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Closely related Salmonella Derby strains triggered distinct gut microbiota alteration

Closely related Salmonella Derby strains triggered distinct gut microbiota alteration Background: Salmonella Derby is one of the most predominant Salmonella serotypes that seriously threatens food safety. This bacterium can be further differentiated to sub-populations with different population sizes; however, whether and how the S. Derby–gut microbiota interactions affect epidemic patterns of S. Derby sub-populations remain largely unknown. Results: We selected two representative strains, 14T and 14C, which represent rarely distributed and prevalent sub-populations of the S. Derby ST40 group, respectively, to address this question using a mouse model. Eec ff ts of oral administration of both strains was monitored for 14 days. Alpha diversity of gut microbiota at early stages of infection (4 h post infection) was higher in 14C-treated mice and lower in 14T-treated mice compared with controls. Strain 14T triggered stronger inflammation responses but with lower pathogen titer in spleen compared with strain 14C at 14 days post infection. Certain known probiotic bacteria that can hinder colonization of Salmonella, such as Bifidobacteriaceae and Akkermansiaceae, exhibited increased relative abundance in 14T-treated mice compared with 14C-treated mice. Our results also demonstrated that Ligilactobacillus strains isolated from gut microbiota showed stronger antagonistic activity against strain 14T compared with strain 14C. Conclusions: We identified how S. Derby infection affected gut microbiota composition, and found that the 14T strain, which represented a rarely distributed S. Derby sub-population, triggered stronger host inflammation responses and gut microbiota disturbance compared with the 14C strain, which represented a prevalent S. Derby sub-population. This study provides novel insights on the impacts of gut microbiota on the epidemic patterns of Salmonella populations. Keywords: Salmonella Derby, Gut microbiota, Inter-strain variation Background gut microbiota, particularly certain keystone microor- Understanding the interactions between gut microbiota ganisms inside the microbiota, play an important role in and Salmonella is critical to managing and preventing the Salmonella colonization and infection process, and infection caused by Salmonella through microbiome the colonization and infection process may be negatively engineering approaches such as probiotic administra- or positively regulated by the microbiota [3–8, 22]. For tion [1, 2]. Increasing evidence has demonstrated that instance, Lactobacillus acidophilus and Mucispirillum schaedleri are proven to ameliorate S. Typhimurium- induced diarrhea and inflammation [9, 10]. Conversely, *Correspondence: zmpan@yzu.edu.cn; yzzhang@yzu.edu.cn certain saccharolytic bacteria, such as Bacteroides the- Jiangsu Co-Innovation Center for Prevention and Control of Important taiotaomicron, can confer advantages to S. Typhimurium Animal Infectious Diseases and Zoonoses, Yangzhou University, during infection by producing 1,2-propanediol, which Yangzhou, China Full list of author information is available at the end of the article serves as an electron acceptor to promote respiratory © The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. The Creative Commons Public Domain Dedication waiver (http:// creat iveco mmons. org/ publi cdoma in/ zero/1. 0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Yuan et al. Gut Pathogens (2022) 14:6 Page 2 of 12 growth of the pathogen [6]. These findings have shown the most predominant population, and the ST40 group promising potential in Salmonella management. How- was further differentiated into sub-populations with ever, the majority of our current knowledge on the inter- distinct population sizes using a very high-resolution actions between Salmonella and gut microbiota comes CRISPR-typing method [14, 15]. For example, our labo- from studies on a single well-characterized strain, such ratory collected 369 ST40-affiliated strains from multi - as S. Typhimurium ATCC 14028, or from only a few Sal- ple sites in Jiangsu province during several years. These monella serotypes including S. Typhimurium. Little is strains were differentiated into 40 sub-populations based known about how other Salmonella serotypes interact on the CRISPR-typing method. Certain sub-populations, with gut microbiota and the consequences of the interac- such as CRISPR-type 38, were found to be present in tions on the epidemic of the pathogens, although many many locations and persisted throughout the sample serotypes have caused dramatic economical losses and collection course, whereas some sub-populations were threatened food safety and public health. Recent studies rarely identified during this long-term epidemiological have demonstrated that strains affiliated with the same study (e.g., CRISPR-type 39 contained only one strain) Salmonella serotype can also exhibit distinct inter-strain (Additional file  1: Figure S1) [14, 15]. In the current variations on epidemic prevalence, pathogenicity, and study, we selected two representative strains, 14T (the risk to food safety, etc. [11–15]. However, the role of gut sole strain in CRISPR-type 39) and 14C (a representative microbiota–Salmonella interactions on the observed strain of CRISPR-type 38 strain group), and investigated epidemic pattern differences as well as other variations the conserved and specifically altered patterns of gut among strains that harbor conserved genomic back- microbiota triggered by the two strains. grounds (i.e., strains from same serotype or even same sequence type (ST) scheme) remain elusive. Here, we Results compared the interaction patterns between gut micro- S. Derby 14T and 14C exhibited distinct cellular adhesion biota and two representative S. Derby strains that were ability and triggered significantly different host selected from two S. Derby sub-populations with distinct inflammation response population sizes (rarely isolated vs. frequently isolated in In our previous study, we isolated 369 S. Derby ST40 our multi-site, long-term epidemic investigation study) strains in Jiangsu, China during 2011–2016, and sub- to address these questions. typed these strains to 40 sub-populations using a CRISPR Recent epidemic studies have demonstrated that S. typing profiling analysis [14, 15]. We selected representa- Derby has become one of the predominant Salmonella tive strains from each sub-population and determined serovars isolated from pork samples and humans globally host responses to pathogen infection using the mouse [16–18]. For instance, around 27% of pork samples col- model. Interestingly, we observed that two closely related lected from China were reported to be contaminated by strains, 14T and 14C, showed distinct cellular adhesion S. Derby [17]. S. Derby causes long-term asymptomatic ability and triggered significantly different host inflam - infection in pigs, and can be released from the gastro- mation response (Fig. 1). Of note, 14T was the sole strain intestinal tract during the slaughtering process, which representing the CRISPR type 39, while 14C was a rep- is probably the main cause of the high contamination resentative strain from a long-term existing sub-popu- rate in the pork samples [19, 20]. More importantly, S. lation CRISPR type 38 that contained multiple strains Derby has become one of the most common Salmonella isolated from 2011–2015 (Additional file  1: Figure S1) serotypes identified in diarrheal patients in China, caus - [15]. Strain 14C exhibited significantly higher epithe - ing heightened interest in the pig farming industry to lia cell adhesion than strain 14T (19. 26 ± 4.14% for 14C eradicate this pathogen [21]. Strains affiliated with the S. and 14.94 ± 3.41% for 14T, mean ± SE, four independent Derby serotype have been further differentiated to ST- biological replicates, Wilcoxon signed-rank test, p < 0.05) types with the multilocus sequence typing method [14]. (Fig.  1A). When determined at 14  days post infection Of the identified S. Derby strains isolated from the pork (dpi), the bacterial titer in spleen of the 14C-adminis- production chains in China, ST40-affiliated strains were trated mice was higher, although not significantly higher, (See figure on next page.) Fig. 1 A Adhesion rates of Salmonella Derby 14T and 14C to MC 38 cells, Wilcoxon signed-rank test, *p < 0.05, error bars represent SE from mean, four independent biological replicates are included, and three technical replicates were included for each biological replicate. B Bacterial titers of 14T (n = 10) and 14C (n = 10) in spleen. BD, below the detection limit. C Quantification of lipocalin-2 level in serum at 14 days post infection among treatments (n = 9 for 14T and 14C treatments and n = 10 for control group), one-way ANOVA with post-hoc Tukey HSD test, *p < 0.05. D Body weight of mice at different time points among treatments (n = 10 for 14T and 14C treatments and n = 9 for control group). The body weight difference between 14T and 14C treatments were determined using one-way ANOVA with post-hoc Duncan test, with significant differences were labeled with + (p < 0.05) Y uan et al. Gut Pathogens (2022) 14:6 Page 3 of 12 Fig. 1 (See legend on previous page.) Yuan et al. Gut Pathogens (2022) 14:6 Page 4 of 12 than that of the 14T-administrated mice (Mann Whit- 14T and 14C groups was significantly higher compared ney test, p > 0.05) (Fig.  1B). Interestingly, both 14T- and with the control group at 14  dpi, suggested that the S. 14C-treated mice exhibited higher Lipocalin-2 lev- Derby treatment dramatically increased the species rich- els compared with control, and those treated with 14T ness of the microbial community, while the microbial exhibited significantly stronger inflammation response diversity was not significantly different among the three compared with 14C (one-way ANOVA with post-hoc groups as suggested by the Shannon index (Fig. 2C). Tukey HSD test, p > 0.05) (Fig.  1C). Furthermore, we The beta diversity results showed that the 14T adminis - found that the mice treated with 14T and 14C gained less tration triggered dramatical microbial community altera- body weight compared with the control mice at several tion at 0 dpi (PERMANOVA, p < 0.05), while the influence time points (one-way ANOVA with post-hoc Duncan of 14C administration on the gut microbial community test, p < 0.05), and the result also suggested 14T-treated structure was not significant (PERMANOVA, p > 0.05) mice gained less body weight than the 14C-treated mice (Additional file  1: Figure S3). As a result, the community at 2 dpi and 3 dpi, despite the difference was not signifi - structure between the 14T and 14C groups differed sig - cant (Fig. 1D). nificantly (PERMANOVA, p < 0.005) (Additional file  1: Figure S3). The community structure of the 14T-treated Strains 14T and 14C perturbed the gut microbiota mice was significantly different from that of the control in different manners mice at 2  dpi (PERMANOVA, p < 0.05), while the com- To reveal the roles of gut microbiota on the observed dif- munity structure difference was not significant between ferent host inflammation response as well as other dif - 14C and control groups or 14T and 14C groups. No sig- ferences triggered by the two S. Derby strains, we sought nificant community structure difference was observed to select representative time points in the infection among the three groups at 14  dpi (PERMANOVA, course based on the in vivo S. Derby population dynamic p > 0.05) (Additional file  1: Figure S3). Taken together, (Additional file  1: Table  S1) for gut microbiota compari- these results suggested that 14C administration did not son analysis. Finally, we select three representative time altered overall structure of the gut microbiota during the points: 0  dpi (approximately 4  h post infection when infection course, while the community structure was sig- high population of S. Derby strains have existed in the nificantly altered by the 14T strain shortly after admin - gut), 2  dpi (S. Derby has successfully invaded the spleen istrated, and then the influence of 14T on the overall and liver), and 14  dpi (majority of the invading S. Derby microbial community was mostly eliminated at 14 dpi. strains have been eliminated from the gut), and collected Through group-wise comparisons, we observed that the fecal samples for 16S rDNA V4 region sequencing several taxa, such as Enterobacteriaceae, exhibited con- analysis. sistent dynamic alteration in relative abundance in both A total of 5,446,132 high quality reads were gener- 14T and 14C groups compared with controls (deter- ated from 87 fecal samples, and the average number of mined by the Heat_tree function in Metacoder package sequences per sample was 62,599 (SD, 6308), with high- implemented in MicrobiomeAnalyst, adjusted p < 0.05, est number 72,646 and lowest number 33,869 per sample. same herein) (Fig.  3 and Additional file  2: Table S2). The These sequenced were trimmed, filtered and clustered relative abundance increases of Enterobacteriaceae in into 1491 Operational Taxonomic Units (OTUs). The 14T and 14C groups at 0 dpi were mainly contributed by rarefaction curve demonstrated that the OTU number the administrated S. Derby strains (accounting for 70.8% increased gradually and tended to be flat as the depth of of the identified Enterobacteriaceae), while the contri - sequencing increased (Additional file  1: Figure S2), which bution of the administrated strains to the Enterobacte- suggested that our sequencing had nearly saturated and riaceae composition was small (< 1%) at 2 dpi and 14 dpi. the abundance results could reflect the bacterial diversity Interestingly, quite a few taxa were found to exhibit in the samples confidently. distinct alteration in relative abundance for 14T- and The alpha diversity of gut microbiota in 14T- and 14C-treated mice compared with control ones (Fig. 3 and 14C- administrated mice was measured using Shan- Additional file  2: Table S2). At 0 dpi, several taxa affiliated non and Chao1 indices. Both indices suggested that the with Clostridiales (an order affiliated with Firmicutes) microbial diversity and richness was significantly lower exhibited significantly increased relative abundance in in the 14T-treated mice than in the 14C-treated mice at 14C-treated mice, but not in the 14T-treated mice com- 0  dpi (one-way ANOVA with post-hoc Tukey HSD test, pared with the control. At the same time, the relative p < 0.005) (Fig.  2A), with the difference diminishing over abundance of Rikenellaceae and Prevotellaceae, both of time. No significant differences among the 14T, 14C which are affiliated with Bacteroidetes, was dramatically and control groups were observed when tested at 2  dpi increased in 14T-treated mice, but not in 14C-treated (ANOVA, p > 0.05) (Fig.  2B). The Chao1 index of both mice, compared with the control. Significant differences Y uan et al. Gut Pathogens (2022) 14:6 Page 5 of 12 Fig. 2 Shannon and Chaol diversity indices of 14T, 14C, and untreated control mice at A 0 days post infection (dpi), B 2 dpi, and C 14 dpi. Mean values are denoted as black diamonds. *p < 0.05, **p < 0.01, according to one-way ANOVA with post-hoc Tukey HSD test. At each timepoint, ten samples from 14T and 14C treatments, and nine samples from the control group were included Yuan et al. Gut Pathogens (2022) 14:6 Page 6 of 12 Fig. 3 Heat tree of differentially abundant taxa in gut microbiota classified at family level (panel A, 0 dpi; panel B, 2 dpi; panel C, 14 dpi). The color of each taxon represents the log2 ratio of median proportion of reads observed in a given treatment. Only significantly differentially abundant taxa were labeled, which were determined by Heat_tree function in the Metacoder package implemented in MicrobiomeAnalyst server. Width of nodes and edges denotes the relative abundance of the given taxa. Ten samples from 14T and 14C treatments, and nine samples from the control group were included in this analysis Y uan et al. Gut Pathogens (2022) 14:6 Page 7 of 12 in relative abundance of Firmicutes and Bacteroidetes between the 14T and 14C groups were also observed (Fig.  3A and Additional file  2: Table  S2). Several taxa that are not affiliated with Firmicutes and Bacteroidetes, such as Burkholderiaceae (affiliated with Proteobacteria) and Bifidobacteriaceae (affiliated with Actinobacteria), were observed to exhibit differential relative abundance between 14C and control or 14T and control groups at 2 dpi, with little overlap observed between the majority of these differentially abundant taxa in the two group-wise comparisons (Fig.  3B and Additional file  2: Table S2). Of note, the relative abundance of Lactobacillaceae, Bifido - bacteriaceae, Enterobacteriaceae, and Akkermansiaceae, were found to be higher in the 14T group compared with the 14C group (Fig.  3B and Additional file  2: Table  S2). At 14  dpi, the bacterial community of the 14T- and 14C-treated mice trended to show similar composition with many fewer differentially abundant taxa observed compared with 2  dpi (Figs.  3B and C and Additional file  2: Table S2); however, the community in both groups diverged from that of the control group, suggesting that the infection of two strains caused dysbiosis of the gut microbiota, although the majority of the infected S. Derby strains were eliminated by 14 dpi. Strains 14T and 14C exhibited different response Fig. 4 A Antagonistic activity of Lactobacillus murine isolates against to mice‑originated antagonistic Ligilactobacillus strains Salmonella Derby 14T (left) and 14C (right). B Diameter of the Through microbiota profiling analysis, we found that inhibition zone of Lactobacillus murine isolates against 14T and 14C, Lactobacillaceae exhibited increased relative abun- shown as mean ± SD, n = 3 dance in both 14T- and 14C-treated mice compared with the control mice at 2  dpi; moreover, this taxon consist- ently exhibited higher, although not significantly, rela - tive abundance in the 14T group than in the 14C group Discussion during the course of infection (Fig.  3 and Additional In this study, we investigated gut microbiota altera- file  2: Table  S2). Lactobacillus (a single genus based on tion patterns triggered by infection with two S. Derby Silva 132 database, has been reclassified to several gen - strains from the same ST40 group but with distinct epi- era since 2020) was the most predominated genus affili - demic patterns (i.e., rarely-distributed vs. prevalent). Our ated with Lactobacillaceae, and accounted for 99.8% of results demonstrated that infection with S. Derby strains the accumulated relative abundance of Lactobacillaceae. triggered distinct microbiota responses compared with Given that many members affiliated with Lactobacillus that of well-studied S. Typhimurium. The diversity of gut are commonly known as probiotic bacteria [23], the Lac- microbiota was increased in S. Derby-treated mice, which tobacillus bacteria were isolated from the fecal samples was opposite compared with the S. Typhimurium-treated of treated mice using MRS medium. Two representative mice [24–26]. High diversity of gut microbiota can ben- isolates, L2 and L19, both of which were affiliated with efit the host by providing nutrients as well as resisting Ligilactobacillus murinus, were obtained. Interestingly, against pathogen colonization; for instance, higher com- both L2 and L19 strains exhibited stronger, although not plexity in gut microbiota usually results in increased pro- significantly, inhibitory effects on growth of S. Derby 14T tection against Salmonella-induced gut inflammation compared with 14C (t-test, p > 0.05 for both strains). The [27]. Certain consistent altered patterns were observed zone of inhibition against 14T and 14C was 1.0 ± 0.16 cm in the gut microbiota of mice infected with S. Derby and (mean ± SD) and 0.78 ± 0.14 cm (28% higher) for L2, and S. Typhimurium, such as reduced relative abundance of the inhibition zone against 14T was 0.49 ± 0.07  cm and Prevotella and Odoribacter [10]; however, the taxonomic the value against 14C was 0.44 ± 0.12 cm (10% higher) for composition was strikingly different. For example, infec - L19 strain, respectively (Fig. 4). tion with S. Typhimurium significantly increased the Yuan et al. Gut Pathogens (2022) 14:6 Page 8 of 12 relative abundance of Citrobacter, a potentially patho- 14C-treated mice (Fig.  3). Lactobacillaceae may reduce genic bacteria [25, 28], whereas infection with both 14T Salmonella shedding and translocation to liver and and 14C strains decreased the relative abundance of Cit- spleen [34–37]. Enterobacteriaceae, population of which robacter (Additional file  1: Figure S4). The microbiota was increased as driven by the elevated oxygen level in composition is strongly associated with the susceptibility the gut due to enteric pathogens infection [38], were to enteric pathogen infection [27, 29]. The differences in reported to restrict Salmonella expansion and infection microbiota alteration between the S. Typhimurium- and by competing for iron, oxygen and other resources with S. Derby-infected mice and its association with the con- this pathogen [24, 39, 40]. Akkermansiaceae are known sequences of the two serotypes on the hosts need to be to exacerbate inflammation in S. Typhimurium-infected further explored. gnotobiotic mice [41]. Furthermore, our results demon- Interestingly, although strains S. Derby 14T and 14C strated that identical microbiota members can exhibit used in this study shared highly conserved genomic con- different direct-contact antagonistic activities against tents [14, 15], the host symptoms and gut microbiota 14T and 14C (Fig.  4). Thus, we speculate that the more alteration patterns mediated by infection with the two aggressive 14T strain triggered higher levels of host and strains were distinct (Figs.  1, 2, 3). Strain 14T treatment microbiota immune responses, which hindered 14T from triggered a stronger inflammation response compared translocating to spleen and liver, resulting in lower 14T with 14C, but a smaller spleen-translocated 14T popu- in vivo populations and restricted distribution compared lation was observed. This observation was in concert with 14C. with the host cell adhesion results in that fewer 14T cells adhered to MC 38 cells compared with 14C (Fig. 1). Low- Conclusion grade inflammation may benefit 14C, possibly by mak - Overall, our study revealed distinct and conserved host ing a trade-off between inflammation and dissemination gut microbiota response patterns triggered by the two S. to and/or survival in the liver and spleen [29]. Of note, Derby strains, 14T and 14C, which represented two dis- the host inflammation response was measured based on tinct epidemic sub-populations with conserved genomic the Lipocalin-2 assay in this study, and the result might background. Colonization resistance conferred by the represent only a part of the immune response. Shortly microbiota helps the host resist a variety of pathogens after intragastric administration (4 h after treatment), the including Salmonella. Elucidating the differences and microbial diversity of 14C-treated mice was increased, conservations of gut microbiota–Salmonella interactions whereas that of 14T-treated mice was decreased (Fig.  2). at serotype- and strain-level will help us understand the Higher complexity of gut microbiota is believed to be epidemic differences in Salmonella, and benefit the devel - associated with increased protection against Salmonella- opment of microbiome engineering-based therapies. induced gut inflammation [27]. At 0  dpi, Enterobacte - riaceae exhibited increased relative abundance in both Methods 14T and 14C treated mice compared with the control Salmonella strains mice at 0 dpi, which was mainly attributed to the admin- Two representative S. Derby strains, 14T-T8N3 and istrated S. Derby strains; however, the high population 14C-D14P2 (S. Derby 14T and 14C herein), were used in of S. Derby in the gut microbiota was temporary and this study. The two strains were isolated from pork sam - represented a very minute fraction of the gut micro- ples collected in Yangzhou, Jiangsu, China, and affiliated biota at 2  dpi and 14  dpi. Increased relative abundance with Salmonella sequence type (ST) 40 by multilocus of Clostridiales in 14C-treated mice, and higher rela- sequence typing analysis, but represented two sub-pop- tive abundance of Rikenellaceae and Prevotellaceae in ulations with different population sizes (14T from the 14T-treated mice were also observed at 0  dpi. Members distribution-restricted CRISPR-type 39 and 14C from of Clostridiales are known as short chain fatty acids pro- the prevalent CRISPR-type 38 sub-populations) (Addi- ducers, which can down-regulate the expression of viru- tional file  1: Figure S1) [14, 15]. The strains were grown in lence genes of Salmonella, as well as limit O availability Luria–Bertani (LB) broth with shaking at 37 ℃ overnight, in the lumen of the gut, together restricting the expan- and the bacterial population was adjusted to OD = 1.0 sion of Salmonella [4, 30, 31]. In contrast, Rikenellaceae with PBS, then centrifuged and suspended with 2.5% and Prevotellaceae produce hydrogen, which may benefit NaHCO solution for intragastric administration. Salmonella in terms of expansion and colonization at the initial infection stage [32, 33]. At 2 dpi, the relative abun- Cellular adhesion assays dance of Lactobacillaceae, Bifidobacteriaceae, Entero- The MC38 (Mouse colon cancer epithelial cell) cell line bacteriaceae, and Akkermansiaceae, were found to be was purchased from Hunan Fenghui Biotechnology Co., dramatically higher in 14T-treated mice compared with Ltd. (Hunan, China) (catalog no. CL0203). S. Derby 14T Y uan et al. Gut Pathogens (2022) 14:6 Page 9 of 12 and 14C strains were cultured in LB medium at 37  °C 2  dpi, and 14  dpi. Fecal pellets collected from individual for 16  h, and then diluted into a new LB medium and mouse were measured and stored at −70 ℃ until further incubated to OD = 1.0. The MC38 cells were seeded processing. into 24-well plates with 4 × 10 cells per well, and cul- tured overnight at 37  °C with 5% CO . A total of 1  mL Inflammation marker quantification of bacterial culture was collected and washed twice with Lipocalin-2 is known as a good biomarker of inflamma - Dulbecco’s Modified Eagle Medium (DMEM) (Gibco, tion [43]. Lipocalin-2 levels in the serum samples were Grand Island, NY, USA), and then added to each well measured using the Duoset murine Lcn-2 ELISA kit with a multiplicity of infection (MOI) of 20:1. The cells (R&D Systems, Minneapolis, MN, USA) according to were incubated at 37  °C for 1  h. Then the cultured cells the manufacturer’s manual. Briefly, blood samples col - were washed twice with DPBS (Gibco, Grand Island, NY, lected by immediate postmortem cardiac puncture were USA), and lysed with 0.1% Triton X-100. The lysates were placed at 4 ℃ overnight, then centrifuged at 4500 rpm for serially diluted and the appropriate dilutions were coated 5  min; the supernatant was transferred to a new 1.5  mL on the LB plates to calculate the number of bacteria. This microtube, and centrifuged again for another 5  min at experiment was performed four times independently, 4500  rpm. The supernatant serum was stored at −20  ℃ with three technical replicates used each time. until use. For lipocalin-2 quantification, the serum sam - ples were diluted properly. Animals and experimental design To select representative time points during the infec- 16S rRNA gene sequencing and analysis tion course for gut microbiota analysis, we firstly deter - The microbiome DNA was extracted from fecal sam - mined the in  vivo S. Derby population dynamic in the ples using the PureLink Microbiome DNA Purification infected mice. The more virulent strain 14T was used in kit (Invitrogen, Carlsbad, CA, USA) according to the this assay. Thirty-five 6-weeks old female C57BL/6J mice manufacturer’s instructions. The quality of the extracted were purchased from Beijing Vital River Laboratory Ani- DNA was checked using a NanoDrop spectrophotometer mals Technology Co., Ltd. The mice were divided into 7 (Thermo Scientific, Carlsbad, CA, USA). The v4 region of groups randomly, each group contains 5 mice. One group the 16S rRNA gene was amplified using the 515F-806R of mice were sacrificed and the spleen, liver, duodenum, primer set and sequenced on an Ion S5 XL platform ileum, colon and cecum tissues were collected one day (Thermo Scientific, Carlsbad, CA, USA) by Novogene, before S. Derby oral administration. Then the remaining China. The raw reads generated by the Ion S5 XL plat- mice were orally administered 2 × 10   CFU (200  μL) of form were quality checked and filtered using an in-house S. Derby 14T strain. The treated mice were sacrificed at pipeline by Novogene. Clean data were further analyzed 0 dpi (4 h after administration), 2 dpi, 4 dpi, 7 dpi, 10 dpi using the Amplicon-based Analysis workflow imple - and 12 dpi, one group of mice at each time point, and the mented in Microbial Genomics module, CLC Genomics organ tissues were collected accordingly. The Salmonella Workbench (ver. 20) with default parameters, in which population in the collected organ tissues were deter- low-quality and chimeric reads were removed, and the mined as described by Zhou et al. [42]. remaining reads were clustered to operational taxonomic To investigate the gut microbiota responses to S. Derby units (OTUs) at 97% similarity using a reference-based infection, thirty 6-weeks old female C57BL/6J mice were (Silva 132 [44]) approach. The generated OTU table was used. The mice were divided randomly into 3 groups with then uploaded to Microbiomeanalyst server for further 10 mice in each group, with 5 mice housed in one cage. analysis [45] with the feature filter step re-set as Mini - Mice were orally administered 2 × 10   CFU (200  μL) of mum count 2, Prevalence in samples (%) 10, percentage S. Derby strain 14T or 14C, or administered an equal vol- in samples (%) 5, and other parameters set as default. ume of 2.5% NaHCO solution to serve as controls. The alpha diversity indices (Shannon and Chao1) and All mice were housed in isolators and kept in a room beta diversity metrics (Bray–Curtis) were calculated with controlled temperature, light, and ventilation. SPF- using Microbiomeanalyst server. Beta diversity met- grade chows (Jiangsu xietong Bioengineering Co., Ltd.) rics were visualized using principal coordinate analysis and sterile water were provided to the mice. The body (PCoA) based on the Bray–Curtis indices, and treatment- weight of each mouse was measured daily during the dependent differences in beta diversity were tested using course of infection, with the baseline weight measured multivariate permutational ANOVA (PERMANOVA) on the day prior to treatment (−1 dpi). The body weight based on the Bray–Curtis similarities. Pairwise com- dynamic of treated mice was calculated as: weight meas- parisons of communities across the three treatments at ured at day n post infection (Dn)/baseline. Fecal samples 0  dpi, 2  dpi and 14  dpi were performed and visualized were collected from all mice on 0 dpi (4 h post infection), using the Heat_tree function in the Metacoder package Yuan et al. Gut Pathogens (2022) 14:6 Page 10 of 12 implemented in MicrobiomeAnalyst server, in which the MicrobiomeAnalyst server. Table S1. The population dynamic of S. Derby differentially abundant taxa are determined by a Wil - in different organs of the orally administrated mice. coxon rank-sum test followed by Benjamini–Hochberg Additional file 2: Table S2. Relative abundance comparison across the three treatments. The differentially abundant taxa were determined at (FDR) correction [46]. family level and labeled accrodingly. Acknowledgements Isolation of fecal lactic acid bacteria strains Not applicable The fecal samples were collected, and homogenized with 0.85% saline solution. Serial tenfold dilution was per- Authors’ contributions YZ and ZP conceived and supervised the project. XY and YZ designed the formed and 100  μL aliquots were plated on MRS agar. experiments, XY, HX, XX performed the experiments, and XY analyzed the Plates were incubated at 37 ℃ for 48  h. Three to five results. YZ, ZP, XY and XJ wrote the paper. All authors read and approved the colonies selected from each plate were streaked at least final manuscript. three times on MRS agar plates, and then colonies were Funding cultured in 10 mL MRS broth. DNA was extracted from This work was supported by the National Key Research and Development Pro- overnight cultures, and 16S rRNA gene was amplified gram Special Project (2018YFD0500501) and the Natural Science Foundation of Jiangsu Province (BK20180911) (Yunzeng Zhang), and the Postgraduate using primer set 27F and 1492R. PCR products were Research and Practice Innovation Program of Jiangsu Province (XKYCX19_147) submitted to Genscript (Nanjing, China) and Sanger (Xiaohui Yuan). sequenced for taxonomy identification. All isolates were sub-cultured in MRS broth and stored at −70  ℃ for Availability of data and materials The 16S sequencing data have been deposited in China National GenBank future experiments. database (CNGBdb) under project ID CNP0001062. Declarations Antagonistic activity of isolated Ligilactobacillus strains against S. Derby 14T and 14C Ethics approval and consent to participate All animal studies were performed in accordance with the Committee on the Antagonistic activity against the two S. Derby strains Ethics of Animal Experiments of Yangzhou University (Approval ID: SYXK [Su] of the isolated Ligilactobacillus strains was measured 2012-0029). using the agar spot method as described by Toure and Consent for publication Koohestani [47, 48] with modifications. Briefly, 10  μL of Not applicable. 24  h culture of a Ligilactobacillus strain was spotted in the middle of the MRS agar plate, and incubated at 37 ℃ Competing interests The authors declare that they have no competing interests. for 24  h. Then the incubated plates were overlaid with 10 mL of LB containing 0.75% agar at 45 ℃, seeded with Author details 1% (v/v) of active overnight cultured of S. Derby strain Jiangsu Co-Innovation Center for Prevention and Control of Important 6 −1 Animal Infectious Diseases and Zoonoses, Yangzhou University, Yangzhou, 14T or 14C (final concentration 10 CFU  mL ), and China. Jiangsu Key Laboratory of Zoonosis, Yangzhou University, Yangzhou, incubated aerobically at 37 ℃ for another 12–16 h. Diam- China. Key Laboratory of Prevention and Control of Biological Hazard Fac- eter of the inhibition zone was measured and recorded. tors (Animal Origin) for Agrifood Safety and Quality, Ministry of Agriculture of China, Yangzhou University, Yangzhou, China. Joint International Research This assay was repeated 3 times, and three technical rep - Laboratory of Agriculture and Agri-Product Safety of the Ministry of Education, licates were used each time. Yangzhou University, Yangzhou, China. Received: 30 July 2021 Accepted: 13 January 2022 Supplementary Information The online version contains supplementary material available at https:// doi. org/ 10. 1186/ s13099- 022- 00480-6. References Additional file 1: Figure S1. Minimum spanning tree analysis of CRISPRS 1. Khan S, Hauptman R, Kelly L. Engineering the microbiome to prevent types for Salmonella Derby. The CRISPR type 38 and type 39 were yellow adverse events: challenges and opportunities. Annu Rev Pharmacol and blue colored, respectively. Figure S2. Rarefaction curve of all samples. Toxicol. 2021;61:159–79. https:// doi. org/ 10. 1146/ annur ev- pharm The x axis represents the sequencing data and the y axis represents the tox- 031620- 031509. OTU numbers in the order of the x axis. Figure S3. Principal coordinate 2. Rogers AWL, Tsolis RM, Baumler AJ. Salmonella versus the Microbiome. analysis showing the beta diversity between treatments, as determined Microbiol Mol Biol Rev. 2021. https:// doi. org/ 10. 1128/ MMBR. 00027- 19. using Bray–Curtis similarities. Results of PERMANOVA are given on each 3. Jacobson A, Lam L, Rajendram M, Tamburini F, Honeycutt J, Pham T, et al. plot; legend at right. Figure S4. The relative abundance comparison of A gut commensal-produced metabolite mediates colonization resistance Prevotella (A), Odoribacter (B), and Citrobacter (C) among the 14T, 14C and to Salmonella infection. Cell Host Microbe. 2018. https:// doi. org/ 10. control mice. The relative abundance of the three genera was significantly 1016/j. chom. 2018. 07. 002. higher in control mice compared with 14T- or 14C-treated mice as deter- 4. Rivera-Chavez F, Zhang LF, Faber F, Lopez CA, Byndloss MX, Olsan EE, mined by Heat_tree function in the Metacoder package implemented in et al. Depletion of butyrate-producing Clostridia from the gut microbiota Y uan et al. Gut Pathogens (2022) 14:6 Page 11 of 12 drives an aerobic luminal expansion of Salmonella. Cell Host Microbe. 23. Kubasova T, Seidlerova Z, Rychlik I. Ecological adaptations of gut micro- 2016;19:443–54. https:// doi. org/ 10. 1016/j. chom. 2016. 03. 004. biota members and their consequences for use as a new generation 5. Litvak Y, Mon KKZ, Nguyen H, Chanthavixay G, Liou M, Velazquez EM, et al. of probiotics. Int J Mol Sci. 2021;22:5471. https:// doi. org/ 10. 3390/ ijms2 Commensal Enterobacteriaceae protect against Salmonella colonization 21154 71. through oxygen competition. Cell Host Microbe. 2019. https:// doi. org/ 10. 24. Bratburd JR, Keller C, Vivas E, Gemperline E, Li LJ, Rey FE, Currie CR. Gut 1016/j. chom. 2018. 12. 003. microbial and metabolic responses to Salmonella enterica serovar Typh- 6. Faber F, Thiennimitr P, Spiga L, Byndloss MX, Litvak Y, Lawhon S, et al. imurium and Candida albicans. Mbio. 2018. https:// doi. org/ 10. 1128/ mBio. Respiration of microbiota-derived 1,2-propanediol drives Salmonella 02032- 18. expansion during colitis. PLoS Pathog. 2017;13: e1006129. https:// doi. org/ 25. Borton MA, Sabag-Daigle A, Wu JK, Solden LM, O’Banion BS, Daly RA, 10. 1371/ journ al. ppat. 10061 29. et al. Chemical and pathogen-induced inflammation disrupt the murine 7. Ng KM, Ferreyra JA, Higginbottom SK, Lynch JB, Kashyap PC, Gopinath S, intestinal microbiome. Microbiome. 2017. https:// doi. org/ 10. 1186/ et al. Microbiota-liberated host sugars facilitate post-antibiotic expansion s40168- 017- 0264-8. of enteric pathogens. Nature. 2013;502:96–9. https:// doi. org/ 10. 1038/ 26. Arguello H, Estelle J, Leonard FC, Crispie F, Cotter PD, O’Sullivan O, et al. natur e12503. Influence of the intestinal microbiota on colonization resistance to Sal- 8. Spiga L, Winter MG, de Carvalho TF, Zhu W, Hughes ER, Gillis CC, et al. An monella and the shedding pattern of naturally exposed pigs. Msystems. oxidative central metabolism enables Salmonella to utilize microbiota- 2019. https:// doi. org/ 10. 1128/ mSyst ems. 00021- 19. derived succinate. Cell Host Microbe. 2017. https:// doi. org/ 10. 1016/j. 27. Stecher B, Chaffron S, Kappeli R, Hapfelmeier S, Freedrich S, Weber TC, chom. 2017. 07. 018. et al. Like will to like: abundances of closely related species can predict 9. Herp S, Brugiroux S, Garzetti D, Ring D, Jochum LM, Beutler M, et al. susceptibility to intestinal colonization by pathogenic and commensal Mucispirillum schaedleri antagonizes Salmonella virulence to protect mice bacteria. PLoS Pathog. 2010. https:// doi. org/ 10. 1371/ journ al. ppat. 10007 against colitis. Cell Host Microbe. 2019. https:// doi. org/ 10. 1016/j. chom. 11. 2019. 03. 004. 28. Arguello H, Estelle J, Zaldivar-Lopez S, Jimenez-Marin A, Carvajal A, 10. Pradhan B, Guha D, Naik AK, Banerjee A, Tambat S, Chawla S, et al. Lopez-Bascon MA, et al. Early Salmonella Typhimurium infection in Probiotics L. acidophilus and B. clausii modulate gut microbiota in Th1- pigs disrupts Microbiome composition and functionality principally and Th2-biased mice to ameliorate Salmonella typhimurium-induced at the ileum mucosa. Sci Rep. 2018;8:7788. https:// doi. org/ 10. 1038/ diarrhea. Probiotics Antimicrob Proteins. 2019. https:// doi. org/ 10. 1007/ s41598- 018- 26083-3. s12602- 018- 9436-5. 29. Bronner DN, Faber F, Olsan EE, Byndloss MX, Sayed NA, Xu GG, et al. 11. Branchu P, Bawn M, Kingsley RA. Genome variation and molecular epide- Genetic ablation of butyrate utilization attenuates gastrointestinal Sal- miology of Salmonella enterica serovar Typhimurium pathovariants. Infect monella disease. Cell Host Microbe. 2018. https:// doi. org/ 10. 1016/j. chom. Immun. 2018. https:// doi. org/ 10. 1128/ IAI. 00079- 18.2018. 01. 004. 12. McWhorter AR, Tearle R, Moyle TS, Chousalkar KK. In vivo passage of Sal- 30. Gantois I, Ducatelle R, Pasmans F, Haesebrouck F, Hautefort I, Thompson monella Typhimurium results in minor mutations in the bacterial genome A, et al. Butyrate specifically down-regulates Salmonella pathogenicity and increases in vitro invasiveness. Vet Res. 2019;50:71. https:// doi. org/ 10. island 1 gene expression. Appl Environ Microbio. 2006;72:946–9. https:// 1186/ s13567- 019- 0688-1.doi. org/ 10. 1128/ Aem. 72.1. 946- 949. 2006. 13. Ramachandran G, Aheto K, Shirtliff ME, Tennant SM. Poor biofilm-forming 31. Sorbara MT, Pamer EG. Interbacterial mechanisms of colonization resist- ability and long-term survival of invasive Salmonella Typhimurium ST313. ance and the strategies pathogens use to overcome them. Mucosal Pathog Dis. 2016. https:// doi. org/ 10. 1093/ femspd/ ftw049. Immunol. 2019;12:1–9. https:// doi. org/ 10. 1038/ s41385- 018- 0053-0. 14. Zheng HJ, Hu YC, Li QC, Tao J, Cai YQ, Wang YN, et al. Subtyping Salmo- 32. Maier L, Vyas R, Cordova CD, Lindsay H, Schmidt TS, Brugiroux S, et al. nella enterica serovar Derby with multilocus sequence typing (MLST ) and Microbiota-derived hydrogen fuels Salmonella Typhimurium invasion of clustered regularly interspaced short palindromic repeats (CRISPRs). Food the gut ecosystem. Cell Host Microbe. 2013;14:641–51. https:// doi. org/ 10. Control. 2017;73:474–84. https:// doi. org/ 10. 1016/j. foodc ont. 2016. 08. 051.1016/j. chom. 2013. 11. 002. 15. Zheng H. CRISPRS molecular subtyping and whole genome sequencing 33. Gagen EJ, Padmanabha J, Denman SE, McSweeney CS. Hydrogenotrophic analysis for Salmonella Derby isolates. Yangzhou: Yangzhou University; culture enrichment reveals rumen Lachnospiraceae and Ruminococcaceae 2017. acetogens and hydrogen-responsive Bacteroidetes from pasture-fed cat- 16. Ferrari RG, Rosario DKA, Cunha-Neto A, Mano SB, Figueiredo EES, Conte tle. FEMS Microbiol Lett. 2015. https:// doi. org/ 10. 1093/ femsle/ fnv104. CA. Worldwide epidemiology of Salmonella serovars in animal-based 34. Casey PG, Gardiner GE, Casey G, Bradshaw B, Lawlor PG, Lynch PB, et al. A foods: a meta-analysis. Appl Environ Microb. 2019. https:// doi. org/ 10. five-strain probiotic combination reduces pathogen shedding and allevi- 1128/ AEM. 00591- 19. ates disease signs in pigs challenged with Salmonella enterica serovar 17. Cai YQ, Tao J, Jiao Y, Fei X, Zhou L, Wang Y, et al. Phenotypic characteristics Typhimurium. Appl Environ Microbiol. 2007;73:1858–63. https:// doi. org/ and genotypic correlation between Salmonella isolates from a slaugh-10. 1128/ AEM. 01840- 06. terhouse and retail markets in Yangzhou. China Int J Food Microbiol. 35. Yang X, Brisbin J, Yu H, Wang Q, Yin F, Zhang Y, et al. Selected lactic 2016;222:56–64. https:// doi. org/ 10. 1016/j. ijfoo dmicro. 2016. 01. 020. acid-producing bacterial isolates with the capacity to reduce Salmonella 18. Hauser E, Hebner F, Tietze E, Helmuth R, Junker E, Prager R, et al. Diversity translocation and virulence gene expression in chickens. PLoS ONE. of Salmonella enterica serovar Derby isolated from pig, pork and humans 2014;9: e93022. https:// doi. org/ 10. 1371/ journ al. pone. 00930 22. in Germany. Int J Food Microbiol. 2011;151:141–9. https:// doi. org/ 10. 36. Hu JL, Yu H, Kulkarni RR, Sharif S, Cui SW, Xie MY, Nie SP, Gong J. Modula- 1016/j. ijfoo dmicro. 2011. 08. 020. tion of cytokine gene expression by selected Lactobacillus isolates in the 19. Zhou ZH, Li JW, Zheng HJ, Jin XC, Shen Y, Lei TY, et al. Diversity of Salmo- ileum, caecal tonsils and spleen of Salmonella-challenged broilers. Avian nella isolates and their distribution in a pig slaughterhouse in Huaian Pathol. 2015;44:463–9. https:// doi. org/ 10. 1080/ 03079 457. 2015. 10867 25. China. Food Control. 2017;78:238–46. https:// doi. org/ 10. 1016/j. foodc ont. 37. Stecher B. The roles of inflammation, nutrient availability and the com- 2017. 02. 064. mensal microbiota in enteric pathogen infection. Microbiol Spectr. 2015. 20. Matiasovic J, Stepanova H, Kudlackova H, Havlickova H, Sisak F, Rychlik I, https:// doi. org/ 10. 1128/ micro biols pec. MBP- 0008- 2014. et al. Immune response of pigs to Salmonella enterica serovar Derby and 38. Rivera-Chavez F, Lopez CA, Baumler AJ. Oxygen as a driver of gut dysbio- Typhimurium infections. Vet Microbiol. 2014;170:284–90. https:// doi. org/ sis. Free Radical Bio Med. 2017;105:93–101. https:// doi. org/ 10. 1016/j. freer 10. 1016/j. vetmic. 2014. 02. 003.adbio med. 2016. 09. 022. 21. Cui S, Li J, Sun Z, Hu C, Jin S, Li F, Guo Y, Ran L, Ma Y. Characterization of 39. Kaiser BLD, Li J, Sanford JA, Kim YM, Kronewitter SR, Jones MB, et al. A Salmonella enterica isolates from infants and toddlers in Wuhan. China J multi-omic view of host–pathogen–commensal interplay in Salmonella- Antimicro Chemo. 2009;63:87–94. https:// doi. org/ 10. 1093/ jac/ dkn452. mediated intestinal infection. PLoS ONE. 2013. https:// doi. org/ 10. 1371/ 22. Velazquez EM, Nguyen H, Heasley KT, Saechao CH, Gil LM, Rogers AWL, journ al. pone. 00671 55. et al. Endogenous Enterobacteriaceae underlie variation in susceptibility 40. Hapfelmeier S. Outrunning Salmonella—the role of endogenous Entero- to Salmonella infection. Nat Microbiol. 2019;4:1057–64. https:// doi. org/ 10. bacteriaceae in variable colonization resistance. Lab Anim. 2019;48:203–4. 1038/ s41564- 019- 0407-8.https:// doi. org/ 10. 1038/ s41684- 019- 0327-5. Yuan et al. Gut Pathogens (2022) 14:6 Page 12 of 12 41. Ganesh BP, Klopfleisch R, Loh G, Blaut M. Commensal Akkermansia mucin- iphila exacerbates gut inflammation in Salmonella Typhimurium-infected gnotobiotic mice. PLoS ONE. 2013. https:// doi. org/ 10. 1371/ journ al. pone. 00749 63. 42. Zhou A, Li J, Xu Z, Ni J, Guo J, Yao Y, et al. Whole-genome comparative and pathogenicity analysis of Salmonella enterica subsp. enterica Serovar Rissen. G3: Genes, Genomes, Genet. 2020. https:// doi. org/ 10. 1534/ g3. 120. 43. Moschen AR, Adolph TE, Gerner RR, Wieser V, Tilg H. Lipocalin-2: a master mediator of intestinal and metabolic inflammation. Trends Endocrinol Metab. 2017;28:388–97. https:// doi. org/ 10. 1016/j. tem. 2017. 01. 003. 44. Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Glock- ner FO. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 2013;41:D590-596. https:// doi. org/ 10. 1093/ nar/ gks12 19. 45. Dhariwal A, Chong J, Habib S, King IL, Agellon LB, Xia J. MicrobiomeAna- lyst: a web-based tool for comprehensive statistical, visual and meta- analysis of microbiome data. Nucleic Acids Res. 2017;45:W180–8. https:// doi. org/ 10. 1093/ nar/ gkx295. 46. Foster Z, Sharpton T, Grünwald N. Metacoder: an R package for visualiza- tion and manipulation of community taxonomic diversity data. PLoS Comput Biol. 2017;13(2): e1005404. https:// doi. org/ 10. 1371/ journ al. pcbi. 10054 04. 47. Toure R, Kheadr E, Lacroix C, Moroni O, Fliss I. Production of antibacterial substances by bifidobacterial isolates from infant stool active against Listeria monocytogenes. J Appl Microbiol. 2003;95:1058–69. https:// doi. org/ 10. 1046/j. 1365- 2672. 2003. 02085.x. 48. Koohestani M, Moradi M, Tajik H, Badali A. Eec ff ts of cell-free superna- tant of Lactobacillus acidophilus LA5 and Lactobacillus casei 431 against planktonic form and biofilm of Staphylococcus aureus. Vet Res Forum. 2018;9:301–6. https:// doi. org/ 10. 30466/ vrf. 2018. 33086. Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in pub- lished maps and institutional affiliations. Re Read ady y to to submit y submit your our re researc search h ? 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Closely related Salmonella Derby strains triggered distinct gut microbiota alteration

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Abstract

Background: Salmonella Derby is one of the most predominant Salmonella serotypes that seriously threatens food safety. This bacterium can be further differentiated to sub-populations with different population sizes; however, whether and how the S. Derby–gut microbiota interactions affect epidemic patterns of S. Derby sub-populations remain largely unknown. Results: We selected two representative strains, 14T and 14C, which represent rarely distributed and prevalent sub-populations of the S. Derby ST40 group, respectively, to address this question using a mouse model. Eec ff ts of oral administration of both strains was monitored for 14 days. Alpha diversity of gut microbiota at early stages of infection (4 h post infection) was higher in 14C-treated mice and lower in 14T-treated mice compared with controls. Strain 14T triggered stronger inflammation responses but with lower pathogen titer in spleen compared with strain 14C at 14 days post infection. Certain known probiotic bacteria that can hinder colonization of Salmonella, such as Bifidobacteriaceae and Akkermansiaceae, exhibited increased relative abundance in 14T-treated mice compared with 14C-treated mice. Our results also demonstrated that Ligilactobacillus strains isolated from gut microbiota showed stronger antagonistic activity against strain 14T compared with strain 14C. Conclusions: We identified how S. Derby infection affected gut microbiota composition, and found that the 14T strain, which represented a rarely distributed S. Derby sub-population, triggered stronger host inflammation responses and gut microbiota disturbance compared with the 14C strain, which represented a prevalent S. Derby sub-population. This study provides novel insights on the impacts of gut microbiota on the epidemic patterns of Salmonella populations. Keywords: Salmonella Derby, Gut microbiota, Inter-strain variation Background gut microbiota, particularly certain keystone microor- Understanding the interactions between gut microbiota ganisms inside the microbiota, play an important role in and Salmonella is critical to managing and preventing the Salmonella colonization and infection process, and infection caused by Salmonella through microbiome the colonization and infection process may be negatively engineering approaches such as probiotic administra- or positively regulated by the microbiota [3–8, 22]. For tion [1, 2]. Increasing evidence has demonstrated that instance, Lactobacillus acidophilus and Mucispirillum schaedleri are proven to ameliorate S. Typhimurium- induced diarrhea and inflammation [9, 10]. Conversely, *Correspondence: zmpan@yzu.edu.cn; yzzhang@yzu.edu.cn certain saccharolytic bacteria, such as Bacteroides the- Jiangsu Co-Innovation Center for Prevention and Control of Important taiotaomicron, can confer advantages to S. Typhimurium Animal Infectious Diseases and Zoonoses, Yangzhou University, during infection by producing 1,2-propanediol, which Yangzhou, China Full list of author information is available at the end of the article serves as an electron acceptor to promote respiratory © The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. The Creative Commons Public Domain Dedication waiver (http:// creat iveco mmons. org/ publi cdoma in/ zero/1. 0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Yuan et al. Gut Pathogens (2022) 14:6 Page 2 of 12 growth of the pathogen [6]. These findings have shown the most predominant population, and the ST40 group promising potential in Salmonella management. How- was further differentiated into sub-populations with ever, the majority of our current knowledge on the inter- distinct population sizes using a very high-resolution actions between Salmonella and gut microbiota comes CRISPR-typing method [14, 15]. For example, our labo- from studies on a single well-characterized strain, such ratory collected 369 ST40-affiliated strains from multi - as S. Typhimurium ATCC 14028, or from only a few Sal- ple sites in Jiangsu province during several years. These monella serotypes including S. Typhimurium. Little is strains were differentiated into 40 sub-populations based known about how other Salmonella serotypes interact on the CRISPR-typing method. Certain sub-populations, with gut microbiota and the consequences of the interac- such as CRISPR-type 38, were found to be present in tions on the epidemic of the pathogens, although many many locations and persisted throughout the sample serotypes have caused dramatic economical losses and collection course, whereas some sub-populations were threatened food safety and public health. Recent studies rarely identified during this long-term epidemiological have demonstrated that strains affiliated with the same study (e.g., CRISPR-type 39 contained only one strain) Salmonella serotype can also exhibit distinct inter-strain (Additional file  1: Figure S1) [14, 15]. In the current variations on epidemic prevalence, pathogenicity, and study, we selected two representative strains, 14T (the risk to food safety, etc. [11–15]. However, the role of gut sole strain in CRISPR-type 39) and 14C (a representative microbiota–Salmonella interactions on the observed strain of CRISPR-type 38 strain group), and investigated epidemic pattern differences as well as other variations the conserved and specifically altered patterns of gut among strains that harbor conserved genomic back- microbiota triggered by the two strains. grounds (i.e., strains from same serotype or even same sequence type (ST) scheme) remain elusive. Here, we Results compared the interaction patterns between gut micro- S. Derby 14T and 14C exhibited distinct cellular adhesion biota and two representative S. Derby strains that were ability and triggered significantly different host selected from two S. Derby sub-populations with distinct inflammation response population sizes (rarely isolated vs. frequently isolated in In our previous study, we isolated 369 S. Derby ST40 our multi-site, long-term epidemic investigation study) strains in Jiangsu, China during 2011–2016, and sub- to address these questions. typed these strains to 40 sub-populations using a CRISPR Recent epidemic studies have demonstrated that S. typing profiling analysis [14, 15]. We selected representa- Derby has become one of the predominant Salmonella tive strains from each sub-population and determined serovars isolated from pork samples and humans globally host responses to pathogen infection using the mouse [16–18]. For instance, around 27% of pork samples col- model. Interestingly, we observed that two closely related lected from China were reported to be contaminated by strains, 14T and 14C, showed distinct cellular adhesion S. Derby [17]. S. Derby causes long-term asymptomatic ability and triggered significantly different host inflam - infection in pigs, and can be released from the gastro- mation response (Fig. 1). Of note, 14T was the sole strain intestinal tract during the slaughtering process, which representing the CRISPR type 39, while 14C was a rep- is probably the main cause of the high contamination resentative strain from a long-term existing sub-popu- rate in the pork samples [19, 20]. More importantly, S. lation CRISPR type 38 that contained multiple strains Derby has become one of the most common Salmonella isolated from 2011–2015 (Additional file  1: Figure S1) serotypes identified in diarrheal patients in China, caus - [15]. Strain 14C exhibited significantly higher epithe - ing heightened interest in the pig farming industry to lia cell adhesion than strain 14T (19. 26 ± 4.14% for 14C eradicate this pathogen [21]. Strains affiliated with the S. and 14.94 ± 3.41% for 14T, mean ± SE, four independent Derby serotype have been further differentiated to ST- biological replicates, Wilcoxon signed-rank test, p < 0.05) types with the multilocus sequence typing method [14]. (Fig.  1A). When determined at 14  days post infection Of the identified S. Derby strains isolated from the pork (dpi), the bacterial titer in spleen of the 14C-adminis- production chains in China, ST40-affiliated strains were trated mice was higher, although not significantly higher, (See figure on next page.) Fig. 1 A Adhesion rates of Salmonella Derby 14T and 14C to MC 38 cells, Wilcoxon signed-rank test, *p < 0.05, error bars represent SE from mean, four independent biological replicates are included, and three technical replicates were included for each biological replicate. B Bacterial titers of 14T (n = 10) and 14C (n = 10) in spleen. BD, below the detection limit. C Quantification of lipocalin-2 level in serum at 14 days post infection among treatments (n = 9 for 14T and 14C treatments and n = 10 for control group), one-way ANOVA with post-hoc Tukey HSD test, *p < 0.05. D Body weight of mice at different time points among treatments (n = 10 for 14T and 14C treatments and n = 9 for control group). The body weight difference between 14T and 14C treatments were determined using one-way ANOVA with post-hoc Duncan test, with significant differences were labeled with + (p < 0.05) Y uan et al. Gut Pathogens (2022) 14:6 Page 3 of 12 Fig. 1 (See legend on previous page.) Yuan et al. Gut Pathogens (2022) 14:6 Page 4 of 12 than that of the 14T-administrated mice (Mann Whit- 14T and 14C groups was significantly higher compared ney test, p > 0.05) (Fig.  1B). Interestingly, both 14T- and with the control group at 14  dpi, suggested that the S. 14C-treated mice exhibited higher Lipocalin-2 lev- Derby treatment dramatically increased the species rich- els compared with control, and those treated with 14T ness of the microbial community, while the microbial exhibited significantly stronger inflammation response diversity was not significantly different among the three compared with 14C (one-way ANOVA with post-hoc groups as suggested by the Shannon index (Fig. 2C). Tukey HSD test, p > 0.05) (Fig.  1C). Furthermore, we The beta diversity results showed that the 14T adminis - found that the mice treated with 14T and 14C gained less tration triggered dramatical microbial community altera- body weight compared with the control mice at several tion at 0 dpi (PERMANOVA, p < 0.05), while the influence time points (one-way ANOVA with post-hoc Duncan of 14C administration on the gut microbial community test, p < 0.05), and the result also suggested 14T-treated structure was not significant (PERMANOVA, p > 0.05) mice gained less body weight than the 14C-treated mice (Additional file  1: Figure S3). As a result, the community at 2 dpi and 3 dpi, despite the difference was not signifi - structure between the 14T and 14C groups differed sig - cant (Fig. 1D). nificantly (PERMANOVA, p < 0.005) (Additional file  1: Figure S3). The community structure of the 14T-treated Strains 14T and 14C perturbed the gut microbiota mice was significantly different from that of the control in different manners mice at 2  dpi (PERMANOVA, p < 0.05), while the com- To reveal the roles of gut microbiota on the observed dif- munity structure difference was not significant between ferent host inflammation response as well as other dif - 14C and control groups or 14T and 14C groups. No sig- ferences triggered by the two S. Derby strains, we sought nificant community structure difference was observed to select representative time points in the infection among the three groups at 14  dpi (PERMANOVA, course based on the in vivo S. Derby population dynamic p > 0.05) (Additional file  1: Figure S3). Taken together, (Additional file  1: Table  S1) for gut microbiota compari- these results suggested that 14C administration did not son analysis. Finally, we select three representative time altered overall structure of the gut microbiota during the points: 0  dpi (approximately 4  h post infection when infection course, while the community structure was sig- high population of S. Derby strains have existed in the nificantly altered by the 14T strain shortly after admin - gut), 2  dpi (S. Derby has successfully invaded the spleen istrated, and then the influence of 14T on the overall and liver), and 14  dpi (majority of the invading S. Derby microbial community was mostly eliminated at 14 dpi. strains have been eliminated from the gut), and collected Through group-wise comparisons, we observed that the fecal samples for 16S rDNA V4 region sequencing several taxa, such as Enterobacteriaceae, exhibited con- analysis. sistent dynamic alteration in relative abundance in both A total of 5,446,132 high quality reads were gener- 14T and 14C groups compared with controls (deter- ated from 87 fecal samples, and the average number of mined by the Heat_tree function in Metacoder package sequences per sample was 62,599 (SD, 6308), with high- implemented in MicrobiomeAnalyst, adjusted p < 0.05, est number 72,646 and lowest number 33,869 per sample. same herein) (Fig.  3 and Additional file  2: Table S2). The These sequenced were trimmed, filtered and clustered relative abundance increases of Enterobacteriaceae in into 1491 Operational Taxonomic Units (OTUs). The 14T and 14C groups at 0 dpi were mainly contributed by rarefaction curve demonstrated that the OTU number the administrated S. Derby strains (accounting for 70.8% increased gradually and tended to be flat as the depth of of the identified Enterobacteriaceae), while the contri - sequencing increased (Additional file  1: Figure S2), which bution of the administrated strains to the Enterobacte- suggested that our sequencing had nearly saturated and riaceae composition was small (< 1%) at 2 dpi and 14 dpi. the abundance results could reflect the bacterial diversity Interestingly, quite a few taxa were found to exhibit in the samples confidently. distinct alteration in relative abundance for 14T- and The alpha diversity of gut microbiota in 14T- and 14C-treated mice compared with control ones (Fig. 3 and 14C- administrated mice was measured using Shan- Additional file  2: Table S2). At 0 dpi, several taxa affiliated non and Chao1 indices. Both indices suggested that the with Clostridiales (an order affiliated with Firmicutes) microbial diversity and richness was significantly lower exhibited significantly increased relative abundance in in the 14T-treated mice than in the 14C-treated mice at 14C-treated mice, but not in the 14T-treated mice com- 0  dpi (one-way ANOVA with post-hoc Tukey HSD test, pared with the control. At the same time, the relative p < 0.005) (Fig.  2A), with the difference diminishing over abundance of Rikenellaceae and Prevotellaceae, both of time. No significant differences among the 14T, 14C which are affiliated with Bacteroidetes, was dramatically and control groups were observed when tested at 2  dpi increased in 14T-treated mice, but not in 14C-treated (ANOVA, p > 0.05) (Fig.  2B). The Chao1 index of both mice, compared with the control. Significant differences Y uan et al. Gut Pathogens (2022) 14:6 Page 5 of 12 Fig. 2 Shannon and Chaol diversity indices of 14T, 14C, and untreated control mice at A 0 days post infection (dpi), B 2 dpi, and C 14 dpi. Mean values are denoted as black diamonds. *p < 0.05, **p < 0.01, according to one-way ANOVA with post-hoc Tukey HSD test. At each timepoint, ten samples from 14T and 14C treatments, and nine samples from the control group were included Yuan et al. Gut Pathogens (2022) 14:6 Page 6 of 12 Fig. 3 Heat tree of differentially abundant taxa in gut microbiota classified at family level (panel A, 0 dpi; panel B, 2 dpi; panel C, 14 dpi). The color of each taxon represents the log2 ratio of median proportion of reads observed in a given treatment. Only significantly differentially abundant taxa were labeled, which were determined by Heat_tree function in the Metacoder package implemented in MicrobiomeAnalyst server. Width of nodes and edges denotes the relative abundance of the given taxa. Ten samples from 14T and 14C treatments, and nine samples from the control group were included in this analysis Y uan et al. Gut Pathogens (2022) 14:6 Page 7 of 12 in relative abundance of Firmicutes and Bacteroidetes between the 14T and 14C groups were also observed (Fig.  3A and Additional file  2: Table  S2). Several taxa that are not affiliated with Firmicutes and Bacteroidetes, such as Burkholderiaceae (affiliated with Proteobacteria) and Bifidobacteriaceae (affiliated with Actinobacteria), were observed to exhibit differential relative abundance between 14C and control or 14T and control groups at 2 dpi, with little overlap observed between the majority of these differentially abundant taxa in the two group-wise comparisons (Fig.  3B and Additional file  2: Table S2). Of note, the relative abundance of Lactobacillaceae, Bifido - bacteriaceae, Enterobacteriaceae, and Akkermansiaceae, were found to be higher in the 14T group compared with the 14C group (Fig.  3B and Additional file  2: Table  S2). At 14  dpi, the bacterial community of the 14T- and 14C-treated mice trended to show similar composition with many fewer differentially abundant taxa observed compared with 2  dpi (Figs.  3B and C and Additional file  2: Table S2); however, the community in both groups diverged from that of the control group, suggesting that the infection of two strains caused dysbiosis of the gut microbiota, although the majority of the infected S. Derby strains were eliminated by 14 dpi. Strains 14T and 14C exhibited different response Fig. 4 A Antagonistic activity of Lactobacillus murine isolates against to mice‑originated antagonistic Ligilactobacillus strains Salmonella Derby 14T (left) and 14C (right). B Diameter of the Through microbiota profiling analysis, we found that inhibition zone of Lactobacillus murine isolates against 14T and 14C, Lactobacillaceae exhibited increased relative abun- shown as mean ± SD, n = 3 dance in both 14T- and 14C-treated mice compared with the control mice at 2  dpi; moreover, this taxon consist- ently exhibited higher, although not significantly, rela - tive abundance in the 14T group than in the 14C group Discussion during the course of infection (Fig.  3 and Additional In this study, we investigated gut microbiota altera- file  2: Table  S2). Lactobacillus (a single genus based on tion patterns triggered by infection with two S. Derby Silva 132 database, has been reclassified to several gen - strains from the same ST40 group but with distinct epi- era since 2020) was the most predominated genus affili - demic patterns (i.e., rarely-distributed vs. prevalent). Our ated with Lactobacillaceae, and accounted for 99.8% of results demonstrated that infection with S. Derby strains the accumulated relative abundance of Lactobacillaceae. triggered distinct microbiota responses compared with Given that many members affiliated with Lactobacillus that of well-studied S. Typhimurium. The diversity of gut are commonly known as probiotic bacteria [23], the Lac- microbiota was increased in S. Derby-treated mice, which tobacillus bacteria were isolated from the fecal samples was opposite compared with the S. Typhimurium-treated of treated mice using MRS medium. Two representative mice [24–26]. High diversity of gut microbiota can ben- isolates, L2 and L19, both of which were affiliated with efit the host by providing nutrients as well as resisting Ligilactobacillus murinus, were obtained. Interestingly, against pathogen colonization; for instance, higher com- both L2 and L19 strains exhibited stronger, although not plexity in gut microbiota usually results in increased pro- significantly, inhibitory effects on growth of S. Derby 14T tection against Salmonella-induced gut inflammation compared with 14C (t-test, p > 0.05 for both strains). The [27]. Certain consistent altered patterns were observed zone of inhibition against 14T and 14C was 1.0 ± 0.16 cm in the gut microbiota of mice infected with S. Derby and (mean ± SD) and 0.78 ± 0.14 cm (28% higher) for L2, and S. Typhimurium, such as reduced relative abundance of the inhibition zone against 14T was 0.49 ± 0.07  cm and Prevotella and Odoribacter [10]; however, the taxonomic the value against 14C was 0.44 ± 0.12 cm (10% higher) for composition was strikingly different. For example, infec - L19 strain, respectively (Fig. 4). tion with S. Typhimurium significantly increased the Yuan et al. Gut Pathogens (2022) 14:6 Page 8 of 12 relative abundance of Citrobacter, a potentially patho- 14C-treated mice (Fig.  3). Lactobacillaceae may reduce genic bacteria [25, 28], whereas infection with both 14T Salmonella shedding and translocation to liver and and 14C strains decreased the relative abundance of Cit- spleen [34–37]. Enterobacteriaceae, population of which robacter (Additional file  1: Figure S4). The microbiota was increased as driven by the elevated oxygen level in composition is strongly associated with the susceptibility the gut due to enteric pathogens infection [38], were to enteric pathogen infection [27, 29]. The differences in reported to restrict Salmonella expansion and infection microbiota alteration between the S. Typhimurium- and by competing for iron, oxygen and other resources with S. Derby-infected mice and its association with the con- this pathogen [24, 39, 40]. Akkermansiaceae are known sequences of the two serotypes on the hosts need to be to exacerbate inflammation in S. Typhimurium-infected further explored. gnotobiotic mice [41]. Furthermore, our results demon- Interestingly, although strains S. Derby 14T and 14C strated that identical microbiota members can exhibit used in this study shared highly conserved genomic con- different direct-contact antagonistic activities against tents [14, 15], the host symptoms and gut microbiota 14T and 14C (Fig.  4). Thus, we speculate that the more alteration patterns mediated by infection with the two aggressive 14T strain triggered higher levels of host and strains were distinct (Figs.  1, 2, 3). Strain 14T treatment microbiota immune responses, which hindered 14T from triggered a stronger inflammation response compared translocating to spleen and liver, resulting in lower 14T with 14C, but a smaller spleen-translocated 14T popu- in vivo populations and restricted distribution compared lation was observed. This observation was in concert with 14C. with the host cell adhesion results in that fewer 14T cells adhered to MC 38 cells compared with 14C (Fig. 1). Low- Conclusion grade inflammation may benefit 14C, possibly by mak - Overall, our study revealed distinct and conserved host ing a trade-off between inflammation and dissemination gut microbiota response patterns triggered by the two S. to and/or survival in the liver and spleen [29]. Of note, Derby strains, 14T and 14C, which represented two dis- the host inflammation response was measured based on tinct epidemic sub-populations with conserved genomic the Lipocalin-2 assay in this study, and the result might background. Colonization resistance conferred by the represent only a part of the immune response. Shortly microbiota helps the host resist a variety of pathogens after intragastric administration (4 h after treatment), the including Salmonella. Elucidating the differences and microbial diversity of 14C-treated mice was increased, conservations of gut microbiota–Salmonella interactions whereas that of 14T-treated mice was decreased (Fig.  2). at serotype- and strain-level will help us understand the Higher complexity of gut microbiota is believed to be epidemic differences in Salmonella, and benefit the devel - associated with increased protection against Salmonella- opment of microbiome engineering-based therapies. induced gut inflammation [27]. At 0  dpi, Enterobacte - riaceae exhibited increased relative abundance in both Methods 14T and 14C treated mice compared with the control Salmonella strains mice at 0 dpi, which was mainly attributed to the admin- Two representative S. Derby strains, 14T-T8N3 and istrated S. Derby strains; however, the high population 14C-D14P2 (S. Derby 14T and 14C herein), were used in of S. Derby in the gut microbiota was temporary and this study. The two strains were isolated from pork sam - represented a very minute fraction of the gut micro- ples collected in Yangzhou, Jiangsu, China, and affiliated biota at 2  dpi and 14  dpi. Increased relative abundance with Salmonella sequence type (ST) 40 by multilocus of Clostridiales in 14C-treated mice, and higher rela- sequence typing analysis, but represented two sub-pop- tive abundance of Rikenellaceae and Prevotellaceae in ulations with different population sizes (14T from the 14T-treated mice were also observed at 0  dpi. Members distribution-restricted CRISPR-type 39 and 14C from of Clostridiales are known as short chain fatty acids pro- the prevalent CRISPR-type 38 sub-populations) (Addi- ducers, which can down-regulate the expression of viru- tional file  1: Figure S1) [14, 15]. The strains were grown in lence genes of Salmonella, as well as limit O availability Luria–Bertani (LB) broth with shaking at 37 ℃ overnight, in the lumen of the gut, together restricting the expan- and the bacterial population was adjusted to OD = 1.0 sion of Salmonella [4, 30, 31]. In contrast, Rikenellaceae with PBS, then centrifuged and suspended with 2.5% and Prevotellaceae produce hydrogen, which may benefit NaHCO solution for intragastric administration. Salmonella in terms of expansion and colonization at the initial infection stage [32, 33]. At 2 dpi, the relative abun- Cellular adhesion assays dance of Lactobacillaceae, Bifidobacteriaceae, Entero- The MC38 (Mouse colon cancer epithelial cell) cell line bacteriaceae, and Akkermansiaceae, were found to be was purchased from Hunan Fenghui Biotechnology Co., dramatically higher in 14T-treated mice compared with Ltd. (Hunan, China) (catalog no. CL0203). S. Derby 14T Y uan et al. Gut Pathogens (2022) 14:6 Page 9 of 12 and 14C strains were cultured in LB medium at 37  °C 2  dpi, and 14  dpi. Fecal pellets collected from individual for 16  h, and then diluted into a new LB medium and mouse were measured and stored at −70 ℃ until further incubated to OD = 1.0. The MC38 cells were seeded processing. into 24-well plates with 4 × 10 cells per well, and cul- tured overnight at 37  °C with 5% CO . A total of 1  mL Inflammation marker quantification of bacterial culture was collected and washed twice with Lipocalin-2 is known as a good biomarker of inflamma - Dulbecco’s Modified Eagle Medium (DMEM) (Gibco, tion [43]. Lipocalin-2 levels in the serum samples were Grand Island, NY, USA), and then added to each well measured using the Duoset murine Lcn-2 ELISA kit with a multiplicity of infection (MOI) of 20:1. The cells (R&D Systems, Minneapolis, MN, USA) according to were incubated at 37  °C for 1  h. Then the cultured cells the manufacturer’s manual. Briefly, blood samples col - were washed twice with DPBS (Gibco, Grand Island, NY, lected by immediate postmortem cardiac puncture were USA), and lysed with 0.1% Triton X-100. The lysates were placed at 4 ℃ overnight, then centrifuged at 4500 rpm for serially diluted and the appropriate dilutions were coated 5  min; the supernatant was transferred to a new 1.5  mL on the LB plates to calculate the number of bacteria. This microtube, and centrifuged again for another 5  min at experiment was performed four times independently, 4500  rpm. The supernatant serum was stored at −20  ℃ with three technical replicates used each time. until use. For lipocalin-2 quantification, the serum sam - ples were diluted properly. Animals and experimental design To select representative time points during the infec- 16S rRNA gene sequencing and analysis tion course for gut microbiota analysis, we firstly deter - The microbiome DNA was extracted from fecal sam - mined the in  vivo S. Derby population dynamic in the ples using the PureLink Microbiome DNA Purification infected mice. The more virulent strain 14T was used in kit (Invitrogen, Carlsbad, CA, USA) according to the this assay. Thirty-five 6-weeks old female C57BL/6J mice manufacturer’s instructions. The quality of the extracted were purchased from Beijing Vital River Laboratory Ani- DNA was checked using a NanoDrop spectrophotometer mals Technology Co., Ltd. The mice were divided into 7 (Thermo Scientific, Carlsbad, CA, USA). The v4 region of groups randomly, each group contains 5 mice. One group the 16S rRNA gene was amplified using the 515F-806R of mice were sacrificed and the spleen, liver, duodenum, primer set and sequenced on an Ion S5 XL platform ileum, colon and cecum tissues were collected one day (Thermo Scientific, Carlsbad, CA, USA) by Novogene, before S. Derby oral administration. Then the remaining China. The raw reads generated by the Ion S5 XL plat- mice were orally administered 2 × 10   CFU (200  μL) of form were quality checked and filtered using an in-house S. Derby 14T strain. The treated mice were sacrificed at pipeline by Novogene. Clean data were further analyzed 0 dpi (4 h after administration), 2 dpi, 4 dpi, 7 dpi, 10 dpi using the Amplicon-based Analysis workflow imple - and 12 dpi, one group of mice at each time point, and the mented in Microbial Genomics module, CLC Genomics organ tissues were collected accordingly. The Salmonella Workbench (ver. 20) with default parameters, in which population in the collected organ tissues were deter- low-quality and chimeric reads were removed, and the mined as described by Zhou et al. [42]. remaining reads were clustered to operational taxonomic To investigate the gut microbiota responses to S. Derby units (OTUs) at 97% similarity using a reference-based infection, thirty 6-weeks old female C57BL/6J mice were (Silva 132 [44]) approach. The generated OTU table was used. The mice were divided randomly into 3 groups with then uploaded to Microbiomeanalyst server for further 10 mice in each group, with 5 mice housed in one cage. analysis [45] with the feature filter step re-set as Mini - Mice were orally administered 2 × 10   CFU (200  μL) of mum count 2, Prevalence in samples (%) 10, percentage S. Derby strain 14T or 14C, or administered an equal vol- in samples (%) 5, and other parameters set as default. ume of 2.5% NaHCO solution to serve as controls. The alpha diversity indices (Shannon and Chao1) and All mice were housed in isolators and kept in a room beta diversity metrics (Bray–Curtis) were calculated with controlled temperature, light, and ventilation. SPF- using Microbiomeanalyst server. Beta diversity met- grade chows (Jiangsu xietong Bioengineering Co., Ltd.) rics were visualized using principal coordinate analysis and sterile water were provided to the mice. The body (PCoA) based on the Bray–Curtis indices, and treatment- weight of each mouse was measured daily during the dependent differences in beta diversity were tested using course of infection, with the baseline weight measured multivariate permutational ANOVA (PERMANOVA) on the day prior to treatment (−1 dpi). The body weight based on the Bray–Curtis similarities. Pairwise com- dynamic of treated mice was calculated as: weight meas- parisons of communities across the three treatments at ured at day n post infection (Dn)/baseline. Fecal samples 0  dpi, 2  dpi and 14  dpi were performed and visualized were collected from all mice on 0 dpi (4 h post infection), using the Heat_tree function in the Metacoder package Yuan et al. Gut Pathogens (2022) 14:6 Page 10 of 12 implemented in MicrobiomeAnalyst server, in which the MicrobiomeAnalyst server. Table S1. The population dynamic of S. Derby differentially abundant taxa are determined by a Wil - in different organs of the orally administrated mice. coxon rank-sum test followed by Benjamini–Hochberg Additional file 2: Table S2. Relative abundance comparison across the three treatments. The differentially abundant taxa were determined at (FDR) correction [46]. family level and labeled accrodingly. Acknowledgements Isolation of fecal lactic acid bacteria strains Not applicable The fecal samples were collected, and homogenized with 0.85% saline solution. Serial tenfold dilution was per- Authors’ contributions YZ and ZP conceived and supervised the project. XY and YZ designed the formed and 100  μL aliquots were plated on MRS agar. experiments, XY, HX, XX performed the experiments, and XY analyzed the Plates were incubated at 37 ℃ for 48  h. Three to five results. YZ, ZP, XY and XJ wrote the paper. All authors read and approved the colonies selected from each plate were streaked at least final manuscript. three times on MRS agar plates, and then colonies were Funding cultured in 10 mL MRS broth. DNA was extracted from This work was supported by the National Key Research and Development Pro- overnight cultures, and 16S rRNA gene was amplified gram Special Project (2018YFD0500501) and the Natural Science Foundation of Jiangsu Province (BK20180911) (Yunzeng Zhang), and the Postgraduate using primer set 27F and 1492R. PCR products were Research and Practice Innovation Program of Jiangsu Province (XKYCX19_147) submitted to Genscript (Nanjing, China) and Sanger (Xiaohui Yuan). sequenced for taxonomy identification. All isolates were sub-cultured in MRS broth and stored at −70  ℃ for Availability of data and materials The 16S sequencing data have been deposited in China National GenBank future experiments. database (CNGBdb) under project ID CNP0001062. Declarations Antagonistic activity of isolated Ligilactobacillus strains against S. Derby 14T and 14C Ethics approval and consent to participate All animal studies were performed in accordance with the Committee on the Antagonistic activity against the two S. Derby strains Ethics of Animal Experiments of Yangzhou University (Approval ID: SYXK [Su] of the isolated Ligilactobacillus strains was measured 2012-0029). using the agar spot method as described by Toure and Consent for publication Koohestani [47, 48] with modifications. Briefly, 10  μL of Not applicable. 24  h culture of a Ligilactobacillus strain was spotted in the middle of the MRS agar plate, and incubated at 37 ℃ Competing interests The authors declare that they have no competing interests. for 24  h. Then the incubated plates were overlaid with 10 mL of LB containing 0.75% agar at 45 ℃, seeded with Author details 1% (v/v) of active overnight cultured of S. Derby strain Jiangsu Co-Innovation Center for Prevention and Control of Important 6 −1 Animal Infectious Diseases and Zoonoses, Yangzhou University, Yangzhou, 14T or 14C (final concentration 10 CFU  mL ), and China. Jiangsu Key Laboratory of Zoonosis, Yangzhou University, Yangzhou, incubated aerobically at 37 ℃ for another 12–16 h. Diam- China. Key Laboratory of Prevention and Control of Biological Hazard Fac- eter of the inhibition zone was measured and recorded. tors (Animal Origin) for Agrifood Safety and Quality, Ministry of Agriculture of China, Yangzhou University, Yangzhou, China. Joint International Research This assay was repeated 3 times, and three technical rep - Laboratory of Agriculture and Agri-Product Safety of the Ministry of Education, licates were used each time. Yangzhou University, Yangzhou, China. Received: 30 July 2021 Accepted: 13 January 2022 Supplementary Information The online version contains supplementary material available at https:// doi. org/ 10. 1186/ s13099- 022- 00480-6. References Additional file 1: Figure S1. Minimum spanning tree analysis of CRISPRS 1. Khan S, Hauptman R, Kelly L. Engineering the microbiome to prevent types for Salmonella Derby. The CRISPR type 38 and type 39 were yellow adverse events: challenges and opportunities. Annu Rev Pharmacol and blue colored, respectively. Figure S2. Rarefaction curve of all samples. Toxicol. 2021;61:159–79. https:// doi. org/ 10. 1146/ annur ev- pharm The x axis represents the sequencing data and the y axis represents the tox- 031620- 031509. OTU numbers in the order of the x axis. Figure S3. Principal coordinate 2. Rogers AWL, Tsolis RM, Baumler AJ. Salmonella versus the Microbiome. analysis showing the beta diversity between treatments, as determined Microbiol Mol Biol Rev. 2021. https:// doi. org/ 10. 1128/ MMBR. 00027- 19. using Bray–Curtis similarities. Results of PERMANOVA are given on each 3. Jacobson A, Lam L, Rajendram M, Tamburini F, Honeycutt J, Pham T, et al. plot; legend at right. Figure S4. The relative abundance comparison of A gut commensal-produced metabolite mediates colonization resistance Prevotella (A), Odoribacter (B), and Citrobacter (C) among the 14T, 14C and to Salmonella infection. Cell Host Microbe. 2018. https:// doi. org/ 10. control mice. The relative abundance of the three genera was significantly 1016/j. chom. 2018. 07. 002. higher in control mice compared with 14T- or 14C-treated mice as deter- 4. Rivera-Chavez F, Zhang LF, Faber F, Lopez CA, Byndloss MX, Olsan EE, mined by Heat_tree function in the Metacoder package implemented in et al. Depletion of butyrate-producing Clostridia from the gut microbiota Y uan et al. Gut Pathogens (2022) 14:6 Page 11 of 12 drives an aerobic luminal expansion of Salmonella. Cell Host Microbe. 23. Kubasova T, Seidlerova Z, Rychlik I. Ecological adaptations of gut micro- 2016;19:443–54. https:// doi. org/ 10. 1016/j. chom. 2016. 03. 004. biota members and their consequences for use as a new generation 5. Litvak Y, Mon KKZ, Nguyen H, Chanthavixay G, Liou M, Velazquez EM, et al. of probiotics. Int J Mol Sci. 2021;22:5471. https:// doi. org/ 10. 3390/ ijms2 Commensal Enterobacteriaceae protect against Salmonella colonization 21154 71. through oxygen competition. Cell Host Microbe. 2019. https:// doi. org/ 10. 24. Bratburd JR, Keller C, Vivas E, Gemperline E, Li LJ, Rey FE, Currie CR. Gut 1016/j. chom. 2018. 12. 003. microbial and metabolic responses to Salmonella enterica serovar Typh- 6. Faber F, Thiennimitr P, Spiga L, Byndloss MX, Litvak Y, Lawhon S, et al. imurium and Candida albicans. Mbio. 2018. https:// doi. org/ 10. 1128/ mBio. Respiration of microbiota-derived 1,2-propanediol drives Salmonella 02032- 18. expansion during colitis. PLoS Pathog. 2017;13: e1006129. https:// doi. org/ 25. Borton MA, Sabag-Daigle A, Wu JK, Solden LM, O’Banion BS, Daly RA, 10. 1371/ journ al. ppat. 10061 29. et al. Chemical and pathogen-induced inflammation disrupt the murine 7. Ng KM, Ferreyra JA, Higginbottom SK, Lynch JB, Kashyap PC, Gopinath S, intestinal microbiome. Microbiome. 2017. https:// doi. org/ 10. 1186/ et al. Microbiota-liberated host sugars facilitate post-antibiotic expansion s40168- 017- 0264-8. of enteric pathogens. Nature. 2013;502:96–9. https:// doi. org/ 10. 1038/ 26. Arguello H, Estelle J, Leonard FC, Crispie F, Cotter PD, O’Sullivan O, et al. natur e12503. Influence of the intestinal microbiota on colonization resistance to Sal- 8. Spiga L, Winter MG, de Carvalho TF, Zhu W, Hughes ER, Gillis CC, et al. An monella and the shedding pattern of naturally exposed pigs. Msystems. oxidative central metabolism enables Salmonella to utilize microbiota- 2019. https:// doi. org/ 10. 1128/ mSyst ems. 00021- 19. derived succinate. Cell Host Microbe. 2017. https:// doi. org/ 10. 1016/j. 27. Stecher B, Chaffron S, Kappeli R, Hapfelmeier S, Freedrich S, Weber TC, chom. 2017. 07. 018. et al. Like will to like: abundances of closely related species can predict 9. Herp S, Brugiroux S, Garzetti D, Ring D, Jochum LM, Beutler M, et al. susceptibility to intestinal colonization by pathogenic and commensal Mucispirillum schaedleri antagonizes Salmonella virulence to protect mice bacteria. PLoS Pathog. 2010. https:// doi. org/ 10. 1371/ journ al. ppat. 10007 against colitis. Cell Host Microbe. 2019. https:// doi. org/ 10. 1016/j. chom. 11. 2019. 03. 004. 28. Arguello H, Estelle J, Zaldivar-Lopez S, Jimenez-Marin A, Carvajal A, 10. Pradhan B, Guha D, Naik AK, Banerjee A, Tambat S, Chawla S, et al. Lopez-Bascon MA, et al. Early Salmonella Typhimurium infection in Probiotics L. acidophilus and B. clausii modulate gut microbiota in Th1- pigs disrupts Microbiome composition and functionality principally and Th2-biased mice to ameliorate Salmonella typhimurium-induced at the ileum mucosa. Sci Rep. 2018;8:7788. https:// doi. org/ 10. 1038/ diarrhea. Probiotics Antimicrob Proteins. 2019. https:// doi. org/ 10. 1007/ s41598- 018- 26083-3. s12602- 018- 9436-5. 29. Bronner DN, Faber F, Olsan EE, Byndloss MX, Sayed NA, Xu GG, et al. 11. Branchu P, Bawn M, Kingsley RA. Genome variation and molecular epide- Genetic ablation of butyrate utilization attenuates gastrointestinal Sal- miology of Salmonella enterica serovar Typhimurium pathovariants. Infect monella disease. Cell Host Microbe. 2018. https:// doi. org/ 10. 1016/j. chom. Immun. 2018. https:// doi. org/ 10. 1128/ IAI. 00079- 18.2018. 01. 004. 12. McWhorter AR, Tearle R, Moyle TS, Chousalkar KK. In vivo passage of Sal- 30. Gantois I, Ducatelle R, Pasmans F, Haesebrouck F, Hautefort I, Thompson monella Typhimurium results in minor mutations in the bacterial genome A, et al. Butyrate specifically down-regulates Salmonella pathogenicity and increases in vitro invasiveness. Vet Res. 2019;50:71. https:// doi. org/ 10. island 1 gene expression. Appl Environ Microbio. 2006;72:946–9. https:// 1186/ s13567- 019- 0688-1.doi. org/ 10. 1128/ Aem. 72.1. 946- 949. 2006. 13. Ramachandran G, Aheto K, Shirtliff ME, Tennant SM. Poor biofilm-forming 31. Sorbara MT, Pamer EG. Interbacterial mechanisms of colonization resist- ability and long-term survival of invasive Salmonella Typhimurium ST313. ance and the strategies pathogens use to overcome them. Mucosal Pathog Dis. 2016. https:// doi. org/ 10. 1093/ femspd/ ftw049. Immunol. 2019;12:1–9. https:// doi. org/ 10. 1038/ s41385- 018- 0053-0. 14. Zheng HJ, Hu YC, Li QC, Tao J, Cai YQ, Wang YN, et al. Subtyping Salmo- 32. Maier L, Vyas R, Cordova CD, Lindsay H, Schmidt TS, Brugiroux S, et al. nella enterica serovar Derby with multilocus sequence typing (MLST ) and Microbiota-derived hydrogen fuels Salmonella Typhimurium invasion of clustered regularly interspaced short palindromic repeats (CRISPRs). Food the gut ecosystem. Cell Host Microbe. 2013;14:641–51. https:// doi. org/ 10. Control. 2017;73:474–84. https:// doi. org/ 10. 1016/j. foodc ont. 2016. 08. 051.1016/j. chom. 2013. 11. 002. 15. Zheng H. CRISPRS molecular subtyping and whole genome sequencing 33. Gagen EJ, Padmanabha J, Denman SE, McSweeney CS. Hydrogenotrophic analysis for Salmonella Derby isolates. Yangzhou: Yangzhou University; culture enrichment reveals rumen Lachnospiraceae and Ruminococcaceae 2017. acetogens and hydrogen-responsive Bacteroidetes from pasture-fed cat- 16. Ferrari RG, Rosario DKA, Cunha-Neto A, Mano SB, Figueiredo EES, Conte tle. FEMS Microbiol Lett. 2015. https:// doi. org/ 10. 1093/ femsle/ fnv104. CA. Worldwide epidemiology of Salmonella serovars in animal-based 34. Casey PG, Gardiner GE, Casey G, Bradshaw B, Lawlor PG, Lynch PB, et al. A foods: a meta-analysis. Appl Environ Microb. 2019. https:// doi. org/ 10. five-strain probiotic combination reduces pathogen shedding and allevi- 1128/ AEM. 00591- 19. ates disease signs in pigs challenged with Salmonella enterica serovar 17. Cai YQ, Tao J, Jiao Y, Fei X, Zhou L, Wang Y, et al. Phenotypic characteristics Typhimurium. Appl Environ Microbiol. 2007;73:1858–63. https:// doi. org/ and genotypic correlation between Salmonella isolates from a slaugh-10. 1128/ AEM. 01840- 06. terhouse and retail markets in Yangzhou. China Int J Food Microbiol. 35. Yang X, Brisbin J, Yu H, Wang Q, Yin F, Zhang Y, et al. Selected lactic 2016;222:56–64. https:// doi. org/ 10. 1016/j. ijfoo dmicro. 2016. 01. 020. acid-producing bacterial isolates with the capacity to reduce Salmonella 18. Hauser E, Hebner F, Tietze E, Helmuth R, Junker E, Prager R, et al. Diversity translocation and virulence gene expression in chickens. PLoS ONE. of Salmonella enterica serovar Derby isolated from pig, pork and humans 2014;9: e93022. https:// doi. org/ 10. 1371/ journ al. pone. 00930 22. in Germany. Int J Food Microbiol. 2011;151:141–9. https:// doi. org/ 10. 36. Hu JL, Yu H, Kulkarni RR, Sharif S, Cui SW, Xie MY, Nie SP, Gong J. Modula- 1016/j. ijfoo dmicro. 2011. 08. 020. tion of cytokine gene expression by selected Lactobacillus isolates in the 19. Zhou ZH, Li JW, Zheng HJ, Jin XC, Shen Y, Lei TY, et al. Diversity of Salmo- ileum, caecal tonsils and spleen of Salmonella-challenged broilers. Avian nella isolates and their distribution in a pig slaughterhouse in Huaian Pathol. 2015;44:463–9. https:// doi. org/ 10. 1080/ 03079 457. 2015. 10867 25. China. Food Control. 2017;78:238–46. https:// doi. org/ 10. 1016/j. foodc ont. 37. Stecher B. The roles of inflammation, nutrient availability and the com- 2017. 02. 064. mensal microbiota in enteric pathogen infection. Microbiol Spectr. 2015. 20. Matiasovic J, Stepanova H, Kudlackova H, Havlickova H, Sisak F, Rychlik I, https:// doi. org/ 10. 1128/ micro biols pec. MBP- 0008- 2014. et al. Immune response of pigs to Salmonella enterica serovar Derby and 38. Rivera-Chavez F, Lopez CA, Baumler AJ. Oxygen as a driver of gut dysbio- Typhimurium infections. Vet Microbiol. 2014;170:284–90. https:// doi. org/ sis. Free Radical Bio Med. 2017;105:93–101. https:// doi. org/ 10. 1016/j. freer 10. 1016/j. vetmic. 2014. 02. 003.adbio med. 2016. 09. 022. 21. Cui S, Li J, Sun Z, Hu C, Jin S, Li F, Guo Y, Ran L, Ma Y. Characterization of 39. Kaiser BLD, Li J, Sanford JA, Kim YM, Kronewitter SR, Jones MB, et al. A Salmonella enterica isolates from infants and toddlers in Wuhan. China J multi-omic view of host–pathogen–commensal interplay in Salmonella- Antimicro Chemo. 2009;63:87–94. https:// doi. org/ 10. 1093/ jac/ dkn452. mediated intestinal infection. PLoS ONE. 2013. https:// doi. org/ 10. 1371/ 22. Velazquez EM, Nguyen H, Heasley KT, Saechao CH, Gil LM, Rogers AWL, journ al. pone. 00671 55. et al. Endogenous Enterobacteriaceae underlie variation in susceptibility 40. Hapfelmeier S. Outrunning Salmonella—the role of endogenous Entero- to Salmonella infection. Nat Microbiol. 2019;4:1057–64. https:// doi. org/ 10. bacteriaceae in variable colonization resistance. Lab Anim. 2019;48:203–4. 1038/ s41564- 019- 0407-8.https:// doi. org/ 10. 1038/ s41684- 019- 0327-5. Yuan et al. Gut Pathogens (2022) 14:6 Page 12 of 12 41. Ganesh BP, Klopfleisch R, Loh G, Blaut M. Commensal Akkermansia mucin- iphila exacerbates gut inflammation in Salmonella Typhimurium-infected gnotobiotic mice. PLoS ONE. 2013. https:// doi. org/ 10. 1371/ journ al. pone. 00749 63. 42. Zhou A, Li J, Xu Z, Ni J, Guo J, Yao Y, et al. Whole-genome comparative and pathogenicity analysis of Salmonella enterica subsp. enterica Serovar Rissen. G3: Genes, Genomes, Genet. 2020. https:// doi. org/ 10. 1534/ g3. 120. 43. Moschen AR, Adolph TE, Gerner RR, Wieser V, Tilg H. Lipocalin-2: a master mediator of intestinal and metabolic inflammation. Trends Endocrinol Metab. 2017;28:388–97. https:// doi. org/ 10. 1016/j. tem. 2017. 01. 003. 44. Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Glock- ner FO. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 2013;41:D590-596. https:// doi. org/ 10. 1093/ nar/ gks12 19. 45. Dhariwal A, Chong J, Habib S, King IL, Agellon LB, Xia J. MicrobiomeAna- lyst: a web-based tool for comprehensive statistical, visual and meta- analysis of microbiome data. Nucleic Acids Res. 2017;45:W180–8. https:// doi. org/ 10. 1093/ nar/ gkx295. 46. Foster Z, Sharpton T, Grünwald N. Metacoder: an R package for visualiza- tion and manipulation of community taxonomic diversity data. PLoS Comput Biol. 2017;13(2): e1005404. https:// doi. org/ 10. 1371/ journ al. pcbi. 10054 04. 47. Toure R, Kheadr E, Lacroix C, Moroni O, Fliss I. Production of antibacterial substances by bifidobacterial isolates from infant stool active against Listeria monocytogenes. J Appl Microbiol. 2003;95:1058–69. https:// doi. org/ 10. 1046/j. 1365- 2672. 2003. 02085.x. 48. Koohestani M, Moradi M, Tajik H, Badali A. Eec ff ts of cell-free superna- tant of Lactobacillus acidophilus LA5 and Lactobacillus casei 431 against planktonic form and biofilm of Staphylococcus aureus. Vet Res Forum. 2018;9:301–6. https:// doi. org/ 10. 30466/ vrf. 2018. 33086. Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in pub- lished maps and institutional affiliations. Re Read ady y to to submit y submit your our re researc search h ? 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Gut Pathogens – Springer Journals

Published: Jan 25, 2022

Keywords: Salmonella Derby; Gut microbiota; Inter-strain variation

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