Strain-level fitness in the gut microbiome is an emergent property of glycans and a single metabolite.

The human gut microbiota resides within a diverse chemical environment challenging our ability to understand the forces shaping this ecosystem. Here, we reveal that fitness of the Bacteroidales, the dominant order of bacteria in the human gut, is an emergent property of glycans and one specific metabolite, butyrate. Distinct sugars serve as strain-variable fitness switches activating context-dependent inhibitory functions of butyrate. Differential fitness effects of butyrate within the Bacteroides are mediated by species-level variation in Acyl-CoA thioesterase activity and nucleotide polymorphisms regulating an Acyl-CoA transferase. Using in vivo multi-omic profiles, we demonstrate Bacteroides fitness in the human gut is associated together, but not independently, with Acyl-CoA transferase expression and butyrate. Our data reveal that each strain of the Bacteroides exists within a unique fitness landscape based on the interaction of chemical components unpredictable by the effect of each part alone mediated by flexibility in the core genome.

Discovery of bioactive microbial gene products in inflammatory bowel disease.

Microbial communities and their associated bioactive compounds1-3 are often disrupted in conditions such as the inflammatory bowel diseases (IBD)4. However, even in well-characterized environments (for example, the human gastrointestinal tract), more than one-third of microbial proteins are uncharacterized and often expected to be bioactive5-7. Here we systematically identified more than 340,000 protein families as potentially bioactive with respect to gut inflammation during IBD, about half of which have not to our knowledge been functionally characterized previously on the basis of homology or experiment. To validate prioritized microbial proteins, we used a combination of metagenomics, metatranscriptomics and metaproteomics to provide evidence of bioactivity for a subset of proteins that are involved in host and microbial cell-cell communication in the microbiome; for example, proteins associated with adherence or invasion processes, and extracellular von Willebrand-like factors. Predictions from high-throughput data were validated using targeted experiments that revealed the differential immunogenicity of prioritized Enterobacteriaceae pilins and the contribution of homologues of von Willebrand factors to the formation of Bacteroides biofilms in a manner dependent on mucin levels. This methodology, which we term MetaWIBELE (workflow to identify novel bioactive elements in the microbiome), is generalizable to other environmental communities and human phenotypes. The prioritized results provide thousands of candidate microbial proteins that are likely to interact with the host immune system in IBD, thus expanding our understanding of potentially bioactive gene products in chronic disease states and offering a rational compendium of possible therapeutic compounds and targets.

Human gut bacteria produce ΤΗ17-modulating bile acid metabolites.

The microbiota modulates gut immune homeostasis. Bacteria influence the development and function of host immune cells, including T helper cells expressing interleukin-17A (TH17 cells). We previously reported that the bile acid metabolite 3-oxolithocholic acid (3-oxoLCA) inhibits TH17 cell differentiation1. Although it was suggested that gut-residing bacteria produce 3-oxoLCA, the identity of such bacteria was unknown, and it was unclear whether 3-oxoLCA and other immunomodulatory bile acids are associated with inflammatory pathologies in humans. Here we identify human gut bacteria and corresponding enzymes that convert the secondary bile acid lithocholic acid into 3-oxoLCA as well as the abundant gut metabolite isolithocholic acid (isoLCA). Similar to 3-oxoLCA, isoLCA suppressed TH17 cell differentiation by inhibiting retinoic acid receptor-related orphan nuclear receptor-γt, a key TH17-cell-promoting transcription factor. The levels of both 3-oxoLCA and isoLCA and the 3α-hydroxysteroid dehydrogenase genes that are required for their biosynthesis were significantly reduced in patients with inflammatory bowel disease. Moreover, the levels of these bile acids were inversely correlated with the expression of TH17-cell-associated genes. Overall, our data suggest that bacterially produced bile acids inhibit TH17 cell function, an activity that may be relevant to the pathophysiology of inflammatory disorders such as inflammatory bowel disease.

Integrated annotation prioritizes metabolites with bioactivity in inflammatory bowel disease.

Microbial biochemistry is central to the pathophysiology of inflammatory bowel diseases (IBD). Improved knowledge of microbial metabolites and their immunomodulatory roles is thus necessary for diagnosis and management. Here, we systematically analyzed the chemical, ecological, and epidemiological properties of ~82k metabolic features in 546 Integrative Human Microbiome Project (iHMP/HMP2) metabolomes, using a newly developed methodology for bioactive compound prioritization from microbial communities. This suggested >1000 metabolic features as potentially bioactive in IBD and associated ~43% of prevalent, unannotated features with at least one well-characterized metabolite, thereby providing initial information for further characterization of a significant portion of the fecal metabolome. Prioritized features included known IBD-linked chemical families such as bile acids and short-chain fatty acids, and less-explored bilirubin, polyamine, and vitamin derivatives, and other microbial products. One of these, nicotinamide riboside, reduced colitis scores in DSS-treated mice. The method, MACARRoN, is generalizable with the potential to improve microbial community characterization and provide therapeutic candidates.

Integrated genomic analyses of cutaneous T-cell lymphomas reveal the molecular bases for disease heterogeneity.

Cutaneous T-cell lymphomas (CTCLs) are a clinically heterogeneous collection of lymphomas of the skin-homing T cell. To identify molecular drivers of disease phenotypes, we assembled representative samples of CTCLs from patients with diverse disease subtypes and stages. Via DNA/RNA-sequencing, immunophenotyping, and ex vivo functional assays, we identified the landscape of putative driver genes, elucidated genetic relationships between CTCLs across disease stages, and inferred molecular subtypes in patients with stage-matched leukemic disease. Collectively, our analysis identified 86 putative driver genes, including 19 genes not previously implicated in this disease. Two mutations have never been described in any cancer. Functionally, multiple mutations augment T-cell receptor-dependent proliferation, highlighting the importance of this pathway in lymphomagenesis. To identify putative genetic causes of disease heterogeneity, we examined the distribution of driver genes across clinical cohorts. There are broad similarities across disease stages. Many driver genes are shared by mycosis fungoides (MF) and Sezary syndrome (SS). However, there are significantly more structural variants in leukemic disease, leading to highly recurrent deletions of putative tumor suppressors that are uncommon in early-stage skin-centered MF. For example, TP53 is deleted in 7% and 87% of MF and SS, respectively. In both human and mouse samples, PD1 mutations drive aggressive behavior. PD1 wild-type lymphomas show features of T-cell exhaustion. PD1 deletions are sufficient to reverse the exhaustion phenotype, promote a FOXM1-driven transcriptional signature, and predict significantly worse survival. Collectively, our findings clarify CTCL genetics and provide novel insights into pathways that drive diverse disease phenotypes.

Statistical approaches for differential expression analysis in metatranscriptomics.

MOTIVATION: Metatranscriptomics (MTX) has become an increasingly practical way to profile the functional activity of microbial communities in situ. However, MTX remains underutilized due to experimental and computational limitations. The latter are complicated by non-independent changes in both RNA transcript levels and their underlying genomic DNA copies (as microbes simultaneously change their overall abundance in the population and regulate individual transcripts), genetic plasticity (as whole loci are frequently gained and lost in microbial lineages) and measurement compositionality and zero-inflation. Here, we present a systematic evaluation of and recommendations for differential expression (DE) analysis in MTX. RESULTS: We designed and assessed six statistical models for DE discovery in MTX that incorporate different combinations of DNA and RNA normalization and assumptions about the underlying changes of gene copies or species abundance within communities. We evaluated these models on multiple simulated and real multi-omic datasets. Models adjusting transcripts relative to their encoding gene copies as a covariate were significantly more accurate in identifying DE from MTX in both simulated and real datasets. Moreover, we show that when paired DNA measurements (metagenomic data) are not available, models normalizing MTX measurements within-species while also adjusting for total-species RNA balance sensitivity, specificity and interpretability of DE detection, as does filtering likely technical zeros. The efficiency and accuracy of these models pave the way for more effective MTX-based DE discovery in microbial communities. AVAILABILITY AND IMPLEMENTATION: The analysis code and synthetic datasets used in this evaluation are available online at http://huttenhower.sph.harvard.edu/mtx2021. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Multivariable association discovery in population-scale meta-omics studies.

It is challenging to associate features such as human health outcomes, diet, environmental conditions, or other metadata to microbial community measurements, due in part to their quantitative properties. Microbiome multi-omics are typically noisy, sparse (zero-inflated), high-dimensional, extremely non-normal, and often in the form of count or compositional measurements. Here we introduce an optimized combination of novel and established methodology to assess multivariable association of microbial community features with complex metadata in population-scale observational studies. Our approach, MaAsLin 2 (Microbiome Multivariable Associations with Linear Models), uses generalized linear and mixed models to accommodate a wide variety of modern epidemiological studies, including cross-sectional and longitudinal designs, as well as a variety of data types (e.g., counts and relative abundances) with or without covariates and repeated measurements. To construct this method, we conducted a large-scale evaluation of a broad range of scenarios under which straightforward identification of meta-omics associations can be challenging. These simulation studies reveal that MaAsLin 2's linear model preserves statistical power in the presence of repeated measures and multiple covariates, while accounting for the nuances of meta-omics features and controlling false discovery. We also applied MaAsLin 2 to a microbial multi-omics dataset from the Integrative Human Microbiome (HMP2) project which, in addition to reproducing established results, revealed a unique, integrated landscape of inflammatory bowel diseases (IBD) across multiple time points and omics profiles.

Biomimetic Modification and In Vivo Safety Assessment of Superparamagnetic Iron Oxide Nanoparticles.

The efficacy of superparamagnetic iron oxide nanoparticles (SPIONs) for biomedical applications depends on the magnetic properties, long time stability in biological fluids, and specific targeting capacity. The properties of SPIONs were generally improved by surface modification, but common modification technologies were usually conducted with multi-steps under rigid conditions. In this work, a facile and simple approach to synthesize functionalized SPIONs contrast agents was set up. First of all, SPIONs were prepared by an improved ultrasonic co-precipitation method. Then the surfaces of these SPIONs were modified biomimeticly by dopamine (DA) with strong adhesion. At last, the c(RGDyK), a biomolecule with the capacity of specific targeting capacity towards liver tumor cells, were coupled with DA on SPIONs via Mannich reaction. Thus the novel magnetic composite nanoparticles (abbreviated as c(RGDyK)-PDA-SPIONs) were successfully prepared. The as-synthesized nanoparticles were characterized by scanning electron microscope (SEM), dynamic light scattering, magnetic hysteresis loop measuring instrument. As a result, that the c(RGDyK)-PDA-SPIONs had an average size of about 50 nm and uniform distribution, and had superparamagnetic properties, good water dispersion stability. The acute toxicity test of the assynthesized c(RGDyK)-PDA-SPIONs to mice was also investigated. It was observed that LD50 of c(RGDyK)-PDA-SPIONs was 4.38 g/kg, with a 95% confidence interval ranging from 3.49 g/kg to 5.87 g/kg. These results indicated the novel c(RGDyK)-PDA-SPIONs had excellent biocompatibility, which was endowed with a potential capacity to serve as MRI contrast agents in diagnosis and treatment of the liver tumor.

Gene expression profiling analysis of locus coeruleus in idiopathic Parkinson's disease by bioinformatics.

This study aimed to explore the underlying molecular mechanisms of idiopathic Parkinson's disease (IPD) by bioinformatics analysis. Gene expression profile GSE34516 was downloaded from the Gene Expression Omnibus. Eight locus coeruleus post-mortem tissue samples derived from four IPD patients and four neurological healthy controls were used to identify the differentially expressed genes (DEGs) by paired t test. Based on the DEGs, principal components were analyzed. The Gene Ontology functional and Kyoto Encyclopedia of Genes and Genomes pathway analysis of the genome microarray data were then performed. Finally, protein-protein interaction (PPI) network of the DEGs was constructed. Total 261 DEGs including 195 up-regulated and 66 down-regulated DEGs were identified. Intracellular protein transport and RNA splicing via transesterification reactions were selected as the most two significantly enriched functions. Mismatch repair, N-glycan biosynthesis, spliceosome and nucleotide excision repair were the significantly enriched pathways. In the PPI network, CTSS, CD53, IGSF6, PTPRC and LAPTM5 were the hub nodes. Intracellular protein transport and RNA splicing via transesterification reactions were closely associated with IPD. The DEGs, such as CX3CR1, SLC5A7, CD53 and PTPRC may be the potential targets for IPD diagnosis and treatment.

Parotid metastasis of rare lung adenocarcinoma: A case report.

BACKGROUND: Lung cancer (LC) is the leading cause of malignancy-related deaths worldwide. The most common sites of metastasis include the nervous system, bone, liver, respiratory system, and adrenal glands. LC metastasis in the parotid gland is very rare, and its diagnosis presents a challenge. Here, we report a case of parotid metastasis in primary LC. CASE SUMMARY: The patient was a 74-year-old male who was discovered to have bilateral facial asymmetry inadvertently two years ago. The right earlobe was slightly swollen and without pain or numbness. Computed tomography (CT) examination showed bilateral lung space-occupying lesions. Pulmonary biopsy was performed and revealed adenocarcinoma (right-upper-lung nodule tissue). Positron emission tomography-CT examination showed: (1) Two hypermetabolic nodules in the right upper lobe of the lung, enlarged hypermetabolic lymph nodes in the right hilar and mediastinum, and malignant space-occupying lesion in the right upper lobe of the lung and possible metastasis to the right hilar and mediastinal lymph nodes; and (2) multiple hypermetabolic nodules in bilateral parotid glands. Parotid puncture biopsy was performed considering lung adenocarcinoma metastasis. Gene detection of lung biopsy specimens revealed an EGFR gene 21 exon L858R mutation. CONCLUSION: This case report highlights the challenging diagnosis of parotid metastasis in LC given its rare nature. Such lesions should be differentiated from primary tumors of the parotid gland. Simple radiological imaging is unreliable, and puncture biopsy is needed for final diagnosis of this condition.

Strain-specific gut microbial signatures in type 2 diabetes identified in a cross-cohort analysis of 8,117 metagenomes.

The association of gut microbial features with type 2 diabetes (T2D) has been inconsistent due in part to the complexity of this disease and variation in study design. Even in cases in which individual microbial species have been associated with T2D, mechanisms have been unable to be attributed to these associations based on specific microbial strains. We conducted a comprehensive study of the T2D microbiome, analyzing 8,117 shotgun metagenomes from 10 cohorts of individuals with T2D, prediabetes, and normoglycemic status in the United States, Europe, Israel and China. Dysbiosis in 19 phylogenetically diverse species was associated with T2D (false discovery rate < 0.10), for example, enriched Clostridium bolteae and depleted Butyrivibrio crossotus. These microorganisms also contributed to community-level functional changes potentially underlying T2D pathogenesis, for example, perturbations in glucose metabolism. Our study identifies within-species phylogenetic diversity for strains of 27 species that explain inter-individual differences in T2D risk, such as Eubacterium rectale. In some cases, these were explained by strain-specific gene carriage, including loci involved in various mechanisms of horizontal gene transfer and novel biological processes underlying metabolic risk, for example, quorum sensing. In summary, our study provides robust cross-cohort microbial signatures in a strain-resolved manner and offers new mechanistic insights into T2D.

RNA-based amplicon sequencing is ineffective in measuring metabolic activity in environmental microbial communities.

BACKGROUND: Characterization of microbial activity is essential to the understanding of the basic biology of microbial communities, as the function of a microbiome is defined by its biochemically active ("viable") community members. Current sequence-based technologies can rarely differentiate microbial activity, due to their inability to distinguish live and dead sourced DNA. As a result, our understanding of microbial community structures and the potential mechanisms of transmission between humans and our surrounding environments remains incomplete. As a potential solution, 16S rRNA transcript-based amplicon sequencing (16S-RNA-seq) has been proposed as a reliable methodology to characterize the active components of a microbiome, but its efficacy has not been evaluated systematically. Here, we present our work to benchmark RNA-based amplicon sequencing for activity assessment in synthetic and environmentally sourced microbial communities. RESULTS: In synthetic mixtures of living and heat-killed Escherichia coli and Streptococcus sanguinis, 16S-RNA-seq successfully reconstructed the active compositions of the communities. However, in the realistic environmental samples, no significant compositional differences were observed in RNA ("actively transcribed - active") vs. DNA ("whole" communities) spiked with E. coli controls, suggesting that this methodology is not appropriate for activity assessment in complex communities. The results were slightly different when validated in environmental samples of similar origins (i.e., from Boston subway systems), where samples were differentiated both by environment type as well as by library type, though compositional dissimilarities between DNA and RNA samples remained low (Bray-Curtis distance median: 0.34-0.49). To improve the interpretation of 16S-RNA-seq results, we compared our results with previous studies and found that 16S-RNA-seq suggests taxon-wise viability trends (i.e., specific taxa are universally more or less likely to be viable compared to others) in samples of similar origins. CONCLUSIONS: This study provides a comprehensive evaluation of 16S-RNA-seq for viability assessment in synthetic and complex microbial communities. The results found that while 16S-RNA-seq was able to semi-quantify microbial viability in relatively simple communities, it only suggests a taxon-dependent "relative" viability in realistic communities.  Video Abstract.

Gut microbial metabolism of 5-ASA diminishes its clinical efficacy in inflammatory bowel disease.

For decades, variability in clinical efficacy of the widely used inflammatory bowel disease (IBD) drug 5-aminosalicylic acid (5-ASA) has been attributed, in part, to its acetylation and inactivation by gut microbes. Identification of the responsible microbes and enzyme(s), however, has proved elusive. To uncover the source of this metabolism, we developed a multi-omics workflow combining gut microbiome metagenomics, metatranscriptomics and metabolomics from the longitudinal IBDMDB cohort of 132 controls and patients with IBD. This associated 12 previously uncharacterized microbial acetyltransferases with 5-ASA inactivation, belonging to two protein superfamilies: thiolases and acyl-CoA N-acyltransferases. In vitro characterization of representatives from both families confirmed the ability of these enzymes to acetylate 5-ASA. A cross-sectional analysis within the discovery cohort and subsequent prospective validation within the independent SPARC IBD cohort (n = 208) found three of these microbial thiolases and one acyl-CoA N-acyltransferase to be epidemiologically associated with an increased risk of treatment failure among 5-ASA users. Together, these data address a longstanding challenge in IBD management, outline a method for the discovery of previously uncharacterized gut microbial activities and advance the possibility of microbiome-based personalized medicine.

A biosynthetic pathway for the selective sulfonation of steroidal metabolites by human gut bacteria.

Members of the human gut microbiome enzymatically process many bioactive molecules in the gastrointestinal tract. Most gut bacterial modifications characterized so far are hydrolytic or reductive in nature. Here we report that abundant human gut bacteria from the phylum Bacteroidetes perform conjugative modifications by selectively sulfonating steroidal metabolites. While sulfonation is a ubiquitous biochemical modification, this activity has not yet been characterized in gut microbes. Using genetic and biochemical approaches, we identify a widespread biosynthetic gene cluster that encodes both a sulfotransferase (BtSULT, BT0416) and enzymes that synthesize the sulfonate donor adenosine 3'-phosphate-5'-phosphosulfate (PAPS), including an APS kinase (CysC, BT0413) and an ATP sulfurylase (CysD and CysN, BT0414-BT0415). BtSULT selectively sulfonates steroidal metabolites with a flat A/B ring fusion, including cholesterol. Germ-free mice monocolonized with Bacteroides thetaiotaomicron ΔBT0416 exhibited reduced gastrointestinal levels of cholesterol sulfate (Ch-S) compared with wild-type B. thetaiotaomicron-colonized mice. The presence of BtSULT and BtSULT homologues in bacteria inhibited leucocyte migration in vitro and in vivo, and abundances of cluster genes were significantly reduced in patients with inflammatory bowel disease. Together, these data provide a mechanism by which gut bacteria sulfonate steroidal metabolites and suggest that these compounds can modulate immune cell trafficking in the host.

Root-secreted bitter triterpene modulates the rhizosphere microbiota to improve plant fitness.

Underground microbial ecosystems have profound impacts on plant health1-5. Recently, essential roles have been shown for plant specialized metabolites in shaping the rhizosphere microbiome6-9. However, the potential mechanisms underlying the root-to-soil delivery of these metabolites remain to be elucidated10. Cucurbitacins, the characteristic bitter triterpenoids in cucurbit plants (such as melon and watermelon), are synthesized by operon-like gene clusters11. Here we report two Multidrug and Toxic Compound Extrusion (MATE) proteins involved in the transport of their respective cucurbitacins, a process co-regulated with cucurbitacin biosynthesis. We further show that the transport of cucurbitacin B from the roots of melon into the soil modulates the rhizosphere microbiome by selectively enriching for two bacterial genera, Enterobacter and Bacillus, and we demonstrate that this, in turn, leads to robust resistance against the soil-borne wilt fungal pathogen, Fusarium oxysporum. Our study offers insights into how transporters for specialized metabolites manipulate the rhizosphere microbiota and thereby affect crop fitness.

Metatranscriptomics for the Human Microbiome and Microbial Community Functional Profiling.

Shotgun metatranscriptomics (MTX) is an increasingly practical way to survey microbial community gene function and regulation at scale. This review begins by summarizing the motivations for community transcriptomics and the history of the field. We then explore the principles, best practices, and challenges of contemporary MTX workflows: beginning with laboratory methods for isolation and sequencing of community RNA, followed by informatics methods for quantifying RNA features, and finally statistical methods for detecting differential expression in a community context. In thesecond half of the review, we survey important biological findings from the MTX literature, drawing examples from the human microbiome, other (nonhuman) host-associated microbiomes, and the environment. Across these examples, MTX methods prove invaluable for probing microbe-microbe and host-microbe interactions, the dynamics of energy harvest and chemical cycling, and responses to environmental stresses. We conclude with a review of open challenges in the MTX field, including making assays and analyses more robust, accessible, and adaptable to new technologies; deciphering roles for millions of uncharacterized microbial transcripts; and solving applied problems such as biomarker discovery and development of microbial therapeutics.

Whole microbial community viability is not quantitatively reflected by propidium monoazide sequencing approach.

BACKGROUND: High-throughput sequencing provides a powerful window into the structural and functional profiling of microbial communities, but it is unable to characterize only the viable portion of microbial communities at scale. There is as yet not one best solution to this problem. Previous studies have established viability assessments using propidium monoazide (PMA) treatment coupled with downstream molecular profiling (e.g., qPCR or sequencing). While these studies have met with moderate success, most of them focused on the resulting "viable" communities without systematic evaluations of the technique. Here, we present our work to rigorously benchmark "PMA-seq" (PMA treatment followed by 16S rRNA gene amplicon sequencing) for viability assessment in synthetic and realistic microbial communities. RESULTS: PMA-seq was able to successfully reconstruct simple synthetic communities comprising viable/heat-killed Escherichia coli and Streptococcus sanguinis. However, in realistically complex communities (computer screens, computer mice, soil, and human saliva) with E. coli spike-in controls, PMA-seq did not accurately quantify viability (even relative to variability in amplicon sequencing), with its performance largely affected by community properties such as initial biomass, sample types, and compositional diversity. We then applied this technique to environmental swabs from the Boston subway system. Several taxa differed significantly after PMA treatment, while not all microorganisms responded consistently. To elucidate the "PMA-responsive" microbes, we compared our results with previous PMA-based studies and found that PMA responsiveness varied widely when microbes were sourced from different ecosystems but were reproducible within similar environments across studies. CONCLUSIONS: This study provides a comprehensive evaluation of PMA-seq exploring its quantitative potential in synthetic and complex microbial communities, where the technique was effective for semi-quantitative purposes in simple synthetic communities but provided only qualitative assessments in realistically complex community samples. Video abstract.

Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3.

Culture-independent analyses of microbial communities have progressed dramatically in the last decade, particularly due to advances in methods for biological profiling via shotgun metagenomics. Opportunities for improvement continue to accelerate, with greater access to multi-omics, microbial reference genomes, and strain-level diversity. To leverage these, we present bioBakery 3, a set of integrated, improved methods for taxonomic, strain-level, functional, and phylogenetic profiling of metagenomes newly developed to build on the largest set of reference sequences now available. Compared to current alternatives, MetaPhlAn 3 increases the accuracy of taxonomic profiling, and HUMAnN 3 improves that of functional potential and activity. These methods detected novel disease-microbiome links in applications to CRC (1262 metagenomes) and IBD (1635 metagenomes and 817 metatranscriptomes). Strain-level profiling of an additional 4077 metagenomes with StrainPhlAn 3 and PanPhlAn 3 unraveled the phylogenetic and functional structure of the common gut microbe Ruminococcus bromii, previously described by only 15 isolate genomes. With open-source implementations and cloud-deployable reproducible workflows, the bioBakery 3 platform can help researchers deepen the resolution, scale, and accuracy of multi-omic profiling for microbial community studies.

A bacterial bile acid metabolite modulates Treg activity through the nuclear hormone receptor NR4A1.

Bile acids act as signaling molecules that regulate immune homeostasis, including the differentiation of CD4+ T cells into distinct T cell subsets. The bile acid metabolite isoallolithocholic acid (isoalloLCA) enhances the differentiation of anti-inflammatory regulatory T cells (Treg cells) by facilitating the formation of a permissive chromatin structure in the promoter region of the transcription factor forkhead box P3 (Foxp3). Here, we identify gut bacteria that synthesize isoalloLCA from 3-oxolithocholic acid and uncover a gene cluster responsible for the conversion in members of the abundant human gut bacterial phylum Bacteroidetes. We also show that the nuclear hormone receptor NR4A1 is required for the effect of isoalloLCA on Treg cells. Moreover, the levels of isoalloLCA and its biosynthetic genes are significantly reduced in patients with inflammatory bowel diseases, suggesting that isoalloLCA and its bacterial producers may play a critical role in maintaining immune homeostasis in humans.

Generation of tooth-periodontium complex structures using high-odontogenic potential dental epithelium derived from mouse embryonic stem cells.

BACKGROUND: A number of studies have shown that tooth-like structures can be regenerated using induced pluripotent stem cells and mouse embryonic stem (mES) cells. However, few studies have reported the regeneration of tooth-periodontium complex structures, which are more suitable for clinical tooth transplantation. We established an optimized approach to induce high-odontogenic potential dental epithelium derived from mES cells by temporally controlling bone morphogenic protein 4 (BMP4) function and regenerated tooth-periodontium complex structures in vivo. METHODS: First, immunofluorescence and quantitative reverse transcription-polymerase chain reaction were used to identify the watershed of skin and the oral ectoderm. LDN193189 was then used to inhibit the BMP4 receptor around the watershed, followed by the addition of exogenous BMP4 to promote BMP4 function. The generated dental epithelium was confirmed by western blot analysis and immunofluorescence. The generated epithelium was ultimately combined with embryonic day 14.5 mouse mesenchyme and transplanted into the renal capsules of nude mice. After 4 weeks, the tooth-periodontium complex structure was examined by micro-computed tomography (CT) and hematoxylin and eosin (H&E) staining. RESULTS: Our study found that the turning point of oral ectoderm differentiation occurred around day 3 after the embryoid body was transferred to a common culture plate. Ameloblastin-positive dental epithelial cells were detected following the temporal regulation of BMP4. Tooth-periodontium complex structures, which included teeth, a periodontal membrane, and alveolar bone, were formed when this epithelium was combined with mouse dental mesenchyme and transplanted into the renal capsules of nude mice. Micro-CT and H&E staining revealed that the generated tooth-periodontium complex structures shared a similar histological structure with normal mouse teeth. CONCLUSIONS: An optimized induction method was established to promote the differentiation of mES cells into dental epithelium by temporally controlling the function of BMP4. A novel tooth-periodontium complex structure was generated using the epithelium.