Integrated metabolomic and microbiome analysis identifies Cupriavidus metallidurans as a potential therapeutic target for β-thalassemia

Integrated metabolomic and microbiome analysis identifies Cupriavidus metallidurans as a potential therapeutic target for β-thalassemia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Integrated metabolomic and microbiome analysis identifies Cupriavidus metallidurans as a potential therapeutic target for β-thalassemia Xianfeng Guo, Xuchao Zhang, Min Li, Yuanliang Peng, Zi Wang, Jing Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4651050/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Oct, 2024 Read the published version in Annals of Hematology → Version 1 posted 9 You are reading this latest preprint version Abstract β-thalassemia(β-TH) is an inherited hemoglobin disorder marked by ineffective erythropoiesis, anemia, splenomegaly, and systemic iron overload, predominantly affecting developing countries in tropical and subtropical regions. Despite extensive research on its pathogenesis, the interactions between gut microbiota and metabolites in β-TH remain poorly understood. This study compares fecal metabolomics and metagenomics between wildtype (WT) and heterozygous Th3/+ mice, a model for non-transfusion-dependent β-thalassemia intermedia. Our results show increased intestinal bilirubin metabolism, with significant elevations in metabolites such as biliverdin, bilirubin, and stercobilin. Metagenomic analysis revealed notable differences in bacterial composition between Th3/+ and WT mice. Specifically, Cupriavidus metallidurans was identified as a key bacterium that mitigates anemia by reducing liver and spleen iron deposition. This is the first study to ameliorate anemia in mice by altering gut microbiota, presenting new strategies for β-TH management. Metabolomics Metagenome β-thalassemia Cupriavidus metallidurans Anemia Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction β-thalassaemia (β-TH) is the most common autosomal recessive blood disorder caused by mutations in the β-globin gene located on chromosome 11 [ 1 ]. Approximately 60,000 newborns are affected annually worldwide, predominantly in developing countries, accounting for about 1.5% of the global population (80–90 million people) [ 2 ]. Hemolysis is a hallmark of β-TH, resulting from an imbalance in the production of β-globin chains (decreased or absent) and normal alpha chains, leading to the precipitation of alpha chains and red cell damage. Ineffective erythropoiesis further increases erythroferrone production, suppresses hepcidin, and consequently enhances iron absorption and disrupts bone metabolism [ 3 ]. Hemolysis leads to the excretion of large amounts of bilirubin into the intestines. Bilirubin, historically regarded as a waste product of heme catabolism [ 4 ], plays a significant role in the pathophysiology of β-TH as a hemolytic disease [ 5 ]. The rupture of erythrocytes in β-TH increases serum levels of total and unconjugated bilirubin due to the oxidation of free hemoglobin's heme moiety [ 6 ]. Normally, bilirubin is conjugated to glucuronic acid, forming a soluble compound excreted as urobilinogen [ 7 ]. However, patients with β-TH have impaired liver function, reducing their ability to metabolize bilirubin, resulting in increased intestinal concentrations [8 , 9]. Intestinal bacteria degrade bilirubin to urobilinogen; half of these entities are reabsorbed into the circulation via the portal system for renal excretion, while the remainder is converted to stercobilinogen for fecal excretion [ 10 ]. The catabolism of bilirubin to urobilinoids regulates specific gut bacteria, maintaining homeostasis [ 11 ]. Fecal microbiota transplantation (FMT) has emerged as a prominent research area in recent years [12 , 13]. We hypothesized that FMT could standardize gut microbiota in Th3/+ mice and controls, thereby highlighting β-TH's impact on gut microbiota. Studying the effect of intestinal flora on the phenotype may provide novel treatments for β-TH. Limited research exists on the gut microbiota in β-TH, and the mechanistic link between gut microbiota alterations and β-TH pathogenesis remains unclear. Given that various circulating metabolites act as intermediaries between the gut microbiome and host biology [14 , 15], integrated analyses of microbial metabolites, gut microbiome, and host phenotype may offer promising strategies to elucidate β-TH's development mechanisms. In this study, we performed integrative metagenomic and metabolomic analyses to identify potential links between gut microbial composition and clinical phenotypes in β-TH. Our dual-omics analysis indicates that dysfunctional bilirubin metabolism, characterized by excess bilirubin, stercobilin, and biliverdin, along with disturbances in gut microbial ecology, is associated with β-TH anemia. Materials and Methods Mice Wild-type C57BL/6 (WT) mice were obtained from Hunan SJA Laboratory Animal Co. Ltd. β-Thalassemia (Th3/+) mice with a C57BL/6 background were originally purchased from Jackson Laboratories. Male Th3/+) and female WT C57BL/6 mice were crossbred to produce β-TH and WT littermates at Central South University Laboratory Animal Center. All experiments were conducted using 8-10-week-old virgin female mice unless otherwise noted. Mice received Cupriavidus metallidurans via gavage three times weekly and were sacrificed two days after the last administration. All experiments were approved by the Animal Ethics Committee of Central South University and conformed to relevant regulatory standards at Central South University Laboratory Animal Center. Metabolomic analysis of fecal samples Untargeted metabolomics profiling was performed on the XploreMET platform (Novogene, China). Samples were prepared following previously reported procedures with minor modifications [ 16 ]. Raw data generated by GC-TOF/MS were processed using XploreMET 3.0. Metagenomic sequencing Metagenomic sequencing was performed as previously described [ 17 ]. DNA (1 µg/sample) was used for sample preparation. Quality control (QC) for DNA samples involved two main methods: (A) DNA degradation degree and potential contamination were monitored on 1% agarose gels. (B) DNA concentration was measured using a Qubit dsDNA assay kit in a Qubit 2.0 fluorometer (Life Technologies, CA, USA). DNA samples with an OD value between 1.8 and 2.0 and contents above 1 µg were used to construct the library. Sequencing libraries were generated using the NEBNext Ultra™ DNA library prep kit for Illumina (NEB, USA) following the manufacturer’s recommendations, with index codes added to attribute sequences to each sample. PCR products were purified, and libraries were analyzed for size distribution using an Agilent 2100 Bioanalyzer and quantified by real-time PCR. The clustering of the index-coded samples was performed on a cBot Cluster Generation System according to the manufacturer’s instructions. After cluster generation, libraries were sequenced on an Illumina HiSeq platform, and paired-end reads were generated. High-quality reads for the ten samples were obtained, averaging 10,583.04 Mbp. Taxonomic classification and functional annotation were analyzed following previously reported procedures with minor modifications [ 18 ]. Fecal microbiota transplantation experiment, and sample collection Fresh stool from Th3/+ and WT mice was collected separately, then mixed and suspended in PBS (10 mL) (phosphate-buffered saline). The suspension was filtered using 70 µm strainers, and the filtrate was centrifuged at 2000 rpm for 10 minutes. After removing the supernatant, the remaining pellet was resuspended in 2 mL of PBS. This mixture was used for fecal microbiota transplantation by gavage (200 µL per mouse). Prior to gavage, all mice were treated with a cocktail of broad-spectrum antibiotics including ampicillin (0.2 g/L), vancomycin (0.1 g/L), neomycin (0.2 g/L), and metronidazole (0.2 g/L) in drinking water for two weeks. Subsequently, FMT was performed on Th3/+ and WT mice, with mice receiving a fecal suspension by gavage three times weekly for six weeks. Quantitative real-time polymerase chain reaction (qPCR) Fecal DNA was isolated using a HiPure Stool DNA Kit (Magen, Guangzhou, China). Total bacteria were identified using primers 1492R (GGTTACCTTGTTACGACTT) and 27F (AGAGTTTGATCCTGGCTCAG). Cupriavidus metallidurans was identified using primers F (GACCTGAGGGTGAAAGTGGG) and R (TGCAGTCACAAGCGCAATTC). Results are presented as fold changes relative to the control and are shown as mean ± standard deviation (SD) or cycle threshold (CT). Liver and spleen iron analyses Mouse spleen iron levels were measured using a Prussian Blue Iron Stain Kit (Solarbio, Beijing, China), while liver iron levels were measured using a DAB Enhanced Prussian Blue Staining Kit (Solarbio, Beijing, China). Statistical analysis The statistical analysis for each plot is described above or in the corresponding figure legend. All grouped data values are presented as mean ± SD. P -values were calculated using Student's t-test or Kruskal-Wallis ANOVA with GraphPad Prism software. Results Basic characteristics of Th3/+ mice and Wt mice Male Th3/+ mice and an equal number of WT mice were selected based on their genotype as previously described [ 19 ]. Routine blood tests revealed that reticulocyte percentage (Ret%) was significantly elevated in Th3/+ mice, while hemoglobin (Hb), red blood cells (RBC), hematocrit (HCT), mean corpuscular hemoglobin concentration (MCHC), and mean corpuscular volume (MCV) were significantly reduced. These phenotypic results were consistent with genotypic results, establishing a solid foundation for the accuracy of the subsequent experimental outcomes. Metabolome data QC analysis Untargeted metabolomics techniques were employed to detect and analyze metabolic changes in feces from Th3/+ and WT mice. Kernel density estimation plots (KDE plots) showed that the negative ion mode distribution of metabolites was satisfactory (Fig. 1 A). The Pearson correlation coefficients of QC samples, calculated from the relative quantitative values of metabolites, ranged from 0.96 to 1.00 (Fig. 1 B). The KDE plot for the positive ion mode distribution of metabolites was also satisfactory (Fig. 1 C), with Pearson correlation coefficients between 0.95 and 1.00 (Fig. 1 D). These data indicate high quality, providing a solid basis for subsequent research. Increased bilirubin metabolism in Th3/+ mouse feces In negative ion mode, 544 metabolites with differential abundance were identified in Th3/+ feces (Supplementary Table 1). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation identified 196 metabolites in metabolism, 6 in genetic information processing, 21 in environmental information processing, 8 in cellular processes, and 46 in organismal systems (Figure S1 ). Partial least squares discriminant analysis (PLS-DA) showed significant differences between Th3/+ and WT mice, with less intragroup variation in WT mice compared to Th3/+ mice (Fig. 2 A). The volcano plot of differential metabolites in negative ion mode revealed only 6 up-regulated and 4 down-regulated metabolites in Th3/+ mice, based on variable importance in the projection (VIP > 1) and fold change (FC > 1.5 or < -1.5) analysis (Fig. 2 B). Due to the limited number of differential metabolites found in this mode, reliable analysis of metabolic disorders was not possible. Positive ion mode metabolomics identified a total of 836 metabolites (Supplementary Table 2). KEGG pathway annotation identified 255 metabolites in metabolism, 10 in genetic information processing, 28 in environmental information processing, 2 in cellular processes, and 78 in organismal systems (Figure S2 ). PLS-DA showed distinct separation between Th3/+ and WT mice, with less intragroup variation in WT mice (Fig. 2 C). The volcano plot identified 30 up-regulated and 26 down-regulated metabolites in Th3/+ mice (Fig. 2 D). VIP scores indicated that normorphine, 2,6-xylidine, and biliverdin were the top three differential metabolites in Th3/+ mice (Figure S3 ). Pearson correlation coefficients demonstrated correlations among certain metabolites, supporting evidence of disordered metabolism in Th3/+ feces (Figure S4). To further understand the functions of these differential metabolites and their effects on the host, we classified and annotated them through the KEGG database to clarify their functional characteristics and determine the main biochemical metabolic pathways and signal transduction pathways [ 20 ]. The bubble diagram of metabolic pathway enrichment analysis showed significant enrichment in pathways such as porphyrin and chlorophyll metabolism (p = 0.002) and drug metabolism-cytochrome P450 ( P = 0.02) (Fig. 2 D). Core metabolites of porphyrin metabolism in the feces of Th3/+ mice included elevated biliverdin, bilirubin, and stercobilin. Heme is synthesized into bilirubin by hepatic heme oxygenase and then excreted into the intestine. Bilirubin is converted to biliverdin by bilirubin oxidase and finally excreted by bacteria through glucuronosyltransferase and β-glucuronidase to L-stercobilin (Fig. 2 E). Increased bilirubin metabolism in the gut aligns with the metabolic manifestations of hemolysis in β-TH, further confirming the reliability of our metabolome sequencing. Alteration of gut microbiome in Th3/+ mice The alteration of gut metabolites directly influences the resident microorganisms. To determine if dysbiosis occurs in the feces of Th3/+ mice, we collected fecal samples for metagenomic sequencing. Microbiome analysis indicated that Th3/+ mice possess more genes compared to WT mice, which exhibited a higher coefficient of variation (Figure S5). A Venn diagram revealed a total of 896,051 genes in both groups, with 17,407 genes specific to Th3/+ mice and 25,805 genes unique to WT mice (Fig. 3 A). Out of the total 986,044 predicted genes, 784,944 open reading frames (ORFs, 79.61%) were annotated in the Non-Redundant database. The proportion of ORFs annotated at the domain level was 80.34%, phylum level 76.51%, class level 71.32%, order level 70.88%, family level 54.16%, genus level 48.93%, and species level 36.98%. Non-metric multidimensional scaling (NMDS) analysis showed a separation trend between Th3/+ and WT mice at the class level (Fig. 3 B). Notably, the k-Archaea population was significantly decreased in Th3/+ mice ( P < 0.01, Fig. 3 C), while the c-Fimbriimonadia, o-Fimbriimonadales, f-Fimbriimonadaceae, and g-Fimbriimonas populations were significantly increased ( P 2] further compared the intestinal microflora between Th3/+ and WT mice (Fig. 3 E). The Th3/+ group showed a significant increase in the abundance of S -bacteroidales bacterium and a distinct decrease in S -uncultured bacteria BAC25G1, S -sphingomonadaceae sp21, and S - Cupriavidus metallidurans (C. metallidurans) (Fig. 3 E). Functional annotation and abundance analysis revealed that methylase (2.1.1.37), glucosidase (3.2.1.21), and mitochondrial ATPase (3.6.3.14) were highly expressed in the Th3/+ group (Figure S6). These findings suggest significant alterations in gut microbiota composition between the two groups. To identify bacteria closely associated with anemia in mice, we correlated hemoglobin levels with the abundances of the three reduced bacteria and found that C. metallidurans (R = 80.6, P = 0.004) showed the highest correlation (Fig. 3 F). We further examined the relative abundance of C. metallidurans in feces from 26 WT mice and 23 Th3/+ mice by qPCR. Results indicated a significantly lower abundance of C. metallidurans in Th3/+ mice, consistent with LEfSe analysis results, suggesting that supplementation with this bacterium could benefit Th3/+ mice (Fig. 3 G). C. metallidurans ameliorates anemia by reduces iron overload in Th3/+ mice We obtained a pure strain of C. metallidurans from the Marine Culture Collection of China and conducted gavage experiments on mice (Fig. 4 A). The results showed that C. metallidurans supplementation slightly improved key hemogram indices (RBC, HGB, HCT, and RDW-CV) without affecting weight (Table 2 ). These results indicate that C. metallidurans ameliorates anemia in Th3/+ mice. Table 1 Mouse red blood cell parameters. groups Hb,g/L, mean(SD) RBC,(10 12 /L) mean(SD) Ret,%, mean(SD) HCT,%, mean(SD) MCHC,g/L, mean(SD) MCV,fL, mean(SD) Wt 139.6(3.5) 8.8(0.3) 3.1(0.8 ) 39.8(1.3) 348.1(4.7) 44.8(0.4) Th3/+ 78.6(4.7) *** 7.8(0.6) ** 31.9(4.5) *** 28.9(1.8) *** 276.7(5.3) *** 37.3(1.3) *** Abbreviations: Hb: haemoglobin; RBC: red blood cells; Ret: Reticulocyte, HCT: hematocrit; MCHC: mean corpuscular hemoglobin concentration. MCV: mean corpuscular volume. Th3/+: β-thalassemic; Wt: wild type. N = 5 mice per group. *** p < 0.001 and ** p < 0.01. Table 2 C. metallidurans ameliorating hemogram indices groups Hb,g/L, mean(SD) RBC,(10 12 /L) mean(SD) RDW,% mean(SD) HCT,%, mean(SD) Wt 142.0(1.8) 8.9(0.1) 18.9(0.4 )*** 37.4(1.3) Wt C.metallidurans 141.8(4.6) 8.9(0.2) 19.0(0.3) 37.5(1.1) Th3/+ 75.2(4.6) *** 8.1(0.5) ** 36.1(1.5)*** 31.3(2.4) *** Th3/+ C.metallidurans 88.4(6.5) ## 8.4(0.4) # 33.8(2.1) # 35.5(1.9) ## Th3/+: β-thalassemic; Wt: wild type. N = 5 mice per group. * p < 0.05; ** p < 0.01; *** p < 0.001 compared to vehicle -Wt mice; # p < 0.05; ## p < 0.01; ### p < 0.001 compared to vehicle -Th3/+ mice. As a bacterium associated with metal metabolism [21 , 22] C. metallidurans 's effect on iron overload, a prominent feature of thalassemia, was investigated in Th3/+ mice. Supplementation with C. metallidurans significantly reduced total bilirubin (TBIL) levels in plasma, suggesting decreased hemolysis in thalassemic mice (Fig. 4 B). Additionally, C. metallidurans treatment markedly reduced liver and spleen iron content in Th3/+ mice (Fig. 4 C-D). These findings demonstrate that C. metallidurans mitigates iron deposition in Th3/+ mice. Fecal microbiota transplantation contributes to anemia improvement in Th3/+ mice FMT is a promising intervention for various diseases [12 , 13 , 23]. We conducted an FMT experiment in Th3/+ mice (Fig. 4 E). Mice were pretreated with antibiotics for two weeks, followed by bacterial colonization and a six-week intervention. Post-intervention analysis revealed significant improvements in key peripheral blood cell indices in Th3/+ and WT mice (Table 3 ). FMT intervention also increased C. metallidurans abundance more than 100-fold (Fig. 4 F). These results suggest that C. metallidurans is a key bacterium playing a crucial role in Th3/+ mice. Table 3 FMT ameliorating hemogram indices groups Hb,g/L, mean(SD) RBC,(10 12 /L) mean(SD) RDW,% mean(SD) HCT,%, mean(SD) Wt 140.6(1.14) 8.9(0.1) 19.1(0.3 ) 37.5(1.4) Th3/+ 81.6(3.4) *** 8.1(0.5) ** 39.6(4.2)*** 31.1(2.2) *** Th3/+FMT 93.2(2.5) ### 8.5(0.3) ## 33.84(2.1 )### 34.8(1.3) ### Th3/+: β-thalassemic; Wt: wild type. N = 5 mice per group. *** p < 0.001 compared to vehicle -Wt mice; ### p < 0.001 compared to vehicle -Th3/+ mice. Discussion In this study, we conducted metabolomic analyses and found dysfunctional bilirubin metabolism in the feces of Th3/+ mice. Our parallel metagenomic analysis of the gut microbiome in Th3/+ and WT mice revealed significant differences in bacterial composition for the first time in Th3/+ mice. Further integrative metagenomic and metabolomic analyses identified gut microbes associated with the development of β-TH anemia and demonstrated that C. metallidurans ameliorates anemia by inhibiting hemolysis and reducing iron deposition in the liver and spleen of Th3/+ mice (Fig. 5 ). Current treatments for thalassemia primarily include blood transfusion and iron chelation therapy. There are three clinically available iron chelators: deferoxamine (administered subcutaneously), deferasirox (taken orally once daily as a dispersible tablet, film-coated tablet, or sprinkle formulation), and deferiprone (taken orally three times a day in liquid or tablet form, or twice daily in a newer modified-release formulation) [ 24 ]. Previous studies have shown that gut microbial metabolites regulate host systemic iron homeostasis and can effectively prevent tissue iron accumulation in a mouse model of systemic iron overload [ 25 ]. Therefore, the metabolic crosstalk between the intestine/microbiota is crucial for systemic iron homeostasis, suggesting that microbiome-based therapeutics could successfully treat iron-related disorders. In our study, we observed significant metabolic changes in the intestinal tract of Th3/+ mice and validated that C. metallidurans ameliorates iron overload. Cupriavidus metallidurans is an aerobic, nonfermenting, non-spore-forming, motile Gram-negative bacillus typically found in environmental habitats [21 , 26]. This bacterium belongs to the genus Cupriavidus , which is abundantly colonized in the colostrum microbiome of maternal cohorts [ 27 ]. It also colonizes human lung tissue and the intestine [28 , 29]. However, its relative abundance in β-TH has not been previously reported. In this study, we discovered that C. metallidurans had a significantly lower colonization rate in Th3/+ mice, providing a foundation for the future development of this bacterium. As a model bacterium for heavy metal detoxification [ 30 ] C. metallidurans can adapt to metal-contaminated environments. It is one of the ideal strains for survival under conditions of reduced biodiversity [ 31 ]. The bacterium possesses numerous transition metal transport systems that can transport toxic metal ions from the cytoplasm to the extracellular environment for detoxification. Given its function of degrading heavy metals such as iron, C. metallidurans holds potential application value for β-TH, where iron deposition is prevalent in patients [ 32 – 34 ]. Although our study analyzed only five mice per group, the metabolic and metagenomic sequencing results were highly reproducible. Various analytical methods yielded valuable information, though we identified only 10 differential metabolites in negative ion mode. Due to the limited data supporting these findings, we chose not to present more results from the negative ion mode. In summary, our findings from the integrated analysis of the intestinal metabolome and microbiome provide insights for future exploration of β-TH, revealing new theranostic targets and presenting innovative ideas for the diagnosis and treatment of β-TH. Declarations Author contributions: X.G., X.Z performed research and acquired the data. X.G., M.L., Y.P., Z.W designed experiments, analyzed the data, and wrote the paper. X.G., M.L responsible for the collection of fecal specimens. J.L provided technical support, reviewed and revised the manuscript. Funding: This work was supported by the grants from National Natural Science Foundation of China (Grant numbers 81920108004 and 82270127 to J.L). The Hunan Provincial Department of Education (Grant number 21B0827 to M.L.),The Hunan Provincial Health Commission (Grant number 202201065317 to M.L.), The Changsha Science and Technology Bureau (Grant number kq2004076 to M.L.). Institutional Review Board Statement: Not applicable. Informed Consent Statement: Informed consent was obtained from subjects involved in the study. Data Availability Statement: Data are contained with the article and Supplementary Materials. Conflicts of Interest: The authors declare no conflict of interest. Acknowledgements ： We are gratitude to EditSprings (https://www.editsprings.cn) for the expert linguistic services provided. References Stamatoyannopoulos G (2005) Control of globin gene expression during development and erythroid differentiation. Exp Hematol 33:259–271. 10.1016/j.exphem.2004.11.007 Modell B, Khan M, Darlison M, Westwood MA, Ingram D, Pennell DJ (2008) Improved survival of thalassaemia major in the UK and relation to T2* cardiovascular magnetic resonance. J Cardiovasc Magn Reson 10:42. 10.1186/1532-429X-10-42 Chauhan W, Shoaib S, Fatma R, Zaka-Ur-Rab Z, Afzal M (2022) Beta-thalassemia and the advent of new interventions beyond transfusion and iron chelation. 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Antonie Van Leeuwenhoek 96:247–258. 10.1007/s10482-009-9361-4 Needs T, Gonzalez-Mosquera LF, Lynch DT (2024) Beta Thalassemia Olivera J, Zhang V, Nemeth E, Ganz T (2023) Erythroferrone exacerbates iron overload and ineffective extramedullary erythropoiesis in a mouse model of beta-thalassemia. Blood Adv 7:3339–3349. 10.1182/bloodadvances.2022009307 Bruzzese A, Martino EA, Mendicino F, Lucia E, Olivito V, Bova C, Filippelli G, Capodanno I, Neri A, Morabito F et al (2023) Iron chelation therapy. Eur J Haematol 110:490–497. 10.1111/ejh.13935 Additional Declarations No competing interests reported. Supplementary Files SupplementaryTable1.xls SupplementaryTable2.xls Supplementaryfiguresandlegends.docx Cite Share Download PDF Status: Published Journal Publication published 01 Oct, 2024 Read the published version in Annals of Hematology → Version 1 posted Editorial decision: Revision requested 23 Jul, 2024 Reviews received at journal 22 Jul, 2024 Reviewers agreed at journal 22 Jul, 2024 Reviews received at journal 12 Jul, 2024 Reviewers agreed at journal 04 Jul, 2024 Reviewers invited by journal 04 Jul, 2024 Editor assigned by journal 03 Jul, 2024 Submission checks completed at journal 03 Jul, 2024 First submitted to journal 27 Jun, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4651050","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":330740777,"identity":"8c20cc79-b60a-42d5-b0bb-db957fd39abe","order_by":0,"name":"Xianfeng Guo","email":"","orcid":"","institution":"Central South University","correspondingAuthor":false,"prefix":"","firstName":"Xianfeng","middleName":"","lastName":"Guo","suffix":""},{"id":330740778,"identity":"8f1569d7-7efb-4623-ab7b-b2a600cccc12","order_by":1,"name":"Xuchao Zhang","email":"","orcid":"","institution":"Central South University","correspondingAuthor":false,"prefix":"","firstName":"Xuchao","middleName":"","lastName":"Zhang","suffix":""},{"id":330740779,"identity":"406e711b-b677-48d2-82e1-ca705ddbc000","order_by":2,"name":"Min Li","email":"","orcid":"","institution":"Changsha Medical University","correspondingAuthor":false,"prefix":"","firstName":"Min","middleName":"","lastName":"Li","suffix":""},{"id":330740780,"identity":"f7cc2347-e26a-4e6f-a840-975e635c1441","order_by":3,"name":"Yuanliang Peng","email":"","orcid":"","institution":"Central South University","correspondingAuthor":false,"prefix":"","firstName":"Yuanliang","middleName":"","lastName":"Peng","suffix":""},{"id":330740781,"identity":"75957377-2b25-471e-bb23-5e90e5513517","order_by":4,"name":"Zi Wang","email":"","orcid":"","institution":"Central South University","correspondingAuthor":false,"prefix":"","firstName":"Zi","middleName":"","lastName":"Wang","suffix":""},{"id":330740782,"identity":"d903200f-7372-4d90-8cf7-7adfdcf102a2","order_by":5,"name":"Jing Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5klEQVRIie3OPwrCMBgF8FcKcSntWhH0CikFJw8TEZws9AD+KQidxK56C0EQx2igXQTXjIpHcFFxMGrntqNg3pB8fORHHqCj84OxTYAyoOmAGPyz4iWE5MSvRwQVSX53V7wyqVk0PG9HxvqYsr18oGlLZlzDwmIWpd1DZrZln4tgrhpKZjYWpSROSVvWIhHMVEPJ1LICsfwk+5BJVTJ0KVSxwQ2MlhMSKsKpK/tMBJHrLQ/naaOIOI7YePd4PEmS1LsMnp2WnfV21yLy/ogC4jsasfs+o2IAmCdgnM/Pssc6Ojo6/5gX/H1NLFqFR/cAAAAASUVORK5CYII=","orcid":"","institution":"Central South University","correspondingAuthor":true,"prefix":"","firstName":"Jing","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2024-06-27 22:21:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4651050/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4651050/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00277-024-06016-z","type":"published","date":"2024-10-01T15:58:09+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":61100984,"identity":"400a607e-2d17-408d-8830-e35232b22c1d","added_by":"auto","created_at":"2024-07-25 15:03:03","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":528583,"visible":true,"origin":"","legend":"\u003cp\u003eQC analysis of the metabolome data. (A-B) Negative ion mode and (C-D) positive ion mode.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4651050/v1/5b523a9395e8df6bee57c2ad.png"},{"id":61101749,"identity":"b60dcbf1-9a04-437f-99f2-ad9a751a5df1","added_by":"auto","created_at":"2024-07-25 15:11:03","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":404689,"visible":true,"origin":"","legend":"\u003cp\u003eMetabolomic analysis in feces of Th3/+ and WT mice. (A) Partial least squares discriminant analysis (PLS-DA) in negative ion mode (n=5). (B) Volcano plot of metabolite differential abundance in negative ion mode (n=5). The horizontal coordinate indicates the variation in the differential multiplicity of metabolites in different subgroups (log2FC) and the vertical coordinate indicates the level of differential significance (-log10(P value)). Each point represents an individual metabolite with a dot size indicating VIP value; yellow dots: upregulated metabolites; green dots: downregulated metabolites (n=5). (C) PLS-DA in positive ion mode (n=5). (D) Volcano plot in positive ion mode (n=5). (E) Bubble diagram of KEGG enrichment analysis of positive ion mode (n=5) (dot color: p value; dot size: number of metabolites with differential abundance in the corresponding pathway). (F) Schematic diagram of metabolic pathways of bilirubin metabolism.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4651050/v1/6e6f0e78c178c86391c756f8.png"},{"id":61100986,"identity":"d2e8cee9-556a-4d2d-9fba-c33e9af36edd","added_by":"auto","created_at":"2024-07-25 15:03:03","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":657359,"visible":true,"origin":"","legend":"\u003cp\u003eTh3/+ mice altered the gut microbiota composition. (A) Venn diagram of gene numbers between Th3/+ and WT mice. (B) NMDS analysis between Th3/+ and WT mice. (C) Relative abundance of k-Archaea. (D) Relative abundance of c-Fimbriimonadia, o-Fimbriimonadales, f-Fimbriimonadaceae, and g-Fimbriimonas between Th3/+ and WT mice. (E) LDA diagram showing significantly different species with LDA score \u0026gt; 2. Histogram colors represent respective groups, and length represents the LDA score. (F) Correlation analysis of hemoglobin levels and \u003cem\u003eC. metallidurans\u003c/em\u003e. (G) Relative abundance of \u003cem\u003eC. metallidurans\u003c/em\u003e. Statistics are shown as mean ± SD. Comparisons between two groups were evaluated with a two-tailed t-test. * \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05; ** \u003cem\u003eP\u003c/em\u003e \u0026lt;0.01; *** \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4651050/v1/97beafdb0eb7a9c7e5c5b4cf.png"},{"id":61101752,"identity":"b8346616-9c99-4b06-96aa-0ebe69ba213b","added_by":"auto","created_at":"2024-07-25 15:11:03","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1132801,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eC. metallidurans \u003c/em\u003eameliorates anemia by reducing iron overload. (A) Schematic diagram of \u003cem\u003eC. metallidurans\u003c/em\u003egavage experiments. (B) Total bilirubin (TBIL) concentration in WT, WT \u003cem\u003eC. metallidurans\u003c/em\u003e, Th3/+, and Th3/+ \u003cem\u003eC. metallidurans\u003c/em\u003e. (C) Representative images of DAB-enhanced Prussian blue staining of the liver and liver iron score. (D) Perls’ Prussian blue staining of the spleen and spleen iron score. (E) Schematic diagram of FMT. (F) Changes in \u003cem\u003eC. metallidurans\u003c/em\u003e abundance after antibiotic and FMT treatment. Comparisons between two groups were evaluated with a two-tailed t-test, and comparisons among multiple groups were evaluated with one-way ANOVA. * \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05; ** \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01; *** \u003cem\u003eP\u003c/em\u003e\u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4651050/v1/d434e44b76b625bc192b0245.png"},{"id":61100991,"identity":"797ee567-0fdc-4fb6-ba0d-ba4b675d7cbf","added_by":"auto","created_at":"2024-07-25 15:03:03","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":177330,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic diagram of \u003cem\u003eC. metallidurans\u003c/em\u003e in β-thalassemic mouse model. Bilirubin metabolism disorders induce a decrease in \u003cem\u003eC. metallidurans\u003c/em\u003e. \u003cem\u003eC. metallidurans\u003c/em\u003e improves anemia and hemolysis in Th3/+ mice, contributing to the reduction of iron overload in the liver and spleen of Th3/+ mice.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-4651050/v1/d707efc2b34636b57f4170e3.png"},{"id":66097476,"identity":"63eb7f04-3aad-4845-9a7d-16fe1eb5c76e","added_by":"auto","created_at":"2024-10-07 16:14:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3235591,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4651050/v1/bb62e59d-6b41-4e22-ba75-171e9ab3e5e7.pdf"},{"id":61101750,"identity":"695a2f48-0315-46a0-b4aa-897f01f65f3c","added_by":"auto","created_at":"2024-07-25 15:11:03","extension":"xls","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":172811,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1.xls","url":"https://assets-eu.researchsquare.com/files/rs-4651050/v1/73a78f11aee627e55ac31e17.xls"},{"id":61100988,"identity":"089a5480-8124-494c-8f6e-8ec764382a15","added_by":"auto","created_at":"2024-07-25 15:03:03","extension":"xls","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":270123,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable2.xls","url":"https://assets-eu.researchsquare.com/files/rs-4651050/v1/b1c81c8f88bbd272fcf0df5a.xls"},{"id":61102476,"identity":"d8a225af-7750-4df5-9b1d-ef150550a048","added_by":"auto","created_at":"2024-07-25 15:19:03","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":1313876,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfiguresandlegends.docx","url":"https://assets-eu.researchsquare.com/files/rs-4651050/v1/9cd4ec1338273f3427660f77.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Integrated metabolomic and microbiome analysis identifies Cupriavidus metallidurans as a potential therapeutic target for β-thalassemia","fulltext":[{"header":"Introduction","content":"\u003cp\u003eβ-thalassaemia (β-TH) is the most common autosomal recessive blood disorder caused by mutations in the β-globin gene located on chromosome 11 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Approximately 60,000 newborns are affected annually worldwide, predominantly in developing countries, accounting for about 1.5% of the global population (80\u0026ndash;90\u0026nbsp;million people) [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHemolysis is a hallmark of β-TH, resulting from an imbalance in the production of β-globin chains (decreased or absent) and normal alpha chains, leading to the precipitation of alpha chains and red cell damage. Ineffective erythropoiesis further increases erythroferrone production, suppresses hepcidin, and consequently enhances iron absorption and disrupts bone metabolism [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHemolysis leads to the excretion of large amounts of bilirubin into the intestines. Bilirubin, historically regarded as a waste product of heme catabolism [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], plays a significant role in the pathophysiology of β-TH as a hemolytic disease [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The rupture of erythrocytes in β-TH increases serum levels of total and unconjugated bilirubin due to the oxidation of free hemoglobin's heme moiety [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Normally, bilirubin is conjugated to glucuronic acid, forming a soluble compound excreted as urobilinogen [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. However, patients with β-TH have impaired liver function, reducing their ability to metabolize bilirubin, resulting in increased intestinal concentrations [8\u003csup\u003e,\u003c/sup\u003e9].\u003c/p\u003e \u003cp\u003eIntestinal bacteria degrade bilirubin to urobilinogen; half of these entities are reabsorbed into the circulation via the portal system for renal excretion, while the remainder is converted to stercobilinogen for fecal excretion [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The catabolism of bilirubin to urobilinoids regulates specific gut bacteria, maintaining homeostasis [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFecal microbiota transplantation (FMT) has emerged as a prominent research area in recent years [12\u003csup\u003e,\u003c/sup\u003e13]. We hypothesized that FMT could standardize gut microbiota in Th3/+ mice and controls, thereby highlighting β-TH's impact on gut microbiota. Studying the effect of intestinal flora on the phenotype may provide novel treatments for β-TH.\u003c/p\u003e \u003cp\u003eLimited research exists on the gut microbiota in β-TH, and the mechanistic link between gut microbiota alterations and β-TH pathogenesis remains unclear. Given that various circulating metabolites act as intermediaries between the gut microbiome and host biology [14\u003csup\u003e,\u003c/sup\u003e15], integrated analyses of microbial metabolites, gut microbiome, and host phenotype may offer promising strategies to elucidate β-TH's development mechanisms.\u003c/p\u003e \u003cp\u003eIn this study, we performed integrative metagenomic and metabolomic analyses to identify potential links between gut microbial composition and clinical phenotypes in β-TH. Our dual-omics analysis indicates that dysfunctional bilirubin metabolism, characterized by excess bilirubin, stercobilin, and biliverdin, along with disturbances in gut microbial ecology, is associated with β-TH anemia.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eMice\u003c/h2\u003e \u003cp\u003eWild-type C57BL/6 (WT) mice were obtained from Hunan SJA Laboratory Animal Co. Ltd. β-Thalassemia (Th3/+) mice with a C57BL/6 background were originally purchased from Jackson Laboratories. Male Th3/+) and female WT C57BL/6 mice were crossbred to produce β-TH and WT littermates at Central South University Laboratory Animal Center. All experiments were conducted using 8-10-week-old virgin female mice unless otherwise noted. Mice received \u003cem\u003eCupriavidus metallidurans\u003c/em\u003e via gavage three times weekly and were sacrificed two days after the last administration. All experiments were approved by the Animal Ethics Committee of Central South University and conformed to relevant regulatory standards at Central South University Laboratory Animal Center.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eMetabolomic analysis of fecal samples\u003c/h2\u003e \u003cp\u003eUntargeted metabolomics profiling was performed on the XploreMET platform (Novogene, China). Samples were prepared following previously reported procedures with minor modifications [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Raw data generated by GC-TOF/MS were processed using XploreMET 3.0.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eMetagenomic sequencing\u003c/h2\u003e \u003cp\u003eMetagenomic sequencing was performed as previously described [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. DNA (1 \u0026micro;g/sample) was used for sample preparation. Quality control (QC) for DNA samples involved two main methods: (A) DNA degradation degree and potential contamination were monitored on 1% agarose gels. (B) DNA concentration was measured using a Qubit dsDNA assay kit in a Qubit 2.0 fluorometer (Life Technologies, CA, USA).\u003c/p\u003e \u003cp\u003eDNA samples with an OD value between 1.8 and 2.0 and contents above 1 \u0026micro;g were used to construct the library. Sequencing libraries were generated using the NEBNext Ultra\u0026trade; DNA library prep kit for Illumina (NEB, USA) following the manufacturer\u0026rsquo;s recommendations, with index codes added to attribute sequences to each sample. PCR products were purified, and libraries were analyzed for size distribution using an Agilent 2100 Bioanalyzer and quantified by real-time PCR. The clustering of the index-coded samples was performed on a cBot Cluster Generation System according to the manufacturer\u0026rsquo;s instructions. After cluster generation, libraries were sequenced on an Illumina HiSeq platform, and paired-end reads were generated. High-quality reads for the ten samples were obtained, averaging 10,583.04 Mbp. Taxonomic classification and functional annotation were analyzed following previously reported procedures with minor modifications [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eFecal microbiota transplantation experiment, and sample collection\u003c/h2\u003e \u003cp\u003eFresh stool from Th3/+ and WT mice was collected separately, then mixed and suspended in PBS (10 mL) (phosphate-buffered saline). The suspension was filtered using 70 \u0026micro;m strainers, and the filtrate was centrifuged at 2000 rpm for 10 minutes. After removing the supernatant, the remaining pellet was resuspended in 2 mL of PBS. This mixture was used for fecal microbiota transplantation by gavage (200 \u0026micro;L per mouse).\u003c/p\u003e \u003cp\u003ePrior to gavage, all mice were treated with a cocktail of broad-spectrum antibiotics including ampicillin (0.2 g/L), vancomycin (0.1 g/L), neomycin (0.2 g/L), and metronidazole (0.2 g/L) in drinking water for two weeks. Subsequently, FMT was performed on Th3/+ and WT mice, with mice receiving a fecal suspension by gavage three times weekly for six weeks.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eQuantitative real-time polymerase chain reaction (qPCR)\u003c/h2\u003e \u003cp\u003eFecal DNA was isolated using a HiPure Stool DNA Kit (Magen, Guangzhou, China). Total bacteria were identified using primers 1492R (GGTTACCTTGTTACGACTT) and 27F (AGAGTTTGATCCTGGCTCAG). \u003cem\u003eCupriavidus metallidurans\u003c/em\u003e was identified using primers F (GACCTGAGGGTGAAAGTGGG) and R (TGCAGTCACAAGCGCAATTC). Results are presented as fold changes relative to the control and are shown as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) or cycle threshold (CT).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eLiver and spleen iron analyses\u003c/h2\u003e \u003cp\u003eMouse spleen iron levels were measured using a Prussian Blue Iron Stain Kit (Solarbio, Beijing, China), while liver iron levels were measured using a DAB Enhanced Prussian Blue Staining Kit (Solarbio, Beijing, China).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe statistical analysis for each plot is described above or in the corresponding figure legend. All grouped data values are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. \u003cem\u003eP\u003c/em\u003e-values were calculated using Student's t-test or Kruskal-Wallis ANOVA with GraphPad Prism software.\u003c/p\u003e \u003c/div\u003e "},{"header":"Results","content":"\u003cdiv id=\"Sec10\" type=\"Results\" class=\"Section2\"\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003eBasic characteristics of Th3/+ mice and Wt mice\u003c/h2\u003e \u003cp\u003eMale Th3/+ mice and an equal number of WT mice were selected based on their genotype as previously described [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Routine blood tests revealed that reticulocyte percentage (Ret%) was significantly elevated in Th3/+ mice, while hemoglobin (Hb), red blood cells (RBC), hematocrit (HCT), mean corpuscular hemoglobin concentration (MCHC), and mean corpuscular volume (MCV) were significantly reduced. These phenotypic results were consistent with genotypic results, establishing a solid foundation for the accuracy of the subsequent experimental outcomes.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eMetabolome data QC analysis\u003c/h2\u003e \u003cp\u003eUntargeted metabolomics techniques were employed to detect and analyze metabolic changes in feces from Th3/+ and WT mice. Kernel density estimation plots (KDE plots) showed that the negative ion mode distribution of metabolites was satisfactory (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). The Pearson correlation coefficients of QC samples, calculated from the relative quantitative values of metabolites, ranged from 0.96 to 1.00 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). The KDE plot for the positive ion mode distribution of metabolites was also satisfactory (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC), with Pearson correlation coefficients between 0.95 and 1.00 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). These data indicate high quality, providing a solid basis for subsequent research.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eIncreased bilirubin metabolism in Th3/+ mouse feces\u003c/h2\u003e \u003cp\u003eIn negative ion mode, 544 metabolites with differential abundance were identified in Th3/+ feces (Supplementary Table\u0026nbsp;1). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation identified 196 metabolites in metabolism, 6 in genetic information processing, 21 in environmental information processing, 8 in cellular processes, and 46 in organismal systems (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Partial least squares discriminant analysis (PLS-DA) showed significant differences between Th3/+ and WT mice, with less intragroup variation in WT mice compared to Th3/+ mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). The volcano plot of differential metabolites in negative ion mode revealed only 6 up-regulated and 4 down-regulated metabolites in Th3/+ mice, based on variable importance in the projection (VIP\u0026thinsp;\u0026gt;\u0026thinsp;1) and fold change (FC\u0026thinsp;\u0026gt;\u0026thinsp;1.5 or \u0026lt; -1.5) analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Due to the limited number of differential metabolites found in this mode, reliable analysis of metabolic disorders was not possible.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePositive ion mode metabolomics identified a total of 836 metabolites (Supplementary Table\u0026nbsp;2). KEGG pathway annotation identified 255 metabolites in metabolism, 10 in genetic information processing, 28 in environmental information processing, 2 in cellular processes, and 78 in organismal systems (Figure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). PLS-DA showed distinct separation between Th3/+ and WT mice, with less intragroup variation in WT mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). The volcano plot identified 30 up-regulated and 26 down-regulated metabolites in Th3/+ mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). VIP scores indicated that normorphine, 2,6-xylidine, and biliverdin were the top three differential metabolites in Th3/+ mice (Figure \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). Pearson correlation coefficients demonstrated correlations among certain metabolites, supporting evidence of disordered metabolism in Th3/+ feces (Figure S4).\u003c/p\u003e \u003cp\u003eTo further understand the functions of these differential metabolites and their effects on the host, we classified and annotated them through the KEGG database to clarify their functional characteristics and determine the main biochemical metabolic pathways and signal transduction pathways [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The bubble diagram of metabolic pathway enrichment analysis showed significant enrichment in pathways such as porphyrin and chlorophyll metabolism (p\u0026thinsp;=\u0026thinsp;0.002) and drug metabolism-cytochrome P450 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003eCore metabolites of porphyrin metabolism in the feces of Th3/+ mice included elevated biliverdin, bilirubin, and stercobilin. Heme is synthesized into bilirubin by hepatic heme oxygenase and then excreted into the intestine. Bilirubin is converted to biliverdin by bilirubin oxidase and finally excreted by bacteria through glucuronosyltransferase and β-glucuronidase to L-stercobilin (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE). Increased bilirubin metabolism in the gut aligns with the metabolic manifestations of hemolysis in β-TH, further confirming the reliability of our metabolome sequencing.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eAlteration of gut microbiome in Th3/+ mice\u003c/h2\u003e \u003cp\u003eThe alteration of gut metabolites directly influences the resident microorganisms. To determine if dysbiosis occurs in the feces of Th3/+ mice, we collected fecal samples for metagenomic sequencing.\u003c/p\u003e \u003cp\u003eMicrobiome analysis indicated that Th3/+ mice possess more genes compared to WT mice, which exhibited a higher coefficient of variation (Figure S5). A Venn diagram revealed a total of 896,051 genes in both groups, with 17,407 genes specific to Th3/+ mice and 25,805 genes unique to WT mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Out of the total 986,044 predicted genes, 784,944 open reading frames (ORFs, 79.61%) were annotated in the Non-Redundant database. The proportion of ORFs annotated at the domain level was 80.34%, phylum level 76.51%, class level 71.32%, order level 70.88%, family level 54.16%, genus level 48.93%, and species level 36.98%. Non-metric multidimensional scaling (NMDS) analysis showed a separation trend between Th3/+ and WT mice at the class level (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Notably, the k-Archaea population was significantly decreased in Th3/+ mice (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC), while the c-Fimbriimonadia, o-Fimbriimonadales, f-Fimbriimonadaceae, and g-Fimbriimonas populations were significantly increased (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eLinear discriminant analysis effect size (LEfSe) analysis [α\u0026thinsp;=\u0026thinsp;0.05, LDA score\u0026thinsp;\u0026gt;\u0026thinsp;2] further compared the intestinal microflora between Th3/+ and WT mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE). The Th3/+ group showed a significant increase in the abundance of \u003cem\u003eS\u003c/em\u003e-bacteroidales bacterium and a distinct decrease in \u003cem\u003eS\u003c/em\u003e-uncultured bacteria BAC25G1, \u003cem\u003eS\u003c/em\u003e-sphingomonadaceae sp21, and \u003cem\u003eS\u003c/em\u003e-\u003cem\u003eCupriavidus metallidurans\u003c/em\u003e (C. metallidurans) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE). Functional annotation and abundance analysis revealed that methylase (2.1.1.37), glucosidase (3.2.1.21), and mitochondrial ATPase (3.6.3.14) were highly expressed in the Th3/+ group (Figure S6). These findings suggest significant alterations in gut microbiota composition between the two groups.\u003c/p\u003e \u003cp\u003eTo identify bacteria closely associated with anemia in mice, we correlated hemoglobin levels with the abundances of the three reduced bacteria and found that \u003cem\u003eC. metallidurans\u003c/em\u003e (R\u0026thinsp;=\u0026thinsp;80.6, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004) showed the highest correlation (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF). We further examined the relative abundance of \u003cem\u003eC. metallidurans\u003c/em\u003e in feces from 26 WT mice and 23 Th3/+ mice by qPCR. Results indicated a significantly lower abundance of \u003cem\u003eC. metallidurans\u003c/em\u003e in Th3/+ mice, consistent with LEfSe analysis results, suggesting that supplementation with this bacterium could benefit Th3/+ mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eG).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e\u003cem\u003eC. metallidurans\u003c/em\u003e ameliorates anemia by reduces iron overload in Th3/+ mice\u003c/h2\u003e \u003cp\u003eWe obtained a pure strain of \u003cem\u003eC. metallidurans\u003c/em\u003e from the Marine Culture Collection of China and conducted gavage experiments on mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). The results showed that \u003cem\u003eC. metallidurans\u003c/em\u003e supplementation slightly improved key hemogram indices (RBC, HGB, HCT, and RDW-CV) without affecting weight (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). These results indicate that \u003cem\u003eC. metallidurans\u003c/em\u003e ameliorates anemia in Th3/+ mice.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMouse red blood cell parameters.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003egroups\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHb,g/L,\u003c/p\u003e \u003cp\u003emean(SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRBC,(10\u003csup\u003e12\u003c/sup\u003e/L)\u003c/p\u003e \u003cp\u003emean(SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRet,%,\u003c/p\u003e \u003cp\u003emean(SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHCT,%,\u003c/p\u003e \u003cp\u003emean(SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMCHC,g/L,\u003c/p\u003e \u003cp\u003emean(SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMCV,fL,\u003c/p\u003e \u003cp\u003emean(SD)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e139.6(3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.8(0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.1(0.8\u003csup\u003e)\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e39.8(1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e348.1(4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e44.8(0.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTh3/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e78.6(4.7)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.8(0.6)\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31.9(4.5)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e28.9(1.8)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e276.7(5.3)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e37.3(1.3)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eAbbreviations: Hb: haemoglobin; RBC: red blood cells; Ret: Reticulocyte, HCT: hematocrit; MCHC: mean corpuscular hemoglobin concentration. MCV: mean corpuscular volume. Th3/+: β-thalassemic; Wt: wild type. N\u0026thinsp;=\u0026thinsp;5 mice per group. ***\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and **\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eC. metallidurans\u003c/em\u003e ameliorating hemogram indices\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003egroups\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHb,g/L,\u003c/p\u003e \u003cp\u003emean(SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRBC,(10\u003csup\u003e12\u003c/sup\u003e/L)\u003c/p\u003e \u003cp\u003emean(SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRDW,%\u003c/p\u003e \u003cp\u003emean(SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHCT,%,\u003c/p\u003e \u003cp\u003emean(SD)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e142.0(1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.9(0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18.9(0.4\u003csup\u003e)***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e37.4(1.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWt \u003cem\u003eC.metallidurans\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e141.8(4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.9(0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19.0(0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e37.5(1.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTh3/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75.2(4.6)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.1(0.5)\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36.1(1.5)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e31.3(2.4)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTh3/+\u003cem\u003eC.metallidurans\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e88.4(6.5)\u003csup\u003e##\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.4(0.4)\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33.8(2.1)\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e35.5(1.9)\u003csup\u003e##\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eTh3/+: β-thalassemic; Wt: wild type. N\u0026thinsp;=\u0026thinsp;5 mice per group. *\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01; ***\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 compared to vehicle -Wt mice; \u003csup\u003e#\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05; \u003csup\u003e##\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01; \u003csup\u003e###\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 compared to vehicle -Th3/+ mice.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAs a bacterium associated with metal metabolism [21\u003csup\u003e,\u003c/sup\u003e22] \u003cem\u003eC. metallidurans\u003c/em\u003e's effect on iron overload, a prominent feature of thalassemia, was investigated in Th3/+ mice. Supplementation with \u003cem\u003eC. metallidurans\u003c/em\u003e significantly reduced total bilirubin (TBIL) levels in plasma, suggesting decreased hemolysis in thalassemic mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Additionally, \u003cem\u003eC. metallidurans\u003c/em\u003e treatment markedly reduced liver and spleen iron content in Th3/+ mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC-D). These findings demonstrate that \u003cem\u003eC. metallidurans\u003c/em\u003e mitigates iron deposition in Th3/+ mice.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eFecal microbiota transplantation contributes to anemia improvement in Th3/+ mice\u003c/h2\u003e \u003cp\u003eFMT is a promising intervention for various diseases [12\u003csup\u003e,\u003c/sup\u003e13\u003csup\u003e,\u003c/sup\u003e23]. We conducted an FMT experiment in Th3/+ mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE). Mice were pretreated with antibiotics for two weeks, followed by bacterial colonization and a six-week intervention. Post-intervention analysis revealed significant improvements in key peripheral blood cell indices in Th3/+ and WT mice (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). FMT intervention also increased \u003cem\u003eC. metallidurans\u003c/em\u003e abundance more than 100-fold (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF). These results suggest that \u003cem\u003eC. metallidurans\u003c/em\u003e is a key bacterium playing a crucial role in Th3/+ mice.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFMT ameliorating hemogram indices\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003egroups\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHb,g/L,\u003c/p\u003e \u003cp\u003emean(SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRBC,(10\u003csup\u003e12\u003c/sup\u003e/L)\u003c/p\u003e \u003cp\u003emean(SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRDW,%\u003c/p\u003e \u003cp\u003emean(SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHCT,%,\u003c/p\u003e \u003cp\u003emean(SD)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e140.6(1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.9(0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19.1(0.3\u003csup\u003e)\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e37.5(1.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTh3/+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e81.6(3.4)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.1(0.5)\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e39.6(4.2)***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e31.1(2.2)\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTh3/+FMT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e93.2(2.5)\u003csup\u003e###\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.5(0.3)\u003csup\u003e##\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33.84(2.1\u003csup\u003e)###\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e34.8(1.3)\u003csup\u003e###\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eTh3/+: β-thalassemic; Wt: wild type. N\u0026thinsp;=\u0026thinsp;5 mice per group. ***\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 compared to vehicle -Wt mice; ###\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 compared to vehicle -Th3/+ mice.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we conducted metabolomic analyses and found dysfunctional bilirubin metabolism in the feces of Th3/+ mice. Our parallel metagenomic analysis of the gut microbiome in Th3/+ and WT mice revealed significant differences in bacterial composition for the first time in Th3/+ mice. Further integrative metagenomic and metabolomic analyses identified gut microbes associated with the development of β-TH anemia and demonstrated that \u003cem\u003eC. metallidurans\u003c/em\u003e ameliorates anemia by inhibiting hemolysis and reducing iron deposition in the liver and spleen of Th3/+ mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCurrent treatments for thalassemia primarily include blood transfusion and iron chelation therapy. There are three clinically available iron chelators: deferoxamine (administered subcutaneously), deferasirox (taken orally once daily as a dispersible tablet, film-coated tablet, or sprinkle formulation), and deferiprone (taken orally three times a day in liquid or tablet form, or twice daily in a newer modified-release formulation) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Previous studies have shown that gut microbial metabolites regulate host systemic iron homeostasis and can effectively prevent tissue iron accumulation in a mouse model of systemic iron overload [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Therefore, the metabolic crosstalk between the intestine/microbiota is crucial for systemic iron homeostasis, suggesting that microbiome-based therapeutics could successfully treat iron-related disorders. In our study, we observed significant metabolic changes in the intestinal tract of Th3/+ mice and validated that \u003cem\u003eC. metallidurans\u003c/em\u003e ameliorates iron overload.\u003c/p\u003e \u003cp\u003e \u003cem\u003eCupriavidus metallidurans\u003c/em\u003e is an aerobic, nonfermenting, non-spore-forming, motile Gram-negative bacillus typically found in environmental habitats [21\u003csup\u003e,\u003c/sup\u003e26]. This bacterium belongs to the genus \u003cem\u003eCupriavidus\u003c/em\u003e, which is abundantly colonized in the colostrum microbiome of maternal cohorts [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. It also colonizes human lung tissue and the intestine [28\u003csup\u003e,\u003c/sup\u003e29]. However, its relative abundance in β-TH has not been previously reported. In this study, we discovered that \u003cem\u003eC. metallidurans\u003c/em\u003e had a significantly lower colonization rate in Th3/+ mice, providing a foundation for the future development of this bacterium.\u003c/p\u003e \u003cp\u003eAs a model bacterium for heavy metal detoxification [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] \u003cem\u003eC. metallidurans\u003c/em\u003e can adapt to metal-contaminated environments. It is one of the ideal strains for survival under conditions of reduced biodiversity [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The bacterium possesses numerous transition metal transport systems that can transport toxic metal ions from the cytoplasm to the extracellular environment for detoxification. Given its function of degrading heavy metals such as iron, \u003cem\u003eC. metallidurans\u003c/em\u003e holds potential application value for β-TH, where iron deposition is prevalent in patients [\u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough our study analyzed only five mice per group, the metabolic and metagenomic sequencing results were highly reproducible. Various analytical methods yielded valuable information, though we identified only 10 differential metabolites in negative ion mode. Due to the limited data supporting these findings, we chose not to present more results from the negative ion mode.\u003c/p\u003e \u003cp\u003eIn summary, our findings from the integrated analysis of the intestinal metabolome and microbiome provide insights for future exploration of β-TH, revealing new theranostic targets and presenting innovative ideas for the diagnosis and treatment of β-TH.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u0026nbsp;\u003c/strong\u003eX.G., X.Z performed research and acquired the data. X.G., M.L., Y.P., Z.W designed experiments, analyzed the data, and wrote the paper. X.G., M.L responsible for the collection of fecal specimens. J.L provided technical support, reviewed and revised the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis work was supported by the grants from National Natural Science Foundation of China (Grant numbers 81920108004 and 82270127 to J.L). The Hunan Provincial Department of Education (Grant number 21B0827 to M.L.),The Hunan Provincial Health Commission (Grant number 202201065317 to M.L.), The Changsha Science and Technology Bureau (Grant number kq2004076 to M.L.).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitutional Review Board Statement:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent Statement:\u003c/strong\u003e Informed consent was obtained from subjects involved in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u0026nbsp;\u003c/strong\u003eData are contained with the article and Supplementary Materials.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u0026nbsp;\u003c/strong\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003eWe are gratitude to EditSprings (https://www.editsprings.cn) for the expert linguistic services provided.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eStamatoyannopoulos G (2005) Control of globin gene expression during development and erythroid differentiation. 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Eur J Haematol 110:490\u0026ndash;497. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/ejh.13935\u003c/span\u003e\u003cspan address=\"10.1111/ejh.13935\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"annals-of-hematology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aohe","sideBox":"Learn more about [Annals of Hematology](http://link.springer.com/journal/277)","snPcode":"277","submissionUrl":"https://submission.nature.com/new-submission/277/3","title":"Annals of Hematology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Metabolomics, Metagenome, β-thalassemia, Cupriavidus metallidurans, Anemia","lastPublishedDoi":"10.21203/rs.3.rs-4651050/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4651050/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eβ-thalassemia(β-TH) is an inherited hemoglobin disorder marked by ineffective erythropoiesis, anemia, splenomegaly, and systemic iron overload, predominantly affecting developing countries in tropical and subtropical regions. Despite extensive research on its pathogenesis, the interactions between gut microbiota and metabolites in β-TH remain poorly understood. This study compares fecal metabolomics and metagenomics between wildtype (WT) and heterozygous Th3/+ mice, a model for non-transfusion-dependent β-thalassemia intermedia. Our results show increased intestinal bilirubin metabolism, with significant elevations in metabolites such as biliverdin, bilirubin, and stercobilin. Metagenomic analysis revealed notable differences in bacterial composition between Th3/+ and WT mice. Specifically, \u003cem\u003eCupriavidus metallidurans\u003c/em\u003e was identified as a key bacterium that mitigates anemia by reducing liver and spleen iron deposition. This is the first study to ameliorate anemia in mice by altering gut microbiota, presenting new strategies for β-TH management.\u003c/p\u003e","manuscriptTitle":"Integrated metabolomic and microbiome analysis identifies Cupriavidus metallidurans as a potential therapeutic target for β-thalassemia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-25 15:02:58","doi":"10.21203/rs.3.rs-4651050/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-07-23T13:07:06+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-22T21:58:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"191195803232103257185840697760483986516","date":"2024-07-22T19:00:32+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-12T19:33:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"251654287231184318010436659888672595725","date":"2024-07-04T14:12:49+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-04T10:40:04+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-03T08:40:24+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-03T08:39:57+00:00","index":"","fulltext":""},{"type":"submitted","content":"Annals of Hematology","date":"2024-06-27T22:19:14+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"annals-of-hematology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aohe","sideBox":"Learn more about [Annals of Hematology](http://link.springer.com/journal/277)","snPcode":"277","submissionUrl":"https://submission.nature.com/new-submission/277/3","title":"Annals of Hematology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"9bb958c1-6e95-4092-9b43-7eadd71dbf00","owner":[],"postedDate":"July 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-10-07T16:08:53+00:00","versionOfRecord":{"articleIdentity":"rs-4651050","link":"https://doi.org/10.1007/s00277-024-06016-z","journal":{"identity":"annals-of-hematology","isVorOnly":false,"title":"Annals of Hematology"},"publishedOn":"2024-10-01 15:58:09","publishedOnDateReadable":"October 1st, 2024"},"versionCreatedAt":"2024-07-25 15:02:58","video":"","vorDoi":"10.1007/s00277-024-06016-z","vorDoiUrl":"https://doi.org/10.1007/s00277-024-06016-z","workflowStages":[]},"version":"v1","identity":"rs-4651050","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4651050","identity":"rs-4651050","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}