Progress in research of enteroaggregative Escherichia coli
LIU Xue-tong, XIONG Yan-wen, XU Jian-guo
National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
Abstract
Enteroaggregative Escherichia coli (EAEC) is an emerging diarrheal pathogen. EAEC has caused sporadic infections and outbreaks in both developing and developed countries. We should pay more attention to this pathogen though no EAEC infection has been reported in our country. The pathogenesis of EAEC is complicated, and the strains are highly heterogeneous (polymorphic). The clinical manifestations are various and many factors influence the diagnosis and treatment of EAEC infection. This paper will summarize the pathogenesis of EAEC and the epidemiological characteristics, clinical manifestation and diagnosis/treatment of EAEC infection.
肠集聚性大肠杆菌研究进展
刘学通, 熊衍文, 徐建国
中国疾病预防控制中心传染病预防控制所, 传染病预防控制国家重点实验室, 北京 102206
摘要
肠集聚性大肠杆菌(enteroaggregative Escherichia coli, EAEC)是一类新发现的致泻性大肠杆菌。该菌目前已在世界各发达、发展中国家出现散发或暴发流行。我国虽尚未报道EAEC的散发或暴发,但仍需给予足够重视。EAEC的致病机制相对复杂,且不同菌株基因组异质性(多态性)较大,其感染后的临床表现不一,诊断治疗更要综合考虑多方面的因素。本文将从EAEC的流行病学特征、致病机制、临床表现、诊断和治疗等方面,对这一新发的肠道病原体做一综述。
内容大纲
1 流行病学特征
1.1 病原学 EAEC为革兰阴性短杆菌，形态上与普通大肠杆菌无异，大小为(0.4~0.7) μm×(1~3) μm，周身鞭毛，能运动，无芽胞。兼性厌氧，最适生长温度37 ℃，最适生长环境pH 7.0~7.4，无特殊营养需求。在普通营养琼脂平板上37 ℃培养18~24 h后，菌落为圆形，直径2~3 mm，稍凸起，灰白色，边缘整齐，不透明。其选择培养基可采用伊红美蓝琼脂﹑麦康凯琼脂等。
1.2 流行概况
1.2.1 发展中国家
EAEC感染是发展中国家腹泻的重要病因之一。巴西的研究数据表明，EAEC感染是小儿腹泻最常见的病因，在<2岁的儿童中，EAEC与发病具有较高的相关性[5]。EAEC与旅行者腹泻相关，在美国，EAEC是继ETEC之后，导致成年人旅行者腹泻的第二大病原菌，在去墨西哥旅游的美国成年人中，虽然大多数人无腹泻症状，但48%的人出现了抗集聚蛋白dispersin抗体的升高[6]。在墨西哥一项有关餐桌调味品的调查中发现，有44%的调味品中可检测到EAEC [7]。伊朗的研究发现，140例腹泻儿童病例中，有15(10.7%)例是由EAEC感染导致[8]。EAEC所导致的腹泻在孟加拉国也有很高的发病率[9]。在中非，EAEC是HIV阳性者腹泻的最常见病因[10]。
1.2.2 发达国家
在发达国家，EAEC是腹泻散发和暴发的病因。欧洲的研究表明，EAEC可能是发达国家儿童腹泻的主要病因[11]。在美国，EAEC是各年龄组儿童腹泻的最常见病因[12]。EAEC除引起散发感染外，在日本、意大利、英国、墨西哥、塞尔维亚等国均有EAEC引起暴发的报道。1993年，日本出现EAEC暴发，来自16所学校的2697名(40.6%)日本儿童，在食用了受到污染的学校午餐后，出现腹痛、恶心以及腹泻症状，10%的病例中可以检测到EAEC[13]。意大利连续两次的EAEC暴发中，24例患者的腹泻与食用未经消毒的EAEC污染的奶酪有关[14]。塞尔维亚的某新生儿病房中，19名婴儿感染EAEC，并有3人出现体重减轻和发热。英国、印度、法国的研究发现，EAEC与儿童及成人腹泻有关[15]。瑞典的一项前瞻性研究中发现，760例腹泻患者中，105例可以检测到致泻性大肠杆菌，其中16例是EAEC，仅次于ETEC[16]。此外，也有EAEC引起社区获得性腹泻病例的报道[17]。
EAEC与顽固性(≥14 d)腹泻有关，最近的研究结果表明，EAEC可从患有顽固性腹泻的患者粪便中分离得到[3]。也有研究发现，可以从患有顽固性腹泻的HIV患者粪便中分离到EAEC[18]。
1.2.3 大肠杆菌O104 ∶ H4感染暴发疫情
2011年5月，德国出现血清型为O104 ∶ H4的产志贺毒素大肠杆菌暴发疫情，共波及16个欧洲和北美国家。此次疫情共报道4075人感染，其中50例死亡，约22%的患者伴发溶血性尿毒综合征(hemolytic uremic syndrome, HUS)(WHO，2011年7月22日数据)。本次疫情的致病菌是获得了毒力基因stx2a的EAEC，并获得了产超光谱β-内酰胺酶(extended-spectrum beta-lactamase, ESBL)的耐药质粒[19]。我国目前尚无EAEC散发或暴发报道，主要原因是我们对这一病原体的认识和检测能力有限，对此需给予足够重视。
1.3 传染源
受感染的人是EAEC的主要传染源，目前尚无动物作为其传染源的报道[20]。
1.4 传播途径
EAEC主要通过粪口途径传播。志愿者试验表明，经口摄入1010 cfu的EAEC就可导致腹泻[21]。被污染的食品或水是传播EAEC的主要媒介，多项研究表明，发展中国家食品具有很高的EAEC污染率。同时，EAEC较其他病原菌，包括ETEC，能更容易从食品中分离到[22]。
1.5 易感人群
人群对EAEC普遍易感。研究发现，在IL-8的启动子区-251位点为AA纯合子基因型的人，更容易感染EAEC而出现腹泻症状[23]。感染EAEC的危险因素包括去发展中国家旅游、摄入受污染的水或食物、卫生条件差、宿主易感性以及免疫抑制(HIV感染)等[24]。
2 致病机制
EAEC致病机制相对复杂，且不同菌株基因型的异质性(多态性)非常大，其致病过程主要包括三个阶段：(1)EAEC依靠集聚粘附菌毛(AAF)和其他粘附因子粘附于肠黏膜；(2)在EAEC作用下，肠道细胞分泌黏液，细菌在肠上皮细胞表面形成生物膜；(3)EAEC释放毒素，引起肠道分泌炎性因子，产生黏膜毒性和炎症反应[2]。关于EAEC的毒力因子和相关粘附因子，研究最多的是具有广泛调节作用的AggR(master regulator)，它调控着pAA质粒和染色体上许多基因的表达[25]。表1列举了目前人们已认识的EAEC毒力因子和相关粘附因子。需要注意的是，由于EAEC菌株间的差异较大，不同菌株间携带的毒力因子种类会有很大差异。
3 临床表现
EAEC可以引起人类特别是小儿急性或顽固性(≥14 d)腹泻，其典型症状包括水样、黏液样、分泌性腹泻，通常无呕吐或很少出现呕吐，不伴有发热或仅有低热[7]。部分患者粪便中可检测到血细胞。
表1 EAEC毒力因子和相关粘附因子
Table 1 Virulence genes and related adherence factors in EAEC
| 基因名称 | 主要功能 | 参考文献 |
| 调节基因 | ||
| aggR | 广泛调控质粒和染色体上许多基因的表达，包括集聚粘附因子，AAF/I和AAF/II，蛋白质dispersin和插入在PheU位点的毒力岛上的大群基因 | [25] |
| 菌毛 | ||
| aggA | 集聚性粘附菌毛AAF/I，参与红细胞凝集 | [26] |
| aafA | 集聚性粘附菌毛AAF/II，介导EAEC粘附于肠黏膜 | [26] |
| agg3A | 集聚性粘附菌毛AAF/Ⅲ | [26] |
| hdaA | 赋予EAEC集聚粘附能力 | [27] |
| agg4A | AAF/IV菌毛亚基 | [28] |
| pilS | EAEC IV型菌毛主要亚单位 | [29] |
| 肠毒素 | ||
| astA | 热稳定肠毒素EAST1 | [26] |
| pet | 是一个108 kDa的自转运蛋白，发挥不耐热肠毒素和细胞毒素的功能 | [26] |
| set1 | 志贺菌肠毒素1 | [26] |
| set2 | 志贺菌肠毒素2 | [30] |
| cdt | 细胞致死肿胀毒素 | [26] |
| 外膜蛋白和其他粘附素 | ||
| hra1 | 耐热凝集素1(Hra1)，是EAEC菌株042的附属定植因子 | [31] |
| hra2 | Hra1、Tia、Hra2的是一个不可分割的外膜蛋白家族成员，赋予不同的定植表型 | [31] |
| tia | Tia，与Hra1高度同源，最初作为肠产毒性大肠杆菌的侵袭素和粘附素被发现 | [32] |
| papC | 肠外致病性大肠杆菌的毒力因子 | [33] |
| sfaD-sfaE | 肠外致病性大肠杆菌的毒力因子 | [33] |
| afaB-afaC | 肠外致病性大肠杆菌的毒力因子 | [33] |
| Dispersin转运子 | ||
| aatA | 编码一个ABC转运蛋白，将dispersin蛋白运送出EAEC的外膜 | [28] |
| 分泌蛋白 | ||
| aap | 编码dispersin分泌蛋白，大小为10 kDa，使EAEC具有分布于肠黏膜表面的能力。dispersin具有免疫原性。 | [26] |
| sat | 分泌的自转运毒素 | [28] |
| aaiC | AaiC，分泌蛋白 | [28] |
| pic | 编码丝氨酸蛋白酶自转运蛋白，大小为109 kDa，催化明胶降解。Pic蛋白具有粘蛋白酶活性，并能够引起红细胞凝集 | [28] |
| 耶尔森菌素系统 | ||
| irp2 | 耶尔森菌素生物合成基因，在铁运输和调控中发挥作用 | [26] |
| 植物血凝素 | ||
| lectin | 与霍乱毒素亚单位具有交叉反应，诱导HEp-2细胞形态变化和兔回肠的液体蓄积 | [34] |
| 其他 | ||
| shf | 隐藏的开放阅读框 | [26] |
| aerA | Aerobacin，见于尿道致病性大肠杆菌 | [35] |
| hly | 溶血素，见于尿道致病性大肠杆菌 | [35] |
| cnf | 细胞毒性坏死因子1型(CNF1)和2型(CNF2)，见于尿道致病性大肠杆菌 | [35] |
感染EAEC的志愿者表现为少量黏液性大便，粪便中无隐血和白细胞，所有感染志愿者均未出现发热。有研究表明，粪便中排泄EAEC的患者，其粪便中可检测到乳铁蛋白，同时粪便中IL-8的水平也异常升高[36]。波兰的一项研究表明，EAEC急性感染后，患者可发展为感染后易激惹肠道综合征(irritable bowel syndrome，IBS)，但EAEC引起IBS的机制目前尚不明确[37]。
EAEC感染产生复杂多样的临床症状，主要与宿主易感性、宿主免疫反应、EAEC菌株毒力异质性以及感染者所摄入的菌量有关[24]。
在免疫缺陷的人群中，腹泻有很高的发生率。在患有腹泻的AIDS患者中，可以检测到很多病原体，但却很难确定是哪一种病原体导致腹泻。研究发现，可从AIDS患者的腹泻粪便中检测到EAEC[38]。
4 鉴别诊断
EAEC感染的诊断，需要根据流行病学病史、临床表现和相关实验室检查结果，排除其他明确病因后做出综合判断。其鉴别需要排除其他类型的致泻性大肠杆菌，主要依靠HEp-2细胞粘附试验和毒力因子检测。
HEp-2细胞粘附试验是鉴定EAEC的“金标准”。EAEC菌株粘附于HEp-2细胞表面，表现为特征性的“叠砖样”粘附表型(图1)[1]。但该实验相对费时费力，且需要专门的设施及实验人员，因此很难在基层实验室开展。
图1 EAEC对HEp-2细胞粘附(×100)
Figure 1 HEp-2 cell adherence assay, aggregative adherence, AA(×100)
目前所报道的EAEC的检测方法很多。经福尔马林固定的HEp-2细胞，通过细胞粘附试验检测EAEC，敏感性为98%，特异性为100%；而采用DNA探针(CVD432)方法检测EAEC，其敏感性为15~89%，特异性为99%。也有文献报道，采用多重PCR和Real-time PCR方法检测EAEC，其敏感性和特异性均可达到100%。由于EAEC菌株基因组的异质性(多态性)，导致利用探针或者PCR方法来鉴定EAEC的敏感性差异很大[39]。
利用血清学方法检测EAEC的主要问题是EAEC血清型的多样性及相关性。德国儿童中分离到的14株典型EAEC菌株，分属于不同的血清型[40]。英国的一项研究中检测的EAEC菌株，分属于40个不同的O血清型。在另一项研究中，143株EAEC菌株中，有93株分属于47个不同的血清型[41]。由此可见，血清型检测已不再是EAEC有用的检测方法。
其他的检测试验包括：生物膜试验[42]、利用ELISA方法定量检测EAEC感染后分泌的免疫球蛋白A(sIgA)[43]，以及确定某种特定的细胞因子反应模式来作为EAEC感染的标志物等[36]。
5 治疗
EAEC感染所致腹泻通常是一种自限性的疾病，口服补液疗法治疗有效。伴有持续腹泻的EAEC感染，通过单纯口服补液疗法很难治愈，因此，在EAEC的高发地区，采用疫苗为主的综合预防策略，成为重中之重[1]。
抗生素疗法需要综合考虑感染者的个体情况以及细菌的抗生素敏感性。治疗EAEC感染通常使用的抗生素是喹诺酮类、阿奇霉素和利福昔明。有研究报道，EAEC对氨苄西林、四环素、三甲氧苄氨嘧啶/磺胺甲基异恶唑和氯霉素有很高的耐药性。研究发现，包括dfrA5、aadA1a、drA13和oxa5在内的耐药整合子可能与EAEC的抗生素耐药性产生有关[24]。
此外，人乳中分离的乳铁蛋白、重组人乳铁蛋白以及牛乳铁蛋白，能够有效抑制EAEC对细胞的“叠砖样”集聚粘附。牛乳铁蛋白还能够抑制EAEC感染后生物膜的形成，并增加EAEC的自身凝集反应，这更表明其对表面粘附素的影响。研究表明，在乳铁蛋白作用下，组氨酸标记的dispersin和表面菌毛(AAF/II)会发生丢失，AAF/II会降解，但dispersin不会降解。然而，乳铁蛋白作为一种非抗生素方法，是否能够有效的治疗和预防EAEC感染仍不清楚[1]。
6 总结
EAEC是儿童、成年人以及艾滋病患者急性和顽固性腹泻的病因之一。EAEC已在世界各发达、发展中国家引起散发或暴发流行。确定EAEC致病机制的主要困难存在于EAEC菌株的多样性和异质性。 HEp-2细胞粘附试验仍然是检测EAEC的“金标准”。虽然aggR在大多数EAEC菌株中存在，但是没有一种毒力基因是所有EAEC菌株所共有的。EAEC感染所致腹泻是一个复杂的宿主病原体相互作用过程，与宿主易感性、宿主免疫反应、菌株毒力异质性以及感染者所摄入的菌量有关。EAEC感染所致腹泻通常是一种自限性的疾病，口服补液疗法治疗有效。抗生素治疗需要综合考虑感染者的个体情况及细菌的抗生素敏感性。伴随着检测、鉴定方法的改进，以及治疗方法的改善，人们将更深入的了解EAEC这一新发病原体。
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[18] Hu WH. The simulation and forecast of Grey model to incidence of four diseases in changsha city[J]. Pratcial Preventive Medicine,2007,14(4):1097-1099.(in Chinese)
胡伟红.灰色模型对长沙市四类传染病发病率的模拟与预测[J].实用预防医学,2007,14(4):1097-1099.
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郭立春,王汉宁,吴伟,等.应用GM(1,1,sinω)模型预测肾综合征出血热发病率研究[J].中国热带医学,2009,9(3):415-417.
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方立群,曹务春,陈化新,等.应用地理信息系统分析中国肾综合征出血热的空间分布[J].中华流行病学杂志,2003,24(4):265-268.
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陈朝,周晓农,姚振奇,等.血吸虫病人群感染危险因素空间关系分析[J].中国血吸虫病防治杂志,2005,17(5):324-327.
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胡伟红.灰色模型对长沙市四类传染病发病率的模拟与预测[J].实用预防医学,2007,14(4):1097-1099.
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郭立春,王汉宁,吴伟,等.应用GM(1,1,sinω)模型预测肾综合征出血热发病率研究[J].中国热带医学,2009,9(3):415-417.
[20] Diez Roux AV, Aiello AE. Multilevel Analysis of Infectious Diseases[J]. J Infect Dis,2005,191 Suppl 1:S25-33.
[21] Jia TW, Zhou XN, Wang XH, et al. Assessment of the age-specific disability weight of chronic schistosomiasis japonica[J]. Bull World Health Organ,2007,85(6):458-465.
[22] Ladeia-Andrade S, Ferreira MU, de Carvalho ME, et al. Age-dependent acquisition of protective immunity to malaria in riverine populations of the amazon basin of brazil[J]. Am J Trop Med Hyg,2009,80(3):452-459.
[23] Backer JA, Hagenaars TJ, Roermund HJ, et al. Modelling the effectiveness and risks of vaccination strategies to control classical swine fever epidemics[J]. J R Soc Interface,2009,6(39):849-861.
[24] Wernck GL, Costa CH, Walker AM, et al. Multilevel modelling of the incidence of visceral leishmaniasis in Teresina, Brazil[J]. Epidemiol Infect,2007,135(2):195-201.
[25] Jewell CP, Kypraios T, Christley RM, et al. A novel approach to real-time risk prediction for emerging infectious diseases: a case study in Avian Influenza H5N1[J]. Prev Vet Med,2009,91(1):19-28.
[26] Black MA, Craig BA. Estimating disease prevalence in the absence of a gold standard[J]. Stat Med,2002,21(18):2653-2669.
[27] Dendukuri N, Joseph L. Bayesian approaches to modeling the conditional dependence between multiple diagnostic tests[J]. Biometrics,2001,57(1):158-167.
[28] Li BD. Mathematical Modeling Method[M]. Gansu: Gansu Education Press,2006.(in Chinese)
李伯德.数学建模方法[M].甘肃:甘肃教育出版社,2006.
[29] Oxlade O, Schwartzman K, Benedetti A, et al. Developing a tuberculosis transmission model that accounts for changes in population health[J]. Med Decis Making,2011,31(1):53-68.
[30] Jin L. Pratcial fuzzy mathematics[M]. Beijing: Scientific and Technical Documentation Press,1989.(in Chinese)
荩垆.实用模糊数学[M].北京:科学技术文献出版社,1989.
[31] Li AG. Fuzzy sets and applications[M]. Beijing: Metallurgical Industuy Press,2005.(in Chinese)
李安贵.模糊数学及其应用[M].第2版. 北京:冶金工业出版社,2005.
[32] Molchanov PA, Dudatiev AV, Podobna YY, et al. Fuzzy sets applications for cancer risk assessment[J]. Cent Eur J Public Health,2002,10(3):121-123.
[33] Grossi E. Medical concepts related to individual risk are better explained with "plausibility" rather than "probability"[J]. BMC Cardiovasc Disord,2005,5:31.
[34] da Costa Sousa JM, Kaymak U. Model predictive control using fuzzy decision functions[J]. IEEE Trans Syst Man Cybern B Cybern,2001,31(1):54-65.
[35] Cazelles B, Chavez M, Magny GC, et al. Time-dependent spectral analysis of epidemiological time-series with wavelets[J]. J R Soc Interface,2007,4(15):625-636.
[36] Johansson MA, Cummings DA, Glass GE. Multiyear climate variability and dengue-El Niño southern oscillation, weather, and dengue incidence in Puerto Rico, Mexico, and Thailand: a longitudinal data analysis[J]. PLoS Med,2009,6(11):e1000168.
[37] Beale L, Abellan JJ, Hodgson S, et al. Methodologie issues and approaches to spatial epidemiology[J]. Environ Health Perspect,2008,116(8):1105-1110.
[38] Fang LQ, Cao WC, Chen HX, et al. Study on the application of geographic information system in spatial distribution of hemorrhagic fever with renal syndrome in China[J].Chinese Journal of Epidemiology,2003,24(4):265-268.(in Chinese)
方立群,曹务春,陈化新,等.应用地理信息系统分析中国肾综合征出血热的空间分布[J].中华流行病学杂志,2003,24(4):265-268.
[39] Chen Z, Zhou XN, Yao ZQ, et al. Analysis of spatial relations of risk factors to infection rate of schistosomiasis in population[J]. Chinese Journal of Schistosomiasis Control,2005,17(5):324-327.(in Chinese)
陈朝,周晓农,姚振奇,等.血吸虫病人群感染危险因素空间关系分析[J].中国血吸虫病防治杂志,2005,17(5):324-327.
[40] Diuk-Wasser MA, Hoen AG, Cislo P, et al. Human risk of infection with Borrelia burgdorferi, the Lyme disease agent, in eastern United States[J]. Am J Trop Med Hyg,2012, 86(2):320-327.
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