Inactivation of foodborne pathogens based on synergistic effects of ultrasound and natural compounds during fresh produce washing

Ultrasound has potential to be used for disinfection, and its antimicrobial effectiveness can be enhanced in presence of natural compounds. In this study, we compared the antimicrobial effects of ultrasound at 20 kHz (US 20 kHz) or 1 MHz (US 1 MHz) in combination with carvacrol, citral, cinnamic acid, geraniol, gallic acid, lactic acid, or limonene against E. coli K12 and Listeria innocua at a constant power density in water. Compared to the cumulative effect of the individual treatments, the combined treatment of US 1 MHz and 10 mM citral generated >1.5 log CFU/mL additional inactivation of E. coli K12. Similarly, combined treatments of US 1 MHz and 2 mM carvacrol (30 min), US 20 kHz and 2 mM carvacrol, 10 mM citral, or 5 mM geraniol (15 min) generated >0.5–2.0 log CFU/mL additional inactivation in L. innocua. The synergistic effect of citral, as a presentative compound, and US 20 kHz treatment was determined to be a result of enhanced dispersion of insoluble citral droplets in combination with physical impact on bacterial membrane structures, whereas the inactivation by US 1 MHz was likely due to generation of oxidative stress within the bacteria. Combined ultrasound and citral treatments improved the bacterial inactivation in simulated wash water in presence of organic matter or during washing of inoculated blueberries but only additive antimicrobial effects were observed. Findings in this study will be useful to enhance fresh produce safety and shelf-life and design other alternative ultrasound based sanitation processes.     

表面增强拉曼光谱在食源性致病微生物检测中的应用研究

食源性致病微生物导致的食源性疾病已成为全球化的公共卫生问题。快速、有效地检测食源性致病微生物是实现食源性疾病预防与控制的关键环节，也是保障食品安全的技术关键。表面增强拉曼光谱(SERS)具有简单、快速、灵敏度高等优点，在食品安全、生物医学、环境监控等领域展现出良好的应用前景。介绍了近年来SERS在食源性致病微生物检测中的应用研究进展。对SERS技术概况、SERS增强理论及SERS增强基底进行了简要介绍，重点回顾了SERS在食源性致病微生物检测中的应用和发展现状。在食品安全分析方面，利用SERS与模式识别方法相结合对食品中常见食源性致病微生物能实现快速、有效鉴别，部分研究已应用于不同食品样品的分析，体现了SERS作为“指纹图谱”的分析优势；在医学诊断方面，SERS可对病理样品(如血液、尿液等)中食源性致病微生物进行快速检测，缩短了样本分析时间，使食源性疾病的快速诊断成为可能；随着微流控技术的发展，微流控平台结合SERS技术被称为“芯片实验室”应用于食源性致病微生物的检测，可提高分析的可控性，稳定性，特异性和灵敏度。通过对比分析，发现不同研究可采用不同分离方法、不同基底、不同目标捕获方式等实现了食源性致病微生物的检测，展示了不同方法间的差异性。已有研究表明了SERS在食源性致病微生物检测中应用可克服传统方法耗时等缺点，实现灵敏快速分析，为食品安全实时监控，食源性疾病即时诊断提供了有效的分析工具。同时，指出了SERS技术应用于食源性致病微生物分析依然面临很大挑战，(1)大多数研究并没有聚焦于实际样品，而标准培养液和实际样品的SERS检测存在较大差异，实际样品组分会对SERS响应产生干扰；(2)不同方法结果有较大差异，主要是由于纳米增强基底差异，吸附方式原理的差异，稳定性的差异等，因此需要更多深入研究进一步优化条件；(3)期望建立标准化的SERS方法替代传统技术，充分展示SERS作为新兴分析工具快速、灵敏、简捷的优势应用于食品安全，医学诊断等领域。将来，随着研究的深入及相关学科的发展，SERS作为极具潜力的快速分析工具，将在食品安全，生物医学等领域具有更广阔的应用前景。     

新型α-蒎烯基苯磺酰胺类化合物的合成及其抗真菌活性

以天然产物α蒎烯为原料,经多步反应合成了9个新型α-蒎烯基苯磺酰胺类化合物（7a~7i）,其结构经¹H NMR、 ¹³C NMR、 FT-IR和MS(ESI)表征。采用离体法测试了化合物的抗真菌活性。结果表明：在50 μg·mL^-1浓度下,目标化合物对黄瓜枯萎病菌、花生褐斑病菌、苹果轮纹病菌、小麦赤霉病菌以及番茄早疫病菌等5种植物病原菌有一定的抑制活性,其中化合物α-蒎烯基p-氯苯基磺酰胺(7d, R=p-Cl)和α-蒎烯基o-硝基苯基磺酰胺(7h, R=o-NO₂)对苹果轮纹病菌的抑制率分别为83.9%和79.6%（B级活性水平）,优于阳性对照百菌清（75.0%）;化合物α-蒎烯基m-甲基苯基磺酰胺(7b, R=m-Me)对番茄早疫病菌的抑制率为82.2%（B级活性水平）,优于阳性对照百菌清（73.9%）。-     

基于显微共聚焦拉曼技术对三种食源性致病菌的快速鉴别研究

采用显微共聚焦拉曼技术,建立了对三种常见食源性致病菌快速鉴别的检测方法。使用XploRA PLUS共聚焦拉曼光谱仪,在激光功率为5 mW、积分时间为30s、积分次数为1次的条件下,对德尔卑沙门氏菌、副溶血性弧菌和金黄色葡萄球菌进行了拉曼光谱数据的采集。对拉曼光谱采用多项式平滑算法和荧光背底扣除后,采用主成分分析法(PCA)对预处理后的数据进行降维,提取出前三个主成分的累计方差贡献率达到了95.4％,样本明显的聚为了3类。同时结合Fisher判别分析法(FLD)构建分类模型,对三种样本进行交叉验证,分类准确率达到了100％。结果表明,采用显微共聚焦拉曼技术与PCA-FLD方法结合可实现对三种食源性致病菌的快速准确鉴别且模型检测精度高,方法具有一定的实用性及参考价值。     

基于硒化锌薄膜法的食源性致病菌原位红外光谱检测

食源性致病菌是引发和威胁公众健康的主要因素之一。由于食源性致病菌种类繁多,常规检测方法复杂耗时要求高,因此迫切需要一种更加快速精确的致病菌检测技术。在传统红外光谱检测致病菌的流程中,如经典的溴化钾压片法,除了压片本身的操作之外通常还需对样品进行冷冻干燥（约需2 d）等耗时前处理过程,因而不利于高通量快速检测。本研究利用硒化锌薄膜法,在硒化锌窗片上直接滴加菌液、低温（48 ℃）烘干后进行原位检测,无需漫长的冻干处理,整个检测过程在50 min之内。同时,检测所需样品量少（10 μL）无需研磨等物理破坏性的制样过程,避免了常规溴化钾压片法中研磨颗粒粗细、制片厚薄误差及易碎片、吸潮等的不利影响。四种常见食源性致病菌（大肠杆菌DH5α;沙门氏菌CMCC 50041;霍乱弧菌SH04;金黄色葡萄球菌SH10）的硒化锌薄膜法与溴化钾压片法红外谱图对比分析表明：在相同的峰值检测阈值下（透过率大于0.05%）,本研究所采用的方法获得的二阶导数图谱在900～1 500 cm-1范围内可被识别的特征峰个数比溴化钾压片法明显增多（硒化锌薄膜法共计81个,溴化钾压片法共计58个）,特征峰在多个位置强度显著增加(1 119,1 085和915 cm-1等),且可将溴化钾压片法中较宽的单峰或不明显的双峰显示为较明显的双峰（大肠杆菌DH5α：1 441,1 391和1 219 cm-1等; 沙门氏菌CMCC 50041：1 490,1 219和1 025 cm-1;霍乱弧菌SH04：1 441和1 219 cm-1;金黄色葡萄球菌SH10：1 491,1 397和1 219 cm-1）,说明硒化锌薄膜法可以提高图谱分辨率及信噪比。基于硒化锌薄膜法的原位红外光谱法对常见食源性致病菌整体快速高通量检测将具有巨大的应用前景。     

SOLVING A CROP PROBLEM BY AN OPTIMAL CONTROL METHOD

ABSTRACT. A system of ordinary differential equations coupled with a parabolic partial differential equation is studied in order to understand an interaction between two crops and a pathogen. Two different types of crops are planted in same field in some pattern so that the spread of pathogen can be controlled. The pathogen prefers to eat one crop. The other crop, which is not preferred by the pathogen, is introduced to control the spread of pathogen in the farming land. The “optimal” initial planting pattern is sought to maximize plant yields while minimizing the variation in the planting pattern. The optimal pattern is characterized by a variation inequality involving the solutions of the optimality system. Numerical examples are given to illustrate the results.     

Rapid detection of Escherichia coli O157:H7 spiked into food matrices

Food poisoning causes untold discomfort to many people each year. One of the primary culprits in food poisoning is Escherichia coli O157:H7. While most cases cause intestinal discomfort, up to 7% of the incidences lead to a severe complication called hemolytic uremic syndrome which may be fatal. The traditional method for detection of E. coli O157:H7 in cases of food poisoning is to culture the food matrices and/or human stool. Additional performance-based antibody methods are also being used. The NRL array biosensor was developed to detect multiple antigens in multiple samples with little sample pretreatment in under 30 min. An assay for the specific detection of E. coli O157:H7 was developed, optimized and tested with a variety of spiked food matrices in this study. With no sample pre-enrichment, 5 × 10³ cells mL⁻¹ were detected in buffer in less than 30 min. Slight losses of sensitivity (1-5 × 10⁻⁴ cell mL⁻¹⁾ but not specificity occur in the presence of high levels of extraneous bacteria and in various food matrices (ground beef, turkey sausage, carcass wash, and apple juice). No significant difference was observed in the detection of E. coli O157:H7 in typical culture media (Luria Broth and Tryptic Soy Broth).     

Toll-like receptors for pathogen detection in water: challenges and benefits

The need for effective and efficient methods for pathogen detection in water is as serious as ever due to the health risk posed to human population by the consumption of pathogen-contaminated water. One of the important research streams which have been focused on by researchers for development of novel techniques for this purpose is biosensor technologies. Using different bio-recognition elements and transduction methodologies, biosensors have the potential to detect their analyte of interest in a fast and highly specific manner. Different pathogenic agents can be recognised by toll-like receptors (TLRs). The innate immune system of higher organisms employs TLRs for triggering intracellular signalling and induction of the expression of immune response genes. In this report, we explore the challenges associated with employing TLRs for pathogen detection in water samples. Although methods using TLR expressing cells also have been discussed, the focus of this review is on using TLR proteins as the bio-recognition elements in biosensors.     

Evaluation of epifluorescence image analysis of biofilm growth on stainless steel surfaces

Biofilm growth of Bacillus subtilis, Pseudomonas fragi, Pediococcus inopinatus and Listeria monocytogenes was studied on stainless steel surfaces at room and low temperatures to evaluate the results of traditional hygiene measures. The results were compared with those of image analysis of stainless steel surfaces in an epifluorescence microscope. Statistical analyses were carried out to determine the variations between the conventional cultivation swab method, the glycocalyx amount obtained using swabbing, and the values of the areas of the biofilm, slime and cells. As a general rule, old biofilms showed total counts at approximately the same levels as the young biofilm. The results showed that temperature affected the results for all strains except B. subtilis. The strains of Pe. inopinatus and Ps. fragi showed increased attachment at 6°C and L. monocytogenes at 25°C. The biofilm slime was more easily detached than the cells. The results indicated that the traditional swab method is not reliable for the measurement of biofilm formation on surfaces.     

A new sequence based encoding for prediction of host–pathogen protein interactions

Pathogen–host interactions are very important to figure out the infection process at the molecular level, where pathogen proteins physically bind to human proteins to manipulate critical biological processes in the host cell. Data scarcity and data unavailability are two major problems for computational approaches in the prediction of pathogen–host interactions. Developing a computational method to predict pathogen–host interactions with high accuracy, based on protein sequences alone, is of great importance because it can eliminate these problems. In this study, we propose a novel and robust sequence based feature extraction method, named Location Based Encoding, to predict pathogen–host interactions with machine learning based algorithms. In this context, we use Bacillus Anthracis and Yersinia Pestis data sets as the pathogen organisms and human proteins as the host model to compare our method with sequence based protein encoding methods, which are widely used in the literature, namely amino acid composition, amino acid pair, and conjoint triad. We use these encoding methods with decision trees (Random Forest, j48), statistical (Bayesian Networks, Naive Bayes), and instance based (kNN) classifiers to predict pathogen–host interactions. We conduct different experiments to evaluate the effectiveness of our method. We obtain the best results among all the experiments with RF classifier in terms of F1, accuracy, MCC, and AUC.