Susceptible bacteria can survive antibiotic treatment in the mammalian gastrointestinal tract without evolving resistance.

Antibiotic resistance and evasion are incompletely understood and complicated by the fact that murine interval dosing models do not fully recapitulate antibiotic pharmacokinetics in humans. To better understand how gastrointestinal bacteria respond to antibiotics, we colonized germ-free mice with a pan-susceptible genetically barcoded Escherichia coli clinical isolate and administered the antibiotic cefepime via programmable subcutaneous pumps, allowing closer emulation of human parenteral antibiotic dynamics. E. coli was only recovered from intestinal tissue, where cefepime concentrations were still inhibitory. Strikingly, "some" E. coli isolates were not cefepime resistant but acquired mutations in genes involved in polysaccharide capsular synthesis increasing their invasion and survival within human intestinal cells. Deleting wbaP involved in capsular polysaccharide synthesis mimicked this phenotype, allowing increased invasion of colonocytes where cefepime concentrations were reduced. Additionally, "some" mutant strains exhibited a persister phenotype upon further cefepime exposure. This work uncovers a mechanism allowing "select" gastrointestinal bacteria to evade antibiotic treatment.

Precision modulation of dysbiotic adult microbiomes with a human-milk-derived synbiotic reshapes gut microbial composition and metabolites.

Manipulation of the gut microbiome using live biotherapeutic products shows promise for clinical applications but remains challenging to achieve. Here, we induced dysbiosis in 56 healthy volunteers using antibiotics to test a synbiotic comprising the infant gut microbe, Bifidobacterium longum subspecies infantis (B. infantis), and human milk oligosaccharides (HMOs). B. infantis engrafted in 76% of subjects in an HMO-dependent manner, reaching a relative abundance of up to 81%. Changes in microbiome composition and gut metabolites reflect altered recovery of engrafted subjects compared with controls. Engraftment associates with increases in lactate-consuming Veillonella, faster acetate recovery, and changes in indolelactate and p-cresol sulfate, metabolites that impact host inflammatory status. Furthermore, Veillonella co-cultured in vitro and in vivo with B. infantis and HMO converts lactate produced by B. infantis to propionate, an important mediator of host physiology. These results suggest that the synbiotic reproducibly and predictably modulates recovery of a dysbiotic microbiome.

IsoAnalytics: a single-cell proteomics web server.

Motivation: Single-cell proteomics provide unprecedented resolution to examine biological processes. Customized data analysis and facile data visualization are crucial for scientific discovery. Further, user-friendly data analysis and visualization software that is easily accessible for the general scientific community is essential. Results: We have created a web server, IsoAnalytics, that gives users without computational or bioinformatics background the ability to directly analyze and interactively visualize data obtained from the Isoplexis single cell technology platform. We envision this open-sourced web server will increase research productivity and serve as a free, competitive alternative for single-cell proteomics research. Availability and implementation: IsoAnalytics is free and available at: https://cdc.biohpc.swmed.edu/isoplexis/ and is implemented in Python, with all major browsers supported. Code for IsoAnalytics is free and available at: https://github.com/zhanxw/Isoplexis_Data_Analysis. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

Immune checkpoint blockade induces gut microbiota translocation that augments extraintestinal antitumor immunity.

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.

Susceptible bacteria survive antibiotic treatment in the mammalian gastrointestinal tract without evolving resistance.

In vitro systems have provided great insight into the mechanisms of antibiotic resistance. Yet, in vitro approaches cannot reflect the full complexity of what transpires within a host. As the mammalian gut is host to trillions of resident bacteria and thus a potential breeding ground for antibiotic resistance, we sought to better understand how gut bacteria respond to antibiotic treatment in vivo . Here, we colonized germ-free mice with a genetically barcoded antibiotic pan-susceptible Escherichia coli clinical isolate and then administered the antibiotic cefepime via programmable subcutaneous pumps which allowed for closer emulation of human parenteral antibiotic pharmacokinetics/dynamics. After seven days of antibiotics, we were unable to culture E. coli from feces. We were, however, able to recover barcoded E. coli from harvested gastrointestinal (GI) tissue, despite high GI tract and plasma cefepime concentrations. Strikingly, these E. coli isolates were not resistant to cefepime but had acquired mutations â€" most notably in the wbaP gene, which encodes an enzyme required for the initiation of the synthesis of the polysaccharide capsule and lipopolysaccharide O antigen - that increased their ability to invade and survive within intestinal cells, including cultured human colonocytes. Further, these E. coli mutants exhibited a persister phenotype when exposed to cefepime, allowing for greater survival to pulses of cefepime treatment when compared to the wildtype strain. Our findings highlight a mechanism by which bacteria in the gastrointestinal tract can adapt to antibiotic treatment by increasing their ability to persist during antibiotic treatment and invade intestinal epithelial cells where antibiotic concentrations are substantially reduced.

IsoAnalytics: A Single-cell Proteomics Web Server.

Motivation: Single-cell proteomics provide unprecedented resolution to examine biological processes. Customized data analysis and facile data visualization are crucial for scientific discovery. Further, userfriendly data analysis and visualization software that is easily accessible for the general scientific community is essential. Results: We have created a web server, IsoAnalytics , that gives users without computational or bioinformatics background the ability to directly analyze and interactively visualize data obtained from the Isoplexis single cell technology platform. We envision this open-sourced web server will increase research productivity and serve as a free, competitive alternative for single-cell proteomics research. Contact: Andrew.Koh@utsouthwestern.edu and Xiaowei.Zhan@utsouthwestern.edu. Availability: IsoAnalytics is free and available at: https://cdc.biohpc.swmed.edu/isoplexis/ and is implemented in Python, with all major browsers supported. Code for IsoAnalytics is free and available at: https://github.com/zhanxw/Isoplexis_Data_Analysis . Supplementary Information: Supplementary data are available at Bioinformatics online.

MB-SupCon: Microbiome-based Predictive Models via Supervised Contrastive Learning.

Human microbiome consists of trillions of microorganisms. Microbiota can modulate the host physiology through molecule and metabolite interactions. Integrating microbiome and metabolomics data have the potential to predict different diseases more accurately. Yet, most datasets only measure microbiome data but without paired metabolome data. Here, we propose a novel integrative modeling framework, Microbiome-based Supervised Contrastive Learning Framework (MB-SupCon). MB-SupCon integrates microbiome and metabolome data to generate microbiome embeddings, which can be used to improve the prediction accuracy in datasets that only measure microbiome data. As a proof of concept, we applied MB-SupCon on 720 samples with paired 16S microbiome data and metabolomics data from patients with type 2 diabetes. MB-SupCon outperformed existing prediction methods and achieved high average prediction accuracies for insulin resistance status (84.62%), sex (78.98%), and race (80.04%). Moreover, the microbiome embeddings form separable clusters for different covariate groups in the lower-dimensional space, which enhances data visualization. We also applied MB-SupCon on a large inflammatory bowel disease study and observed similar advantages. Thus, MB-SupCon could be broadly applicable to improve microbiome prediction models in multi-omics disease studies.

Dosing a synbiotic of human milk oligosaccharides and B. infantis leads to reversible engraftment in healthy adult microbiomes without antibiotics.

Predictable and sustainable engraftment of live biotherapeutic products into the human gut microbiome is being explored as a promising way to modulate the human gut microbiome. We utilize a synbiotic approach pairing the infant gut microbe Bifidobacterium longum subspecies infantis (B. infantis) and human milk oligosaccharides (HMO). B. infantis, which is typically absent in adults, engrafts into healthy adult microbiomes in an HMO-dependent manner at a relative abundance of up to 25% of the bacterial population without antibiotic pretreatment or adverse effects. Corresponding changes in metabolites are detected. Germ-free mice transplanted with dysbiotic human microbiomes also successfully engraft with B. infantis in an HMO-dependent manner, and the synbiotic augments butyrate levels both in this in vivo model and in in vitro cocultures of the synbiotic with specific Firmicutes species. Finally, the synbiotic inhibits the growth of enteropathogens in vitro. Our findings point to a potential safe mechanism for ameliorating dysbioses characteristic of numerous human diseases.

Association between Antibiotic Exposure and Systemic Immune Parameters in Cancer Patients Receiving Checkpoint Inhibitor Therapy.

Antibiotic administration is associated with worse clinical outcomes and changes to the gut microbiome in cancer patients receiving immune checkpoint inhibitors (ICI). However, the effects of antibiotics on systemic immune function are unknown. We, therefore, evaluated antibiotic exposure, therapeutic responses, and multiplex panels of 40 serum cytokines and 124 antibodies at baseline and six weeks after ICI initiation, with p < 0.05 and false discovery rate (FDR) < 0.2 considered significant. A total of 251 patients were included, of whom the 135 (54%) who received antibiotics had lower response rates and shorter survival. Patients who received antibiotics prior to ICI initiation had modestly but significantly lower baseline levels of nucleolin, MDA5, c-reactive protein, and liver cytosol antigen type 1 (LC1) antibodies, as well as higher levels of heparin sulfate and Matrigel antibodies. After ICI initiation, antibiotic-treated patients had significantly lower levels of MDA5, CENP.B, and nucleolin antibodies. Although there were no clear differences in cytokines in the overall cohort, in the lung cancer subset (53% of the study population), we observed differences in IFN-γ, IL-8, and macrophage inflammatory proteins. In ICI-treated patients, antibiotic exposure is associated with changes in certain antibodies and cytokines. Understanding the relationship between these factors may improve the clinical management of patients receiving ICI.

Candida albicans Isolates 529L and CHN1 Exhibit Stable Colonization of the Murine Gastrointestinal Tract.

Candida albicans is a pathobiont that colonizes multiple niches in the body including the gastrointestinal (GI) tract but is also responsible for both mucosal and systemic infections. Despite its prevalence as a human commensal, the murine GI tract is generally refractory to colonization with the C. albicans reference isolate SC5314. Here, we identify two C. albicans isolates, 529L and CHN1, that stably colonize the murine GI tract in three different animal facilities under conditions where SC5314 is lost from this niche. Analysis of the bacterial microbiota did not show notable differences among mice colonized with the three C. albicans strains. We compared the genotypes and phenotypes of these three strains and identified thousands of single nucleotide polymorphisms (SNPs) and multiple phenotypic differences, including their ability to grow and filament in response to nutritional cues. Despite striking filamentation differences under laboratory conditions, however, analysis of cell morphology in the GI tract revealed that the three isolates exhibited similar filamentation properties in this in vivo niche. Notably, we found that SC5314 is more sensitive to the antimicrobial peptide CRAMP, and the use of CRAMP-deficient mice modestly increased the ability of SC5314 to colonize the GI tract relative to CHN1 and 529L. These studies provide new insights into how strain-specific differences impact C. albicans traits in the host and advance CHN1 and 529L as relevant strains to study C. albicans pathobiology in its natural host niche. IMPORTANCE Understanding how fungi colonize the GI tract is increasingly recognized as highly relevant to human health. The animal models used to study Candida albicans commensalism commonly rely on altering the host microbiome (via antibiotic treatment or defined diets) to establish successful GI colonization by the C. albicans reference isolate SC5314. Here, we characterize two C. albicans isolates that can colonize the murine GI tract without antibiotic treatment and can therefore be used as tools for studying fungal commensalism. Importantly, experiments were replicated in three different animal facilities and utilized three different mouse strains. Differential colonization between fungal isolates was not associated with alterations in the bacterial microbiome but rather with distinct responses to CRAMP, a host antimicrobial peptide. This work emphasizes the importance of C. albicans intraspecies variation as well as host antimicrobial defense mechanisms in defining the outcome of commensal interactions.

The microbial and host factors that govern Candida gastrointestinal colonization and dissemination.

Candida species are among the most prevalent and abundant members of the gut mycobiota, with Candida albicans (CA) being the most prominent member. CA colonizes numerous mucosal surfaces, most notably the gastrointestinal (GI) and genitourinary tracts. In a healthy host, CA is a pathobiont that exists as a commensal but can become pathogenic if the host's immune system becomes suppressed. The microbial and/or host factors that dictate CA's ability to colonize mucosal surfaces and its ability to disseminate remain of great interest. Here, we review the recent advances and insights regarding Candida colonization and dissemination of the mammalian GI tract.

The Antibiotic Efflux Protein TolC Is a Highly Evolvable Target under Colicin E1 or TLS Phage Selection.

Bacteriophages and bacterial toxins are promising antibacterial agents to treat infections caused by multidrug-resistant (MDR) bacteria. In fact, bacteriophages have recently been successfully used to treat life-threatening infections caused by MDR bacteria (Schooley RT, Biswas B, Gill JJ, Hernandez-Morales A, Lancaster J, Lessor L, Barr JJ, Reed SL, Rohwer F, Benler S, et al. 2017. Development and use of personalized bacteriophage-based therapeutic cocktails to treat a patient with a disseminated resistant Acinetobacter baumannii infection. Antimicrob Agents Chemother. 61(10); Chan BK, Turner PE, Kim S, Mojibian HR, Elefteriades JA, Narayan D. 2018. Phage treatment of an aortic graft infected with Pseudomonas aeruginosa. Evol Med Public Health. 2018(1):60-66; Petrovic Fabijan A, Lin RCY, Ho J, Maddocks S, Ben Zakour NL, Iredell JR, Westmead Bacteriophage Therapy Team. 2020. Safety of bacteriophage therapy in severe Staphylococcus aureus infection. Nat Microbiol. 5(3):465-472). One potential problem with using these antibacterial agents is the evolution of resistance against them in the long term. Here, we studied the fitness landscape of the Escherichia coli TolC protein, an outer membrane efflux protein that is exploited by a pore forming toxin called colicin E1 and by TLS phage (Pagie L, Hogeweg P. 1999. Colicin diversity: a result of eco-evolutionary dynamics. J Theor Biol. 196(2):251-261; Andersen C, Hughes C, Koronakis V. 2000. Chunnel vision. Export and efflux through bacterial channel-tunnels. EMBO Rep. 1(4):313-318; Koronakis V, Andersen C, Hughes C. 2001. Channel-tunnels. Curr Opin Struct Biol. 11(4):403-407; Czaran TL, Hoekstra RF, Pagie L. 2002. Chemical warfare between microbes promotes biodiversity. Proc Natl Acad Sci U S A. 99(2):786-790; Cascales E, Buchanan SK, Duché D, Kleanthous C, Lloubès R, Postle K, Riley M, Slatin S, Cavard D. 2007. Colicin biology. Microbiol Mol Biol Rev. 71(1):158-229). By systematically assessing the distribution of fitness effects of ∼9,000 single amino acid replacements in TolC using either positive (antibiotics and bile salts) or negative (colicin E1 and TLS phage) selection pressures, we quantified evolvability of the TolC. We demonstrated that the TolC is highly optimized for the efflux of antibiotics and bile salts. In contrast, under colicin E1 and TLS phage selection, TolC sequence is very sensitive to mutations. Finally, we have identified a large set of mutations in TolC that increase resistance of E. coli against colicin E1 or TLS phage without changing antibiotic susceptibility of bacterial cells. Our findings suggest that TolC is a highly evolvable target under negative selection which may limit the potential clinical use of bacteriophages and bacterial toxins if evolutionary aspects are not taken into account.

A trimethoprim derivative impedes antibiotic resistance evolution.

The antibiotic trimethoprim (TMP) is used to treat a variety of Escherichia coli infections, but its efficacy is limited by the rapid emergence of TMP-resistant bacteria. Previous laboratory evolution experiments have identified resistance-conferring mutations in the gene encoding the TMP target, bacterial dihydrofolate reductase (DHFR), in particular mutation L28R. Here, we show that 4'-desmethyltrimethoprim (4'-DTMP) inhibits both DHFR and its L28R variant, and selects against the emergence of TMP-resistant bacteria that carry the L28R mutation in laboratory experiments. Furthermore, antibiotic-sensitive E. coli populations acquire antibiotic resistance at a substantially slower rate when grown in the presence of 4'-DTMP than in the presence of TMP. We find that 4'-DTMP impedes evolution of resistance by selecting against resistant genotypes with the L28R mutation and diverting genetic trajectories to other resistance-conferring DHFR mutations with catalytic deficiencies. Our results demonstrate how a detailed characterization of resistance-conferring mutations in a target enzyme can help identify potential drugs against antibiotic-resistant bacteria, which may ultimately increase long-term efficacy of antimicrobial therapies by modulating evolutionary trajectories that lead to resistance.

Unbiased Microbiome and Metabolomic Profiling of Fecal Samples from Patients with Melanoma.

Gut microbiota influence and modulate host immune responses. In preclinical cancer models, mice lacking gut microbiota have a markedly diminished response to immune checkpoint inhibitor therapy. Further, in melanoma patients, specific commensal gut microbiota have been associated with a positive clinical response to immunotherapy. In order to study the gut microbiome and metabolome, we have developed methods for fecal sample collection and processing, microbiome and metabolome profiling, and bioinformatic analysis. This protocol will be a useful tool for interrogating the taxonomic composition and functional output of a melanoma patient's gut microbiome.

A Bayesian zero-inflated negative binomial regression model for the integrative analysis of microbiome data.

Microbiome omics approaches can reveal intriguing relationships between the human microbiome and certain disease states. Along with identification of specific bacteria taxa associated with diseases, recent scientific advancements provide mounting evidence that metabolism, genetics, and environmental factors can all modulate these microbial effects. However, the current methods for integrating microbiome data and other covariates are severely lacking. Hence, we present an integrative Bayesian zero-inflated negative binomial regression model that can both distinguish differentially abundant taxa with distinct phenotypes and quantify covariate-taxa effects. Our model demonstrates good performance using simulated data. Furthermore, we successfully integrated microbiome taxonomies and metabolomics in two real microbiome datasets to provide biologically interpretable findings. In all, we proposed a novel integrative Bayesian regression model that features bacterial differential abundance analysis and microbiome-covariate effects quantifications, which makes it suitable for general microbiome studies.

Transient neonatal antibiotic exposure increases susceptibility to late-onset sepsis driven by microbiota-dependent suppression of type 3 innate lymphoid cells.

Extended early antibiotic exposure in the neonatal intensive care unit is associated with an increased risk for the development of late-onset sepsis (LOS). However, few studies have examined the mechanisms involved. We sought to determine how the neonatal microbiome and intestinal immune response is altered by transient early empiric antibiotic exposure at birth. Neonatal mice were transiently exposed to broad-spectrum antibiotics from birth for either 3- (SE) or 7-days (LE) and were examined at 14-days-old. We found that mice exposed to either SE or LE showed persistent expansion of Proteobacteria (2 log difference, P < 0.01). Further, LE mice demonstrated baseline translocation of E. coli into the liver and spleen and were more susceptible K. pneumoniae-induced sepsis. LE mice had a significant and persistent decrease in type 3 innate lymphoid cells (ILC3) in the lamina propria. Reconstitution of the microbiome with mature microbiota by gavage in LE mice following antibiotic exposure resulted in an increase in ILC3 and partial rescue from LOS. We conclude that prolonged exposure to broad spectrum antibiotics in the neonatal period is associated with persistent alteration of the microbiome and innate immune response resulting in increased susceptibility to infection that may be partially rescued by microbiome reconstitution.

HARMONIES: A Hybrid Approach for Microbiome Networks Inference via Exploiting Sparsity.

The human microbiome is a collection of microorganisms. They form complex communities and collectively affect host health. Recently, the advances in next-generation sequencing technology enable the high-throughput profiling of the human microbiome. This calls for a statistical model to construct microbial networks from the microbiome sequencing count data. As microbiome count data are high-dimensional and suffer from uneven sampling depth, over-dispersion, and zero-inflation, these characteristics can bias the network estimation and require specialized analytical tools. Here we propose a general framework, HARMONIES, Hybrid Approach foR MicrobiOme Network Inferences via Exploiting Sparsity, to infer a sparse microbiome network. HARMONIES first utilizes a zero-inflated negative binomial (ZINB) distribution to model the skewness and excess zeros in the microbiome data, as well as incorporates a stochastic process prior for sample-wise normalization. This approach infers a sparse and stable network by imposing non-trivial regularizations based on the Gaussian graphical model. In comprehensive simulation studies, HARMONIES outperformed four other commonly used methods. When using published microbiome data from a colorectal cancer study, it discovered a novel community with disease-enriched bacteria. In summary, HARMONIES is a novel and useful statistical framework for microbiome network inference, and it is available at https://github.com/shuangj00/HARMONIES.

The gut microbiome and thromboembolism.

The gut microbiome plays a critical role in various inflammatory conditions, and its modulation is a potential treatment option for these conditions. The role of the gut microbiome in the pathogenesis of thromboembolism has not been fully elucidated. In this review, we summarize the evidence linking the gut microbiome to the pathogenesis of arterial and venous thrombosis. In a human host, potentially pathogenic bacteria are normal residents of the human gut microbiome, but significantly outnumbered by commensal anaerobic bacteria. Several disease states with an increased risk of venous thromboembolism (VTE) are associated with an imbalance in the gut microbiome characterized by a decrease in commensal anaerobic bacteria and an increase in the abundance of pathogenic bacteria of which the most common is the gram-negative Enterobacteriaceae (ENTERO) family. Bacterial lipopolysaccharides (LPS), the glycolipids found on the outer membrane of gram-negative bacteria, is one of the links between the microbiome and hypercoagulability. LPS binds to toll-like receptors to activate endothelial cells and platelets, leading to activation of the coagulation cascade. Bacteria in the microbiome can also metabolite compounds in the diet to produce important metabolites like trimethylamine-N-oxide (TMAO). TMAO causes platelet hyperreactivity, promotes thrombus formation and is associated with cardiovascular disease. Modulating the gut microbiome to target LPS and TMAO levels may be an innovative approach for decreasing the risk of thrombosis.

The Impact of Lactobacillus Probiotics on the Gut Microbiota in Children With Short Bowel Syndrome.

BACKGROUND: Children with short bowel syndrome (SBS) frequently struggle with malabsorption and poor growth. The intestinal microbiota plays an important role in gut function, and children with SBS have known deficiencies in some commensal gut microbes. One strategy to enhance the gut microbiota is by taking probiotics. However, the efficacy of this approach is not well established. We hypothesized that probiotic supplementation would result in increased levels of the supplemented bacteria and improved growth. MATERIALS AND METHODS: Children with SBS who had weaned from parenteral nutrition but with suboptimal growth were randomized to receive probiotics (Lactobacillus rhamnosus and Lactobacillus johnsonii) or placebo daily for 2 mo. The gut microbiota from monthly stool samples were compared between groups using 16S ribosomal ribonucleic acid sequencing and quantitative polymerase chain reaction. Growth between groups was also compared. Statistical analysis was completed using Mann-Whitney, Kruskal-Wallis, and chi-square tests as appropriate. RESULTS: Eighteen children with SBS completed the study (n = 9 per group). There were no significant changes to the major bacterial families in either group. Median relative abundance of Lactobacillus did not differ between groups at baseline or at the end of the study (7.67 versus 13.23, P = 0.523 and 1.93 versus 15.8, P = 0.161). Median z scores for weight and length did not differ between groups at the beginning or end of the study. CONCLUSIONS: The efficacy of daily probiotic use in children with intestinal failure is unknown. In this study, Lactobacillus probiotics did not result in a predictable change to the fecal microbiota or overall growth compared with placebo in these patients.

A comparison of small bowel and fecal microbiota in children with short bowel syndrome.

BACKGROUND: Babies with short bowel syndrome (SBS) have small intestinal microbial disturbances that impact gut function. Characterizing the small bowel microbiota is challenging, and the utility of sampling stool is unclear. This study compares the microbiota from fecal samples and the small bowel. METHODS: Stool samples were collected (2016-2017) from infants with SBS and colon in continuity (COLON) or SBS with small bowel ostomy (sbSTOMA). The abundance and quantity of major bacterial genera was compared between groups and to healthy controls using 16S rRNA sequencing and qPCR. Kruskall-Wallis test was used for analysis with P values <0.05 considered significant. RESULTS: Samples (n = 41) were collected from 15 SBS infants (<2 years) (9 sbSTOMA, 6 COLON) and 3 healthy infants. Demographics and small intestinal length did not differ between sbSTOMA and COLON infants. The microbiota of SBS groups differed significantly from healthy controls. Fecal samples contained higher quantities of bacteria, but there were no significant differences between sbSTOMA and COLON groups in the abundance of facultative or obligate anaerobes, anti-inflammatory Clostridia, Enterobacteriaceae, or Bifidobacterium. CONCLUSION: Infants with SBS have disturbances to their intestinal microbiota. Sampling small intestinal effluent is challenging. Stool samples may provide a window into the more proximal microbial community. TYPE OF STUDY: Diagnostic. LEVEL OF EVIDENCE: Level II.