Rapid bacterial detection and antibiotic susceptibility testing in whole blood using one-step, high throughput blood digital PCR

Detection and quantification of Brucella abortus DNA in water buffaloes (bubalus bubalis) using droplet digital polymerase chain reaction

Brucellosis represents a major public health concern worldwide. Human transmission is mainly due to the consumption of unpasteurized milk and dairy products of infected animals. The gold standard for the diagnosis of Brucella spp in ruminants is the bacterial isolation, but it is time-consuming. Polymerase Chain Reaction (PCR) is a quicker and more sensitive technique than bacterial culture. Droplet digital PCR (ddPCR) is a novel molecular assay showing high sensitivity in samples with low amount of DNA and lower susceptibility to amplification inhibitors. Present study aimed to develop a ddPCR protocol for the detection of Brucella abortus in buffalo tissue samples. The protocol was validated using proficiency test samples for Brucella spp by real time qPCR. Furthermore, 599 tissue samples were examined. Among reference materials, qPCR and ddPCR demonstrated same performance and were able to detect up to 225 CFU/mL. Among field samples, ddPCR showed higher sensitivity (100%), specificity and accuracy of 93.4% and 94.15%, respectively. ddPCR could be considered a promising technique to detect B. abortus in veterinary specimens, frequently characterized by low amount of bacteria, high diversity in matrices and species and poor storage conditions.

Lab-In-Fiber Optofluidic Device for Droplet Digital Polymerase Chain Reaction (DdPCR) with Real-Time Monitoring

Droplet microfluidic systems have emerged as indispensable and advanced tools in contemporary biological science. A prominent example is the droplet digital polymerase chain reaction (ddPCR), which plays a pivotal role in next-generation sequencing and the detection of rare nucleic acids or mutations. However, existing optical detection configurations are bulky, intricate, and costly, and require meticulous optical alignment to optimize fluorescence sensing. Herein, we propose a lab-in-fiber optofluidic system (LiFO), which provides a stable and compact footprint, self-alignment, and enhanced optical coupling for high-accuracy ddPCR. Moreover, LiFO could expand its capabilities for multiangle-scattering light collection in which we collect focused forward-scattering light (fFSL) to enable real-time droplet counting and size monitoring. To accomplish these attributes, LiFO incorporates optical fibers, along with fabricated PDMS grooves, for a self-aligned optical setup to implement simultaneous fluorescence and scattering detection. Furthermore, LiFO harnesses the concept of flowing droplets functioning as microlenses, which allows us to collect and translate fFSL signals into droplet size information. We have demonstrated the effectiveness of LiFO in ddPCR applications, illustrating its capacity to enhance the accuracy and precision of DNA quantification. Notably, LiFO exhibits improved linearity in the measurement of serial DNA dilutions, reflected by an increase in R2 from 0.956 to 0.997. These results demonstrate the potential of LiFO to serve as a valuable tool across a wide spectrum of droplet microfluidic platforms, offering opportunities for advancement in practical applications.

High-throughput fluorescence sensing array based on tetraphenylethylene derivatives for detecting and distinguishing pathogenic microbes

Infections induced by pathogenic microorganisms will bring negative effects such as diseases that damage health and result in heavy economic burden. Therefore, it is very important to detect and identify the pathogens in time. Moreover, traditional clinical diagnosis or food testing often faces the problem of dealing with a large number of samples. Here, we designed a high-throughput fluorescent sensor array based on the different binding ability of five tetraphenylethylene derivatives (TPEs) with various side chains to different kinds of pathogenic microbes, which is used to detect and distinguish various species, so as to realize rapid mass diagnosis, and hopefully provide guidance for further determination of microbial infections and clinical treatment.

Phenotypic and genotypic perspectives on detection methods for bacterial antimicrobial resistance in a One Health context: research progress and prospects

The widespread spread of bacterial antimicrobial resistance (AMR) and multidrug-resistant bacteria poses a significant threat to global public health. Traditional methods for detecting bacterial AMR are simple, reproducible, and intuitive, requiring long time incubation and high labor intensity. To quickly identify and detect bacterial AMR is urgent for clinical treatment to reduce mortality rate, and many new methods and technologies were required to be developed. This review summarizes the current phenotypic and genotypic detection methods for bacterial AMR. Phenotypic detection methods mainly include antimicrobial susceptibility tests, while genotypic detection methods have higher sensitivity and specificity and can detect known or even unknown drug resistance genes. However, most of the current tests are either genotypic or phenotypic and rarely combined. Combining the advantages of phenotypic and genotypic methods, combined with the joint application of multiple rapid detection methods may be the trend for future AMR testing. Driven by rapid diagnostic technology, big data analysis, and artificial intelligence, detection methods of bacterial AMR are expected to constantly develop and innovate. Adopting rational detection methods and scientific data analysis can better address the challenges of bacterial AMR and ensure human health and social well-being.

A Novel Truncated CHAP Modular Endolysin, CHAPSAP26-161, That Lyses Staphylococcus aureus, Acinetobacter baumannii, and Clostridioides difficile, and Exhibits Therapeutic Effects in a Mouse Model of A. baumannii Infection

Development of novel antibacterial agents is imperative due to the increasing threat of antibiotic-resistant pathogens. This study aimed to develop the enhanced antibacterial activity and in-vivo efficacy of a novel truncated endolysin, CHAPSAP26-161, derived from the endolysin LysSAP26, against multidrug-resistant bacteria. CHAPSAP26-161 exhibited higher protein purification efficiency in E. coli and antibacterial activity than LysSAP26. Moreover, CHAPSAP26-161 showed the higher lytic activity against A. baumannii with minimal bactericidal concentrations (MBCs) of 5-10 μg/ml, followed by Staphylococcus aureus with MBCs of 10-25 μg/ml. Interestingly, CHAPSAP26-161 could lyse anaerobic bacteria, such as Clostridioides difficile, with MBCs of 25-50 μg/ml. At pH 4-8 and temperatures of 4°C-45°C, CHAPSAP26-161 maintained antibacterial activity without remarkable difference. The lytic activity of CHAPSAP26-161 was increased with Zn2+. In vivo tests demonstrated the therapeutic effects of CHAPSAP26-161 in murine systemic A. baumannii infection model. In conclusion, CHAPSAP26-161, a truncated endolysin that retains only the CHAP domain from LysSAP26, demonstrated enhanced protein purification efficiency and antibacterial activity compared to LysSAP26. It further displayed broad-spectrum antibacterial effects against S. aureus, A. baumannii, and C. difficile. Our in vitro and in-vivo results of CHAPSAP26-161 highlights its promise as an innovative therapeutic option against those bacteria with multiple antibiotic resistance.

Blood culture-free ultra-rapid antimicrobial susceptibility testing

Treatment assessment and patient outcome for sepsis depend predominantly on the timely administration of appropriate antibiotics1-3. However, the clinical protocols used to stratify and select patient-specific optimal therapy are extremely slow4. In particular, the major hurdle in performing rapid antimicrobial susceptibility testing (AST) remains in the lengthy blood culture procedure, which has long been considered unavoidable due to the limited number of pathogens present in the patient's blood. Here we describe an ultra-rapid AST method that bypasses the need for traditional blood culture, thereby demonstrating potential to reduce the turnaround time of reporting drug susceptibility profiles by more than 40-60 h compared with hospital AST workflows. Introducing a synthetic beta-2-glycoprotein I peptide, a broad range of microbial pathogens are selectively recovered from whole blood, subjected to species identification or instantly proliferated and phenotypically evaluated for various drug conditions using a low-inoculum AST chip. The platform was clinically evaluated by the enrolment of 190 hospitalized patients suspected of having infection, achieving 100% match in species identification. Among the eight positive cases, six clinical isolates were retrospectively tested for AST showing an overall categorical agreement of 94.90% with an average theoretical turnaround time of 13 ± 2.53 h starting from initial blood processing.

Clinical evaluation of droplet digital PCR in the early identification of suspected sepsis patients in the emergency department: a prospective observational study

Background

Rapid and accurate diagnosis of the causative agents is essential for clinical management of bloodstream infections (BSIs) that might induce sepsis/septic shock. A considerable number of suspected sepsis patients initially enter the health-care system through an emergency department (ED), hence it is vital to establish an early strategy to recognize sepsis and initiate prompt care in ED. This study aimed to evaluate the diagnostic performance and clinical value of droplet digital PCR (ddPCR) assay in suspected sepsis patients in the ED.

Methods

This was a prospective single-centered observational study including patients admitted to the ED from 25 October 2022 to 3 June 2023 with suspected BSIs screened by Modified Shapiro Score (MSS) score. The comparison between ddPCR and blood culture (BC) was performed to evaluate the diagnostic performance of ddPCR for BSIs. Meanwhile, correlative analysis between ddPCR and the inflammatory and prognostic-related biomarkers were conducted to explore the relevance. Further, the health economic evaluation of the ddPCR was analyzed.

Results

258 samples from 228 patients, with BC and ddPCR performed simultaneously, were included in this study. We found that ddPCR results were positive in 48.13% (103 of 214) of episodes, with identification of 132 pathogens. In contrast, BC only detected 18 positives, 88.89% of which were identified by ddPCR. When considering culture-proven BSIs, ddPCR shows an overall sensitivity of 88.89% and specificity of 55.61%, the optimal diagnostic power for quantifying BSI through ddPCR is achieved with a copy cutoff of 155.5. We further found that ddPCR exhibited a high accuracy especially in liver abscess patients. Among all the identified virus by ddPCR, EBV has a substantially higher positive rate with a link to immunosuppression. Moreover, the copies of pathogens in ddPCR were positively correlated with various markers of inflammation, coagulation, immunity as well as prognosis. With high sensitivity and specificity, ddPCR facilitates precision antimicrobial stewardship and reduces health care costs.

Conclusions

The multiplexed ddPCR delivers precise and quantitative load data on the causal pathogen, offers the ability to monitor the patient's condition and may serve as early warning of sepsis in time-urgent clinical situations as ED.

Importance

Early detection and effective administration of antibiotics are essential to improve clinical outcomes for those with life-threatening infection in the emergency department. ddPCR, an emerging tool for rapid and sensitive pathogen identification used as a precise bedside test, has developed to address the current challenges of BSI diagnosis and precise treatment. It characterizes sensitivity, specificity, reproducibility, and absolute quantifications without a standard curve. ddPCR can detect causative pathogens and related resistance genes in patients with suspected BSIs within a span of three hours. In addition, it can identify polymicrobial BSIs and dynamically monitor changes in pathogenic microorganisms in the blood and can be used to evaluate antibiotic efficacy and survival prognosis. Moreover, the copies of pathogens in ddPCR were positively correlated with various markers of inflammation, coagulation, immunity. With high sensitivity and specificity, ddPCR facilitates precision antimicrobial stewardship and reduces health care costs.

Droplet digital PCR aids in the diagnosis of children with fever of unknown origin --A typical case report

Many clinical conditions can cause fever of unknown origin (FUO) in children, but the etiological diagnosis remains challenging despite the variety of inspection methods available at present. This study aims to investigate the effectiveness of droplet digital polymerase chain reaction (ddPCR) in identifying pathogens in children with FUO as a novel application. A 7-month-old boy failed to obtain etiology evidence for his disease through various tests. After collecting peripheral blood for ddPCR analysis, Staphylococcus aureus and Escherichia coli were detected, and Sanger sequencing confirmed the pathogens. During the disease, the child developed septic arthritis and osteomyelitis in the femur. Despite the patient's fever being removed, his limb activity improving, and inflammatory biomarkers decreasing, avascular necrosis of the femoral head remained after targeted antibiotic treatment and surgery. If the patient had undergone ddPCR analysis at an early stage, it may be possible to avoid sequelae. ddPCR helps identify pathogens in the diagnosis of children with FUO and could be a promising complementary tool.

Microfluidic technologies for advanced antimicrobial susceptibility testing

Antimicrobial resistance is getting serious and becoming a threat to public health worldwide. The improper and excessive use of antibiotics is responsible for this situation. The standard methods used in clinical laboratories, to diagnose bacterial infections, identify pathogens, and determine susceptibility profiles, are time-consuming and labor-intensive, leaving the empirical antimicrobial therapy as the only option for the first treatment. To prevent the situation from getting worse, evidence-based therapy should be given. The choosing of effective drugs requires powerful diagnostic tools to provide comprehensive information on infections. Recent progress in microfluidics is pushing infection diagnosis and antimicrobial susceptibility testing (AST) to be faster and easier. This review summarizes the recent development in microfluidic assays for rapid identification and AST in bacterial infections. Finally, we discuss the perspective of microfluidic-AST to develop the next-generation infection diagnosis technologies.

A novel multifunctional SERS microfluidic sensor based on ZnO/Ag nanoflower arrays for label-free ultrasensitive detection of bacteria

This study proposes a microfluidic platform for rapid enrichment and ultrasensitive SERS detection of bacteria. The platform comprises ZnO nanoflower arrays decorated with silver nanoparticles to enhance the SERS sensitivity. The ZnO nanoflower array substrate with a 3D reticular columnar structure is prepared using the hydrothermal method. SEM analysis depicts the 3.05 μm gap distribution of the substrate array to intercept the most bacteria in the particle sizes range of 0.5 to 3 μm. Then, silver nanoparticles are deposited on the ZnO nano-array surface by liquid evaporation self-assembly. TEM and SEM analysis indicate nanosize of Ag particles, evenly distributed on the substrate, enhancing the SERS efficiency and improving sensing reproducibility. The probe molecules (R6G) are tested to demonstrate the high SERS activity of the proposed microfluidic sensor. Then, Escherichia coli, Staphylococcus aureus, Enterococcus faecalis, and Bacillus subtilis are selected, demonstrating the sensor's excellent bacterial capture and sensitive recognition capabilities, with a detection limit as low as 102 CFU mL-1. Additionally, the antibacterial properties of ZnO/Ag heterojunction nanostructures are studied, suggesting their ability to inactivate bacteria. Compared with the traditional Au-enhanced chip, the sensor preparation is easy, safe, reliable, and low-cost. Moreover, the ZnO nano-array exhibits a large specific surface area, high interception ability, stronger and uniform SERS performance, and effective and reliable detection of trace pathogens. This work provides potential future ZnO/Ag microfluidic SERS sensor applications for rapid, unlabeled, and trace pathogens detection in clinical and environmental applications, potentially achieving breakthroughs in early detection, prevention, and treatment.

A retrospective study of the detection of sepsis pathogens comparing blood culture and culture-independent digital PCR

Fast and precise identification of microorganisms in the early diagnosis of sepsis is crucial for enhancing patient outcomes. Digital PCR (dPCR) is a highly sensitive approach for absolute quantification that can be utilized as a culture-independent molecular technique for diagnosing sepsis pathogens. We performed a retrospective investigation on 69 ICU patients suspected of sepsis. Our findings showed that a multiplex dPCR diagnostic kit outperformed blood culture in detecting the 15 most frequent bacteria that cause sepsis. Ninety-two bacterial strains were identified using dPCR at concentrations varying from 34 copies/mL to 105,800 copies/mL. The detection rate of dPCR was much greater than that of BC, with 27.53% (19/69) versus 73.91% (51/69). The sensitivity of dPCR was 63.2%. Our research indicated that dPCR outperforms blood culture in the early detection of sepsis-causing microorganisms. The diagnostic kit can detect a greater variety of pathogens with quantitative data, including polymicrobial infections, and has a quicker processing time. DPCR is a valuable technique that could aid in the proper management of sepsis.

Reliability of Droplet Digital PCR Alone and in Combination with Interleukin-6 and Procalcitonin for Prognosis of Bloodstream Infection

Purpose

Bloodstream infection(BSI) is linked with high mortality, underscoring the significance of prompt etiological diagnosis for timely and precise treatment. This study aims to investigate the diagnostic value of droplet digital polymerase chain reaction(ddPCR) in combination with conventional inflammatory markers [interleukin-6(IL-6) and procalcitonin(PCT)] concerning disease progression and treatment prognosis in BSI patients. Furthermore, the study aims to explore a more efficient clinical application strategy.

Patients and Methods

This prospective case seried study centers on 176 patients suspected of or confirmed with BSI. Blood samples were collected to extract nucleic acids for identifying pathogens (bacteria, fungi, and viruses) and determining copy loads via ddPCR.

Results

The sensitivity of ddPCR was markedly higher compared to the culture method (74.71% vs 31.03%). A positive correlation existed between bacterial load and levels of inflammatory markers [IL-6 (P=0.0182), PCT (P=0.0029), and CRP (P=0.0005)]. In suspected BSI cases, the combination of ddPCR and inflammatory markers could predict sepsis risk [ROC: Area under the curve(AUC)=0.6071, P=0.0383]. Within confirmed BSI patients, the ddPCR bacterial load of those with SOFA<7 was lower than that of the SOFA≥7 (P=0.0334). ddPCR (OR: 1.789, P=0.035) monitoring combined with PCT (OR: 1.787, P=0.035) holded predictive value for SOFA progression (AUC=0.7913, P=0.0003). Similarly, BSI survivors displayed a lower burden than non-survivors (P=0.0170). Additionally, ddPCR combinated with IL-6 provided a more accurate and expedited insight into clinical outcomes prediction for BSI confirmed patients (AUC=0.7352, P=0.0030). Serial monitoring of bacterial load by ddPCR effectively mirrored the clinical course of BSI in patients. Notably, patients with positive ddPCR virus infection exhibited significantly reduced lymphocyte counts (P=0.0003).

Conclusion

In a clinical context, qualitative ddPCR results and quantitative continuous monitoring can more precisely assess sepsis progression and treatment prognosis in BSI patients. Furthermore, ddPCR results offer quicker and more accurate reference points for clinical antibacterial and antiviral interventions.

Microfluidic systems for infectious disease diagnostics

Microorganisms, encompassing both uni- and multicellular entities, exhibit remarkable diversity as omnipresent life forms in nature. They play a pivotal role by supplying essential components for sustaining biological processes across diverse ecosystems, including higher host organisms. The complex interactions within the human gut microbiota are crucial for metabolic functions, immune responses, and biochemical signalling, particularly through the gut-brain axis. Viruses also play important roles in biological processes, for example by increasing genetic diversity through horizontal gene transfer when replicating inside living cells. On the other hand, infection of the human body by microbiological agents may lead to severe physiological disorders and diseases. Infectious diseases pose a significant burden on global healthcare systems, characterized by substantial variations in the epidemiological landscape. Fast spreading antibiotic resistance or uncontrolled outbreaks of communicable diseases are major challenges at present. Furthermore, delivering field-proven point-of-care diagnostic tools to the most severely affected populations in low-resource settings is particularly important and challenging. New paradigms and technological approaches enabling rapid and informed disease management need to be implemented. In this respect, infectious disease diagnostics taking advantage of microfluidic systems combined with integrated biosensor-based pathogen detection offers a host of innovative and promising solutions. In this review, we aim to outline recent activities and progress in the development of microfluidic diagnostic tools. Our literature research mainly covers the last 5 years. We will follow a classification scheme based on the human body systems primarily involved at the clinical level or on specific pathogen transmission modes. Important diseases, such as tuberculosis and malaria, will be addressed more extensively.

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.

Label-free multidimensional bacterial characterization with an ultrawide detectable concentration range by microfluidic impedance cytometry

Rapid and accurate identification of bacteria is of great importance to public health in various fields, including medical diagnostics, food safety, and environmental monitoring. However, most existing bacterial detection methods have very narrow detectable concentration ranges and limited detection information, which easily leads to wrong diagnosis and treatment. This work presents a novel high-throughput microfluidic electrical impedance-based multidimensional single-bacterium profiling system for ultrawide concentration range detection and accurate differentiation of viability and Gram types of bacteria. The electrical impedance-based microfluidic cytometry is capable of multi-frequency impedance quantification, which allows profiling of the bacteria size, concentration, and membrane impedance as an indicator of bacterial viability and Gram properties in a single flow-through interrogation. It has been demonstrated that this novel impedance cytometry has an ultrawide bacterial counting range (102-108 cells per mL), and exhibits a rapid and accurate discrimination of viability and Gram types of bacteria in a label-free manner. Escherichia coli (E. coli) has been used as an analog species for the accuracy assessment of the electrical impedance-based bacterial detection system in an authentic complex beverage matrix within 24 hours. The impedance-based quantifications of viable bacteria are consistent with those obtained by the classical bacterial colony counting method (R2 = 0.996). This work could pave the way for providing a novel microfluidic cytometry system for rapid and multidimensional bacterial detection in diverse areas.

Harnessing Variabilities in Digital Melt Curves for Accurate Identification of Bacteria

Digital PCR combined with high resolution melt (HRM) is an emerging method for identifying pathogenic bacteria with single cell resolution via species-specific digital melt curves. Currently, the development of such digital PCR-HRM assays entails first identifying PCR primers to target hypervariable gene regions within the target bacteria panel, next performing bulk-based PCR-HRM to examine whether the resulting species-specific melt curves possess sufficient interspecies variability (i.e., variability between bacterial species), and then digitizing the bulk-based PCR-HRM assays with melt curves that have high interspecies variability via microfluidics. In this work, we first report our discovery that the current development workflow can be inadequate because a bulk-based PCR-HRM assay that produces melt curves with high interspecies variability can, in fact, lead to a digital PCR-HRM assay that produces digital melt curves with unwanted intraspecies variability (i.e., variability within the same bacterial species), consequently hampering bacteria identification accuracy. Our subsequent investigation reveals that such intraspecies variability in digital melt curves can arise from PCR primers that target nonidentical gene copies or amplify nonspecifically. We then show that computational in silico HRM opens a window to inspect both interspecies and intraspecies variabilities and thus provides the missing link between bulk-based PCR-HRM and digital PCR-HRM. Through this new development workflow, we report a new digital PCR-HRM assay with improved bacteria identification accuracy. More broadly, this work can serve as the foundation for enhancing the development of future digital PCR-HRM assays toward identifying causative pathogens and combating infectious diseases.

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

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

Electrochemical nucleic acid sensors: Competent pathways for mobile molecular diagnostics

Electrochemical nucleic acid biosensor has demonstrated great promise in clinical diagnostic tests, mainly because of its flexibility, high efficiency, low cost, and easy integration for analytical applications. Numerous nucleic acid hybridization-based strategies have been developed for the design and construction of novel electrochemical biosensors for diagnosing genetic-related diseases. This review describes the advances, challenges, and prospects of electrochemical nucleic acid biosensors for mobile molecular diagnosis. Specifically, the basic principles, sensing elements, applications in diagnosis of cancer and infectious diseases, integration with microfluidic technology and commercialization are mainly included in this review, aiming to provide new insights and directions for the future development of electrochemical nucleic acid biosensors.

Development and evaluation of a droplet digital PCR assay to detect Brucella in human whole blood

BACKGROUND

With the development of domestic animal husbandry, the spread of brucellosis has accelerated, and the scope of the epidemic has expanded. The timely and accurate diagnosis of human brucellosis continues to challenge clinicians in endemic areas. Droplet digital PCR (ddPCR) technology can quickly and accurately determine DNA load in samples, providing laboratory evidence for diagnosis, prognosis and management of brucellosis patients. In this study, a ddPCR method was established to accurately quantify Brucella DNA load in whole blood samples, and its diagnostic, prognostic, and therapeutic value for human brucellosis was evaluated.

METHODS

Annealing temperature, primers, and probe targeting the Brucella bcsp31 gene were optimised, and the sensitivity, specificity and repeatability of the ddPCR assay were assessed using 94 whole blood samples from 61 confirmed and 33 suspected cases. Results were compared with those of quantitative PCR (qPCR). Nine follow-up brucellosis patients were also analysed by the two methods after 2 and 6 months of treatment.

RESULTS

Optimal primer and probe concentrations were 800 nmol/L and 400 nmol/L, respectively, and the optimal annealing temperature was 55.3 °C. The ddPCR results showed that the limit of detection was 1.87 copies per reaction, with high repeatability. The positive rates for ddPCR and qPCR were 88.5% and 75.4% among 61 serum agglutination test (SAT) positive patients. In addition, 57.6% (19/33) of suspected sero-negative samples were positive by ddPCR, but only 36.3% (12/33) were positive by qPCR. Analysis of nine post-therapy follow-up brucellosis patients revealed that the Brucella DNA load in the whole blood samples decreased after 2 and 6 months of treatment, and was slightly increased following relapse and continuous exposure.

CONCLUSION

The ddPCR assay showed good accuracy for whole blood samples, and could be a potential diagnostic and prognostic tool for detecting Brucella.

Interfacing centrifugal microfluidics with linear-oriented 8-tube strips and multichannel pipettes for increased throughput of digital assays

We present a centrifugal microfluidic cartridge for the eight-fold parallel generation of monodisperse water-in-oil droplets using standard laboratory equipment. The key element is interfacing centrifugal microfluidics with its design based on polar coordinates to the linear structures of standard high-throughput laboratory automation. Centrifugal step emulsification is used to simultaneously generate droplets from eight samples directly into standard 200 μl PCR 8-tube strips. To ensure minimal manual liquid handling, the design of the inlets allows the user to load the samples and the oil via a standard multichannel pipette. Simulation-based design of the cartridge ensures that the performance is consistent in each droplet generation unit despite the varying radial positions that originate from the interface to the linear oriented PCR 8-tube strip and from the integration of linear oriented inlet holes for the multichannel pipettes. Within 10 minutes, sample volumes of 50 μl per droplet generation unit are emulsified at a fixed rotation speed of 960 rpm into 1.47 × 105 monodisperse droplets with a mean diameter of 86 μm. The overall coefficient of variation (CV) of the droplet diameter was below 4%. Feasibility is demonstrated by an exemplary digital droplet polymerase chain reaction (ddPCR) assay which showed high linearity (R2 ≥ 0.999) across all of the eight tubes of the strip.

Polyaniline-based 3D network structure promotes entrapment and detection of drug-resistant bacteria

Sensitive and accurate capture, enrichment, and identification of drug-resistant bacteria on human skin are important for early-stage diagnosis and treatment of patients. Herein, we constructed a three-dimensional hierarchically structured polyaniline nanoweb (3D HPN) to capture, enrich, and detect drug-resistant bacteria on-site by rubbing infected skins. These unique hierarchical nanostructures enhance bacteria capture efficiency and help severely deform the surface of the bacteria entrapped on them. Therefore, 3D HPN significantly contributes to the effective and reliable recovery of drug-resistant bacteria from the infected skin and the prevention of potential secondary infection. The recovered bacteria were successfully identified by subsequent real-time polymerase chain reaction (PCR) analysis after the lysis process. The molecular analysis results based on a real-time PCR exhibit excellent sensitivity to detecting target bacteria of concentrations ranging from 102 to 107 CFU/mL without any fluorescent signal interruption. To confirm the field applicability of 3D HPN, it was tested with a drug-resistant model consisting of micropig skin similar to human skin and Klebsiella pneumoniae carbapenemase-producing carbapenem-resistant Enterobacteriaceae (KPC-CRE). The results show that the detection sensitivity of this assay is 102 CFU/mL. Therefore, 3D HPN can be extended to on-site pathogen detection systems, along with rapid molecular diagnostics through a simple method, to recover KPC-CRE from the skin.

Multiplex single-cell droplet PCR with machine learning for detection of high-risk human papillomaviruses

High-risk human papillomavirus (HPV) testing can significantly decline the incidence and mortality of cervical cancer. Microfluidic technology provides an effective method for accurate detection of high-risk HPV by utilizing multiplex single-cell droplet polymerase chain reaction (PCR). However, current strategies are limited by low-integration microfluidic chip, complex reagent system, expensive detection equipment and time-consuming droplet identification. Here, we developed a novel multiplex droplet PCR method that directly detected high-risk HPV sequences in single cells. A multiplex microfluidic chip integrating four flow-focusing structures was designed for one-step and parallel droplet preparation. Using single-cell droplet PCR, multi-target sequences were detected simultaneously based on a monochromatic fluorescence signal. We applied machine learning to automatically identify the large populations of single-cell droplets with 97% accuracy. HPV16, 18 and 45 sequences were sensitively detected without cross-contamination in mixed CaSki and Hela cells. The approach enables rapid and reliable detection of multi-target sequences in single cells, making it powerful for investigating cellular heterogeneity related to cancer diagnosis and treatment.

Emerging Microfluidic Devices for Sample Preparation of Undiluted Whole Blood to Enable the Detection of Biomarkers

Blood testing allows for diagnosis and monitoring of numerous conditions and illnesses; it forms an essential pillar of the health industry that continues to grow in market value. Due to the complex physical and biological nature of blood, samples must be carefully collected and prepared to obtain accurate and reliable analysis results with minimal background signal. Examples of common sample preparation steps include dilutions, plasma separation, cell lysis, and nucleic acid extraction and isolation, which are time-consuming and can introduce risks of sample cross-contamination or pathogen exposure to laboratory staff. Moreover, the reagents and equipment needed can be costly and difficult to obtain in point-of-care or resource-limited settings. Microfluidic devices can perform sample preparation steps in a simpler, faster, and more affordable manner. Devices can be carried to areas that are difficult to access or that do not have the resources necessary. Although many microfluidic devices have been developed in the last 5 years, few were designed for the use of undiluted whole blood as a starting point, which eliminates the need for blood dilution and minimizes blood sample preparation. This review will first provide a short summary on blood properties and blood samples typically used for analysis, before delving into innovative advances in microfluidic devices over the last 5 years that address the hurdles of blood sample preparation. The devices will be categorized by application and the type of blood sample used. The final section focuses on devices for the detection of intracellular nucleic acids, because these require more extensive sample preparation steps, and the challenges involved in adapting this technology and potential improvements are discussed.

Advances in droplet digital polymerase chain reaction on microfluidic chips

The PCR technique has been known to the general public since the pandemic outbreak of COVID-19. This technique has progressed through three stages: from simple PCR to real-time fluorescence PCR to digital PCR. Among them, the microfluidic-based droplet digital PCR technique has attracted much attention and has been widely applied due to its advantages of high throughput, high sensitivity, low reagent consumption, low cross-contamination, and absolute quantification ability. In this review, we introduce various designs of microfluidic-based ddPCR developed within the last decade. The microfluidic-based droplet generation methods, thermal cycle strategies, and signal counting approaches are described, and the applications in the fields of single-cell analysis, disease diagnosis, and pathogen detection are introduced. Further, the challenges and prospects of microfluidic-based ddPCR are discussed. We hope that this review can contribute to the further development of the microfluidic-based ddPCR technique.

Decoding the metabolic response of Escherichia coli for sensing trace heavy metals in water

Heavy metal contamination due to industrial and agricultural waste represents a growing threat to water supplies. Frequent and widespread monitoring for toxic metals in drinking and agricultural water sources is necessary to prevent their accumulation in humans, plants, and animals, which results in disease and environmental damage. Here, the metabolic stress response of bacteria is used to report the presence of heavy metal ions in water by transducing ions into chemical signals that can be fingerprinted using machine learning analysis of vibrational spectra. Surface-enhanced Raman scattering surfaces amplify chemical signals from bacterial lysate and rapidly generate large, reproducible datasets needed for machine learning algorithms to decode the complex spectral data. Classification and regression algorithms achieve limits of detection of 0.5 pM for As³⁺ and 6.8 pM for Cr⁶⁺, 100,000 times lower than the World Health Organization recommended limits, and accurately quantify concentrations of analytes across six orders of magnitude, enabling early warning of rising contaminant levels. Trained algorithms are generalizable across water samples with different impurities; water quality of tap water and wastewater was evaluated with 92% accuracy.

Clinical Diagnostic Performance of Droplet Digital PCR for Suspected Bloodstream Infections

Accurate and timely etiological diagnosis is crucial for bloodstream infections (BSIs) due to their high disability and mortality. We conducted a single-center prospective cohort study to compare the digital droplet PCR (ddPCR) assay with traditional blood culture. A total of 169 blood samples from 122 patients with suspected BSIs were collected, mostly from the department of infectious diseases, the emergency department, and the intensive care units, and the clinical data were also recorded. Nucleic acid was extracted from the blood samples, and a 5-fluorescent-channel droplet digital PCR assay was performed and then fed back with the pathogen and its copies. In BSI patients, ddPCR reported an overall 85.71% (12/14) (95% confidence interval [CI], 56.15 to 97.48%) sensitivity, 100% (7/7) (95% CI, 56.09 to 100.00%) and 71.43% (5/7) (95% CI, 30.26 to 94.89%) sensitivity in patients without empirical treatment and in empirically treated patients, respectively. Compared to traditional blood culture, the overall detection rate of ddPCR was significantly higher, 11.27% (16/142) (95% CI, 6.78 to 17.93%) versus 30.28% (43/142) (95% CI, 23.01 to 38.64%), and the extra detection rate of ddPCR was 19.01% (27/142) (95% CI, 13.11 to 26.63%). Of the ddPCR-positive culture-negative cases, 74.19% (23/31) (95% CI, 55.07 to 87.46%) were consistent with the final clinical diagnosis, including 10 bacteria and fungi. The detection rate of ddPCR was significantly higher in patients with white blood cell (WBC) counts of >10 · 109/L, C-reactive protein (CRP) of >70 mg/L, or procalcitonin (PCT) of >0.9 ng/L. Pathogen loads detected by ddPCR are correlated with WBC, CRP, and especially, PCT levels, precisely and rapidly reflecting clinical disease progression. ddPCR has an important guiding value for the clinical use of antibiotics to achieve the best pathogen coverage and the antibacterial effect. Collectively, ddPCR showed a great diagnostic performance in BSIs and had an overall higher detection rate than blood culture. In addition, ddPCR could be used to dynamically monitor the disease progression and provide medication guidance on antibiotic use. IMPORTANCE ddPCR is a promising method to address the current challenges of BSI diagnosis and precise treatment, as it is highly efficient in DNA detection. It shortens the identification of BSI-related pathogens from several days of traditional bacterial culture to 4 to 5 h. It is extremely sensitive and more tolerant to PCR inhibitors, which may facilitate the amplification and enable the detection of a meager amount of DNA fragments in detecting BSI-related pathogens and drug-resistant genes. It can identify almost 20 pathogens in one reaction, which reduces the usage of clinical blood samples to no more than 2 mL. Additionally, dynamic monitoring, assessment of pathogens, and antibiotic resistance genes in patients could be used to guide timely and precise adjustment of antimicrobial prescription. The short turnaround time of ddPCR may have the potential to guide antimicrobial treatment in the very early stage of sepsis and reduce the mortality and disability rate of sepsis.

Digital Protein Detection in Bulk Solutions

Quick and accurate molecular diagnostics in protein detection can greatly benefit medicine in disease diagnosis and lead to positive patient outcomes. However, specialized equipment used in clinical laboratories often comes with trade-offs between operation and function serving a single role for very specific needs. For example, to achieve high analytical sensitivity and specificity, instruments such as high-performance liquid chromatography and/or liquid chromatography-mass spectrometry use a complex instrument design and require thorough training of the users. On the other hand, simple tests such as protein detection in urinary tract infection using dip-stick assays provide very quick results but suffer from poor analytical sensitivity. Here, we present an application study for the 3D particle counter technology, which is based on optical confocal detection in order to scan large sample volumes (0.5-3 mL) in glass cuvettes, that aims to close the gap between analytical sensitivity and turnover assay time and simplify protein detection by adopting bead-based immunoassays. Combining the 3D particle counter technology with bead-based immunoassays, a subpicomolar limit of detection-ranging from 119 to 346 fM-was achieved within 3.5-hour assay time for recombinant mouse interleukin 6 detection. As an alternative instrument to a flow cytometer, the 3D particle counter takes advantages of bead-based immunoassays and provides unique accessibility and flexibility for users.

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

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

Single Domain Antibody application in bacterial infection diagnosis and neutralization

Increasing antibiotic resistance to bacterial infections causes a serious threat to human health. Efficient detection and treatment strategies are the keys to preventing and reducing bacterial infections. Due to the high affinity and antigen specificity, antibodies have become an important tool for diagnosis and treatment of various human diseases. In addition to conventional antibodies, a unique class of “heavy-chain-only” antibodies (HCAbs) were found in the serum of camelids and sharks. HCAbs binds to the antigen through only one variable domain Referred to as VHH (variable domain of the heavy chain of HCAbs). The recombinant format of the VHH is also called single domain antibody (sdAb) or nanobody (Nb). Sharks might also have an ancestor HCAb from where SdAbs or V-NAR might be engineered. Compared with traditional Abs, Nbs have several outstanding properties such as small size, high stability, strong antigen-binding affinity, high solubility and low immunogenicity. Furthermore, they are expressed at low cost in microorganisms and amenable to engineering. These superior properties make Nbs a highly desired alternative to conventional antibodies, which are extensively employed in structural biology, unravelling biochemical mechanisms, molecular imaging, diagnosis and treatment of diseases. In this review, we summarized recent progress of nanobody-based approaches in diagnosis and neutralization of bacterial infection and further discussed the challenges of Nbs in these fields.

Microfluidics for antibiotic susceptibility testing

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

Recent Advances in Digital Biosensing Technology

Digital biosensing assays demonstrate remarkable advantages over conventional biosensing systems because of their ability to achieve single-molecule detection and absolute quantification. Unlike traditional low-abundance biomarking screening, digital-based biosensing systems reduce sample volumes significantly to the fL-nL level, which vastly reduces overall reagent consumption, improves reaction time and throughput, and enables high sensitivity and single target detection. This review presents the current technology for compartmentalizing reactions and their applications in detecting proteins and nucleic acids. We also analyze existing challenges and future opportunities associated with digital biosensing and research opportunities for developing integrated digital biosensing systems.

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

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

Clinical validation of a multiplex droplet digital PCR for diagnosing suspected bloodstream infections in ICU practice: a promising diagnostic tool

Background

Droplet digital PCR (ddPCR) has emerged as a promising tool of pathogen detection in bloodstream infections (BSIs) in critical care medicine. However, different ddPCR platforms have variable sensitivity and specificity for diverse microorganisms at various infection sites. There is still a lack of prospective clinical studies aimed at validating and interpreting the discrepant ddPCR results for diagnosing BSI in intensive care unit (ICU) practice.

Methods

A prospective diagnostic study of multiplex ddPCR panels was conducted in a general ICU from May 21, 2021, to December 22, 2021. Paired blood cultures (BCs) and ddPCRs (2.5 h) were obtained synchronously to detect the 12 most common BSI pathogens and three antimicrobial resistance (AMR) genes. Firstly, ddPCR performance was compared to definite BSI. Secondly, clinical validation of ddPCR was compared to composite clinical diagnosis. Sensitivity, specificity, and positive and negative predictive values were calculated. Thirdly, the positive rate of AMR genes and related analysis was presented.

Results

A total of 438 episodes of suspected BSIs occurring in 150 critical patients were enrolled. BC and ddPCR were positive for targeted bacteria in 40 (9.1%) and 180 (41.1%) cases, respectively. There were 280 concordant and 158 discordant. In comparison with BCs, the sensitivity of ddPCR ranged from 58.8 to 86.7% with an aggregate of 72.5% in different species, with corresponding specificity ranging from 73.5 to 92.2% with an aggregate of 63.1%. Furthermore, the rate of ddPCR+/BC− results was 33.6% (147/438) with 87.1% (128 of 147) cases was associated with probable (n = 108) or possible (n = 20) BSIs. When clinically diagnosed BSI was used as true positive, the final sensitivity and specificity of ddPCR increased to 84.9% and 92.5%, respectively. In addition, 40 blaKPC, 3blaNDM, and 38 mecA genes were detected, among which 90.5% were definitely positive for blaKPC. Further, 65.8% specimens were predicted to be mecA-positive in Staphylococcus sp. according to all microbiological analysis.

Conclusions

The multiplexed ddPCR is a flexible and universal platform, which can be used as an add-on complementary to conventional BC. When combined with clinical infection evidence, ddPCR shows potential advantages for rapidly diagnosing suspected BSIs and AMR genes in ICU practice.

SAMBA: A Multicolor Digital Melting PCR Platform for Rapid Microbiome Profiling

During the past decade, breakthroughs in sequencing technology have provided the basis for studies of the myriad ways in which microbial communities in and on the human body influence human health and disease. In almost every medical specialty, there is now a growing interest in accurate and quantitative profiling of the microbiota for use in diagnostic and therapeutic applications. However, the current next-generation sequencing approach for microbiome profiling is costly, requires laborious library preparation, and is challenging to scale up for routine diagnostics. Split, Amplify, and Melt analysis of BActeria-community (SAMBA), a novel multicolor digital melting polymerase chain reaction platform with unprecedented multiplexing capability is presented, and the capability to distinguish and quantify 16 bacteria species in mixtures is demonstrated. Subsequently, SAMBA is applied to measure the compositions of bacteria in the gut microbiome to identify microbial dysbiosis related to colorectal cancer. This rapid, low cost, and high-throughput approach will enable the implementation of microbiome diagnostics in clinical laboratories and routine medical practice.

Evaluation of droplet digital PCR rapid detection method and precise diagnosis and treatment for suspected sepsis (PROGRESS): a study protocol for a multi-center pragmatic randomized controlled trial

Background

Sepsis is still a major public health concern and a medical emergency due to its high morbidity and mortality. Accurate and timely etiology diagnosis is crucial for sepsis management. As an emerging rapid and sensitive pathogen detection tool, digital droplet PCR (ddPCR) has shown promising potential in rapid identification of pathogens and antimicrobial resistance genes. However, the diagnostic value and clinical impact of ddPCR tests remains to be studied in patients with suspected sepsis. PROGRESS trial is aimed to evaluate the clinical effectiveness of a novel ddPCR assay compared with standard practice.

Methods

PROGRESS is a multicenter, open-label, pragmatic randomized controlled trial (pRCT) set in ten hospitals, including departments of infectious disease and intensive care units. In this study, a total of 2292 patients with suspected sepsis will be randomly assigned to two arms: the ddPCR group and the control group with a ratio of 3:1. The primary outcome is the diagnostic efficacy, that is, the sensitivity and specificity of the ddPCR assay compared with the synchronous blood culture. Secondary outcomes include the mortality rates and the mean Sequential Organ Failure Assessment (SOFA) score at follow-up time points, the length of stay in the hospital, the time to directed antimicrobial therapy, duration of broad-spectrum antibiotic use, and the EQ-5D-5L score on day 90.

Discussion

It is the first multicenter pragmatic RCT to explore the diagnostic efficacy and clinical impact of the ddPCR assay in patients with suspected sepsis, taking advantage of both RCT’s ability to establish causality and the feasibility of pragmatic approaches in real-world studies (RWS). This trial will help us to get a comprehensive view of the assay’s capacity for precise diagnosis and treatment of sepsis. It has the potential to monitor the pathogen load change and to guide the antimicrobial therapy, making a beneficial impact on the prognosis of sepsis patients.

Trial registration: ClinicalTrial.gov, NCT05190861. Registered January 13, 2022—‘Retrospectively registered’, https://clinicaltrials.gov/ct2/show/NCT05190861.

Droplet-based methods for tackling antimicrobial resistance

Application of droplet-based methods enables (i) faster detection, (ii) increased sensitivity, (iii) characterization of the level of heterogeneity in response to antibiotics by bacterial populations, and (iv) expanded screening of the effectiveness of antibiotic combinations. Hereby, we discuss the key steps and parameters of droplet-based experiments to investigate antimicrobial resistance. We also review recent findings accomplished with these methods and highlight their advantages and capacity to yield new insights into the problem of antimicrobial resistance.

Diagnosis of Bloodstream Infections: An Evolution of Technologies towards Accurate and Rapid Identification and Antibiotic Susceptibility Testing

Bloodstream infections (BSI) are a leading cause of death worldwide. The lack of timely and reliable diagnostic practices is an ongoing issue for managing BSI. The current gold standard blood culture practice for pathogen identification and antibiotic susceptibility testing is time-consuming. Delayed diagnosis warrants the use of empirical antibiotics, which could lead to poor patient outcomes, and risks the development of antibiotic resistance. Hence, novel techniques that could offer accurate and timely diagnosis and susceptibility testing are urgently needed. This review focuses on BSI and highlights both the progress and shortcomings of its current diagnosis. We surveyed clinical workflows that employ recently approved technologies and showed that, while offering improved sensitivity and selectivity, these techniques are still unable to deliver a timely result. We then discuss a number of emerging technologies that have the potential to shorten the overall turnaround time of BSI diagnosis through direct testing from whole blood-while maintaining, if not improving-the current assay's sensitivity and pathogen coverage. We concluded by providing our assessment of potential future directions for accelerating BSI pathogen identification and the antibiotic susceptibility test. While engineering solutions have enabled faster assay turnaround, further progress is still needed to supplant blood culture practice and guide appropriate antibiotic administration for BSI patients.

Near-Infrared Responsive Droplet for Digital PCR

Digital PCR (dPCR) surpasses the performance of earlier PCR formats because of highly precise, absolute quantification and other unique merits. A simple thermocycling approach and durable microcarrier are of great value for dPCR advancement and application. Herein, a near-infrared (NIR) controlled thermocycling approach by embedding magnetic graphene oxide (GO) composite into the agarose microcarriers is developed. The core-shell composite is constructed by sequentially encapsulating GO and silica outside the magnetic nanocores. Benefiting from these additives, the resultant composite agarose gains appealing features as light-driven temperature changing, switchable gel-sol phase transforming, biocompatibility, and magnetic traction. By further emulsifying into droplets via the microfluidics method, the influence of typical parameters including material loading amount, laser intensity, and droplet diameter at various ranges is investigated for assembling microcarriers with different responsiveness. Then a paradigm of the NIR program can be easily tailored for PCR thermocycling. Finally, the feasibility of the approach is verified by detecting statistically diluted Klebsiella pneumoniae DNA samples, from 0.1 to 2 copies per drop. It is anticipated that this method has promising prospects for dPCR-based and other temperature-controlled applications.

Advances in Nucleic Acid Amplification-Based Microfluidic Devices for Clinical Microbial Detection

Accurate and timely detection of infectious pathogens is urgently needed for disease treatment and control of possible outbreaks worldwide. Conventional methods for pathogen detection are usually time-consuming and labor-intensive. Novel strategies for the identification of pathogenic nucleic acids are necessary for practical application. The advent of microfluidic technology and microfluidic devices has offered advanced and miniaturized tools to rapidly screen microorganisms, improving many drawbacks of conventional nucleic acid amplification-based methods. In this review, we summarize advances in the microfluidic approach to detect pathogens based on nucleic acid amplification. We survey microfluidic platforms performing two major types of nucleic acid amplification strategies, namely, polymerase chain reaction (PCR) and isothermal nucleic acid amplification. We also provide an overview of nucleic acid amplification-based platforms including studies and commercialized products for SARS-CoV-2 detection. Technologically, we focus on the design of the microfluidic devices, the selected methods for sample preparation, nucleic acid amplification techniques, and endpoint analysis. We also compare features such as analysis time, sensitivity, and specificity of different platforms. The first section of the review discusses methods used in microfluidic devices for upstream clinical sample preparation. The second section covers the design, operation, and applications of PCR-based microfluidic devices. The third section reviews two common types of isothermal nucleic acid amplification methods (loop-mediated isothermal amplification and recombinase polymerase amplification) performed in microfluidic systems. The fourth section introduces microfluidic applications for nucleic acid amplification-based detection of SARS-CoV-2. Finally, the review concludes with the importance of full integration and quantitative analysis for clinical microbial identification.

Combating Antimicrobial Resistance via Single-Cell Diagnostic Technologies Powered by Droplet Microfluidics

Antimicrobial resistance is a global threat that if left unchecked could lead to 10 million annual mortalities by 2050. One factor contributing to the rise of multi-drug-resistant (MDR) pathogens is the reliance on traditional culture-based pathogen identification (ID) and antimicrobial susceptibility testing (AST) that typically takes several days. This delay of objective pathogen ID and AST information to inform clinical decision making results in clinicians treating patients empirically often using first-line, broad-spectrum antibiotics, contributing to the misuse/overuse of antibiotics. To combat the rise in MDR pathogens, there is a critical demand for rapid ID and AST technologies. Among the advances in ID and AST technologies in the past decade, single-cell diagnostic technologies powered by droplet microfluidics offer great promise due to their potential for high-sensitivity detection and rapid turnaround time. Our laboratory has been at the forefront of developing such technologies and applying them to diagnosing urinary tract infections (UTIs), one of the most common infections and a frequent reason for the prescription of antimicrobials. For pathogen ID, we first demonstrated the highly sensitive, amplification-free detection of single bacterial cells by confining them in picoliter-scale droplets and detection with fluorogenic peptide nucleic acid (PNA) probes that target their 16S rRNA (rRNA), a well-characterized marker for phylogenic classification. We subsequently improved the PNA probe design and enhanced detection sensitivity. For single-cell AST, we first employed a growth indicator dye and engineered an integrated device that allows us to detect growth from single bacterial cells under antibiotic exposure within 1 h, equivalent to two to three bacterial replications. To expand beyond testing a single antibiotic condition per device, a common limitation for droplet microfluidics, we developed an integrated programmable droplet microfluidic device for scalable single-cell AST. Using the scalable single-cell AST platform, we demonstrated the generation of up to 32 droplet groups in a single device with custom antibiotic titers and the capacity to scale up single-cell AST, and providing reliable pathogen categories beyond a binary call embodies a critical advance. Finally, we developed an integrated ID and AST platform. To this end, we developed a PNA probe panel that can identify nearly 90% of uropathogens and showed the quantitative detection of 16S rRNA from single bacterial cells in droplet-enabled AST after as little as 10 min of antibiotic exposure. This platform achieved both ID and AST from minimally processed urine samples in 30 min, representing one of the fastest turnaround times to date. In addition to tracing the development of our technologies, we compare them with contemporary research advances and offer our perspectives for future development, with the vision that single-cell ID and AST technologies powered by droplet microfluidics can indeed become a useful diagnostic tool for combating antimicrobial resistance.

Progressing Antimicrobial Resistance Sensing Technologies across Human, Animal, and Environmental Health Domains

The spread of antimicrobial resistance (AMR) is a rapidly growing threat to humankind on both regional and global scales. As countries worldwide prepare to embrace a One Health approach to AMR management, which is one that recognizes the interconnectivity between human, animal, and environmental health, increasing attention is being paid to identifying and monitoring key contributing factors and critical control points. Presently, AMR sensing technologies have significantly progressed phenotypic antimicrobial susceptibility testing (AST) and genotypic antimicrobial resistance gene (ARG) detection in human healthcare. For effective AMR management, an evolution of innovative sensing technologies is needed for tackling the unique challenges of interconnected AMR across various and different health domains. This review comprehensively discusses the modern state-of-play for innovative commercial and emerging AMR sensing technologies, including sequencing, microfluidic, and miniaturized point-of-need platforms. With a unique view toward the future of One Health, we also provide our perspectives and outlook on the constantly changing landscape of AMR sensing technologies beyond the human health domain.

Deep Learning Assisted Microfluidic Impedance Flow Cytometry for Label-free Foodborne Bacteria Analysis and Classification. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021;2021:7087-7090. [PMID: 34892734 DOI: 10.1109/embc46164.2021.9630684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

According to the urgent need for rapid detection and identification of foodborne bacteria to prevent public health event, a microfluidic electrical impedance flow cytometry assisted with convolutional neural network (ConvNet) based deep learning algorithm was proposed in this study to analyze the impedance signals of bacteria. With the assistance of the deep learning algorithm, Escherichia coli (EPEC), Salmonella enteritidis (SE) and Vibrio parahaemolyticus (VP) were identified with an accuracy of 100%. The proposed impedance based analysis system can be potentially applied for pre-classification of different subtypes of bacteria in a label-free manner.Clinical Relevance-The whole platform can be miniaturized and applied for point-of-care testing (POCT) of pathogenic bacteria detection.

Bacterial classification and antibiotic susceptibility testing on an integrated microfluidic platform

With the prevalence of bacterial infections and increasing levels of antibiotic resistance comes the need for rapid and accurate methods for bacterial classification (BC) and antibiotic susceptibility testing (AST). Here we demonstrate the use of the fluid handling technique digital microfluidics (DMF) for automated and simultaneous BC and AST using growth metabolic markers. Custom instrumentation was developed for this application including an integrated heating module and a machine-learning-enabled low-cost colour camera for real-time absorbance and fluorescent sample monitoring on multipurpose devices. Antibiotic dilutions along with sample handling, mixing and incubation at 37 °C were all pre-programmed and processed automatically. By monitoring the metabolism of resazurin, resorufin beta-D-glucuronide and resorufin beta-D-galactopyranoside to resorufin, BC and AST were achieved in under 18 h. AST was validated in two uropathogenic E. coli strains with antibiotics ciprofloxacin and nitrofurantoin. BC was performed independently and simultaneously with ciprofloxacin AST for E. coli, K. pneumoniae, P. mirabilis and S. aureus. Finally, a proof-of-concept multiplexed system for breakpoint testing of two antibiotics, as well as E. coli and coliform classification was investigated with a multidrug-resistant E. coli strain. All bacteria were correctly identified, while AST and breakpoint test results were in essential and category agreement with reference methods. These results show the versatility and accuracy of this all-in-one microfluidic system for analysis of bacterial growth and phenotype.

Droplet microfluidics on analysis of pathogenic microbes for wastewater-based epidemiology

Infectious diseases caused by pathogenic microbes have posed a major health issue for the public, such as the ongoing COVID-19 global pandemic. In recent years, wastewater-based epidemiology (WBE) is emerging as an effective and unbiased method for monitoring public health. Despite its increasing importance, the advancement of WBE requires more competent and streamlined analytical platforms. Herein we discuss the interactions between WBE and droplet microfluidics, focusing on the analysis of pathogens in droplets, which is hard to be tackled by traditional analytical tools. We highlight research works from three aspects, namely, quantitation of pathogen biomarkers in droplets, single-cell analysis in droplets, and living cell biosensors in droplets, as well as providing future perspectives on the synergy between WBE and droplet microfluidics.

Electrochemical-based ''antibiotsensor'' for the whole-cell detection of the vancomycin-susceptible bacteria

In this study, we aim to develop an antibiotic-based biosensor platform 'Antibiotsensor' for the specific detection of gram-positive bacteria using vancomycin modified Screen Printed Gold Electrodes (SPGEs). Through this pathway, vancomycin molecules were first functionalized with thiol groups and characterized with quadrupole time of flight (q-TOF) mass spectroscopy analysis. Immobilization of thiolated vancomycin molecules (HS-Van) onto SPGEs was carried out based on self-assembled monolayer (SAM) phenomenon. Electrochemical impedance spectroscopy (EIS) was employed to test the detection and showed a considerable change in impedance value upon the binding of HS-Van molecules onto the electrode surface. Atomic Force Microscopy analysis indicated that SPGE was successfully modified upon the treatment with HS-Van molecules based on the shift in surface roughness from 173 ± 2 nm to 301 ± 3 nm. Fourier Transform Infrared Spectroscopy (FTIR) spectroscopy proved the EIS and AFM results as well by showing characteristic peaks of immobilized HS-Van molecule. As a proof-of-concept, EIS-based susceptibility testing was performed using Escherichia coli, Staphylococcus aureus and Mycobacterium smegmatis bacteria to prove the specificity of obtained SPGE-Van. EIS data showed that the charge transfer resistance (R_ct) values changed from 1.08, 1.18 to 26.5, respectively, indicating that vancomycin susceptible S. aureus was successfully attached onto SPGE-Van surface strongly, while vancomycin resistance E. coli and M. smegmatis did not show any significant attachment properties. In addition, different concentration (10⁸-10 CFU/mL) of S. aureus was performed to investigate sensitivity of proposed sensor platform. Limit of detection and limit of quantitation was calculated as 10^1.58 and 10^4.81 CFU/mL, respectively. Scanning electron microscopy (SEM) analysis also confirmed that only S. aureus bacteria was attached to the surface in a dense monolayer distribution. We believe that the proposed approach is selective and sensitive towards the whole-cell detection of vancomycin-susceptible bacteria and can be modified for different purposes in the future.