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Outline
Cronobacter are common pathogenic bacteria that can cause meningitis, septicemia and necrotizing enterocolitis in neonates and infants. Severe infections may lead to neurological sequelae, posing a serious threat to infant food safety and public health. Therefore, the establishment of efficient and accurate detection methods is great significance. This review systematically summarized recent advances in the detection technologies for Cronobacter in foods and organized them according to a hierarchical framework of “culture-based confirmation-rapid screening-viable-cell quantification-on-site detection-intelligent interpretation”. Conventional culture-based methods remain fundamental for obtaining viable isolates, confirming results and supporting subsequent source-tracing analysis. Immunoenrichment, real-time fluorescent quantitative polymerase chain reaction/digital polymerase chain reaction and isothermal amplification technologies had improved the screening efficiency and quantitative capability for low-abundance samples. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry,metabolomics, surface-enhanced Raman spectroscopy and flow cytometry had expanded the application boundaries of rapid identification, phenotypic characterization and cellular state evaluation. Nanomaterials, microfluidic chips,biosensors and portable platforms had further promoted the integration, field applicability and high sensitivity of detection methods. In addition, the application of artificial intelligence in genomic source tracing, sensor signal analysis, image recognition and multi-source data fusion provides new perspectives for the intelligent interpretation of detection results. This review focused on the complementary relationships, applicable scenarios and translational bottlenecks of different detection methods, thereby providing stronger technical support for food safety supervision.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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