key: cord-0270590-6wkzz8tx authors: Yawen, Zong; Lei, Cheng; Xiangyun, Cheng; Binyou, Liao; Xingchen, Ye; Taiping, Liu; Jiyao, Li; Xuedong, Zhou; Wenyue, Xu; Biao, Ren title: The dynamic landscape of parasitaemia dependent intestinal microbiota shifting at species level and the correlated gut transcriptome during Plasmodium yoelii infection date: 2020-12-18 journal: bioRxiv DOI: 10.1101/2020.12.17.423374 sha: fc44224bbac6856c5ee7082499067d832155ae40 doc_id: 270590 cord_uid: 6wkzz8tx Background Malaria, caused by Plasmodium, is a global life-threatening infection disease especially during the COVID-19 pandemic. However, it is still unclear about the dynamic change and the interactions between intestinal microbiota and host immunity. Here, we investigated the change of intestinal microbiome and transcriptome during the whole Plasmodium infection process in mice to analyze the dynamic landscape of parasitaemia dependent intestinal microbiota shifting and related to host immunity. Results There were significant parasitaemia dependent changes of intestinal microbiota and transcriptome, and the microbiota was significantly correlated to the intestinal immunity. We found that (i) the diversity and composition of the intestinal microbiota represented a significant correlation along with the Plasmodium infection in family, genus and species level; (ii) the up-regulated genes from the intestinal transcriptome were mainly enriched in immune cell differentiation pathways along with the malaria development, particularly, naive CD4+ T cells differentiation; (iii) the abundance of the parasitaemia phase-specific microbiota represented a high correlation with the phase-specific immune cells development, particularly, Th1 cell with family Bacteroidales BS11 gut group, genera Prevotella 9, Ruminococcaceae UCG 008, Moryella and specie Sutterella*, Th2 cell with specie Sutterella*, Th17 cell with family Peptococcaceae, genus Lachnospiraceae FCS020 group and spices Ruminococcus 1*, Ruminococcus UGG 014* and Eubacterium plexicaudatum ASF492, Tfh and B cell with genera Moryella and species Erysipelotrichaceae bacterium canine oral taxon 255. Conclusion There was a remarkable dynamic landscape of the parasitaemia dependent shifting of intestinal microbiota and immunity, and a notable correlation between the abundance of intestinal microbiota. intestinal microbiota and immunity, and a notable correlation between the abundance of intestinal microbiota. [15] demonstrated that both Plasmodium spp. and human intestinal microbe E. coli O86:B7 could express α-gal as the anti-α-gal Abs were associated with the protection against malaria transmission in human after colonization of E. coli O86:B7. In addition to 16S rDNA sequencing, Stough JM and colleagues [16] combined transcriptome of whole ceca and metabolomics of contents to determine related microbiota. Moreover, Joshua ED et at [17] found that the effect of severe malaria on microbial homeostasis was greater than mild malaria using metabolomics. core OTUs from all of the four groups (Fig.2b) . Similar with OTU counts, alpha diversity of mice intestinal microbiome increased along with parasitaemia rates (Fig.2c) . Meanwhile, the community diversity and parasitaemia showed a positive correlation during the P. yoelii infectious phase until to the parasitaemia peak point (Fig.2d) . Interestingly, the diversity recovered a little but with no statistical differences when the prarasitaema rates returned to 0% (Fig.2c) The comparison rates were 78.53%-97.50%. The correlation coefficient from the sequencing samples based on gene expression revealed that samples were in good reliability and rationality (Fig.S1 ). According to the Principal component analysis (PCA analysis), malaria procession significantly affected the mice intestinal gene expression (Fig.4a ). There were 22 core genes representing significant difference along with the malaria process (Fig.4b) .The number of the differently expressed genes at 10 % and 50% parasitaemia was significantly increased comparing with uninfected samples, while was reduced when the parasitaemia recovered to 0% (Fig.4c ). There were 42.36% and 72.32% of those genes up-regulated when parasitaemia was at 10% and 50% respectively (Fig.S2 ). The similarity between M3 group (recovered group) and C group (uninfected group) was extremely higher than that from M1 (10% parasitaemia) and M2 (50% parasitaemia) groups (Fig.S3) , indicating that the intestinal response was highly corelated to the infectious states. Fig.5b) . However, the expression of the above genes showed a downward trend along with the malaria process ( Fig.5b) Fig.5b) suggesting that Th2 might only appear in early host immune response after P. yoelii infection. Th17 cell was only activated at 50 parasitaemia according to the up-regulation of Il21 and Rorc genes (Tab.1, Tab.S3 and Fig.5b ) indicating that Th17 cell was an essential immune executor with TGF-β production. Intestinal microbiota was correlated with the host immune response against We then analyzed the relationship between intestinal microbiota at family, genus and species levels and host immunity by calculating person index (Fig.7) . At family level, Bacteroidales BS11 gut group was only detected at 10% parasitaemia (Fig.3a) and it was in a high-correlation with the expression of Cd40lg, Icos, Il10, Il12a, Il12b and Stat4 (Fig.7) indicated that Bacteroidales BS11 gut group was Peptococcaceae and genus Lachnospiraceae FCS020 group whose abundance were significant higher in 50% parasitaemia (Fig.3b, 3c and Fig.7) , indicated that Peptococcaceae and Lachnospiraceae FCS020 group were related with Th17 cells in later host immune response against P. yoelii infection. The genus Sutterella* was high-correlated with Stat4, Tbx21, Gata3 and Il4, genes coding master transcription factors of IFN-γ+ Th1 and IL-4+ Th2 cells differentiation (Fig.7) . The abundance of Sutterella* significantly reduced from 10% to 50% parasitaemia (Fig.3c) suggested that the early activation of Th1/Th2 cells and the reduce of IFN-γ and IL-4 along with the development of parasitaemia were related to the abundance change of Sutterella*. Erysipelotrichaceae bacterium canine oral taxon 255 were in a high correlation with Tfh and B cells activation in early host immune response (Fig.7) . Another several species, including Ruminococcus 1*, Ruminococcus UGG 014* and Eubacterium plexicaudatum ASF492, were highly correlated with Rorc expression (Fig.7) and the abundance of these three species was dominant when the parasitaemia reached to the peak (Fig.3c) . (Fig.S4) , which might be caused by the shifted microbiome and the activation of host immune [22] . The intestinal microbiota was also highly correlated with the activation of certain immune 125bp/150bp paired-end reads were generated. Trimmomatic [47] was used to perform quality control. Then the clean reads were mapped to reference genome using hisat [48] . FPKM [49] value of each gene was calculated using cufflinks [50] and the read counts of each gene were obtained by htseq count [51] . Additional file1: Table S1 . Anosim analysis of NMDS. Table S2 . Kruskal-Wallis Test of intestinal microbial relative abundance on family level. Figure S1 . Inter-sample correlation. The abscissa represents the sample name, and the ordinate represents the corresponding sample name. Blue: samples with high correlation coefficient; white: low correlation coefficient among samples. Table S3 . Expression of genes related to host immunity with statistical differences. The X axis shows rich factor while the left vertical axis lists different gene pathways. The larger the bubble is, the more the number of differential protein coding genes contained in the entry. The P-value legend reveals the degree of enrichment significance. The bubble color changes comply red to blue while P-value increasing. Gut microbiota elicits a protective immune response against malaria transmission Diferential Sensitivity to Plasmodium yoelii Infection in C57BL/6 Mice Impacts Gut-Liver Axis Homeostasis Multiview learning for understanding functional multiomics The MultiOmics Explainer: explaining omics results in the context of a pathway/genome database Multiomics modeling of the immunome, transcriptome, microbiome CD4 T-cell subsets in malaria TH1/TH2 revisited. Front Immunol Insights into malaria pathogenesis gained from host metabolomics Plasmodium berghei ANKA causes intestinal malaria associated with dysbiosis Linkage maps from multiple genetic crosses and loci linked to growth-related virulent phenotype in Plasmodium yoelii Role of IFN-gamma in lethal and nonlethal malaria in susceptible and resistant murine hosts Frequencies of CD4+ T cells reactive with Plasmodium chabaudi chabaudi: distinct response kinetics for cells with Th1 and Th2 characteristics during infection Differential induction of helper T cell subsets during blood-stage T-bet modulates the antibody response and immune protection during murine malaria Differential role of T regulatory and Th17 in Swiss mice infected with Plasmodium berghei ANKA and Plasmodium yoelii Development of experimental cerebral malaria is independent of IL-23 and IL-17 Plasmodium yoelii infection of BALB/c mice results in expansion rather than induction of CD4(+) Foxp3(+) regulatory T cells Phenotypic and functional profiling of CD4 T cell compartment in distinct populations of healthy adults with different antigenic exposure Malaria antigen-mediated enhancement of interleukin-21 adults Interaction between microbiota and immunity in health and disease The Th17 Lineage: From Barrier Surfaces Homeostasis to Autoimmunity, Cancer, and HIV-1 Pathogenesis T-cell recognition of a cross-reactive antigen(s) in erythrocyte stages of Plasmodium falciparum and Plasmodium yoelii: inhibition of parasitemia by this antigen(s) The gut microbiota is associated with immune cell dynamics in humans Gut microbiota, metabolites and host immunity Bacterial metabolism of bile acids promotes generation of peripheral regulatory T cells Interaction between microbiota and immunity in health and disease Worldwide malaria incidence and cancer mortality are inversely associated. Infect Agent Cancer Attenuated plasmodium sporozoite expressing MAGE-A3 induces antigen-specific CD8+ T cell response against lung cancer in mice Association of Fusobacterium nucleatum with immunity and molecular alterations in colorectal cancer The Complex Puzzle of Interactions Among Functional Food, Gut Microbiota, and Colorectal Cancer Vertical distribution of the soil microbiota along a successional gradient in a glacier forefield Trimmomatic: a flexible trimmer for Illumina sequence data HISAT: a fast spliced aligner with low memory requirements Improving RNA-Seq expression estimates by correcting for fragment bias Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation HTSeq--a Python framework to work with high-throughput sequencing data Differential expression of RNA Seq data at the gene level the DESeq package KEGG for linking genomes to life and the environment Animal ethical statement (AMUWEC2019000) approved by Laboratory Animal Welfare Ethics Committee of the Third Military Medical University. Not applicable. The authors declare that they have no competing interests.