Search Results (111)

Background/Objective: Sewage sludge (biosolids) is increasingly reused as a fertilizer to recycle nutrients and close material cycles; however, concerns persist regarding antibiotics and antimicrobial resistance. This study evaluated the agronomic safety and microbiological integrity of biosolid fertilization in soybean and maize systems, with particular attention to grain quality and food safety. Methods: Soybean and maize were cultivated in greenhouse microcosms under biosolid or mineral fertilization. Soil, roots, shoots, and grains were analyzed for antibiotic residues using LC–MS/MS and antibiotic-resistant bacteria (ARB) using culture-based assays. Minimum inhibitory concentrations for isolates from grains were compared with clinical breakpoints to verify phenotypic susceptibility. Multivariate analyses (PCA) integrating real-time antibiotic concentrations and updated resistance indicators were performed using centered and scaled data. Results: Fluoroquinolones were the predominant residues introduced by biosolids and exhibited consistent time-dependent declines across all treatments, although low concentrations remained detectable at 90 d in several soil–fertilizer–crop combinations. Tetracyclines, macrolides, and sulfonamides showed similar decreasing trends, with planted soils displaying faster dissipation than bulk control soils. Biosolid fertilization increased shoot biomass by 1.5–2.3-fold and nitrogen, phosphorus, and potassium uptake by 30–60% without impairing soybean nodulation or nitrogenase function. ARB was observed in all soils, including mineral and plant-free controls, indicating a natural background resistome. Ciprofloxacin-resistant isolates were detected in one simple sampling point, and MDR proportions were transient (67%), returning to their background levels by 45–90 days. PCA showed that crop presence, not fertilizer type, was the primary driver of microbial ordination, and that antibiotic concentrations and resistance indicators were only weakly aligned, indicating a limited selective pressure. No antibiotic residues or phenotypically resistant bacteria were detected in the soybean or maize grains. Conclusions: Updated residue, resistance, and multivariate data confirmed that biosolids did not induce, amplify, or transfer antibiotic resistance and maintained complete grain safety. Properly treated biosolids function as safe, agronomically beneficial fertilizers aligned with One Health goals, enhancing crop productivity without compromising food quality or increasing antimicrobial resistance. Full article

Macrolides are crucial for the management and treatment of bovine respiratory disease (BRD). However, antimicrobial resistance (AMR) threatens the efficacy of these and other antimicrobials. We developed real-time recombinase polymerase amplification (RPA) assays targeting three clinically relevant macrolide antimicrobial resistance genes (ARGs)—msrE-mphE and erm42—in ≤30 min using extracted DNA. A set of 199 deep nasopharyngeal swabs (DNPS) collected from feedlot calves near the time of arrival were selected based on bacterial culture (BC) results for Mannheimia haemolytica, Pasteurella multocida, and Histophilus somni and antimicrobial susceptibility testing (AST) for tulathromycin, tilmicosin, tildipirosin, or gamithromycin. Samples were also tested for the same targets using RPA and polymerase chain reaction (PCR). In samples that were culture-positive for one or more macrolide-resistant BRD-associated bacteria (n = 101), msrE-mphE and/or erm42 were detected in 95% of cases using RPA. The remaining 98 samples were either culture-negative, or the recovered bacteria were macrolide-susceptible: 43% of these were RPA-positive for at least one macrolide ARG. Together with BC-AST and PCR, Bayesian latent class modelling estimated the clinical sensitivity of RPA for macrolide ARGs to be 95% and specificity to be 58%, with moderate agreement between RPA and BC-AST (κ = 0.52) or PCR (κ = 0.55). The estimated sensitivity of the RPA multiplex assay for the targeted macrolide ARGs was very good, although estimated specificity was limited. However, Sanger sequencing confirmed RPA detection of msrE-mphE in BC-AST/PCR-negative samples (n = 23), reflecting the presence of this locus in non-target bacteria, as well as potential ARG variants among BRD bacteria. These findings support the potential of RPA for rapid ARG detection from extracted DNA. Continued assay optimization and evaluation for detection of respiratory bacteria and ARGs will further enhance its diagnostic utility. Full article

Ensuring the quality and safety of agricultural and food products is crucial for protecting consumer health, meeting market expectations, and complying with regulatory requirements. Quality and safety parameters are commonly assessed using chemical and microbiological analyses, which are time-consuming, impractical, and involve the use of toxic solvents, often disrupting the material’s original structure. An alternative technique, infrared spectroscopy, including near-infrared (NIR), mid-infrared (MIR), and short-wave infrared (SWIR), has emerged as a rapid, powerful, and minimally destructive technique for evaluating the quality and safety of food and agricultural products. This review focuses on discussing MIR spectroscopy, particularly Fourier transform infrared (FTIR) techniques, with emphasis on the attenuated total reflectance (ATR) measurement mode (globar infrared light source is commonly used) and on the use of synchrotron radiation (SR) as an alternative high-brightness light source. Both approaches enable the extraction of detailed spectral data related to molecular and functional attributes concerning quality and safety, thereby facilitating the assessment of crop disorders, food chemical composition, microbial contamination (e.g., mycotoxins, bacteria), and the detection of food adulterants, among several other applications. In combination with advanced chemometric techniques, FTIR spectroscopy, whether employing ATR as a measurement mode or SR as a high-brightness light source, is a powerful analytical tool for classification based on attributes, variety, nutritional and geographical origins, with or without minimal sample preparation, no chemical use, and short analysis time. However, limitations exist regarding calibrations, validations, and accessibility. The objective of this review is to address recent technological advancements and existing constraints of FTIR conducted in ATR mode and using SR as a light source (not necessarily in combination). It defines potential pathways for the comprehensive integration of FTIR and chemometrics for real-time quality and safety monitoring systems into the global food supply chain. Full article

Bathing water quality (BWQ) monitoring and prediction are essential to safeguard public health by informing bathers about the risk of exposure to faecal indicator bacteria (FIBs). Traditional monitoring approaches, such as manual sampling and laboratory analysis, while effective, are often constrained by delayed reporting, limited spatial and temporal coverage, and high operational costs. The integration of artificial intelligence (AI), particularly machine learning (ML), with automated data sources such as environmental sensors and satellite imagery has offered novel predictive and real-time monitoring opportunities in BWQ assessment. This systematic literature review synthesises current research on the application of AI in BWQ assessment, focusing on predictive modelling techniques and remote sensing approaches. Following the PRISMA methodology, 63 relevant studies are reviewed. The review identifies dominant modelling techniques such as Artificial Neural Networks (ANN), Deep Learning (DL), Decision Tree (DT), Random Forest (RF), Multiple Linear Regression (MLR), Support Vector Machine (SVM), and Hybrid and Ensemble Boosting algorithms. The integration of AI with remote sensing platforms such as Google Earth Engine (GEE) has improved the spatial and temporal solution of BWQ monitoring systems. The performance of modelling approaches varied depending on data availability, model flexibility, and integration with alternative data sources like remote sensing. Notable research gaps include short-term faecal pollution prediction and incomplete datasets on key environmental variables, data scarcity, and model interpretability of complex AI models. Emerging trends point towards the potential of near-real-time modelling, Internet of Things (IoT) integration, standardised data protocols, global data sharing, the development of explainable AI models, and integrating remote sensing and cloud-based systems. Future research should prioritise these areas while promoting the integration of AI-driven BWQ systems into public health monitoring and environmental management through multidisciplinary collaboration. Full article

Microbial forensics involves analyzing biological evidence to evaluate weaponized microorganisms or their toxins. This study aimed to detect and type Yersinia pestis from four simulated forensic samples—human plasma diluted in phosphate-buffered saline (#24-2), tomato juice (#24-5), grape juice (#24-8), and a surgical mask (#24-10). Notably, samples #24-10 may have contained live bacteria other than Y. pestis. A real-time polymerase chain reaction confirmed the presence of Y. pestis in all samples; however, whole-genome sequencing (WGS) coverage of the Y. pestis chromosome ranged from 0.46% to 97.1%, largely due to host DNA interference and low abundance. To address these limitations and enable strain-level identification, we designed a hybridization-based target enrichment approach focused on multilocus variable number tandem repeat analysis (MLVA). Next-generation sequencing (NGS) using whole-genome amplification revealed that the accuracy of the 25 MLVA profiles of Y. pestis for samples #24-2, #24-5, #24-8, and #24-10 was 4%, 100%, 52%, and 0%, respectively. However, all samples showed 100% accuracy with target-enriched NGS, confirming they all belong to the same strain. These findings demonstrate that a targeted enrichment strategy for MLVA loci can overcome common obstacles in microbial forensics, particularly when working with trace or degraded samples where conventional WGS proves challenging. Full article

Car wash wastewaters (CWW) bring growing environmental challenges due to the increasing number of vehicles worldwide and they require novel, optimized and sustainable treatment methods. They are highly heterogenous, typically containing complex mixtures of detergents, waxes, oils, petroleum derivatives, corrosion inhibitors and salts, with the composition depending on installation age, geographic location, season, and weather. This study aimed to select bacteria resistant to variable and potentially toxic CWW, capable of biodegrading organic pollutants. A total of 81 strains isolated from various environmental sites were screened for tolerance to CWW environments by performing growth inhibition tests in 20 real wastewater samples with chemical oxygen demand (COD) ranging from 122 to 2267 mg O₂/dm³. Seventeen strain candidates were chosen, identified with molecular proteomics, and further evaluated for biodegradation potential. Based on the most robust isolates, six microbial consortia were developed and examined. Biodegradation experiments were conducted at ambient temperature without active pH control and nutrient supplementation to reflect real conditions occurring in wastewater treatment practice. The best-performing consortium reduced COD by 86% within 7 days. These findings should help improve the treatment of complex CWW by highlighting the potential of thoroughly selected bacteria as effective tools for bioremediation of extremely harsh environments. Full article

Healthcare professionals (HCPs) working in paediatric settings are routinely exposed to respiratory pathogens, increasing their risk of asymptomatic colonisation by meningitis-associated bacteria. This study is the first to assess oropharyngeal and nasopharyngeal carriage of major bacterial meningitis pathogens among paediatric HCPs in Benin, and to identify associated risk factors. A cross-sectional analytical study was conducted in nine hospitals between 1 September 2023 and 30 September 2024. Data collection involved a structured questionnaire and paired oropharyngeal and nasopharyngeal swabs. Culture-based identification and antimicrobial susceptibility testing were performed according to CA-SFM guidelines. By culture method, Streptococcus pneumoniae was the most frequently isolated pathogen, mainly from oropharyngeal samples (47.5%). Most of these strains exhibited multidrug resistance. In nasopharyngeal samples analysed by real-time PCR, detection rates for S. pneumoniae were markedly higher (24.4%) compared to culture (5.0%), highlighting the limited sensitivity of conventional methods in detecting asymptomatic carriage. Pneumococcal colonisation was significantly associated with recent respiratory tract infections, and residence in high-risk areas (p < 0.05). These findings underscore the need for enhanced molecular surveillance, along with strengthened infection control measures and targeted vaccination strategies, to mitigate the risk of horizontal transmission in paediatric wards. Full article

Climate change increases microbial contamination risks in food, highlighting the need for real-time biosensors. However, food residues often interfere with detection signals, limiting the direct application. An integrated system of filter-assisted sample preparation (FASP) and an immunoassay-based colorimetric biosensor offers the rapid and simple on-site detection of foodborne pathogens in complex food matrices. The accuracy and stability of biosensor analysis were ensured via filter-assisted preprocessing, which separated food residues from bacteria. The system was applied to various food matrices, including vegetables, meats, and cheese brine, using samples spiked at contamination levels ranging from 10² to 10³ CFU per 25 g, thereby demonstrating broad applicability. Bacterial recovery varied by food matrix, with vegetables showing a 1-log reduction and meats, melon, and cheese brine showing a 2-log reduction relative to the initial inoculum. A detection limit of 10¹ CFU/mL was achieved for Escherichia coli O157:H7, Salmonella Typhimurium, and Listeria monocytogenes in the final preprocessed sample solutions. Sample preparation took under 3 min, and detection was completed within 2 h under stationary conditions. This approach enables rapid pathogen detection in various food matrices without the need for special reading devices, contributing to food safety as a real-time, rapid-response food biosensor. Full article

Antimicrobial resistance (AMR) is a significant global threat and is driven by the overuse of antibiotics in both clinical and agricultural settings. This issue is further complicated by the lack of rapid surveillance tools to detect resistant bacteria in clinical, environmental, and food systems. Of particular concern is the rise in resistance to carbapenems, a critical class of beta-lactam antibiotics. Rapid detection methods are necessary for prevention and surveillance effort. This study utilized a gold nanoparticle-based plasmonic biosensor to detect three CR genes: bla_KPC-3, bla_NDM-1, and bla_OXA-1. Optical signals were analyzed using both a spectrophotometer and a smartphone app that quantified visual color changes using RGB values. This app, combined with a simple boiling method for DNA extraction and a portable thermal cycler, was used to evaluate the biosensor’s potential for POC use. Advantages of the portable bacterial detection device include real time monitoring for immediate decision-making in critical situations, field and on-site testing in resource-limited settings without needing to transport samples to a centralized lab, minimal training required, automatic data analysis, storage and sharing, and reduced operational cost. Bacteria were inoculated into sterile water, river water, and turkey rinse water samples to determine the biosensor’s success in detecting target genes from sample matrices. Magnetic nanoparticles were used to capture and concentrate bacteria to avoid time-consuming cultivation and separation steps. The biosensor successfully detected the target CR genes in all tested samples using three gene-specific DNA probes. Target genes were detected with a limit of detection of 2.5 ng/L or less, corresponding to ~10³ CFU/mL of bacteria. Full article

Metagenomic next-generation sequencing (mNGS) is transforming infectious disease diagnostics by enabling simultaneous, hypothesis-free detection of a broad array of pathogens—including bacteria, viruses, fungi, and parasites—directly from clinical specimens such as cerebrospinal fluid, blood, and bronchoalveolar lavage fluid. Unlike traditional culture and targeted molecular assays, mNGS serves as a powerful complementary approach, capable of identifying novel, fastidious, and polymicrobial infections while also characterizing antimicrobial resistance (AMR) genes. These advantages are particularly relevant in diagnostically challenging scenarios, such as infections in immunocompromised patients, sepsis, and culture-negative cases. Despite its potential, mNGS remains underutilized in clinical microbiology due to persistent gaps between its technical capabilities and routine diagnostic adoption. This review addresses key translational challenges that limit the broader implementation of mNGS, especially in resource-constrained and critical care settings. We provide a comprehensive overview of the entire workflow—from sample processing and host DNA depletion to sequencing platforms and downstream bioinformatics—and highlight sources of variability, including contamination, human DNA interference, and inconsistencies in resistance gene annotation. Additionally, we explore the ethical, legal, and privacy implications of host genomic data, as well as economic and regulatory obstacles hindering mNGS integration into standard clinical practice. To illustrate clinical relevance, we examine real-world evidence from large-scale trials such as MATESHIP, GRAIDS, DISQVER, and NGS-CAP. Finally, we outline future directions involving artificial intelligence, multi-omics integration, cloud-based analytics, and portable sequencing technologies for point-of-care diagnostics. By addressing both current limitations and emerging innovations, this review offers a translational framework for integrating mNGS into precision diagnostics and infection management across diverse healthcare environments. Full article

Foodborne pathogenic bacteria critically threaten public health and food industry sustainability, serving as a predominant trigger of food contamination incidents. To mitigate these risks, the development of rapid, sensitive, and highly specific detection technologies is essential for early warning and effective control of foodborne diseases. In recent years, biosensors have gained prominence as a cutting-edge tool for detecting foodborne pathogens, owing to their operational simplicity, rapid response, high sensitivity, and suitability for on-site applications. This review provides a comprehensive evaluation of critical biorecognition elements, such as antibodies, aptamers, nucleic acids, enzymes, cell receptors, molecularly imprinted polymers (MIPs), and bacteriophages. We highlight their design strategies, recent advancements, and pivotal contributions to improving detection specificity and sensitivity. Additionally, we systematically examine mainstream biosensor-based detection technologies, with a focus on three dominant types: electrochemical biosensors, optical biosensors, and piezoelectric biosensors. For each category, we analyze its fundamental principles, structural features, and practical applications in food safety monitoring. Finally, this review identifies future research priorities, including multiplex target detection, enhanced processing of complex samples, commercialization, and scalable deployment of biosensors. These advancements are expected to bridge the gap between laboratory research and real-world food safety surveillance, fostering more robust and practical solutions. Full article

Background/Objectives: Increasing levels of antimicrobial resistance (AMR) have recently been observed at the human–domestic animal–wildlife interface. Wild birds have been identified as carriers of antimicrobial-resistant bacteria and serve as excellent biomarkers for epidemiological studies. This study assessed the current AMR presence in Eastern Spain’s commensal Escherichia coli isolated from free-ranging Bonelli’s eagles (Aquila fasciata). Methods: Nestlings and their nests were intensively sampled between 2022 and 2024 to determine their AMR profile and characterize E. coli. AMR testing was conducted using the broth microdilution method, following the European Committee on Antimicrobial Susceptibility Testing guidelines. Additionally, the presence of eaeA (intimin gene) and stx-1 and stx-2 (shiga toxins) was analyzed by real-time PCR to classify E. coli strains into enteropathogenic (EPEC) and Shiga-toxigenic (STEC) pathotypes. Results: Of all E. coli isolates, 41.7% were resistant to at least one antimicrobial, and 30% were multidrug-resistant. Only two strains were classified as EPEC and none as STEC. The highest resistance rates were observed for amoxicillin and tetracycline (19.6% each). Alarmingly, resistance to colistin and meropenem, last-resort antibiotics in human medicine, was also detected. Conclusions: Although the mechanisms of resistance acquisition remain unclear, transmission is likely to occur through the food chain, with synanthropic prey acting as intermediary vectors. These results highlight the role of Bonelli’s eagles as essential sentinels of environmental AMR dissemination, even in remote ecosystems. Strengthening One Health-based surveillance is necessary to address AMR’s ecological and public health risks in wildlife. Full article

The detection of particulate matter, particularly pathogenic bacteria, is essential in environmental monitoring, food safety, and clinical diagnostics. Among the various sensing techniques used, cantilever-based sensors offer a promising platform for label-free, real-time detection due to their high sensitivity. Here, we present a coupled cantilever sensor incorporating interdigitated comb-shaped structures to enhance dielectrophoretic (DEP) capture of Escherichia coli in liquid samples. During operation, one cantilever is externally actuated and the other oscillates passively through fluid-mediated coupling. The sensor was experimentally evaluated across a broad concentration range from 10 to 10⁵ cells/mL and the resonant frequency shifts were recorded for both beams. The results showed a strong linear frequency shift across all tested concentrations, without saturation. This demonstrates the sensor’s ability to detect both trace and high bacterial loads without needing recalibration. High frequency shifts of 4863 Hz were recorded for 10⁵ cells/mL and 225 Hz for the lowest concentration of 10 cells/mL, giving a limit of detection of 10 cells/mL. The sensor also showed a higher signal to noise ratio of 265.7 compared to previously reported designs. These findings showed that the enhanced sensor design enables sensitive, linear, and reliable bioparticle detection across a wide range, making it suitable for diverse applications. Full article

Piroplasmids (Babesia spp., Rangelia spp., Theileria spp., Cytauxzoon spp.) are tick-borne apicomplexan protozoa that infect, depending on the species, erythrocytes and leucocytes in a wide variety of mammals and birds. The genera Bartonella and Borrelia include vector-borne bacteria that can infect and cause disease in both animals and humans. Detection of hemotropic bacteria and piroplasmids in wild animals is often challenging due to low bacteremia or parasitemia. Digital (d)PCR has proven to be an effective modality for the detection and quantification of DNA of hemotropic pathogens with low parasitemia. This study compared dPCR results from 366 biological samples from seven different Brazilian wild animal groups (5 Xenarthra species, 5 deer species, 3 felid species, 1 canid species, 3 rodent species, 1 bat species, 1 tapir species, and 12 bird species) to two other molecular diagnostic techniques: quantitative real-time (qPCR) and nested (nPCR). For this study, DNA extracted from wild animal blood and spleen samples were subjected to a multiplex dPCR assay for piroplasmids, Bartonella spp., and Borrelia spp. For comparison, the same primers and probes for each agent were used in qPCR assays. Additionally, an nPCR based on the 18S rRNA gene for piroplasmids was performed. The proportions of positive results obtained using dPCR were 85.5% for piroplasmids, 33.6% for Bartonella spp., and 16.7% for Borrelia spp. For all tested agents, dPCR proved to be the technique with the highest sensitivity, making it a useful tool for screening vector-borne agents in biological samples from wild animals with low parasitemia. Full article

Microbial detection in milk is crucial for food safety and quality, as beneficial and harmful microorganisms can affect consumer health and dairy product integrity. Identifying and quantifying these microorganisms helps prevent contamination and spoilage. The study employs advanced molecular techniques to detect and quantify the genomic DNA for the target hydrolytic enzyme coding genes lipA and aprX based on the multi-align sequence conserved region, specific primer pair, and hydrolysis probes designed using the singleplex qPCR and multiplex qPCR. Cultured isolates and artificially contaminated sterilized ultra-high-temperature (UHT) milk were analyzed for their specificity, cross-reactivity, and sensitivity. The finding indicated that strains with lipA and aprX genes were amplified while the other strains were not amplified. This indicated that the designed primer pairs/probes were very specific to the target gene of interest. The specificity of each design primer pair was checked using SYBR Green qPCR using 16 different isolate strains from the milk sample. The quantification specificity of each strain target gene was deemed to be with a mean Ct value for positive pseudomonas strain > 16.98 ± 1.76 (p < 0.0001), non-pseudomonas positive strain ≥ 27.47 ± 1.25 (p < 0.0001), no Ct for the negative control and molecular grade water. The sensitivity limit of detection (LOD) analyzed based on culture broth and milk sample was >10⁵ and >10⁴ in PCR amplification while it was >10⁴ and >10³ in real-time qPCR, respectively. At the same time, the correlation regression coefficient of the standard curve based on the pure culture cell DNA as the DNA concentration serially diluted (20 ng/µL to 0.0002 ng/µL) was obtained in multiplex without interference and cross-reactivity, yielding R² ≥ 0.9908 slope (−3.2591) and intercepting with a value of 37, where the efficiency reached the level of 95–102% sensitivity reached up to 0.0002 ng/µL concentration of DNA, and sensitivity of microbial load was up to 1.2 × 10² CFU/mL. Therefore, multiplex TaqMan qPCR simultaneous amplification was considered the best method developed for the detection of the lipA and aprX genes in a single tube. This will result in developing future simultaneous (three- to four-gene) detection of spoilage psychrotrophic bacteria in raw milk. Full article