www.nature.com/scientificreports OPEN Strain‑specific alterations in gut microbiome and host immune responses elicited by tolerogenic Bifidobacterium pseudolongum Bing Ma 1,2*, Samuel J. Gavzy 3,4, Vikas Saxena 4, Yang Song 1, Wenji Piao 4, Hnin Wai Lwin 1, Ram Lakhan 4, Jegan lyyathurai 4, Lushen Li 4, Michael France 1,2, Christina Paluskievicz 4, Marina W. Shirkey 4, Lauren Hittle 1, Arshi Munawwar 5, Emmanuel F. Mongodin 1,2,6 & Jonathan S. Bromberg 2,3,4* The beneficial effects attributed to Bifidobacterium are largely attributed to their immunomodulatory capabilities, which are likely to be species- and even strain-specific. However, their strain-specificity in direct and indirect immune modulation remain largely uncharacterized. We have shown that B. pseudolongum UMB-MBP-01, a murine isolate strain, is capable of suppressing inflammation and reducing fibrosis in vivo. To ascertain the mechanism driving this activity and to determine if it is specific to UMB-MBP-01, we compared it to a porcine tropic strain B. pseudolongum ATCC25526 using a combination of cell culture and in vivo experimentation and comparative genomics approaches. Despite many shared features, we demonstrate that these two strains possess distinct genetic repertoires in carbohydrate assimilation, differential activation signatures and cytokine responses signatures in innate immune cells, and differential effects on lymph node morphology with unique local and systemic leukocyte distribution. Importantly, the administration of each B. pseudolongum strain resulted in major divergence in the structure, composition, and function of gut microbiota. This was accompanied by markedly different changes in intestinal transcriptional activities, suggesting strain-specific modulation of the endogenous gut microbiota as a key to immune modulatory host responses. Our study demonstrated a single probiotic strain can influence local, regional, and systemic immunity through both innate and adaptive pathways in a strain-specific manner. It highlights the importance to investigate both the endogenous gut microbiome and the intestinal responses in response to probiotic supplementation, which underpins the mechanisms through which the probiotic strains drive the strain-specific effect to impact health outcomes. Bifidobacterium spp. are naturally occurring residents within the gastrointestinal (GI) tract of mammals and are typically considered b ­ eneficial1,2. Due to their purported health-promoting properties, Bifidobacterium spp. have been incorporated into many live biotherapeutic (LBP) prophylactic formulations, mostly known for applications in alleviating intestinal inflammatory c­ onditions3–7. The potential mechanisms underlying the health benefits of Bifidobacterium include the suppression of gut pathogens g­ rowth8,9, capabilities to alter gut metabolism and to enhance epithelial barrier ­function10,11, and anti-inflammatory modulation of host ­immunity12–15. In particular, their immunomodulatory properties are not limited to the direct effects on GI tissues, but also indirect effects enacted through their influence on the gut ­microbiota16. Bifidobacterium spp. are known to participate in mutualistic interactions with endogenous intestinal microorganisms that can subsequently evoke both immediate as well as delayed immune ­responses17,18. However, the cellular and molecular underpinnings Bifidobacterium’s 1 Institute of Genome Sciences, University of Maryland School of Medicine, Baltimore, MD 21201, USA. 2Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, MD 21201, USA. 3Department of Surgery, University of Maryland Medical Center, Baltimore, MD 21201, USA. 4Center for Vascular and Inflammatory Diseases, University of Maryland School of Medicine, Baltimore, MD 21201, USA. 5Institute of Human Virology, University of Maryland School of Medicine, Baltimore, MD 21201, USA. 6Present address: Division of Lung Diseases, National Heart, Lung, and Blood Institute (NHLBI), National Institutes of Health (NIH), Bethesda, MD, USA. *email: bma@som.umaryland.edu; JBromberg@ som.umaryland.edu Scientific Reports | (2023) 13:1023 | https://doi.org/10.1038/s41598-023-27706-0 1 Vol.:(0123456789) www.nature.com/scientificreports/ biotherapeutic effects remain unclear with contradictory findings r­ eported19. Fundamentally important questions such as what specific mechanisms through which they exert immunomodulatory effects, to what extent the interactions with the gut microorganisms affect the immune responses, and what are the roles of elicited intestinal responses in these processes remain outstanding. The immunomodulatory properties of individual Bifidobacterium spp. are strain-dependent, despite similar effects produced by closely related strains (i.e., alleviation of lactose intolerance or improved host antimicrobial activity)20–22. In fact, immunomodulatory effects are independent of microbial ­phylogeny20. Recent investigations suggested that differences in cell wall composition and structure might be responsible for strain-specific immunomodulatory ­effects23. Microorganism-associated molecular patterns (MAMPs) possess variable biochemistry, even between strains, serving as microbial stimuli that orchestrate molecular cascades in the host immune response and mucosal ­homeostasis24–26. Exopolysaccharide (EPS) and pili may play a role in Bifidobacterium’s strain-specific pro-homeostatic immune ­modulation27,28. Other molecular mechanisms such as lipoteichoic acid and specific metabolites such as acetate could also contribute to strain-specific ­immunity26,29,30. Comparisons of the immunomodulatory properties of closely related strains can be leveraged to identify which are strainspecific and to characterize the microbial determinants of specific host responses, which will provide the basis to rationally hone biotherapeutics for prophylactic a­ pplications15,31,32. We previously showed, using a major histocompatibility complex (MHC)-mismatched murine cardiac transplant model, that fecal microbiota transfer (FMT) caused shifts in the gut microbiota which profoundly influenced allograft o ­ utcomes33. FMT using stool samples from healthy pregnant mice (immune suppressed) resulted in improved long-term allograft survival and prevented inflammation and fibrosis in grafts, as compared to FMT using stool samples from colitic or nonpregnant control ­mice33. B. pseudolongum was revealed as a microbial biomarker for the pregnant mouse gut microbiota, from which we subsequently isolated and sequenced as UMB-MBP-0134. Importantly, gavage with UMB-MBP-01 alone reproduced the same improved graft outcomes as FMT using whole stool of pregnant mice, implicating this strain as one of the main responsible m ­ icrobes33. Thus, the murine tropic strain UMB-MBP-01 may serve as a model organism to investigate the mechanisms of microbe-driven immunomodulation. In this study, we used a combination of cell culture and in vivo experimentation with mice, and comparative genomics approaches to investigate the mechanisms underpinning the strain-specific immunomodulatory capabilities of probiotic Bifidobacterium strains. We performed a genome-wide comparison of UMB-MBP-01 to all other B. pseudolongum genomes, including three additional B. pseudolongum strains (E, EM10, EM13) isolated from the same feces sample of a pregnant mouse, as well as to the porcine tropic strain ATCC25526, in order to investigate the genetic attributes underlying their immunomodulatory properties. Further, we revealed distinct effects on local and systemic immunity induced by UMB-MBP-01 and ATCC25526, using both cell culture and in vivo approaches. Importantly, the oral administration of the two B. pseudolongum strains resulted in profound alterations in composition, structure and function of the murine gut microbiome, accompanied with markedly different intestinal transcriptome activities. These observations indicate that a single probiotic strain can influence local, regional, and systemic immunity through both innate and adaptive pathways in a strain-specific manner. Our study suggests that the modulation of the endogenous gut microbiome is a key element by which Bifidobacterium probiotic strains impose their immunomodulatory effects. A deeper understanding of the strain specificity and mechanisms of action through which specific strains regulate host responses will facilitate the clinical translation of live therapeutics and the development of potential targets for immunomodulatory therapy. Results Differential activation and cytokine responses in dendritic cells and macrophages induced by B. pseudolongum strains ATCC25526 and UMB‑MBP‑01. To understand the immunomodulatory impact of the two B. pseudolongum strains, bone marrow derived dendritic cells (BMDC) and peritoneal macrophages (MΦ) were treated with UV-killed bacteria or isolated Bifidobacterium exopolysaccharide (EPS). We first examined the effect of these treatments on expression of myeloid costimulatory receptors using flow cytometry to assess whether contact with whole bacteria or simply bacterial surface components were necessary for immunomodulation. For BDMCs, treatment with either B. pseudolongum strain stimulated increased CD40 and CD86 expression, however, CD86 expression was greatest after treatment with ATCC25526 UV-killed bacteria compared to UMB-MBP-01 (Fig. 1A–D). Treatment with ATCC25526 UV-killed bacteria stimulated increased BDMC MHC class II, while treatment with UMB-MBP-01 stimulated increased CD80 expression. Neither UMB-MBP-01 EPS nor ATCC25526 EPS altered expression of these surface receptors on BMDCs. The MΦ cell surface receptors were not differentially affected by treatment with UV-killed bacteria or EPS (Fig. 1E–G). Overall, ATCC25526 and UMB-MBP-01 UV-killed bacteria, but not their respective EPS, each triggered a unique activation of important costimulatory receptors on innate myeloid cells in culture. We next examined the effect of UV-killed bacteria and EPS alone on cytokine production in innate immune cells. Using ELISA, both BMDC and MΦ showed increased secretion of IL-6, TNFα, and IL-10 when stimulated with UMB-MBP-01 or ATCC25526 UV-killed bacteria. Induction of cytokine expression was also strain-specific as ATCC25526 UV-killed bacteria stimulated a greater increase in IL-6 and IL-10 than UMB-MBP-01 in BMDCs (Fig. 2A, C), suggesting a more pro-inflammatory effect. TNFα expression was also increased to a greater extent by ATCC25526 compared to UMB-MBP-01 with a borderline statistical significance (p = 0.059, Fig. 2B). For MΦ, treatment with ATCC25526 UV-killed bacteria increased TNFα compared to UMB-MBP-01 (Fig. 2E), suggesting a greater pro-inflammatory effect in MΦ as well as BMDC, whereas there were no strain-specific differences in IL-6 or IL-10 (Fig. 2D, F). EPS of either B. pseudolongum strains did not stimulate cytokine production in either BMDC or MΦ. Similar to co-stimulatory receptor activation, UMB-MBP-01 and ATCC25526 UV-killed bacteria elicited unique myeloid cell cytokine responses that differed from one another and were not recapitulated by EPS. Scientific Reports | Vol:.(1234567890) (2023) 13:1023 | https://doi.org/10.1038/s41598-023-27706-0 2 www.nature.com/scientificreports/ DC MHC II 2.5 B3 CD40 2.0 CD80 D3 1.5 MFI MFI MFI 1.0 1.0 1 1 0.5 0.5 MD ATCC EPS 0 ATCC MD UV-Killed CD86 2 2 1.5 0.0 C2.0 MFI A MD ATCC EPS ATCC MD UV-Killed 0.0 MD ATCC EPS ATCC MD UV-Killed 0 MD ATCC EPS ATCC MD UV-Killed M E1.0 MHC II F6 CD40 CD80 0.8 0.8 4 0.4 MFI 0.6 MFI MFI 0.6 0.4 2 0.2 0.2 0.0 G1.0 MD ATCC EPS ATCC MD UV-Killed 0 MD ATCC EPS ATCC MD UV-Killed 0.0 MD ATCC EPS ATCC MD UV-Killed Figure 1.  Bifidobacterium alters DC and MΦ surface phenotype. DC and MΦ cultured with media alone (to which treatment groups are normalized), ATCC25526 (ATCC) or UMB-MBP-01 (MD) UV-killed Bifidobacterium or EPS derived from each strain. After 24 h of culture, cells analyzed by flow cytometry. DC gated on live CD11c + , and MΦ gated on live F4/80 + populations. DC stained for (A) MHC class II, (B) CD40, (C) CD80, and (D) CD86. MΦ stained for (E) MHC class II, (F) CD40 and (G) CD80. MFI: normalized mean fluorescence intensity; MFI values normalized to control and compared using one-way ANOVA. *p value < 0.05; **p value < 0.01. UV-killed MΦ data representative of 3 separate experiments (one of which is shown), 2 wells/culture condition, i.e. 6 total wells per condition over 3 experiments. EPS MΦ data representative of 2 separate experiments (one of which is shown), 2 wells/culture condition, i.e. 4 total wells per condition over 2 experiments. DC data merged from one experiment with EPS treatment and 2 experiments with UV-killed bacteria (one of which is shown), each data set is normalized to its respective “media only” control, i.e. 4 total wells per condition over 2 experiments for UV-killed bacteria and 2 total wells per condition for EPS. The raw files from these experiments are available to download at https://​doi.​org/​10.​6084/​m9.​figsh​are.​21685​814. Bifidobacterium strains induce distinct changes in local and systemic leukocyte distribution and lymph node morphology. We next assessed whether Bifidobacterium strains differentially induced changes in immune cell distribution and lymph node (LN) architecture in vivo using a mouse model. Mice received broad spectrum antibiotics for 6 days, a regimen that depleted endogenous ­microbiota35, followed by oral gavage with live bacteria (bacteria gavage) or their EPS only, and then daily immunosuppression with tacrolimus (3 mg/kg/d subcutaneously) (experiment design in Fig. 3A). Tacrolimus is the most commonly used clinical immunosuppressive drug and was thus used to recapitulate the immunologic variables to which transplant recipients are subjected, as demonstrated in our clinically relevant murine model to study bacteria-driven allograft ­immunomodulation33. Two days after gavage, mesenteric and peripheral LNs (MLN and PLN) and intestinal tissues were harvested. The effect of these microbiota on the distribution of immune cell populations was assessed by flow cytometry to characterize overall LN cell content, and immunohistochemistry (IHC) to characterize relative immune cell positioning and architectural changes in LN and intestinal segments. Using flow cytometry (gating protocol in Supplemental Fig. 3), we observed decreased MLN Foxp3 + regulatory T cells (Treg) in UMB-MBP-01 EPS treated animals, but otherwise no other differences in the number and proportion of innate myeloid (DC, MΦ) or adaptive lymphoid cells (CD4 T cells, CD8 T cells, Treg, and B cells) in the MLN or PLN of mice with B. pseudolongum gavage compared to those treated with antibiotics alone or untreated controls (Supplemental Fig. 4A–L). We therein used IHC to investigate changes in cell content versus microanatomic shifts in cell positioning and interactions, as our previous work showed that architectural and cellular changes within the LN cortical zone were most critical in mediating immune tolerance and s­ uppression36,37. Using IHC to examine the MLN and PLN T cell cortex, neither bacteria gavage nor EPS affected the number of Treg present. This contrasts with the flow cytometry results above which showed that UMB-MBP-01 EPS treatment caused a decrease in MLN Treg (Supplemental Fig. 4D). Gavage with live bacteria and EPS of both strains increased DCs in MLN compared to control (Fig. 3B), but not PLN (Supplemental Fig. 4M). The number of DCs enumerated by flow cytometry, however, did not change in MLN or PLN (Supplemental Fig. 4E, K). MΦ increased in the cortex of MLN after bacteria gavage or EPS treatments from both strains (Fig. 3C), but not Scientific Reports | (2023) 13:1023 | https://doi.org/10.1038/s41598-023-27706-0 3 Vol.:(0123456789) www.nature.com/scientificreports/ DC IL-6 B 80000 15000 Media ATCC MD Only EPS 0 ATCC MD UV-Killed 3000 1000 5000 20000 IL-10 2000 10000 40000 0 C pg/ml pg/ml 60000 TNF pg/ml A Media ATCC MD Only EPS 0 ATCC MD UV-Killed Media ATCC MD Only EPS ATCC MD UV-Killed M IL-6 E 80000 F 15000 pg/ml 60000 pg/ml TNF 20000 pg/ml D 10000 40000 600 IL-10 400 200 5000 20000 0 Media ATCC MD Only EPS ATCC MD UV-Killed 0 Media ATCC MD Only EPS ATCC MD UV-Killed 0 Media ATCC MD Only EPS ATCC MD UV-Killed Figure 2.  Bifidobacterium alters DC and MΦ cytokine secretion. DCs (A–C) or MΦ (D–F) stimulated with EPS or UV-killed ATCC25526 (ATCC) or UMB-MBP-01 (MD), and 24 h later supernatants analyzed for (A, D) IL-6, (B, E) TNFα, and (C, F) IL-10 by ELISA. Treatments compared using one-way ANOVA. * p value < 0.05; **p value < 0.01, ***p value < 0.001, ****p value < 0.0001. UV-killed bacteria data representative of 3 separate experiments, 2–3 wells/culture condition, 2 technical replicates/well (supernatants from each well split and analyzed in duplicate), i.e. 4–6 wells per condition per experiment, 14 total wells per condition over 3 experiments. EPS data representative of 2 separate experiments, 2–3 wells/culture condition, 2 technical replicates/well (supernatants from each well split and analyzed in duplicate), i.e. 4 wells per condition per experiment, 10 total wells per condition over 2 experiments. The raw files from these experiments are available at https://​doi.​org/​10.​6084/​m9.​figsh​are.​21685​838. in PLN (Supplemental Fig. 4N). ATCC25526 bacteria gavage also resulted in a greater increase in MLN MΦ compared to UMB-MBP-01 (Fig. 3C). Again, this result contrasts with flow cytometry data where there was no difference in MΦ populations in MLN or PLN after treatment. The differences between the flow cytometry and histologic results for Treg are likely due to the focus of histologic analysis only on cells in the cortex while flow cytometry summates all the cells in the entire LN, emphasizing that microanatomic shifts in cell positioning are more outstanding than cell content. We next assessed LN architecture using the ratio of laminin α4 to laminin α5 in the LN T cell cortex of the cortical ridge (CR) and around the high endothelial venules (HEV) by IHC. LN stromal fiber structures are important mediators of immune ­responses36, and an increased laminin α4: α5 ratio is indicative of immune tolerance and ­suppression38. In the MLN CR, both UMB-MBP-01 and ATCC25526 bacterial gavage increased the laminin α4: α5 ratio, with UMB-MBP-01 causing an even greater increase (Fig. 3F). The laminin α4: α5 ratio was not changed around the MLN HEV by either bacteria gavage or EPS (Supplemental Fig. 4O). In PLN CR, only UMB-MBP-01 bacteria gavage resulted in an increased laminin α4: α5 ratio (Fig. 3G). Overall, gavage with both B. pseudolongum strains increased local MLN CR laminin α4: α5 ratios, while only UMB-MBP-01 increased the laminin α4: α5 ratio in systemic PLN CR. Increased MLN CR laminin α4: α5 ratios were also more prominent with UMB-MBP-01 compared to ATCC25526, further demonstrating strain-specific differences in immune modulation. Only IHC was employed to examine the small intestinal segments, since dissociation of this organ followed by leukocyte isolation results in major losses of total cells and unequal loss of cell subsets compared to LN where Scientific Reports | Vol:.(1234567890) (2023) 13:1023 | https://doi.org/10.1038/s41598-023-27706-0 4 www.nature.com/scientificreports/ Figure 3.  Bifidobacterium strains induce unique changes in local and systemic immune cell distribution and LN architecture. (A) Experimental design. C57BL/6 mice treated with antibiotics for 6 days followed by oral gavage with B. pseudolongum ATCC25526 (ATCC), UMB-MBP-01 (MD), or PBS (control). Mice then treated with the immunosuppressant tacrolimus for the next two days. Tissues harvested 2 days after oral gavage of bacteria. Frozen MLN sections stained for (B) CD11c + DC, and (C) F4/80 + MΦ. Small intestine stained for (D) Foxp3 + Treg, and (E) CD11c + DC. LN stained for laminin α4 and laminin α5 with their ratio depicted for (F) MLN CR, and (G) PLN CR. MFI values normalized using the sum of mean, and categories compared using oneway ANOVA. *p value < 0.05; **p value < 0.01, ***p value < 0.001, ****p value < 0.0001. Data representative of 2 separate experiments, 3 mice/group, i.e. 6 total mice per condition over 2 experiments. The raw files from these experiments are available at https://​doi.​org/​10.​6084/​m9.​figsh​are.​21685​850. dissociation is far ­easier39. Both UMB-MBP-01 and ATCC25526 bacteria gavage or EPS resulted in significantly more Treg compared to PBS control, while UMB-MBP-01 resulted in even more Treg compared to ATCC25526 (Fig. 3D), emphasizing its pronounced impact on intestinal Treg. ATCC25526 and UMB-MBP-01 bacteria gavage resulted in more DC compared to no bacteria control, while ATCC25526 also resulted in more DC compared to UMB-MBP-01 (Fig. 3E). UMB-MBP-01 and ATCC25526 EPS resulted in increased DC compared to PBS control, while UMB-MBP-01 EPS also resulted in more DC compared to ATCC25526 EPS (Fig. 3E). Intestinal MΦ did not significantly change after bacteria or EPS gavage. In contrast with our findings in cell culture where EPS was generally inactive, in vivo treatment with EPS alone stimulated similar innate myeloid cell and Treg increases in gut and MLN compared to increases induced by bacterial gavage. Overall, gavage with live bacteria and EPS altered gut associated innate myeloid cells and Tregs without affecting systemic distribution, as evidenced by unchanged PLN populations by flow and IHC (Supplemental Fig. 3J–N). The gavage of live UMB-MBP-01 bacteria was most impactful on intestinal Treg, while ATCC25526 most pronouncedly affected DC. Again, these results indicate both shared characteristics and some significant differences between the immunomodulatory effects of the two different B. pseudolongum strains on intestinal segments. Markedly different intestinal transcriptional activities in response to UMB‑MBP‑01 than to ATCC25526. To determine the effect of UMB-MBP-01 and ATCC25526 on host gene expression, we characterized the transcriptome of mouse intestinal tissues harvested two days after gavage with either UMBMBP-01, ATCC25526, or no bacteria control. Differentially expressed genes (DEGs) were identified by comparing the two treatment groups to the control and revealed both shared and strain-specific effects on transcription (Supplemental Table 6B-D). A total of 420 and 425 DEGs were observed in comparisons of UMB-MBP-01 vs. control and ATCC25526 vs. control, respectively, and 139 DEGs were observed comparing UMB-MBP-01 to ATCC25526 directly. Based on the l­og2 fold change (LFC) scale of DEGs, the strongest intestinal response was elicited by UMB-MBP-01, compared to either ATCC25526 or control (Supplemental Fig. 5). Functional enrichment analyses revealed the effects elicited by UMB-MBP-01 were mainly involved in positive regulation of cell activation, leukocyte and lymphocyte activation, B cell activation, and somatic recombination of immunoglobulin superfamily domains (Supplemental Fig. 5A,C). ATCC25526 elicited responses in phagocytosis, membrane invagination, defense responses to bacterium, and complement activation (Supplemental Fig. 5E). These results further support our observations that ATCC25526 elicited distinct host responses compared to UMB-MBP-01, which induced greater numbers of DEGs and stronger host responses. We further examined the host responses to both UMB-MBP-01 and ATCC25526 as well as those respond only to one but not the other, to pinpoint the differential host responses induced by the two strains. Of the DEGs identified comparing UMB-MBP-01 or ATCC25526 to the control (n = 411 and 416), 59.6% and 58.9%, Scientific Reports | (2023) 13:1023 | https://doi.org/10.1038/s41598-023-27706-0 5 Vol.:(0123456789) www.nature.com/scientificreports/ respectively, were identified in both comparisons (Fig. 4A, Supplemental Table 6). These overlapping DEGs (N = 238) and the condition-specific DEGs, that included 164 DEGs only up-regulated in UMB-MBP-01 versus control and 111 DEGs only upregulated in UMB-MBP-01 versus ATCC25526, comprised the majority of all DEGs (85.9%). Downregulated genes accounted for only a small fraction of all DEGs (14.1%) and the majority of them were identified only in the comparison of UMB-MBP-01 versus ATCC25526 (N = 67, 80.1% of downregulated). The DEGs that were upregulated in both UMB-MBP-01 vs. control and ATCC25526 vs. control include B cell immunity, collagen metabolism, immunoglobulin protein expression, cytokines (IL-1β, IL-10, IL-13, IL-21), TNF receptor superfamily, among others (Supplemental Table 6). Two functional pathways were enriched in UMB-MBP-01 vs control, but not in ATCC25526 vs control: regulation of cell–cell adhesion, regulation of T cell activation, and the response to interferon γ and interferon β (Fig. 4B). In contrast, the host responses to ATCC25526 but not UMB-MBP-01 were enriched in functions involved in fatty acid metabolism, lipid localization, acylglycerol metabolism, and cholesterol and sterol homeostasis (Supplemental Fig. 5D). Together these data further indicated that the effects of UMB-MBP-01 or ATCC25526 were mediated through different pathways. The ATCC25526 strain appeared to exert immunomodulatory effects, at least in part, via stimulation of phagocytosis and induced lipid metabolism, while the UMB-MBP-01 strain exerted stronger effects, mostly through upregulating antibody secretion and regulation of multiple aspects of lymphocyte function, including cytokines, adhesion, and activation. As extracellular molecules may play an important role in eliciting immunomodulatory effects, we also compared intestinal gene expression following gavage with live B. pseudolongum bacteria to that with B. pseudolongum derived EPS. The comparison revealed DEGs that were mostly group-specific without much overlap with EPS vs. control group (12.1%, N = 39) (Supplemental Fig. 6A,B). These data indicated that the predominant intestinal transcriptional responses were due to B. pseudolongum bacteria gavage (62.6%, N = 201), compared to DEGs in EPS gavage (25.5%, N = 82). Gene-pathway network analyses indicated B cell receptor activation and signaling, antigen-receptor mediated signaling, and phagocytosis recognition and engulfment were highly upregulated by B. pseudolongum bacteria gavage (Supplemental Fig. 6C). While both live bacteria and EPS induced antimicrobial circulating immunoglobulin expression, the transcriptional effects were an order of magnitude higher for live bacteria (Supplemental Fig. 6C,D). This result was commensurate with the observations above that EPS did not stimulate cytokine production or cell surface costimulatory receptor expression in either BMDC or MΦ in cell culture. Together, our data support the speculation that the immunomodulatory effects of B. pseudolongum are mostly potentiated through pathways such as influencing gut microbiomes and host metabolic activities, secreted molecules, and/or other cell membrane components, while the surface structure of EPS may play a minor role in these biological processes. Different B. pseudolongum strains elicit rapid, profound alterations in both structure and function of gut microbiome. We next investigated the impact of bacterial gavage on the gut microbiome using shotgun metagenomic sequencing of the intraluminal fecal content (40.6 ± 7.7 million reads per sample; Supplemental Table 2B). Taxonomic composition was established using the comprehensive mouse gut metagen- A B 10 LFC (UMB-MBP-01 vs. control) Apoa1 Apoa1 Psmb8 Irf5 Gbp3 Gbp7 Rorc 0 Lpl Hcls1 Psmb9 Ubd Nos2 Sema4d Samhd1 Zap70 Was Rasgrp1 Tnfsf11 Ccl22 Grap2 Ccl20 Ccl4 Cd6 Lat a UP/UP: 238 a DOWN/UP: 1 a DOWN/DOWN: 7 a UP/NONE: 111 a NONE/UP: 164 −10 a DOWN/NONE: 67 a NONE/DOWN: 9 −10 0 LFC (UMB-MBP-01 vs. ATCC25526) Ccl20 Ccl20 10 Ccl22 Ccl22 H2−DMa H2−DMa Pathway over-representation 8 10 12 14 16 LFC of DEGs 12 8 4 0 Rasgrp1 Rasgrp1 Card11 Card11 Cd5 Cd5 Zap70 Zap70 Tnfsf11 Tnfsf11 Rac2 Rac2 Egr3 Egr3 Lat Lat Stat1 Stat1 Gbp3 Gbp3 Ccl6 Ccl6 Pck1 Pck1 regulation of T cell activation Tigit Tigit Was Was cellular response to interferon−γ Gbp5 Gbp5 Slfn1 Slfn1 leukocyte cell−cell adhesion response to interferon−γ Nos2 Nos2 Expression patterns Ccl4 Ccl4 Runx3 Runx3 regulation of cell−cell adhesion Cd6 Gbp7 Gbp7 Tigit Carmil2 Carmil2 Rorc Rorc Madcam1 Madcam1 Ubd Ubd Card11 Rac2 Arhgdib Stat1 Apoa1 Sting1 Gbp5 Sema4d Sema4d Akna Akna response to interferon−β Gm4841 Gm4841 Ifi206 Ifi206 Gm12185 Gm12185 cellular response to interferon−β F830016B08Rik F830016B08Rik Ifi47 Sting1 Sting1 Figure 4.  Transcriptome profiling of intestinal tissues in response to ATCC25526 or UMB-MBP-01. (A) Quadrant plot to show whether differential expressed genes (DEGs) have the same or opposite relationships between each of the pairwise comparison of UMB-MBP-001 vs control and UMB-MBP-001 vs ATCC25526. DEGs were determined using log2 fold change (LFC) > (+ /−)1 and false discovery rate (FDR) < 0.05. (B) GeneConcept network for most over-represented Gene Ontology (GO) terms to depict over-represented functions based on q-value and gene-count. Over-representation a­ nalyses106 of DEGs that are only different abundant in UMB-MBP-001 vs control but not in ATCC25526 vs control, using GO ontologies performed using enrichGO function of clusterProfile Bioconductor p ­ ackage107. For pairwise comparison enrichment analyses for any two conditions, please refer to Supplemental Fig. 4. Scientific Reports | Vol:.(1234567890) (2023) 13:1023 | https://doi.org/10.1038/s41598-023-27706-0 6 www.nature.com/scientificreports/ ome catalog (CMGM)40 designed specifically to characterize the mouse gut microbiome (Fig. 5A, Supplemental Table 7). A significant reduction in gut microbial community diversity was observed after both UMB-MBP-01 and ATCC25526 gavage, with UMB-MBP-01 gavage resulting in the lowest diversity (Fig. 5C). After B. pseudolongum administration, the most outstanding changes in specific taxonomic groups were the marked increases in the relative abundance of Bacteroides thetaiotaomicron and Lactobacillus johnsonii and relative depletion of Muribaculaceae and Erysipelotrichaceae (Fig. 5B, Supplemental Fig. 7). Gavage with the Desulfovibrio did not produce a significant change in the microbiome, and Muribaculaceae, Erysipelotrichaceae, and Lachnospiraceae were the most abundant groups in these communities and in the not-treatment control communities. These data indicated the gavage of either B. pseudolongum strains profoundly altered the gut microbial community, with a significant reduction in the relative abundance of endogenous gut microorganisms. Canonical Correspondence Analysis (CCA) on both community taxonomic profiles and functional pathways resulted in concordant clustering patterns, in that ATCC25526 or UMB-MBP-01 each resulted in a distinct community, and that were clearly separate from Desulfovibrio-treated and no bacteria controls (Fig. 5D,E). Based on linear discriminant analysis (LDA) effect size (LEfSe) a­ nalysis41, UMB-MBP-01 resulted in a significantly higher relative abundance of B. pseudolongum than ATCC25526 (19.8 ± 6.1% vs. 6.1% ± 2.0%, P = 0.02, Supplemental Fig. 8A,B). This suggests that murine isolate strain UMB-MBP-01 was better able to colonize the mouse gut than the porcine isolate strain ATCC25526 in the murine gut microenvironment. This is not surprising given the provenance of the UMB-MBP-01 strain and its probable prior adaptation to the murine gut microenvironment that it was originally derived from, comparing to ATCC25526 and Desulfovibrio that have different host origins. On the other hand, Enterobacteriaceae (Klebsiella michiganensis and Enterobacter himalayensis), and Clostridiaceae (Clostridium paraputrificum and Clostridium MGG49300) were significantly more enriched in terms of relative abundance in the ATCC25526 treated group but were mostly absent in the UMB-MBP-01 gavage mice (Supplemental Fig. 8C–F). Based the scaled eigenvalue, the top taxa and pathways that contributed to the separation of the clusters in ordination analyses were identified (Supplemental Fig. 9A,B, Supplemental Table 9). The ATCC25526 cluster was attributed to Enterobacteriaceae and Clostridiaceae, and the top contributors included K. pneumonia, K. michiganensis, B. animalis, E. himalayensis, and Clostridium paraputrificum. The most prominent pathways attributed to ATCC25526 cluster include motility (peptidoglycan maturation), gluconeogenesis, energy conversion (fatty acid β-oxidation), and L-threonine biosynthesis. On the other hand, Akkermansia muciniphila, Paeniclostridium sordellii, and B. pseudolongum were among the top significant contributors to the UMB-MBP-01 cluster. The most outstanding pathways for UMB-MBP-01 included ribonucleotide and amino acid biosynthesis (folate transformation, L-isoleucine, L-arginine, L-lysine) and pyruvate fermentation (pyruvate/acetyl-CoA pathway). Together, the data indicated UMB-MBP-01 or ATCC25526 each altered the gut microbiota profoundly and distinctively, which may contribute to their distinct immunomodulatory effect. High genome plasticity of B. pseudolongum reflects strong host adaptability. The pangenome of B. pseudolongum was constructed using 79 strains including the 4 strains sequenced as part of this study (Supplemental Table 1A). Homologous gene clusters (HGCs) were identified in this set of genomes based on allversus-all sequence similarity (Supplemental Table 1B). A total of 4,321 B. pseudolongum HGCs were revealed, among which 31.7% were core (present in almost all strains), 57.0% were dispensable (singleton or present in very few genomes), and the remaining 11.3% were considered accessory. B. pseudolongum demonstrated a smaller pangenome size that was 87.8% of B. breve and 59.5% of B. longum pangenomes (Supplemental Fig. 1). B. pseudolongum had the fewest number of conserved HGCs (N = 1370) but the largest proportion of dispensable pangenome (57.0%) compared to the two other Bifidobacterium species B. longum and B. breve that were both human associated. This disproportionally large dispensable pangenome may be indicative of strong niche adaptation capabilities of B. pseudolongum, reflecting its broad host range, being widely distributed among ­mammals42. Whole genome sequencing was performed on three B. pseudolongum strains (E, EM10, and EM13) isolated from the same pregnant mice feces as UMB-MBP-01 (sequencing statistics in Supplemental Table 2A). Comparison among the four murine strains revealed 1,520 shared coding DNA sequence (CDS), which comprised 97.2% of UMB-MBP-01 coding genes (Supplemental Table 1C). 107 CDS were conserved in at least two but not in all four genomes, and 37 CDS were strain-specific. Most of these genes had unknown functions, and those with known functions related to bacteriophage assembly and function (i.e., capsid protein, integrase, transposes, bacteriophage replication gene, cell lysis protein, microvirus H protein) or carbohydrate hydrolysis and transport (glycosyl hydrolases, ABC transporter permease). On the other hand, comparison between UMB-MBP-01 and ATCC25526 revealed 1,351 shared CDS (86.4% of UMB-MBP-01 coding genes), and 157 genes that belonged to one strain but not the other (Supplemental Table 1D). Interestingly, most of these strain-specific genes also belonged to the categories of bacteriophage assembly and functions as well as carbohydrate hydrolysis and transport, in addition to genes with unknown function. Together these data suggested bacteriophage-mediated transduction might have been a major contributor to dissemination of carbohydrate metabolism capabilities, potentially through horizontal gene transfer among closely related murine-derived strains, as well as more distantly related B. pseudolongum strains. Whole genome Average Nucleotide Identity (ANI) clustering suggested two subspecies, B. pseudolongum subsp. pseudolongum clade that contained ATCC25526, and B. pseudolongum subsp. globosum clusters that had three distinct clades I-III (Fig. 6). Subspecies globosum clade III had the largest number of coding genes (1642 ± 70) among all clades and contained UMB-MBP-01 and the three isolates from the source stools of pregnant mice. The subspecies pseudolongum clade had the smallest number of coding genes among all clades (1519 ± 35.6). Overall, 1599 HGCs accounted for 37.0% of B. pseudolongum pangenome were identified as clade-specific (> 90% genes belonging to the same clade), and the majority originated from globosum clade III (N = 648), while clade pseudolongum provided the fewest (N = 130). The large number of clade-specific genes Scientific Reports | (2023) 13:1023 | https://doi.org/10.1038/s41598-023-27706-0 7 Vol.:(0123456789) www.nature.com/scientificreports/ A 0 20 40 60 80 C 100 2.5 1 2 3 Cluster Shannon Diversity Index relative abundance % 3.0 group Bacteroides thetaiotaomicron 2.0 Bifidobacterium globosum Duncaniella MGG30877 Lactobacillus johnsonii 1.5 Akkermansia muciniphila Duncaniella MGG31006 l ro nt s Co an r ic lfu su m de gu D. on ol -01 ud P se MB m .p gu B MB on U ol 6 ud 52 se 25 .p C B TC A Dubosiella newyorkensis CAG−485 sp002362485 Klebsiella A michiganensis Turicibacter sp002311155 Paramuribaculum MGG30915 D Enterobacter himalayensis Parasutterella excrementihominis Clostridium MGG49300 2 1 CA2 [12.8%] Paeniclostridium sordellii COE1 MGG22796 CAG−873 MGG32771 0 MGG34735 MGG07741 Lactobacillus MGG05725 Bacteroides caecimuris −1 An181 MGG45370 UBA7182 MGG38183 Clostridium paraputrificum 1.5 1.0 0.0 1.5 * 1.0 0.5 0.0 2.5 −1 2.0 * 1.5 1.0 * 0.5 0.0 2.5 2.0 1.0 * 0.5 Ak ke Ba rm ct an si er Bi ac oi fid ea da e Bu ob ce rk ac ae te Cl ho os ria ld ce er ae tri ia En di te ce ac ae ro ea e Er ys ba ct ip er ia Er el ys at ce oc ip ae La lo el ch ot st ric rid ae ae M ob ira ce ce ct sp ha ia La no ur ce ac ae ib ill Os ac ac 0 ci ea ul e ac llo Pe p ea sp e ira to Ru st ce m re ae Tu pt in oc o oc o ric ib cc cc ac ac ac ea te ea e e 1 CA1 [51.2%] group Bifidobacterium pseudolongum ATCC25526 Bifidobacterium pseudolongum UMB-MBP-01 Desulfovibrio desulfurican ATCC27774 Control Control * 1.5 0.0 1.0 0 D. desulfuricans Abundance 2.0 0.5 1 UMB-MBP-01 * 2.5 * * 0.5 0 CA1 [61.7%] E ATCC25526 * 2.5 2.0 −0.5 CA2 [22.6%] B −1.0 ra ce ae Figure 5.  Alterations in gut microbiome after bacterial gavage. (A) Heatmap of the top most abundant intestinal bacterial taxa relative abundance in mice intraluminal samples. Ward linkage clustering based on Jensen-Shannon distance was calculated using the vegan package in ­R101. Taxonomic profiles of the microbial community were characterized using the comprehensive mouse gut metagenome (CMGM) c­ atalog40. R codes and input dataset used to generate the heatmap was deposited in github (https://​github.​com/​igsbma/​genome_​ paper). (B) Cumulative relative abundance of major bacterial families. The relative abundances of each family are stacked in order from greatest to least, and are separated by a horizontal line. (C) Shannon diversity index (within-community diversity) of the four experimental groups. Canonical Correspondence Analysis (CCA) of (D) microbial functional pathways and (E) taxonomy. Pathways were characterized using HUMAnN2 (v0.11.2)98 and Uniref90 d ­ atabase97 based on Bray–Curtis distance. CA1 and CA2 selected as the major components based on the eigenvalue. Scientific Reports | Vol:.(1234567890) (2023) 13:1023 | https://doi.org/10.1038/s41598-023-27706-0 8 www.nature.com/scientificreports/ gl1 B. pseudolongum subsp. globosum gl2 B. pseudolongum subsp. pseudolongum ps pseudolongum GCF 004155015 ATCC25526 pseudolongum GCF 000741325 pseudolongum GCF 004155835 pseudolongum GCF 002846755 pseudolongum GCF 002846725 pseudolongum GCF 004155725 pseudolongum GCF 004155395 pseudolongum GCF 004155715 globosum GCF 004155325 globosum GCF 004155435 globosum GCF 004155425 globosum GCF 004155405 globosum GCF 004155115 globosum GCF 004155855 globosum DSM 20092 GCF 002706665 globosum GCF 004155695 globosum GCF 004168525 globosum GCF 004156145 globosum GCF 002846675 globosum GCF 004155045 globosum GCF 002846685 globosum GCF 004155645 globosum GCF 004155145 globosum GCF 004155305 globosum GCF 004155625 globosum GCF 004155135 globosum GCF 004156235 globosum GCF 004155285 globosum GCF 004156115 globosum GCF 002846715 globosum GCF 004155235 globosum GCF 004155595 globosum GCF 002846835 globosum GCF 002846845 AGR2145 globosum GCF 004155745 globosum GCF 004155635 globosum GCF 004155805 PV8 2 globosum GCF 004155705 globosum GCF 004155565 globosum GCF 004156135 globosum GCF 004155535 globosum GCF 002846815 globosum GCF 004155095 globosum GCF 002846775 E EM13 EM10 globosum GCF 004155505 UMB-MBP-01 globosum GCF 004154995 globosum GCF 004155525 globosum GCF 004156085 AF13 3LB globosum GCF 004155475 S22 20 globosum GCF 004155615 globosum GCF 004155375 globosum GCF 004156175 NM87 A27A Num contributing genomes Num genes in GC gl3 ATCC25526 GCF 000741325 GCF 004155835 GCF 004155015 GCF 002846755 GCF 002846725 GCF 004155725 GCF 004155395 GCF 004155715 GCF 004155325 GCF 004155435 GCF 004155425 GCF 004155405 GCF 004155115 GCF 004155855 GCF 002706665 GCF 004155695 GCF 004168525 GCF 004156145 GCF 002846675 GCF 004155045 GCF 002846685 GCF 004155645 GCF 004155145 GCF 004155305 GCF 004155625 GCF 004155135 GCF 004156235 GCF 004155285 GCF 004156115 GCF 002846715 GCF 004155235 GCF 004155595 AGR2145 GCF 002846835 GCF 002846845 PV8 2 GCF 004155745 GCF 004155635 GCF 004155805 GCF 004155705 GCF 004155565 GCF 004156135 GCF 004155535 E GCF 002846815 EM13 GCF 004155095 EM10 GCF 002846775 GCF 004155505 UMB MBP01 AF13 3LB GCF 004154995 GCF 004155525 GCF 004156085 GCF 004155475 S22 20 NM87 A27A GCF 004155615 GCF 004155375 GCF 004156175 Num gene clusters re Singleton gene clusters GC-content Total length co e y bl sa or ss en ce sp di ac Figure 6.  Pangenome analyses of B. pseudolongum genomes. Pangenome constructed using 79 strains, including the 5 strains sequenced in this study (Supplemental Table 3) and displayed using anvi’o vers 6.274. Homologous gene clusters (HGCs) were identified based on all-versus-all sequence similarity in left panel and categorized as core, accessory or dispensable depending on their level of conservation. Genome ANI (Average Nucleotide Identity) was calculated using Sourmash vers 3.376. Blue arrows indicate the two strains compared: ATCC25526 and UMB-MBP-001. Black arrows indicate the other three B. pseudolongum strains isolated from the source stool of pregnant mice. found in globosum clade III genomes suggested a high degree of genome plasticity to facilitate adaptation to cope with environmental heterogeneity. Further functional enrichment analyses revealed globosum cluster IIIspecific HGCs were mostly involved in periplasmic transport systems, permeases and glycoside hydrolases (GHs), particularly the families GH29 (α-L-fucosidase), GH3 (β-glucosidase) and GH31 (α-glucosidase) (Supplemental Table 1E). No GH families were enriched in any of the other clades. Together, UMB-MBP-01 and ATCC25526 belonged to two different subspecies, each of which comprises considerable genetic variation. The genome of UMB-MBP-01 contained more clade-specific genes and was enriched for genetic features in carbohydrate metabolism to assimilate greater varieties of glycans. Further investigation is needed to characterize the role of carbohydrate metabolism in niche adaptive capabilities of murine isolates in the glycan-rich murine gut microenvironment. We sought to characterize the secretome of B. pseudolongum by in silico examining protein localization based on the presence of a signal p ­ eptide43. Proteins which are secreted extracellularly have the potential to directly interact with the other gut microorganisms and with host tissues (Supplemental Table 3A)27,44. Overall, the secdependent secretion machinery, but not the twin-arginine (Tat) system, was conserved in all B. pseudolongum strains, indicating protein translocation function was conserved but likely occurs only in the unfolded s­ tate45. Secreted proteins were more likely to be part of the dispensable genome (73% of secreted proteins versus 53% of cytoplasmic proteins; Supplemental Table 3B), indicating a high degree of diversity in the secretome among strains of B. pseudolongum. Proteins which were predicted to be extracellularly secreted include solute-binding proteins of ABC transporter systems, amidases related to the peptidoglycan hydrolysis, glycosyl hydrolyses, cell surface proteins that make up pilus subunits, and cell wall-degrading peptidases. Interestingly, the secretome of the clade containing ATCC25526 was enriched for collagen adhesion proteins (Supplemental Table 3C) but lacked multiple secreted GH25 extracellular proteins. These proteins are prevalent in the clade which includes UMB-MBP-01 and are involved in the binding and hydrolysis of peptidoglycan (Supplemental Table 5D). As peptidoglycan components were implicated in important aspects of mucosal immunological s­ ignaling46, this may contribute to varied immunomodulatory capabilities between UMB-MBP-01 and ATCC25526. Specialized carbohydrate metabolizing capabilities of UMB‑MBP‑01 and ATCC25526. The abundance of Bifidobacterium glycolytic features is reflective of their metabolic adaptation to the complex carbohydrate-rich GI ­tract47,48. We performed in silico prediction of the carbohydrate fermentation capabilities to comprehensively investigate glycan-assimilation capabilities for all 79 B. pseudolongum genomes, using with Scientific Reports | (2023) 13:1023 | https://doi.org/10.1038/s41598-023-27706-0 9 Vol.:(0123456789) www.nature.com/scientificreports/ the Carbohydrate-Active enZYmes Database (CAZy) ­database49. This analysis revealed 236 genes of B. pseudolongum pangenome encoding predicted carbohydrate-active enzymes from 34 glycosyl hydrolase families, 14 glycosyl transferase families and eight carbohydrate esterase families (Supplemental Table 4A). Only 33.5% of the carbohydrate-active enzyme coding genes belonged to the core pangenome. Core GHs included those mostly responsible for the breakdown of plant-derived polysaccharides (i.e., starch) and a wide range of other carbohydrates, such as GH13 (glycosidase), GH77 (α-amylase), GH43 (β-xylosidase), GH36 (α-galactosidase), GH2 (β-galactosidase), GH3, and GH6 (cellobiohydrolases). Notably, GH13 is the enzyme family known to be most commonly found in Bifidobacterium genomes and active on a wide range of carbohydrates including the plant-derived starch and the related substrates of trehalose, stachyose, raffinose, and m ­ elibiose48,50. Conversely, 47.9% of the identified carbohydrate-active enzymes genes were found in the dispensable pangenome. The globosum clade II (N = 72) and III (N = 58) encoded most of these enzymes, while the pseudolongum clade encoded the least (N = 13). These results demonstrated the highly specialized carbohydrate assimilation gene repertoires of different strains, particularly in globosum clade II and III. Using UMB-MBP-01 as the reference for all other B. pseudolongum strains, both conserved and specific glycohydrolases capabilities were revealed (Supplemental Fig. 2, Supplemental Table 1F, 4B). Interestingly, the clusters based on GH are mostly in agreement with the clades generated based on ANI, suggesting distinct carbohydrates assimilation capabilities of different B. pseudolongum clades. GH29, GH31, GH42 (β-galactosidase), and ABC-type polysaccharide transport permease genes were most prevalent in globosum clade III that contained UMB-MBP-01. Further, GH36, GH2, and GH94 (cellobiose phosphorylase) were found absent in subspecies pseudolongum clade but prevalent in globosum clade III. In particular, an uncommon GH23 family (peptidoglycan lyses) was only observed in UMB-MBP-01 and the three other isolates from the pregnant mouse. Overall UMB-MBP-01 and ATCC25526 share some enzymatic capabilities in metabolizing dietary polysaccharides and host-derived glycogens, while also having specialized glycohydrolases genes. We further characterize the carbohydrate utilization capabilities of UMB-MBP-01 and ATCC25526 using anaerobic microplates pre-coated with various carbon sources. Out of the 95 carbon sources tested, the two strains demonstrated the same capabilities on 86 (90.5%) (Supplemental Table 5), including key carbon sources N-acetyl-D-glucosamine, D-fructose, L-fucose, α-D-glucose, glucose-6-phosphate, maltose, maltotriose, D-mannose, D-sorbitol, and pyruvic acid. Two relatively uncommon sugars D-melibiose and D-raffinose could be metabolized by ATCC25526 but not UMB-MBP-01. On the other hand, D-galactose, D-gluconic acid, D-glucosaminic acid, glycerol, D-mannitol, α-ketovaleric acid, and D, L-lactic acid were uniquely metabolized by UMB-MBP-01. This result is in principle in an agreement of the specific GH families predicated in silico. Together these data indicated a wide range of carbohydrate metabolizing capabilities ranging from dietary to host-derived glycans for both strains, while UMB-MBP-01 had specialized capabilities to metabolize galacto-oligosaccharides. Discussion Bifidobacterium pseudolongum demonstrates great intraspecies genetic diversity and shows patterns consistent with host specificity, rendering it an advantageous model organism to study the effect of intraspecies variation on host ­immunomodulation42. Further, as a predominant species in the murine GI tract, B. pseudolongum displays an extensive enzymatic capacity and might act as a keystone species in this e­ nvironment42,51. In this study, we employed the murine strain UMB-MBP-01, which demonstrates an anti-inflammatory and pro-homeostatic ­effect33,34, and porcine-isolated B. pseudolongum strain ATCC25526 to investigate the strain-specific mechanisms of host responses in culture and in vivo. The distinct genetic attributes and immunomodulatory capabilities between UMB-MBP-01 and the ATCC25526 show that B. pseudolongum modulates intestinal responses and host immunity in a strain-specific manner. Using our clinically relevant murine model, we observed UMB-MBP-01 exerted stronger immunologic effects in intestinal responses mostly likely through regulation of multiple aspects of lymphocyte functions, while ATCC25526 appeared to exert immunomodulatory effects, at least in part, via stimulation of phagocytosis and induced lipid metabolism. We further demonstrated the in culture that B. pseudolongum elicited strain-specific activation and cytokine responses in isolated DC and MΦ. B. pseudolongum also uniquely changed in local and systemic leukocyte distribution and LN morphology in vivo, demonstrating the unique immune modulatory effects of the two strains. Furthermore, in the small intestine segments, UMBMBP-01 was most impactful in modulating Tregs, while ATCC25526 most pronouncedly increased DCs. We speculate that these strain-specific immunomodulatory effects are rooted in their niche adaption due to the different mammalian gut microenvironments from which they were derived. This reinforces the importance of understanding strain-specific immunomodulatory properties and host tropism that underline the beneficial effects of probiotics, which is fundamentally critical to inform selection of probiotic strains as therapeutic targets. It remains unclear whether B. pseudolongum immune and intestinal modulation is mediated through direct interactions with the intestinal epithelium, or indirectly via modulation of endogenous gut microbiome with consequent effects on intestinal metabolism and immunity, or b ­ oth18. In our study, the administration of two separate B. pseudolongum strains resulted in profoundly different gut microbiomes in both structure and functional capabilities as well as intestinal responses, suggesting the critical involvement of the endogenous gut microbiome as a key element of their immunomodulatory attributes and indicating likely indirect effects. Future investigations on the functional output of the gut microbial community would provide important insights on the mechanistic role of gut microbiome that may critically contribute to host regulation. Our results align with recent key clinical findings, suggesting that Bif