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ABSTRACT Although antibiotics remain a cornerstone of modern medicine, the issues of widespread antibiotic resistance and collateral damage to the microbiome from antibiotic use are driving a need for drug developers to consider more tailored, patient-directed products to avoid antibiotic-induced perturbations of the structure and function of the indigenous microbiota. This perspective summarizes a cascade of microbiome health effects that is initiated by antibiotic-mediated microbiome disruption at an individual level and ultimately leads to infection and transmission of multidrug-resistant pathogens across patient populations. The scientific evidence behind each of the key steps of this cascade is presented. The interruption of this cascade through the use of highly targeted, microbiome-sparing antibiotics aiming to improve health outcomes is discussed. Further, this perspective reflects on some key clinical trial design and reimbursement considerations to be addressed as part of the drug development path.

Summary: Clostridioides difficile produces toxins that damage the colonic epithelium, causing colitis. Variation in disease severity is poorly understood and has been attributed to host factors and virulence differences between C. difficile strains. We test 23 epidemic ST1 C. difficile clinical isolates for their virulence in mice. All isolates encode a complete Tcd pathogenicity locus and achieve similar colonization densities. However, disease severity varies from lethal to avirulent infections. Genomic analysis of avirulent isolates reveals a 69-bp deletion in the cdtR gene, which encodes a response regulator for binary toxin expression. Deleting the 69-bp sequence in virulent R20291 strain renders it avirulent in mice with reduced toxin gene transcription. Our study demonstrates that a natural deletion within cdtR attenuates virulence in the epidemic ST1 C. difficile isolates without reducing colonization and persistence. Distinguishing strains on the basis of cdtR may enhance the specificity of diagnostic tests for C. difficile colitis.

Abstract Background Effective surveillance of microbial communities in the healthcare environment is increasingly important in infection prevention. Metagenomics-based techniques are promising due to their untargeted nature but are currently challenged by several limitations: (1) they are not powerful enough to extract valid signals out of the background noise for low-biomass samples, (2) they do not distinguish between viable and nonviable organisms, and (3) they do not reveal the microbial load quantitatively. An additional practical challenge towards a robust pipeline is the inability to efficiently allocate sequencing resources a priori. Assessment of sequencing depth is generally practiced post hoc, if at all, for most microbiome studies, regardless of the sample type. This practice is inefficient at best, and at worst, poor sequencing depth jeopardizes the interpretation of study results. To address these challenges, we present a workflow for metagenomics-based environmental surveillance that is appropriate for low-biomass samples, distinguishes viability, is quantitative, and estimates sequencing resources. Results The workflow was developed using a representative microbiome sample, which was created by aggregating 120 surface swabs collected from a medical intensive care unit. Upon evaluating and optimizing techniques as well as developing new modules, we recommend best practices and introduce a well-structured workflow. We recommend adopting liquid-liquid extraction to improve DNA yield and only incorporating whole-cell filtration when the nonbacterial proportion is large. We suggest including propidium monoazide treatment coupled with internal standards and absolute abundance profiling for viability assessment and involving cultivation when demanding comprehensive profiling. We further recommend integrating internal standards for quantification and additionally qPCR when we expect poor taxonomic classification. We also introduce a machine learning-based model to predict required sequencing effort from accessible sample features. The model helps make full use of sequencing resources and achieve desired outcomes. Video Abstract Conclusions This workflow will contribute to more accurate and robust environmental surveillance and infection prevention. Lessons gained from this study will also benefit the continuing development of methods in relevant fields.

ABSTRACT Susceptibility to Clostridioides difficile infection (CDI) typically follows the administration of antibiotics. Patients with inflammatory bowel disease (IBD) have increased incidence of CDI, even in the absence of antibiotic treatment. However, the mechanisms underlying this susceptibility are not well understood. To explore the intersection between CDI and IBD, we recently described a mouse model where colitis triggered by the murine gut bacterium, Helicobacter hepaticus, in IL-10−/− mice led to susceptibility to C. difficile colonization without antibiotic administration. The current work disentangles the relative contributions of inflammation and gut microbiota in colonization resistance to C. difficile in this model. We show that inflammation drives changes in microbiota composition, which leads to CDI susceptibility. Decreasing inflammation with an anti-p40 monoclonal antibody promotes a shift of the microbiota back toward a colonization-resistant state. Transferring microbiota from susceptible and resistant mice to germfree animals transfers the susceptibility phenotype, supporting the primacy of the microbiota in colonization resistance. These findings shine light on the complex interactions between the host, microbiota, and C. difficile in the context of intestinal inflammation, and may form a basis for the development of strategies to prevent or treat CDI in IBD patients. IMPORTANCE Patients with inflammatory bowel disease (IBD) have an increased risk of developing C. difficile infection (CDI), even in the absence of antibiotic treatment. Yet, mechanisms regulating C. difficile colonization in IBD patients remain unclear. Here, we use an antibiotic-independent mouse model to demonstrate that intestinal inflammation alters microbiota composition to permit C. difficile colonization in mice with colitis. Notably, treating inflammation with an anti-p40 monoclonal antibody, a clinically relevant IBD therapeutic, restores microbiota-mediated colonization resistance to the pathogen. Through microbiota transfer experiments in germfree mice, we confirm that the microbiota shaped in the setting of IBD is the primary driver of susceptibility to C. diffiicile colonization. Collectively, our findings provide insight into CDI pathogenesis in the context of intestinal inflammation, which may inform methods to manage infection in IBD patients. More broadly, this work advances our understanding of mechanisms by which the host-microbiota interface modulates colonization resistance to C. difficile.

ABSTRACT The severity of Clostridioides difficile infections (CDI) has increased over the last few decades. Patient age, white blood cell count, and creatinine levels as well as C. difficile ribotype and toxin genes have been associated with disease severity. However, it is unclear whether specific members of the gut microbiota are associated with variations in disease severity. The gut microbiota is known to interact with C. difficile during infection. Perturbations to the gut microbiota are necessary for C. difficile to colonize the gut. The gut microbiota can inhibit C. difficile colonization through bile acid metabolism, nutrient consumption, and bacteriocin production. Here, we sought to demonstrate that members of the gut bacterial communities can also contribute to disease severity. We derived diverse gut communities by colonizing germfree mice with different human fecal communities. The mice were then infected with a single C. difficile ribotype 027 clinical isolate, which resulted in moribundity and histopathologic differences. The variation in severity was associated with the human fecal community that the mice received. Generally, bacterial populations with pathogenic potential, such as Enterococcus, Helicobacter, and Klebsiella, were associated with more-severe outcomes. Bacterial groups associated with fiber degradation and bile acid metabolism, such as Anaerotignum, Blautia, Lactonifactor, and Monoglobus, were associated with less-severe outcomes. These data indicate that, in addition to the host and C. difficile subtype, populations of gut bacteria can influence CDI disease severity. IMPORTANCE Clostridioides difficile colonization can be asymptomatic or develop into an infection ranging in severity from mild diarrhea to toxic megacolon, sepsis, and death. Models that predict severity and guide treatment decisions are based on clinical factors and C. difficile characteristics. Although the gut microbiome plays a role in protecting against CDI, its effect on CDI disease severity is unclear and has not been incorporated into disease severity models. We demonstrated that variation in the microbiome of mice colonized with human feces yielded a range of disease outcomes. These results revealed groups of bacteria associated with both severe and mild C. difficile infection outcomes. Gut bacterial community data from patients with CDI could improve our ability to identify patients at risk of developing more severe disease and improve interventions that target C. difficile and the gut bacteria to reduce host damage.

Abstract For more than a century, the prenatal environment was considered sterile. Over the last few years, findings obtained with next-generation sequencing approaches from samples of the placenta, the amniotic fluid, meconium, and even fetal tissues have challenged the dogma of a sterile womb, and additional reports have emerged that used culture, microscopy, and quantitative PCR to support the presence of a low-biomass microbial community at prenatal sites. Given the substantial implications of prenatal exposure to microbes for the development and health of the host, the findings have gathered substantial interest from academics, high impact journals, the public press, and funding agencies. However, an increasing number of studies have challenged the prenatal microbiome identifying contamination as a major issue, and scientists that remained skeptical have pointed to inconsistencies with in utero colonization, the impact of c-sections on early microbiome assembly, and the ability to generate germ-free mammals. A lively academic controversy has emerged on the existence of the wider importance of prenatal microbial communities. Microbiome has asked experts to discuss these issues and provide their thoughts on the implications. To allow for a broader perspective of this discussion, we have specifically selected scientists, who have a long-standing expertise in microbiome sciences but who have not directly been involved in the debate so far.

ABSTRACT The gastrointestinal ecosystem is formed from interactions between the host, indigenous gut microbiota, and external world. When colonizing the gut, bacteria must overcome barriers imposed by the intestinal environment, such as host immune responses and microbiota-mediated nutrient limitation. Thus, understanding bacterial colonization requires determining how the gut landscape interacts with microbes attempting to establish within the ecosystem. However, the complicated network of interactions between elements of the intestinal environment makes it challenging to uncover emergent properties of the system using only reductionist methods. A systems biology approach, which aims to investigate complex systems by examining the behavior and relationships of all elements of the system, may afford a more holistic perspective of the colonization process. Here, we examine the confluence between the gut landscape and bacterial colonization through the lens of systems biology. We offer an overview of the conceptual and methodological underpinnings of systems biology, followed by a discussion of key elements of the gut ecosystem as they pertain to bacterial establishment and growth. We conclude by reintegrating these elements to guide future comprehensive investigations of the ecosystem in the context of bacterial intestinal colonization.

Salmonella entericaS

The incidence of C. difficileC. difficile

Antibiotic-associated colitis is often caused by infection with the bacterium Clostridioides difficileC. difficile

Environmental surveillance is a critical tool for combatting public health threats represented by the global COVID-19 pandemic and the continuous increase of antibiotic resistance in pathogens. With its power to detect entire microbial communities, metagenomics-based methods stand out in addressing the need. However, several hurdles remain to be overcome in order to generate actionable interpretations from metagenomic sequencing data for infection prevention. Conceptually and technically, we focus on viability assessment, taxonomic resolution, and quantitative metagenomics, and discuss their current advancements, necessary precautions and directions to further development. We highlight the importance of building solid conceptual frameworks and identifying rational limits to facilitate the application of techniques. We also propose the usage of internal standards as a promising approach to overcome analytical bottlenecks introduced by low biomass samples and the inherent lack of quantitation in metagenomics. Taken together, we hope this perspective will contribute to bringing accurate and consistent metagenomics-based environmental surveillance to the ground.

ABSTRACT Pluripotent stem-cell-derived human intestinal organoids (HIOs) are three-dimensional, multicellular structures that model a naive intestinal epithelium in an in vitro system. Several published reports have investigated the use of HIOs to study host-microbe interactions. We recently demonstrated that microinjection of the nonpathogenic Escherichia coli strain ECOR2 into HIOs induced morphological and functional maturation of the HIO epithelium, including increased secretion of mucins and cationic antimicrobial peptides. In the current work, we use ECOR2 as a biological probe to further characterize the environment present in the HIO lumen. We generated an isogenic mutant in the general stress response sigma factor RpoS and employed this mutant to compare challenges faced by a bacterium during colonization of the HIO lumen relative to the germ-free mouse intestine. We demonstrate that the loss of RpoS significantly decreases the ability of ECOR2 to colonize HIOs, although it does not prevent colonization of germ-free mice. These results indicate that the HIO lumen is a more restrictive environment to E. coli than the germ-free mouse intestine, thus increasing our understanding of the HIO model system as it pertains to studying the establishment of intestinal host-microbe symbioses. IMPORTANCE Technological advancements have driven and will continue to drive the adoption of organotypic systems for investigating host-microbe interactions within the human intestinal ecosystem. Using E. coli deficient in the RpoS-mediated general stress response, we demonstrate that the type or severity of microbial stressors within the HIO lumen is more restrictive than those of the in vivo environment of the germ-free mouse gut. This study provides important insight into the nature of the HIO microenvironment from a microbiological standpoint.

ABSTRACT Clostridioides difficile infection (CDI) can result in severe disease and death, with no accurate models that allow for early prediction of adverse outcomes. To address this need, we sought to develop serum-based biomarker models to predict CDI outcomes. We prospectively collected sera ≤48 h after diagnosis of CDI in two cohorts. Biomarkers were measured with a custom multiplex bead array assay. Patients were classified using IDSA severity criteria and the development of disease-related complications (DRCs), which were defined as ICU admission, colectomy, and/or death attributed to CDI. Unadjusted and adjusted models were built using logistic and elastic net modeling. The best model for severity included procalcitonin (PCT) and hepatocyte growth factor (HGF) with an area (AUC) under the receiver operating characteristic (ROC) curve of 0.74 (95% confidence interval, 0.67 to 0.81). The best model for 30-day mortality included interleukin-8 (IL-8), PCT, CXCL-5, IP-10, and IL-2Rα with an AUC of 0.89 (0.84 to 0.95). The best model for DRCs included IL-8, procalcitonin, HGF, and IL-2Rα with an AUC of 0.84 (0.73 to 0.94). To validate our models, we employed experimental infection of mice with C. difficile. Antibiotic-treated mice were challenged with C. difficile and a similar panel of serum biomarkers was measured. Applying each model to the mouse cohort of severe and nonsevere CDI revealed AUCs of 0.59 (0.44 to 0.74), 0.96 (0.90 to 1.0), and 0.89 (0.81 to 0.97). In both human and murine CDI, models based on serum biomarkers predicted adverse CDI outcomes. Our results support the use of serum-based biomarker panels to inform Clostridioides difficile infection treatment. IMPORTANCE Each year in the United States, Clostridioides difficile causes nearly 500,000 gastrointestinal infections that range from mild diarrhea to severe colitis and death. The ability to identify patients at increased risk for severe disease or mortality at the time of diagnosis of C. difficile infection (CDI) would allow clinicians to effectively allocate disease modifying therapies. In this study, we developed models consisting of only a small number of serum biomarkers that are capable of predicting both 30-day all-cause mortality and adverse outcomes of patients at time of CDI diagnosis. We were able to validate these models through experimental mouse infection. This provides evidence that the biomarkers reflect the underlying pathophysiology and that our mouse model of CDI reflects the pathogenesis of human infection. Predictive models can not only assist clinicians in identifying patients at risk for severe CDI but also be utilized for targeted enrollment in clinical trials aimed at reduction of adverse outcomes from severe CDI.

ABSTRACT Dietary fiber provides a variety of microbiota-mediated benefits ranging from anti-inflammatory metabolites to pathogen colonization resistance. A healthy gut microbiota protects against Clostridioides difficile colonization. Manipulation of these microbes through diet may increase colonization resistance to improve clinical outcomes. The primary objective of this study was to identify how the dietary fiber xanthan gum affects the microbiota and C. difficile colonization. We added 5% xanthan gum to the diet of C57BL/6 mice and examined its effect on the microbiota through 16S rRNA gene amplicon sequencing and short-chain fatty acid analysis. Following either cefoperazone or an antibiotic cocktail administration, we challenged mice with C. difficile and measured colonization by monitoring the CFU. Xanthan gum administration is associated with increases in fiber-degrading taxa and short-chain fatty acid concentrations. However, by maintaining both the diversity and absolute abundance of the microbiota during antibiotic treatment, the protective effects of xanthan gum administration on the microbiota were more prominent than the enrichment of these fiber-degrading taxa. As a result, mice that were on the xanthan gum diet experienced limited to no C. difficile colonization. Xanthan gum administration alters mouse susceptibility to C. difficile colonization by maintaining the microbiota during antibiotic treatment. While antibiotic-xanthan gum interactions are not well understood, xanthan gum has previously been used to bind drugs and alter their pharmacokinetics. Thus, xanthan gum may alter the activity of the oral antibiotics used to make the microbiota susceptible. Future research should further characterize how this and other common dietary fibers interact with drugs. IMPORTANCE A healthy gut bacterial community benefits the host by breaking down dietary nutrients and protecting against pathogens. Clostridioides difficile capitalizes on the absence of this community to cause diarrhea and inflammation. Thus, a major clinical goal is to find ways to increase resistance to C. difficile colonization by either supplementing with bacteria that promote resistance or a diet to enrich for those already present in the gut. In this study, we describe an interaction between xanthan gum, a human dietary additive, and the microbiota resulting in an altered gut environment that is protective against C. difficile colonization.

Intestinal organoids are 3D cell structures that replicate some aspects of organ function and are organized with a polarized epithelium facing a central lumen. To enable more applications, new technologies are needed to access the luminal cavity and apical cell surface of organoids. We developed a perfusion system utilizing a double-barrel glass capillary with a pressure-based pump to access and modify the luminal contents of a human intestinal organoid for extended periods of time while applying cyclic cellular strain. Cyclic injection and withdrawal of fluorescent FITC-Dextran coupled with real-time measurement of fluorescence intensity showed discrete changes of intensity correlating with perfusion cycles. The perfusion system was also used to modify the lumen of organoids injected with GFP-expressing E. coli. Due to the low concentration and fluorescence of the E. coli, a novel imaging analysis method utilizing bacteria enumeration and image flattening was developed to monitor E. coli within the organoid. Collectively, this work shows that a double-barrel perfusion system provides constant luminal access and allows regulation of luminal contents and luminal mixing.

Abstract Background Sample collection for gut microbiota analysis from in-patients can be challenging. Collection method and storage conditions are potential sources of variability. In this study, we compared the bacterial microbiota from stool stored under different conditions, as well as stool and swab samples, to assess differences due to sample storage conditions and collection method. Methods Using bacterial 16S rRNA gene sequence analysis, we compared the microbiota profiles of stool samples stored and collected under various conditions. Stool samples (2 liquid, 1 formed) from three different patients at two hospitals were each evaluated under the following conditions: immediately frozen at -80°C, stored at 4°C for 12-48 hours before freezing at -80°C and stored at -20°C with 1-2 thaw cycles before storage at -80°C. Additionally, 8 stool and 30 rectal swab samples were collected from 8 in-patients at one hospital. Microbiota differences were assessed using the Yue and Clayton dissimilarity index (θYC distance) and analysis of molecular variance (AMOVA). Results Regardless of the storage conditions, the bacterial communities of aliquots from the same stool samples were very similar based on θYC distances (median intra-sample θYC distance: 0.035, IQR: 0.015-0.061) compared to aliquots from different stool samples (median inter-sample θYC distance: 0.93, IQR: 0.85-0.97) (Wilcoxon test p-value:

ABSTRACT Nursing home residents are at a greater risk of developing pressure injuries that develop into an open wound, which can become colonized with bacteria. Understanding the factors that influence microbial colonization of open wounds can lead to the prevention of infections. The relationship between bacteria found in urine and those in open wounds is currently unknown. To determine if bacterial species colonizing open wounds are also found in the urine, we conducted a pilot study with nursing home residents, comparing bacterial species present in the urine with those present in wounds between the umbilicus and mid-thigh. To identify microbial species that were present in both urine and open wound at one time point in one patient, standard clinical bacteriologic culture techniques followed by matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) were used, as well as 16S rRNA-encoding gene amplicon sequencing. We found some bacterial species detected in urine were also detected in open wounds in one individual at one time point, using both culture-dependent and -independent techniques. Bacterial species that were more often detected, using culture-dependent and -independent methods, at both sites included Enterococcus faecalis, Proteus mirabilis, Escherichia coli, and Providencia stuartii. This pilot study provides evidence that bacterial species identified within the urine can also be identified in open wounds in the same patient at one point in time. Further studies are needed to investigate if these species are of the same lineage and if the urinary microbiota are able to seed colonization of open wounds below the umbilicus. IMPORTANCE Older adults, specifically those in nursing facilities, are more susceptible to developing chronic open nonhealing wounds. Chronic open nonhealing wounds severely impact an individual’s quality of life and can lead to other comorbidities, such as infection. Recent evidence suggests that the open wound bacterial community can influence wound healing and repair. It is important to understand all sources of open wound contamination to improve preventative infection measures and treatment protocols. In this pilot study, we investigated if bacterial species isolated from urine can also be isolated from open wounds located between the levels of the umbilicus and mid-thigh in the same patient at the same point in time. A growing body of evidence suggests that urine can harbor a microbial community, even in asymptomatic individuals, and older adults are more prone to urinary incontinence. This is the first study to investigate bacterial species concordance between these two anatomical sites. We found, using both culture-dependent and -independent methods, that the same bacterial species can colonize both the urine and wound in one patient at one point in time. Further studies are needed to investigate if these species are of the same lineage and if the urinary microbiota are able to seed colonization of these types of open wounds.

ABSTRACT Between October 2016 and June 2017, a C57BL/6J mouse colony that was undergoing a pre- and perinatal methyl donor supplementation diet intervention to study the impact of parental nutrition on offspring susceptibility to disease was found to suffer from an epizootic of unexpected deaths. Necropsy revealed the presence of severe colitis, and further investigation linked these outbreak deaths to a Clostridium difficile strain of ribotype 027 that we term 16N203. C. difficile infection (CDI) is associated with antibiotic use in humans. Current murine models of CDI rely on antibiotic pretreatment to establish clinical phenotypes. In this report, the C. difficile outbreak occurs in F1 mice linked to alterations in the parental diet. The diagnosis of CDI in the affected mice was confirmed by cecal/colonic histopathology, the presence of C. difficile bacteria in fecal/colonic culture, and detection of C. difficile toxins. F1 mice from parents fed the methyl supplementation diet also had significantly reduced survival (P < 0.0001) compared with F1 mice from parents fed the control diet. When we tested the 16N203 outbreak strain in an established mouse model of antibiotic-induced CDI, we confirmed that this strain is pathogenic. Our serendipitous observations from this spontaneous outbreak of C. difficile in association with a pre- and perinatal methyl donor diet suggest the important role that diet may play in host defense and CDI risk factors. IMPORTANCE Clostridium difficile infection (CDI) has become the leading cause of infectious diarrhea in hospitals worldwide, owing its preeminence to the emergence of hyperendemic strains, such as ribotype 027 (RT027). A major CDI risk factor is antibiotic exposure, which alters gut microbiota, resulting in the loss of colonization resistance. Current murine models of CDI also depend on pretreatment of animals with antibiotics to establish disease. The outbreak that we report here is unique in that the CDI occurred in mice with no antibiotic exposure and is associated with a pre- and perinatal methyl supplementation donor diet intervention study. Our investigation subsequently reveals that the outbreak strain that we term 16N203 is an RT027 strain, and this isolated strain is also pathogenic in an established murine model of CDI (with antibiotics). Our report of this spontaneous outbreak offers additional insight into the importance of environmental factors, such as diet, and CDI susceptibility.

ABSTRACT Although the microbiota in the proximal gastrointestinal (GI) tract have been implicated in health and disease, much about these microbes remains understudied compared to those in the distal GI tract. This study characterized the microbiota across multiple proximal GI sites over time in healthy individuals. As part of a study of the pharmacokinetics of oral mesalamine administration, healthy, fasted volunteers (n = 8; 10 observation periods total) were orally intubated with a four-lumen catheter with multiple aspiration ports. Samples were taken from stomach, duodenal, and multiple jejunal sites, sampling hourly (≤7 h) to measure mesalamine (administered at t = 0), pH, and 16S rRNA gene-based composition. We observed a predominance of Firmicutes across proximal GI sites, with significant variation compared to stool. The microbiota was more similar within individuals over time than between subjects, with the fecal microbiota being unique from that of the small intestine. The stomach and duodenal microbiota displayed highest intraindividual variability compared to jejunal sites, which were more stable across time. We observed significant correlations in the duodenal microbial composition with changes in pH; linear mixed models identified positive correlations with multiple Streptococcus operational taxonomic units (OTUs) and negative correlations with multiple Prevotella and Pasteurellaceae OTUs. Few OTUs correlated with mesalamine concentration. The stomach and duodenal microbiota exhibited greater compositional dynamics than the jejunum. Short-term fluctuations in the duodenal microbiota were correlated with pH. Given the unique characteristics and dynamics of the proximal GI tract microbiota, it is important to consider these local environments in health and disease states. IMPORTANCE The gut microbiota are linked to a variety of gastrointestinal diseases, including inflammatory bowel disease. Despite this importance, microbiota dynamics in the upper gastrointestinal tract are understudied. Our article seeks to understand what factors impact microbiota dynamics in the healthy human upper gut. We found that the upper gastrointestinal tract contains consistently prevalent bacterial OTUs that dominate the overall community. Microbiota variability is highest in the stomach and duodenum and correlates with pH.

ABSTRACT Clostridium (Clostridioides) difficile, a Gram-positive, anaerobic bacterium, is the leading single cause of nosocomial infections in the United States. A major risk factor for Clostridium difficile infection (CDI) is prior exposure to antibiotics, as they increase susceptibility to CDI by altering the membership of the microbial community enabling colonization. The importance of the gut microbiota in providing protection from CDI is underscored by the reported 80 to 90% success rate of fecal microbial transplants in treating recurrent infections. Adaptive immunity, specifically humoral immunity, is also sufficient to protect from both acute and recurrent CDI. However, the role of the adaptive immune system in mediating clearance of C. difficile has yet to be resolved. Using murine models of CDI, we found that adaptive immunity is dispensable for clearance of C. difficile. However, random forest analysis using only two members of the resident bacterial community correctly identified animals that would go on to clear the infection with 66.7% accuracy. These findings indicate that the indigenous gut microbiota independent of adaptive immunity facilitates clearance of C. difficile from the murine gastrointestinal tract. IMPORTANCE Clostridium difficile infection is a major cause of morbidity and mortality in hospitalized patients in the United States. Currently, the role of the adaptive immune response in modulating levels of C. difficile colonization is unresolved. This work suggests that the indigenous gut microbiota is a main factor that promotes clearance of C. difficile from the GI tract. Our results show that clearance of C. difficile can occur without contributions from the adaptive immune response. This study also has implications for the design of preclinical studies testing the efficacy of vaccines on clearance of bacterial pathogens, as inherent differences in the baseline community structure of animals may bias findings.

ABSTRACT IMPACT: Use of this novel murine model of inflammatory bowel disease (IBD) and C. difficile infection (CDI) will aid in developing new clinical approaches to predict, diagnose, and treat CDI in the IBD population. OBJECTIVES/GOALS: IBD is associated with intestinal inflammation and alterations of the gut microbiota, both of which can diminish colonization resistance to C. difficile. Here, we sought to determine if IBD is sufficient to render mice susceptible to C. difficile colonization and infection in the absence of other perturbations, such as antibiotic treatment. METHODS/STUDY POPULATION: C57BL/6 IL-10-/- mice were colonized with Helicobacter hepaticus to trigger colonic inflammation akin to human IBD. Control mice, not colonized with H. hepaticus, were pretreated with the antibiotic cefoperazone to render the gut microbiota susceptible to CDI. Mice were then gavaged with spores of the toxigenic C. difficile strain VPI 10463 and monitored for C. difficile colonization and disease. The fecal microbiota at the time of C. difficile exposure was profiled by 16S rRNA gene sequencing and analyzed using mothur. Statistical analyses were performed using R. RESULTS/ANTICIPATED RESULTS: Mice with IBD harbored significantly distinct intestinal microbial communities compared to non-IBD controls at the time of C. difficile spore exposure (14 days post-IBD trigger). Mice with IBD were susceptible to persistent C. difficile colonization, while genetically identical non-IBD controls were resistant to C. difficile colonization. Concomitant IBD and CDI was associated with significantly worse clinical and intestinal disease than unaccompanied IBD. DISCUSSION/SIGNIFICANCE OF FINDINGS: Patients with IBD who develop concurrent CDI experience increased morbidity and mortality. These studies in a novel mouse model of IBD and CDI emphasize the dual importance of host responses and alterations of the gut microbiota in susceptibility to C. difficile colonization and infection in the setting of IBD.

ABSTRACT IMPACT: Our goal is to identify bacterial biomarkers of adverse Clostridioides difficile infection outcomes OBJECTIVES/GOALS: We characterized microbiota features of Clostridioides difficile infections (CDIs) and will investigate the association between bacterial taxa and adverse outcomes, which includes severe and recurrent CDIs. METHODS/STUDY POPULATION: 1,517 stool samples were collected from patients diagnosed with a CDI at the University of Michigan along with 1,516 unformed and 910 formed stool control samples. We characterized the microbiota of the 3,943 stool samples by sequencing the V4 region of the 16S rRNA gene and used the Dirichlet Multinomial Mixtures method to cluster samples into community types. Severe CDI cases were defined using the Infectious Diseases Society of America criteria and recurrent CDIs were defined as CDIs that occurred within 2-12 weeks of the primary CDI. We will use machine learning to examine whether specific bacterial taxa can predict severe or recurrent CDIs. We will test 5 machine learning models with 80% training and 20% testing data split. RESULTS/ANTICIPATED RESULTS: Similar to findings from a previous study with 338 samples, we found there was no difference in diversity between CDI cases and unformed controls (Inverse Simpson index, p > 0.5) and samples from the 3 groups (CDIs, unformed controls, and formed controls) clustered into 12 community types. To investigate the bacterial taxa that are important for predicting adverse CDI outcomes, we will select the best machine learning model based on performance and training time and examine how much each feature contributes to performance. We anticipate the large number of CDI cases in our cohort and robust machine learning approaches will enable us to identify more bacteria associated with adverse outcomes compared to other studies that have attempted to predict CDI recurrence with fewer CDI cases. DISCUSSION/SIGNIFICANCE OF FINDINGS: Adverse CDI outcomes are a significant source of the morbidities, mortalities, and healthcare costs associated with CDIs. Identifying bacterial biomarkers of severe and recurrent CDIs could enhance our ability to stratify patients into risk groups and may lead to the development of more targeted therapeutics.

Background & Aims: Gut dysbiosis is closely involved in the pathogenesis of inflammatory bowel disease (IBD). However, it remains unclear whether IBD-associated gut dysbiosis contributes to disease pathogenesis or is merely secondary to intestinal inflammation. We established a humanized gnotobiotic (hGB) mouse system to assess the functional role of gut dysbiosis associated with 2 types of IBD: Crohn's disease (CD) and ulcerative colitis (UC). Methods: Germ-free mice were colonized by the gut microbiota isolated from patients with CD and UC, and healthy controls. Microbiome analysis, bacterial functional gene analysis, luminal metabolome analysis, and host gene expression analysis were performed in hGB mice. Moreover, the colitogenic capacity of IBD-associated microbiota was evaluated by colonizing germ-free colitis-prone interleukin 10âdeficient mice with dysbiotic patients' microbiota. Results: Although the microbial composition seen in donor patients' microbiota was not completely reproduced in hGB mice, some dysbiotic features of the CD and UC microbiota (eg, decreased diversity, alteration of bacterial metabolic functions) were recapitulated in hGB mice, suggesting that microbial community alterations, characteristic for IBD, can be reproduced in hGB mice. In addition, colonization by the IBD-associated microbiota induced a proinflammatory gene expression profile in the gut that resembles the immunologic signatures found in CD patients. Furthermore, CD microbiota triggered more severe colitis than healthy control microbiota when colonized in germ-free interleukin 10âdeficient mice. Conclusions: Dysbiosis potentially contributes to the pathogenesis of IBD by augmenting host proinflammatory immune responses. Transcript profiling: GSE73882. Keywords: Dysbiosis, Microbiota, Crohn's Disease, Ulcerative Colitis

ABSTRACT Susceptibility to Clostridium difficile infection (CDI) is primarily associated with previous exposure to antibiotics, which compromise the structure and function of the gut bacterial community. Specific antibiotic classes correlate more strongly with recurrent or persistent C. difficile infection. As such, we utilized a mouse model of infection to explore the effect of distinct antibiotic classes on the impact that infection has on community-level transcription and metabolic signatures shortly following pathogen colonization and how those changes may associate with persistence of C. difficile. Untargeted metabolomic analysis revealed that C. difficile infection had significantly larger impacts on the metabolic environment across cefoperazone- and streptomycin-pretreated mice, which became persistently colonized compared to clindamycin-pretreated mice, where infection quickly became undetectable. Through metagenome-enabled metatranscriptomics, we observed that transcripts for genes associated with carbon and energy acquisition were greatly reduced in infected animals, suggesting that those niches were instead occupied by C. difficile. Furthermore, the largest changes in transcription were seen in the least abundant species, indicating that C. difficile may “attack the loser” in gut environments where sustained infection occurs more readily. Overall, our results suggest that C. difficile is able to restructure the nutrient-niche landscape in the gut to promote persistent infection. IMPORTANCE Clostridium difficile has become the most common single cause of hospital-acquired infection over the last decade in the United States. Colonization resistance to the nosocomial pathogen is primarily provided by the gut microbiota, which is also involved in clearing the infection as the community recovers from perturbation. As distinct antibiotics are associated with different risk levels for CDI, we utilized a mouse model of infection with 3 separate antibiotic pretreatment regimens to generate alternative gut microbiomes that each allowed for C. difficile colonization but varied in clearance rate. To assess community-level dynamics, we implemented an integrative multi-omics approach that revealed that infection significantly changed many aspects of the gut community. The degree to which the community changed was inversely correlated with clearance during the first 6 days of infection, suggesting that C. difficile differentially modifies the gut environment to promote persistence. This is the first time that metagenome-enabled metatranscriptomics have been employed to study the behavior of a host-associated microbiota in response to an infection. Our results allow for a previously unseen understanding of the ecology associated with C. difficile infection and provide the groundwork for identification of context-specific probiotic therapies.

ABSTRACT Recurrent Clostridium difficile infection (rCDI) frequently complicates recovery from CDI. Accurately predicting rCDI would allow judicious allocation of limited resources, but published models have met with limited success. Thus, biomarkers predictive of recurrence have been sought. This study tested whether PCR ribotype independently predicted rCDI. Stool samples from nonpregnant inpatients ≥18 years of age with diarrhea were included from October 2010 to January 2013 after the patients tested positive for C. difficile in the clinical microbiology laboratory. Per guidelines, the rCDI was defined as a positive test for C. difficile at >2 weeks but ≤8 weeks from the index episode. For each sample, a single colony of C. difficile was isolated by anaerobic culture, confirmed to be toxigenic by PCR, and ribotyped. Simple logistic regression and multiple logistic regression were used to model the primary outcome of rCDI, incorporating a wide range of clinical parameters. In total, 927 patients with 968 index episodes of CDI were included, with 110 (11.4%) developing rCDI. Age and use of proton pump inhibitors or concurrent antibiotics did not increase the risk of rCDI. Low serum bilirubin levels and ribotype 027 were associated with increased risk of rCDI on unadjusted analysis, with health care-associated CDI being inversely associated. In the final multivariable model, ribotype 027 was the strongest independent predictor of rCDI (odds ratio, 2.17; 95% confidence interval, 1.33 to 3.56; P = 0.002). Ribotype 027 is an independent predictor of rCDI. IMPORTANCE CDI is a major public health issue, with over 400,000 cases per year in the United States alone. Recurrent CDI is common, occurring in approximately one in five individuals after a primary episode. Although interventions exist that could reduce the risk of recurrence, deployment in all patients is limited by cost, invasiveness, and/or an undetermined long-term safety profile. Thus, clinicians need risk stratification tools to properly allocate treatments. Because prior research on clinical predictors has failed to yield a reliable, reproducible, and effective predictive model to assist treatment decisions, accurate biomarkers of recurrence would be of great value. This study tested whether PCR ribotype independently predicted rCDI, and the data build upon prior research in showing that ribotype 027 is associated with rCDI.

ABSTRACT Clostridium difficile is the largest single cause of hospital-acquired infection in the United States. A major risk factor for Clostridium difficile infection (CDI) is prior exposure to antibiotics, as they disrupt the gut bacterial community which protects from C. difficile colonization. Multiple antibiotic classes have been associated with CDI susceptibility, many leading to distinct community structures stemming from variation in bacterial targets of action. These community structures present separate metabolic challenges to C. difficile. Therefore, we hypothesized that the pathogen adapts its physiology to the nutrients within different gut environments. Utilizing an in vivo CDI model, we demonstrated that C. difficile highly colonized ceca of mice pretreated with any of three antibiotics from distinct classes. Levels of C. difficile spore formation and toxin activity varied between animals based on the antibiotic pretreatment. These physiologic processes in C. difficile are partially regulated by environmental nutrient concentrations. To investigate metabolic responses of the bacterium in vivo, we performed transcriptomic analysis of C. difficile from ceca of infected mice across pretreatments. This revealed heterogeneous expression in numerous catabolic pathways for diverse growth substrates. To assess which resources C. difficile exploited, we developed a genome-scale metabolic model with a transcriptome-enabled metabolite scoring algorithm integrating network architecture. This platform identified nutrients that C. difficile used preferentially between pretreatments, which were validated through untargeted mass spectrometry of each microbiome. Our results supported the hypothesis that C. difficile inhabits alternative nutrient niches across cecal microbiomes with increased preference for nitrogen-containing carbon sources, particularly Stickland fermentation substrates and host-derived glycans. IMPORTANCE Infection by the bacterium Clostridium difficile causes an inflammatory diarrheal disease which can become life threatening and has grown to be the most prevalent nosocomial infection. Susceptibility to C. difficile infection is strongly associated with previous antibiotic treatment, which disrupts the gut microbiota and reduces its ability to prevent colonization. In this study, we demonstrated that C. difficile altered pathogenesis between hosts pretreated with antibiotics from separate classes and exploited different nutrient sources across these environments. Our metabolite score calculation also provides a platform to study nutrient requirements of pathogens during an infection. Our results suggest that C. difficile colonization resistance is mediated by multiple groups of bacteria competing for several subsets of nutrients and could explain why total reintroduction of competitors through fecal microbial transplant currently is the most effective treatment for recurrent CDI. This work could ultimately contribute to the identification of targeted, context-dependent measures that prevent or reduce C. difficile colonization, including pre- and probiotic therapies.

OBJECTIVES/SPECIFIC AIMS: The central goal of this proposal is to characterize the mechanisms that mediate success or failure of immature intestinal barrier in necrotizing enterocilitis. METHODS/STUDY POPULATION: To do this, I will utilize stem cell derived human intestinal organoids (HIOs), an innovative model of the immature intestine, and a cohort of bacterial isolates collected from premature infants who developed NEC to interrogate the cause-effect relationship of these strains on maintenance of the intestinal barrier. I hypothesize that the epithelial response to bacterial colonization is strain-dependent and results in differences in inflammatory signaling that shape epithelial barrier function in the immature intestine. RESULTS/ANTICIPATED RESULTS: Preliminary data shows that colonization of HIOs with different bacteria leads to species-specific changes in barrier function, and some species selectively damage the epithelial barrier while others enhance epithelial barrier function. I have identified key inflammatory signals that serve as central drivers of intestinal barrier function. DISCUSSION/SIGNIFICANCE OF IMPACT: Characterization of this process is expected to substantially advance scientific understanding of early events in NEC pathogenesis and lead to new opportunities for targeted therapeutic intervention to accelerate barrier maturation or prevent hyperinflammatory reactivity in the neonatal intestine. The research proposed in this application represents an entirely novel approach to studying host-microbial interactions in the immature. Conceptually, this novel translational approach will help to define the pivotal role of colonizing bacteria in initiating epithelial inflammation in NEC patients.

ABSTRACT It is hypothesized that the depletion of microbial members responsible for converting primary bile acids into secondary bile acids reduces resistance to Clostridium difficile colonization. To date, inhibition of C. difficile growth by secondary bile acids has only been shown in vitro. Using targeted bile acid metabolomics, we sought to define the physiologically relevant concentrations of primary and secondary bile acids present in the murine small and large intestinal tracts and how these impact C. difficile dynamics. We treated mice with a variety of antibiotics to create distinct microbial and metabolic (bile acid) environments and directly tested their ability to support or inhibit C. difficile spore germination and outgrowth ex vivo. Susceptibility to C. difficile in the large intestine was observed only after specific broad-spectrum antibiotic treatment (cefoperazone, clindamycin, and vancomycin) and was accompanied by a significant loss of secondary bile acids (deoxycholate, lithocholate, ursodeoxycholate, hyodeoxycholate, and ω-muricholate). These changes were correlated to the loss of specific microbiota community members, the Lachnospiraceae and Ruminococcaceae families. Additionally, physiological concentrations of secondary bile acids present during C. difficile resistance were able to inhibit spore germination and outgrowth in vitro. Interestingly, we observed that C. difficile spore germination and outgrowth were supported constantly in murine small intestinal content regardless of antibiotic perturbation, suggesting that targeting growth of C. difficile will prove most important for future therapeutics and that antibiotic-related changes are organ specific. Understanding how the gut microbiota regulates bile acids throughout the intestine will aid the development of future therapies for C. difficile infection and other metabolically relevant disorders such as obesity and diabetes. IMPORTANCE Antibiotics alter the gastrointestinal microbiota, allowing for Clostridium difficile infection, which is a significant public health problem. Changes in the structure of the gut microbiota alter the metabolome, specifically the production of secondary bile acids. Specific bile acids are able to initiate C. difficile spore germination and also inhibit C. difficile growth in vitro, although no study to date has defined physiologically relevant bile acids in the gastrointestinal tract. In this study, we define the bile acids C. difficile spores encounter in the small and large intestines before and after various antibiotic treatments. Antibiotics that alter the gut microbiota and deplete secondary bile acid production allow C. difficile colonization, representing a mechanism of colonization resistance. Multiple secondary bile acids in the large intestine were able to inhibit C. difficile spore germination and growth at physiological concentrations and represent new targets to combat C. difficile in the large intestine.

ABSTRACT Multiple molecular assays now enable high-throughput profiling of the ecology, metabolic capacity, and activity of the human microbiome. However, to date, analyses of such multi-omic data typically focus on statistical associations, often ignoring extensive prior knowledge of the mechanisms linking these various facets of the microbiome. Here, we introduce a comprehensive framework to systematically link variation in metabolomic data with community composition by utilizing taxonomic, genomic, and metabolic information. Specifically, we integrate available and inferred genomic data, metabolic network modeling, and a method for predicting community-wide metabolite turnover to estimate the biosynthetic and degradation potential of a given community. Our framework then compares variation in predicted metabolic potential with variation in measured metabolites’ abundances to evaluate whether community composition can explain observed shifts in the community metabolome, and to identify key taxa and genes contributing to the shifts. Focusing on two independent vaginal microbiome data sets, each pairing 16S community profiling with large-scale metabolomics, we demonstrate that our framework successfully recapitulates observed variation in 37% of metabolites. Well-predicted metabolite variation tends to result from disease-associated metabolism. We further identify several disease-enriched species that contribute significantly to these predictions. Interestingly, our analysis also detects metabolites for which the predicted variation negatively correlates with the measured variation, suggesting environmental control points of community metabolism. Applying this framework to gut microbiome data sets reveals similar trends, including prediction of bile acid metabolite shifts. This framework is an important first step toward a system-level multi-omic integration and an improved mechanistic understanding of the microbiome activity and dynamics in health and disease. IMPORTANCE Studies characterizing both the taxonomic composition and metabolic profile of various microbial communities are becoming increasingly common, yet new computational methods are needed to integrate and interpret these data in terms of known biological mechanisms. Here, we introduce an analytical framework to link species composition and metabolite measurements, using a simple model to predict the effects of community ecology on metabolite concentrations and evaluating whether these predictions agree with measured metabolomic profiles. We find that a surprisingly large proportion of metabolite variation in the vaginal microbiome can be predicted based on species composition (including dramatic shifts associated with disease), identify putative mechanisms underlying these predictions, and evaluate the roles of individual bacterial species and genes. Analysis of gut microbiome data using this framework recovers similar community metabolic trends. This framework lays the foundation for model-based multi-omic integrative studies, ultimately improving our understanding of microbial community metabolism.

Clostridium difficile infection (CDI) is a significant source of healthcare-associated morbidity and mortality. This study investigated whether serum 25-hydroxyvitamin D is associated with adverse outcomes from CDI. Patients with CDI were prospectively enrolled. Charts were reviewed and serum 25-hydroxyvitamin D was measured. The primary outcome was a composite definition of severe disease: fever (temperature >38°C), acute organ dysfunction, or serum white blood cell count >15,000 cells/μL within 24-48 hours of diagnosis; lack of response to therapy by day 5; and intensive care unit admission; colectomy; or death within 30 days. Sixty-seven patients were included in the final analysis. Mean (±SD) serum 25- hydroxyvitamin D was 26.1 (±18.54) ng/mL. Severe disease, which occurred in 26 (39%) participants, was not associated with serum 25-hydroxyvitamin D [odds ratio (OR) 1.00; 95% confidence interval (CI) 0.96-1.04]. In the adjusted model for severe disease only serum albumin (OR 0.12; 95%CI 0.02-0.64) and diagnosis by detection of stool toxin (OR 5.87; 95%CI 1.09-31.7) remained independent predictors. We conclude that serum 25-hydroxyvitamin D is not associated with the development of severe disease in patients with CDI.

ABSTRACT No studies have examined the relationships between bacterial communities along sites of the upper aerodigestive tract of an individual subject. Our objective was to perform an intrasubject and intersite analysis to determine the contributions of two upper mucosal sites (mouth and nose) as source communities for the bacterial microbiome of lower sites (lungs and stomach). Oral wash, bronchoalveolar lavage (BAL) fluid, nasal swab, and gastric aspirate samples were collected from 28 healthy subjects. Extensive analysis of controls and serial intrasubject BAL fluid samples demonstrated that sampling of the lungs by bronchoscopy was not confounded by oral microbiome contamination. By quantitative PCR, the oral cavity and stomach contained the highest bacterial signal levels and the nasal cavity and lungs contained much lower levels. Pyrosequencing of 16S rRNA gene amplicon libraries generated from these samples showed that the oral and gastric compartments had the greatest species richness, which was significantly greater in both than the richness measured in the lungs and nasal cavity. The bacterial communities of the lungs were significantly different from those of the mouth, nose, and stomach, while the greatest similarity was between the oral and gastric communities. However, the bacterial communities of healthy lungs shared significant membership with the mouth, but not the nose, and marked subject-subject variation was noted. In summary, microbial immigration from the oral cavity appears to be the significant source of the lung microbiome during health, but unlike the stomach, the lungs exhibit evidence of selective elimination of Prevotella bacteria derived from the upper airways. IMPORTANCE We have demonstrated that the bacterial communities of the healthy lung overlapped those found in the mouth but were found at lower concentrations, with lower membership and a different community composition. The nasal microbiome, which was distinct from the oral microbiome, appeared to contribute little to the composition of the lung microbiome in healthy subjects. Our studies of the nasal, oral, lung, and stomach microbiomes within an individual illustrate the microbiological continuity of the aerodigestive tract in healthy adults and provide culture-independent microbiological support for the concept that microaspiration is common in healthy individuals.

ABSTRACT DNA from phylogenetically diverse microbes is routinely recovered from healthy human lungs and used to define the lung microbiome. The proportion of this DNA originating from microbes adapted to the lungs, as opposed to microbes dispersing to the lungs from other body sites and the atmosphere, is not known. We use a neutral model of community ecology to distinguish members of the lung microbiome whose presence is consistent with dispersal from other body sites and those that deviate from the model, suggesting a competitive advantage to these microbes in the lungs. We find that the composition of the healthy lung microbiome is consistent with predictions of the neutral model, reflecting the overriding role of dispersal of microbes from the oral cavity in shaping the microbial community in healthy lungs. In contrast, the microbiome of diseased lungs was readily distinguished as being under active selection. We also assessed the viability of microbes from lung samples by cultivation with a variety of media and incubation conditions. Bacteria recovered by cultivation from healthy lungs represented species that comprised 61% of the 16S rRNA-encoding gene sequences derived from bronchoalveolar lavage samples. IMPORTANCE Neutral distribution of microbes is a distinguishing feature of the microbiome in healthy lungs, wherein constant dispersal of bacteria from the oral cavity overrides differential growth of bacteria. No bacterial species consistently deviated from the model predictions in healthy lungs, although representatives of many of the dispersed species were readily cultivated. In contrast, bacterial populations in diseased lungs were identified as being under active selection. Quantification of the relative importance of selection and neutral processes such as dispersal in shaping the healthy lung microbiome is a first step toward understanding its impacts on host health.

ABSTRACT Antibiotic usage is the most commonly cited risk factor for hospital-acquired Clostridium difficile infections (CDI). The increased risk is due to disruption of the indigenous microbiome and a subsequent decrease in colonization resistance by the perturbed bacterial community; however, the specific changes in the microbiome that lead to increased risk are poorly understood. We developed statistical models that incorporated microbiome data with clinical and demographic data to better understand why individuals develop CDI. The 16S rRNA genes were sequenced from the feces of 338 individuals, including cases, diarrheal controls, and nondiarrheal controls. We modeled CDI and diarrheal status using multiple clinical variables, including age, antibiotic use, antacid use, and other known risk factors using logit regression. This base model was compared to models that incorporated microbiome data, using diversity metrics, community types, or specific bacterial populations, to identify characteristics of the microbiome associated with CDI susceptibility or resistance. The addition of microbiome data significantly improved our ability to distinguish CDI status when comparing cases or diarrheal controls to nondiarrheal controls. However, only when we assigned samples to community types was it possible to differentiate cases from diarrheal controls. Several bacterial species within the Ruminococcaceae, Lachnospiraceae, Bacteroides, and Porphyromonadaceae were largely absent in cases and highly associated with nondiarrheal controls. The improved discriminatory ability of our microbiome-based models confirms the theory that factors affecting the microbiome influence CDI. IMPORTANCE The gut microbiome, composed of the trillions of bacteria residing in the gastrointestinal tract, is responsible for a number of critical functions within the host. These include digestion, immune system stimulation, and colonization resistance. The microbiome’s role in colonization resistance, which is the ability to prevent and limit pathogen colonization and growth, is key for protection against Clostridium difficile infections. However, the bacteria that are important for colonization resistance have not yet been elucidated. Using statistical modeling techniques and different representations of the microbiome, we demonstrated that several community types and the loss of several bacterial populations, including Bacteroides, Lachnospiraceae, and Ruminococcaceae, are associated with CDI. Our results emphasize the importance of considering the microbiome in mediating colonization resistance and may also direct the design of future multispecies probiotic therapies.

ABSTRACT Clostridium difficile infection is one of the most common health care-associated infections, and up to 40% of patients suffer from recurrence of disease following standard antibiotic therapy. Recently, fecal microbiota transplantation (FMT) has been successfully used to treat recurrent C. difficile infection. It is hypothesized that FMT aids in recovery of a microbiota capable of colonization resistance to C. difficile. However, it is not fully understood how this occurs. Here we investigated changes in the fecal microbiota structure following FMT in patients with recurrent C. difficile infection, and imputed a hypothetical functional profile based on the 16S rRNA profile using a predictive metagenomic tool. Increased relative abundance of Bacteroidetes and decreased abundance of Proteobacteria were observed following FMT. The fecal microbiota of recipients following transplantation was more diverse and more similar to the donor profile than the microbiota prior to transplantation. Additionally, we observed differences in the imputed metagenomic profile. In particular, amino acid transport systems were overrepresented in samples collected prior to transplantation. These results suggest that functional changes accompany microbial structural changes following this therapy. Further identification of the specific community members and functions that promote colonization resistance may aid in the development of improved treatment methods for C. difficile infection. IMPORTANCE Within the last decade, Clostridium difficile infection has surpassed other bacterial infections to become the leading cause of nosocomial infections. Antibiotic use, which disrupts the gut microbiota and its capability in providing colonization resistance against C. difficile, is a known risk factor in C. difficile infection. In particular, recurrent C. difficile remains difficult to treat with standard antibiotic therapy. Fecal microbiota transplantation (FMT) has provided a successful treatment method for some patients with recurrent C. difficile infection, but its mechanism and long-term effects remain unknown. Our results provide insight into the structural and potential metabolic changes that occur following FMT, which may aid in the development of new treatment methods for C. difficile infection.

The prevalence of carbapenemase-producing Enterobacteriaceae (CPE) in our hospital increased beginning in 2009. We aimed to study the clinical and molecular epidemiology of these emerging isolates. We performed a retrospective review of all adult patients with clinical cultures confirmed as CPE by positive modified Hodge test from 5/2009-5/2010 at the University of Michigan Health System (UMHS). Clinical information was obtained from electronic medical records. Available CPE isolates were analyzed by polymerase chain reaction (PCR) and sequencing of the 16S rRNA encoding gene and blaKPC locus. Multilocus sequence typing (MLST) was used to characterize Klebsiella pneumoniae isolates. Twenty six unique CPE isolates were obtained from 25 adult patients. The majority were Klebsiella pneumoniae (n=17). Other isolates included K. oxytoca (n=3), Citrobacter freundii (n=2), Enterobacter cloacae (n=2), Enterobacter aerogenes (n=1) and Escherichia coli (n=1). Molecular characterization of 19 available CPE isolates showed that 13 (68%) carried the KPC-3 allele and 6 (32%) carried the KPC-2 allele. Among 14 available K. pneumoniae strains, 12 (86%) carried the KPC-3 allele and belonged to a common lineage, sequence type (ST) 258. The other 2 (14%) K. pneumoniae isolates carried the KPC-2 allele and belonged to two unique STs. Among these ST 258 strains, 67% were isolated from patients with prior exposures to health care settings outside of our institution. In contrast, all CPE isolates carrying the KPC-2 allele and all non ST 258 CPE isolates had acquisition attributable to our hospital. Molecular epidemiology of carbapenemase producing K. pneumoniae suggests that KPC-3 producing K. pneumoniae isolates of a common lineage, sequence type (ST 258), are emerging in our hospital. While ST 258 is a dominant sequence type throughout the United States, this study is the first to report its presence in Michigan.

Antibiotics are the main, and often only, clinical intervention for prophylactic and active treatment of bacterial infections in humans. Perhaps it is not surprising that these drugs also shift the composition of commensal bacteria inside our bodies, especially those within the gut microbial community (microbiota). How these dynamics ultimately affect the function of the gut microbiota, however, is not fully appreciated. Likewise, how antibiotic induced changes facilitate the outgrowth and pathogenicity of certain bacterial strains remains largely enigmatic. Here, we discuss the merits of a microbial ecology approach toward understanding a common side effect of antibiotic use, antibiotic-associated diarrhea (AAD), and the opportunistic bacterial infections that sometimes underlie it. As an example, we discuss how this approach is being used to address complex disease dynamics during Clostridium difficile infection.