Understanding disorder in monolayer graphene devices with gate-defined superlattices.

Engineering superlattices (SLs)-which are spatially periodic potential landscapes for electrons-is an emerging approach for the realization of exotic properties, including superconductivity and correlated insulators, in two-dimensional materials. While moiré SL engineering has been a popular approach, nanopatterning is an attractive alternative offering control over the pattern and wavelength of the SL. However, the disorder arising in the system due to imperfect nanopatterning is seldom studied. Here, by creating a square lattice of nanoholes in the SiO2dielectric layer using nanolithography, we study the SL potential and the disorder formed in hBN-graphene-hBN heterostructures. Specifically, we observe that while electrical transport shows distinct SL satellite peaks, the disorder of the device is significantly higher than graphene devices without any SL. We use finite-element simulations combined with a resistor network model to calculate the effects of this disorder on the transport properties of graphene. We consider three types of disorder: nanohole size variations, adjacent nanohole mergers, and nanohole vacancies. Comparing our experimental results with the model, we find that the disorder primarily originates from nanohole size variations rather than nanohole mergers in square SLs. We further confirm the validity of our model by comparing the results with quantum transport simulations. Our findings highlight the applicability of our simple framework to predict and engineer disorder in patterned SLs, specifically correlating variations in the resultant SL patterns to the observed disorder. Our combined experimental and theoretical results could serve as a valuable guide for optimizing nanofabrication processes to engineer disorder in nanopatterned SLs.

Cellulose-Based Laser-Induced Graphene Devices for Electrochemical Monitoring of Bacterial Phenazine Production and Viability.

As an easily disposable substrate with a microporous texture, paper is a well-suited, generic substrate to build analytical devices for studying bacteria. Using a multi-pass lasing process, cellulose-based laser-induced graphene (cLIG) with a sheet resistance of 43.7 ± 2.3 Ωsq-1 is developed and utilized in the fabrication of low-cost and environmentally-friendly paper sensor arrays. Two case studies with Pseudomonas aeruginosa and Escherichia coli demonstrate the practicality of the cLIG sensors for the electrochemical analysis of bacteria. The first study measures the time-dependent profile of phenazines released from both planktonic (up to 60 h) and on-chip-grown (up to 22 h) Pseudomonas aeruginosa cultures. While similarities do exist, marked differences in phenazine production are seen with cells grown directly on cLIG compared to the planktonic culture. Moreover, in planktonic cultures, pyocyanin levels increase early on and plateau around 20 h, while optical density measurements increase monotonically over the duration of testing. The second study monitors the viability and metabolic activity of Escherichia coli using a resazurin-based electrochemical assay. These results demonstrate the utility of cLIG paper sensors as an inexpensive and versatile platform for monitoring bacteria and could enable new opportunities in high-throughput antibiotic susceptibility testing, ecological studies, and biofilm studies.

Antibiotic Susceptibility, Biofilm-Forming Ability, and Prevalence of Extended-Spectrum Beta-Lactamase (ESBL)- and Biofilm-Associated Genes Among Klebsiella pneumoniae Isolates from Hospitalized Patients in Northwest of Iran.

Klebsiella pneumoniae is an opportunistic bacterium, which is globally recognized for its high prevalence and antimicrobial resistance (AMR). Biofilm-forming capability, susceptibility testing, and phenotypic confirmatory test for extended-spectrum beta-lactamase (ESBL)-producing isolate recognition of 104 K. pneumoniae isolates were performed according to the Clinical Laboratory Standard Institute (CLSI) guidelines. The prevalence of ESBL-associated genes bla-VIM, bla-NDM, and bla-OXA-48, as well as biofilm-associated genes luxS, fimH1, wza, and mrkD, was determined by multiplex PCR. The highest resistance rate was against ampicillin (100.0%). Among the 104 K. pneumoniae isolates, 52 (50.0%) and 31 (29.8%) isolates were determined as multi- and extensively drug resistant (MDR, XDR), respectively. Moreover, 21 (40.4%) isolates were determined as ESBL producing. Among 50 biofilm-producing K. pneumoniae isolates, 7 (14.0%), 15 (30.0%), and 28 (56.0%) isolates exhibited high, moderate, and weak levels of biofilm formation, respectively. A number of 41 (78.8%) isolates were susceptible to colistin, and 10 (19.2%) were resistant. AMR was significantly higher (P < 0.05) in the biofilm-forming isolates compared with non-biofilm formers.

99mTc- Anionic dendrimer targeted vascular endothelial growth factor as a novel nano-radiotracer for in-vivo breast cancer imaging.

Since breast cancer is the commonly cause of death among women around the world, diagnosis at the early stages is significantly important to prevent the metastasis of the cancer. Among the various growth factors that are involved in angiogenesis, vascular endothelial growth factor (VEGF) is believed to be the most important factor. Overexpressed VEGF receptor on tumors surface, is particularly interesting for cancer cells targeting purposes. In this study, citric acid dendrimer conjugated with VEGF antagonist peptide was synthesized. The obtained product was confirmed by FT-IR, TEM, DLS, and EDS. In vitro cytotoxicity assay showed no toxicity on normal cells and indicated the notably dose-dependence toxicity on cancer cells. Box-Behnken software as a computational method was used to determine the optimum amount of radiolabeling parameters. Optimized parameters for reducing agent, dendrimer-anti-VEGF, and time were 1.4 mg, 17.5 mg, and about 30 min respectively. Radiochemical purity of radio-labeled conjugated dendrimer was determined about 90 percent. SPECT imaging was done to observe the in vivo accumulation of dendrimer-anti-VEGF in the tumor site. Images showed high accumulation of radio-tracer in the tumor region. All in all, obtained results confirmed our hypothesis that the dendrimer-anti-VEGF can be a good radio-tracer for diagnosis of cancer.

Evaporation-induced stimulation of bacterial osmoregulation for electrical assessment of cell viability.

Bacteria cells use osmoregulatory proteins as emergency valves to respond to changes in the osmotic pressure of their external environment. The existence of these emergency valves has been known since the 1960s, but they have never been used as the basis of a viability assay to tell dead bacteria cells apart from live ones. In this paper, we show that osmoregulation provides a much faster, label-free assessment of cell viability compared with traditional approaches that rely on cell multiplication (growth) to reach a detectable threshold. The cells are confined in an evaporating droplet that serves as a dynamic microenvironment. Evaporation-induced increase in ionic concentration is reflected in a proportional increase of the droplet's osmotic pressure, which in turn, stimulates the osmoregulatory response from the cells. By monitoring the time-varying electrical conductance of evaporating droplets, bacterial cells are identified within a few minutes compared with several hours in growth-based methods. To show the versatility of the proposed method, we show detection of WT and genetically modified nonhalotolerant cells (Salmonella typhimurium) and dead vs. live differentiation of nonhalotolerant (such as Escherichia coli DH5α) and halotolerant cells (such as Staphylococcus epidermidis). Unlike the growth-based techniques, the assay time of the proposed method is independent of cell concentration or the bacteria type. The proposed label-free approach paves the road toward realization of a new class of real time, array-formatted electrical sensors compatible with droplet microfluidics for laboratory on a chip applications.

Analyzing Thermal Stability of Cell Membrane of Salmonella Using Time-Multiplexed Impedance Sensing.

Heat treatment is one of the most widely used methods for inactivation of bacteria in food products. Heat-induced loss of bacterial viability has been variously attributed to protein denaturation, oxidative stress, or membrane leakage; indeed, it is likely to involve a combination of these processes. We examine the effect of mild heat stress (50-55°C for ≤12 min) on cell permeability by directly measuring the electrical conductance of samples of Salmonella enterica serovar Typhimurium to answer a fundamental biophysical question, namely, how bacteria die under mild heat stress. Our results show that when exposed to heat shock, the cell membrane is damaged and cells die mainly due to the leakage of small cytoplasmic species to the surrounding media without lysis (confirmed by fluorescent imaging). We measured the conductance change, ΔY, of wild-type versus genetically modified heat-resistant (HR) cells in response to pulse and ramp heating profiles with different thermal time constants. In addition, we developed a phenomenological model to correlate the membrane damage, cytoplasmic leakage, and cell viability. This model traces the differential viability and ΔY of wild-type and HR cells to the difference in the effective activation energies needed to permeabilize the cells, implying that HR cells are characterized by stronger lateral interactions between molecules, such as lipids, in their cell envelope.

Droplet-based non-faradaic impedance sensors for assessment of susceptibility of Escherichia coli to ampicillin in 60 min.

Direct antibiotic susceptibility tests (AST) are essential for rapid detection of bacterial infection and administration of appropriate antibiotics. Conventional AST systems are usually slow as they rely on cell growth for an indirect assessment of antibiotics' effectiveness. Therefore, a faster method is desirable, especially for emergency cases. In this work, we studied the performance of label-free, droplet-based impedance sensors for rapid characterization of the effects of ampicillin (Amp) on Escherichia coli. Ampicillin damages cell wall integrity and makes cells permeable (leaky). The leakage results in significant increase of the electrical conductance measured directly by the microfabricated sensing unit. We studied the conductance signal as a function of both antibiotic treatment time and dosage and demonstrated susceptibility testing within 60 min. These findings demonstrate the potential of droplet-based electrical chips for the realization of electrical antibiotic susceptibility testing (e-AST) for early-stage diagnostic/treatment, and consequently, preventing antibiotic misuse/overuse.

Systematic Study of Various Functionalization Steps for Ultrasensitive Detection of SARS-CoV-2 with Direct Laser-Functionalized Au-LIG Electrochemical Sensors.

The 2019 coronavirus (COVID-19) pandemic impaired global health, disrupted society, and slowed the economy. Early detection of the infection using highly sensitive diagnostics is crucial in preventing the disease's spread. In this paper, we demonstrate electrochemical sensors based on laser induced graphene (LIG) functionalized directly with gold (Au) nanostructures for the detection of SARS-CoV-2 with an outstanding limit of detection (LOD) of ∼1.2 ag·mL-1. To achieve the optimum performance, we explored various functionalization parameters to elucidate their impact on the LOD, sensitivity, and linearity. Specifically, we investigated the effect of (i) gold precursor concentration, (ii) cross-linker chemistry, (iii) cross-linker and antibody incubation conditions, and (iv) antigen-sensor interaction (diffusion-dominated incubation vs pipette-mixing), as there is a lack of a systematic study of these parameters. Our benchmarking analysis highlights the critical role of the antigen-sensor interaction and cross-linker chemistry. We showed that pipette-mixing enhances sensitivity and LOD by more than 1.6- and 5.5-fold, respectively, and also enables multimodal readout compared to diffusion-dominated incubation. Moreover, the PBA/Sulfo-NHS: EDC cross-linker improves the sensitivity and LOD compared to PBASE. The sensors demonstrate excellent selectivity against other viruses, including HCoV-229E, HCoV-OC43, HCoV-NL63, and influenza H5N1. Beyond the ability to detect antigen fragments, our sensors enable the detection of antigen-coated virion mimics (which are a better representative of the real infection) down to an ultralow concentration of ∼5 particles·mL-1.

Recent advances in graphene-based electroanalytical devices for healthcare applications.

Graphene, with its outstanding mechanical, electrical, and biocompatible properties, stands out as an emerging nanomaterial for healthcare applications, especially in building electroanalytical biodevices. With the rising prevalence of chronic diseases and infectious diseases, such as the COVID-19 pandemic, the demand for point-of-care testing and remote patient monitoring has never been greater. Owing to their portability, ease of manufacturing, scalability, and rapid and sensitive response, electroanalytical devices excel in these settings for improved healthcare accessibility, especially in resource-limited settings. The development of different synthesis methods yielding large-scale graphene and its derivatives with controllable properties, compatible with device manufacturing - from lithography to various printing methods - and tunable electrical, chemical, and electrochemical properties make it an attractive candidate for electroanalytical devices. This review article sheds light on how graphene-based devices can be transformative in addressing pressing healthcare needs, ranging from the fundamental understanding of biology in in vivo and ex vivo studies to early disease detection and management using in vitro assays and wearable devices. In particular, the article provides a special focus on (i) synthesis and functionalization techniques, emphasizing their suitability for scalable integration into devices, (ii) various transduction methods to design diverse electroanalytical device architectures, (iii) a myriad of applications using devices based on graphene, its derivatives, and hybrids with other nanomaterials, and (iv) emerging technologies at the intersection of device engineering and advanced data analytics. Finally, some of the major hurdles that graphene biodevices face for translation into clinical applications are discussed.

Mechanistic Insight into Intestinal α-Synuclein Aggregation in Parkinson's Disease Using a Laser-Printed Electrochemical Sensor.

Aggregated deposits of the protein α-synuclein and depleting levels of dopamine in the brain correlate with Parkinson's disease development. Treatments often focus on replenishing dopamine in the brain; however, the brain might not be the only site requiring attention. Aggregates of α-synuclein appear to accumulate in the gut years prior to the onset of any motor symptoms. Enteroendocrine cells (specialized gut epithelial cells) may be the source of intestinal α-synuclein, as they natively express this protein. Enteroendocrine cells are constantly exposed to gut bacteria and their metabolites because they border the gut lumen. These cells also express the dopamine metabolic pathway and form synapses with vagal neurons, which innervate the gut and brain. Through this connection, Parkinson's disease pathology may originate in the gut and spread to the brain over time. Effective therapeutics to prevent this disease progression are lacking due to a limited understanding of the mechanisms by which α-synuclein aggregation occurs in the gut. We previously proposed a gut bacterial metabolic pathway responsible for the initiation of α-synuclein aggregation that is dependent on the oxidation of dopamine. Here, we develop a new tool, a laser-induced graphene-based electrochemical sensor chip, to track α-synuclein aggregation and dopamine level over time. Using these sensor chips, we evaluated diet-derived catechols dihydrocaffeic acid and caffeic acid as potential inhibitors of α-synuclein aggregation. Our results suggest that these molecules inhibit dopamine oxidation. We also found that these dietary catechols inhibit α-synuclein aggregation in STC-1 enteroendocrine cells. These findings are critical next steps to reveal new avenues for targeted therapeutics to treat Parkinson's disease, specifically in the context of functional foods that may be used to reshape the gut environment.

Frequencies of mobilized colistin resistance (mcr-1, 2) genes in clinically isolated Escherichia coli; a cross sectional study.

OBJECTIVE: Escherichia coli (E. coli) is an opportunistic bacterium, which is globally recognized for its high prevalence and antimicrobial resistance (AMR). The presence of colistin-resistant representative mcr- 1, 2 genes in multi-drug resistant (MDR) clinically isolated E. coli is the main goal of this survey. After biochemically and molecular confirmation tests, susceptibility testing, biofilm formation, and minimum inhibitory concentration to colistin were performed on 100 E. coli isolates. Subsequently, taking advantage of uniplex-PCR, the presence of some responsible genes (mcr- 1, mcr- 2) to colistin-resistant phenotypes in mentioned bacterium was assessed. RESULTS: Disc diffusion methods indicated that the highest resistance rate was against ampicillin (80.0%), and trimethoprim/sulfamethoxazole (63%). Among the E. coli isolates, 72 (72.0%) was determined as MDR, respectively. Moreover, 47 (47%) strains were determined as extreme beta-lactamase (ESBL) phenotypes. Among 41 slime-producing E. coli strains, 7 (17.07%), 14 (34.14%), and 20 (48.78%) strains exhibited high, moderate, and weak levels of biofilm formation, respectively. Fifty-nine (81.94%), and 1(100%) of MDR isolates were assessed as colistin resistant (MIC > 2) and susceptible (MIC ≤ 2) as well. In 26(36.11%) of colistin-resistant isolates and 1(1.38%) of colistin, susceptible isolate mcr-1 gene was found. There is no mcr- 2 gene was detected in isolates. CONCLUSION: The diversity of high antibiotic-resistant rates could be avoided by developing appropriate healthcare policies and community awareness. Alarming resistance rates were observed in colistin and ampicillin, which should be taken into account in therapy guidelines.

Rapid and sensitive detection of viral particles by coupling redox cycling and electrophoretic enrichment.

The COVID-19 pandemic has highlighted the need for rapid, low-cost, and sensitive virus detection platforms to monitor and mitigate widespread outbreaks. Electrochemical sensors are a viable choice to fill this role but still require improvements to the signal magnitude, especially for early detection and low viral loads. Herein, finite element analysis of a novel biosensor concept for single virion counting using a generator-collector microelectrode design is presented. The proposed design combines a redox-cycling amplified electrochemical current with electrophoresis-driven electrode-particle collision for rapid virus detection. The effects of experimental (e.g. scan rate, collector bias) and geometric factors are studied to optimize the sensor design. Two generator-collector configurations are explored: a ring-disk configuration to analyze sessile droplets and an interdigitated electrode (IDE) design housed in a microchannel. For the ring-disk configuration, we calculate an amplification factor of ∼5 and collector efficiency of ∼0.8 for a generator-collector spacing of 600 nm. For the IDE, the collector efficiency is even larger, approaching unity. The dual-electrode mode is critical for increasing the current and electric field strength. As a result, the current steps upon virus capture are more than an order of magnitude larger compared to single-mode. Additionally, single virus capture times are reduced from over 700 s down to ∼20 s. Overall, the frequency of virus capture and magnitude of the electrochemical current steps depend on the virus properties and electrode configuration, with the IDE capable of single virus detection within seconds owing to better particle confinement in the microchannel.

Agar-Integrated Three-Dimensional Microelectrodes for On-Chip Impedimetric Monitoring of Bacterial Viability.

Monitoring bacterial viability is critical in food safety, clinical microbiology, therapeutics, and microbial fuel cell applications. Traditional techniques for detecting and counting viable cells are slow, require expensive and bulky analytical tools and labeling agents, or are destructive to cells. Development of low-cost, portable diagnostics to enable label-free detection and in situ probing of bacterial viability can significantly advance the biomedical field (both applied and basic research). We developed a highly sensitive method for the detection of bacterial viability based on their metabolic activity using non-Faradaic impedimetric sensors comprised of three-dimensional (3D) interdigitated microelectrodes (3D-IDME). Specifically, the 3D-IDME is modified with electrolessly deposited gold (Au) nanoparticles which amplify the sensitivity by increasing the sensing area. A nutrient-rich agarose gel as the seeding layer is integrated with the sensor to enable direct culturing of bacteria and probing of their metabolic activity in situ. The proposed platform enables monitoring of bacterial viability, even in lag-phase, as they metabolize and release ionic species into the surrounding environment (nutrient agar layer). The sensor can detect down to 104 CFU/mL (~2.5 CFU/mm2) of Escherichia coli K12 (a model strain) in under 1 h without the need for any labeling. By integrating these sensors with agar layers containing different types/concentrations of antibacterial agents, this work can be expanded to enable rapid, high-throughput antibacterial susceptibility testing which can in turn assist caregivers in early prescription of the right treatment to patients with clinical conditions.

A machine learning-based multimodal electrochemical analytical device based on eMoSx-LIG for multiplexed detection of tyrosine and uric acid in sweat and saliva.

Multiplexed detection of biomolecules is of great value in various fields, from disease diagnosis to food safety and environmental monitoring. However, accurate and multiplexed analyte detection is challenging to achieve in mixtures using a single device/material. In this paper, we demonstrate a machine learning (ML)-powered multimodal analytical device based on a single sensing material made of electrodeposited molybdenum polysulfide (eMoSx) on laser induced graphene (LIG) for multiplexed detection of tyrosine (TYR) and uric acid (UA) in sweat and saliva. Electrodeposition of MoSx shows an increased electrochemically active surface area (ECSA) and heterogeneous electron transfer rate constant, k0. Features are extracted from the electrochemical data in order to train ML models to predict the analyte concentration in the sample (both singly spiked and mixed samples). Different ML architectures are explored to optimize the sensing performance. The optimized ML-based multimodal analytical system offers a limit of detection (LOD) that is two orders of magnitude better than conventional approaches which rely on single peak analysis. A flexible and wearable sensor patch is also fabricated and validated on-body, achieving detection of UA and TYR in sweat over a wide concentration range. While the performance of the developed approach is demonstrated for detecting TYR and UA using eMoSx-LIG sensors, it is a general analytical methodology and can be extended to a variety of electrochemical sensors to enable accurate, reliable, and multiplexed sensing.

Electrochemical Sensors Based on MoSx -Functionalized Laser-Induced Graphene for Real-Time Monitoring of Phenazines Produced by Pseudomonas aeruginosa.

Pseudomonas aeruginosa (P. aeruginosa) is an opportunistic pathogen causing infections in blood and implanted devices. Traditional identification methods take more than 24 h to produce results. Molecular biology methods expedite detection, but require an advanced skill set. To address these challenges, this work demonstrates functionalization of laser-induced graphene (LIG) for developing flexible electrochemical sensors for P. aeruginosa based on phenazines. Electrodeposition as a facile approach is used to functionalize LIG with molybdenum polysulfide (MoSx ). The sensor's limit of detection (LOD), sensitivity, and specificity are determined in broth, agar, and wound simulating medium (WSM). Control experiments with Escherichia coli, which does not produce phenazines, demonstrate specificity of sensors for P. aeruginosa. The LOD for pyocyanin (PYO) and phenazine-1-carboxylic acid (PCA) is 0.19 × 10-6  and 1.2 × 10-6  m, respectively. Furthermore, the highly stable sensors enable real-time monitoring of P. aeruginosa biofilms over several days. Comparing square wave voltammetry data over time shows time-dependent generation of phenazines. In particular, two configurations-"Normal" and "Flipped"-are studied, showing that the phenazines time dynamics vary depending on how cells interact with sensors. The reported results demonstrate the potential of the developed sensors for integration with wound dressings for early diagnosis of P. aeruginosa infection.

Non-Enzymatic Detection of Glucose in Neutral Solution Using PBS-Treated Electrodeposited Copper-Nickel Electrodes.

Transition metals have been explored extensively for non-enzymatic electrochemical detection of glucose. However, to enable glucose oxidation, the majority of reports require highly alkaline electrolytes which can be damaging to the sensors and hazardous to handle. In this work, we developed a non-enzymatic sensor for detection of glucose in near-neutral solution based on copper-nickel electrodes which are electrochemically modified in phosphate-buffered saline (PBS). Nickel and copper were deposited using chronopotentiometry, followed by a two-step annealing process in air (Step 1: at room temperature and Step 2: at 150 °C) and electrochemical stabilization in PBS. Morphology and chemical composition of the electrodes were characterized using scanning electron microscopy and energy-dispersive X-ray spectroscopy. Cyclic voltammetry was used to measure oxidation reaction of glucose in sodium sulfate (100 mM, pH 6.4). The PBS-Cu-Ni working electrodes enabled detection of glucose with a limit of detection (LOD) of 4.2 nM, a dynamic response from 5 nM to 20 mM, and sensitivity of 5.47 ± 0.45 µA cm-2/log10(mole.L-1) at an applied potential of 0.2 V. In addition to the ultralow LOD, the sensors are selective toward glucose in the presence of physiologically relevant concentrations of ascorbic acid and uric acid spiked in artificial saliva. The optimized PBS-Cu-Ni electrodes demonstrate better stability after seven days storage in ambient compared to the Cu-Ni electrodes without PBS treatment.

Facile Post-deposition Annealing of Graphene Ink Enables Ultrasensitive Electrochemical Detection of Dopamine.

A growing body of research focuses on engineering materials for electrochemical detection of dopamine (DA), a critical neurotransmitter involved in motor function, reward processes, and blood pressure regulation. Among various sensing materials, graphene is highly attractive due to its excellent electrical conductivity and, in particular, the π-π interaction between the aromatic rings of DA and graphene. However, the lowest detection limits reported solely using graphene are nominally 1 nM. To improve the sensor sensitivity, various strategies are being explored, including chemical functionalization, heterostructure/composite formation, elemental doping, and modification with biomolecules (aptamers, enzymes, etc.). In this work, we demonstrate that commercially available graphene ink can exhibit selective and highly sensitive detection of DA by tuning the surface chemistry utilizing a simple, one-step annealing process. The annealing condition directly impacts the sensor response to DA, with the optimal conditions (30 min at 300 °C under 3% H2 + Ar) yielding a distinguishable and selective response to DA down to 5 pM. X-ray photoelectron spectroscopy (XPS) confirms that the improved selectivity is due to the increased fraction of oxygen functionalities (in particular, C-OH), while Raman spectroscopy shows a higher degree of defectiveness for this condition compared to others. Evaluation of the interaction of three molecular components of DA (i.e., aromatic ring, hydroxyl groups, and amine group) with graphene confirms that the π-π interaction and -OH groups play a prominent role in the improved adsorption of DA on the graphene surface. Furthermore, we demonstrate a proof-of-concept, all-solution processable sensor on polyimide substrates using graphene ink. Tuning the sensor response by varying the annealing condition offers a simple avenue for developing sensitive, selective, and low-cost point-of-care biosensors, while low-temperature annealing ensures compatibility with flexible substrates, such as polyimide.

Organic redox-active crystalline layers for reagent-free electrochemical antibiotic susceptibility testing (ORACLE-AST).

Rapid antibiotic susceptibility testing (AST) is critical in determining bacterial resistance or susceptibility to a particular antibiotic. Simple-to-use phenotype-based AST platforms can assist care-givers in timely prescription of the right antibiotic. Monitoring the change of bacterial viability by measuring electrochemical Faradaic current is a promising approach for rapid AST. However, the existing works require mixing redox-active reagents in the solution which can interfere with the antibiotics. In this paper, we developed a facile electrodeposition process for creating a redox-active crystalline layer (denoted as RZx) on pyrolytic graphite sheets (PGS), which was then utilized as the sensing layer for reagent-free electrochemical AST. To demonstrate the proof-of-principle, we tested the sensors with Escherichia coli (E. coli) K-12 treated with two antibiotics, ampicillin and kanamycin. While the sensors enable detection of bacterial metabolism mainly due to pH-sensitivity of RZx (∼ 53 mV/pH), secreted redox-active metabolites/compounds from whole cells are likely contributing to the signal as well. By monitoring the differential voltammetric signals, the sensors enable accurate prediction of the minimum inhibitory concentration (MIC) in 60 min (p < 0.03). The sensors are stable after 60 days storage in ambient conditions and enable analysis of microbial viability in complex solutions, as demonstrated in spiked milk and human whole blood.

Pathogen-specific antimicrobials engineered de novo through membrane-protein biomimicry.

Precision antimicrobials aim to kill pathogens without damaging commensal bacteria in the host, and thereby cure disease without antibiotic-associated dysbiosis. Here we report the de novo design of a synthetic host defence peptide that targets a specific pathogen by mimicking key molecular features of the pathogen's channel-forming membrane proteins. By exploiting physical and structural vulnerabilities within the pathogen's cellular envelope, we designed a peptide sequence that undergoes instructed tryptophan-zippered assembly within the mycolic acid-rich outer membrane of Mycobacterium tuberculosis to specifically kill the pathogen without collateral toxicity towards lung commensal bacteria or host tissue. These mycomembrane-templated assemblies elicit rapid mycobactericidal activity and enhance the potency of antibiotics by improving their otherwise poor diffusion across the rigid M. tuberculosis envelope with respect to agents that exploit transmembrane protein channels for antimycobacterial activity. This biomimetic strategy may aid the design of other narrow-spectrum antimicrobial peptides.

Dynamic Laser Speckle Imaging Meets Machine Learning to Enable Rapid Antibacterial Susceptibility Testing (DyRAST).

Rapid antibacterial susceptibility testing (RAST) methods are of significant importance in healthcare, as they can assist caregivers in timely administration of the correct treatments. Various RAST techniques have been reported for tracking bacterial phenotypes, including size, shape, motion, and redox state. However, they still require bulky and expensive instruments-which hinder their application in resource-limited environments-and/or utilize labeling reagents which can interfere with antibiotics and add to the total cost. Furthermore, the existing RAST methods do not address the potential gradual adaptation of bacteria to antibiotics, which can lead to a false diagnosis. In this work, we present a RAST approach by leveraging machine learning to analyze time-resolved dynamic laser speckle imaging (DLSI) results. DLSI captures the change in bacterial motion in response to antibiotic treatments. Our method accurately predicts the minimum inhibitory concentration (MIC) of ampicillin and gentamicin for a model strain of Escherichia coli (E. coli K-12) in 60 min, compared to 6 h using the currently FDA-approved phenotype-based RAST technique. In addition to ampicillin (a ß-lactam) and gentamicin (an aminoglycoside), we studied the effect of ceftriaxone (a third-generation cephalosporin) on E. coli K-12. The machine learning algorithm was trained and validated using the overnight results of a gold standard antibacterial susceptibility testing method enabling prediction of MIC with a similarly high accuracy yet substantially faster.