginosus. Several genes relevant to plant growth-promoting traits, i.e., IAA production and phosphate solubilization are well conserved compared with other 40 other Paenibacillus strains. The current study can benefit for understanding the plant growth-promoting traits of P. mucilaginosus as well as its potential application in agriculture as PGPR.

Identification of pathogens and detection of antibiotic susceptibility at single-cell resolution by Raman spectroscopy combined with machine learning

Rapid, accurate, and label-free detection of pathogenic bacteria and antibiotic resistance at single-cell resolution is a technological challenge for clinical diagnosis. Overcoming the cumbersome culture process of pathogenic bacteria and time-consuming antibiotic susceptibility assays will significantly benefit early diagnosis and optimize the use of antibiotics in clinics. Raman spectroscopy can collect molecular fingerprints of pathogenic bacteria in a label-free and culture-independent manner, which is suitable for pathogen diagnosis at single-cell resolution. Here, we report a method based on Raman spectroscopy combined with machine learning to rapidly and accurately identify pathogenic bacteria and detect antibiotic resistance at single-cell resolution. Our results show that the average accuracy of identification of 12 species of common pathogenic bacteria by the machine learning method is 90.73 ± 9.72%. Antibiotic-sensitive and antibiotic-resistant strains of Acinetobacter baumannii isolated from hospital patients were distinguished with 99.92 ± 0.06% accuracy using the machine learning model. Meanwhile, we found that sensitive strains had a higher nucleic acid/protein ratio and antibiotic-resistant strains possessed abundant amide II structures in proteins. This study suggests that Raman spectroscopy is a promising method for rapidly identifying pathogens and detecting their antibiotic susceptibility.

A 3D-printed microfluidic gradient generator with integrated photonic silicon sensors for rapid antimicrobial susceptibility testing

With antimicrobial resistance becoming a major threat to healthcare settings around the world, there is a paramount need for rapid point-of-care antimicrobial susceptibility testing (AST) diagnostics. Unfortunately, most currently available clinical AST tools are lengthy, laborious, or are simply inappropriate for point-of-care testing. Herein, we design a 3D-printed microfluidic gradient generator that automatically produces two-fold dilution series of clinically relevant antimicrobials. We first establish the compatibility of these generators for classical AST (i.e., broth microdilution) and then extend their application to include a complete on-chip label-free and phenotypic AST. This is accomplished by the integration of photonic silicon chips, which provide a preferential surface for microbial colonization and allow optical tracking of bacterial behavior and growth at a solid-liquid interface in real-time by phase shift reflectometric interference spectroscopic measurements (PRISM). Using Escherichia coli and ciprofloxacin as a model pathogen-drug combination, we successfully determine the minimum inhibitory concentration within less than 90 minutes. This gradient generator-based PRISM assay provides an integrated AST device that is viable for convenient point-of-care testing and offers a promising and most importantly, rapid alternative to current clinical practices, which extend to 8-24 h.

Overcoming Antibiotic Resistance with Novel Paradigms of Antibiotic Selection

Conventional antimicrobial susceptibility tests, including phenotypic and genotypic methods, are insufficiently accurate and frequently fail to identify effective antibiotics. These methods predominantly select therapies based on the antibiotic response of only the lead bacterial pathogen within pure bacterial culture. However, this neglects the fact that, in the majority of human infections, the lead bacterial pathogens are present as a part of multispecies communities that modulate the response of these lead pathogens to antibiotics and that multiple pathogens can contribute to the infection simultaneously. This discrepancy is a major cause of the failure of antimicrobial susceptibility tests to detect antibiotics that are effective in vivo. This review article provides a comprehensive overview of the factors that are missed by conventional antimicrobial susceptibility tests and it explains how accounting for these methods can aid the development of novel diagnostic approaches.

YOLO Algorithm for Long-Term Tracking and Detection of Escherichia Coli at Different Depths of Microchannels Based on Microsphere Positioning Assistance

The effect evaluation of the antibiotic susceptibility test based on bacterial solution is of great significance for clinical diagnosis and prevention of antibiotic abuse. Applying a microfluidic chip as the detection platform, the detection method of using microscopic images to observe bacteria under antibiotic can greatly speed up the detection time, which is more suitable for high-throughput detection. However, due to the influence of the depth of the microchannel, there are multiple layers of bacteria under the focal depth of the microscope, which greatly affects the counting and recognition accuracy and increases the difficulty of relocation of the target bacteria, as well as extracting the characteristics of bacterial liquid changes under the action of antibiotics. After the focal depth of the target bacteria is determined, although the z-axis can be controlled with the help of a three-dimensional micro-operator, the equipment is difficult to operate and the long-term changes of the target bacteria cannot be tracked quickly and accurately. In this paper, the YOLOv5 algorithm is adopted to accurately identify bacteria with different focusing states of multi-layer bacteria at the z-axis with any focal depth. In the meantime, a certain amount of microspheres were mixed into bacteria to assist in locating bacteria, which was convenient for tracking the growth state of bacteria over a long period, and the recognition rates of both bacteria and microspheres were high. The recognition accuracy and counting accuracy of bacteria are 0.734 and 0.714, and the two recognition rates of microspheres are 0.910 and 0.927, respectively, which are much higher than the counting accuracy of 0.142 for bacteria and 0.781 for microspheres with the method of enhanced depth of field (EDF method). Moreover, during long-term bacterial tracking and detection, target bacteria at multiple z-axis focal depth positions can be recorded by the aid of microspheres as a positioning aid for 3D reconstruction, and the focal depth positions can be repositioned within 3-10 h. The structural similarity (SSIM) of microscopic image structure differences at the same focal depth fluctuates between 0.960 and 0.975 at different times, and the root-mean-square error (RMSE) fluctuates between 8 and 12, which indicates that the method also has good relocation accuracy. Thus, this method provides the basis for rapid, high-throughput, and long-term analysis of microscopic changes (e.g., morphology, size) of bacteria detection under the addition of antibiotics with different concentrations based on microfluidic channels in the future.

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.

Highly Accurate Identification of Bacteria's Antibiotic Resistance Based on Raman Spectroscopy and U-Net Deep Learning Algorithms

Bacterial pathogens especially antibiotic-resistant ones are a public health concern worldwide. To oppose the morbidity and mortality associated with them, it is critical to select an appropriate antibiotic by performing a rapid bacterial diagnosis. Using a combination of Raman spectroscopy and deep learning algorithms to identify bacteria is a rapid and reliable method. Nevertheless, due to the loss of information during training a model, some deep learning algorithms suffer from low accuracy. Herein, we modify the U-Net architecture to fit our purpose of classifying the one-dimensional Raman spectra. The proposed U-Net model provides highly accurate identification of the 30 isolates of bacteria and yeast, empiric treatment groups, and antimicrobial resistance, thanks to its capability to concatenate and copy important features from the encoder layers to the decoder layers, thereby decreasing the data loss. The accuracies of the model for the 30-isolate level, empiric treatment level, and antimicrobial resistance level tasks are 86.3, 97.84, and 95%, respectively. The proposed deep learning model has a high potential for not only bacterial identification but also for other diagnostic purposes in the biomedical field.

Antibiotic Susceptibility of Bacterial Pathogens That Infect Olive Flounder (Paralichthys olivaceus) Cultivated in Korea

Paralichthys olivaceus (olive flounder) is widely cultivated in Korea. However, data on the antibiotic susceptibility of bacterial pathogens that infect olive flounders in Korea are limited. The susceptibility of 84 strains of 3 pathogenic bacteria (Streptococcus spp., Vibrio spp., and Edwardsiella piscicida) to 18 antibiotics was tested using the minimum inhibitory concentration (MIC) panels, and the distribution of the MIC values for each species was confirmed. Among the panel antibiotics, nine commonly used antibiotics were selected, and the multiple antibiotic resistance (MAR) index and antibiotic resistance pattern were indicated using the disk diffusion method. It was confirmed that most of the isolates had a MAR index greater than 0.2, indicating a high-risk source. The distribution patterns of the MIC values and resistance pattern between gram-positive and gram-negative bacteria showed slightly different results. Ampicillin, erythromycin, and clindamycin were more effective against gram-positive bacteria than gram-negative bacteria. However, the MIC values of flumequine for gram-positive bacteria were higher than those of gram-negative bacteria. Through the distribution patterns of the MIC values and resistance patterns presented in this study, the need for monitoring the multidrug-resistant bacteria in aquaculture is emphasised.

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.

Considerable Production of Ulvan from Ulva lactuca with Special Emphasis on Its Antimicrobial and Anti-fouling Properties

In the current study, a significant amount of ulvan was extracted from Ulva lactuca collected from Alexandria coastline, Egypt, using a simple extraction method. According to the chemical analysis, the obtained polysaccharide content is estimated to be 36.50 g/100 g with a high sulfate content of 19.72%. Physio-chemically, the FTIR analysis confirmed the presence of sulfated groups attached to the carbohydrate backbone. The GC–MS results revealed the presence of various monosaccharides with relative abundances in the order: fucopyranose (22.09%) > L-rhamnose (18.17%) > L-fucose (17.46%) > rhamnopyranose (14.29%) > mannopyranose (8.59%) > α-D-glactopyranose (7.64%) > galactopyranose (6.14%) > β-arabinopyranose (5.62%). In addition, the SEM–EDX depicted an amorphous architecture with a majority wt% for the elements of C, O, and S. The partially purified ulvan demonstrated potent antimicrobial activity against some fish and human pathogenic microbes. The inhibition zone diameter ranged from 11 to 18 mm. On the other hand, the prepared ulvan-chitosan hydrogel significantly improved the antimicrobial activity as the inhibition zone diameter ranged from 12 to 20. Moreover, when compared to the controls, the extracted ulvan demonstrated anti-fouling properties and successfully disrupted the biofilm formed on a glass slide submerged in seawater.

Antimicrobial Susceptibility Testing: A Comprehensive Review of Currently Used Methods

Antimicrobial resistance (AMR) has emerged as a major threat to public health globally. Accurate and rapid detection of resistance to antimicrobial drugs, and subsequent appropriate antimicrobial treatment, combined with antimicrobial stewardship, are essential for controlling the emergence and spread of AMR. This article reviews common antimicrobial susceptibility testing (AST) methods and relevant issues concerning the advantages and disadvantages of each method. Although accurate, classic technologies used in clinical microbiology to profile antimicrobial susceptibility are time-consuming and relatively expensive. As a result, physicians often prescribe empirical antimicrobial therapies and broad-spectrum antibiotics. Although recently developed AST systems have shown advantages over traditional methods in terms of testing speed and the potential for providing a deeper insight into resistance mechanisms, extensive validation is required to translate these methodologies to clinical practice. With a continuous increase in antimicrobial resistance, additional efforts are needed to develop innovative, rapid, accurate, and portable diagnostic tools for AST. The wide implementation of novel devices would enable the identification of the optimal treatment approaches and the surveillance of antibiotic resistance in health, agriculture, and the environment, allowing monitoring and better tackling the emergence of AMR.

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.

In vitro investigations of Staphylococcus aureus biofilms in physiological fluids suggest that current antibiotic delivery systems may be limited

Orthopaedic surgical site infections, especially when a hardware is involved, are associated with biofilm formation. Clinical strategies for biofilm eradication still fall short. The present study used a novel animal model of long-bone fixation with vancomycin- or gentamicin-controlled release and measured the levels of antibiotic achieved at the site of release and in the surrounding tissue. Then, using fluids that contain serum proteins (synovial fluid or diluted serum), the levels of vancomycin or gentamicin required to substantially reduce colonising bacteria were measured in a model representative of either prophylaxis or established biofilms. In the in vivo model, while the levels immediately adjacent to the antibiotic release system were up to 50× the minimal inhibitory concentration in the first 24 h, they rapidly dropped. At peripheral sites, values never reached these levels. In the in vitro experiments, Staphylococcus aureus biofilms formed in serum or in synovial fluid showed a 5-10 fold increase in antibiotic tolerance. Importantly, concentrations required were much higher than those achieved in the local delivery systems. Finally, the study determined that the staged addition of vancomycin and gentamicin was not more efficacious than simultaneous vancomycin and gentamicin administration when using planktonic bacteria. On the other hand, for biofilms, the staged addition seemed more efficacious than adding the antibiotics simultaneously. Overall, data showed that the antibiotics' concentrations near the implant in the animal model fall short of the concentrations required to eradicate biofilms formed in either synovial fluid or serum.

Detection of multi-resistant clinical strains of E. coli with Raman spectroscopy

In recent years, we have seen a steady rise in the prevalence of antibiotic-resistant bacteria. This creates many challenges in treating patients who carry these infections, as well as stopping and preventing outbreaks. Identifying these resistant bacteria is critical for treatment decisions and epidemiological studies. However, current methods for identification of resistance either require long cultivation steps or expensive reagents. Raman spectroscopy has been shown in the past to enable the rapid identification of bacterial strains from single cells and cultures. In this study, Raman spectroscopy was applied for the differentiation of resistant and sensitive strains of Escherichia coli. Our focus was on clinical multi-resistant (extended-spectrum β-lactam and carbapenem-resistant) bacteria from hospital patients. The spectra were collected using both UV resonance Raman spectroscopy in bulk and single-cell Raman microspectroscopy, without exposure to antibiotics. We found resistant strains have a higher nucleic acid/protein ratio, and used the spectra to train a machine learning model that differentiates resistant and sensitive strains. In addition, we applied a majority of voting system to both improve the accuracy of our models and make them more applicable for a clinical setting. This method could allow rapid and accurate identification of antibiotic resistant bacteria, and thus improve public health.

Rapid Detection and Antimicrobial Susceptibility Testing of Pathogens Using AgNPs-Invertase Complexes and the Personal Glucose Meter

Rapid detection of pathogens and assessment of antimicrobial susceptibility is of great importance for public health, especially in resource-limiting regions. Herein, we developed a rapid, portable, and universal detection method for bacteria using AgNPs-invertase complexes and the personal glucose meter (PGM). In the presence of bacteria, the invertase could be released from AgNPs-invertase complexes where its enzyme activity of invertase was inhibited. Then, the enzyme activity of invertase was restored and could convert sucrose into glucose measured by a commercially PGM. There was a good linear relationship between PGM signal and concentration of E. coli or S. aureus as the bacteria model with high sensitivity. And our proposed biosensor was proved to be a rapid and reliable method for antimicrobial susceptibility testing within 4 h with consistent results of Minimum Inhibitory Concentrations (MICs) testing, providing a portable and convenient method to treat infected patients with correct antibiotics and reduce the production of antibiotic-resistant bacteria, especially for resource-limiting settings.

Antibiotic-functionalized gold nanoparticles for the detection of active β-lactamases

Antimicrobial resistance (AMR) continues to threaten the effective treatment and prevention of bacterial infections. The spread of resistant infections is accelerated by the lack of fast and cost-effective tests for the detection of AMR at the point-of-care. We aimed to address this challenge by developing a diagnostic tool to detect one of the major forms of AMR, the β-lactamase enzymes. Antibiotic-functionalized gold nanoparticles (AuNPs) have been successfully developed for the detection of β-lactamases in challenging biological media, namely undiluted urine. Furthermore, these tools are compatible with samples containing a urine sample preservative (boric acid) or hematuria (blood). The functionalized AuNPs interact with the active β-lactamases, resulting in the hydrolysis of the surface-bound antibiotics, which then inhibits binding of the AuNPs to a capture protein (a penicillin-binding protein) to indicate the presence of active β-lactamases. We successfully integrated the antibiotic-functionalized AuNPs into a new lateral flow assay (LFA), which can be used to detect active β-lactamases down to the detection limit of 11 nM. While we demonstrate the use of antibiotic-functionalized AuNPs in an LFA format to provide a novel method of detecting active β-lactamases, these functionalized AuNPs are amenable to a range of alternative diagnostic technologies and could lead to vital point-of-care diagnostics for the early detection of multi-drug resistant infections.