暂无摘要。

Compared with traditional diagnostic methods (TDMs), rapid diagnostic methods for infectious diseases (IDs) are urgently needed. Metagenomic next-generation sequencing (mNGS) has emerged as a promising diagnostic technology for clinical infections.
This retrospective observational study was performed at a tertiary hospital in China between May 2019 and August 2022. The chi-square test was used to compare the sensitivity and specificity of mNGS and TDMs. We also performed a subgroup analysis of the different pathogens and samples.
A total of 435 patients with clinical suspicion of infection were enrolled and 372 (85.5%) patients were finally categorized as the ID group. The overall sensitivity of mNGS was significantly higher than that of the TDMs (59.7% vs. 30.1%, P < 0.05). However, there was no significant difference in the overall specificity between the two methods (83.3% vs. 89.6%, P = 0.37). In patients with identified pathogens, the positive rates of mNGS for detecting bacteria (88.7%), fungi (87.9%), viruses (96.9%), and Nontuberculous mycobacteria (NTM; 100%) were significantly higher than those of TDMs (P < 0.05). The positive rate of mNGS for detecting Mycobacterium tuberculosis was not superior to that of TDMs (77.3% vs. 54.5%, P = 0.11). The sensitivity rates of mNGS for pathogen identification in bronchoalveolar lavage fluid, blood, cerebrospinal fluid, pleural fluid, and tissue were 72.6%, 39.3%, 37.5%, 35.0% and 80.0%, respectively.
With the potential for screening multiple clinical samples, mNGS has an overall advantage over TDMs. It can effectively identify pathogens, especially those that are difficult to identify using TDMs, such as NTM, chlamydia, and parasites.

Pseudomonas aeruginosa is an opportunist pathogen responsible for causing several infections in the human body, especially in patients with weak immune systems. The proposed approach reports a novel pathogens detection system based on cultivating microdroplets and acquiring the scattered light signals from the incubated droplets using a microfluidic device. Initially, the microdroplets were generated and incubated to cultivate bacteria inside the microdroplets. The second part of the microfluidic chip is the detection module, embedded with three optical fibers to connect laser light and photosensors. The incubated droplets were reinjected in the detection module and passed through the laser light. The surrounding photosensors were arranged symmetrically at 45° to the flowing channel for acquiring the scattered light signal. The noise was removed from the acquired data, and time-domain waveform features were evaluated. The acquired features were trained using machine learning classifiers to classify P. aeruginosa. The k-nearest neighbors (KNN) showed superior classification performance with 95.6 % accuracy among other classifiers, including logistic regression (LR), support vector machines (SVM), and naïve Bayes (NB). The proposed research was performed to validate the method for pathogens detection with a concentration of 105 CFU/mL. The total duration of 6 h is required to test the sample, including five hours for droplets incubation and one hour for sample preparation and detection using light scattering module. The results indicate that acquiring the light scattering patterns from incubated droplets can detect P. aeruginosa using machine learning classification. The proposed system is anticipated to be helpful as a rapid device for diagnosing pathogenic infections.

The dairy sector is frequently affected by contagious and environmental factors that spread between animals by numerous means and induce the inflammatory disease of bovine mastitis (BM). Herein, silver decorated porous silicon (Ag-pSi) SERS platform was designed for rapid and reliable Escherichia coli (predominant BM pathogen) detection in various milk origins. The inherent surface void and pore morphology were physically optimized to augment the SERS effect using 4-aminothiphenol (4ATP) while achieving an enhancement factor >4.6 × 107. An indirect immunoassay evaluated the residual unreacted antibodies using an optimized 4ATP/Ag-pSi SERS platform modified with secondary antibodies. Under optimized conditions, the porous substrate offered high sensitivity toward target bacteria detection of 3 CFU mL-1 and linear response of 101-105 CFU mL-1. Moreover, the selectivity and specificity of the designed sensing platform were cross-validated against other interfering bacteria without compromising its performance efficiencies. Finally, the applicability of the developed system for real-life conditions was elucidated in different milk samples (bovine, goat, sheep) with recovery values of 78-115% compared to the conventional culture technique. Considering the complex media analysis, the miniaturized SERS platform is highly reliable, rapid and accurate that could be applicable for routine on-site analysis of various emerging pathogens relevant to BM management.

In recent years, a number of bacterial detection methods have been developed to replace time-consuming culture methods. One interesting approach is to mobilize the ability of phage tail proteins to recognize and bind to bacterial hosts. In this paper, the authors provide an overview of the current methodologies in which phage proteins play major roles in detecting pathogenic bacteria. Authors focus on proteins capable of recognizing highly pathogenic strains, such as Acinetobacter baumannii, Campylobacter spp., Yersinia pestis, Pseudomonas aeruginosa, Listeria monocytogenes, Staphylococcus aureus, Enterococcus spp., Salmonella spp., and Shigella. These pathogens may be diagnosed by capture-based detection methods involving the use of phage protein-coated nanoparticles, ELISA (enzyme-linked immunosorbent assay)-based methods, or biosensors. The reviewed studies show that phage proteins are becoming an important diagnostic tool due to the discovery of new phages and the increasing knowledge of understanding the specificity and functions of phage tail proteins.

A disposable visual microfluidic immunosensor is described for the determination of foodborne pathogens using immunomagnetic separation, enzymatic catalysis and distance indication. Specifically, a sensor was designed to detect Salmonella typhimurium as a model pathogen. Magnetic nanoparticles (MNPs) were modified with the anti-Salmonella monoclonal antibodies and then used to enrich S. typhimurium from the sample. This is followed by conjugation to polystyrene microspheres modified with anti-Salmonella polyclonal antibodies and catalase to form the MNP-bacteria-polystyrene-catalase sandwich. The catalase on the complexes catalyzes the decomposition of hydrogen peroxide to produce oxygen after passing a micromixer. The generated oxygen gas increases the pressure in the chip and pushes the indicating red dye solution to travel along the channel towards the unsealed outlet. The travel distance of the red dye can be visually read and related to the amount of S. typhimurium using the calibration scale. The sensor can detect as low as 150 CFU·mL-1 within 2 h. Graphical abstractSchematic representation of the distance-based microfluidic immunosensor for visual detection of foodborne bacteria using immunomagnetic nanoparticles for bacteria separation, catalase for decomposition of hydrogen peroxide to form oxygen which causes a pressure increase, and red dyed particles movement for distance indication.

UNASSIGNED: Metagenomic methods have been widely applied to study the relationship between gut microbiota and human health. To test whether metagenomic amplicon sequencing could be an effective method to diagnose and trace the pathogens of infantile infectious diarrhea, the fecal samples of 20 diarrheic and 13 healthy infants were collected. After 16S rDNA amplicon sequencing, diversity analyses were carried out. The relationship between the pathogens of the gut microbiota and geography of patients was analyzed.
UNASSIGNED: The diversity of the gut microbiota in diarrheic infants was significantly lower than that of the gut microbiota in healthy ones and that, the composition of gut microbiota in the diarrheic group was significantly different than that of the gut microbiota in the healthy group. The results also indicated that in some of the patients, the amounts of Escherichia coli were significantly increased in the diarrheic infants, which was in agreement with the result of the qPCR analysis. Using a geographical map, we found some patterns between pathogen source and geographical location. This is helpful for an early warning of the disease.
UNASSIGNED: The method of using high-throughput DNA sequencing and a comprehensive and deep data analysis can be a new strategy to detect and trace pathogens in infantile infectious diarrhea.Trial registration Diagnosing and tracing the pathogens of infantile infectious diarrhea by amplicon sequencing, ChiCTR-DDD-1701088, Registered 16 March 2017-Retrospectively registered, http://www.chictr.org.cn/showproj.aspx?proj=18477.

Cryptosporidium parvum ( C. parvum) is a highly potent zoonotic pathogen, which can do significant harm to both human beings and livestock. However, existing technologies or methods are deficient for rapid on-site detection of water contaminated with C. parvum. Better detection approaches are needed to allow water management agencies to stop major breakouts of the pathogen. Herein, we present a novel detection method for cryptosporidium in a tiny drop of sample using a magnetic nanoparticle (MNP) probe combined with dark-field microscopy in 30 min. The designed MNP probes bind with high affinity to C. parvum, resulting in the formation of a golden garland-like structure under dark-field microscopy. This MNP-based dark-field counting strategy yields an amazing PCR-like sensitivity of 8 attomolar (aM) (5 pathogens in 1 μL). Importantly, the assay is very rapid (∼30 min) and is very simple to perform as it involves only one step of mixing and magnetic separation, followed by dropping on a slide for counting under dark-field microscope. By combining the advantages of the specific light-scattering characteristic of MNP probe under dark field and the selective magnetic separation ability of functionalized MNP, the proposed MNP-based dark-field enumeration method offers low cost and significant translational potential.

Here we innovate a portable and quantitative immunochromatographic assay (ICA) with a personal glucose meter (PGM) as readout for the detection of Escherichia coli O157:H7 (E. coli O157:H7). The carboxyl group coated Fe3O4 nanoparticles (MNPs) were synthesized by a one pot method and used as carriers of invertase and monoclonal antibody against E. coli O157:H7. Initially, the invertase and antibody double functionalized MNPs (Invertase-MNPs-IgG) conjugates were prepared and used as label probe in this assay system. Before laminating onto the baking card, the absorbent pad was soaked in sucrose solution and desiccated. MNPs produced brown band at the detection zone of the ICA when acting as direct labels. As they were also coupled with invertase, the invertase catalyzed the hydrolysis of sucrose on the absorbent pad into glucose, which was detected by the PGM. To increase the sensitivity, antibody functionalized MNPs were used to enrich E. coli O157:H7 from sample solution. The innovative aspect of this approach lies in the visualization and quantification of E. coli O157:H7 through Invertase-MNPs-IgG and the detection of glucose concentration using PGM. Although the feasibility is demonstrated using E. coli O157:H7 as a model analyte, this approach can be easily developed to be a universal analysis system and applied to detection of a wide variety of foodborne pathogens and protein biomarkers. This study proposed a qualitative and quantitative analysis device for the clinic diagnostics and food safety analysis.

Escherichia coli O157:H7 is one of the most notorious foodborne pathogens causing serious disease at low infectious dose. To protect consumers from deadly foodborne E. coli O157:H7 infection, it is vital to develop a simple, reliable, sensitive and rapid method which can detect low level E. coli O157:H7 in foods at real-time. We have successfully developed a novel immunochromatographic assay (ICA) with enhanced sensitivity for the visual and quantitative detection of E. coli O157:H7. Sandwich-type immunoreactions were performed on the ICA, and Pt-Au bimetal nanoparticles (NPs) were accumulated on the test zone. The signal amplification is based on Pt-Au bimetal NPs possessing high peroxidase activity toward 3,3\',5,5\'-tetramethylbenzidine, which can produce characteristic colored bands and thus, enable visual detection of E. coli O157:H7 without instrumentation. The innovative aspect of this approach lies in the visualization and quantification of target pathogen through the detection of color intensity. Due to the excellent peroxidase activity of Pt-Au NPs, they emit strong visible color intensity in less than 1 min for visual observation even in low concentration range of E. coli O157:H7. Quantification was performed using a commercial assay meter. The sensitivity was improved more than 1000-folds compared to the conventional test strip based on colored gold-colloids. Although the feasibility was demonstrated using E. coli O157:H7 as a model analyte, this approach could be easily developed to be a universal signal amplification technique and applied to detection of a wide variety of foodborne pathogens and protein biomarkers.