Pan-cancer analyses reveal cancer-type-specific fungal ecologies and bacteriome interactions.

Cancer-microbe associations have been explored for centuries, but cancer-associated fungi have rarely been examined. Here, we comprehensively characterize the cancer mycobiome within 17,401 patient tissue, blood, and plasma samples across 35 cancer types in four independent cohorts. We report fungal DNA and cells at low abundances across many major human cancers, with differences in community compositions that differ among cancer types, even when accounting for technical background. Fungal histological staining of tissue microarrays supported intratumoral presence and frequent spatial association with cancer cells and macrophages. Comparing intratumoral fungal communities with matched bacteriomes and immunomes revealed co-occurring bi-domain ecologies, often with permissive, rather than competitive, microenvironments and distinct immune responses. Clinically focused assessments suggested prognostic and diagnostic capacities of the tissue and plasma mycobiomes, even in stage I cancers, and synergistic predictive performance with bacteriomes.

FXR Regulates Intestinal Cancer Stem Cell Proliferation.

Increased levels of intestinal bile acids (BAs) are a risk factor for colorectal cancer (CRC). Here, we show that the convergence of dietary factors (high-fat diet) and dysregulated WNT signaling (APC mutation) alters BA profiles to drive malignant transformations in Lgr5-expressing (Lgr5+) cancer stem cells and promote an adenoma-to-adenocarcinoma progression. Mechanistically, we show that BAs that antagonize intestinal farnesoid X receptor (FXR) function, including tauro-ß-muricholic acid (T-ßMCA) and deoxycholic acid (DCA), induce proliferation and DNA damage in Lgr5+ cells. Conversely, selective activation of intestinal FXR can restrict abnormal Lgr5+ cell growth and curtail CRC progression. This unexpected role for FXR in coordinating intestinal self-renewal with BA levels implicates FXR as a potential therapeutic target for CRC.

A gut-derived metabolite alters brain activity and anxiety behaviour in mice.

Integration of sensory and molecular inputs from the environment shapes animal behaviour. A major site of exposure to environmental molecules is the gastrointestinal tract, in which dietary components are chemically transformed by the microbiota1 and gut-derived metabolites are disseminated to all organs, including the brain2. In mice, the gut microbiota impacts behaviour3, modulates neurotransmitter production in the gut and brain4,5, and influences brain development and myelination patterns6,7. The mechanisms that mediate the gut-brain interactions remain poorly defined, although they broadly involve humoral or neuronal connections. We previously reported that the levels of the microbial metabolite 4-ethylphenyl sulfate (4EPS) were increased in a mouse model of atypical neurodevelopment8. Here we identified biosynthetic genes from the gut microbiome that mediate the conversion of dietary tyrosine to 4-ethylphenol (4EP), and bioengineered gut bacteria to selectively produce 4EPS in mice. 4EPS entered the brain and was associated with changes in region-specific activity and functional connectivity. Gene expression signatures revealed altered oligodendrocyte function in the brain, and 4EPS impaired oligodendrocyte maturation in mice and decreased oligodendrocyte-neuron interactions in ex vivo brain cultures. Mice colonized with 4EP-producing bacteria exhibited reduced myelination of neuronal axons. Altered myelination dynamics in the brain have been associated with behavioural outcomes7,9-14. Accordingly, we observed that mice exposed to 4EPS displayed anxiety-like behaviours, and pharmacological treatments that promote oligodendrocyte differentiation prevented the behavioural effects of 4EPS. These findings reveal that a gut-derived molecule influences complex behaviours in mice through effects on oligodendrocyte function and myelin patterning in the brain.

Microbiome analyses of blood and tissues suggest cancer diagnostic approach.

Systematic characterization of the cancer microbiome provides the opportunity to develop techniques that exploit non-human, microorganism-derived molecules in the diagnosis of a major human disease. Following recent demonstrations that some types of cancer show substantial microbial contributions1-10, we re-examined whole-genome and whole-transcriptome sequencing studies in The Cancer Genome Atlas11 (TCGA) of 33 types of cancer from treatment-naive patients (a total of 18,116 samples) for microbial reads, and found unique microbial signatures in tissue and blood within and between most major types of cancer. These TCGA blood signatures remained predictive when applied to patients with stage Ia-IIc cancer and cancers lacking any genomic alterations currently measured on two commercial-grade cell-free tumour DNA platforms, despite the use of very stringent decontamination analyses that discarded up to 92.3% of total sequence data. In addition, we could discriminate among samples from healthy, cancer-free individuals (n = 69) and those from patients with multiple types of cancer (prostate, lung, and melanoma; 100 samples in total) solely using plasma-derived, cell-free microbial nucleic acids. This potential microbiome-based oncology diagnostic tool warrants further exploration.

Tankyrases inhibit innate antiviral response by PARylating VISA/MAVS and priming it for RNF146-mediated ubiquitination and degradation.

During viral infection, sensing of viral RNA by retinoic acid-inducible gene-I-like receptors (RLRs) initiates an antiviral innate immune response, which is mediated by the mitochondrial adaptor protein VISA (virus-induced signal adaptor; also known as mitochondrial antiviral signaling protein [MAVS]). VISA is regulated by various posttranslational modifications (PTMs), such as polyubiquitination, phosphorylation, O-linked ß-d-N-acetylglucosaminylation (O-GlcNAcylation), and monomethylation. However, whether other forms of PTMs regulate VISA-mediated innate immune signaling remains elusive. Here, we report that Poly(ADP-ribosyl)ation (PARylation) is a PTM of VISA, which attenuates innate immune response to RNA viruses. Using a biochemical purification approach, we identified tankyrase 1 (TNKS1) as a VISA-associated protein. Viral infection led to the induction of TNKS1 and its homolog TNKS2, which translocated from cytosol to mitochondria and interacted with VISA. TNKS1 and TNKS2 catalyze the PARylation of VISA at Glu137 residue, thereby priming it for K48-linked polyubiquitination by the E3 ligase Ring figure protein 146 (RNF146) and subsequent degradation. Consistently, TNKS1, TNKS2, or RNF146 deficiency increased the RNA virus-triggered induction of downstream effector genes and impaired the replication of the virus. Moreover, TNKS1- or TNKS2-deficient mice produced higher levels of type I interferons (IFNs) and proinflammatory cytokines after virus infection and markedly reduced virus loads in the brains and lungs. Together, our findings uncover an essential role of PARylation of VISA in virus-triggered innate immune signaling, which represents a mechanism to avoid excessive harmful immune response.

Efficient computation of Faith's phylogenetic diversity with applications in characterizing microbiomes.

The number of publicly available microbiome samples is continually growing. As data set size increases, bottlenecks arise in standard analytical pipelines. Faith's phylogenetic diversity (Faith's PD) is a highly utilized phylogenetic alpha diversity metric that has thus far failed to effectively scale to trees with millions of vertices. Stacked Faith's phylogenetic diversity (SFPhD) enables calculation of this widely adopted diversity metric at a much larger scale by implementing a computationally efficient algorithm. The algorithm reduces the amount of computational resources required, resulting in more accessible software with a reduced carbon footprint, as compared to previous approaches. The new algorithm produces identical results to the previous method. We further demonstrate that the phylogenetic aspect of Faith's PD provides increased power in detecting diversity differences between younger and older populations in the FINRISK study's metagenomic data.

High-accuracy long-read amplicon sequences using unique molecular identifiers with Nanopore or PacBio sequencing.

High-throughput amplicon sequencing of large genomic regions remains challenging for short-read technologies. Here, we report a high-throughput amplicon sequencing approach combining unique molecular identifiers (UMIs) with Oxford Nanopore Technologies (ONT) or Pacific Biosciences circular consensus sequencing, yielding high-accuracy single-molecule consensus sequences of large genomic regions. We applied our approach to sequence ribosomal RNA operon amplicons (~4,500 bp) and genomic sequences (>10,000 bp) of reference microbial communities in which we observed a chimera rate <0.02%. To reach a mean UMI consensus error rate <0.01%, a UMI read coverage of 15× (ONT R10.3), 25× (ONT R9.4.1) and 3× (Pacific Biosciences circular consensus sequencing) is needed, which provides a mean error rate of 0.0042%, 0.0041% and 0.0007%, respectively.

Challenges in benchmarking metagenomic profilers.

Accurate microbial identification and abundance estimation are crucial for metagenomics analysis. Various methods for classification of metagenomic data and estimation of taxonomic profiles, broadly referred to as metagenomic profilers, have been developed. Nevertheless, benchmarking of metagenomic profilers remains challenging because some tools are designed to report relative sequence abundance while others report relative taxonomic abundance. Here we show how misleading conclusions can be drawn by neglecting this distinction between relative abundance types when benchmarking metagenomic profilers. Moreover, we show compelling evidence that interchanging sequence abundance and taxonomic abundance will influence both per-sample summary statistics and cross-sample comparisons. We suggest that the microbiome research community pay attention to potentially misleading biological conclusions arising from this issue when benchmarking metagenomic profilers, by carefully considering the type of abundance data that were analyzed and interpreted and clearly stating the strategy used for metagenomic profiling.

MicroRNA-200c-targeted contactin 1 facilitates the replication of influenza A virus by accelerating the degradation of MAVS.

Influenza A viruses (IAVs) continuously challenge the poultry industry and human health. Elucidation of the host factors that modulate the IAV lifecycle is vital for developing antiviral drugs and vaccines. In this study, we infected A549 cells with IAVs and found that host protein contactin-1 (CNTN1), a member of the immunoglobulin superfamily, enhanced viral replication. Bioinformatic prediction and experimental validation indicated that the expression of CNTN1 was reduced by microRNA-200c (miR-200c) through directly targeting. We further showed that CNTN1-modulated viral replication in A549 cells is dependent on type I interferon signaling. Co-immunoprecipitation experiments revealed that CNTN1 specifically interacts with MAVS and promotes its proteasomal degradation by removing its K63-linked ubiquitination. Moreover, we discovered that the deubiquitinase USP25 is recruited by CNTN1 to catalyze the deubiquitination of K63-linked MAVS. Consequently, the CNTN1-induced degradation cascade of MAVS blocked RIG-I-MAVS-mediated interferon signaling, leading to enhanced viral replication. Taken together, our data reveal novel roles of CNTN1 in the type I interferon pathway and regulatory mechanism of IAV replication.

DEPP: Deep Learning Enables Extending Species Trees using Single Genes.

Placing new sequences onto reference phylogenies is increasingly used for analyzing environmental samples, especially microbiomes. Existing placement methods assume that query sequences have evolved under specific models directly on the reference phylogeny. For example, they assume single-gene data (e.g., 16S rRNA amplicons) have evolved under the GTR model on a gene tree. Placement, however, often has a more ambitious goal: extending a (genome-wide) species tree given data from individual genes without knowing the evolutionary model. Addressing this challenging problem requires new directions. Here, we introduce Deep-learning Enabled Phylogenetic Placement (DEPP), an algorithm that learns to extend species trees using single genes without prespecified models. In simulations and on real data, we show that DEPP can match the accuracy of model-based methods without any prior knowledge of the model. We also show that DEPP can update the multilocus microbial tree-of-life with single genes with high accuracy. We further demonstrate that DEPP can combine 16S and metagenomic data onto a single tree, enabling community structure analyses that take advantage of both sources of data. [Deep learning; gene tree discordance; metagenomics; microbiome analyses; neural networks; phylogenetic placement.].

The gut microbiome is a significant risk factor for future chronic lung disease.

BACKGROUND: The gut-lung axis is generally recognized, but there are few large studies of the gut microbiome and incident respiratory disease in adults. OBJECTIVE: We sought to investigate the association and predictive capacity of the gut microbiome for incident asthma and chronic obstructive pulmonary disease (COPD). METHODS: Shallow metagenomic sequencing was performed for stool samples from a prospective, population-based cohort (FINRISK02; N = 7115 adults) with linked national administrative health register-derived classifications for incident asthma and COPD up to 15 years after baseline. Generalized linear models and Cox regressions were used to assess associations of microbial taxa and diversity with disease occurrence. Predictive models were constructed using machine learning with extreme gradient boosting. Models considered taxa abundances individually and in combination with other risk factors, including sex, age, body mass index, and smoking status. RESULTS: A total of 695 and 392 statistically significant associations were found between baseline taxonomic groups and incident asthma and COPD, respectively. Gradient boosting decision trees of baseline gut microbiome abundance predicted incident asthma and COPD in the validation data sets with mean area under the curves of 0.608 and 0.780, respectively. Cox analysis showed that the baseline gut microbiome achieved higher predictive performance than individual conventional risk factors, with C-indices of 0.623 for asthma and 0.817 for COPD. The integration of the gut microbiome and conventional risk factors further improved prediction capacities. CONCLUSIONS: The gut microbiome is a significant risk factor for incident asthma and incident COPD and is largely independent of conventional risk factors.

Specific Monoclonal Antibodies Targeting Unique HA Epitopes Block H7N9 Influenza A Viral Replication.

The H7N9 subtype influenza A viruses pose a serious threat to public health, and there is still a lack of vaccines or drugs for humans against H7N9 influenza viruses. In this study, we screened two monoclonal antibodies (MAbs), 4H1E8 and 7H9A6, that specifically recognize the hemagglutinin (HA) protein of H7N9 influenza virus and display highly neutralizing activity against H7N9 virus. The epitopes recognized by two MAbs are nearly all conserved within all known H7 subtypes. Characteristic identification showed that two MAbs have high avidity for the HA protein but no hemagglutinin inhibition activity or antibody-dependent cellular cytotoxicity. Mechanistically, the 4H1E8 and 7H9A6 antibodies inhibit the pH-dependent conformational change of HA and block the HA-mediated membrane fusion. More importantly, 4H1E8 and 7H9A6 exhibit promising prophylactic and therapeutic effects against lethal challenge with H7N9 virus. Moreover, 4H1E8- and 7H9A6-treated mice displayed inhibition of pulmonary viral replication and reduced lung lesions after viral challenge. Together, these findings indicate that antibodies 4H1E8 and 7H9A6 recognize unique epitopes in the HA protein and possess the neutralizing activity and protective efficacy against the H7N9 influenza A viruses. IMPORTANCE In 2013, H7N9 influenza viruses appeared in China and other countries resulting in more than 1,500 individual infections or death. There are still limited studies on vaccines or drugs for humans against H7N9 influenza viruses. Alternative approaches against H7N9 virus infection need to be developed. Here, we identified two monoclonal antibodies (4H1E8 and 7H9A6) that possess neutralizing activity by blocking the pH-dependent HA-mediated membrane fusion. Additionally, the two monoclonal antibodies protect mice against the H7N9 virus challenge prophylactically or therapeutically. Therefore, our study demonstrates that 4H1E8 and 7H9A6 could be used for the prevention and treatment of the H7N9 influenza virus, and the conserved epitopes we identified may contribute to the development of a broad H7N9 vaccine and provide insights into unique antiviral approaches.

The PB1 protein of influenza A virus inhibits the innate immune response by targeting MAVS for NBR1-mediated selective autophagic degradation.

Influenza A virus (IAV) has evolved various strategies to counteract the innate immune response using different viral proteins. However, the mechanism is not fully elucidated. In this study, we identified the PB1 protein of H7N9 virus as a new negative regulator of virus- or poly(I:C)-stimulated IFN induction and specifically interacted with and destabilized MAVS. A subsequent study revealed that PB1 promoted E3 ligase RNF5 to catalyze K27-linked polyubiquitination of MAVS at Lys362 and Lys461. Moreover, we found that PB1 preferentially associated with a selective autophagic receptor neighbor of BRCA1 (NBR1) that recognizes ubiquitinated MAVS and delivers it to autophagosomes for degradation. The degradation cascade mediated by PB1 facilitates H7N9 virus infection by blocking the RIG-I-MAVS-mediated innate signaling pathway. Taken together, these data uncover a negative regulatory mechanism involving the PB1-RNF5-MAVS-NBR1 axis and provide insights into an evasion strategy employed by influenza virus that involves selective autophagy and innate signaling pathways.

Chemically informed analyses of metabolomics mass spectrometry data with Qemistree.

Untargeted mass spectrometry is employed to detect small molecules in complex biospecimens, generating data that are difficult to interpret. We developed Qemistree, a data exploration strategy based on the hierarchical organization of molecular fingerprints predicted from fragmentation spectra. Qemistree allows mass spectrometry data to be represented in the context of sample metadata and chemical ontologies. By expressing molecular relationships as a tree, we can apply ecological tools that are designed to analyze and visualize the relatedness of DNA sequences to metabolomics data. Here we demonstrate the use of tree-guided data exploration tools to compare metabolomics samples across different experimental conditions such as chromatographic shifts. Additionally, we leverage a tree representation to visualize chemical diversity in a heterogeneous collection of samples. The Qemistree software pipeline is freely available to the microbiome and metabolomics communities in the form of a QIIME2 plugin, and a global natural products social molecular networking workflow.

A communal catalogue reveals Earth's multiscale microbial diversity.

Our growing awareness of the microbial world's importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth's microbial diversity.

The Nucleoprotein of H7N9 Influenza Virus Positively Regulates TRAF3-Mediated Innate Signaling and Attenuates Viral Virulence in Mice.

H7N9 influenza A virus (IAV) is an emerged contagious pathogen that may cause severe human infections, even death. Understanding the precise cross talk between virus and host is vital for the development of effective vaccines and therapeutics. In the present study, we identified the nucleoprotein (NP) of H7N9 IAV as a positive regulator of RIG-I like receptor (RLR)-mediated signaling. Based on a loss-of-function strategy, we replaced H1N1 (mouse-adapted PR8 strain) NP with H7N9 NP, by using reverse genetics, and found that the replication and pathogenicity of recombinant PR8-H7N9NP (rPR8-H7N9NP) were significantly attenuated in cells and mice. Biochemical and cellular analyses revealed that H7N9 NP specifically interacts with tumor necrosis factor receptor (TNFR)-associated factor 3 (TRAF3) after viral infection. Subsequently, we identified a PXXQXS motif in the H7N9 NP that may be a determinant for the NP and TRAF3 interaction. Furthermore, H7N9 NP stabilized TRAF3 expression via competitively binding to TRAF3 with cellular inhibitor of apoptosis 2 (cIAP2), leading to the inhibition of the Lys48-linked polyubiquitination and degradation of TRAF3. Taken together, these data uncover a novel mechanism by which the NP of H7N9 IAV positively regulates TRAF3-mediated type I interferon signaling. Our findings provide insights into virus and host survival strategies that involve a specific viral protein that modulates an appropriate immune response in hosts.IMPORTANCE The NS1, PB2, PA-X, and PB1-F2 proteins of influenza A virus (IAV) are known to employ various strategies to counteract and evade host defenses. However, the viral components responsible for the activation of innate immune signaling remain elusive. Here, we demonstrate for the first time that the NP of H7N9 IAV specifically associates with and stabilizes the important adaptor molecule TRAF3, which potentiates RLR-mediated type I interferon induction. Moreover, we reveal that this H7N9 NP protein prevents the interaction between TRAF3 and cIAP2 that mediates Lys48-linked polyubiquitination of TRAF3 for degradation. The current study revealed a novel mechanism by which H7N9 NP upregulates TRAF3-mediated type I interferon production, leading to attenuation of viral replication and pathogenicity in cells and mice. Our finding provides a possible explanation for virus and host commensalism via viral manipulation of the host immune system.

SHOGUN: a modular, accurate and scalable framework for microbiome quantification.

SUMMARY: The software pipeline SHOGUN profiles known taxonomic and gene abundances of short-read shotgun metagenomics sequencing data. The pipeline is scalable, modular and flexible. Data analysis and transformation steps can be run individually or together in an automated workflow. Users can easily create new reference databases and can select one of three DNA alignment tools, ranging from ultra-fast low-RAM k-mer-based database search to fully exhaustive gapped DNA alignment, to best fit their analysis needs and computational resources. The pipeline includes an implementation of a published method for taxonomy assignment disambiguation with empirical Bayesian redistribution. The software is installable via the conda resource management framework, has plugins for the QIIME2 and QIITA packages and produces both taxonomy and gene abundance profile tables with a single command, thus promoting convenient and reproducible metagenomics research. AVAILABILITY AND IMPLEMENTATION: https://github.com/knights-lab/SHOGUN.

USP49 negatively regulates cellular antiviral responses via deconjugating K63-linked ubiquitination of MITA.

Mediator of IRF3 activation (MITA, also known as STING and ERIS) is an essential adaptor protein for cytoplasmic DNA-triggered signaling and involved in innate immune responses, autoimmunity and tumorigenesis. The activity of MITA is critically regulated by ubiquitination and deubiquitination. Here, we report that USP49 interacts with and deubiquitinates MITA after HSV-1 infection, thereby turning down cellular antiviral responses. Knockdown or knockout of USP49 potentiated HSV-1-, cytoplasmic DNA- or cGAMP-induced production of type I interferons (IFNs) and proinflammatory cytokines and impairs HSV-1 replication. Consistently, Usp49-/- mice exhibit resistance to lethal HSV-1 infection and attenuated HSV-1 replication compared to Usp49+/+ mice. Mechanistically, USP49 removes K63-linked ubiquitin chains from MITA after HSV-1 infection which inhibits the aggregation of MITA and the subsequent recruitment of TBK1 to the signaling complex. These findings suggest a critical role of USP49 in terminating innate antiviral responses and provide insights into the complex regulatory mechanisms of MITA activation.

Exploring the Composition and Functions of Plastic Microbiome Using Whole-Genome Sequencing.

Besides the ecotoxicological consequences of microplastics and associated chemicals, the association of microbes on plastics has greater environmental implications as microplastics may select for unique microbiome participating in environmentally significant functions. Despite this, the functional potential of the microbiome associated with different types of plastics is understudied. Here, we investigate the interaction between plastic and marine biofilm-forming microorganisms through a whole-genome sequencing approach on four types of microplastics incubated in the marine environment. Taxonomic analysis suggested that the microplastic surfaces exhibit unique microbial profiles and niche partitioning among the substrates. In particular, the abundance of Vibrio alginolyticus and Vibrio campbellii suggested that microplastic pollution may pose a potential risk to the marine food chain and negatively impact aquaculture industries. Microbial genera involved in xenobiotic compound degradation, carbon cycling, and genes associated with the type IV secretion system, conjugal transfer protein TraG, plant-pathogen interaction, CusA/CzcA family heavy metal efflux transfer proteins, and TolC family proteins were significantly enriched on all the substrates, indicating the variety of processes operated by the plastic-microbiome. The present study gives a detailed characterization of the rapidly altering microbial composition and gene pools on plastics and adds new knowledge surrounding the environmental ramifications of marine plastic pollution.