Microbial communities in the food chain: application of whole genome sequencing and metagenomics to investigate interactions between pathogens, commen

食源性疾病仍然是国家和全球的健康问题。根据食品标准局(2011年)的数据，据估计，每年约有100万人患有食源性疾病，其中约2万人需要住院治疗，500人死于食源性疾病。在英国，与食源性疾病相关的成本估计为15亿GB。考虑到食源性疾病对公众健康和经济的影响，重要的是更好地了解食源性病原体在食品生产链中的分布，并开发可靠和快速的食源性病原体检测和跟踪方法，特别是导致大量食源性疾病病例的致病菌。众所周知，周围环境对细菌种群造成压力，导致微生物群落的重组，这些都有可能影响致病菌在食品生产链中的持久性。一些疫情，包括最近在法国爆发的2018年与婴儿配方奶粉有关的沙门氏菌病，证明了了解持久性和影响这种情况的因素的重要性，以便制定预防这种情况发生的战略。组学技术的出现使微生物群落的特征及其对病原体存在的影响方面的进展成为可能。例如，元基因组学最近已被用于检测、鉴定和鉴定食品和食物链环境中的病原体。它提供了一个机会，以公正的方式观察样本中病原体的多样性和动态丰富性，并被用于改进以培养为基础的增菌方法。尽管目前由于元基因组数据的复杂性，这些标记不能被分配给特定的细菌基因组，但鸟枪式元基因组学可以提供一个有价值的、快速的观察特定物种、血清型、毒力和抗菌素耐药基因等遗传标记的存在。未来的元基因组和元基因组编码生物信息学的发展可能使这一点和研究系统发育的能力成为可能，并可能允许在病原体(如沙门氏菌)的存在与更广泛的亚群(如肠杆菌科)之间建立联系。基于培养的方法和随后的全基因组测序可以作为病原体确认和跟踪的补充方法。Mondelez希望探索这些新技术的应用，以更好地了解病原体在食品制造环境中的持久性，目的是开发预防发生的方法，并确定消除持续不需要的微生物的策略。为此，Mondelez感兴趣的是对病原体持久性的基本了解以及更广泛的细菌群落之间的相互作用，以确定确定病原体存在的标记和通过食物链跟踪病原体的技术方法。描述从指定食品生产环境中回收的沙门氏菌物种之间的遗传关系；并阐明基于独立于培养的方法的动态定居模式，以发现新的自然作用的生物控制策略

Foodborne illness remains a national and global health concern. According to the Food Standards Agency (2011), it is estimated that around 1 million people suffer a foodborne illness every year, with approximately 20,000 requiring hospital treatment and 500 deaths resulting from foodborne illness. The costs associated with foodborne disease in the UK are estimated to be £1.5 billion. Considering the public health impact and economic impact of foodborne illness, it is important to better understand the distribution of foodborne pathogens in food production chains and to develop reliable and rapid methods for foodborne pathogen detection and tracking, particularly pathogenic bacteria that cause a large-numbers of cases of foodborne disease. It is well known that surrounding environments cause stresses on bacterial populations and lead to reorganisation of microbial communities and these have the potential to influence the persistence of pathogenic bacteria in the food production chain. A number of outbreaks including the recent salmonellosis outbreak in France linked to infant formula in 2018 serve to demonstrate the importance of understanding persistence and the factors that influence this, in order to develop strategies to prevent this occurring. The advent of omics technologies enables advances in relation to characterization of microbial communities and their influence on the presence of pathogens. For example, metagenomics has recently been used for the detection, identification and characterisation of pathogens in food and in the food chain environment. It provides an opportunity to look at the diversity and the dynamic abundance of pathogens within a sample in an unbiased manner and is being used to improve culture-based enrichment methods. Shotgun metagenomics can provide a valuable, rapid view of the presence of genetic markers specifying species, serotype, virulence and antimicrobial resistance genes etc. although, at present, these markers cannot be assigned to specific bacterial genomes due to the complexity of the metagenomic data. Future metagenomic and metabarcoding bioinformatic developments are likely to make this and the ability to investigate phylogeny possible, and perhaps allow links to be drawn between presence of pathogens, such as Salmonella, and wider sub-groups, such as the Enterobacteriaceae. Culture-based methods followed by whole-genome sequencing may be used as a complementary approach to allow pathogen confirmation and tracking.Mondelez would like to explore application of these new techniques to better understand persistence of pathogens in food manufacturing settings with the aim of developing approaches to prevent occurrence and to identify strategies to remove persisting unwanted microorganisms. To that effect, Mondelez is interested in the fundamental understanding of pathogen persistence and the interactions between the wider bacterial communities to identify technological approaches to identify markers for pathogen presence and for tracking pathogens through the food chain. To characterise and describe the genetic relationships between a collection of Salmonella species recovered from a designated food production environment; and elucidate the dynamic colonisation patterns based on culture-independent methods to discover novel naturally-acting biocontrol strategies