A metabolomics analysis of Salmonella infection

The interplay between pathogens and hosts has been studied for decades using targeted approaches such as the analysis of mutants and host immunological responses. Although much has been learned from such studies, they focus on individual pathways and fail to reveal the global effects of infection on the host. To alleviate this issue, high-throughput methods such as transcriptomics and proteomics have been used to study host-pathogen interactions. Recently, metabolomics was established as a new method to study changes in the biochemical composition of host tissues. We report a metabolomics study of Salmonella enterica serovar Typhimurium infection. We used Fourier Transform Ion Cyclotron Resonance Mass Spectrometry with Direct Infusion to reveal that dozens of host metabolic pathways are affected by Salmonella in a murine infection model. In particular, multiple host hormone pathways are disrupted. Our results identify unappreciated effects of infection on host metabolism and shed light on mechanisms used by Salmonella to cause disease, and by the host to counter infection. Female C57BL/6 mice were infected with Salmonella enterica serovar Typhimurium SL1344 cells by oral gavage. Feces and livers were collected and metabolites extracted using acetonitrile. For experiments with feces, samples were collected from 4 mice before and after infection. For liver experiments, 11 uninfected and 11 infected mice were used. Samples were combined into 3 groups of 3-4 mice each, resulting in the analysis of 3 group samples of uninfected and 3 of infected mice. Extracts were infused into a 12-T Apex-Qe hybrid quadrupole-FT-ICR mass spectrometer equipped with an Apollo II electrospray ionization source, a quadrupole mass filter and a hexapole collision cell. Raw mass spectrometry data were processed as described elsewhere (Han et al. 2008. Metabolomics. 4:128-140 [PMID 19081807]). To identify differences in metabolite composition between uninfected and infected samples, we filtered the list of masses for metabolites which were present on one set of samples but not the other. Additionally, we calculated the ratios between averaged intensities of metabolites from uninfected and infected mice. To assign possible metabolite identities, monoisotopic neutral masses of interest were queried against MassTrix (http://masstrix.org). Masses were searched against the Mus musculus database within a mass error of 3 ppm. Data were analyzed by unpaired t tests with 95% confidence intervals.

病原体与宿主的相互作用已通过靶向研究方法被探索数十年，例如对突变体以及宿主免疫应答的分析。尽管此类研究已积累诸多认知，但它们仅聚焦于单一通路，无法揭示感染对宿主产生的全局影响。为解决这一局限，高通量组学方法如转录组学（transcriptomics）与蛋白质组学（proteomics）已被用于宿主-病原体互作研究。近年来，代谢组学（metabolomics）作为一种全新的宿主组织生化组成变化分析方法得以确立。

本研究报道了鼠伤寒沙门氏菌（Salmonella enterica serovar Typhimurium）感染的代谢组学分析。我们采用直接进样傅里叶变换离子回旋共振质谱法（Fourier Transform Ion Cyclotron Resonance Mass Spectrometry），在小鼠感染模型中证实，数十条宿主代谢通路会受沙门氏菌调控，其中多条宿主激素通路发生紊乱。本研究结果明确了此前未被关注的感染对宿主代谢的影响，同时为沙门氏菌的致病机制以及宿主的抗感染防御机制提供了新的见解。

本研究选用雌性C57BL/6小鼠，通过灌胃方式感染鼠伤寒沙门氏菌SL1344菌株。收集粪便与肝脏组织，采用乙腈（acetonitrile）提取代谢物。针对粪便样本的实验，我们在感染前后分别从4只小鼠体内采集样本；针对肝脏样本的实验，共设置11只未感染小鼠与11只感染小鼠。将样本按每3-4只小鼠合并为一组，最终得到3组未感染样本与3组感染样本用于后续分析。

将代谢物提取物注入配备Apollo II电喷雾电离源、四极杆质量过滤器与六极杆碰撞池的12-T Apex-Qe混合型四极杆-FT-ICR质谱仪中进行分析。原始质谱数据的处理流程参照已发表方法（Han等人，2008，《代谢组学》（Metabolomics），第4卷：128-140 [PMID 19081807]）。

为鉴定未感染与感染样本间的代谢物组成差异，我们对质量数列表进行筛选，仅保留仅在一组样本中存在的代谢物。此外，我们计算了未感染与感染小鼠的代谢物平均强度比值。为推定代谢物的可能身份，我们针对目标单同位素中性质量数，在MassTrix数据库（http://masstrix.org）中进行检索。检索范围限定为小家鼠（Mus musculus）数据库，质量误差阈值设置为3 ppm。数据统计分析采用非配对t检验，置信区间设置为95%。