Transkingdom Network Analysis (TkNA): a systems framework for inferring causal factors underlying host-microbiota and other multi-omic interactions

We present Transkingdom Network Analysis (TkNA), a unique causal-inference analytical framework that offers a holistic view of biological systems by integrating data from multiple cohorts and diverse omics types. TkNA helps to decipher key players and mechanisms governing host-microbiota (or any multi-omic data) interactions in specific conditions or diseases. TkNA reconstructs a network that represents a statistical model capturing the complex relationships between different omics in the biological system. It identifies robust and reproducible patterns of fold change direction and correlation sign across several cohorts to select differential features and their per-group correlations. The framework then uses causality-sensitive metrics, statistical thresholds and topological criteria to determine the final edges forming the transkingdom network. With the subsequent network's topological features, TkNA identifies nodes controlling a given subnetwork or governing communication between kingdoms and/or subnetworks. The computational time for the millions of correlations necessary for network reconstruction in TkNA typically takes only a few minutes, varying with the study design. Unlike most other multi-omics approaches that find only associations, TkNA focuses on establishing causality while accounting for the complex structure of multi-omic data. It achieves this without requiring huge sample sizes. Moreover, the TkNA protocol is user friendly, requiring minimal installation and basic familiarity with Unix. Researchers can access the TkNA software at https://github.com/CAnBioNet/TkNA/ .

Intestinal IL-22RA1 signaling regulates intrinsic and systemic lipid and glucose metabolism to alleviate obesity-associated disorders

IL-22 is critical for ameliorating obesity-induced metabolic disorders. However, it is unknown where IL-22 acts to mediate these outcomes. Here we examine the importance of tissue-specific IL-22RA1 signaling in mediating long-term high fat diet (HFD) driven metabolic disorders. To do so, we generated intestinal epithelium-, liver-, and white adipose tissue (WAT)-specific Il22ra1 knockout and littermate control mice. Intestinal epithelium- and liver-specific IL-22RA1 signaling upregulated systemic glucose metabolism. Intestinal IL-22RA1 signaling also mediated liver and WAT metabolism in a microbiota-dependent manner. We identified an association between Oscillibacter and elevated WAT inflammation, likely induced by Mmp12 expressing macrophages. Mechanistically, transcription of intestinal lipid metabolism genes is regulated by IL-22 and potentially IL-22-induced IL-18. Lastly, we show that Paneth cell-specific IL-22RA1 signaling, in part, mediates systemic glucose metabolism after HFD. Overall, these results elucidate a key role of intestinal epithelium-specific IL-22RA1 signaling in regulating intestinal metabolism and alleviating systemic obesity-associated disorders.

Multi-omic network analysis identified betacellulin as a novel target of omega-3 fatty acid attenuation of western diet-induced nonalcoholic steatohepatitis

Clinical and preclinical studies established that supplementing diets with ω3 polyunsaturated fatty acids (PUFA) can reduce hepatic dysfunction in nonalcoholic steatohepatitis (NASH) but molecular underpinnings of this action were elusive. Herein, we used multi-omic network analysis that unveiled critical molecular pathways involved in ω3 PUFA effects in a preclinical mouse model of western diet induced NASH. Since NASH is a precursor of liver cancer, we also performed meta-analysis of human liver cancer transcriptomes that uncovered betacellulin as a key EGFR-binding protein upregulated in liver cancer and downregulated by ω3 PUFAs in animals and humans with NASH. We then confirmed that betacellulin acts by promoting proliferation of quiescent hepatic stellate cells, inducing transforming growth factor-β2 and increasing collagen production. When used in combination with TLR2/4 agonists, betacellulin upregulated integrins in macrophages thereby potentiating inflammation and fibrosis. Taken together, our results suggest that suppression of betacellulin is one of the key mechanisms associated with anti-inflammatory and anti-fibrotic effects of ω3 PUFA on NASH.

Reducing gut microbiome-driven adipose tissue inflammation alleviates metabolic syndrome

BACKGROUND

The gut microbiota contributes to macrophage-mediated inflammation in adipose tissue with consumption of an obesogenic diet, thus driving the development of metabolic syndrome. There is a need to identify and develop interventions that abrogate this condition. The hops-derived prenylated flavonoid xanthohumol (XN) and its semi-synthetic derivative tetrahydroxanthohumol (TXN) attenuate high-fat diet-induced obesity, hepatosteatosis, and metabolic syndrome in C57Bl/6J mice. This coincides with a decrease in pro-inflammatory gene expression in the gut and adipose tissue, together with alterations in the gut microbiota and bile acid composition.

RESULTS

In this study, we integrated and interrogated multi-omics data from different organs with fecal 16S rRNA sequences and systemic metabolic phenotypic data using a Transkingdom Network Analysis. By incorporating cell type information from single-cell RNA-seq data, we discovered TXN attenuates macrophage inflammatory processes in adipose tissue. TXN treatment also reduced levels of inflammation-inducing microbes, such as Oscillibacter valericigenes, that lead to adverse metabolic phenotypes. Furthermore, in vitro validation in macrophage cell lines and in vivo mouse supplementation showed addition of O. valericigenes supernatant induced the expression of metabolic macrophage signature genes that are downregulated by TXN in vivo.

CONCLUSIONS

Our findings establish an important mechanism by which TXN mitigates adverse phenotypic outcomes of diet-induced obesity and metabolic syndrome. TXN primarily reduces the abundance of pro-inflammatory gut microbes that can otherwise promote macrophage-associated inflammation in white adipose tissue. Video Abstract.

Early transcriptome changes associated with western diet induced NASH in Ldlr-/- mice points to activation of hepatic macrophages and an acute phase response

Background

Nonalcoholic fatty liver disease (NAFLD) is a global health problem. Identifying early gene indicators contributing to the onset and progression of NAFLD has the potential to develop novel targets for early therapeutic intervention. We report on the early and late transcriptomic signatures of western diet (WD)-induced nonalcoholic steatohepatitis (NASH) in female and male Ldlr-/- mice, with time-points at 1 week and 40 weeks on the WD. Control Ldlr-/- mice were maintained on a low-fat diet (LFD) for 1 and 40 weeks.

Methods

The approach included quantitation of anthropometric and hepatic histology markers of disease as well as the hepatic transcriptome.

Results

Only mice fed the WD for 40 weeks revealed evidence of NASH, i.e., hepatic steatosis and fibrosis. RNASeq transcriptome analysis, however, revealed multiple cell-specific changes in gene expression after 1 week that persisted to 40 weeks on the WD. These early markers of disease include induction of acute phase response (Saa1-2, Orm2), fibrosis (Col1A1, Col1A2, TGFβ) and NASH associated macrophage (NAM, i.e., Trem2 high, Mmp12 low). We also noted the induction of transcripts associated with metabolic syndrome, including Mmp12, Trem2, Gpnmb, Lgals3 and Lpl. Finally, 1 week of WD feeding was sufficient to significantly induce TNFα, a cytokine involved in both hepatic and systemic inflammation.

Conclusion

This study revealed early onset changes in the hepatic transcriptome that develop well before any anthropometric or histological evidence of NALFD or NASH and pointed to cell-specific targeting for the prevention of disease progression.

Transkingdom Network Analysis (TkNA): a systems framework for inferring causal factors underlying host-microbiota and other multi-omic interactions

Technological advances have generated tremendous amounts of high-throughput omics data. Integrating data from multiple cohorts and diverse omics types from new and previously published studies can offer a holistic view of a biological system and aid in deciphering its critical players and key mechanisms. In this protocol, we describe how to use Transkingdom Network Analysis (TkNA), a unique causal-inference analytical framework that can perform meta-analysis of cohorts and detect master regulators among measured parameters that govern pathological or physiological responses of host-microbiota (or any multi-omic data) interactions in a particular condition or disease. TkNA first reconstructs the network that represents a statistical model capturing the complex relationships between the different omics of the biological system. Here, it selects differential features and their per-group correlations by identifying robust and reproducible patterns of fold change direction and sign of correlation across several cohorts. Next, a causality-sensitive metric, statistical thresholds, and a set of topological criteria are used to select the final edges that form the transkingdom network. The second part of the analysis involves interrogating the network. Using the network's local and global topology metrics, it detects nodes that are responsible for control of given subnetwork or control of communication between kingdoms and/or subnetworks. The underlying basis of the TkNA approach involves fundamental principles including laws of causality, graph theory and information theory. Hence, TkNA can be used for causal inference via network analysis of any host and/or microbiota multi-omics data. This quick and easy-to-run protocol requires very basic familiarity with the Unix command-line environment.

GATA4 controls regionalization of tissue immunity and commensal-driven immunopathology

There is growing recognition that regionalization of bacterial colonization and immunity along the intestinal tract has an important role in health and disease. Yet, the mechanisms underlying intestinal regionalization and its dysregulation in disease are not well understood. This study found that regional epithelial expression of the transcription factor GATA4 controls bacterial colonization and inflammatory tissue immunity in the proximal small intestine by regulating retinol metabolism and luminal IgA. Furthermore, in mice without jejunal GATA4 expression, the commensal segmented filamentous bacteria promoted pathogenic inflammatory immune responses that disrupted barrier function and increased mortality upon Citrobacter rodentium infection. In celiac disease patients, low GATA4 expression was associated with metabolic alterations, mucosal Actinobacillus, and increased IL-17 immunity. Taken together, these results reveal broad impacts of GATA4-regulated intestinal regionalization on bacterial colonization and tissue immunity, highlighting an elaborate interdependence of intestinal metabolism, immunity, and microbiota in homeostasis and disease.

The C-SHIFT Algorithm for Normalizing Covariances

Omics technologies are powerful tools for analyzing patterns in gene expression data for thousands of genes. Due to a number of systematic variations in experiments, the raw gene expression data is often obfuscated by undesirable technical noises. Various normalization techniques were designed in an attempt to remove these non-biological errors prior to any statistical analysis. One of the reasons for normalizing data is the need for recovering the covariance matrix used in gene network analysis. In this paper, we introduce a novel normalization technique, called the covariance shift (C-SHIFT) method. This normalization algorithm uses optimization techniques together with the blessing of dimensionality philosophy and energy minimization hypothesis for covariance matrix recovery under additive noise (in biology, known as the bias). Thus, it is perfectly suited for the analysis of logarithmic gene expression data. Numerical experiments on synthetic data demonstrate the method's advantage over the classical normalization techniques. Namely, the comparison is made with Rank, Quantile, cyclic LOESS (locally estimated scatterplot smoothing), and MAD (median absolute deviation) normalization methods. We also evaluate the performance of C-SHIFT algorithm on real biological data.

Microbiota and adipocyte mitochondrial damage in type 2 diabetes are linked by Mmp12+ macrophages

Microbiota contribute to the induction of type 2 diabetes by high-fat/high-sugar (HFHS) diet, but which organs/pathways are impacted by microbiota remain unknown. Using multiorgan network and transkingdom analyses, we found that microbiota-dependent impairment of OXPHOS/mitochondria in white adipose tissue (WAT) plays a primary role in regulating systemic glucose metabolism. The follow-up analysis established that Mmp12+ macrophages link microbiota-dependent inflammation and OXPHOS damage in WAT. Moreover, the molecular signature of Mmp12+ macrophages in WAT was associated with insulin resistance in obese patients. Next, we tested the functional effects of MMP12 and found that Mmp12 genetic deficiency or MMP12 inhibition improved glucose metabolism in conventional, but not in germ-free mice. MMP12 treatment induced insulin resistance in adipocytes. TLR2-ligands present in Oscillibacter valericigenes bacteria, which are expanded by HFHS, induce Mmp12 in WAT macrophages in a MYD88-ATF3-dependent manner. Thus, HFHS induces Mmp12+ macrophages and MMP12, representing a microbiota-dependent bridge between inflammation and mitochondrial damage in WAT and causing insulin resistance.

Interactions Between Aryl Hydrocarbon Receptor and the Microbiome Regulate Intestinal Macrophages in Non Obese Diabetic Mice

Type 1 diabetes (T1D) arises from a complex interaction between genetic and environmental factors. Multiple environmental signals predicted to impact T1D development occur at the intestinal surface, as a result of exposures through ingestion, dietary antigens, and microbial colonization. It is hypothesized that an inappropriate immune response to these exposures precipitates overt T1D. We discovered a novel mechanism by which environmental surveillance interacts with the immune system: immunosuppressive lamina propria (LP) macrophage regulation via the aryl hydrocarbon receptor (AhR). In NOD mice, AhR negatively regulates a macrophage subset (CD11b+CX3CR1+MHCIIhi; AhR-MFs) that have a strong positive correlation CD4+IL10R+Foxp3+ Tregs in the small intestine. To identify the potential source of AhR ligands that regulate these resident-like macrophages, mice were fed an AhR ligand-deficient diet. These cells were not further regulated by dietary ligands, suggesting that AhR activation originates from ligands produced by the intestinal microbiome. Therefore, germ-free NOD AhR knockout mice were derived and the AhR-MF population was measured. In the absence of the microbiome, both AhR knockout and wild type mice had high levels of AhR-MFs, demonstrating that the microbiome is required for AhR-mediated regulation of LP macrophages. RNAseq analysis of sorted AhR-MFs demonstrate that these cells are antigen presenting but lack an inflammatory gene signature. Currently, single cell sequencing of CD45+ LP cells from AhR knockout NOD mice is being performed to identify how AhR alters macrophage differentiation and predict mechanisms of crosstalk with intestinal CD4+ T cell populations.

Supported by R00 DK117509-03, T32 ES007059

Intestinal microbiota signatures of clinical response and immune-related adverse events in melanoma patients treated with anti-PD-1

Ample evidence indicates that the gut microbiome is a tumor-extrinsic factor associated with antitumor response to anti-programmed cell death protein-1 (PD-1) therapy, but inconsistencies exist between published microbial signatures associated with clinical outcomes. To resolve this, we evaluated a new melanoma cohort, along with four published datasets. Time-to-event analysis showed that baseline microbiota composition was optimally associated with clinical outcome at approximately 1 year after initiation of treatment. Meta-analysis and other bioinformatic analyses of the combined data show that bacteria associated with favorable response are confined within the Actinobacteria phylum and the Lachnospiraceae/Ruminococcaceae families of Firmicutes. Conversely, Gram-negative bacteria were associated with an inflammatory host intestinal gene signature, increased blood neutrophil-to-lymphocyte ratio, and unfavorable outcome. Two microbial signatures, enriched for Lachnospiraceae spp. and Streptococcaceae spp., were associated with favorable and unfavorable clinical response, respectively, and with distinct immune-related adverse effects. Despite between-cohort heterogeneity, optimized all-minus-one supervised learning algorithms trained on batch-corrected microbiome data consistently predicted outcomes to programmed cell death protein-1 therapy in all cohorts. Gut microbial communities (microbiotypes) with nonuniform geographical distribution were associated with favorable and unfavorable outcomes, contributing to discrepancies between cohorts. Our findings shed new light on the complex interaction between the gut microbiome and response to cancer immunotherapy, providing a roadmap for future studies.

Citation of the “Psychological Journal” in the Information Space of the World's Leading Scientific Editions

The article analyzes the key scientometric indicators associated with the citation of the leading domestic industry periodical — “Psychological Journal”: the impact factor of the publication, the average citation of articles in thematic areas, the Hirsch index and others. The sectoral structure of citation of the “Psychological Journal”, as well as the geography of citation of publications of the journal, is revealed. The publication productivity and citation of the thematic areas supported by the journal in the international information space of the world's leading scientific publications are considered. The conclusion is made about the most demanded (cited) scientific directions of the “Psychological Journal”; its interdisciplinary status is emphasized.

Dietary fiber and probiotics influence the gut microbiome and melanoma immunotherapy response

Gut bacteria modulate the response to immune checkpoint blockade (ICB) treatment in cancer, but the effect of diet and supplements on this interaction is not well studied. We assessed fecal microbiota profiles, dietary habits, and commercially available probiotic supplement use in melanoma patients and performed parallel preclinical studies. Higher dietary fiber was associated with significantly improved progression-free survival in 128 patients on ICB, with the most pronounced benefit observed in patients with sufficient dietary fiber intake and no probiotic use. Findings were recapitulated in preclinical models, which demonstrated impaired treatment response to anti–programmed cell death 1 (anti–PD-1)–based therapy in mice receiving a low-fiber diet or probiotics, with a lower frequency of interferon-γ–positive cytotoxic T cells in the tumor microenvironment. Together, these data have clinical implications for patients receiving ICB for cancer.

Xanthohumol Requires the Intestinal Microbiota to Improve Glucose Metabolism in Diet-Induced Obese Mice

SCOPE

The polyphenol xanthohumol (XN) improves dysfunctional glucose and lipid metabolism in diet-induced obesity animal models. Because XN changes intestinal microbiota composition, the study hypothesizes that XN requires the microbiota to mediate its benefits.

METHODS AND RESULTS

To test the hypothesis, the study feeds conventional and germ-free male Swiss Webster mice either a low-fat diet (LFD, 10% fat derived calories), a high-fat diet (HFD, 60% fat derived calories), or a high-fat diet supplemented with XN at 60 mg kg-1 body weight per day (HXN) for 10 weeks, and measure parameters of glucose and lipid metabolism. In conventional mice, the study discovers XN supplementation decreases plasma insulin concentrations and improves Homeostatic Model Assessment of Insulin Resistance (HOMA-IR). In germ-free mice, XN supplementation fails to improve these outcomes. Fecal sample 16S rRNA gene sequencing analysis suggests XN supplementation changes microbial composition and dramatically alters the predicted functional capacity of the intestinal microbiota. Furthermore, the intestinal microbiota metabolizes XN into bioactive compounds, including dihydroxanthohumol (DXN), an anti-obesogenic compound with improved bioavailability.

CONCLUSION

XN requires the intestinal microbiota to mediate its benefits, which involves complex diet-host-microbiota interactions with changes in both microbial composition and functional capacity. The study results warrant future metagenomic studies which will provide insight into complex microbe-microbe interactions and diet-host-microbiota interactions.

Abstract LB062: Efficacy of Responder-derived Fecal Microbiota Transplant (R-FMT) and Pembrolizumab in Anti-PD-1 Refractory Patients with Advanced Melanoma

Background: Monoclonal antibodies (mAb) targeting the programmed cell death protein 1 (PD-1) receptor provide durable long-term benefit in a subset of patients (pts) with advanced melanoma with response rates of 35-42% and 4-year progression-free survival (PFS) rate of 27%. Separately, the composition of the gut microbiota has been shown to correlate with anti-PD-1 efficacy in human cancer pts with melanoma, renal cell cancer and non-small cell lung cancer (NSCLC) although the precise organisms differ considerably across various studies. In preclinical models, responder-derived fecal microbiome and microbiome consortia produce anti-tumor responses. The effect of microbiome modulation in pts with anti-PD-1 refractory melanoma has not been evaluated. Methods: To evaluate whether primary resistance to anti-PD-1 immunotherapy could be overcome by intestinal microbiome modulation, we designed and conducted a phase II study (NCT03341143). We enrolled pts with primary refractory metastatic melanoma with best response of short-term stable disease (≤6 months) or progressive disease (PD) to prior anti-PD-1 based immunotherapy. Pts received single-administration of responder-derived fecal microbiota transplantation (R-FMT) together with pembrolizumab. Candidate donors were pts with advanced melanoma treated with anti-PD-1 immunotherapy with durable partial or complete response (PR, CR). Pembrolizumab was continued till intolerable toxicity or disease progression. Safety and clinical activity (based on RECIST v1.1) were main objectives; while progression-free survival (PFS) was a key secondary endpoint. Results: As of December 1, 2020, 16 pts with primary refractory melanoma were enrolled, of whom 15 were evaluable. LDH was elevated in 14/15 pts; and the median number of prior therapies was 2. Recipient pts were seromatched to receive a single R-FMT from one of eight candidate donors (5 CR; 3 PR; median PFS 58 months, range 43-70). R-FMT was administered via colonoscopy after bowel preparation with no use of antibiotics. Pembrolizumab was administered IV per label. R-FMT/pembrolizumab was well-tolerated, with no unusual toxicity signals. R-FMT induced rapid and durable microbiota perturbation in most pts; while 6 of 15 evaluable pts had evidence of clinical benefit. Response to R-FMT/pembrolizumab was associated with an increased abundance of taxa previously shown to be associated with response to anti-PD-1, increased CD8+ T cell activation, and decreased frequency of IL-8 expressing myeloid cells. Responders had distinct proteomic and metabolomic signatures, and transkingdom network analyses confirmed that the gut microbiome regulated these changes. Conclusions: In pts with anti-PD-1 primary refractory melanoma, R-FMT/pembrolizumab changed the gut microbiome and reprogrammed the tumor microenvironment to overcome resistance to anti-PD-1 immunotherapy. Response was associated with CD8 T cell induction and reduction of IL-8 expressing myeloid cells.

Citation Format: Diwakar Davar, Amiran Dzutsev, John A. McCulloch, Richard R. Rodrigues, Joe-Marc Chauvin, Robert M. Morrison, Richelle N. Deblasio, Carmine Menna, Quanquan Ding, Ornella Pagliano, Bochra Zidi, Shuowen Zhang, Jonathan H. Badger, Marie Vetizou, Alicia M. Cole, Miriam R. Fernandes, Stephanie Prescott, Raquel G. Costa, Ascharya K. Balaji, Andrey Morgun, Ivan Vujkovic-Cvijin, Hong Wang, Amir A. Borhani, Marc B. Schwartz, Howard M. Dubner, Scarlett J. Ernst, Amy Rose, Yana G. Najjar, Yasmine Belkaid, John M. Kirkwood, Giorgio Trinchieri, Hassane M. Zarour. Efficacy of Responder-derived Fecal Microbiota Transplant (R-FMT) and Pembrolizumab in Anti-PD-1 Refractory Patients with Advanced Melanoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB062.

Fecal microbiota transplant overcomes resistance to anti-PD-1 therapy in melanoma patients

Anti-programmed cell death protein 1 (PD-1) therapy provides long-term clinical benefits to patients with advanced melanoma. The composition of the gut microbiota correlates with anti-PD-1 efficacy in preclinical models and cancer patients. To investigate whether resistance to anti-PD-1 can be overcome by changing the gut microbiota, this clinical trial evaluated the safety and efficacy of responder-derived fecal microbiota transplantation (FMT) together with anti-PD-1 in patients with PD-1-refractory melanoma. This combination was well tolerated, provided clinical benefit in 6 of 15 patients, and induced rapid and durable microbiota perturbation. Responders exhibited increased abundance of taxa that were previously shown to be associated with response to anti-PD-1, increased CD8⁺ T cell activation, and decreased frequency of interleukin-8-expressing myeloid cells. Responders had distinct proteomic and metabolomic signatures, and transkingdom network analyses confirmed that the gut microbiome regulated these changes. Collectively, our findings show that FMT and anti-PD-1 changed the gut microbiome and reprogrammed the tumor microenvironment to overcome resistance to anti-PD-1 in a subset of PD-1 advanced melanoma.

Dietary Indole-3-Carbinol Activates AhR in the Gut, Alters Th17-Microbe Interactions, and Exacerbates Insulitis in NOD Mice

The diet represents one environmental risk factor controlling the progression of type 1 diabetes (T1D) in genetically susceptible individuals. Consequently, understanding which specific nutritional components promote or prevent the development of disease could be used to make dietary recommendations in prediabetic individuals. In the current study, we hypothesized that the immunoregulatory phytochemcial, indole-3-carbinol (I3C) which is found in cruciferous vegetables, will regulate the progression of T1D in nonobese diabetic (NOD) mice. During digestion, I3C is metabolized into ligands for the aryl hydrocarbon receptor (AhR), a transcription factor that when systemically activated prevents T1D. In NOD mice, an I3C-supplemented diet led to strong AhR activation in the small intestine but minimal systemic AhR activity. In the absence of this systemic response, the dietary intervention led to exacerbated insulitis. Consistent with the compartmentalization of AhR activation, dietary I3C did not alter T helper cell differentiation in the spleen or pancreatic draining lymph nodes. Instead, dietary I3C increased the percentage of CD4+RORγt+Foxp3- (Th17 cells) in the lamina propria, intraepithelial layer, and Peyer's patches of the small intestine. The immune modulation in the gut was accompanied by alterations to the intestinal microbiome, with changes in bacterial communities observed within one week of I3C supplementation. A transkingdom network was generated to predict host-microbe interactions that were influenced by dietary I3C. Within the phylum Firmicutes, several genera (Intestinimonas, Ruminiclostridium 9, and unclassified Lachnospiraceae) were negatively regulated by I3C. Using AhR knockout mice, we validated that Intestinimonas is negatively regulated by AhR. I3C-mediated microbial dysbiosis was linked to increases in CD25high Th17 cells. Collectively, these data demonstrate that site of AhR activation and subsequent interactions with the host microbiome are important considerations in developing AhR-targeted interventions for T1D.

Transkingdom interactions between Lactobacilli and hepatic mitochondria attenuate western diet-induced diabetes

Western diet (WD) is one of the major culprits of metabolic disease including type 2 diabetes (T2D) with gut microbiota playing an important role in modulating effects of the diet. Herein, we use a data-driven approach (Transkingdom Network analysis) to model host-microbiome interactions under WD to infer which members of microbiota contribute to the altered host metabolism. Interrogation of this network pointed to taxa with potential beneficial or harmful effects on host's metabolism. We then validate the functional role of the predicted bacteria in regulating metabolism and show that they act via different host pathways. Our gene expression and electron microscopy studies show that two species from Lactobacillus genus act upon mitochondria in the liver leading to the improvement of lipid metabolism. Metabolomics analyses revealed that reduced glutathione may mediate these effects. Our study identifies potential probiotic strains for T2D and provides important insights into mechanisms of their action.

Gut-resident CX3CR1hi macrophages induce tertiary lymphoid structures and IgA response in situ

Intestinal mononuclear phagocytes (MPs) are composed of heterogeneous dendritic cell (DC) and macrophage subsets necessary for the initiation of immune response and control of inflammation. Although MPs in the normal intestine have been extensively studied, the heterogeneity and function of inflammatory MPs remain poorly defined. We performed phenotypical, transcriptional, and functional analyses of inflammatory MPs in infectious Salmonella colitis and identified CX3CR1⁺ MPs as the most prevalent inflammatory cell type. CX3CR1⁺ MPs were further divided into three distinct populations, namely, Nos2 ⁺CX3CR1^lo, Ccr7 ⁺CX3CR1^int (lymph migratory), and Cxcl13 ⁺CX3CR1^hi (mucosa resident), all of which were transcriptionally aligned with macrophages and derived from monocytes. In follow-up experiments in vivo, intestinal CX3CR1⁺ macrophages were superior to conventional DC1 (cDC1) and cDC2 in inducing Salmonella-specific mucosal IgA. We next examined spatial organization of the immune response induced by CX3CR1⁺ macrophage subsets and identified mucosa-resident Cxcl13 ⁺CX3CR1^hi macrophages as the antigen-presenting cells responsible for recruitment and activation of CD4⁺ T and B cells to the sites of Salmonella invasion, followed by tertiary lymphoid structure formation and the local pathogen-specific IgA response. Using mice we developed with a floxed Ccr7 allele, we showed that this local IgA response developed independently of migration of the Ccr7 ⁺CX3CR1^int population to the mesenteric lymph nodes and contributed to the total mucosal IgA response to infection. The differential activity of intestinal macrophage subsets in promoting mucosal IgA responses should be considered in the development of vaccines to prevent Salmonella infection and in the design of anti-inflammatory therapies aimed at modulating macrophage function in inflammatory bowel disease.

Role of gut microbiota in type 2 diabetes pathophysiology

A substantial body of literature has provided evidence for the role of gut microbiota in metabolic diseases including type 2 diabetes. However, reports vary regarding the association of particular taxonomic groups with disease. In this systematic review, we focused on the potential role of different bacterial taxa affecting diabetes. We have summarized evidence from 42 human studies reporting microbial associations with disease, and have identified supporting preclinical studies or clinical trials using treatments with probiotics. Among the commonly reported findings, the genera of Bifidobacterium, Bacteroides, Faecalibacterium, Akkermansia and Roseburia were negatively associated with T2D, while the genera of Ruminococcus, Fusobacterium, and Blautia were positively associated with T2D. We also discussed potential molecular mechanisms of microbiota effects in the onset and progression of T2D.

Improvements in Metabolic Syndrome by Xanthohumol Derivatives Are Linked to Altered Gut Microbiota and Bile Acid Metabolism

SCOPE

Two hydrogenated xanthohumol (XN) derivatives, α,β-dihydro-XN (DXN) and tetrahydro-XN (TXN), improved parameters of metabolic syndrome (MetS), a critical risk factor of cardiovascular disease (CVD) and type 2 diabetes, in a diet-induced obese murine model. It is hypothesized that improvements in obesity and MetS are linked to changes in composition of the gut microbiota, bile acid metabolism, intestinal barrier function, and inflammation.

METHODS AND RESULTS

To test this hypothesis, 16S rRNA genes were sequenced and bile acids were measured in fecal samples from C57BL/6J mice fed a high-fat diet (HFD) or HFD containing XN, DXN or TXN. Expression of genes associated with epithelial barrier function, inflammation, and bile acid metabolism were measured in the colon, white adipose tissue (WAT), and liver, respectively. Administration of XN derivatives decreases intestinal microbiota diversity and abundance-specifically Bacteroidetes and Tenericutes-alters bile acid metabolism, and reduces inflammation. In WAT, TXN supplementation decreases pro-inflammatory gene expression by suppressing macrophage infiltration. Transkingdom network analysis connects changes in the microbiota to improvements in MetS in the host.

CONCLUSION

Changes in the gut microbiota and bile acid metabolism may explain, in part, the improvements in obesity and MetS associated with administration of XN and its derivatives.

Commensal bacteria contribute to insulin resistance in aging by activating innate B1a cells

Aging in humans is associated with increased hyperglycemia and insulin resistance (collectively termed IR) and dysregulation of the immune system. However, the causative factors underlying their association remain unknown. Here, using "healthy" aged mice and macaques, we found that IR was induced by activated innate 4-1BBL⁺ B1a cells. These cells (also known as 4BL cells) accumulated in aging in response to changes in gut commensals and a decrease in beneficial metabolites such as butyrate. We found evidence suggesting that loss of the commensal bacterium Akkermansia muciniphila impaired intestinal integrity, causing leakage of bacterial products such as endotoxin, which activated CCR2⁺ monocytes when butyrate was decreased. Upon infiltration into the omentum, CCR2⁺ monocytes converted B1a cells into 4BL cells, which, in turn, induced IR by expressing 4-1BBL, presumably to trigger 4-1BB receptor signaling as in obesity-induced metabolic disorders. This pathway and IR were reversible, as supplementation with either A. muciniphila or the antibiotic enrofloxacin, which increased the abundance of A. muciniphila, restored normal insulin response in aged mice and macaques. In addition, treatment with butyrate or antibodies that depleted CCR2⁺ monocytes or 4BL cells had the same effect on IR. These results underscore the pathological function of B1a cells and suggest that the microbiome-monocyte-B cell axis could potentially be targeted to reverse age-associated IR.

Effect of temperature and time on the thanatomicrobiome of the cecum, ileum, kidney, and lung of domestic rabbits

Knowledge of changes in the composition of microbial communities (microbiota) in tissues after death, over time, is critical to correctly interpret results of microbiologic testing from postmortem examinations. Limited information is available about postmortem changes of the microbiota and the associated microbial genes (microbiome) of internal organs in any species. We examined the effect of time and ambient temperature on the postmortem microbiome (thanatomicrobiome) of tissues typically sampled for microbiologic testing during autopsies. Twenty rabbits were euthanized and their bodies stored at 4°C or 20°C for 6 or 48 h. Ileum, cecum, kidney, and lung tissue were sampled. Bacterial DNA abundance was determined by RT-qPCR. Microbiome diversity was determined by 16S rRNA gene sequencing. By relative abundance of the microbiome composition, intestinal tissues were clearly separated from lungs and kidneys, which were similar to each other, over all times and temperatures. Only cecal thanatomicrobiomes had consistently high concentrations and consistent composition in all conditions. In lungs and kidneys, but not intestine, proteobacteria were highly abundant at specific times and temperatures. Thanatomicrobiome variation was not explained by minor subclinical lesions identified upon microscopic examination of tissues. Bacterial communities typically found in the intestine were not identified at extra-intestinal sites in the first 48 h at 4°C and only in small amounts at 20°C. However, changes in tissue-specific microbiomes during the postmortem interval should be considered when interpreting results of microbiologic testing.

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.

Transkingdom network reveals bacterial players associated with cervical cancer gene expression program

Cervical cancer is the fourth most common cancer in women worldwide with human papillomavirus (HPV) being the main cause the disease. Chromosomal amplifications have been identified as a source of upregulation for cervical cancer driver genes but cannot fully explain increased expression of immune genes in invasive carcinoma. Insight into additional factors that may tip the balance from immune tolerance of HPV to the elimination of the virus may lead to better diagnosis markers. We investigated whether microbiota affect molecular pathways in cervical carcinogenesis by performing microbiome analysis via sequencing 16S rRNA in tumor biopsies from 121 patients. While we detected a large number of intra-tumor taxa (289 operational taxonomic units (OTUs)), we focused on the 38 most abundantly represented microbes. To search for microbes and host genes potentially involved in the interaction, we reconstructed a transkingdom network by integrating a previously discovered cervical cancer gene expression network with our bacterial co-abundance network and employed bipartite betweenness centrality. The top ranked microbes were represented by the families Bacillaceae, Halobacteriaceae, and Prevotellaceae. While we could not define the first two families to the species level, Prevotellaceae was assigned to Prevotella bivia. By co-culturing a cervical cancer cell line with P. bivia, we confirmed that three out of the ten top predicted genes in the transkingdom network (lysosomal associated membrane protein 3 (LAMP3), STAT1, TAP1), all regulators of immunological pathways, were upregulated by this microorganism. Therefore, we propose that intra-tumor microbiota may contribute to cervical carcinogenesis through the induction of immune response drivers, including the well-known cancer gene LAMP3.

Transkingdom Networks: A Systems Biology Approach to Identify Causal Members of Host-Microbiota Interactions

Improvements in sequencing technologies and reduced experimental costs have resulted in a vast number of studies generating high-throughput data. Although the number of methods to analyze these "omics" data has also increased, computational complexity and lack of documentation hinder researchers from analyzing their high-throughput data to its true potential. In this chapter we detail our data-driven, transkingdom network (TransNet) analysis protocol to integrate and interrogate multi-omics data. This systems biology approach has allowed us to successfully identify important causal relationships between different taxonomic kingdoms (e.g., mammals and microbes) using diverse types of data.

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.

Interplay between viruses and bacterial microbiota in cancer development

During the last few decades we have become accustomed to the idea that viruses can cause tumors. It is much less considered and discussed, however, that most people infected with oncoviruses will never develop cancer. Therefore, the genetic and environmental factors that tip the scales from clearance of viral infection to development of cancer are currently an area of active investigation. Microbiota has recently emerged as a potentially critical factor that would affect this balance by increasing or decreasing the ability of viral infection to promote carcinogenesis. In this review, we provide a model of microbiome contribution to the development of oncogenic viral infections and viral associated cancers, give examples of this process in human tumors, and describe the challenges that prevent progress in the field as well as their potential solutions.

Differentially correlated genes in co-expression networks control phenotype transitions

Background: Co-expression networks are a tool widely used for analysis of “Big Data” in biology that can range from transcriptomes to proteomes, metabolomes and more recently even microbiomes. Several methods were proposed to answer biological questions interrogating these networks. Differential co-expression analysis is a recent approach that measures how gene interactions change when a biological system transitions from one state to another. Although the importance of differentially co-expressed genes to identify dysregulated pathways has been noted, their role in gene regulation is not well studied. Herein we investigated differentially co-expressed genes in a relatively simple mono-causal process (B lymphocyte deficiency) and in a complex multi-causal system (cervical cancer).

Methods: Co-expression networks of B cell deficiency (Control and BcKO) were reconstructed using Pearson correlation coefficient for two mus musculus datasets: B10.A strain (12 normal, 12 BcKO) and BALB/c strain (10 normal, 10 BcKO). Co-expression networks of cervical cancer (normal and cancer) were reconstructed using local partial correlation method for five datasets (total of 64 normal, 148 cancer). Differentially correlated pairs were identified along with the location of their genes in BcKO and in cancer networks. Minimum Shortest Path and Bi-partite Betweenness Centrality where statistically evaluated for differentially co-expressed genes in corresponding networks.   

Results: We show that in B cell deficiency the differentially co-expressed genes are highly enriched with immunoglobulin genes (causal genes). In cancer we found that differentially co-expressed genes act as “bottlenecks” rather than causal drivers with most flows that come from the key driver genes to the peripheral genes passing through differentially co-expressed genes. Using in vitro knockdown experiments for two out of 14 differentially co-expressed genes found in cervical cancer (FGFR2 and CACYBP), we showed that they play regulatory roles in cancer cell growth.

Conclusion: Identifying differentially co-expressed genes in co-expression networks is an important tool in detecting regulatory genes involved in alterations of phenotype.

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.

Mice deficient in the pro-inflammatory cytokine IFNγ have improved glucose tolerance. Here, the authors show that this effect depends on the gut microbe Akkermansia muciniphila, whose abundance increases in the absence IFNγ, and which is known to have beneficial effects on host metabolism.

Unexpected links reflect the noise in networks

BACKGROUND

Gene covariation networks are commonly used to study biological processes. The inference of gene covariation networks from observational data can be challenging, especially considering the large number of players involved and the small number of biological replicates available for analysis.

RESULTS

We propose a new statistical method for estimating the number of erroneous edges in reconstructed networks that strongly enhances commonly used inference approaches. This method is based on a special relationship between sign of correlation (positive/negative) and directionality (up/down) of gene regulation, and allows for the identification and removal of approximately half of all erroneous edges. Using the mathematical model of Bayesian networks and positive correlation inequalities we establish a mathematical foundation for our method. Analyzing existing biological datasets, we find a strong correlation between the results of our method and false discovery rate (FDR). Furthermore, simulation analysis demonstrates that our method provides a more accurate estimate of network error than FDR.

CONCLUSIONS

Thus, our study provides a new robust approach for improving reconstruction of covariation networks.

REVIEWERS

This article was reviewed by Eugene Koonin, Sergei Maslov, Daniel Yasumasa Takahashi.

STUDY OF DOSES TO HIPPOCAMPUS OF INTERVENTIONAL CARDIOLOGISTS AND THEIR IMPLICATION FOR DOSIMETRIC MONITORING

Dosimetric monitoring and protection of the personnel involved into interventional procedures is one of the key issues nowadays, yet doses received by their brains were left without rigorous consideration so far. The paper is the fast track of the results of the pilot study of possible magnitude of operator's doses with particular focus on difference between doses in left and right hippocampi and their relation to effective doses of personnel using protective aprons. Monte Carlo simulation of irradiation in a typical interventional cardiology (IC) operation room shows that for standard C-arm angulations difference in doses between left and right hippocampi can be as large as 5-fold (depending on energy and projection), under certain conditions dose to left (most exposed) hippocampus can be up to two times higher than effective dose estimated by a common double dosimetry algorithm. This finding calls for closer attention to possible manifestations of health detriment associated with occupational irradiation of left hippocampus in course of IC practice.

Investigating a holobiont: Microbiota perturbations and transkingdom networks

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.

Problems following hippocampal irradiation in interventional radiologists - doses and potential effects: a Monte Carlo simulation

OBJECTIVE

This study aimed at investigating radiation exposure of hippocampus in interventional medical profes sionals irradiated in the operating room, and to compare doses in the hippocampus with the effective dose (protec tion quantity), as well as with the doses measured by individual dosimeter, in order to estimate probability of reach ing levels of radiation induced cognitive and other neuropsychiatric alterations during their working career, through a Monte Carlo simulation.

MATERIALS AND METHODS

A Monte Carlo simulation of hippocampal exposure was used by means of a hybrid voxel mathematical phantom of a doctor irradiated in typical angiographic projections and energy spectra inherent to interventional cardiology procedures.

RESULTS

The results showed that cranial irradiation was very heterogeneous and depended on the projection: doses of left and right hippocampi may be different up to a factor of 2.5; under certain conditions, the dose of the left hippocampus may be twice the effective dose, estimated by conventional double dosimetry algorithm.

CONCLUSIONS

The professional span doses of the irradiated hippocampus may overcome the threshold able to pro voke possible cognitive and emotional behavioral impairment. Therefore, in depth studies of the effects of brain irradiation in occupationally exposed interventional medical personnel appear urgently needed and crucial.

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.

Reverse enGENEering of Regulatory Networks from Big Data: A Roadmap for Biologists

Omics technologies enable unbiased investigation of biological systems through massively parallel sequence acquisition or molecular measurements, bringing the life sciences into the era of Big Data. A central challenge posed by such omics datasets is how to transform these data into biological knowledge, for example, how to use these data to answer questions such as: Which functional pathways are involved in cell differentiation? Which genes should we target to stop cancer? Network analysis is a powerful and general approach to solve this problem consisting of two fundamental stages, network reconstruction, and network interrogation. Here we provide an overview of network analysis including a step-by-step guide on how to perform and use this approach to investigate a biological question. In this guide, we also include the software packages that we and others employ for each of the steps of a network analysis workflow.

Ménage à trois: an evolutionary interplay between human papillomavirus, a tumor, and a woman

Cervical cancer is the third most common cancer in women with human papillomavirus (HPV) being a key etiologic factor of this devastating disease. In this article, we describe modern advances in the genomics and transcriptomics of cervical cancer that led to uncovering the key gene drivers. We also introduce, herein, a model of cervical carcinogenesis that explains how the interplay between virus, tumor, and woman results in the selection of clones that simultaneously harbor genomic amplifications for genes that drive cell cycle, antiviral response, and inhibit cell differentiation. The new model may help researchers understand the controversies in antiviral therapy and immunogenetics of this cancer and may provide a basis for future research directions in early diagnostics and personalization of therapy.

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.

Gene network reconstruction reveals cell cycle and antiviral genes as major drivers of cervical cancer

Although human papillomavirus was identified as an aetiological factor in cervical cancer, the key human gene drivers of this disease remain unknown. Here we apply an unbiased approach integrating gene expression and chromosomal aberration data. In an independent group of patients, we reconstruct and validate a gene regulatory meta-network, and identify cell cycle and antiviral genes that constitute two major subnetworks upregulated in tumour samples. These genes are located within the same regions as chromosomal amplifications, most frequently on 3q. We propose a model in which selected chromosomal gains drive activation of antiviral genes contributing to episomal virus elimination, which synergizes with cell cycle dysregulation. These findings may help to explain the paradox of episomal human papillomavirus decline in women with invasive cancer who were previously unable to clear the virus.

Construct and Compare Gene Coexpression Networks with DAPfinder and DAPview

BACKGROUND

DAPfinder and DAPview are novel BRB-ArrayTools plug-ins to construct gene coexpression networks and identify significant differences in pairwise gene-gene coexpression between two phenotypes.

RESULTS

Each significant difference in gene-gene association represents a Differentially Associated Pair (DAP). Our tools include several choices of filtering methods, gene-gene association metrics, statistical testing methods and multiple comparison adjustments. Network results are easily displayed in Cytoscape. Analyses of glioma experiments and microarray simulations demonstrate the utility of these tools.

CONCLUSIONS

DAPfinder is a new friendly-user tool for reconstruction and comparison of biological networks.

Dissecting the effects of microflora and antibiotics on immune and metabolic compartments in the gut (90.7)

Because germ-free animals are difficult to generate and maintain, antibiotic-treated animals are often substituted in studies designed to determine the role of the normal microflora in health and disease. To determine the extent to which antibiotic (AB) treatment mimics the germ-free condition, and to ascertain the direct effects of AB on the host, we orally treated conventional and germ-free (GF) mice with a combination of four antibiotics for one month and performed microarray analysis of terminal ileum. We observed a decrease in the expression of T lymphocyte genes in both AB-treated and GF mice whereas B-lymphocyte transcripts had much higher expression in AB-treated and conventional than in GF mice. This result was confirmed at the cell number level in the tissue. Among the direct effects of antibiotics independent on flora, we found a decrease in the expression of genes related to mitochondrial functions and cell division. Concordantly, we detected lower amounts of mitochondria and a higher rate of cell death in the gut epithelial cells of AB-treated than of control mice. In conclusion, we found that antibiotics treatment only partially recapitulates the GF condition for mucosal immune system being able to mimic the germ-free status of mucosal T lymphocytes but not of B lymphocytes. In addition, antibiotics have some major direct effects decreasing energy metabolism in the host tissue independently on flora elimination.

Shaping of the gut microbiota by B lymphocytes influences GATA4-dependent lipid absorption and body fat accumulation (90.8)

In order to understand the role for B lymphocytes in normal physiology of intestine, we compared global gene expression in the jejunum of wild-type (WT) and B-cell knockout (KO) mice. We found about 300 genes whose expression differed between WT and B-cell KO mice. Genes down-regulated in B- cell KO intestines, were highly enriched for lipid/energy metabolism genes. Consistent with this result, we found lower amounts of para-genital fat and serum leptin level in B-cell KO mice than in their B-cell-sufficient littermates. We revealed GATA4 as the most enriched transcription factor for the down regulated genes. Conditional KO of Gata4 in the intestinal epithelium showed a high correlation with BcKO gene signature. We also found a decrease in cholesterol absorption in the gut of B-cell KO mice (p<0.005) previously observed in Gata4 intestinal KO. In addition, Gata4 KO mice perfectly recapitulated the systemic effects observed in B-cell KO mice presenting decreased levels of body fat and leptin (p<0.01). Studying the mechanism, we found that mice that have B lymphocytes but do not produce soluble antibodies exhibit a very similar gene expression profile as the B-cell KO mice implying that this phenomenon is antibody-dependent. Under germ-free conditions, we found almost no difference between B-cell KO and control mice. Thus we conclude that B lymphocytes are involved in the control of GATA4-dependent lipid absorption and accumulation of body fat by shaping the gut microflora.

New approach reveals CD28 and IFNG gene interaction in the susceptibility to cervical cancer

Cervical cancer is a complex disease with multiple environmental and genetic determinants. In this study, we sought an association between polymorphisms in immune response genes and cervical cancer using both single-locus and multi-locus analysis approaches. A total of 14 single nucleotide polymorphisms (SNPs) distributed in CD28, CTLA4, ICOS, PDCD1, FAS, TNFA, IL6, IFNG, TGFB1 and IL10 genes were determined in patients and healthy individuals from three independent case/control sets. The first two sets comprised White individuals (one group with 82 cases and 85 controls, the other with 83 cases and 85 controls) and the third was constituted by non-white individuals (64 cases and 75 controls). The multi-locus analysis revealed higher frequencies in cancer patients of three three-genotype combinations [CD28+17(TT)/IFNG+874(AA)/TNFA-308(GG), CD28+17(TT)/IFN+847(AA)/PDCD1+7785(CT), and CD28 +17(TT)/IFNG+874(AA)/ICOS+1564(TT)] (P < 0.01, Monte Carlo simulation). We hypothesized that this two-genotype [CD28(TT) and IFNG(AA)] combination could have a major contribution to the observed association. To address this question, we analyzed the frequency of the CD28(TT), IFNG(AA) genotype combination in the three groups combined, and observed its increase in patients (P = 0.0011 by Fisher's exact test). The contribution of a third polymorphism did not reach statistical significance (P = 0.1). Further analysis suggested that gene-gene interaction between CD28 and IFNG might contribute to susceptibility to cervical cancer. Our results showed an epistatic effect between CD28 and IFNG genes in susceptibility to cervical cancer, a finding that might be relevant for a better understanding of the disease pathogenesis. In addition, the novel analytical approach herein proposed might be useful for increasing the statistical power of future genome-wide multi-locus studies.

Differential expression of new LTA splice variants upon lymphocyte activation

Lymphotoxin alpha (LTA) is a member of the TNF cytokine superfamily, produced principally by lymphocytes. It plays an important role in immune and inflammatory responses. Many TNF superfamily members have functionally important isoforms generated by alternative splicing but alternative splicing of LTA has never been studied. The known LTA protein is encoded by a transcript containing four exons. Here we report seven new LTA splice variants, three of them evolutionary conserved. We demonstrate their presence in cytoplasmic RNA suggesting that they could be translated into new LTA isoforms. We observed that their expression is differentially regulated upon activation of peripheral blood mononuclear cells and lymphocyte subpopulations (CD4+, CD8+, and CD19+). Our data suggest that the new LTA splice variants might play a role in the regulation of the immune response.

Microarrays for Cancer Diagnosis and Classification

Microarray analysis has yet to be widely accepted for diagnosis and classification of human cancers, despite the exponential increase in microarray studies reported in the literature. Among several methods available, a few refined approaches have evolved for the analysis of microarray data for cancer diagnosis. These include class comparison, class prediction and class discovery. Using as examples some of the major experimental contributions recently provided in the field of both hematological and solid tumors, we discuss the steps required to utilize microarray data to obtain general and reliable gene profiles that could be universally used in clinical laboratories. As we show, microarray technology is not only a new tool for the clinical lab but it can also improve the accuracy of the classical diagnostic techniques by suggesting novel tumor-specific markers. We then highlight the importance of publicly available microarray data and the development of their integrated analysis that may fulfill the promise that this new technology holds for cancer diagnosis and classification.

A novel strategy for defining haplotypes by selective depletion using restriction enzymes

Various single nucleotide polymorphisms (SNPs) have been investigated regarding association with gene expression levels or human diseases. Although different SNPs within one gene are frequently analyzed individually, it is highly probable that in the majority of the cases, a precise combination of SNP alleles, i.e., haplotype, determines a functional trait. Methods commonly used for haplotype determination, involving studies in families, cloning, or somatic cell hybrids, are expensive and time-consuming. We herein suggest a novel and simple strategy for haplotype determination, involving selective haplotype depletion with a restriction enzyme, followed by sequencing. We studied 11 LTA gene polymorphisms in 102 Brazilian individuals, and we applied this novel methodology for haplotyping 67 out of 70 LTA heterozygous individuals. We concluded that the method is rapid and efficient, and, as it includes only simple and widespread-used techniques, it could be used in most of the laboratories without further investment in equipments. The wider usage of haplotyping could be important to clarify contradictory results frequently observed among studies that focus on a single SNP.