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Changes to the gut microbiota in mice induced by infection with Toxoplasma gondii
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Changes to the gut microbiota in mice induced by infection with Toxoplasma gondii Dong Yan Shao , Xue Bai , Ming Wei Tong , Yuan yuan Zhang , Xiao lei Liu , Yong hua Zhou , Chengyao Li , Wei Cai , Xin Gao , Mingyuan Liu , Yong Yang PII: DOI: Reference:
S0001-706X(19)31455-X https://doi.org/10.1016/j.actatropica.2019.105301 ACTROP 105301
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Acta Tropica
Received date: Revised date: Accepted date:
22 October 2019 12 December 2019 12 December 2019
Please cite this article as: Dong Yan Shao , Xue Bai , Ming Wei Tong , Yuan yuan Zhang , Xiao lei Liu , Yong hua Zhou , Chengyao Li , Wei Cai , Xin Gao , Mingyuan Liu , Yong Yang , Changes to the gut microbiota in mice induced by infection with Toxoplasma gondii, Acta Tropica (2019), doi: https://doi.org/10.1016/j.actatropica.2019.105301
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In mice at 13 days post-infection with Toxoplasma gondii, the relative abundance of Proteobacteria increased, along with that of harmful bacteria.
The mice at 21 days post-infection with Toxoplasma gondii, had more beneficial intestinal bacteria than the control group, such as Lactobacillus, with harmful bacteria reduced than 13 days post-infection group. The intestinal flora in 21days is similar to that of healthy mice, but not completely identical.
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Changes to the gut microbiota in mice induced by infection with Toxoplasma gondii Dong Yan Shao1a, Xue Bai1a, Ming Wei Tong2a, Yuan yuan Zhang1, Xiao lei Liu1, Yong hua Zhou4, Chengyao Li 1, Wei Cai5, Xin Gao1, Mingyuan Liu1*, Yong Yang 1,3*
1. Key Laboratory of Zoonosis Research, Ministry of Education, Institute of Zoonosis/ College of Veterinary Medicine, Jilin University, Changchun, China. 2.School of Basic Medical Sciences, Shanxi Medical University, Taiyuan, China. 3. Wu Xi Medical School, Jiangnan University, Wu xi, China. 4. Jiang Su Institute of Parasitic Disease Wu xi, China. 5. Affiliated Hospital of Jiangnan University, The Forth People's Hospital of Wuxi City, Wuxi, China.
a These authors contributed equally to this work.
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Abstract Toxoplasma gondii (T. gondii) is a common parasite worldwide, which can cause encephalitis, enteritis and miscarriage in abortion women. This study examined the cecal microbiome of mice infected with T. gondii through analysis of 16S rRNA genes determined by Illumina sequencing. BALB/c mice were orally infected with sporulated T. gondii oocysts. Mice were killed after 13-days- and 21-days- post infection, respectively, then their cecal contents were extracted and examined to determine the composition of gut microflora by illumina sequencing of the V3 +V4 region of the 16S rRNA genes. Our results showed the alterations in the gut microbes of BALB/c mice infected with T. gondii infection, where we observed a significant shift in the relative abundance of cecal bacteria. In mice at 13 days post-infection, the relative abundance of Proteobacteria increased, along with that of harmful bacteria, such as Bilopha and Desulfovibrio. However, the abundance of Lactobacillus decreased. At 21 days post-infection, the abundance of Lactobacillus was more than that observed for the uninfected control, with harmful bacteria, such as Bilopha and Desulfovibrio being reduced. The mice at 21-days post-infection had more beneficial intestinal bacteria than the control group. Our results suggested that the gut microbiota play an important role in disease progression from acute infection to chronic infection. Keywords: Toxoplasma gondii; gut microbiota; 16S rRNA; host-parasite interaction
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1. Introduction T. gondii is an obligate intracellular parasite that has been shown to infect a wide variety of hosts (Lindsay and Dubey, 2014). Humans and other mammals, or birds, are usually infected with T. gondii through the ingestion of contaminated food and water (Black and Boothroyd, 2000). Following the acute infection phase, T. gondii enters a period of long-term infection characterized by the formation of tissue cysts, largely in the brain and muscles (Hutchinson, 1966). Currently, the mechanism of by which T. gondii infections progress from acute to chronic disease is not well understood. The composition of gut microbiota can influence the pathophysiology of parasite infections, and changes in microbiota may confer resistance to enteric parasite or alternatively, promote parasite infection. For example, the susceptibility of germfree mice to Cryptosporidium parvum was higher than that of normal mice (Harp et al., 1992). Intestinal flora also regulates many physiological processes in the body, such as metabolism and immunity (Brestoff and Artis, 2013; Knaus et al., 2017). Recently, there has been a growing interest in the study of the influence of parasite infections on the gut microbiome. However, the change in intestinal flora during the progression of T. gondii infection from the acute to chronic stage is not yet well understood. In this study, we investigated the intestinal flora of mice at 13- and 21-days post infection with T. gondii using analysis of the 16S rRNA gene sequence determined with high-throughput sequencing technology. Our results found that T. gondii infection altered intestinal flora in early stage infections and suggested that intestinal 4
flora could play an important role in the host defense against disease progression and contribute to the improvement of enteritis. 2. Materials and methods 2.1Mice. Female BALB/c mice (n = 30), 6-week-age, were randomly divided into three treatment groups (n = 10/group): infection for thirteen days, infection for twenty-one-days, and the uninfected control group. Mice were orally infected with 100 purified sporulated ME49 strain oocysts (from Jiang Su Institute of Parasitic Disease) suspended in sterile phosphate buffered solution (PBS) 0.5ml while controls were infected with a same volume of sterile PBS containing no oocysts. All mice had ad libitum access to disinfected feed and water. 2.2 Sample collection Three groups were respectively euthanized on day 0 (before infection), 13 days and 21 days post infection prior to harvesting of cecum contents. Three mice were randomly selected from each group to collect the cecal contents. Cecal contents were aseptically collected and stored at -80°C until extraction of bacterial extraction. 2.3. 16S rRNA amplification PCR amplification of the bacterial 16S rRNA genes (V3–V4 region) was carried out using
the
following
sequences
for
the
forward
primer
338F
(5 ′
-ACTCCTACGGGAGGCAGCA-3 ′ ) and the reverse primer 806R (5 ′ -GGACTACHVGGGTWTCTAAT-3′). PCR reaction we designed was in a 25ul reaction system that has 5 μl Q5 reaction buffer (5×), 5 μl Q5 High-Fidelity GC buffer 5
(5×), 0.25 μl Q5 High-Fidelity DNA polymerase (5 U/μl), 2 μl dNTPs (2.5 mM), 1 μl of each forward and reverse primers (10 μM), 2 μl DNA template, and 8.75 μl ddH2O. The PCR conditions used had an initial denaturation at 95 °C for 2 min, followed by 25 cycles of denaturation at 95 °C for 30 s, annealing at 55 °C for 30 s and elongation at 72 °C for 45 s, with a final augmentation stage at 72 °C for 10 min. The products of PCR were purified using Ageuncourt AMPure Beads (Beckman Coulter, Indianapolis, IN, United States). The concentration of the PCR products was assessed by PicoGreen dsDNA Assay Kit (Invitrogen, Carlsbad, CA, United States). 2.4. Bioinformatics' analysis of sequencing data Illumina MiSeq Paired-end sequencing was used to determine the sequences of the amplified 16S RNA genes. The OTU whose abundance value is less than 0.001% (1/100,000) of the total sequencing amount of all samples is removed, and the abundance matrix of the rare OTU is used for subsequent analysis. The 16S rRNA gene sequencing data was clustered with a 97% similarity into Operational Taxonomic Units (OTUs). . In order to compare the diversity of different samples, we did the rarefaction , which is a homogenization method that is used to randomly draw OTUs to the same quantity based on a minimum value (90%), so as to correct the diversity difference caused by sequencing depth. Finally, depth statistics and visualization analysis of the species composition for all samples were determined. Concrete analysis of different categorical levels and significant difference between groups were also performed. Principal component analysis (PCA) uses linear transformation to combine the original high-dimensional data (such as the OTU abundance matrix) into 6
a lower-dimensional space coordinate system (i.e. principal component) to simplify the data structure and display the natural distribution of the samples. Nonmetric Multidimensional Scaling (NMDS) simplified the data structure by reducing the number of dimensions and, reordering the samples into a new low-dimensional coordinate system, that describes the distribution characteristics of the samples at a specific distance scale, such as Unweighted UniFrac distance. The R software package was used to conduct a NMDS analysis for Unweighted and Weighted Unirac distance matrix. 2.5. Statistical analyses Metagenomic inferences and Kyoto Encyclopedia for Genes and Genomics (KEGG) classifications were performed with the PICRUST package (Langille et al., 2013) with statistical analyses done with R Software. Alpha diversity index analyses of the samples were conducted using QIIME to calculate the Shannon index, Simpson Index, and Ace Index. 3. Results 3.1 T. gondii infection is associated with bacterial diversity in the intestine The bacterial diversity was assessed by analysis of the OTU in each group of samples. The number of observed OTUs in the control samples was less than for the T. gondii infected intestine samples after thirteen days, but more than that those from T. gondii infected intestine after twenty-one days (Figure 1A). Intestine samples at thirteen days post-infection with T. gondii had a higher sample richness that was also reflected by the abundance Ace index and Chao index (Table 1). Within treatment 7
groups, the bacterial diversity could be assessed by the Simpson index and Shannon diversity index, which demonstrated that the bacterial diversity increased for the T. gondii infected intestine after thirteen days compared to the control ones, but that the bacterial diversity of T. gondii infected intestine after twenty-one days was less than for the control ones. In summary, these data point to a more diverse bacterial population in the T. gondii infected mouse at thirteen days compared to the control ones, but the control one has more diverse bacterial population than the T. gondii infected mouse after twenty-one days. 3.2 The ceca microbiome composition is significantly altered in the T. gondii infected mouse In order to examine the global differences in bacterial composition between mice that were infected with T. gondii and the uninfected controls, we performed a nonmetric multidimensional scaling (NMDS) analysis of all samples using the UniFrac distance. NMDS is a powerful ordination method that can uncover nonlinear relationships between samples and is widely used in ecology. The results showed that there was differential grouping of the control samples in the center of the graph, while samples from mice at 13 days post infection with T. gondii were more dispersed and grouped to the right. Mice infected for 21 days were grouped to the left (Figure 1B). PLS-DA analysis is a supervised pattern recognition method based on a partial least squares regression model to analyze data. As shown at Figure 1C, the three models did not co-localize confirming that samples from mice infected by T. gondii clustered differently to those from controls (Figure 1C). Sample data for 21 days of infection 8
were more intensive than those for the control group. To uncover relationships based on the presence or absence of bacterial groups as well as their phylogenetic relatedness, we performed a principal coordinates analysis of the samples using the phylogenetic-tree-based unweighted Unifrac metric. As shown in Figure 1D, there was a separation between samples from T. gondii infected mice and the controls using principal component PC2 (15.62% of the explained variance) and mice infected by T. gondii for thirteen days and those infected for twenty-one days are parted by the PC1 (24.56% of the explained variance). 3.3 Comparison of the intestinal microbiome at different taxonomic levels Statistical analysis of the intestinal microbiome structure of the three groups in each taxonomic classification level was carried out on the basis of the out data (Figure 2). The composition of the entire microbiome for each group is shown at the phylum level by Figure 2 and Figure 3A. The bacteria in the control samples at the phylum level belonged to the Firmicutes (60.0%), with Bacteroidetes (30.1%), Proteobacteria (4.2%), TM7 (3.6%), Verrucomicrobia (1.3%), and Tenericute (0.6%). In all T. gondii infected mice, the proportional composition for Bacteroidetes decreased (13-day group 23.4%, 21-day group 24.7%), as did the proportion of Firmicutes (41.37%), Bacteroidetes (24.7%), TM7 (1.5%), and actinobacteria (0.6%). Conversely, the proportion of proteobacteria (31.2%) increased in the mice that were infected by T. gondii after thirteen days compared to the controls. In the 21-day post-infection group the Firmicutes (66.67%) were enriched while the proportion of Bacteroidetes (23.4%), proteobacteria (3.5%) TM7 (1.23%) and Tenericute (0.03%) were decreased in T. 9
gondii infected mice after twenty-one days compared to the uninfected controls (Figure 3A). When comparing the microbiome at the family and genus level by relative abundance, the organisms in uninfected mice were found to be the Lactobacillaceae (26.9%), the S24-7 (23%) and the Clostridiales (18.5%), followed by the Lachnospiraceae (8.13%), Desulfovibrionaceae (2.23%) and Ruminococcaceae (3.83%). In the T. gondii infected mice at 13 days post-infection，when compared with the uninfected controls the relative abundance of Lactobacillus from Lactobacillaceae, and the S24-7 from Bacteroidales decreased, while that of Desulfovibrio from Desulfovibrionaceae
(26.9%),
Bilophila
from
Desulfovibrionaceae
(2.7%),
Ruminococcus from Ruminococcaceae (3.6%) increased. Compared to the controls, mice that were infected with T. gondii for 21 days, had an increase in the proportion of lactobacillus from Lactobacillaceae; Rikenella from Rikenellaceae, Odoribacter from Odoribacteraceae, while the S24-7, Clostridiales, Desulfovibrio, and the Lachnospiraceae decreased (Figure 3B and Figure 4). 3.4 Comparison of cecal bacterial functional abundance profile In order to estimate the difference in bacterial function between the treatment groups, we conducted a PICRUSt (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States) analysis. The PICRUSt software package predicts the bacterial function by comparing the existing 16S rRNA gene sequencing data with a microbial reference genome database where metabolic functions have been defined. KEGG Database analysis determined that the mice that were infected 10
by T. gondii for thirteen days had a higher probability of acquiring Neurodegenerative Disease than the control mice and the treatment group infected with T. gondii for twenty-one days. However, mice that were infected by T. gondii for thirteen days were less likely to get the Immune System Diseases than the control mice and those infected with T. gondii for twenty-one days. (Figure 5). In the Metabolism aspect, the mice that were infected by T. gondii for thirteen days has fewer bacteria involved Carbohydrate Metabolism, Enzyme Families, Xenobiotics Biodegradation and Metabolism, Lipid Metabolism abundance than the control mice and the mice infected T. gondii twenty-one days. About the cecal bacteria’s influence on the organismal system, the T. gondii infected mice had fewer bacteria about Nervous System and Excretory System, but had more bacteria about the Immune System than the control mice. The mice that were infected by T. gondii for thirteen days had a higher bacterial abundance associated with Environmental Adaptation.
4. Discussion T. gondii is an obligate intracellular parasite that can infect any nucleated avian or mammalian cell (Robert-Gangneux and Dardé, 2012). In mice, T. gondii replicates agamically in two different forms: the rapidly replicating tachyzoite form; and the bradyzoite form, which grows more slowly within intracellular cyst structures. Tachyzoites occur during acute infection, and after a period of infection, tachyzoites become bradyzoites. The bradyzoite growth induces a tissue cyst, which can then enter the muscles and nerves (Dubey, 1998). 11
The mechanism of intestinal inflammation and intestinal dysfunction caused by parasite infection is closely related to the change in intestinal flora (Partida-Rodriguez et al., 2017). In this study, we investigated the intestinal flora of mice infected with T. gondii. At thirteen days post-infection, T. gondii parasite has recently left the intestinal tract, however the intestinal flora has not yet completely recovered. Compared with normal intestinal flora, there were more opportunistic pathogens in the mice at thirteen days post-infection. For example, these mice had a higher proportion of Proteobacteria in their intestinal flora, which include a large number of opportunistic pathogens, such as Escherichia coli, Salmonella and Campylobacter (Rizzatti et al., 2017). Most intestinal bacteria are obligate anaerobes, but Proteobacteria are facultative anaerobic bacteria. The increase in Proteobacteria will alter the overall structure of the intestinal flora (Shin et al., 2015). In many hosts, the relative abundance of Proteobacteria is considered to be associated with ecological imbalance in intestinal flora in enteritis hosts and serves as a marker for the instability of intestinal flora (Walker et al., 2011). Indeed, the severity of colitis is positively correlated with the abundance of Proteobacteria (Maharshak et al., 2013). With induction of inflammation, the associated secretion of inflammatory molecules and the concomitant changes in the intestinal environment are also conducive to a large expansion of Proteobacteria. As a result, the structure of intestinal flora changes, and the number of Firmicutes and Bacteroides is known to decrease (Carvalho et al., 2012), consistent with our results. However, some studies indicated that an increase in the relative abundance of facultative anaerobes such as Proteobacteria, can assist the 12
colonization of beneficial obligate anaerobes. As the body recovers from the inflammation, Proteobacteria are quickly replaced by beneficial obligate anaerobes, so parasitic infections can improve the overall intestinal environment and alleviate enteritis(Davis et al., 2017). Therefore, the increase in Proteobacteria is not necessarily harmful; it could serve to regulate the structure of the flora, ultimately inducing a healthier intestinal microbiome.(Mirpuri et al., 2014) Except for Proteobacteria, In, wewe found that the abundance of Desulfovibrio and Bilophila increased significantly (26.9% and 2.2% respectively) at thirteen-days post-infection, above that of control group and the 23-day post-infection group. Desulfovibrio, that is the main component of sulfate-reducing bacteria (SRB) in the intestine (Christophersen et al., 2011) , are usually found to be increased in enteritis (Rowan et al., 2010). Most SRB use sulfate or other sulfur compounds such as thiosulfate, sulfite and sulfur as the terminal electron acceptor during anaerobic respiration. Hydrogen sulfide, the main product of SRB metabolism, is toxic to human cells, damaging DNA and, inhibiting oxidizing (Short-chain fatty acids SCFA ) and its protective properties (Attene-Ramos et al., 2010; Carbonero et al., 2012). It can also destroy the function of the epithelial barrier by weakening the oxidation of butyrate, which leads to the specific inflammatory response of Inflammatory bowel disease (IBD)(Roediger et al., 1997). Mucosal barriers are also attenuated which reduces the protective effect of intestinal epithelium (Gibson et al., 1993; Wyatt et al., 1993). In addition to the effects of sulfides, extracellular polymers produced by SRB are species-specific and may contain highly immunogenic components, such as O‐ 13
antigenic portions of lipopolysaccharides (Beech and C. Tapper, 1999). These antigens elicit an immune response in genetically susceptible individuals and initiate or contribute to the inflammatory process of Ulcerative Colitis (UC) (Hisamatsu et al., 2013). Thus, we speculated that Desulfovibrio may play an important role in the process by which Toxoplasma infection causes enteritis, through destruction of the epithelial barrier, along with other toxic effects of hydrogen sulfide. One representative of Bilophila is Bilophila wadsworthia, a Gram-negative anaerobic bacterium that accounts for less than 0.1% of the intestinal microbiota in healthy animals (Baron, 1997). However, this bacterial species is increased in the intestinal tract of patients with colitis and intestinal cancer (Scanlan et al., 2009), and is considered to be an opportunistic pathogen in the gut (da Silva et al., 2008). Bilophila wadsworthia is similar to Desulfovibrio (Laue et al., 1997), uniquely using taurine-derived sulfite as an electron acceptor to perform anaerobic respiration. (Laue et al., 2001). Taurine respiration produces sulfide, which has a toxic effect on colonic epithelial cells, and is thought to play a role in inflammatory bowel diseases (CAMPIERI and GIONCHETTI, 2001). Bile is not only a very effective digestive juice, but also has effective antimicrobial properties, assisting in the selection or exclusion of potential intestinal microorganisms and protozoa, such as Giardia, Microsporidia and Cryptosporidium. However, some bacteria like B. wadsworthia have anti-biliary effects and reproduce better in the presence of bile (Ananieva et al., 2002). Such symbiotic relationships can help pathogens to establish a niche in the intestine (Devkota et al., 2012) and may create conditions conducive to the early 14
colonization of T. gondii in the intestinal tract (Chen et al., 2018). In addition to the proinflammatory effects within the intestine, B. wadsworthia promotes intestinal barrier defects, systemic inflammation, bile acid metabolism disorders, and changes in overall microbial functional characteristics (Natividad et al., 2018). However, after a longer period of time, when T. gondii has left the intestine, Bilophila was no longer detected in the group 21-days post-infection. This indicated that the effect of T. gondii on the intestinal tract is not sustained after disease progression, with the inflammation of the intestines slowly improving, and the intestinal microbial structure returning to its healthy composition. A low F/B (Firmicutes/Bacteroides) index is associated with a variety of diseases, such as irritable bowel syndrome (IBS) (Collins, 2014) and inflammatory bowel disease (IBD) (Tamboli et al., 2004). Compared with 13-day post-infection group, our results showed that F/B index rises in the 21-day post-infection group. The proportion of Proteobacteria also decreased from 31.2% (13 days) to 3.17% (21 days), which was lower than for the control group (4.17%). These results indicated that the intestinal flora of the twenty-one-day group was greatly recovered, with the chance of the growth of pathogenic bacteria being reduced, and the overall intestinal environment improving.Lactobacillus can regulate the secretion of cytokines by immune cells. IL-10, secreted by Treg cells, and IL-17 and IL-22 secreted by Th17 cells, are important immune signaling molecules for maintaining intestinal homeostasis (Liu et al., 2009). Lactobacillus acidophilus can restore the balance of inflammatory cytokines and Th17/Treg cells in the gut of mice with dextran sulfate-induced colitis (Park et al., 2018). Lactobacillus can also restore 15
intestinal barrier function (Mao et al., 1996), reducing the permeability of the intestinal epithelium (Mangell et al., 2002) by promoting the secretion of tight junction proteins in epithelial cells (Karczewski et al., 2010). These bacteria can also reduce endotoxin levels in the blood (Xue et al., 2017) and down-regulate the level of interleukin-8 secretion, thus playing an anti-inflammatory role (Pan et al., 2018). A variety of lactic acid bacteria have also been shown to effective treatments for symptoms of bowel cancer (Lenoir et al., 2016), enteritis (Khazaie et al., 2012) and irritable bowel syndrome (Clarke et al., 2012). Our results show that the lactobacilli component of the gut microbiome is increased in the 21-day post-infection group compared with the control group. This further indicates that the intestinal flora rapidly recovers after the T. gondii parasite leaves the intestine and the resulting gut flora was healthier and more beneficial than the original biome in the control group, containing fewer pathogens and having a better resistance to intestinal diseases. Some studies have shown that probiotics, such as Lactobacillus, can have a therapeutic effect on brain disease, through the brain-gut axis, but the mechanism of this action still needs to be confirmed (Brenner et al., 2017; Mancuso and Santangelo, 2018). Since in chronic T. gondii infections, the parasite eventually colonizes the brain, the increase in lactic acid bacteria may also inhibit the progression of T. gondii infection and may be a natural defense mechanism of the body. In a word, we our results showed the alterations in the gut microbes of BALB/c mice infected with T. gondii, where we observed a significant shift in the relative abundance of cecal bacteria. On the thirteenth day post-infection, the intestinal flora 16
was different from that of healthy mice, with the number of harmful bacteria, such as bilophila increasing. By the 21st day post-infection, the intestinal flora had partially recovered, with the harmful bacteria, such as bilophila, decreasing, such that the intestinal flora is similar to that of healthy mice, but not completely identical. And the mice at 21 days post-infection with T. gondii, had more beneficial intestinal bacteria than the control group, such as Lactobacillus. Based on our results that the intestinal flora can be restructured during infection with T. gondii and the existing literature on the role of intestinal microflora in health and disease, our study suggests that intestinal flora could play an important role in the infection of T. gondii. But whether these changes are involved in the parasitism and pathology of T. gondii needs further investigation.
Conflict of Interest Statement The authors declare they have no competing interests.
Author Contributions Statement The study was conceived and designed by YY and LMY, YY and ZYH performed the experiments. SDY , YY and TMW analyzed the data. SDY and BX wrote the manuscript.. TMW, ZYY, LCY, LXL, GX and CW improved the manuscript. All authors read and approved the final manuscript.
Conflict of Interest Statement The authors declare they have no competing interests.
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Acknowledgements This study was supported by The National Key Research and Development Program of China (2018YFD0502202, 2017YFD0501302, 2017YFC1601206,); Jilin Provincial Science and Technology Development Project（20180520042JH），scientific fund from Health and Family Planning Commission of Wuxi (No. Q201640) and the Fundamental Research Funds for the Central Universities , JLU..
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wadsworthia RZATAU contains a fused DsrB-DsrD subunit. Journal of bacteriology 183, 1727-1733. Lenoir, M., Del Carmen, S., Cortes-Perez, N.G., Lozano-Ojalvo, D., Munoz-Provencio, D., Chain, F., Langella, P., de Moreno de LeBlanc, A., LeBlanc, J.G., Bermudez-Humaran, L.G., 2016. Lactobacillus casei BL23 regulates Treg and Th17 T-cell populations and reduces DMH-associated colorectal cancer. J Gastroenterol 51, 862-873. Lindsay, D.S., Dubey, J.P., 2014. Chapter 6–Toxoplasmosis in Wild and Domestic Animals. Toxoplasma Gondii, 193-215. Liu, Z.J., Yadav, P.K., Su, J.L., Wang, J.S., Fei, K., 2009. Potential role of Th17 cells in the pathogenesis of inflammatory bowel disease. World J Gastroenterol 15, 5784-5788. Maharshak, N., Packey, C.D., Ellermann, M., Manick, S., Siddle, J.P., Huh, E.Y., Plevy, S., Sartor, R.B., Carroll, I.M., 2013. Altered enteric microbiota ecology in interleukin 10-deficient mice during development and progression of intestinal inflammation. Gut Microbes 4, 316-324. Mancuso, C., Santangelo, R., 2018. Alzheimer's disease and gut microbiota modifications: The long way between preclinical studies and clinical evidence. Pharmacol Res 129, 329-336. Mangell, P., Nejdfors, P., Wang, M., Ahrne, S., Westrom, B., Thorlacius, H., Jeppsson, B., 2002. Lactobacillus plantarum 299v inhibits Escherichia coli-induced intestinal permeability. Digestive diseases and sciences 47, 511-516. Mao, Y., Nobaek, S., Kasravi, B., Adawi, D., Stenram, U., Molin, G., Jeppsson, B., 1996. The effects of Lactobacillus strains and oat fiber on methotrexate-induced enterocolitis in rats. Gastroenterology 111, 334-344. Mirpuri, J., Raetz, M., Sturge, C.R., Wilhelm, C.L., Benson, A., Savani, R.C., Hooper, L.V., Yarovinsky, F., 2014. Proteobacteria-specific IgA regulates maturation of the intestinal microbiota. Gut Microbes 5, 28-39. Natividad, J.M., Lamas, B., Pham, H.P., Michel, M.L., Rainteau, D., Bridonneau, C., da Costa, G., van Hylckama Vlieg, J., Sovran, B., Chamignon, C., Planchais, J., Richard, M.L., Langella, P., Veiga, P., Sokol, H., 2018. Bilophila wadsworthia aggravates high fat diet induced metabolic dysfunctions in mice. Nat Commun 9, 2802. Pan, F., Zhang, L., Li, M., Hu, Y., Zeng, B., Yuan, H., Zhao, L., Zhang, C., 2018. Predominant gut Lactobacillus murinus strain mediates anti-inflammaging effects in calorie-restricted mice. Microbiome 6, 54. Park, J.S., Choi, J.W., Jhun, J., Kwon, J.Y., Lee, B.I., Yang, C.W., Park, S.H., Cho, M.L., 2018. Lactobacillus acidophilus Improves Intestinal Inflammation in an Acute Colitis Mouse Model by Regulation of Th17 and Treg Cell Balance and Fibrosis Development. J Med Food 21, 215-224. Partida-Rodriguez, O., Serrano-Vazquez, A., Nieves-Ramirez, M.E., Moran, P., Rojas, L., Portillo, T., Gonzalez, E., Hernandez, E., Finlay, B.B., Ximenez, C., 2017. Human Intestinal Microbiota: Interaction Between Parasites and the Host Immune Response. Arch Med Res 48, 690-700. 20
Rizzatti, G., Lopetuso, L.R., Gibiino, G., Binda, C., Gasbarrini, A., 2017. Proteobacteria: A Common Factor in Human Diseases. Biomed Res Int 2017, 9351507. Robert-Gangneux, F., Dardé, M.-L., 2012. Epidemiology of and diagnostic strategies for toxoplasmosis. Clinical microbiology reviews 25, 264-296. Roediger, W.E.W., Moore, J., Babidge, W., 1997. Colonic Sulfide in Pathogenesis and Treatment of Ulcerative Colitis. Digestive Diseases & Sciences 42, 1571-1579. Rowan, F., Docherty, N.G., Murphy, M., Murphy, B., Calvin Coffey, J., O'Connell, P.R., 2010. Desulfovibrio bacterial species are increased in ulcerative colitis. Dis Colon Rectum 53, 1530-1536. Scanlan, P.D., Shanahan, F., Marchesi, J.R., 2009. Culture-independent analysis of desulfovibrios in the human distal colon of healthy, colorectal cancer and polypectomized individuals. FEMS microbiology ecology 69, 213-221. Shin, N.R., Whon, T.W., Bae, J.W., 2015. Proteobacteria: microbial signature of dysbiosis in gut microbiota. Trends Biotechnol 33, 496-503. Tamboli, C.P., Neut, C., Desreumaux, P., Colombel, J.F., 2004. Dysbiosis in inflammatory bowel disease. Gut 53, 1-4. Walker, A.W., Sanderson, J.D., Churcher, C., Parkes, G.C., Hudspith, B.N., Rayment, N., Brostoff, J., Parkhill, J., Dougan, G., Petrovska, L., 2011. High-throughput clone library analysis of the mucosa-associated microbiota reveals dysbiosis and differences between inflamed and non-inflamed regions of the intestine in inflammatory bowel disease. BMC Microbiol 11, 7. Wyatt, J., Vogelsang, H., Hubl, W., Waldhoer, T., Lochs, H., 1993. Intestinal permeability and the prediction of relapse in Crohn's disease. Lancet 341, 1437-1439. Xue, L., He, J., Gao, N., Lu, X., Li, M., Wu, X., Liu, Z., Jin, Y., Liu, J., Xu, J., Geng, Y., 2017. Probiotics may delay the progression of nonalcoholic fatty liver disease by restoring the gut microbiota structure and improving intestinal endotoxemia. Sci Rep 7, 45176.
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Figure 1 Alterations in gut microbiota caused by Toxoplasma gondii infection. A. Venn diagram showing overlap in OTUs with differential abundance in control, mice 13 days, and 21 days post-infection with Toxoplasma gondii. B. NMDS (Nonmetric Multidimensional Scaling) showing the difference in bacterial communities according to the Unweighted Unifrac distance. C. PLS-DA showing that there are significant differences between the three treatment groups. D. PCA of the unweighted UniFrac values for samples from infected and control mice. Each point represents the gut microbiota for each group.
22
Figure 2 Community structure of bacteria from different treatment groups in each taxonomic classification level. The percentage and distribution of bacterial communities were showed at the taxonomic classification level of kingdom, phylum, class, order, family, genus and species through the number of concentric circles from inside to outside. Statistically significant difference between groups (p<0.05).
23
Figure 3 Community structure of bacteria from different treatment groups in different taxonomic classification level. A. Community structure of bacteria from different treatment groups in phylum level. B. Community structure of bacteria from different treatment groups in family level.
Figure 4 Bacterial distribution of the top 100 most abundant genera among the nine treatment samples. Double hierarchical dendrogram shows the bacterial distribution. The heatmap plot depicts the relative percentage of each bacterial genus within each sample. The relative values for bacterial family are indicated by color intensity with the legend indicated under the heatmap
24
Figure 5 KEGG functional classification. The red bars represent the control group. The blue bars represent the infected 13-day group. The green bars represent the infected 21-day group.
25
Table 1 Estimators of per group’s sequence diversity and richness. Sample id
Reads
0.90
Ace
Chao1
Shannon
coverage
Simpson
CK_1
887.35
587.00
5.70
0.990899
0.942799
CK_2
1219.88
825.00
6.31
0.999248
0.961652
CK_3
1249.63
1007.00
6.66
0.999367
0.959456
Tg_13_1
1903.79
1180.00
6.22
0.999418
0.907526
Tg_13_2
1589.19
1007.00
6.24
0.999355
0.953486
Tg_13_3
1463.70
1230.00
6.79
0.999413
0.927441
Tg_21_1
793.27
614.00
4.14
0.998984
0.723298
Tg_21_2
1124.87
950.00
6.47
0.999290
0.929651
Tg_21_3
856.30
625.00
4.18
0.998971
0.752064
26
Changes to the gut microbiota in mice induced by infection with Toxoplasma gondii Dong Yan Shao , Xue Bai , Ming Wei Tong , Yuan yuan Zhang , Xiao lei Liu , Yong hua Zhou , Chengyao Li , Wei Cai , Xin Gao , Mingyuan Liu , Yong Yang PII: DOI: Reference:
S0001-706X(19)31455-X https://doi.org/10.1016/j.actatropica.2019.105301 ACTROP 105301
To appear in:
Acta Tropica
Received date: Revised date: Accepted date:
22 October 2019 12 December 2019 12 December 2019
Please cite this article as: Dong Yan Shao , Xue Bai , Ming Wei Tong , Yuan yuan Zhang , Xiao lei Liu , Yong hua Zhou , Chengyao Li , Wei Cai , Xin Gao , Mingyuan Liu , Yong Yang , Changes to the gut microbiota in mice induced by infection with Toxoplasma gondii, Acta Tropica (2019), doi: https://doi.org/10.1016/j.actatropica.2019.105301
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In mice at 13 days post-infection with Toxoplasma gondii, the relative abundance of Proteobacteria increased, along with that of harmful bacteria.
The mice at 21 days post-infection with Toxoplasma gondii, had more beneficial intestinal bacteria than the control group, such as Lactobacillus, with harmful bacteria reduced than 13 days post-infection group. The intestinal flora in 21days is similar to that of healthy mice, but not completely identical.
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Changes to the gut microbiota in mice induced by infection with Toxoplasma gondii Dong Yan Shao1a, Xue Bai1a, Ming Wei Tong2a, Yuan yuan Zhang1, Xiao lei Liu1, Yong hua Zhou4, Chengyao Li 1, Wei Cai5, Xin Gao1, Mingyuan Liu1*, Yong Yang 1,3*
1. Key Laboratory of Zoonosis Research, Ministry of Education, Institute of Zoonosis/ College of Veterinary Medicine, Jilin University, Changchun, China. 2.School of Basic Medical Sciences, Shanxi Medical University, Taiyuan, China. 3. Wu Xi Medical School, Jiangnan University, Wu xi, China. 4. Jiang Su Institute of Parasitic Disease Wu xi, China. 5. Affiliated Hospital of Jiangnan University, The Forth People's Hospital of Wuxi City, Wuxi, China.
a These authors contributed equally to this work.
2
Abstract Toxoplasma gondii (T. gondii) is a common parasite worldwide, which can cause encephalitis, enteritis and miscarriage in abortion women. This study examined the cecal microbiome of mice infected with T. gondii through analysis of 16S rRNA genes determined by Illumina sequencing. BALB/c mice were orally infected with sporulated T. gondii oocysts. Mice were killed after 13-days- and 21-days- post infection, respectively, then their cecal contents were extracted and examined to determine the composition of gut microflora by illumina sequencing of the V3 +V4 region of the 16S rRNA genes. Our results showed the alterations in the gut microbes of BALB/c mice infected with T. gondii infection, where we observed a significant shift in the relative abundance of cecal bacteria. In mice at 13 days post-infection, the relative abundance of Proteobacteria increased, along with that of harmful bacteria, such as Bilopha and Desulfovibrio. However, the abundance of Lactobacillus decreased. At 21 days post-infection, the abundance of Lactobacillus was more than that observed for the uninfected control, with harmful bacteria, such as Bilopha and Desulfovibrio being reduced. The mice at 21-days post-infection had more beneficial intestinal bacteria than the control group. Our results suggested that the gut microbiota play an important role in disease progression from acute infection to chronic infection. Keywords: Toxoplasma gondii; gut microbiota; 16S rRNA; host-parasite interaction
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1. Introduction T. gondii is an obligate intracellular parasite that has been shown to infect a wide variety of hosts (Lindsay and Dubey, 2014). Humans and other mammals, or birds, are usually infected with T. gondii through the ingestion of contaminated food and water (Black and Boothroyd, 2000). Following the acute infection phase, T. gondii enters a period of long-term infection characterized by the formation of tissue cysts, largely in the brain and muscles (Hutchinson, 1966). Currently, the mechanism of by which T. gondii infections progress from acute to chronic disease is not well understood. The composition of gut microbiota can influence the pathophysiology of parasite infections, and changes in microbiota may confer resistance to enteric parasite or alternatively, promote parasite infection. For example, the susceptibility of germfree mice to Cryptosporidium parvum was higher than that of normal mice (Harp et al., 1992). Intestinal flora also regulates many physiological processes in the body, such as metabolism and immunity (Brestoff and Artis, 2013; Knaus et al., 2017). Recently, there has been a growing interest in the study of the influence of parasite infections on the gut microbiome. However, the change in intestinal flora during the progression of T. gondii infection from the acute to chronic stage is not yet well understood. In this study, we investigated the intestinal flora of mice at 13- and 21-days post infection with T. gondii using analysis of the 16S rRNA gene sequence determined with high-throughput sequencing technology. Our results found that T. gondii infection altered intestinal flora in early stage infections and suggested that intestinal 4
flora could play an important role in the host defense against disease progression and contribute to the improvement of enteritis. 2. Materials and methods 2.1Mice. Female BALB/c mice (n = 30), 6-week-age, were randomly divided into three treatment groups (n = 10/group): infection for thirteen days, infection for twenty-one-days, and the uninfected control group. Mice were orally infected with 100 purified sporulated ME49 strain oocysts (from Jiang Su Institute of Parasitic Disease) suspended in sterile phosphate buffered solution (PBS) 0.5ml while controls were infected with a same volume of sterile PBS containing no oocysts. All mice had ad libitum access to disinfected feed and water. 2.2 Sample collection Three groups were respectively euthanized on day 0 (before infection), 13 days and 21 days post infection prior to harvesting of cecum contents. Three mice were randomly selected from each group to collect the cecal contents. Cecal contents were aseptically collected and stored at -80°C until extraction of bacterial extraction. 2.3. 16S rRNA amplification PCR amplification of the bacterial 16S rRNA genes (V3–V4 region) was carried out using
the
following
sequences
for
the
forward
primer
338F
(5 ′
-ACTCCTACGGGAGGCAGCA-3 ′ ) and the reverse primer 806R (5 ′ -GGACTACHVGGGTWTCTAAT-3′). PCR reaction we designed was in a 25ul reaction system that has 5 μl Q5 reaction buffer (5×), 5 μl Q5 High-Fidelity GC buffer 5
(5×), 0.25 μl Q5 High-Fidelity DNA polymerase (5 U/μl), 2 μl dNTPs (2.5 mM), 1 μl of each forward and reverse primers (10 μM), 2 μl DNA template, and 8.75 μl ddH2O. The PCR conditions used had an initial denaturation at 95 °C for 2 min, followed by 25 cycles of denaturation at 95 °C for 30 s, annealing at 55 °C for 30 s and elongation at 72 °C for 45 s, with a final augmentation stage at 72 °C for 10 min. The products of PCR were purified using Ageuncourt AMPure Beads (Beckman Coulter, Indianapolis, IN, United States). The concentration of the PCR products was assessed by PicoGreen dsDNA Assay Kit (Invitrogen, Carlsbad, CA, United States). 2.4. Bioinformatics' analysis of sequencing data Illumina MiSeq Paired-end sequencing was used to determine the sequences of the amplified 16S RNA genes. The OTU whose abundance value is less than 0.001% (1/100,000) of the total sequencing amount of all samples is removed, and the abundance matrix of the rare OTU is used for subsequent analysis. The 16S rRNA gene sequencing data was clustered with a 97% similarity into Operational Taxonomic Units (OTUs). . In order to compare the diversity of different samples, we did the rarefaction , which is a homogenization method that is used to randomly draw OTUs to the same quantity based on a minimum value (90%), so as to correct the diversity difference caused by sequencing depth. Finally, depth statistics and visualization analysis of the species composition for all samples were determined. Concrete analysis of different categorical levels and significant difference between groups were also performed. Principal component analysis (PCA) uses linear transformation to combine the original high-dimensional data (such as the OTU abundance matrix) into 6
a lower-dimensional space coordinate system (i.e. principal component) to simplify the data structure and display the natural distribution of the samples. Nonmetric Multidimensional Scaling (NMDS) simplified the data structure by reducing the number of dimensions and, reordering the samples into a new low-dimensional coordinate system, that describes the distribution characteristics of the samples at a specific distance scale, such as Unweighted UniFrac distance. The R software package was used to conduct a NMDS analysis for Unweighted and Weighted Unirac distance matrix. 2.5. Statistical analyses Metagenomic inferences and Kyoto Encyclopedia for Genes and Genomics (KEGG) classifications were performed with the PICRUST package (Langille et al., 2013) with statistical analyses done with R Software. Alpha diversity index analyses of the samples were conducted using QIIME to calculate the Shannon index, Simpson Index, and Ace Index. 3. Results 3.1 T. gondii infection is associated with bacterial diversity in the intestine The bacterial diversity was assessed by analysis of the OTU in each group of samples. The number of observed OTUs in the control samples was less than for the T. gondii infected intestine samples after thirteen days, but more than that those from T. gondii infected intestine after twenty-one days (Figure 1A). Intestine samples at thirteen days post-infection with T. gondii had a higher sample richness that was also reflected by the abundance Ace index and Chao index (Table 1). Within treatment 7
groups, the bacterial diversity could be assessed by the Simpson index and Shannon diversity index, which demonstrated that the bacterial diversity increased for the T. gondii infected intestine after thirteen days compared to the control ones, but that the bacterial diversity of T. gondii infected intestine after twenty-one days was less than for the control ones. In summary, these data point to a more diverse bacterial population in the T. gondii infected mouse at thirteen days compared to the control ones, but the control one has more diverse bacterial population than the T. gondii infected mouse after twenty-one days. 3.2 The ceca microbiome composition is significantly altered in the T. gondii infected mouse In order to examine the global differences in bacterial composition between mice that were infected with T. gondii and the uninfected controls, we performed a nonmetric multidimensional scaling (NMDS) analysis of all samples using the UniFrac distance. NMDS is a powerful ordination method that can uncover nonlinear relationships between samples and is widely used in ecology. The results showed that there was differential grouping of the control samples in the center of the graph, while samples from mice at 13 days post infection with T. gondii were more dispersed and grouped to the right. Mice infected for 21 days were grouped to the left (Figure 1B). PLS-DA analysis is a supervised pattern recognition method based on a partial least squares regression model to analyze data. As shown at Figure 1C, the three models did not co-localize confirming that samples from mice infected by T. gondii clustered differently to those from controls (Figure 1C). Sample data for 21 days of infection 8
were more intensive than those for the control group. To uncover relationships based on the presence or absence of bacterial groups as well as their phylogenetic relatedness, we performed a principal coordinates analysis of the samples using the phylogenetic-tree-based unweighted Unifrac metric. As shown in Figure 1D, there was a separation between samples from T. gondii infected mice and the controls using principal component PC2 (15.62% of the explained variance) and mice infected by T. gondii for thirteen days and those infected for twenty-one days are parted by the PC1 (24.56% of the explained variance). 3.3 Comparison of the intestinal microbiome at different taxonomic levels Statistical analysis of the intestinal microbiome structure of the three groups in each taxonomic classification level was carried out on the basis of the out data (Figure 2). The composition of the entire microbiome for each group is shown at the phylum level by Figure 2 and Figure 3A. The bacteria in the control samples at the phylum level belonged to the Firmicutes (60.0%), with Bacteroidetes (30.1%), Proteobacteria (4.2%), TM7 (3.6%), Verrucomicrobia (1.3%), and Tenericute (0.6%). In all T. gondii infected mice, the proportional composition for Bacteroidetes decreased (13-day group 23.4%, 21-day group 24.7%), as did the proportion of Firmicutes (41.37%), Bacteroidetes (24.7%), TM7 (1.5%), and actinobacteria (0.6%). Conversely, the proportion of proteobacteria (31.2%) increased in the mice that were infected by T. gondii after thirteen days compared to the controls. In the 21-day post-infection group the Firmicutes (66.67%) were enriched while the proportion of Bacteroidetes (23.4%), proteobacteria (3.5%) TM7 (1.23%) and Tenericute (0.03%) were decreased in T. 9
gondii infected mice after twenty-one days compared to the uninfected controls (Figure 3A). When comparing the microbiome at the family and genus level by relative abundance, the organisms in uninfected mice were found to be the Lactobacillaceae (26.9%), the S24-7 (23%) and the Clostridiales (18.5%), followed by the Lachnospiraceae (8.13%), Desulfovibrionaceae (2.23%) and Ruminococcaceae (3.83%). In the T. gondii infected mice at 13 days post-infection，when compared with the uninfected controls the relative abundance of Lactobacillus from Lactobacillaceae, and the S24-7 from Bacteroidales decreased, while that of Desulfovibrio from Desulfovibrionaceae
(26.9%),
Bilophila
from
Desulfovibrionaceae
(2.7%),
Ruminococcus from Ruminococcaceae (3.6%) increased. Compared to the controls, mice that were infected with T. gondii for 21 days, had an increase in the proportion of lactobacillus from Lactobacillaceae; Rikenella from Rikenellaceae, Odoribacter from Odoribacteraceae, while the S24-7, Clostridiales, Desulfovibrio, and the Lachnospiraceae decreased (Figure 3B and Figure 4). 3.4 Comparison of cecal bacterial functional abundance profile In order to estimate the difference in bacterial function between the treatment groups, we conducted a PICRUSt (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States) analysis. The PICRUSt software package predicts the bacterial function by comparing the existing 16S rRNA gene sequencing data with a microbial reference genome database where metabolic functions have been defined. KEGG Database analysis determined that the mice that were infected 10
by T. gondii for thirteen days had a higher probability of acquiring Neurodegenerative Disease than the control mice and the treatment group infected with T. gondii for twenty-one days. However, mice that were infected by T. gondii for thirteen days were less likely to get the Immune System Diseases than the control mice and those infected with T. gondii for twenty-one days. (Figure 5). In the Metabolism aspect, the mice that were infected by T. gondii for thirteen days has fewer bacteria involved Carbohydrate Metabolism, Enzyme Families, Xenobiotics Biodegradation and Metabolism, Lipid Metabolism abundance than the control mice and the mice infected T. gondii twenty-one days. About the cecal bacteria’s influence on the organismal system, the T. gondii infected mice had fewer bacteria about Nervous System and Excretory System, but had more bacteria about the Immune System than the control mice. The mice that were infected by T. gondii for thirteen days had a higher bacterial abundance associated with Environmental Adaptation.
4. Discussion T. gondii is an obligate intracellular parasite that can infect any nucleated avian or mammalian cell (Robert-Gangneux and Dardé, 2012). In mice, T. gondii replicates agamically in two different forms: the rapidly replicating tachyzoite form; and the bradyzoite form, which grows more slowly within intracellular cyst structures. Tachyzoites occur during acute infection, and after a period of infection, tachyzoites become bradyzoites. The bradyzoite growth induces a tissue cyst, which can then enter the muscles and nerves (Dubey, 1998). 11
The mechanism of intestinal inflammation and intestinal dysfunction caused by parasite infection is closely related to the change in intestinal flora (Partida-Rodriguez et al., 2017). In this study, we investigated the intestinal flora of mice infected with T. gondii. At thirteen days post-infection, T. gondii parasite has recently left the intestinal tract, however the intestinal flora has not yet completely recovered. Compared with normal intestinal flora, there were more opportunistic pathogens in the mice at thirteen days post-infection. For example, these mice had a higher proportion of Proteobacteria in their intestinal flora, which include a large number of opportunistic pathogens, such as Escherichia coli, Salmonella and Campylobacter (Rizzatti et al., 2017). Most intestinal bacteria are obligate anaerobes, but Proteobacteria are facultative anaerobic bacteria. The increase in Proteobacteria will alter the overall structure of the intestinal flora (Shin et al., 2015). In many hosts, the relative abundance of Proteobacteria is considered to be associated with ecological imbalance in intestinal flora in enteritis hosts and serves as a marker for the instability of intestinal flora (Walker et al., 2011). Indeed, the severity of colitis is positively correlated with the abundance of Proteobacteria (Maharshak et al., 2013). With induction of inflammation, the associated secretion of inflammatory molecules and the concomitant changes in the intestinal environment are also conducive to a large expansion of Proteobacteria. As a result, the structure of intestinal flora changes, and the number of Firmicutes and Bacteroides is known to decrease (Carvalho et al., 2012), consistent with our results. However, some studies indicated that an increase in the relative abundance of facultative anaerobes such as Proteobacteria, can assist the 12
colonization of beneficial obligate anaerobes. As the body recovers from the inflammation, Proteobacteria are quickly replaced by beneficial obligate anaerobes, so parasitic infections can improve the overall intestinal environment and alleviate enteritis(Davis et al., 2017). Therefore, the increase in Proteobacteria is not necessarily harmful; it could serve to regulate the structure of the flora, ultimately inducing a healthier intestinal microbiome.(Mirpuri et al., 2014) Except for Proteobacteria, In, wewe found that the abundance of Desulfovibrio and Bilophila increased significantly (26.9% and 2.2% respectively) at thirteen-days post-infection, above that of control group and the 23-day post-infection group. Desulfovibrio, that is the main component of sulfate-reducing bacteria (SRB) in the intestine (Christophersen et al., 2011) , are usually found to be increased in enteritis (Rowan et al., 2010). Most SRB use sulfate or other sulfur compounds such as thiosulfate, sulfite and sulfur as the terminal electron acceptor during anaerobic respiration. Hydrogen sulfide, the main product of SRB metabolism, is toxic to human cells, damaging DNA and, inhibiting oxidizing (Short-chain fatty acids SCFA ) and its protective properties (Attene-Ramos et al., 2010; Carbonero et al., 2012). It can also destroy the function of the epithelial barrier by weakening the oxidation of butyrate, which leads to the specific inflammatory response of Inflammatory bowel disease (IBD)(Roediger et al., 1997). Mucosal barriers are also attenuated which reduces the protective effect of intestinal epithelium (Gibson et al., 1993; Wyatt et al., 1993). In addition to the effects of sulfides, extracellular polymers produced by SRB are species-specific and may contain highly immunogenic components, such as O‐ 13
antigenic portions of lipopolysaccharides (Beech and C. Tapper, 1999). These antigens elicit an immune response in genetically susceptible individuals and initiate or contribute to the inflammatory process of Ulcerative Colitis (UC) (Hisamatsu et al., 2013). Thus, we speculated that Desulfovibrio may play an important role in the process by which Toxoplasma infection causes enteritis, through destruction of the epithelial barrier, along with other toxic effects of hydrogen sulfide. One representative of Bilophila is Bilophila wadsworthia, a Gram-negative anaerobic bacterium that accounts for less than 0.1% of the intestinal microbiota in healthy animals (Baron, 1997). However, this bacterial species is increased in the intestinal tract of patients with colitis and intestinal cancer (Scanlan et al., 2009), and is considered to be an opportunistic pathogen in the gut (da Silva et al., 2008). Bilophila wadsworthia is similar to Desulfovibrio (Laue et al., 1997), uniquely using taurine-derived sulfite as an electron acceptor to perform anaerobic respiration. (Laue et al., 2001). Taurine respiration produces sulfide, which has a toxic effect on colonic epithelial cells, and is thought to play a role in inflammatory bowel diseases (CAMPIERI and GIONCHETTI, 2001). Bile is not only a very effective digestive juice, but also has effective antimicrobial properties, assisting in the selection or exclusion of potential intestinal microorganisms and protozoa, such as Giardia, Microsporidia and Cryptosporidium. However, some bacteria like B. wadsworthia have anti-biliary effects and reproduce better in the presence of bile (Ananieva et al., 2002). Such symbiotic relationships can help pathogens to establish a niche in the intestine (Devkota et al., 2012) and may create conditions conducive to the early 14
colonization of T. gondii in the intestinal tract (Chen et al., 2018). In addition to the proinflammatory effects within the intestine, B. wadsworthia promotes intestinal barrier defects, systemic inflammation, bile acid metabolism disorders, and changes in overall microbial functional characteristics (Natividad et al., 2018). However, after a longer period of time, when T. gondii has left the intestine, Bilophila was no longer detected in the group 21-days post-infection. This indicated that the effect of T. gondii on the intestinal tract is not sustained after disease progression, with the inflammation of the intestines slowly improving, and the intestinal microbial structure returning to its healthy composition. A low F/B (Firmicutes/Bacteroides) index is associated with a variety of diseases, such as irritable bowel syndrome (IBS) (Collins, 2014) and inflammatory bowel disease (IBD) (Tamboli et al., 2004). Compared with 13-day post-infection group, our results showed that F/B index rises in the 21-day post-infection group. The proportion of Proteobacteria also decreased from 31.2% (13 days) to 3.17% (21 days), which was lower than for the control group (4.17%). These results indicated that the intestinal flora of the twenty-one-day group was greatly recovered, with the chance of the growth of pathogenic bacteria being reduced, and the overall intestinal environment improving.Lactobacillus can regulate the secretion of cytokines by immune cells. IL-10, secreted by Treg cells, and IL-17 and IL-22 secreted by Th17 cells, are important immune signaling molecules for maintaining intestinal homeostasis (Liu et al., 2009). Lactobacillus acidophilus can restore the balance of inflammatory cytokines and Th17/Treg cells in the gut of mice with dextran sulfate-induced colitis (Park et al., 2018). Lactobacillus can also restore 15
intestinal barrier function (Mao et al., 1996), reducing the permeability of the intestinal epithelium (Mangell et al., 2002) by promoting the secretion of tight junction proteins in epithelial cells (Karczewski et al., 2010). These bacteria can also reduce endotoxin levels in the blood (Xue et al., 2017) and down-regulate the level of interleukin-8 secretion, thus playing an anti-inflammatory role (Pan et al., 2018). A variety of lactic acid bacteria have also been shown to effective treatments for symptoms of bowel cancer (Lenoir et al., 2016), enteritis (Khazaie et al., 2012) and irritable bowel syndrome (Clarke et al., 2012). Our results show that the lactobacilli component of the gut microbiome is increased in the 21-day post-infection group compared with the control group. This further indicates that the intestinal flora rapidly recovers after the T. gondii parasite leaves the intestine and the resulting gut flora was healthier and more beneficial than the original biome in the control group, containing fewer pathogens and having a better resistance to intestinal diseases. Some studies have shown that probiotics, such as Lactobacillus, can have a therapeutic effect on brain disease, through the brain-gut axis, but the mechanism of this action still needs to be confirmed (Brenner et al., 2017; Mancuso and Santangelo, 2018). Since in chronic T. gondii infections, the parasite eventually colonizes the brain, the increase in lactic acid bacteria may also inhibit the progression of T. gondii infection and may be a natural defense mechanism of the body. In a word, we our results showed the alterations in the gut microbes of BALB/c mice infected with T. gondii, where we observed a significant shift in the relative abundance of cecal bacteria. On the thirteenth day post-infection, the intestinal flora 16
was different from that of healthy mice, with the number of harmful bacteria, such as bilophila increasing. By the 21st day post-infection, the intestinal flora had partially recovered, with the harmful bacteria, such as bilophila, decreasing, such that the intestinal flora is similar to that of healthy mice, but not completely identical. And the mice at 21 days post-infection with T. gondii, had more beneficial intestinal bacteria than the control group, such as Lactobacillus. Based on our results that the intestinal flora can be restructured during infection with T. gondii and the existing literature on the role of intestinal microflora in health and disease, our study suggests that intestinal flora could play an important role in the infection of T. gondii. But whether these changes are involved in the parasitism and pathology of T. gondii needs further investigation.
Conflict of Interest Statement The authors declare they have no competing interests.
Author Contributions Statement The study was conceived and designed by YY and LMY, YY and ZYH performed the experiments. SDY , YY and TMW analyzed the data. SDY and BX wrote the manuscript.. TMW, ZYY, LCY, LXL, GX and CW improved the manuscript. All authors read and approved the final manuscript.
Conflict of Interest Statement The authors declare they have no competing interests.
17
Acknowledgements This study was supported by The National Key Research and Development Program of China (2018YFD0502202, 2017YFD0501302, 2017YFC1601206,); Jilin Provincial Science and Technology Development Project（20180520042JH），scientific fund from Health and Family Planning Commission of Wuxi (No. Q201640) and the Fundamental Research Funds for the Central Universities , JLU..
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Figure 1 Alterations in gut microbiota caused by Toxoplasma gondii infection. A. Venn diagram showing overlap in OTUs with differential abundance in control, mice 13 days, and 21 days post-infection with Toxoplasma gondii. B. NMDS (Nonmetric Multidimensional Scaling) showing the difference in bacterial communities according to the Unweighted Unifrac distance. C. PLS-DA showing that there are significant differences between the three treatment groups. D. PCA of the unweighted UniFrac values for samples from infected and control mice. Each point represents the gut microbiota for each group.
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Figure 2 Community structure of bacteria from different treatment groups in each taxonomic classification level. The percentage and distribution of bacterial communities were showed at the taxonomic classification level of kingdom, phylum, class, order, family, genus and species through the number of concentric circles from inside to outside. Statistically significant difference between groups (p<0.05).
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Figure 3 Community structure of bacteria from different treatment groups in different taxonomic classification level. A. Community structure of bacteria from different treatment groups in phylum level. B. Community structure of bacteria from different treatment groups in family level.
Figure 4 Bacterial distribution of the top 100 most abundant genera among the nine treatment samples. Double hierarchical dendrogram shows the bacterial distribution. The heatmap plot depicts the relative percentage of each bacterial genus within each sample. The relative values for bacterial family are indicated by color intensity with the legend indicated under the heatmap
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Figure 5 KEGG functional classification. The red bars represent the control group. The blue bars represent the infected 13-day group. The green bars represent the infected 21-day group.
25
Table 1 Estimators of per group’s sequence diversity and richness. Sample id
Reads
0.90
Ace
Chao1
Shannon
coverage
Simpson
CK_1
887.35
587.00
5.70
0.990899
0.942799
CK_2
1219.88
825.00
6.31
0.999248
0.961652
CK_3
1249.63
1007.00
6.66
0.999367
0.959456
Tg_13_1
1903.79
1180.00
6.22
0.999418
0.907526
Tg_13_2
1589.19
1007.00
6.24
0.999355
0.953486
Tg_13_3
1463.70
1230.00
6.79
0.999413
0.927441
Tg_21_1
793.27
614.00
4.14
0.998984
0.723298
Tg_21_2
1124.87
950.00
6.47
0.999290
0.929651
Tg_21_3
856.30
625.00
4.18
0.998971
0.752064
26