Renee L. Greer

Uncovering effects of antibiotics on the host and microbiota using transkingdom gene networks

Objective Despite widespread use of antibiotics for the treatment of life-threatening infections and for research on the role of commensal microbiota, our understanding of their effects on the host is still very limited. Design Using a popular mouse model of microbiota depletion by a cocktail of antibiotics, we analysed the effects of antibiotics by combining intestinal transcriptome together with metagenomic analysis of the gut microbiota. In order to identify specific microbes and microbial genes that influence the host phenotype in antibiotic-treated mice, we developed and applied analysis of the transkingdom network. Results We found that most antibiotic-induced alterations in the gut can be explained by three factors: depletion of the microbiota; direct effects of antibiotics on host tissues and the effects of remaining antibiotic-resistant microbes. Normal microbiota depletion mostly led to downregulation of different aspects of immunity. The two other factors (antibiotic direct effects on host tissues and antibiotic-resistant microbes) primarily inhibited mitochondrial gene expression and amounts of active mitochondria, increasing epithelial cell death. By reconstructing and analysing the transkingdom network, we discovered that these toxic effects were mediated by virulence/quorum sensing in antibiotic-resistant bacteria, a finding further validated using in vitro experiments. Conclusions In addition to revealing mechanisms of antibiotic-induced alterations, this study also describes a new bioinformatics approach that predicts microbial components that regulate host functions and establishes a comprehensive resource on what, why and how antibiotics affect the gut in a widely used mouse model of microbiota depletion by antibiotics.

Akkermansia muciniphila mediates negative effects of IFNγ on glucose metabolism

Cross-talk between the gut microbiota and the host immune system regulates host metabolism, and its dysregulation can cause metabolic disease. Here, we show that the gut microbe Akkermansia muciniphila can mediate negative effects of IFNγ on glucose tolerance. In IFNγ-deficient mice, A. muciniphila is significantly increased and restoration of IFNγ levels reduces A. muciniphila abundance. We further show that IFNγ-knockout mice whose microbiota does not contain A. muciniphila do not show improvement in glucose tolerance and adding back A. muciniphila promoted enhanced glucose tolerance. We go on to identify Irgm1 as an IFNγ-regulated gene in the mouse ileum that controls gut A. muciniphila levels. A. muciniphila is also linked to IFNγ-regulated gene expression in the intestine and glucose parameters in humans, suggesting that this trialogue between IFNγ, A. muciniphila and glucose tolerance might be an evolutionally conserved mechanism regulating metabolic health in mice and humans.

Bridging immunity and lipid metabolism by gut microbiota

The human gut is a unique organ in which hundreds of different microbial species find their habitat and in which different host physiologic functions, such as digestion, nutrition, and immunity, coexist. Although all these players were studied separately for decades, recently, there has been an explosion of studies demonstrating the essential role for interactions between these components in gut function. Furthermore, new systems biology methods provide essential tools to study this complex system as a whole and to identify key elements that define the crosstalk between the gut microbiota, immunity, and metabolism. This review is devoted to several human diseases resulting from the disruption in this crosstalk, including immunodeficiency-associated and environmental enteropathies, celiac disease, inflammatory bowel disease, and obesity. We describe findings in experimental models of these diseases and in germ-free animals that help us understand the mechanisms and test new therapeutic strategies. We also discuss current challenges that the field is facing and propose that a new generation of antibiotics, prebiotics, and probiotics coupled with novel, systems biology-driven diagnostics will provide the basis for future personalized therapy.

Numb Regulates Acinar Cell Dedifferentiation and Survival During Pancreatic Damage and Acinar-to-Ductal Metaplasia

BACKGROUND & AIMS Pancreatic ductal adenocarcinoma (PDA) is a leading cause of cancer-related death. Through the process of acinar-to-ductal metaplasia (ADM), pancreatic acinar cells give rise to pancreatic intraepithelial neoplasia (PanIN), the most common precursor of PDA. However, even when Kras is activated in a majority of acinar cells, ADM and subsequent development of PanINs is inefficient in the absence of additional stresses. Numb regulates cell junctions, integrins, and the activity of embryonic signaling pathways; therefore, we investigated its effects on acinar cell dedifferentiation, regeneration, and metaplasia. METHODS We used mouse models of pancreatic regeneration and PDA as well as mice with loss-of-function alleles of Numb (p48Cre/p48Cre(ER);Numb(f/f) and p48Cre/p48Cre(ER);Kras(G12D);Numb(f/f) mice) to study the roles of Numb in pancreatic regeneration and ADM. RESULTS Loss of Numb resulted in premature dedifferentiation of acinar cells in response to injury due to administration of the cholecystokinin analogue cerulein and interfered with acinar cell regeneration. Numb was found to regulate multiple signaling pathways in acinar cells during cerulein-induced pancreatitis. Disruption of Numb accelerated and destabilized ADM in the context of oncogenic Kras (in p48Cre;Kras(G12D);Numb(f/f) and p48Cre(ER);Kras(G12D);Numb(f/f) mice). CONCLUSIONS Numb is an important regulator of acinar cell differentiation and viability during metaplasia. In mice with pancreatitis or pancreatic injury, elimination of Numb causes dedifferentiated acinar cells to undergo apoptosis, and this is not mitigated by oncogenic Kras.

Dicer Regulates Differentiation and Viability during Mouse Pancreatic Cancer Initiation

miRNA levels are altered in pancreatic ductal adenocarcinoma (PDA), the most common and lethal pancreatic malignancy, and intact miRNA processing is essential for lineage specification during pancreatic development. However, the role of miRNA processing in PDA has not been explored. Here we study the role of miRNA biogenesis in PDA development by deleting the miRNA processing enzyme Dicer in a PDA mouse model driven by oncogenic Kras. We find that loss of Dicer accelerates Kras driven acinar dedifferentiation and acinar to ductal metaplasia (ADM), a process that has been shown to precede and promote the specification of PDA precursors. However, unconstrained ADM also displays high levels of apoptosis. Dicer loss does not accelerate development of Kras driven PDA precursors or PDA, but surprisingly, we observe that mouse PDA can develop without Dicer, although at the expense of proliferative capacity. Our data suggest that intact miRNA processing is involved in both constraining pro-tumorigenic changes in pancreatic differentiation as well as maintaining viability during PDA initiation.

Antibiotic-Induced Alterations in Gut Microbiota Are Associated with Changes in Glucose Metabolism in Healthy Mice

The gut microbiome plays an important role in health and disease. Antibiotics are known to alter gut microbiota, yet their effects on glucose tolerance in lean, normoglycemic mice have not been widely investigated. In this study, we aimed to explore mechanisms by which treatment of lean mice with antibiotics (ampicillin, metronidazole, neomycin, vancomycin, or their cocktail) influences the microbiome and glucose metabolism. Specifically, we sought to: (i) study the effects on body weight, fasting glucose, glucose tolerance, and fasting insulin, (ii) examine the changes in expression of key genes of the bile acid and glucose metabolic pathways in the liver and ileum, (iii) identify the shifts in the cecal microbiota, and (iv) infer interactions between gene expression, microbiome, and the metabolic parameters. Treatment with individual or a cocktail of antibiotics reduced fasting glucose but did not affect body weight. Glucose tolerance changed upon treatment with cocktail, ampicillin, or vancomycin as indicated by reduced area under the curve of the glucose tolerance test. Antibiotic treatment changed gene expression in the ileum and liver, and shifted the alpha and beta diversities of gut microbiota. Network analyses revealed associations between Akkermansia muciniphila with fasting glucose and liver farsenoid X receptor (Fxr) in the top ranked host-microbial interactions, suggesting possible mechanisms by which this bacterium can mediate systemic changes in glucose metabolism. We observed Bacteroides uniformis to be positively and negatively correlated with hepatic Fxr and Glucose 6-phosphatase, respectively. Overall, our transkingdom network approach is a useful hypothesis generating strategy that offers insights into mechanisms by which antibiotics can regulate glucose tolerance in non-obese healthy animals. Experimental validation of our predicted microbe-phenotype interactions can help identify mechanisms by which antibiotics affect host phenotypes and gut microbiota.

Investigating a holobiont: Microbiota perturbations and transkingdom networks

Abstract The scientific community has recently come to appreciate that, rather than existing as independent organisms, multicellular hosts and their microbiota comprise a complex evolving superorganism or metaorganism, termed a holobiont. This point of view leads to a re-evaluation of our understanding of different physiological processes and diseases. In this paper we focus on experimental and computational approaches which, when combined in one study, allowed us to dissect mechanisms (traditionally named host-microbiota interactions) regulating holobiont physiology. Specifically, we discuss several approaches for microbiota perturbation, such as use of antibiotics and germ-free animals, including advantages and potential caveats of their usage. We briefly review computational approaches to characterize the microbiota and, more importantly, methods to infer specific components of microbiota (such as microbes or their genes) affecting host functions. One such approach called transkingdom network analysis has been recently developed and applied in our study.1 Finally, we also discuss common methods used to validate the computational predictions of host-microbiota interactions using in vitro and in vivo experimental systems.

Dynamic Proteomic Analysis of Pancreatic Mesenchyme Reveals Novel Factors That Enhance Human Embryonic Stem Cell to Pancreatic Cell Differentiation

Current approaches in human embryonic stem cell (hESC) to pancreatic beta cell differentiation have largely been based on knowledge gained from developmental studies of the epithelial pancreas, while the potential roles of other supporting tissue compartments have not been fully explored. One such tissue is the pancreatic mesenchyme that supports epithelial organogenesis throughout embryogenesis. We hypothesized that detailed characterization of the pancreatic mesenchyme might result in the identification of novel factors not used in current differentiation protocols. Supplementing existing hESC differentiation conditions with such factors might create a more comprehensive simulation of normal development in cell culture. To validate our hypothesis, we took advantage of a novel transgenic mouse model to isolate the pancreatic mesenchyme at distinct embryonic and postnatal stages for subsequent proteomic analysis. Refined sample preparation and analysis conditions across four embryonic and prenatal time points resulted in the identification of 21,498 peptides with high-confidence mapping to 1,502 proteins. Expression analysis of pancreata confirmed the presence of three potentially important factors in cell differentiation: Galectin-1 (LGALS1), Neuroplastin (NPTN), and the Laminin α-2 subunit (LAMA2). Two of the three factors (LGALS1 and LAMA2) increased expression of pancreatic progenitor transcript levels in a published hESC to beta cell differentiation protocol. In addition, LAMA2 partially blocks cell culture induced beta cell dedifferentiation. Summarily, we provide evidence that proteomic analysis of supporting tissues such as the pancreatic mesenchyme allows for the identification of potentially important factors guiding hESC to pancreas differentiation.

Arsenic exposure and intestinal microbiota in children from Sirajdikhan, Bangladesh

Background Arsenic has antimicrobial properties at high doses yet few studies have examined its effect on gut microbiota. This warrants investigation since arsenic exposure increases the risk of many diseases in which gut microbiota have been shown to play a role. We examined the association between arsenic exposure from drinking water and the composition of intestinal microbiota in children exposed to low and high arsenic levels during prenatal development and early life. Results 16S rRNA gene sequencing revealed that children with high arsenic exposure had a higher abundance of Proteobacteria in their stool compared to matched controls with low arsenic exposure. Furthermore, whole metagenome shotgun sequencing identified 332 bacterial SEED functions that were enriched in the high exposure group. A separate model showed that these genes, which included genes involved in virulence and multidrug resistance, were positively correlated with arsenic concentration within the group of children in the high arsenic group. We performed reference free genome assembly, and identified strains of E.coli as contributors to the arsenic enriched SEED functions. Further genome annotation of the E.coli genome revealed two strains containing two different arsenic resistance operons that are not present in the gut microbiome of a recently described European human cohort (Metagenomics of the Human Intestinal Tract, MetaHIT). We then performed quantification by qPCR of two arsenic resistant genes (ArsB, ArsC). We observed that the expression of these two operons was higher among the children with high arsenic exposure compared to matched controls. Conclusions This preliminary study indicates that arsenic exposure early in life was associated with altered gut microbiota in Bangladeshi children. The enrichment of E.coli arsenic resistance genes in the high exposure group provides an insight into the possible mechanisms of how this toxic compound could affect gut microbiota.

CVID enteropathy is characterized by exceeding low mucosal IgA levels and interferon-driven inflammation possibly related to the presence of a pathobiont

Common variable immunodeficiency (CVID), the most common symptomatic primary antibody deficiency, is accompanied in some patients by a duodenal inflammation and malabsorption syndrome known as CVID enteropathy (E-CVID).The goal of this study was to investigate the immunological abnormalities in CVID patients that lead to enteropathy as well as the contribution of intestinal microbiota to this process.We found that, in contrast to noE-CVID patients (without enteropathy), E-CVID patients have exceedingly low levels of IgA in duodenal tissues. In addition, using transkingdom network analysis of the duodenal microbiome, we identified Acinetobacter baumannii as a candidate pathobiont in E-CVID. Finally, we found that E-CVID patients exhibit a pronounced activation of immune genes and down-regulation of epithelial lipid metabolism genes. We conclude that in the virtual absence of mucosal IgA, pathobionts such as A. baumannii, may induce inflammation that re-directs intestinal molecular pathways from lipid metabolism to immune processes responsible for enteropathy.