Gut microbiota, specifically gut bacteria, are critical for effective immune checkpoint blockade therapy (ICT) for cancer. The mechanisms by which gut microbiota augment extraintestinal anticancer immune responses, however, are largely unknown. Here, we find that ICT induces the translocation of specific endogenous gut bacteria into secondary lymphoid organs and subcutaneous melanoma tumors. Mechanistically, ICT induces lymph node remodeling and dendritic cell (DC) activation, which facilitates the translocation of a selective subset of gut bacteria to extraintestinal tissues to promote optimal antitumor T cell responses in both the tumor-draining lymph nodes (TDLNs) and the primary tumor. Antibiotic treatment results in decreased gut microbiota translocation into mesenteric lymph nodes (MLNs) and TDLNs, diminished DC and effector CD8 ⁺ T cell responses, and attenuated responses to ICT. Our findings illuminate a key mechanism by which gut microbiota promote extraintestinal anticancer immunity.

Precision probiotics have shown great promise as novel therapies but have not been fully realized. One major obstacle is that different strains of the same gut microbiota species can induce markedly variable phenotypic outcomes. Here, we aimed to optimize and validate in a preclinical model, a six-species precision probiotic therapy for graft-versus-host disease (GVHD), an autoimmune complication following allogeneic stem cell transplantation. We had identified these six species as associated with protection against GVHD in a prior clinical study. We isolated strains of three of the targeted taxa (B. longum, C. bolteae, and Blautia spp.) from human stem cell transplant patients and characterized their SCFA production in vitro. We observed significant strain-to-strain variability among these gut microbiota taxa in their capacity to produce short-chain fatty acids, a microbiota-derived metabolite shown to be important for mitigating gut GVHD and inflammatory bowel disease, in vitro. We found that B. longum was able to augment butyrate production by C. bolteae and Blautia when co-cultured in vitro. “Optimized” precision probiotics mitigated GVHD and significantly increased survival (p = 0.013, log-rank test) in mice compared to a “standard” probiotic consortium of the same bacterial species obtained from a commercial repository. Importantly, the optimized probiotics resulted in significant increases in intestinal short-chain fatty acid concentrations compared to standard probiotics (p < 0.001, Mann–Whitney test). Our findings highlight the promising potential of utilizing an optimized precision probiotic approach to maximize therapeutic efficacy.

Background/Objectives: Preterm infants often require increased caloric intake to maintain appropriate growth while in the neonatal intensive care unit (NICU). Emerging evidence suggests that alterations of the gut microbiome may play a role in infant and childhood growth patterns. The fecal microbiome patterns in infants with normal and poor growth patterns were classified in this study. Methods: We conducted a prospective trial of infants of less than 29 weeks’ gestation with an embedded case–control analysis of infants with normal or poor growth patterns. Fecal samples were collected weekly from infants on full enteral feeds and analyzed blindly using 16s rRNA next-generation sequencing. The relationship between gut microbial diversity and composition and growth pattern and trajectory were assessed. Results: A total of 115 infants were enrolled in the trial with 263 fecal samples selected from 87 enrolled infants for analysis. In total, 37 samples were available from the normal growth cohort, 56 samples from the poor growth cohort, and 170 samples were available for analysis from the very poor growth cohort. Analysis of relative abundance revealed increased representation of Veillonella, Bifidobacterium, and Clostridium in very poor growth infants compared to normal growth infants. Variation in specific taxa was also found to vary significantly across post-menstrual age depending on the degree of growth failure. Conclusions: Gut microbiome composition and variance was modified by the degree of growth failure in our cohort of preterm infants. Our study adds to the growing body of evidence that alteration of the microbiome is associated with poor growth in preterm infants. This may ultimately represent a therapeutic target for growth failure in preterm infants.

Gut microbiota are critical determinants of effective immune checkpoint therapy (ICT), yet the microbial mediators and host mechanisms that enhance antitumor immunity remain poorly understood. Here, we identify the microbiota-derived bile acid taurodeoxycholic acid (TDCA) as a metabolite associated with immune checkpoint therapy (ICT) response. TDCA administration alone is sufficient to overcome antibiotic-induced ICT hyporesponsiveness across multiple murine tumor models. Mechanistically, TDCA directly enhances CD8⁺ T cell–mediated antitumor immunity, increasing cytotoxicity. These effects required signaling through the bile acid receptor TGR5. Together, these findings reveal TDCA as a gut microbial metabolite that restores ICT efficacy after antibiotic disruption by directly augmenting CD8⁺ T cell anti-tumor activity. This work supports metabolite replacement as a therapeutic strategy to mitigate antibiotic-associated loss of cancer immunotherapy response. Significance: TDCA is a microbiota-derived metabolite that restores immune checkpoint therapy efficacy after antibiotic disruption by directly enhancing CD8⁺ T-cell–mediated anti-tumor immunity through bile acid receptor TGR5 signaling. Our findings suggest that supplementation with defined microbial metabolites can mitigate antibiotic-associated loss of immunotherapy response without requiring broader microbiome reconstitution.

Background/Objectives: Oxford Nanopore sequencing produces long reads quickly, but most functional profiling tools were developed for short reads or rely on assembly pipelines that are computationally costly and sensitive to long-read error rates. We present NanoPrism, a taxonomy-guided pipeline for rapid functional profiling of long-read metagenomes. Methods: NanoPrism (i) identifies sample composition with Kraken2, (ii) constructs compact species-specific coding sequence (CDS)–KEGG ortholog databases, and (iii) estimates ortholog abundances by direct minimap2 alignment of nanopore reads with single-copy marker normalization. We evaluated NanoPrism on simulated Pseudomonas aeruginosa PAO1 and PA14 reads and on ZymoBIOMICS mock-community datasets sequenced on GridION and PromethION platforms. Results: On the Zymo long-read datasets, NanoPrism achieved Pearson correlations of 0.917–0.922 against independent expected ortholog profiles under unit-sum normalization. On matched one-million-read subsets, NanoPrism achieved higher correlations and lower Jensen–Shannon distances and mean absolute errors than the evaluated DIAMOND-based MEGAN-LR workflow. Experiments that omitted one species at a time from the reference database showed that omission of low-abundance community members had limited effects on the aggregate KO profile, whereas omission of the dominant Listeria monocytogenes reference from the Log community reduced Pearson correlation from approximately 0.92 to 0.29. Conclusions: NanoPrism offers a computationally efficient option for taxonomy-guided functional profiling of bacterial isolates and defined microbial communities. Validation on complex clinical and environmental metagenomes, broader forms of taxonomic-classification error, and dedicated fungal benchmarks remain necessary.