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/ .

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-ß2 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.

Targeting TREM1 augments antitumor T cell immunity by inhibiting myeloid-derived suppressor cells and restraining anti-PD-1 resistance.

The triggering receptor expressed on myeloid cell 1 (TREM1) plays a critical role in development of chronic inflammatory disorders and the inflamed tumor microenvironment (TME) associated with most solid tumors. We examined whether loss of TREM1 signaling can abrogate the immunosuppressive TME and enhance cancer immunity. To investigate the therapeutic potential of TREM1 in cancer, we used mice deficient in Trem1 and developed a novel small molecule TREM1 inhibitor, VJDT. We demonstrated that genetic or pharmacological TREM1 silencing significantly delayed tumor growth in murine melanoma (B16F10) and fibrosarcoma (MCA205) models. Single-cell RNA-Seq combined with functional assays during TREM1 deficiency revealed decreased immunosuppressive capacity of myeloid-derived suppressor cells (MDSCs) accompanied by expansion in cytotoxic CD8+ T cells and increased PD-1 expression. Furthermore, TREM1 inhibition enhanced the antitumorigenic effect of anti-PD-1 treatment, in part, by limiting MDSC frequency and abrogating T cell exhaustion. In patient-derived melanoma xenograft tumors, treatment with VJDT downregulated key oncogenic signaling pathways involved in cell proliferation, migration, and survival. Our work highlights the role of TREM1 in cancer progression, both intrinsically expressed in cancer cells and extrinsically in the TME. Thus, targeting TREM1 to modify an immunosuppressive TME and improve efficacy of immune checkpoint therapy represents what we believe to be a promising therapeutic approach to cancer.

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.

Predicting cancer immunotherapy response from gut microbiomes using machine learning models.

Cancer immunotherapy has significantly improved patient survival. Yet, half of patients do not respond to immunotherapy. Gut microbiomes have been linked to clinical responsiveness of melanoma patients on immunotherapies; however, different taxa have been associated with response status with implicated taxa inconsistent between studies. We used a tumor-agnostic approach to find common gut microbiome features of response among immunotherapy patients with different advanced stage cancers. A combined meta-analysis of 16S rRNA gene sequencing data from our mixed tumor cohort and three published immunotherapy gut microbiome datasets from different melanoma patient cohorts found certain gut bacterial taxa correlated with immunotherapy response status regardless of tumor type. Using multivariate selbal analysis, we identified two separate groups of bacterial genera associated with responders versus non-responders. Statistical models of gut microbiome community features showed robust prediction accuracy of immunotherapy response in amplicon sequencing datasets and in cross-sequencing platform validation with shotgun metagenomic datasets. Results suggest baseline gut microbiome features may be predictive of clinical outcomes in oncology patients on immunotherapies, and some of these features may be generalizable across different tumor types, patient cohorts, and sequencing platforms. Findings demonstrate how machine learning models can reveal microbiome-immunotherapy interactions that may ultimately improve cancer patient outcomes.

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.

IL27 Signaling Serves as an Immunologic Checkpoint for Innate Cytotoxic Cells to Promote Hepatocellular Carcinoma.

Although inflammatory mechanisms driving hepatocellular carcinoma (HCC) have been proposed, the regulators of anticancer immunity in HCC remain poorly understood. We found that IL27 receptor (IL27R) signaling promotes HCC development in vivo. High IL27EBI3 cytokine or IL27RA expression correlated with poor prognosis for patients with HCC. Loss of IL27R suppressed HCC in vivo in two different models of hepatocarcinogenesis. Mechanistically, IL27R sig-naling within the tumor microenvironment restrains the cytotoxicity of innate cytotoxic lymphocytes. IL27R ablation enhanced their accumulation and activation, whereas depletion or functional impairment of innate cytotoxic cells abrogated the effect of IL27R disruption. Pharmacologic neutralization of IL27 signaling increased infiltration of innate cytotoxic lymphocytes with upregulated cytotoxic molecules and reduced HCC development. Our data reveal an unexpected role of IL27R signaling as an immunologic checkpoint regulating innate cytotoxic lymphocytes and promoting HCC of different etiologies, thus indicating a therapeutic potential for IL27 pathway blockade in HCC. SIGNIFICANCE: HCC, the most common form of liver cancer, is characterized by a poor survival rate and limited treatment options. The discovery of a novel IL27-dependent mechanism controlling anticancer cytotoxic immune response will pave the road for new treatment options for this devastating disease. This article is highlighted in the In This Issue feature, p. 1825.

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.

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.

Distinct contributions of cathelin-related antimicrobial peptide (CRAMP) derived from epithelial cells and macrophages to colon mucosal homeostasis.

The cathelin-related antimicrobial peptide CRAMP protects the mouse colon from inflammation, inflammation-associated carcinogenesis, and disrupted microbiome balance, as shown in systemic Cnlp-/- mice (also known as Camp-/- mice). However, the mechanistic basis for the role and the cellular source of CRAMP in colon pathophysiology are ill defined. This study, using either epithelial or myeloid conditional Cnlp-/- mice, demonstrated that epithelial cell-derived CRAMP played a major role in supporting normal development of colon crypts, mucus production, and repair of injured mucosa. On the other hand, myeloid cell-derived CRAMP potently supported colon epithelial resistance to bacterial invasion during acute inflammation with exacerbated mucosal damage and higher rate of mouse mortality. Therefore, a well concerted cooperation of epithelial- and myeloid-derived CRAMP is essential for colon mucosal homeostasis. © 2020 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

The Antimicrobial Peptide CRAMP Is Essential for Colon Homeostasis by Maintaining Microbiota Balance.

Commensal bacteria are critical for physiological functions in the gut, and dysbiosis in the gut may cause diseases. In this article, we report that mice deficient in cathelin-related antimicrobial peptide (CRAMP) were defective in the development of colon mucosa and highly sensitive to dextran sulfate sodium (DSS)-elicited colitis, as well as azoxymethane-mediated carcinogenesis. Pretreatment of CRAMP-/- mice with antibiotics markedly reduced the severity of DSS-induced colitis, suggesting CRAMP as a limiting factor on dysbiosis in the colon. This was supported by observations that wild-type (WT) mice cohoused with CRAMP-/- mice became highly sensitive to DSS-induced colitis, and the composition of fecal microbiota was skewed by CRAMP deficiency. In particular, several bacterial species that are typically found in oral microbiota, such as Mogibacterium neglectum, Desulfovibrio piger, and Desulfomicrobium orale, were increased in feces of CRAMP-/- mice and were transferred to WT mice during cohousing. When littermates of CRAMP+/- parents were examined, the composition of the fecal microbiota of WT pups and heterozygous parents was similar. In contrast, although the difference in fecal microbiota between CRAMP-/- and WT pups was small early on after weaning and single mouse housing, there was an increasing divergence with prolonged single housing. These results indicate that CRAMP is critical in maintaining colon microbiota balance and supports mucosal homeostasis, anti-inflammatory responses, and protection from carcinogenesis.

Interleukin-1 and interferon-γ orchestrate ß-glucan-activated human dendritic cell programming via IκB-ζ modulation.

Recognition of microbial components via innate receptors including the C-type lectin receptor Dectin-1, together with the inflammatory environment, programs dendritic cells (DCs) to orchestrate the magnitude and type of adaptive immune responses. The exposure to ß-glucan, a known Dectin-1 agonist and component of fungi, yeasts, and certain immune support supplements, activates DCs to induce T helper (Th)17 cells that are essential against fungal pathogens and extracellular bacteria but may trigger inflammatory pathology or autoimmune diseases. However, the exact mechanisms of DC programming by ß-glucan have not yet been fully elucidated. Using a gene expression/perturbation approach, we demonstrate that in human DCs ß-glucan transcriptionally activates via an interleukin (IL)-1- and inflammasome-mediated positive feedback late-induced genes that bridge innate and adaptive immunity. We report that in addition to its known ability to directly prime T cells toward the Th17 lineage, IL-1 by promoting the transcriptional cofactor inhibitor of κB-ζ (IκB-ζ) also programs ß-glucan-exposed DCs to express cell adhesion and migration mediators, antimicrobial molecules, and Th17-polarizing factors. Interferon (IFN)-γ interferes with the IL-1/IκB-ζ axis in ß-glucan-activated DCs and promotes T cell-mediated immune responses with increased release of IFN-γ and IL-22, and diminished production of IL-17. Thus, our results identify IL-1 and IFN-γ as regulators of DC programming by ß-glucan. These molecular networks provide new insights into the regulation of the Th17 response as well as new targets for the modulation of immune responses to ß-glucan-containing microorganisms.

Intraluminal containment of commensal outgrowth in the gut during infection-induced dysbiosis.

Shifts in commensal microbiota composition are emerging as a hallmark of gastrointestinal inflammation. In particular, outgrowth of γ-proteobacteria has been linked to the etiology of inflammatory bowel disease and the pathologic consequences of infections. Here we show that following acute Toxoplasma gondii gastrointestinal infection of mice, control of commensal outgrowth is a highly coordinated process involving both the host response and microbial signals. Notably, neutrophil emigration to the intestinal lumen results in the generation of organized intraluminal structures that encapsulate commensals and limit their contact with the epithelium. Formation of these luminal casts depends on the high-affinity N-formyl peptide receptor, Fpr1. Consequently, after infection, mice deficient in Fpr1 display increased microbial translocation, poor commensal containment, and increased mortality. Altogether, our study describes a mechanism by which the host rapidly contains commensal pathobiont outgrowth during infection. Further, these results reveal Fpr1 as a major mediator of host commensal interaction during dysbiosis.

Estimation of low frequency antigen-presenting cells with a novel RELISPOT assay.

Adequate presentation of self and foreign antigens is a key factor for efficient T-cell immunosurveillance against pathogens and tumors. Cells presenting foreign antigens usually comprise a rare population and are difficult to detect even at the peak of infection. Here we demonstrate a CD8(+) T-cell-based approach that allows detection of specific antigen-presenting cells (APC) at a frequency of less than 0.0005%. When T cells are in excess, they form rosettes with rare APCs, which appear as single spots in an IFN-gamma ELISPOT assay. Using this RELISPOT (Rosette ELISPOT) method we demonstrate the dynamic interplay between CD8 T cells and professional and non-professional APCs following virus challenge.