Antimicrobial susceptibility testing: currently used methods and devices and the near future in clinical practice

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.

CS/PVP Hydrogel-Based Nanocapillary for Monitoring Bacterial Growth and Rapid Antibiotic Susceptibility Testing

Infection with drug-resistant bacteria poses a significant threat to human health. Judicious use of antibiotics could reduce the likelihood of bacterial resistance, which can be evaluated through antibiotic susceptibility testing (AST). This paper focuses on the application of a needle-like nanocapillary tip filled with chitosan (CS)/polyethylene pyrrolidone (PVP) hydrogel based on its specific pH-sensitive properties. The gel-filled nanocapillary has the potential to be used for electrical pH detection with a sensitivity of 3.06 nA/pH and a linear range from 7.3 to 4.3. Such sensitivity for pH measurement could be extended for monitoring of bacterial (such as Escherichia coli and Streptococcus salivarius) growth because of the relationship between pH and bacterial growth. Bacterial growth curves obtained using the hydrogel-filled nanocapillary showed good agreement with the OD600 method. Moreover, this device could be applied for rapid AST for tetracycline and norfloxacin on E. coli with minimum inhibitory concentrations of 2 and 0.125 μg/mL, respectively. This study expands the application of the hydrogel-based nanocapillary for bacterial research by monitoring changes in pH values.

Maximally stable extremal regions-based algorithm for automatic interpretation of disc-diffusion antibiotic sensitivity test

Antibiotic resistance causes a major threat to patients suffering from infectious diseases. Accurate and timely assessment of Antibiotic Susceptibility Test (AST) is of great importance to ensure adequate treatment for patients and for epidemiological monitoring. Disc Diffusion Test (DDT) is a standard and widely used method for AST. Manual interpretation of DDT results is a tedious task and susceptible to human errors. Computer vision-based automated interpretation of DDT results will speed up the process and reduces the manpower requirement. This would assist the physician to initiate the antibiotic treatment for the patients on time and results in saving the patient's life. The crucial step in automatic interpretation of DDT result is to measure and present the diameter of zone of inhibition without manual intervention. The existing methods require manual interventions at various stages during inhibition zone diameter measurement for some typical cases. This issue is addressed in the present work through maximally stable extremal regions (MSER) based algorithm. Dataset consisting of 60 agar plate images that includes different agar medium, images having different resolution and visual quality is used to validate the proposed method. Experimental results demonstrated that there is a strong correlation between standard method and the proposed method.

The quality of antimicrobial susceptibility test discs and implications for clinical outcomes

Disc diffusion remains the main technique for evaluating antibiotic activity in clinical microbiology laboratories. However, the assay protocol endorsed by the FDA, DIN, and WHO is invalid. Despite decades of research and practice in this field, the quantitative quality of manufactured discs is largely unknown, potentially leading to adverse clinical outcomes. The usual standards expected for new medical devices in terms of quality control, QA, and evidence-based assessment of outcomes are almost completely lacking. Recent data indicate that a large proportion of discs do not meet the specifications, and that disc diffusion is a poor predictor of clinical outcomes. In addition, lack of harmonisation between EUCAST and CLSI, despite many years of effort, strongly suggests that there are serious flaws in these systems. This area lacks scientific rigour, which may have also contributed to adverse clinical outcomes and the emergence of antimicrobial resistance.

Inferring fungal growth rates from optical density data

Quantifying fungal growth underpins our ability to effectively treat severe fungal infections. Current methods quantify fungal growth rates from time-course morphology-specific data, such as hyphal length data. However, automated large-scale collection of such data lies beyond the scope of most clinical microbiology laboratories. In this paper, we propose a mathematical model of fungal growth to estimate morphology-specific growth rates from easy-to-collect, but indirect, optical density (OD600) data of Aspergillus fumigatus growth (filamentous fungus). Our method accounts for OD600 being an indirect measure by explicitly including the relationship between the indirect OD600 measurements and the calibrating true fungal growth in the model. Therefore, the method does not require de novo generation of calibration data. Our model outperformed reference models at fitting to and predicting OD600 growth curves and overcame observed discrepancies between morphology-specific rates inferred from OD600 versus directly measured data in reference models that did not include calibration.

Journey of technological advancements in the detection of antimicrobial resistance

Increased uses rather an extensive misuse of antibiotics due to easy availability and easy access have resulted in antibiotic resistance as a global crisis. The speed of discovery of new antibiotics has slowed down recently. Therefore, there is a need to reduce the rate of increase in resistance against the presently available antibiotics, or else many infections may be left untreatable or difficult to be treated due to the high prevalence of resistance. The judicious use of broad-spectrum antibiotics can control the increase in resistance profile. Various techniques are presently being used for the detection of antibiotic resistance. Conventional phenotypic methods are preferred that are highly reliable but are much more time-consuming. The patients cannot spare more time as the infection keeps increasing. The results with genotypic methods are obtained within 24 h as compared to phenotypic methods. Hence, recent molecular methods like qPCR can be used for detection. In this review, we present an overview of various methods useful for the detection of antibiotic resistance, with emphasis on their advantages and limitations. The review also emphasizes qPCR to be the most preferred method out of all because of various advantageous factors.

Nephroprotective Effect of the Leaf Extract of Ajuga remota Benth Against Gentamicin-Induced Nephrotoxicity in Swiss Albino Mice

Background

Drug-induced kidney injury was among the most common renal damages, from which gentamicin occupies around 25% of this injury. Gentamicin-induced renal damage is caused by increased free radicals with subsequent amplified inflammation. Ajuga remota leaf extract has many phytochemicals with antioxidant activities, which may improve gentamicin-induced renal damage. Thus, we aimed to investigate the nephroprotective effect of Ajuga remota leaf methanolic extract on gentamicin-induced nephrotoxicity in Swiss Albino Mice.

Methods

An experimental study design was used on 30 experimental mice randomly allocated in six groups: Group I, II, II, IV, and VI, among which mice were given only distilled water, only gentamicin, 600 mg/kg Ajuga remota leaf extract only, gentamicin along with 200 mg/kg extract, gentamicin with 400 mg/kg extract and gentamicin with 600 mg/kg extract, respectively. At the end of the experiment, the mice were sacrificed after being anaesthetized, and blood samples were collected through a cardiac puncture for renal function tests while the kidneys were removed for histopathological evaluation. The data were entered into Epidata version 4.6 and exported to SPSS version 25 for further analysis using one-way analysis of variance. Statistical significance was set at p < 0.05.

Results

Group II mice had significantly higher levels of serum creatinine and blood urea levels compared to group I and III. The body weight of the mice in group V and group VI showed a significant increase compared with Group II. Serum creatinine and blood urea levels were reduced significantly in the Ajuga remota leaf extract administered group of mice compared to group II. Abnormal kidney architectural changes were seen among group II mice; however, those changes were improved after administration of Ajuga remota leaf methanolic extract.

Conclusion

Methanol extract of Ajuga remota leaf provided effective protection against gentamicin-induced oxidative renal damage through its antioxidant effects.

Multipad agarose plate: a rapid and high-throughput approach for antibiotic susceptibility testing

We describe a phenotypic antibiotic susceptibility testing (AST) method that can provide an eightfold speed-up in turnaround time compared with the current clinical standard by leveraging advances in microscopy and single-cell imaging. A newly developed growth plate containing 96 agarose pads, termed the multipad agarose plate (MAP), can be assembled at low cost. Pads can be prepared with dilution series of antibiotics. Bacteria are seeded on the pads and automatically imaged using brightfield microscopy, with a fully automated segmentation pipeline quantifying microcolony formation and growth rate. Using a test set of nine antibiotics with very different targets, we demonstrate that accurate minimum inhibitory concentration (MIC) measurements can be performed based on the growth rate of microcolonies within 3 h of incubation with the antibiotic when started from exponential phase. Faster, reliable and high-throughput methods for AST, such as MAP, could improve patient care by expediting treatment initiation and alleviating the burden of antimicrobial resistance.

Prediction of Antibiotic Resistance in Patients With a Urinary Tract Infection: Algorithm Development and Validation

BACKGROUND

The early prediction of antibiotic resistance in patients with a urinary tract infection (UTI) is important to guide appropriate antibiotic therapy selection.

OBJECTIVE

In this study, we aimed to predict antibiotic resistance in patients with a UTI. Additionally, we aimed to interpret the machine learning models we developed.

METHODS

The electronic medical records of patients who were admitted to Yongin Severance Hospital, South Korea were used. A total of 71 features extracted from patients' admission, diagnosis, prescription, and microbiology records were used for classification. UTI pathogens were classified as either sensitive or resistant to cephalosporin, piperacillin-tazobactam (TZP), carbapenem, trimethoprim-sulfamethoxazole (TMP-SMX), and fluoroquinolone. To analyze how each variable contributed to the machine learning model's predictions of antibiotic resistance, we used the Shapley Additive Explanations method. Finally, a prototype machine learning-based clinical decision support system was proposed to provide clinicians the resistance probabilities for each antibiotic.

RESULTS

The data set included 3535, 737, 708, 1582, and 1365 samples for cephalosporin, TZP, TMP-SMX, fluoroquinolone, and carbapenem resistance prediction models, respectively. The area under the receiver operating characteristic curve values of the random forest models were 0.777 (95% CI 0.775-0.779), 0.864 (95% CI 0.862-0.867), 0.877 (95% CI 0.874-0.880), 0.881 (95% CI 0.879-0.882), and 0.884 (95% CI 0.884-0.885) in the training set and 0.638 (95% CI 0.635-0.642), 0.630 (95% CI 0.626-0.634), 0.665 (95% CI 0.659-0.671), 0.670 (95% CI 0.666-0.673), and 0.721 (95% CI 0.718-0.724) in the test set for predicting resistance to cephalosporin, TZP, carbapenem, TMP-SMX, and fluoroquinolone, respectively. The number of previous visits, first culture after admission, chronic lower respiratory diseases, administration of drugs before infection, and exposure time to these drugs were found to be important variables for predicting antibiotic resistance.

CONCLUSIONS

The study results demonstrated the potential of machine learning to predict antibiotic resistance in patients with a UTI. Machine learning can assist clinicians in making decisions regarding the selection of appropriate antibiotic therapy in patients with a UTI.

Uncovering the secrets of resistance: An introduction to computational methods in infectious disease research

Antimicrobial resistance (AMR) is a growing global concern with significant implications for infectious disease control and therapeutics development. This chapter presents a comprehensive overview of computational methods in the study of AMR. We explore the prevalence and statistics of AMR, underscoring its alarming impact on public health. The role of AMR in infectious disease outbreaks and its impact on therapeutics development are discussed, emphasizing the need for novel strategies. Resistance mutations are pivotal in AMR, enabling pathogens to evade antimicrobial treatments. We delve into their importance and contribution to the spread of AMR. Experimental methods for quantitatively evaluating resistance mutations are described, along with their limitations. To address these challenges, computational methods provide promising solutions. We highlight the advantages of computational approaches, including rapid analysis of large datasets and prediction of resistance profiles. A comprehensive overview of computational methods for studying AMR is presented, encompassing genomics, proteomics, structural bioinformatics, network analysis, and machine learning algorithms. The strengths and limitations of each method are briefly outlined. Additionally, we introduce ResScan-design, our own computational method, which employs a protein (re)design protocol to identify potential resistance mutations and adaptation signatures in pathogens. Case studies are discussed to showcase the application of ResScan in elucidating hotspot residues, understanding underlying mechanisms, and guiding the design of effective therapies. In conclusion, we emphasize the value of computational methods in understanding and combating AMR. Integration of experimental and computational approaches can expedite the discovery of innovative antimicrobial treatments and mitigate the threat posed by AMR.

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.

Agreement of methods to assess antimicrobial susceptibility using Escherichia coli isolates as target models

Antimicrobial susceptibility tests (AST) conducted in vitro offer a range of methods to assess the antimicrobial resistance (AMR) of microorganisms. Escherichia coli, a widely distributed bacterium, is closely linked to the issue of AMR. In this way, the present study aimed to assess the agreement among different in vitro AST methods, including disk diffusion in agar, broth dilution, and agar dilution method. A total of 100 E. coli isolates were analyzed for their resistance levels against six antibiotics: amoxicillin, ceftiofur, ciprofloxacin, chloramphenicol, tetracycline, and sulfamethoxazole + trimethoprim, using the aforementioned AST methods. Standard breakpoint values were employed to classify isolates as resistant, intermediate, or susceptible, and comparisons among the AST methods were conducted by McNemar's test (P < .05). The obtained data demonstrated equivalence among the AST methods, highlighting the reliability of these standardized classical methodologies. This standardization aids in preventing the inappropriate use of antimicrobials and the dissemination of antimicrobial-resistant microorganisms.

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

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

Cost-Efficient Micro-Well Array-Based Colorimetric Antibiotic Susceptibility Testing (MacAST) for Bacteria from Culture or Community

Rapid and cost-efficient antibiotic susceptibility testing (AST) is key to timely prescription-oriented diagnosis and precision treatment. However, current AST methods have limitations in throughput or cost effectiveness, and are impractical for microbial communities. Here, we developed a high-throughput micro-well array-based colorimetric AST (macAST) system equipped with a self-developed smartphone application that could efficiently test sixteen combinations of bacteria strains and antibiotics, achieving comparable AST results based on resazurin metabolism assay. For community samples, we integrated immunomagnetic separation into the macAST (imacAST) system to specifically enrich the target cells before testing, which shortened bacterial isolation time from days to only 45 min and achieved AST of the target bacteria with a low concentration (~103 CFU/mL). This proof-of-concept study developed a high-throughput AST system with an at least ten-fold reduction in cost compared with a system equipped with a microscope or Raman spectrum. Based on colorimetric readout, the antimicrobial susceptibility of the bacteria from microbial communities can be delivered within 6 h, compared to days being required based on standard procedures, bypassing the need for precise instrumentation in therapy to combat bacterial antibiotic resistance in resource-limited settings.

Genomic analysis reveals the presence of emerging pathogenic Klebsiella lineages aboard the International Space Station

IMPORTANCE

The International Space Station (ISS) is a unique, hermetically sealed environment, subject to environmental pressures not encountered on Earth, including microgravity and radiation (cosmic ionising/UV). While bacteria's adaptability during spaceflight remains elusive, recent research suggests that it may be species and even clone-specific. Considering the documented spaceflight-induced suppression of the human immune system, a deper understanding of the genomics of potential human pathogens in space could shed light on species and lineages of medical astromicrobiological significance. In this study, we used hybrid assembly methods and comparative genomics to deliver a comprehensive genomic characterization of 10 Klebsiella isolates retrieved from the ISS. Our analysis unveiled that Klebsiella quasipneumoniae ST138 demonstrates both spatial and temporal persistence aboard the ISS, showing evidence of genomic divergence from its Earth-based ST138 lineage. Moreover, we characterized plasmids from Klebsiella species of ISS origin, which harbored genes for disinfectant resistance and enhanced thermotolerance, suggestin possible adaptive advantages. Furthermore, we identified a mobile genetic element containing a hypervirulence-associated locus belonging to a Klebsiella pneumoniae isolate of the "high-risk" ST101 clone. Our work provides insights into the adaptability and persistence of Klebsiella species during spaceflight, highlighting the importance of understanding the dynamics of potential pathogenic bacteria in such environments.

High Bacterial Contamination Load of Self-Service Facilities in Sakaka City, Aljouf, Saudi Arabia, with Reduced Sensitivity to Some Antimicrobials

Although self-service facilities (SSFs) have been used on a large scale worldwide, they can be easily contaminated by microorganisms from the hands of their sequential users. This research aimed to study the prevalence and antimicrobial susceptibility/resistance of bacteria contaminating SSFs in Sakaka, Aljouf, Saudi Arabia. We randomly swabbed the surfaces of 200 SSFs, then used the suitable culture media, standard microbiological methods, and the MicroScan WalkAway Microbiology System, including the identification/antimicrobial susceptibility testing-combo panels. A high SSFs' bacterial contamination load was detected (78.00%). Ninety percent of the samples collected in the afternoon, during the maximum workload of the SSFs, yielded bacterial growth (p < 0.001 *). Most of the contaminated SSFs were supermarket payment machines, self-pumping equipment at gas stations (p = 0.004 *), online banking service machines (p = 0.026 *), and barcode scanners in supermarkets. In the antiseptic-deficient areas, 55.1% of the contaminated SSFs were detected (p = 0.008 *). Fifty percent of the contaminated SSFs were not decontaminated. The most common bacterial contaminants were Escherichia coli (70 isolates), Klebsiella pneumoniae (66 isolates), Staphylococcus epidermidis (34 isolates), methicillin-resistant Staphylococcus aureus (18 isolates), and methicillin-sensitive Staphylococcus aureus (14 isolates), representing 31.53%, 29.73%, 15.32%, 8.11%, and 6.31% of the isolates, respectively. Variable degrees of reduced sensitivity to some antimicrobials were detected among the bacterial isolates. The SSFs represent potential risks for the exchange of antimicrobial-resistant bacteria between the out-hospital environment and the hospitals through the hands of the public. As technology and science advance, there is an urgent need to deploy creative and automated techniques for decontaminating SSFs and make use of recent advancements in materials science for producing antibacterial surfaces.

Multimodal learning in clinical proteomics: enhancing antimicrobial resistance prediction models with chemical information

MOTIVATION

Large-scale clinical proteomics datasets of infectious pathogens, combined with antimicrobial resistance outcomes, have recently opened the door for machine learning models which aim to improve clinical treatment by predicting resistance early. However, existing prediction frameworks typically train a separate model for each antimicrobial and species in order to predict a pathogen's resistance outcome, resulting in missed opportunities for chemical knowledge transfer and generalizability.

RESULTS

We demonstrate the effectiveness of multimodal learning over proteomic and chemical features by exploring two clinically relevant tasks for our proposed deep learning models: drug recommendation and generalized resistance prediction. By adopting this multi-view representation of the pathogenic samples and leveraging the scale of the available datasets, our models outperformed the previous single-drug and single-species predictive models by statistically significant margins. We extensively validated the multi-drug setting, highlighting the challenges in generalizing beyond the training data distribution, and quantitatively demonstrate how suitable representations of antimicrobial drugs constitute a crucial tool in the development of clinically relevant predictive models.

AVAILABILITY AND IMPLEMENTATION

The code used to produce the results presented in this article is available at https://github.com/BorgwardtLab/MultimodalAMR.

Microwell-enhanced optical rapid antibiotic susceptibility testing of single bacteria

Bacteria that are resistant to antibiotics present an increasing burden on healthcare. To address this emerging crisis, novel rapid antibiotic susceptibility testing (AST) methods are eagerly needed. Here, we present an optical AST technique that can determine the bacterial viability within 1 h down to a resolution of single bacteria. The method is based on measuring intensity fluctuations of a reflected laser focused on a bacterium in reflective microwells. Using numerical simulations, we show that both refraction and absorption of light by the bacterium contribute to the observed signal. By administering antibiotics that kill the bacteria, we show that the variance of the detected fluctuations vanishes within 1 h, indicating the potential of this technique for rapid sensing of bacterial antibiotic susceptibility. We envisage the use of this method for massively parallelizable AST tests and fast detection of drug-resistant pathogens.

Bovine Lactoferrin and Current Antifungal Therapy Against Candida Albicans: A Systematic Review and Meta-Analysis

Candida albicans is an important causative organism of opportunistic fungal infection, and it is a growing medical concern due to the increasing usage of broad-spectrum antibiotics, immunosuppressant agents, and other immunocompromising conditions. Currently, bLf and antifungal drugs have been known to have synergistic effects, increasing the drug's efficacy. This study aims to investigate the efficacy of the synergistic effect of bLf and antifungal drugs. This review addressed the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. We conducted literature searches to assess the association of lactoferrin and current antifungal therapy against Candida albicans in ProQuest, PubMed, MEDLINE, EBSCOhost, SAGE, JSTOR, GARUDA, and Open Gray with no date restriction (until March 5th, 2021). We used Jeffry's Amazing Statistical Program (JASP) to measure the overall size effect of MIC (minimum inhibitory concentration) between studies. A total of 7 studies retained were experimental in vitro studies. Based on the available data, 4 out of 7 studies were included in the quantitative analysis. This systematic review showed that bovine lactoferrin could help inhibit the development of azole-susceptible and azole-resistant C. albicans. Furthermore, there was synergistic activity between lactoferrin and various antifungals. Our meta-analysis showed that lactoferrin could significantly inhibit the C. albicans growth than the control group. Bovine lactoferrin and its peptide derivatives isolated from bovine milk can significantly inhibit the growth of C. albicans, both susceptible to azoles and those with azole resistance.

Automatically showing microbial growth kinetics with a high-performance microbial growth analyzer

It is difficult to show microbial growth kinetics online when they grow in complex matrices. We presented a novel strategy to address this challenge by developing a high-performance microbial growth analyzer (HPMGA), which employed a unique 32-channel capacitively coupled contactless conductivity detector as a sensing element and fixed with a CellStatz software. It was capable of online showing accurate and repeatable growth curves of well-dispersed and bad-dispersed microbes, whether they grew in homogeneous simple culture broth or heterogeneous complex matrices. Moreover, it could automatically report key growth kinetics parameters. In comparison to optical density (OD), plate counting and broth microdilution (BMD) methods, we demonstrated its practicability in five scenarios: 1) the illustration of the growth, growth rate, and acceleration curves of Escherichia coli (E. coli); 2) the antimicrobial susceptibility testing (AST) of Oxacillin against Staphylococcus aureus (S. aureus); 3) the determination of Ag nanoparticle toxicity on Providencia rettgeri (P. rettgeri); 4) the characterization of milk fermentation; and 5) the enumeration of viable pathogenic Vibrio in shrimp body. Results highlighted that the HPMGA method had the advantages of universality and effectivity. This technology would significantly facilitate the routine analysis of microbial growth in many fields (biology, medicine, clinic, life, food, environment, and ecology), paving an avenue for microbiologists to achieve research goals that have been inhibited for years due to a lack of practical analytical methods.

Portable Colorimetric Hydrogel Beads for Point-of-Care Antimicrobial Susceptibility Testing

Sepsis is a life-threatening condition with systemic inflammatory responses caused by bacterial infections. Considering the emergence of antibiotic-resistant bacteria such as methicillin-resistant Staphylococcus aureus (MRSA), sepsis is a great threat to public health. The gold standard methods for antimicrobial susceptibility testing (AST), however, take at least approximately 3 days to implement the entire blood culture, pure culture, and AST processes. To overcome the time-consuming nature of conventional AST, a method employing a chromatic biosensor composed of poly(diacetylene), alginate, and LB broth (PAL) is introduced in this study. Compared to the gold standards, AST with PAL biosensors can be completed within a time frame as short as 16 h. Such a significant reduction in time is possible because the consecutive cultures and AST are carried out simultaneously by encapsulating the bacterial nutrients and detection molecules into a single component. The bead-like hydrogel sensors were used in their freeze-dried form, which endows them with portability and stability, thus making them adequate for point-of-care testing. The PAL biosensor yields minimum inhibitory concentrations comparable to those from the Clinical and Laboratory Standards Institute, and the applicability of the biosensor is further shown in MRSA-infected mice.

Polysaccharide-based antibacterial coating technologies

To tackle antimicrobial resistance, a global threat identified by the United Nations, is a common cause of healthcare-associated infections (HAI) and is responsible for significant costs on healthcare systems, a substantial amount of research has been devoted to developing polysaccharide-based strategies that prevent bacterial attachment and biofilm formation on surfaces. Polysaccharides are essential building blocks for life and an abundant renewable resource that have attracted much attention due to their intrinsic remarkable biological potential antibacterial activities. If converted into efficient antibacterial coatings that could be applied to a broad range of surfaces and applications, polysaccharide-based coatings could have a significant potential global impact. However, the ultimate success of polysaccharide-based antibacterial materials will be determined by their potential for use in manufacturing processes that are scalable, versatile, and affordable. Therefore, in this review we focus on recent advances in polysaccharide-based antibacterial coatings from the perspective of fabrication methods. We first provide an overview of strategies for designing polysaccharide-based antimicrobial formulations and methods to assess the antibacterial properties of coatings. Recent advances on manufacturing polysaccharide-based coatings using some of the most common polysaccharides and fabrication methods are then detailed, followed by a critical comparative overview of associated challenges and opportunities for future developments. STATEMENT OF SIGNIFICANCE: Our review presents a timely perspective by being the first review in the field to focus on advances on polysaccharide-based antibacterial coatings from the perspective of fabrication methods along with an overview of strategies for designing polysaccharide-based antimicrobial formulations, methods to assess the antibacterial properties of coatings as well as a critical comparative overview of associated challenges and opportunities for future developments. Meanwhile this work is specifically targeted at an audience focused on featuring critical information and guidelines for developing polysaccharide-based coatings. Including such a complementary work in the journal could lead to further developments on polysaccharide antibacterial applications.

Accuracy of T2 magnetic resonance assays as point-of-care methods in the intensive care unit

BACKGROUND

Novel molecular diagnostic methods are being evaluated in order to expedite pathogen identification in patients with bacteraemia.

AIMS

To evaluate the feasibility and diagnostic accuracy of the T2 magnetic resonance (T2MR) assays - T2 Bacteria (T2B) and T2 Resistance (T2R) - as point-of-care tests in the intensive care unit compared with blood-culture-based tests.

METHODS

Prospective cross-sectional study of consecutive patients with suspected bacteraemia. Diagnostic accuracy was evaluated using blood culture as the reference method.

FINDINGS

In total, 208 cases were included in the study. The mean time from sampling to report was lower for the T2MR assays compared with blood-culture-based methods (P<0.001). The rate of invalid reports was 6.73% for the T2B assay and 9.9% for the T2R assay. For the T2B assay, overall positive percentage agreement (PPA) was 84.6% [95% confidence interval (CI) 71.9-93.1%], negative percentage agreement (NPA) was 64.3% (95% CI 55.4-72.6%), positive predictive value (PPV) was 48.9% (95% CI 42.5-55.3%) and negative predictive value (NPV) was 91.2% (95% CI 84.4-95.2%). Cohen's kappa coefficient was 0.402. For the T2R assay, overall PPA was 80% (95% CI 51.9-95.7%), NPA was 69.2% (95% CI 54.9-81.3%), PPV was 42.9% (95% CI 31.7-54.8%) and NPV was 92.3% (95% CI 81.1-97.1%). Cohen's kappa coefficient was 0.376.

CONCLUSION

T2MR assays have high NPV for rapid exclusion of bacteraemia, and could potentially assist with antimicrobial stewardship when applied as point-of-care diagnostic tests in the intensive care unit.

Using Protein Fingerprinting for Identifying and Discriminating Methicillin Resistant Staphylococcus aureus Isolates from Inpatient and Outpatient Clinics

In hospitals and other clinical settings, Methicillin-resistant Staphylococcus aureus (MRSA) is a particularly dangerous pathogen that can cause serious or even fatal infections. Thus, the detection and differentiation of MRSA has become an urgent matter in order to provide appropriate treatment and timely intervention in infection control. To ensure this, laboratories must have access to the most up-to-date testing methods and technology available. This study was conducted to determine whether protein fingerprinting technology could be used to identify and distinguish MRSA recovered from both inpatients and outpatients. A total of 326 S. aureus isolates were obtained from 2800 in- and outpatient samples collected from King Faisal Specialist Hospital and Research Centre in Riyadh, Saudi Arabia, from October 2018 to March 2021. For the phenotypic identification of 326 probable S. aureus cultures, microscopic analysis, Gram staining, a tube coagulase test, a Staph ID 32 API system, and a Vitek 2 Compact system were used. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), referred to as protein fingerprinting, was performed on each bacterial isolate to determine its proteomic composition. As part of the analysis, Principal Component Analysis (PCA) and a single-peak analysis of MALDI-TOF MS software were also used to distinguish between Methicillin-sensitive Staphylococcus aureus (MSSA) and MRSA. According to the results, S. aureus isolates constituted 326 out of 2800 (11.64%) based on the culture technique. The Staph ID 32 API system and Vitek 2 Compact System were able to correctly identify 262 (80.7%) and 281 (86.2%) S. aureus strains, respectively. Based on the Oxacillin Disc Diffusion Method, 197 (62.23%) of 326 isolates of S. aureus exhibited a cefoxitin inhibition zone of less than 21 mm and an oxacillin inhibition zone of less than 10 mm, and were classified as MRSA under Clinical Laboratory Standards Institute guidelines. MALDI-TOF MS was able to correctly identify 100% of all S. aureus isolates with a score value equal to or greater than 2.00. In addition, a close relationship was found between S. aureus isolates and higher peak intensities in the mass ranges of 3990 Da, 4120 Da, and 5850 Da, which were found in MRSA isolates but absent in MSSA isolates. Therefore, protein fingerprinting has the potential to be used in clinical settings to rapidly detect and differentiate MRSA isolates, allowing for more targeted treatments and improved patient outcomes.

Less Is More: When to Repeat Antimicrobial Susceptibility Testing

This study investigated the frequency of change of the antimicrobial susceptibility pattern when the same isolate was found in the same patient in various situations. We used laboratory data collected over a period of 8 years (January 2014 to December 2021) at the clinical microbiology laboratory of a tertiary hospital for Escherichia coli, Klebsiella pneumoniae, Enterobacter spp., Pseudomonas aeruginosa, and Staphylococcus aureus. Antimicrobial susceptibility tests (AST) were performed using Vitek 2 automated system. We determined essential agreement and categorical agreement, and introduced the new terms essential MIC increase and change from nonresistant to resistant to present changes in antimicrobial susceptibility over time. During the study period, 18,501 successive AST were included. The risk for S. aureus to be resistant to any antibiotic upon repeated culture was <10% during a follow-up of 30 days. For Enterobacterales, this risk was approximately 10% during a follow-up of 7 days. For P. aeruginosa, this risk was higher. The longer the follow-up period, the higher the risk that the bacteria would show phenotypic resistance. We also found that some drug-bug combinations were more likely to develop phenotypical resistance (i.e., E. coli/amoxicillin-clavulanic acid and E. coli/cefuroxime). A potential consequence of our finding is that if we regard a risk of resistance below 10% as acceptable, it may be feasible to omit follow-up AST within 7 days for the microorganisms investigated in this study. This approach saves money, time, and will reduce laboratory waste. Further studies are needed to determine whether these savings are in balance with the small possibility of treating patients with inadequate antibiotics.

Atmospheric and Room Temperature Plasma (ARTP) Mutagenesis Improved the Anti-MRSA Activity of Brevibacillus sp. SPR20

Brevibacillus sp. SPR20 produced potentially antibacterial substances against methicillin-resistant Staphylococcus aureus (MRSA). The synthesis of these substances is controlled by their biosynthetic gene clusters. Several mutagenesis methods are used to overcome the restriction of gene regulations when genetic information is absent. Atmospheric and room temperature plasma (ARTP) is a powerful technique to initiate random mutagenesis for microbial strain improvement. This study utilized an argon-based ARTP to conduct the mutations on SPR20. The positive mutants of 40% occurred. The M27 mutant exhibited an increase in anti-MRSA activity when compared to the wild-type strain, with the MIC values of 250-500 and 500 μg/mL, respectively. M27 had genetic stability because it exhibited constant activity throughout fifteen generations. This mutant had similar morphology and antibiotic susceptibility to the wild type. Comparative proteomic analysis identified some specific proteins that were upregulated in M27. These proteins were involved in the metabolism of amino acids, cell structure and movement, and catalytic enzymes. These might result in the enhancement of the anti-MRSA activity of the ARTP-treated SPR20 mutant. This study supports the ARTP technology designed to increase the production of valuable antibacterial agents.

Fungistatic Effect of Phthalide Lactones on Rhodotorula mucilaginosa

Currently, there is an increasing number of cases of fungal infections caused by opportunistic strains of the yeast Rhodotorula mucilaginosa, mainly in immunocompromised patients during hospitalization. The excessive use of antibiotics and azole compounds increases the risk of resistance to microorganisms. A new alternative to these drugs may be synthetic phthalide lactones with a structure identical to or similar to the natural ones found in celery plants, which show low toxicity and relatively high fungistatic activity. In the present study, the fungistatic activity of seven phthalide lactones was determined against R. mucilaginosa IHEM 18459. We showed that 3-n-butylidenephthalide, the most potent compound selected in the microdilution test, caused a dose-dependent decrease in dry yeast biomass. Phthalide accumulated in yeast cells and contributed to an increase in reactive oxygen species content. The synergistic effect of fluconazole resulted in a reduction in the azole concentration required for yeast inhibition. We observed changes in the color of the yeast cultures; thus, we conducted experiments to prove that the carotenoid profile was altered. The addition of lactones also triggered a decline in fatty acid methyl esters.

Electroacoustic Biosensor Systems for Evaluating Antibiotic Action on Microbial Cells

Antibiotics are widely used to treat infectious diseases. This leads to the presence of antibiotics and their metabolic products in the ecosystem, especially in aquatic environments. In many countries, the growth of pathogen resistance to antibiotics is considered a threat to national security. Therefore, methods for determining the sensitivity/resistance of bacteria to antimicrobial drugs are important. This review discusses the mechanisms of the formation of antibacterial resistance and the various methods and sensor systems available for analyzing antibiotic effects on bacteria. Particular attention is paid to acoustic biosensors with active immobilized layers and to sensors that analyze antibiotics directly in liquids. It is shown that sensors of the second type allow analysis to be done within a short period, which is important for timely treatment.

Bioinspired Synthesis of Silver Nanoparticles for the Remediation of Toxic Pollutants and Enhanced Antibacterial Activity

This research presents a novel and environmentally friendly approach for the synthesis of multifunctional nanobiocomposites for the efficient removal of toxic heavy metal and dye, as well as the disinfection of wastewater microorganisms. The nanobiocomposites (KAC-CS-AgNPs) were prepared by incorporating photochemically generated silver nanoparticles (AgNPs) within a chitosan (CS)-modified, high-surface-area activated carbon derived from kenaf (KAC), using a unique self-activation method. The even distribution of AgNPs was visible in the scanning electron microscopy images and a Fourier transform infra red study demonstrated major absorption peaks. The experimental results revealed that KA-CS-AgNPs exhibited exceptional adsorption efficiency for copper (Cu²⁺), lead (Pb²⁺), and Congo Red dye (CR), and showed potent antibacterial activity against Staphylococcus aureus and Escherichia coli. The maximum adsorption capacity (mg g^-1) of KAC-CS-AgNPs was 71.5 for Cu²⁺, 72.3 for Pb²⁺, and 75.9 for CR, and the adsorption phenomena followed on the Freundlich and Langmuir isotherm models and the second-order kinetic model (R² > 0.99). KAC-CS-AgNPs also exhibited excellent reusability of up to four consecutive cycles with minor losses in adsorption ability. The thermodynamic parameters indicated that the adsorption process was spontaneous and endothermic in nature. The bacterial inactivation tests demonstrated that KAC-CS-AgNPs had a strong bactericidal effect on both E. coli and S. aureus, with MIC calculated for E. coli and S. aureus as 32 µg mL^-1 and 44 µg mL^-1, respectively. The synthesized bioinspired nanocomposite KAC-CS-AgNPs could be an innovative solution for effective and sustainable wastewater treatment and has great potential for commercial applications.

Enhancing the Antibiotic Production by Thermophilic Bacteria Isolated from Hot Spring Waters via Ethyl Methanesulfonate Mutagenesis

Antibiotic-resistant bacteria represent a serious public health threat. For that reason, the development of new and effective antibiotics to control pathogens has become necessary. The current study aims to search for new microorganisms expressing antibiotic production capacity. Fifteen sites covering a wide range of harsh environmental conditions in Egypt were investigated. Two hundred and eighty bacterial isolates were obtained and then tested against pathogenic bacteria using the agar disk diffusion technique. Fifty-two (18.6% of the total) of the isolates exhibited antagonistic properties, which affected one or more of the tested pathogens. The isolate 113 was identified as Bacillus licheniformis and isolate 10 was identified as Brevibacillus borstelensis using the 16S rRNA technique. The B. licheniformis strain was stronger in antibiotic production against S. typhi, M. luteus, and P. ariginosa, whereas the strain Br. borstelensis was more efficient against B. cereus, E. coli, and Klebs. sp. The sensitivity of the strains to commercial antibiotics showed that B. licheniformis was highly sensitive to seven commercial antibiotics, whereas Br. borstelensis was sensitive to nine antibiotics. The two strains were subjected to ethyl methanesulfonate (EMS) mutagenesis to obtain mutants with a higher antibiotic production. The total bacterial count was measured after treatment with EMS mutagen and showed a significant gradual increase in the antimicrobial activity, which was achieved via shaking in the presence of EMS for 60 min. High antimicrobial activities were noted with 17 and 14 mutants from the B. licheniformis and Br. borstelensis strains, respectively. The mutant B. licheniformis (M15/Amo) was more active than the parent strain against S. aureus (212.5%), while the mutant Br. borstelensis (B7/Neo) was more effective against S. typhi (83.3%). The present study demonstrates the possibility of obtaining potent antibiotic-producing bacteria in hot spring waters and further improving the indigenous bacterial capacity to produce antibiotics by using EMS mutagenesis.

What's the Matter with MICs: Bacterial Nutrition, Limiting Resources, and Antibiotic Pharmacodynamics

The MIC of an antibiotic required to prevent replication is used both as a measure of the susceptibility/resistance of bacteria to that drug and as the single pharmacodynamic parameter for the rational design of antibiotic treatment regimes. MICs are experimentally estimated in vitro under conditions optimal for the action of the antibiotic. However, bacteria rarely grow in these optimal conditions. Using a mathematical model of the pharmacodynamics of antibiotics, we make predictions about the nutrient dependency of bacterial growth in the presence of antibiotics. We test these predictions with experiments in broth and a glucose-limited minimal media with Escherichia coli and eight different antibiotics. Our experiments question the sufficiency of using MICs and simple pharmacodynamic functions as measures of the pharmacodynamics of antibiotics under the nutritional conditions of infected tissues. To an extent that varies among drugs: (i) the estimated MICs obtained in rich media are greater than those estimated in minimal media; (ii) exposure to these drugs increases the time before logarithmic growth starts, their lag; and (iii) the stationary-phase density of E. coli populations declines with greater sub-MIC antibiotic concentrations. We postulate a mechanism to account for the relationship between sub-MICs of antibiotics and these growth parameters. This study is limited to a single bacterial strain and two types of culture media with different nutritive content. These limitations aside, the results of our study clearly question the use of MIC as the unique pharmacodynamic parameter to develop therapeutically oriented protocols. IMPORTANCE For studies of antibiotics and how they work, the most-often used measurement of drug efficacy is the MIC. The MIC is the concentration of an antibiotic needed to inhibit bacterial growth. This parameter is critical to the design and implementation of antibiotic therapy. We provide evidence that the use of MIC as the sole measurement for antibiotic efficacy ignores important aspects of bacterial growth dynamics. Before now, there has not been a nexus between bacteria, the conditions in which they grow, and the MIC. Most importantly, few studies have considered sub-MICs of antibiotics, despite their clinical importance. Here, we explore these concentrations in-depth, and we demonstrate MIC to be an incomplete measure of how an infection will interact with a specific antibiotic. Understanding the critiques of MIC is the first of many steps needed to improve infectious disease treatment.

Conventional methods and future trends in antimicrobial susceptibility testing

Antimicrobial susceptibility testing is an essential task for selecting appropriate antimicrobial agents to treat infectious diseases. Constant evolution has been observed in methods used in the diagnostic microbiology laboratories. Disc diffusion or broth microdilution are classical and conventional phenotypic methods with long turnaround time and labour-intensive but still widely practiced as gold-standard. Scientists are striving to develop innovative, novel and faster methods of antimicrobial susceptibility testing to be applicable for routine microbiological laboratory practice and research. To meet the requirements, there is an increasing trend towards automation, genotypic and micro/nano technology-based innovations. Automation in detection systems and integration of computers for online data analysis and data sharing are giant leaps towards versatile nature of automated methods currently in use. Genotypic methods detect a specific genetic marker associated with resistant phenotypes using molecular amplification techniques and genome sequencing. Microfluidics and microdroplets are recent addition in the continuous advancement of methods that show great promises with regards to safety and speed and have the prospect to identify and monitor resistance mechanisms. Although genotypic and microfluidics methods have many exciting features, however, their applications into routine clinical laboratory practice warrant extensive validation. The main impetus behind the evolution of methods in antimicrobial susceptibility testing is to shorten the overall turnaround time in obtaining the results and to enhance the ease of sample processing. This comprehensive narrative review summarises major conventional phenotypic methods and automated systems currently in use, and highlights principles of some of the emerging genotypic and micro/nanotechnology-based methods in antimicrobial susceptibility testing.

Using Machine Learning to Predict Antimicrobial Resistance-A Literature Review

Machine learning (ML) algorithms are increasingly applied in medical research and in healthcare, gradually improving clinical practice. Among various applications of these novel methods, their usage in the combat against antimicrobial resistance (AMR) is one of the most crucial areas of interest, as increasing resistance to antibiotics and management of difficult-to-treat multidrug-resistant infections are significant challenges for most countries worldwide, with life-threatening consequences. As antibiotic efficacy and treatment options decrease, the need for implementation of multimodal antibiotic stewardship programs is of utmost importance in order to restrict antibiotic misuse and prevent further aggravation of the AMR problem. Both supervised and unsupervised machine learning tools have been successfully used to predict early antibiotic resistance, and thus support clinicians in selecting appropriate therapy. In this paper, we reviewed the existing literature on machine learning and artificial intelligence (AI) in general in conjunction with antimicrobial resistance prediction. This is a narrative review, where we discuss the applications of ML methods in the field of AMR and their value as a complementary tool in the antibiotic stewardship practice, mainly from the clinician's point of view.

Improving droplet microfluidic systems for studying single bacteria growth

Antimicrobial resistance remains a global threat with ~ 5 million deaths in 2019 alone and 10 million deaths projected every year by 2050. Current tools employed in the analysis of bacteria can be time inefficient, leading to delayed diagnosis and treatment. In this work, we develop a microfluidic setup capable of bacteria incubation and detection of growth in ~ 2 h. We fabricated polydimethylsiloxane (PDMS) microchips via soft lithography, enclosed microchannels by plasma bonding to glass, and utilized PDMS blocks for simplified connection of devices to a flow system. We generated uniform droplets enclosing zero, one or two bacteria within our devices, and incubated droplet-encapsulated bacteria with 100 × lower concentrations of a fluorescence probe of bacterial growth compared to prior work. We assessed bacterial growth via laser induced fluorescence after room temperature incubation for 2 h and obtained a range of signals corresponding to droplets with or without bacteria. Our devices allow for online droplet incubation, monitoring, detection, and tracking. Developing microfluidic chips for single bacteria studies will improve the analysis and treatment of antimicrobial resistance.

Electrokinetics in antimicrobial resistance analysis: A review

Infections caused by antimicrobial resistance are a serious problem in the world. Currently, commercial devices for antimicrobial susceptibility testing and resistant bacteria identification are time-consuming. There is an urgent need to develop fast and accurate methods, especially in the process of sample pretreatment. Electrokinetic (EK) is a family of electric-field-based kinetic phenomena of fluid or embedded objects, and EK applications have been found in various fields. In this paper, EK bacteria manipulation, including enrichment and separation, is reviewed. Focus is given to the rapid electric-based minimum inhibitory concentration measurement. The future directions and major challenges in this field are also outlined.

A review of antibiotic resistance among Campylobacter species in human, animal, and water sources in South Africa: a One Health Approach

Campylobacter species are among the aetiological agents responsible for 400-500 million human diarrhoea cases per annum. The risk of dissemination of antibiotic-resistant Campylobacter species between humans, animals, and the environment is anticipated, given its transmissibility through these sources. The objective of this paper is to present a situation analysis that reports the current patterns and determinants of Campylobacter antibiotic resistance in South Africa. This review applies the One Health (OH) Approach to systematically review and collate the current antibiotic resistance status among Campylobacter spp. in South Africa. The highest level of resistance of Campylobacter in humans is to azithromycin (69.7%), whereas the lowest level of resistance of Campylobacter is to gatifloxacin (8.3%). In animals, high resistance to common antibiotics erythromycin (95.06%), clindamycin (95.68%), doxycycline (87.65%), erythromycin (90%), tetracycline (84.3%), streptomycin (88%), and ampicillin (73%) while 100% resistance of Campylobacter from water samples to tetracycline, imipenem, is recorded. Furthermore, resistance to clarithromycin (95%), azithromycin (92%), clindamycin (84.2%), doxycycline (80%), and ciprofloxacin (77.8%) is reported among Campylobacter spp. from water samples. The genetic similarity results suggest the movement of antibiotic-resistant Campylobacter spp. between humans and the environment. More research on antibiotic resistance among Campylobacter from other sources, outside clinical isolates, is recommended.

Rapid Antimicrobial Susceptibility Testing Based on a Bio-Inspired Chemiluminescence Sensor

Indiscriminate usage of antibiotics has caused accelerating growth and global expansion of antimicrobial resistance. Therefore, rapid antimicrobial susceptibility testing (AST) for guiding antibiotic prescription and preventing the spread of antimicrobial resistance is in urgent need. Phenotypic AST is the clinical gold standard method; however, no phenotypic AST has realized a colony-to-answer at about 1 h by utilizing the chemiluminescence sensor to detect the enzyme expressed by bacteria. Inspired by the bubble formation in the mixture of Escherichia coli and H₂O₂, we demonstrate a strategy based on the chemiluminescence sensor for rapid AST. Compared with the gold standard methods, the values of AUC are 0.960 for E. coli and 0.950 for Staphylococcus aureus, close to 1, indicating superb diagnostic performance as an AST method. The whole process from colonies to answer is 55 min for E. coli and 70 min for S. aureus. The chemiluminescence readout is based on the common equipment in the laboratory of the hospital, which is conducive to follow-up clinical promotion. Our sensor promises great potential in rapid AST, facilitating antimicrobial stewardship.

Optimizing antimicrobial therapy in urinary tract infections: A focus on urine culture and sensitivity testing

Objectives: This cross-sectional study was conducted at Jordan university hospital to evaluate the impact of microbial culture data and sensitivity results on optimizing UTI treatment. Methods: All positive urine cultures requested for adult patients (≥18 years) admitted to Jordan University Hospital (JUH) within the period from January 2019-July 2021 were evaluated. The antibiotics prescribed before and after culture data and sensitivity results were compared to evaluate the impact of these diagnostic measures on optimizing UTI treatment. Results: During the study period, 2400 urine cultures revealed positive results. Among those patients, 1,600 (66.7%) were discharged before the availability of culture results and excluded. Of the remaining 800 patients, 701 patients (87.6%) received empiric treatment. After culture and sensitivity results were available, overall, 84 (10.5%) patients had optimization (improvement) in their UTI management after culture results were known, while 6 (0.8%) patients had a worsening in their treatments. Based on the culture results, we found that only 12.4% of patients were appropriately treated before and after the culture results. Moreover, our results revealed that 31.9% were inappropriately treated for their UTIs before and after culture results. Conclusion: This study revealed an alarmingly high rate of inappropriate treatment of UTIs despite the availability of urine culture and sensitivity data, and that culture results were not used to optimize treatment strategies for UTI. This practice can potentially result in poor health-related outcomes and adversely affects efforts to battle AMR. Multifaceted strategies must be implemented to help clinicians follow the best current evidence and current guidelines in their selection of antibiotics for the management of UTIs.

The potential of 4D's approach in curbing antimicrobial resistance among bacterial pathogens

INTRODUCTION

Antibiotics are life-saving drugs but irrational/inappropriate use leads to the emergence of antibiotic-resistant bacterial superbugs, making their treatment extremely challenging. Increasing antimicrobial resistance (AMR) among bacterial pathogens is becoming a serious public health concern globally. If ignorance persists, there would not be any antibiotics available to treat even a common bacterial infection in future.

AREA COVERED

This article intends to collate and discuss the potential of 4D's (right Drug, Dose, Duration, and De-escalation of therapy) approach to tackle the emerging problem of AMR. For this, we searched PubMed, Google Scholar, Medline, and clinicaltrials.gov databases primarily using keywords 'optimal antibiotic therapy,' 'antimicrobial resistance,' 'higher versus lower dose antibiotic treatment,' 'shorter versus longer duration antibiotic treatment,' 'de-escalation study', and 'antimicrobial stewardship measures' and based on the findings, form and expressed our opinion.

EXPERT OPINION

More efforts are needed for developing diagnostics for rapid, accurate, point-of-care, and cost-effective pathogen identification and antimicrobial susceptibility testing (AST) to facilitate rational use of antibiotics. Current dosing and duration of therapies also need to be redefined to maximize their impact. Furthermore, de-escalation approaches should be developed and encouraged in the clinic. This altogether will minimize selection pressure on the pathogens and reduce emergence of AMR.

Early appropriate diagnostics and treatment of MDR Gram-negative infections

The term difficult-to-treat resistance has been recently coined to identify Gram-negative bacteria exhibiting resistance to all fluoroquinolones and all β-lactam categories, including carbapenems. Such bacteria are posing serious challenges to clinicians trying to identify the best therapeutic option for any given patient. Delayed appropriate therapy has been associated with worse outcomes including increase in length of stay, increase in total in-hospital costs and ∼20% increase in the risk of in-hospital mortality. In addition, time to appropriate antibiotic therapy has been shown to be an independent predictor of 30 day mortality in patients with resistant organisms. Improving and anticipating aetiological diagnosis through optimizing not only the identification of phenotypic resistance to antibiotic classes/agents, but also the identification of specific resistance mechanisms, would have a major impact on reducing the frequency and duration of inappropriate early antibiotic therapy. In light of these considerations, the present paper reviews the increasing need for rapid diagnosis of bacterial infections and efficient laboratory workflows to confirm diagnoses and facilitate prompt de-escalation to targeted therapy, in line with antimicrobial stewardship principles. Rapid diagnostic tests currently available and future perspectives for their use are discussed. Early appropriate diagnostics and treatment of MDR Gram-negative infections require a multidisciplinary approach that includes multiple different diagnostic methods and further consensus of algorithms, protocols and guidelines to select the optimal antibiotic therapy.

An Insight into Efflux-Mediated Arsenic Resistance and Biotransformation Potential of Enterobacter Cloacae RSC3 from Arsenic Polluted Area

Indiscriminate discharge of heavy metals/metalloids from different sources into the sustainable agro-ecosystem is a major global concern for food security and human health. Arsenic (As), categorized as group one human carcinogen is a quintessential toxic metalloid that alters the microbial compositions and functions, induce physiological and metabolic changes in plants and contaminate surface/ground water. The management of arsenic toxicity, therefore, becomes imminent. Acknowledging the arsenic threat, the study was aimed at identifying arsenic resistant bacteria and evaluating its arsenic removal/detoxification potential. Of the total 118 bacterial isolates recovered from arsenic rich environment, the bacterial strain RSC3 demonstrating highest As tolerance was identified as Enterobacter cloacae by 16S rRNA gene sequence analysis. Enterobacter cloacae tolerated high concentration (6000 ppm) of As and exhibited 0.55 h-1 of specific growth rate as calculated from growth kinetics data. Strain RSC3 also displayed varying level of resistance to other heavy metals and many antibacterial drugs in plate bioassay. The bacterial strain RSC3 possessed gene (arsC) which causes transformation of arsenate to arsenite. The arsenate uptake and efflux of the bacterial cells was revealed by high throughput techniques such as AAS, SEM/TEM and EDX. The simultaneous As reducing ability, and multi metal/multi-antibiotics resistance potentials of E. cloacae provides a promising option in the microbes based remediation of As contaminated environments.

GC-MS Analysis, Antibacterial and Antioxidant Potential of Ethyl Acetate Leaf Extract of Senna singueana (Delile) Grown in Kenya

Bacterial diseases are a leading cause of mortality and morbidity globally. During bacterial diseases, an elevation of host immune response occurs, which involves the production of free radicals in response to the bacterial infection. The overproduction of free radicals in excess of the antioxidants leads to oxidative stress. Conventional antibiotics are linked to side effects such as hypersensitivity reactions in addition to bacterial pathogens developing resistance against them. Artificial antioxidants are said to be carcinogenic. This study sought to confirm folklore use and validate the antibacterial and antioxidant potential of Senna singueana which has been widely used in the Mbeere community. The in vitro antibacterial potentials of the plant extract were investigated on Bacillus subtilis ATCC 21332, Escherichia coli ATCC 25922, Salmonella typhi ATCC 1408, and Staphylococcus aureus ATCC 25923. Ciprofloxacin (100 µg/ml) drug was used as a standard reference, whereas 5% DMSO was used as a negative reference. The antibacterial tests included disc diffusion and minimum inhibitory and bactericidal concentrations. S. singueana ethyl acetate extract showed broad-spectrum potential against tested bacterial microbes producing mean zones of inhibition (MZI) from 07.67 ± 0.33 to 17.67 ± 0.33 mm. The extract demonstrated a greater effect on Gram-positive than Gram-negative bacterial pathogens. Antibacterial properties of ciprofloxacin were significantly greater in comparison to plant extract in all the dilutions ( $p<0.05$ ), while 5% DMSO was inactive against all the tested bacteria. MBC values were greater than MIC values. Antioxidant properties of the extract were determined through scavenging effects of DPPH and hydroxyl radicals (•OH) as well as ferric reducing antioxidant potential (FRAP) assay. S. singueana demonstrated effects against all radicals formed. Additionally, the extract exhibited ferric reducing abilities. The extract also contained various phytocompounds with known antibacterial and antioxidant properties. This study recommends the therapeutic use of S. singueana as an antibacterial as well as an antioxidant agent.

Azithromycin possesses biofilm–inhibitory activity and potentiates non-bactericidal colistin methanesulfonate (CMS) and polymyxin B against Klebsiella pneumonia

Novel antibiotic combinations may act synergistically to inhibit the growth of multidrug-resistant bacterial pathogens but predicting which combination will be successful is difficult, and standard antimicrobial susceptibility testing may not identify important physiological differences between planktonic free-swimming and biofilm-protected surface-attached sessile cells. Using a nominally macrolide-resistant model Klebsiella pneumoniae strain (ATCC 10031) we demonstrate the effectiveness of several macrolides in inhibiting biofilm growth in multi-well plates, and the ability of azithromycin (AZM) to improve the effectiveness of the antibacterial last-agent-of-choice for K. pneumoniae infections, colistin methanesulfonate (CMS), against biofilms. This synergistic action was also seen in biofilm tests of several K. pneumoniae hospital isolates and could also be identified in polymyxin B disc-diffusion assays on azithromycin plates. Our work highlights the complexity of antimicrobial-resistance in bacterial pathogens and the need to test antibiotics with biofilm models where potential synergies might provide new therapeutic opportunities not seen in liquid culture or colony-based assays.

One Day in Denmark: Comparison of Phenotypic and Genotypic Antimicrobial Susceptibility Testing in Bacterial Isolates From Clinical Settings

Antimicrobial susceptibility testing (AST) should be fast and accurate, leading to proper interventions and therapeutic success. Clinical microbiology laboratories rely on phenotypic methods, but the continuous improvement and decrease in the cost of whole-genome sequencing (WGS) technologies make them an attractive alternative. Studies evaluating the performance of WGS-based prediction of antimicrobial resistance (AMR) for selected bacterial species have shown promising results. There are, however, significant gaps in the literature evaluating the applicability of WGS as a diagnostics method in real-life clinical settings against the range of bacterial pathogens experienced there. Thus, we compared standard phenotypic AST results with WGS-based predictions of AMR profiles in bacterial isolates without preselection of defined species, to evaluate the applicability of WGS as a diagnostics method in clinical settings. We collected all bacterial isolates processed by all Danish Clinical Microbiology Laboratories in 1 day. We randomly selected 500 isolates without any preselection of species. We performed AST through standard broth microdilution (BMD) for 488 isolates (n = 6,487 phenotypic AST results) and compared results with in silico antibiograms obtained through WGS (Illumina NextSeq) followed by bioinformatics analyses using ResFinder 4.0 (n = 5,229 comparisons). A higher proportion of AMR was observed for Gram-negative bacteria (10.9%) than for Gram-positive bacteria (6.1%). Comparison of BMD with WGS data yielded a concordance of 91.7%, with discordant results mainly due to phenotypically susceptible isolates harboring genetic AMR determinants. These cases correspond to 6.2% of all isolate-antimicrobial combinations analyzed and to 6.8% of all phenotypically susceptible combinations. We detected fewer cases of phenotypically resistant isolates without any known genetic resistance mechanism, particularly 2.1% of all combinations analyzed, which corresponded to 26.4% of all detected phenotypic resistances. Most discordances were observed for specific combinations of species-antimicrobial: macrolides and tetracycline in streptococci, ciprofloxacin and β-lactams in combination with β-lactamase inhibitors in Enterobacterales, and most antimicrobials in Pseudomonas aeruginosa. WGS has the potential to be used for surveillance and routine clinical microbiology. However, in clinical microbiology settings and especially for certain species and antimicrobial agent combinations, further developments in AMR gene databases are needed to ensure higher concordance between in silico predictions and expected phenotypic AMR profiles.

3D-Printed Dip Slides Miniaturize Bacterial Identification and Antibiotic Susceptibility Tests Allowing Direct Mastitis Sample Analysis

The early detection of antimicrobial resistance remains an essential step in the selection and optimization of antibiotic treatments. Phenotypic antibiotic susceptibility testing including the measurement of minimum inhibitory concentration (MIC) remains critical for surveillance and diagnostic testing. Limitations to current testing methods include bulky labware and laborious methods. Furthermore, the requirement of a single strain of bacteria to be isolated from samples prior to antibiotic susceptibility testing delays results. The mixture of bacteria present in a sample may also have an altered resistance profile to the individual strains, and so measuring the susceptibility of the mixtures of organisms found in some samples may be desirable. To enable simultaneous MIC and bacterial species detection in a simple and rapid miniaturized format, a 3D-printed frame was designed for a multi-sample millifluidic dip-slide device that combines panels of identification culture media with a range of antibiotics (Ampicillin, Amoxicillin, Amikacin, Ceftazidime, Cefotaxime, Ofloxacin, Oxytetracycline, Streptomycin, Gentamycin and Imipenem) diluted in Muëller-Hinton Agar. Our proof-of-concept evaluation confirmed that the direct detection of more than one bacterium parallel to measuring MIC in samples is possible, which is validated using reference strains E. coli ATCC 25922, Klebsiella pneumoniae ATCC 13883, Pseudomonas aeruginosa ATCC 10145, and Staphylococcus aureus ATCC 12600 and with mastitis milk samples collected from Reading University Farm. When mixtures were tested, a MIC value was obtained that reflected the most resistant organism present (i.e., highest MIC), suggesting it may be possible to estimate a minimum effective antibiotic concentration for mixtures directly from samples containing multiple pathogens. We conclude that this simple miniaturized approach to the rapid simultaneous identification and antibiotic susceptibility testing may be suitable for directly testing agricultural samples, which is achieved through shrinking conventional tests into a simple "dip-and-incubate" device that can be 3D printed anywhere.

Recent Advances in the Use of Molecular Methods for the Diagnosis of Bacterial Infections

Infections caused by bacteria have a major impact on public health-related morbidity and mortality. Despite major advances in the prevention and treatment of bacterial infections, the latter continue to represent a significant economic and social burden worldwide. The WHO compiled a list of six highly virulent multidrug-resistant bacteria named ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) responsible for life-threatening diseases. Taken together with Clostridioides difficile, Escherichia coli, Campylobacter spp., (C. jejuni and C. coli), Legionella spp., Salmonella spp., and Neisseria gonorrhoeae, all of these microorganisms are the leading causes of nosocomial infections. The rapid and accurate detection of these pathogens is not only important for the early initiation of appropriate antibiotic therapy, but also for resolving outbreaks and minimizing subsequent antimicrobial resistance. The need for ever-improving molecular diagnostic techniques is also of fundamental importance for improving epidemiological surveillance of bacterial infections. In this review, we aim to discuss the recent advances on the use of molecular techniques based on genomic and proteomic approaches for the diagnosis of bacterial infections. The advantages and limitations of each of the techniques considered are also discussed.