Metagenomic and metabolomic analyses reveal distinct stage-specific phenotypes of the gut microbiota in colorectal cancer. Nat Med. 2019;25:968-976. [PMID: 31171880 DOI: 10.1038/s41591-019-0458-7]

Explainable machine learning model for identifying key gut microbes and metabolites biomarkers associated with myasthenia gravis

Diagnostic markers for myasthenia gravis (MG) are limited; thus, innovative approaches are required for supportive diagnosis and personalized care. Gut microbes are associated with MG pathogenesis; however, few studies have adopted machine learning (ML) to identify the associations among MG, gut microbiota, and metabolites. In this study, we developed an explainable ML model to predict biomarkers for MG diagnosis. We enrolled 19 MG patients and 10 non-MG individuals. Stool samples were collected and microbiome assessment was performed using 16S rRNA sequencing. Untargeted metabolic profiling was conducted to identify fecal amplicon significant variants (ASVs) and metabolites. We developed an explainable ML model in which the top ASVs and metabolites are combined to identify the best predictive performance. This model uses the SHapley Additive exPlanations method to generate both global and personalized explanations. Fecal microbe-metabolite composition differed significantly between groups. The key bacterial families were Lachnospiraceae and Ruminococcaceae, and the top three features were Lachnospiraceae, inosine, and methylhistidine. An ML model trained with the top 1 % ASVs and top 15 % metabolites combined outperformed all other models. Personalized explanations revealed different patterns of microbe-metabolite contributions in patients with MG. The integration of the microbiota-metabolite features and the development of an explainable ML framework can accurately identify MG and provide personalized explanations, revealing the associations between gut microbiota, metabolites, and MG. An online calculator employing this algorithm was developed that provides a streamlined interface for MG diagnosis screening and conducting personalized evaluations.

Targeting bacterial metabolites in tumor for cancer therapy: An alternative approach for targeting tumor-associated bacteria

Emerging evidence reveal that tumor-associated bacteria (TAB) can facilitate the initiation and progression of multiple types of cancer. Recent work has emphasized the significant role of intestinal microbiota, particularly bacteria, plays in affecting responses to chemo- and immuno-therapies. Hence, it seems feasible to improve cancer treatment outcomes by targeting intestinal bacteria. While considering variable richness of the intestinal microbiota and diverse components among individuals, direct manipulating the gut microbiota is complicated in clinic. Tumor initiation and progression requires the gut microbiota-derived metabolites to contact and reprogram neoplastic cells. Hence, directly targeting tumor-associated bacteria metabolites may have the potential to provide alternative and innovative strategies to bypass the gut microbiota for cancer therapy. As such, there are great opportunities to explore holistic approaches that incorporates TAB-derived metabolites and related metabolic signals modulation for cancer therapy. In this review, we will focus on key opportunistic areas by targeting TAB-derived metabolites and related metabolic signals, but not bacteria itself, for cancer treatment, and elucidate future challenges that need to be addressed in this emerging field.

The first diagnosis of Severe Fever with Thrombocytopenia Syndrome caused by tick-borne Severe Fever with Thrombocytopenia Syndrome virus in Chongqing, China: A case report and literature review

BACKGROUND

Severe Fever with Thrombocytopenia Syndrome (SFTS) is a tick-borne disease caused by the SFTS virus (SFTSV) which has the potential to become a pandemic and is currently a major public health concern.

CASE PRESENTATION

We present the case of a 74-year-old female from an urban area of Chongqing, with leukocytopenia, thrombocytopenia, organ function, inflammatory, blood coagulation, and immune abnormalities. SFTSV infection was confirmed through molecular detection and metagenomic next-generation sequencing (mNGS) analysis, indicating a diagnosis of SFTS due to the patient's history of tick bites. The patient received symptomatic and supportive therapy, including antibiotics, antiviral treatment, and antifungal therapy, and finally discharged from the hospital on day 18.

CONCLUSIONS

This study highlights the need for increased awareness, early diagnosis, and prompt treatment for tick-borne SFTS. It also provides a comprehensive understanding of the disease's characteristics, pathogenesis, detection methods, and available treatments.

Distinct gut microbiomes in Thai patients with colorectal polyps

BACKGROUND

Colorectal polyps that develop via the conventional adenoma-carcinoma sequence [e.g., tubular adenoma (TA)] often progress to malignancy and are closely associated with changes in the composition of the gut microbiome. There is limited research concerning the microbial functions and gut microbiomes associated with colorectal polyps that arise through the serrated polyp pathway, such as hyperplastic polyps (HP). Exploration of microbiome alterations associated with HP and TA would improve the understanding of mechanisms by which specific microbes and their metabolic pathways contribute to colorectal carcinogenesis.

AIM

To investigate gut microbiome signatures, microbial associations, and microbial functions in HP and TA patients.

METHODS

Full-length 16S rRNA sequencing was used to characterize the gut microbiome in stool samples from control participants without polyps [control group (CT), n = 40], patients with HP (n = 52), and patients with TA (n = 60). Significant differences in gut microbiome composition and functional mechanisms were identified between the CT group and patients with HP or TA. Analytical techniques in this study included differential abundance analysis, co-occurrence network analysis, and differential pathway analysis.

RESULTS

Colorectal cancer (CRC)-associated bacteria, including Streptococcus gallolyticus (S. gallolyticus), Bacteroides fragilis, and Clostridium symbiosum, were identified as characteristic microbial species in TA patients. Mediterraneibacter gnavus, associated with dysbiosis and gastrointestinal diseases, was significantly differentially abundant in the HP and TA groups. Functional pathway analysis revealed that HP patients exhibited enrichment in the sulfur oxidation pathway exclusively, whereas TA patients showed dominance in pathways related to secondary metabolite biosynthesis (e.g., mevalonate); S. gallolyticus was a major contributor. Co-occurrence network and dynamic network analyses revealed co-occurrence of dysbiosis-associated bacteria in HP patients, whereas TA patients exhibited co-occurrence of CRC-associated bacteria. Furthermore, the co-occurrence of SCFA-producing bacteria was lower in TA patients than HP patients.

CONCLUSION

This study revealed distinct gut microbiome signatures associated with pathways of colorectal polyp development, providing insights concerning the roles of microbial species, functional pathways, and microbial interactions in colorectal carcinogenesis.

Fusobacterium species are distinctly associated with patients with Lynch syndrome colorectal cancer

Accumulating evidence demonstrates clear correlation between the gut microbiota and sporadic colorectal cancer (CRC). Despite this, there is limited understanding of the association between the gut microbiota and CRC in Lynch Syndrome (LS), a hereditary type of CRC. Here, we analyzed fecal shotgun metagenomic and targeted metabolomic of 71 Japanese LS subjects. A previously published Japanese sporadic CRC cohort, which includes non-LS controls, was utilized as a non-LS cohort (n = 437). LS subjects exhibited reduced microbial diversity and low-Faecalibacterium enterotypes compared to non-LS. Patients with LS-CRC had higher levels of Fusobacterium nucleatum and fap2. Differential fecal metabolites and functional genes suggest heightened degradation of lysine and arginine in LS-CRC. A comparison between LS and non-LS subjects prior to adenoma formation revealed distinct fecal metabolites of LS subjects. These findings suggest that the gut microbiota plays a more responsive role in CRC tumorigenesis in patients with LS than those without LS.

Species-level identification of enterotype-specific microbial markers for colorectal cancer and adenoma

Enterotypes have been shown to be an important factor for population stratification based on gut microbiota composition, leading to a better understanding of human health and disease states. Classifications based on compositional patterns will have implications for personalized microbiota-based solutions. There have been limited enterotype based studies on colorectal adenoma and cancer. Here, an enterotype-based meta-analysis of fecal shotgun metagenomic studies was performed, including 1579 samples of healthy controls (CTR), colorectal adenoma (ADN) and colorectal cancer (CRC) in total. Gut microbiota of healthy people were clustered into three enterotypes (Ruminococcus-, Bacteroides- and Prevotella-dominated enterotypes). Reference-based enterotype assignments were performed for CRC and ADN samples, using the supervised machine learning algorithm, K-nearest neighbors. Differential abundance analyses and random forest classification were conducted on each enterotype between healthy controls and CRC-ADN groups, revealing novel enterotype-specific microbial markers for non-invasive CRC screening strategies. Furthermore, we identified microbial species unique to each enterotype that play a role in the production of secondary bile acids and short-chain fatty acids, unveiling the correlation between cancer-associated gut microbes and dietary patterns. The enterotype-based approach in this study is promising in elucidating the mechanisms of differential gut microbiome profiles, thereby improving the efficacy of personalized microbiota-based solutions.

Advancements in 3D In Vitro Models for Colorectal Cancer

The process of drug discovery and pre-clinical testing is currently inefficient, expensive, and time-consuming. Most importantly, the success rate is unsatisfactory, as only a small percentage of tested drugs are made available to oncological patients. This is largely due to the lack of reliable models that accurately predict drug efficacy and safety. Even animal models often fail to replicate human-specific pathologies and human body's complexity. These factors, along with ethical concerns regarding animal use, urge the development of suitable human-relevant, translational in vitro models.

VirRep: a hybrid language representation learning framework for identifying viruses from human gut metagenomes

Identifying viruses from metagenomes is a common step to explore the virus composition in the human gut. Here, we introduce VirRep, a hybrid language representation learning framework, for identifying viruses from human gut metagenomes. VirRep combines a context-aware encoder and an evolution-aware encoder to improve sequence representation by incorporating k-mer patterns and sequence homologies. Benchmarking on both simulated and real datasets with varying viral proportions demonstrates that VirRep outperforms state-of-the-art methods. When applied to fecal metagenomes from a colorectal cancer cohort, VirRep identifies 39 high-quality viral species associated with the disease, many of which cannot be detected by existing methods.

Ginsenoside Rh4 inhibits colorectal cancer via the modulation of gut microbiota-mediated bile acid metabolism

INTRODUCTION

Dysbiosis of the gut microbiota is emerging as a pivotal factor in the pathogenesis of colorectal cancer (CRC). Ginsenoside Rh4 (Rh4) is an active compound isolated from ginseng with beneficial effects in modulating intestinal inflammation and gut microbiota dysbiosis, but how Rh4 regulates the gut microbiota to alleviate CRC remains underexplored.

OBJECTIVES

We investigated the impact of Rh4 on CRC and the mechanism of its action in inhibiting CRC via modulation of gut microbiota.

METHODS

We used the AOM/DSS model and employed transcriptomics, genomics and metabolomics techniques to explore the inhibitory impact of Rh4 on CRC. Furthermore, we employed experiments involving antibiotic treatment and fecal microbiota transplantation (FMT) to investigate the role of the gut microbiota. Finally, we elucidated the pivotal role of key functional bacteria and metabolites regulated by Rh4 in CRC.

RESULTS

Our research findings indicated that Rh4 repaired intestinal barrier damage caused by CRC, alleviated intestinal inflammation, and inhibited the development of CRC. Additionally, Rh4 inhibited CRC in a gut microbiota-dependent manner. Rh4 increased the diversity of gut microbiota, enriched the probiotic Akkermansia muciniphila (A. muciniphila), and alleviated gut microbiota dysbiosis caused by CRC. Subsequently, Rh4 regulated A. muciniphila-mediated bile acid metabolism. A. muciniphila promoted the production of UDCA by enhancing the activity of 7α-hydroxysteroid dehydrogenase (7α-HSDH). UDCA further activated FXR, modulated the TLR4-NF-κB signaling pathway, thus inhibiting the development of CRC.

CONCLUSION

Our results confirm that Rh4 inhibits CRC in a gut microbiota-dependent manner by modulating gut microbiota-mediated bile acid metabolism and promoting the production of UDCA, which further activates the FXR receptor and regulates the TLR4-NF-κB signaling pathway. Our results confirm that Rh4 has the potential to be used as a modulator of gut microbiota for preventing and treatment of CRC.

Characterization of the gut microbiota and fecal metabolome in the osteosarcoma mouse model

Previous studies have reported the correlation between gut microbiota (GM), GM-derived metabolites, and various intestinal and extra-intestinal cancers. However, limited studies have investigated the correlation between GM, GM-derived metabolites, and osteosarcoma (OS). This study successfully established a female BALB/c nude mouse model of OS. Mice (n = 14) were divided into the following two groups (n = 7/group): OS group named OG, injected with Saos-2 OS cells; normal control group named NCG, injected with Matrigel. The GM composition and metabolites were characterized using 16S rDNA sequencing and untargeted metabolomics, respectively. Bioinformatics analysis revealed that amino acid metabolism was dysregulated in OS. The abundances of bone metabolism-related genera Alloprevotella, Rikenellaceae_RC9_gut_group, and Muribaculum were correlated with amino acid metabolism, especially histidine metabolism. These findings suggest the correlation between GM, GM-derived metabolites, and OS pathogenesis. Clinical significance: The currently used standard therapeutic strategies for OS, including surgery, chemotherapy, and radiation, are not efficacious. The findings of this study provided novel insights for developing therapeutic, diagnostic, and prognostic strategies for OS.

Organoids in gastrointestinal diseases: from bench to clinic

The etiology of gastrointestinal (GI) diseases is intricate and multifactorial, encompassing complex interactions between genetic predisposition and gut microbiota. The cell fate change, immune function regulation, and microenvironment composition in diseased tissues are governed by microorganisms and mutated genes either independently or through synergistic interactions. A comprehensive understanding of GI disease etiology is imperative for developing precise prevention and treatment strategies. However, the existing models used for studying the microenvironment in GI diseases-whether cancer cell lines or mouse models-exhibit significant limitations, which leads to the prosperity of organoids models. This review first describes the development history of organoids models, followed by a detailed demonstration of organoids application from bench to clinic. As for bench utilization, we present a layer-by-layer elucidation of organoid simulation on host-microbial interactions, as well as the application in molecular mechanism analysis. As for clinical adhibition, we provide a generalized interpretation of organoid application in GI disease simulation from inflammatory disorders to malignancy diseases, as well as in GI disease treatment including drug screening, immunotherapy, and microbial-targeting and screening treatment. This review draws a comprehensive and systematical depiction of organoids models, providing a novel insight into the utilization of organoids models from bench to clinic.

Embryo injected with Ochratoxin A induced jejunum injury in ducklings by activating the TLR4 signaling pathway: Involvement of intestinal microbiota

Ochratoxin A (OTA) is a common mycotoxin that causes intestinal injury in humans and various animal species. OTA may lead to intestinal injury in offspring due to the maternal effect. The aim of this study was to investigate the mechanism of embryo injected with OTA induced jejunum injury in ducklings. The results showed that OTA disrupted the jejunum tight junctions in hatching ducklings, and promoted the secretion of inflammatory cytokines. And this inflammatory response was caused by the activation of the TLR4 signaling pathway. Moreover, embryo injected with OTA could cause damage to the intestinal barrier in 21-day-old ducks, characterized by shortened villi, crypt hyperplasia, disrupted intestinal tight junctions, increased level of LPS in the jejunum, activation of the TLR4 signaling pathway, and increased levels of pro-inflammatory cytokines. Meanwhile, OTA induced oxidative stress in the jejunum. And dysbiosis of gut microbiota was mainly characterized by an increased the relative abundance of Bacteroides, Megamonas, Fournierella, and decreased the relative abundance of Alistipes and Weissella. Interestingly, embryo injected with OTA did not induce these changes in the jejunum of antibiotics-treated 21-day-old ducks. In conclusion, embryo injected with OTA induced jejunum injury in ducklings by activating the TLR4 signaling pathway, which involvement of intestinal microbiota.

Machine learning for the advancement of genome-scale metabolic modeling

Constraint-based modeling (CBM) has evolved as the core systems biology tool to map the interrelations between genotype, phenotype, and external environment. The recent advancement of high-throughput experimental approaches and multi-omics strategies has generated a plethora of new and precise information from wide-ranging biological domains. On the other hand, the continuously growing field of machine learning (ML) and its specialized branch of deep learning (DL) provide essential computational architectures for decoding complex and heterogeneous biological data. In recent years, both multi-omics and ML have assisted in the escalation of CBM. Condition-specific omics data, such as transcriptomics and proteomics, helped contextualize the model prediction while analyzing a particular phenotypic signature. At the same time, the advanced ML tools have eased the model reconstruction and analysis to increase the accuracy and prediction power. However, the development of these multi-disciplinary methodological frameworks mainly occurs independently, which limits the concatenation of biological knowledge from different domains. Hence, we have reviewed the potential of integrating multi-disciplinary tools and strategies from various fields, such as synthetic biology, CBM, omics, and ML, to explore the biochemical phenomenon beyond the conventional biological dogma. How the integrative knowledge of these intersected domains has improved bioengineering and biomedical applications has also been highlighted. We categorically explained the conventional genome-scale metabolic model (GEM) reconstruction tools and their improvement strategies through ML paradigms. Further, the crucial role of ML and DL in omics data restructuring for GEM development has also been briefly discussed. Finally, the case-study-based assessment of the state-of-the-art method for improving biomedical and metabolic engineering strategies has been elaborated. Therefore, this review demonstrates how integrating experimental and in silico strategies can help map the ever-expanding knowledge of biological systems driven by condition-specific cellular information. This multiview approach will elevate the application of ML-based CBM in the biomedical and bioengineering fields for the betterment of society and the environment.

Gut microbiota characteristics of colorectal cancer patients in Hubei, China, and differences with cohorts from other Chinese regions

The research on the correlation or causality between gut microbiota and the occurrence, development, and treatment of colorectal cancer (CRC) is receiving increasing emphasis. At the same time, the incidence and mortality of colorectal cancer vary among individuals and regions, as does the gut microbiota. In order to gain a better understanding of the characteristics of the gut microbiota in CRC patients and the differences between different regions, we initially compared the gut microbiota of 25 CRC patients and 26 healthy controls in the central region of China (Hubei Province) using 16S rRNA high-throughput sequencing technology. The results showed that Corynebacterium, Enterococcus, Lactobacillus, and Escherichia-Shigella were significantly enriched in CRC patients. In addition, we also compared the potential differences in functional pathways between the CRC group and the healthy control group using PICRUSt's functional prediction analysis. We then analyzed and compared it with five cohort studies from various regions of China, including Central, East, and Northeast China. We found that geographical factors may affect the composition of intestinal microbiota in CRC patients. The composition of intestinal microbiota is crucial information that influences colorectal cancer screening, early detection, and the prediction of CRC treatment outcomes. This emphasizes the importance of conducting research on CRC-related gut microbiota in various regions of China.

Tumor initiation and early tumorigenesis: molecular mechanisms and interventional targets

Tumorigenesis is a multistep process, with oncogenic mutations in a normal cell conferring clonal advantage as the initial event. However, despite pervasive somatic mutations and clonal expansion in normal tissues, their transformation into cancer remains a rare event, indicating the presence of additional driver events for progression to an irreversible, highly heterogeneous, and invasive lesion. Recently, researchers are emphasizing the mechanisms of environmental tumor risk factors and epigenetic alterations that are profoundly influencing early clonal expansion and malignant evolution, independently of inducing mutations. Additionally, clonal evolution in tumorigenesis reflects a multifaceted interplay between cell-intrinsic identities and various cell-extrinsic factors that exert selective pressures to either restrain uncontrolled proliferation or allow specific clones to progress into tumors. However, the mechanisms by which driver events induce both intrinsic cellular competency and remodel environmental stress to facilitate malignant transformation are not fully understood. In this review, we summarize the genetic, epigenetic, and external driver events, and their effects on the co-evolution of the transformed cells and their ecosystem during tumor initiation and early malignant evolution. A deeper understanding of the earliest molecular events holds promise for translational applications, predicting individuals at high-risk of tumor and developing strategies to intercept malignant transformation.

Enhancing insights into diseases through horizontal gene transfer event detection from gut microbiome

Horizontal gene transfer (HGT) phenomena pervade the gut microbiome and significantly impact human health. Yet, no current method can accurately identify complete HGT events, including the transferred sequence and the associated deletion and insertion breakpoints from shotgun metagenomic data. Here, we develop LocalHGT, which facilitates the reliable and swift detection of complete HGT events from shotgun metagenomic data, delivering an accuracy of 99.4%-verified by Nanopore data-across 200 gut microbiome samples, and achieving an average F1 score of 0.99 on 100 simulated data. LocalHGT enables a systematic characterization of HGT events within the human gut microbiome across 2098 samples, revealing that multiple recipient genome sites can become targets of a transferred sequence, microhomology is enriched in HGT breakpoint junctions (P-value = 3.3e-58), and HGTs can function as host-specific fingerprints indicated by the significantly higher HGT similarity of intra-personal temporal samples than inter-personal samples (P-value = 4.3e-303). Crucially, HGTs showed potential contributions to colorectal cancer (CRC) and acute diarrhoea, as evidenced by the enrichment of the butyrate metabolism pathway (P-value = 3.8e-17) and the shigellosis pathway (P-value = 5.9e-13) in the respective associated HGTs. Furthermore, differential HGTs demonstrated promise as biomarkers for predicting various diseases. Integrating HGTs into a CRC prediction model achieved an AUC of 0.87.

Gut microbiota and serum metabolite signatures along the colorectal adenoma-carcinoma sequence: Implications for early detection and intervention

AIM

Our study focuses on the microbial and metabolomic profile changes during the adenoma stage, as adenomas can be considered potential precursors to colorectal cancer through the adenoma-carcinoma sequence. Identifying possible intervention targets at this stage may aid in preventing the progression of colorectal adenoma (CRA) to malignant lesions. Furthermore, we evaluate the efficacy of combined microbial and metabolite biomarkers in detecting CRA.

METHODS

Fecal metagenomic and serum metabolomic analyses were performed for the discovery of alterations of gut microbiome and metabolites in CRA patients (n = 26), Colorectal cancer (CRC) patients (n = 19), Familial Adenomatous Polyposis (FAP) patients (n = 10), and healthy controls (n = 20). Finally, analyzing the associations between gut microbes and metabolites was performed by a Receiver Operating Characteristic (ROC) curve.

RESULTS

Our analysis present that CRA patients differ significantly in gut microflora and serum metabolites compared with healthy controls, especially for Lachnospiraceae and Parasutterella. Its main metabolite, butyric acid, concentrations were raised in CRA patients compared with the healthy controls, indicating its role as a promoter of colorectal tumorigenesis. α-Linolenic acid and lysophosphatidylcholine represented the other healthy metabolite for CRA. Combining five microbial and five metabolite biomarkers, we differentiated CRA from CRC with an Area Under the Curve (AUC) of 0.85 out of this performance vastly superior to the specificity recorded by traditional markers CEA and CA199 in such differentiation of these conditions.

CONCLUSIONS

The study underlines significant microbial and metabolic alterations in CRA with a novel insight into screening and early intervention of its tumorigenesis.

Effects of Bifidobacterium breve 207-1 on regulating lifestyle behaviors and mental wellness in healthy adults based on the microbiome-gut-brain axis: a randomized, double-blind, placebo-controlled trial

PURPOSE

Our study aimed to explore the efficacy of Bifidobacterium breve 207-1 on specific neurotransmitters and hormones and the ability to regulate lifestyle behaviors in healthy adults.

METHODS

In total, 120 healthy adults with high mental stress, overweight, insomnia, and constipation were randomly assigned to receive low-dose B. breve 207-1 (LD, n = 40), high-dose B. breve 207-1 (HD, n = 40), or placebo (n = 40) for 28 days. Fecal and blood samples were collected and questionnaires were answered before and after the trial. Neurotransmitters and serum hormones were detected using enzyme-linked immunosorbent assay. The gut microbiota composition was assessed using 16 S rRNA sequencing. Short-chain fatty acids (SCFAs) concentrations were determined via gas chromatography-mass spectrometry (GC-MS).

RESULTS

The primary outcome of our study was changes in mental wellness, including neurotransmitters, the hypothalamic-pituitary-adrena (HPA) axis hormones, and the psychological scales. The results showed that γ-aminobutyric acid (GABA) increased significantly and the HPA axis hormones were suppressed overall in the probiotic groups while 5-hydroxytryptamine (5-HT) did not change significantly. However, there was no significant change in mood scale scores. The secondary outcome focused on the ability of 207-1 to regulate the body and lifestyle of healthy adults (e.g., sleep, diet, exercise, etc.). The PSQI scores in the probiotics groups significantly decreased, indicating improved sleep quality. Meanwhile, the probiotic groups had a slight increase in exercise consumption while dietary intake stabilized. By physical examination, the participants showed weight loss although no statistically significant difference was observed between the groups. Then, validated by gut microbiota, changes in the gut microbiota were observed under the effective intervention of 207-1 while short-chain fatty acids (SCFAs) increased in the LD group, particularly acetic and propionic acids. There was a slight decrease in alpha-diversity in the HD group.

CONCLUSION

Bifidobacterium breve 207-1 entered the organism and affected neurotransmitter and the HPA axis hormone levels via the microbiome-gut-brain axis. Meanwhile, 207-1 supplementation improved daily lifestyle behaviors in healthy adults, which may in turn lead to changes in their bodies (e.g. weight and lipid metabolism). However, this study did not find significant mood-modulating efficacy. The mechanism of the overall study is unclear, but we hypothesize that SCFAs may be the key pathway, and more experiments are needed for validation in the future.

TRIAL REGISTRATION

This trial was retrospectively registered in the Chinese Clinical Trial Registry under the accession number ChiCTR2300069453 on March 16, 2023.

Sexual dimorphism in colorectal cancer: molecular mechanisms and treatment strategies

INTRODUCTION

Sexual dimorphism significantly influences cancer incidence and prognosis. Notably, females exhibit a lower risk and favorable prognosis for non-reproductive cancers compared to males, a pattern observable beyond the scope of risk behaviors such as alcohol consumption and smoking. Colorectal cancer, ranking third in global prevalence and second in mortality, disproportionately affects men. Sex steroid hormones, particularly estrogens and androgens, play crucial roles in cancer progression, considering epidemiological in vivo and in vitro, in general estrogens imparting a protective effect in females and androgens correlating with an increasing risk of colorectal cancer development.

MAIN BODY

The hormonal impact on immune response is mediated by receptor interactions, resulting in heightened inflammation, modulation of NF-kB, and fostering an environment conducive to cancer progression and metastasis. These molecules also influence the enteric nervous system, that is a pivotal in neuromodulator release and intestinal neuron stimulation, also contributes to cancer development, as evidenced by nerve infiltration into tumors. Microbiota diversity further intersects with immune, hormonal, and neural mechanisms, influencing colorectal cancer dynamics. A comprehensive understanding of hormonal influences on colorectal cancer progression, coupled with the complex interplay between immune responses, microbiota diversity and neurotransmitter imbalances, underpins the development of more targeted and effective therapies.

CONCLUSIONS

Estrogens mitigate colorectal cancer risk by modulating anti-tumor immune responses, enhancing microbial diversity, and curbing the pro-tumor actions of the sympathetic and enteric nervous systems. Conversely, androgens escalate tumor growth by dampening anti-tumor immune activity, reducing microbial diversity, and facilitating the release of tumor-promoting factors by the nervous system. These findings hold significant potential for the strategic purposing of drugs to fine-tune the extensive impacts of sex hormones within the tumor microenvironment, promising advancements in colorectal cancer therapies.

A genomic compendium of cultivated human gut fungi characterizes the gut mycobiome and its relevance to common diseases

The gut fungal community represents an essential element of human health, yet its functional and metabolic potential remains insufficiently elucidated, largely due to the limited availability of reference genomes. To address this gap, we presented the cultivated gut fungi (CGF) catalog, encompassing 760 fungal genomes derived from the feces of healthy individuals. This catalog comprises 206 species spanning 48 families, including 69 species previously unidentified. We explored the functional and metabolic attributes of the CGF species and utilized this catalog to construct a phylogenetic representation of the gut mycobiome by analyzing over 11,000 fecal metagenomes from Chinese and non-Chinese populations. Moreover, we identified significant common disease-related variations in gut mycobiome composition and corroborated the associations between fungal signatures and inflammatory bowel disease (IBD) through animal experimentation. These resources and findings substantially enrich our understanding of the biological diversity and disease relevance of the human gut mycobiome.

Evaluation of normalization methods for predicting quantitative phenotypes in metagenomic data analysis

Genotype-to-phenotype mapping is an essential problem in the current genomic era. While qualitative case-control predictions have received significant attention, less emphasis has been placed on predicting quantitative phenotypes. This emerging field holds great promise in revealing intricate connections between microbial communities and host health. However, the presence of heterogeneity in microbiome datasets poses a substantial challenge to the accuracy of predictions and undermines the reproducibility of models. To tackle this challenge, we investigated 22 normalization methods that aimed at removing heterogeneity across multiple datasets, conducted a comprehensive review of them, and evaluated their effectiveness in predicting quantitative phenotypes in three simulation scenarios and 31 real datasets. The results indicate that none of these methods demonstrate significant superiority in predicting quantitative phenotypes or attain a noteworthy reduction in Root Mean Squared Error (RMSE) of the predictions. Given the frequent occurrence of batch effects and the satisfactory performance of batch correction methods in predicting datasets affected by these effects, we strongly recommend utilizing batch correction methods as the initial step in predicting quantitative phenotypes. In summary, the performance of normalization methods in predicting metagenomic data remains a dynamic and ongoing research area. Our study contributes to this field by undertaking a comprehensive evaluation of diverse methods and offering valuable insights into their effectiveness in predicting quantitative phenotypes.

TARO: tree-aggregated factor regression for microbiome data integration

MOTIVATION

Although the human microbiome plays a key role in health and disease, the biological mechanisms underlying the interaction between the microbiome and its host are incompletely understood. Integration with other molecular profiling data offers an opportunity to characterize the role of the microbiome and elucidate therapeutic targets. However, this remains challenging to the high dimensionality, compositionality, and rare features found in microbiome profiling data. These challenges necessitate the use of methods that can achieve structured sparsity in learning cross-platform association patterns.

RESULTS

We propose Tree-Aggregated factor RegressiOn (TARO) for the integration of microbiome and metabolomic data. We leverage information on the taxonomic tree structure to flexibly aggregate rare features. We demonstrate through simulation studies that TARO accurately recovers a low-rank coefficient matrix and identifies relevant features. We applied TARO to microbiome and metabolomic profiles gathered from subjects being screened for colorectal cancer to understand how gut microrganisms shape intestinal metabolite abundances.

AVAILABILITY AND IMPLEMENTATION

The R package TARO implementing the proposed methods is available online at https://github.com/amishra-stats/taro-package.

Gut Microbiota, Human Blood Metabolites, and Esophageal Cancer: A Mendelian Randomization Study

BACKGROUND

Unbalances in the gut microbiota have been proposed as a possible cause of esophageal cancer (ESCA), yet the exact causal relationship remains unclear.

PURPOSE

To investigate the potential causal relationship between the gut microbiota and ESCA with Mendelian randomization (MR) analysis.

METHODS

Genome-wide association studies (GWASs) of 207 gut microbial taxa (5 phyla, 10 classes, 13 orders, 26 families, 48 genera, and 105 species) and 205 gut microbiota metabolic pathways conducted by the Dutch Microbiome Project (DMP) and a FinnGen cohort GWAS of esophageal cancer specified the summary statistics. To investigate the possibility of a mediation effect between the gut microbiota and ESCA, mediation MR analyses were performed for 1091 blood metabolites and 309 metabolite ratios.

RESULTS

MR analysis indicated that the relative abundance of 10 gut microbial taxa was associated with ESCA but all the 12 gut microbiota metabolic pathways with ESCA indicated no statistically significant association existing. Two blood metabolites and a metabolite ratio were discovered to be mediating factors in the pathway from gut microbiota to ESCA.

CONCLUSION

This research indicated the potential mediating effects of blood metabolites and offered genetic evidence in favor of a causal correlation between gut microbiota and ESCA.

Development and establishment of oral microbiota in early life

BACKGROUND

The oral microbiota has recently attracted attention owing to its association with oral and systemic diseases. Accordingly, gaining an understanding of oral microbiota development and the factors influencing it can contribute to preventing the establishment of dysbiotic oral microbiota and, eventually, oral microbiota-related diseases.

HIGHLIGHT

In this review, we highlight the results of a longitudinal project focusing on oral microbiota development during early life. At 4 months of age, the oral microbiota of infants was found to differ considerably from the maternal oral microbiota, even though infants acquire oral bacteria from their mothers. At 18 months, although the infant microbiota is still not completely comparable with that of adults, from 4 to 18 months, there is a rapid phase of development, during which the microbial composition undergoes considerable change to a profile more similar to that in adults. During this development, the infant oral microbiota converges into two different profiles with adult-like traits, namely, Streptococcus salivarius- and Neisseria-dominant profiles. This divergence is strongly influenced by dietary habits, with a frequent intake of sweetened beverages being associated with an S. salivarius-dominant profile, which is suspected to be implicated in oral and systemic diseases.

CONCLUSION

The foundation of the adult oral microbiota may be established by 18 months of age, and the developmental period from 4 to 18 months may be an appropriate period during which to modify the microbial balance to obtain a desirable healthy state. In particular, dietary habits during this period warrant close attention.

Intestinal metabolite xylulose inhibits colorectal cancer by inducing apoptosis through the MAPK signalling pathway

BACKGROUND

The intestinal metabolites are involved in the initiation, progression and metastasis of colorectal cancer (CRC). They are a potential source of agents for cancer therapy. Our previous study identified altered faecal metabolites between CRC patients and healthy volunteers. However, no specific metabolite was clearly illustrated for CRC therapy.

RESULTS

We found that the level of xylulose was lower in the stools of CRC patients than in those of healthy volunteers. Xylulose inhibited cell growth without affecting the cell cycle by inducing apoptosis in CRC cells, which was evidenced by increased expression of the proapoptotic proteins C-PARP and C-Caspase3 and decreased expression of the antiapoptotic protein BCL-2 in CRC cells. Mechanistically, xylulose reduced the activity of the MAPK signalling pathway, represented by reduced phosphorylation of JNK, ERK, and P38. Furthermore, an ALI model was used to show the tumour killing ability of xylulose on human CRC spheres, as well as human colorectal adenoma (AD) spheres.

CONCLUSION

Xylulose inhibits CRC growth by inducing apoptosis through attenuation of the MAPK signalling pathway. These results suggest that xylulose may serve as an effective agent for CRC therapy.

How Diet and Lifestyle Can Fine-Tune Gut Microbiomes for Healthy Aging

Many physical, social, and psychological changes occur during aging that raise the risk of developing chronic diseases, frailty, and dependency. These changes adversely affect the gut microbiota, a phenomenon known as microbe-aging. Those microbiota alterations are, in turn, associated with the development of age-related diseases. The gut microbiota is highly responsive to lifestyle and dietary changes, displaying a flexibility that also provides anactionable tool by which healthy aging can be promoted. This review covers, firstly, the main lifestyle and socioeconomic factors that modify the gut microbiota composition and function during healthy or unhealthy aging and, secondly, the advances being made in defining and promoting healthy aging, including microbiome-informed artificial intelligence tools, personalized dietary patterns, and food probiotic systems.

Mulberry Leaf Lipid Nanoparticles: a Naturally Targeted CRISPR/Cas9 Oral Delivery Platform for Alleviation of Colon Diseases

Oral treatment of colon diseases with the CRISPR/Cas9 system has been hampered by the lack of a safe and efficient delivery platform. Overexpressed CD98 plays a crucial role in the progression of ulcerative colitis (UC) and colitis-associated colorectal cancer (CAC). In this study, lipid nanoparticles (LNPs) derived from mulberry leaves are functionalized with Pluronic copolymers and optimized to deliver the CRISPR/Cas gene editing machinery for CD98 knockdown. The obtained LNPs possessed a hydrodynamic diameter of 267.2 nm, a narrow size distribution, and a negative surface charge (-25.6 mV). Incorporating Pluronic F127 into LNPs improved their stability in the gastrointestinal tract and facilitated their penetration through the colonic mucus barrier. The galactose end groups promoted endocytosis of the LNPs by macrophages via asialoglycoprotein receptor-mediated endocytosis, with a transfection efficiency of 2.2-fold higher than Lipofectamine 6000. The LNPs significantly decreased CD98 expression, down-regulated pro-inflammatory cytokines (TNF-α and IL-6), up-regulated anti-inflammatory factors (IL-10), and polarized macrophages to M2 phenotype. Oral administration of LNPs mitigated UC and CAC by alleviating inflammation, restoring the colonic barrier, and modulating intestinal microbiota. As the first oral CRISPR/Cas9 delivery LNP, this system offers a precise and efficient platform for the oral treatment of colon diseases.

Network impact of a single-time-point microbial sample

The human microbiome plays a crucial role in determining our well-being and can significantly influence human health. The individualized nature of the microbiome may reveal host-specific information about the health state of the subject. In particular, the microbiome is an ecosystem shaped by a tangled network of species-species and host-species interactions. Thus, analysis of the ecological balance of microbial communities can provide insights into these underlying interrelations. However, traditional methods for network analysis require many samples, while in practice only a single-time-point microbial sample is available in clinical screening. Recently, a method for the analysis of a single-time-point sample, which evaluates its 'network impact' with respect to a reference cohort, has been applied to analyze microbial samples from women with Gestational Diabetes Mellitus. Here, we introduce different variations of the network impact approach and systematically study their performance using simulated 'samples' fabricated via the Generalized Lotka-Volttera model of ecological dynamics. We show that the network impact of a single sample captures the effect of the interactions between the species, and thus can be applied to anomaly detection of shuffled samples, which are 'normal' in terms of species abundance but 'abnormal' in terms of species-species interrelations. In addition, we demonstrate the use of the network impact in binary and multiclass classifications, where the reference cohorts have similar abundance profiles but different species-species interactions. Individualized analysis of the human microbiome has the potential to improve diagnosis and personalized treatments.

Mechanisms of metastatic colorectal cancer

Despite extensive research and improvements in understanding colorectal cancer (CRC), its metastatic form continues to pose a substantial challenge, primarily owing to limited therapeutic options and a poor prognosis. This Review addresses the emerging focus on metastatic CRC (mCRC), which has historically been under-studied compared with primary CRC despite its lethality. We delve into two crucial aspects: the molecular and cellular determinants facilitating CRC metastasis and the principles guiding the evolution of metastatic disease. Initially, we examine the genetic alterations integral to CRC metastasis, connecting them to clinically marked characteristics of advanced CRC. Subsequently, we scrutinize the role of cellular heterogeneity and plasticity in metastatic spread and therapy resistance. Finally, we explore how the tumour microenvironment influences metastatic disease, emphasizing the effect of stromal gene programmes and the immune context. The ongoing research in these fields holds immense importance, as its future implications are projected to revolutionize the treatment of patients with mCRC, hopefully offering a promising outlook for their survival.

Molecular Signatures for Microbe-Associated Colorectal Cancers

Background

Genetic factors and microbial imbalances play crucial roles in colorectal cancers (CRCs), yet the impact of infections on cancer initiation remains poorly understood. While bioinformatic approaches offer valuable insights, the rising incidence of CRCs creates a pressing need to precisely identify early CRC events. We constructed a network model to identify continuum states during CRC initiation spanning normal colonic tissue to pre-cancer lesions (adenomatous polyps) and examined the influence of microbes and host genetics.

Methods

A Boolean network was built using a publicly available transcriptomic dataset from healthy and adenoma affected patients to identify an invariant Microbe-Associated Colorectal Cancer Signature (MACS). We focused on Fusobacterium nucleatum ( Fn ), a CRC-associated microbe, as a model bacterium. MACS-associated genes and proteins were validated by RT-qPCR, RNA seq, ELISA, IF and IHCs in tissues and colon-derived organoids from genetically predisposed mice ( CPC-APC Min+/- ) and patients (FAP, Lynch Syndrome, PJS, and JPS).

Results

The MACS that is upregulated in adenomas consists of four core genes/proteins: CLDN2/Claudin-2 (leakiness), LGR5/leucine-rich repeat-containing receptor (stemness), CEMIP/cell migration-inducing and hyaluronan-binding protein (epithelial-mesenchymal transition) and IL8/Interleukin-8 (inflammation). MACS was induced upon Fn infection, but not in response to infection with other enteric bacteria or probiotics. MACS induction upon Fn infection was higher in CPC-APC Min+/- organoids compared to WT controls. The degree of MACS expression in the patient-derived organoids (PDOs) generally corresponded with the known lifetime risk of CRCs.

Conclusions

Computational prediction followed by validation in the organoid-based disease model identified the early events in CRC initiation. MACS reveals that the CRC-associated microbes induce a greater risk in the genetically predisposed hosts, suggesting its potential use for risk prediction and targeted cancer prevention.

Dencichine attenuates the virulence of Fusobacterium nucleatum by targeting hydrogen sulfide-producing enzyme

Oral opportunistic pathogen Fusobacterium nucleatum can participate in various disease processes through the metabolite hydrogen sulfide, such as halitosis and colorectal cancer. The object of this study is to identify inhibitor capable of suppressing Fn1220, which is the principal hydrogen sulfide-producing enzyme in F. nucleatum. Through this inhibition, we aim to reduce the hydrogen sulfide production of F. nucleatum, consequently diminishing its virulence. Employing molecular docking techniques for inhibitor screening, we identified dencichine as the monomeric compound from Chinese medicine exhibiting the lowest binding energy to Fn1220 among a set of 27,045 candidates, and evaluated in vitro the ability of dencichine to inhibit hydrogen sulfide production using bismuth chloride method. Additionally, we investigated its impact on key virulence factors, including biofilm formation, hemolysis, and adhesion factors of F. nucleatum, using the crystalline violet method, sheep blood method, and RT-qPCR, respectively. Furthermore, we assessed the influence of dencichine on the lifespan of Caenorhabditis elegans. Results showed that dencichine was a suitable inhibitor of the Fn1220 of F. nucleatum, which significantly inhibited the production of virulence factors, e.g., biofilm, hemolysin, FadA, and Fap2 of F. nucleatum and improved the survival of C. elegans. We successfully identified the inhibitor of the enzyme Fn1220, dencichine, which inhibited the production of hydrogen sulfide and attenuated the virulence of F. nucleatum and holds promise as a potential therapeutic avenue for addressing oral diseases, e.g., halitosis in the future.

Exploring Gut Microbiome Composition and Circulating Microbial DNA Fragments in Patients with Stage II/III Colorectal Cancer: A Comprehensive Analysis

BACKGROUND

Colorectal cancer (CRC) significantly contributes to cancer-related mortality, necessitating the exploration of prognostic factors beyond TNM staging. This study investigates the composition of the gut microbiome and microbial DNA fragments in stage II/III CRC.

METHODS

A cohort of 142 patients with stage II/III CRC and 91 healthy controls underwent comprehensive microbiome analysis. Fecal samples were collected for 16S rRNA sequencing, and blood samples were tested for the presence of microbial DNA fragments. De novo clustering analysis categorized individuals based on their microbial profiles. Alpha and beta diversity metrics were calculated, and taxonomic profiling was conducted.

RESULTS

Patients with CRC exhibited distinct microbial composition compared to controls. Beta diversity analysis confirmed CRC-specific microbial profiles. Taxonomic profiling revealed unique taxonomies in the patient cohort. De novo clustering separated individuals into distinct groups, with specific microbial DNA fragment detection associated with certain patient clusters.

CONCLUSIONS

The gut microbiota can differentiate patients with CRC from healthy individuals. Detecting microbial DNA fragments in the bloodstream may be linked to CRC prognosis. These findings suggest that the gut microbiome could serve as a prognostic factor in stage II/III CRC. Identifying specific microbial markers associated with CRC prognosis has potential clinical implications, including personalized treatment strategies and reduced healthcare costs. Further research is needed to validate these findings and uncover underlying mechanisms.

Role of Probiotics in Gut Microbiome and Metabolome in Non-Alcoholic Fatty Liver Disease Mouse Model: A Comparative Study

Non-alcoholic fatty liver disease (NAFLD) is the most prevalent chronic liver condition worldwide. Numerous studies conducted recently have demonstrated a connection between the dysbiosis of the development of NAFLD and gut microbiota. Rebuilding a healthy gut ecology has been proposed as a strategy involving the use of probiotics. The purpose of this work is to investigate and compare the function of probiotics Akkermansia muciniphila (A. muciniphila) and VSL#3 in NAFLD mice. Rodent NAFLD was modeled using a methionine choline-deficient diet (MCD) with/without oral probiotic delivery. Subsequently, qPCR, histological staining, and liver function tests were conducted. Mass spectrometry-based analysis and 16S rDNA gene sequencing were used to investigate the liver metabolome and gut microbiota. We found that while both A. muciniphila and VSL#3 reduced hepatic fat content, A. muciniphila outperformed VSL#3. Furthermore, probiotic treatment restored the β diversity of the gut flora and A. muciniphila decreased the abundance of pathogenic bacteria such as Ileibacterium valens. These probiotics altered the metabolism in MCD mice, especially the glycerophospholipid metabolism. In conclusion, our findings distinguished the role of A. muciniphila and VSL#3 in NAFLD and indicated that oral-gavage probiotics remodel gut microbiota and improve metabolism, raising the possibility of using probiotics in the cure of NAFLD.

Tannic acid delaying metabolism of resistant starch by gut microbiota during in vitro human fecal fermentation

This work investigated the effect of tannic acid on the fermentation rate of resistant starch. It was found that 1.0 and 1.5 μmol/L tannic acid decreased the rate of producing gas and short-chain fatty acids (SCFAs) from fermentation of resistant starch, and 1.5 μmol/mL tannic acid had a more profound effect, which confirmed that tannic acid delayed the metabolism of resistant starch. Moreover, tannic acid significantly inhibited the α-amylase activity during fermentation. On the other hand, tannic acid delayed the enrichment of some starch-degrading bacteria. Besides, fermentation of the resistant starch/tannic acid mixtures resulted in more SCFAs, particularly butyrate, and higher abundance of beneficial bacteria, including Bifidobacterium, Faecalibacterium, Blautia and Dorea, than fermentation of resistant starch after 48 h. Thus, it was inferred that tannic acid could delay the metabolism of resistant starch, which was due to its inhibitory effect on the α-amylase activity and regulatory effect on gut microbiota.

A metagenomics pipeline reveals insertion sequence-driven evolution of the microbiota

Insertion sequence (IS) elements are mobile genetic elements in bacterial genomes that support adaptation. We developed a database of IS elements coupled to a computational pipeline that identifies IS element insertions in the microbiota. We discovered that diverse IS elements insert into the genomes of intestinal bacteria regardless of human host lifestyle. These insertions target bacterial accessory genes that aid in their adaptation to unique environmental conditions. Using IS expansion in Bacteroides, we show that IS activity leads to the insertion of "hot spots" in accessory genes. We show that IS insertions are stable and can be transferred between humans. Extreme environmental perturbations force IS elements to fall out of the microbiota, and many fail to rebound following homeostasis. Our work shows that IS elements drive bacterial genome diversification within the microbiota and establishes a framework for understanding how strain-level variation within the microbiota impacts human health.

The immune interactions of gut glycans and microbiota in health and disease

The human digestive system harbors a vast diversity of commensal bacteria and maintains a symbiotic relationship with them. However, imbalances in the gut microbiota accompany various diseases, such as inflammatory bowel diseases (IBDs) and colorectal cancers (CRCs), which significantly impact the well-being of populations globally. Glycosylation of the mucus layer is a crucial factor that plays a critical role in maintaining the homeostatic environment in the gut. This review delves into how the gut microbiota, immune cells, and gut mucus layer work together to establish a balanced gut environment. Specifically, the role of glycosylation in regulating immune cell responses and mucus metabolism in this process is examined.

The role of gut microbiota and probiotics in preventing, treating, and boosting the immune system in colorectal cancer

The gut microbiome plays a significant role in developing colorectal cancer (CRC). The gut microbiome usually acts as a protective barrier against harmful pathogens and infections in the intestine, while also regulating inflammation by affecting the human immune system. The gut microbiota and probiotics play a role not only in intestinal inflammation associated with tumor formation but also in regulating anti-cancer immune response. As a result, they associated with tumor progression and the effectiveness of anti-cancer therapies. Research indicates that gut microbiota and probiotics can be used as biomarkers to predict the impact of immunotherapy and enhance its efficacy in treating CRC by regulating it. This review examines the importance of gut microbiota and probiotics in the development and progression of CRC, as well as their synergistic impact on anti-cancer treatments.

Colorectal cancer initiation: Understanding early-stage disease for intervention

How tumors arise or the cause of precancerous lesions is a fundamental question in cancer biology. It is generally accepted that tumors originate from normal cells that undergo uncontrolled proliferation owing to genetic alterations. At the onset of adenoma formation, cancer driver mutations confer clonal growth advantage, enabling mutant cells to outcompete and eliminate the surrounding healthy cells. Hence, the development of precancerous lesions is not only attributed to the expansion of pre-malignant clones, but also relies on the relative fitness of mutated cells compared to the neighboring cells. Colorectal cancer (CRC) is an excellent model to investigate cancer origin as it follows a stereotypical process from mutant cell hyperplasia to adenoma formation and progression. Here, we review the evolving understanding of colonic tumor development, focusing on how cell intrinsic and extrinsic factors impact cell competition and the "clone war" between cancer-initiating cells and normal stem cells. We also discuss the promises and limitations of targeting cell competitiveness in cancer prevention and early intervention. The field of tumor initiation is currently in its infancy, elucidating the adenoma origin is crucial for designing effective prevention strategies and early treatments before cancer becomes incurable.

mi-Mic: a novel multi-layer statistical test for microbiota-disease associations

mi-Mic, a novel approach for microbiome differential abundance analysis, tackles the key challenges of such statistical tests: a large number of tests, sparsity, varying abundance scales, and taxonomic relationships. mi-Mic first converts microbial counts to a cladogram of means. It then applies a priori tests on the upper levels of the cladogram to detect overall relationships. Finally, it performs a Mann-Whitney test on paths that are consistently significant along the cladogram or on the leaves. mi-Mic has much higher true to false positives ratios than existing tests, as measured by a new real-to-shuffle positive score.

The interactions between traditional Chinese medicine and gut microbiota in cancers: Current status and future perspectives

The gut microbiota, known as the "forgotten organ" and "human second genome," comprises a complex microecosystem. It significantly influences the development of various tumors, including colorectal, liver, stomach, breast, and lung cancers, through both direct and indirect mechanisms. These mechanisms include the "gut-liver" axis, the "lung-intestine" axis, and interactions with the immune system. The intestinal flora exhibits dual roles in cancer, both promoting and suppressing its progression. Traditional Chinese medicine (TCM) can alter cancer progression by regulating the intestinal flora. It modifies the intestinal flora's composition and structure, along with the levels of endogenous metabolites, thus affecting the intestinal barrier, immune system, and overall body metabolism. These actions contribute to TCM's significant antitumor effects. Moreover, the gut microbiota metabolizes TCM components, enhancing their antitumor properties. Therefore, exploring the interaction between TCM and the intestinal flora offers a novel perspective in understanding TCM's antitumor mechanisms. This paper succinctly reviews the association between gut flora and the development of tumors, including colorectal, liver, gastric, breast, and lung cancers. It further examines current research on the interaction between TCM and intestinal flora, with a focus on its antitumor efficacy. It identifies limitations in existing studies and suggests recommendations, providing insights into antitumor drug research and exploring TCM's antitumor effectiveness. Additionally, this paper aims to guide future research on TCM and the gut microbiota in antitumor studies.

BugSigDB captures patterns of differential abundance across a broad range of host-associated microbial signatures

The literature of human and other host-associated microbiome studies is expanding rapidly, but systematic comparisons among published results of host-associated microbiome signatures of differential abundance remain difficult. We present BugSigDB, a community-editable database of manually curated microbial signatures from published differential abundance studies accompanied by information on study geography, health outcomes, host body site and experimental, epidemiological and statistical methods using controlled vocabulary. The initial release of the database contains >2,500 manually curated signatures from >600 published studies on three host species, enabling high-throughput analysis of signature similarity, taxon enrichment, co-occurrence and coexclusion and consensus signatures. These data allow assessment of microbiome differential abundance within and across experimental conditions, environments or body sites. Database-wide analysis reveals experimental conditions with the highest level of consistency in signatures reported by independent studies and identifies commonalities among disease-associated signatures, including frequent introgression of oral pathobionts into the gut.

Utilization of the microbiome in personalized medicine

Inter-individual human variability, driven by various genetic and environmental factors, complicates the ability to develop effective population-based early disease detection, treatment and prognostic assessment. The microbiome, consisting of diverse microorganism communities including viruses, bacteria, fungi and eukaryotes colonizing human body surfaces, has recently been identified as a contributor to inter-individual variation, through its person-specific signatures. As such, the microbiome may modulate disease manifestations, even among individuals with similar genetic disease susceptibility risks. Information stored within microbiomes may therefore enable early detection and prognostic assessment of disease in at-risk populations, whereas microbiome modulation may constitute an effective and safe treatment tailored to the individual. In this Review, we explore recent advances in the application of microbiome data in precision medicine across a growing number of human diseases. We also discuss the challenges, limitations and prospects of analysing microbiome data for personalized patient care.

Multi-omics staging of locally advanced rectal cancer predicts treatment response: a pilot study

Treatment response assessment of rectal cancer patients is a critical component of personalized cancer care and it allows to identify suitable candidates for organ-preserving strategies. This pilot study employed a novel multi-omics approach combining MRI-based radiomic features and untargeted metabolomics to infer treatment response at staging. The metabolic signature highlighted how tumor cell viability is predictively down-regulated, while the response to oxidative stress was up-regulated in responder patients, showing significantly reduced oxoproline values at baseline compared to non-responder patients (p-value < 10-4). Tumors with a high degree of texture homogeneity, as assessed by radiomics, were more likely to achieve a major pathological response (p-value < 10-3). A machine learning classifier was implemented to summarize the multi-omics information and discriminate responders and non-responders. Combining all available radiomic and metabolomic features, the classifier delivered an AUC of 0.864 (± 0.083, p-value < 10-3) with a best-point sensitivity of 90.9% and a specificity of 81.8%. Our results suggest that a multi-omics approach, integrating radiomics and metabolomic data, can enhance the predictive value of standard MRI and could help to avoid unnecessary surgical treatments and their associated long-term complications.

Microbiome confounders and quantitative profiling challenge predicted microbial targets in colorectal cancer development

Despite substantial progress in cancer microbiome research, recognized confounders and advances in absolute microbiome quantification remain underused; this raises concerns regarding potential spurious associations. Here we study the fecal microbiota of 589 patients at different colorectal cancer (CRC) stages and compare observations with up to 15 published studies (4,439 patients and controls total). Using quantitative microbiome profiling based on 16S ribosomal RNA amplicon sequencing, combined with rigorous confounder control, we identified transit time, fecal calprotectin (intestinal inflammation) and body mass index as primary microbial covariates, superseding variance explained by CRC diagnostic groups. Well-established microbiome CRC targets, such as Fusobacterium nucleatum, did not significantly associate with CRC diagnostic groups (healthy, adenoma and carcinoma) when controlling for these covariates. In contrast, the associations of Anaerococcus vaginalis, Dialister pneumosintes, Parvimonas micra, Peptostreptococcus anaerobius, Porphyromonas asaccharolytica and Prevotella intermedia remained robust, highlighting their future target potential. Finally, control individuals (age 22-80 years, mean 57.7 years, standard deviation 11.3) meeting criteria for colonoscopy (for example, through a positive fecal immunochemical test) but without colonic lesions are enriched for the dysbiotic Bacteroides2 enterotype, emphasizing uncertainties in defining healthy controls in cancer microbiome research. Together, these results indicate the importance of quantitative microbiome profiling and covariate control for biomarker identification in CRC microbiome studies.

Gut microbiome affects the response to immunotherapy in non-small cell lung cancer

BACKGROUND

Immunotherapy has revolutionized cancer treatment. Recent studies have suggested that the efficacy of immunotherapy can be further enhanced by the influence of gut microbiota. In this study, we aimed to investigate the impact of bacteria on the effectiveness of cancer immunotherapy by combining analysis of clinical samples with validation in animal models.

METHODS

In order to characterize the diversity and composition of microbiota and its relationship with response to immune checkpoint inhibitors (ICIs), 16S ribosomal RNA (rRNA) and GC-MS sequencing was performed on 71 stool samples from patients with advanced non-small cell lung cancer (NSCLC) prior to treatment with immune checkpoint blockade (ICB). Furthermore, fecal microbiota transplantation (FMT) was performed from different patients into mice and a subcutaneous tumor model established using the Lewis lung cancer cell line to evaluate the therapeutic effect of PD-1 on mice with varying gut microbiota.

RESULTS

The results demonstrated a significant association between elevated gut microbiota diversity and response to treatment with ICIs, p < 0.05. Faecalibacterium was markedly increased in the gut microbiota of responders (R), accompanied by increased short-chain fatty acid (SCFA) levels, especially butanoic acid, acetic acid and hexanoic acid, p < 0.05. Additionally, FMT from R and nonresponders (NR) could promote an anticancer effect and reduce the expression of Ki-67 cells in tumors in mice, p < 0.05. Moreover, R and NR FMT did not alter PD-L1 expression in the tumor tissues of mice, p > 0.05. The diversity of gut microbiota consistently correlated with an optimistic prognosis in NSCLC patients with immunotherapy, which could be functionally mediated by SCFAs.

CONCLUSION

The findings of the present study indicated that the diversity of gut microbiota and SCFAs is related to the efficacy of immunotherapy. FMT can effectively delay tumor progression, and enhance the effect of immunotherapy, thus providing evidence for improving the efficacy of immunotherapy in NSCLC patients.

Nanomedomics

Nanomaterials have attractive physicochemical properties. A variety of nanomaterials such as inorganic, lipid, polymers, and protein nanoparticles have been widely developed for nanomedicine via chemical conjugation or physical encapsulation of bioactive molecules. Superior to traditional drugs, nanomedicines offer high biocompatibility, good water solubility, long blood circulation times, and tumor-targeting properties. Capitalizing on this, several nanoformulations have already been clinically approved and many others are currently being studied in clinical trials. Despite their undoubtful success, the molecular mechanism of action of the vast majority of nanomedicines remains poorly understood. To tackle this limitation, herein, this review critically discusses the strategy of applying multiomics analysis to study the mechanism of action of nanomedicines, named nanomedomics, including advantages, applications, and future directions. A comprehensive understanding of the molecular mechanism could provide valuable insight and therefore foster the development and clinical translation of nanomedicines.

Gut microbiota and their derivatives in the progression of colorectal cancer: Mechanisms of action, genome and epigenome contributions

Gut microbiota interacts with host epithelial cells and regulates many physiological functions such as genetics, epigenetics, metabolism of nutrients, and immune functions. Dietary factors may also be involved in the etiology of colorectal cancer (CRC), especially when an unhealthy diet is consumed with excess calorie intake and bad practices like smoking or consuming a great deal of alcohol. Bacteria including Fusobacterium nucleatum, Enterotoxigenic Bacteroides fragilis (ETBF), and Escherichia coli (E. coli) actively participate in the carcinogenesis of CRC. Gastrointestinal tract with chronic inflammation and immunocompromised patients are at high risk for CRC progression. Further, the gut microbiota is also involved in Geno-toxicity by producing toxins like colibactin and cytolethal distending toxin (CDT) which cause damage to double-stranded DNA. Specific microRNAs can act as either tumor suppressors or oncogenes depending on the cellular environment in which they are expressed. The current review mainly highlights the role of gut microbiota in CRC, the mechanisms of several factors in carcinogenesis, and the role of particular microbes in colorectal neoplasia.

A pervasive large conjugative plasmid mediates multispecies biofilm formation in the intestinal microbiota increasing resilience to perturbations

Although horizontal gene transfer is pervasive in the intestinal microbiota, we understand only superficially the roles of most exchanged genes and how the mobile repertoire affects community dynamics. Similarly, little is known about the mechanisms underlying the ability of a community to recover after a perturbation. Here, we identified and functionally characterized a large conjugative plasmid that is one of the most frequently transferred elements among Bacteroidales species and is ubiquitous in diverse human populations. This plasmid encodes both an extracellular polysaccharide and fimbriae, which promote the formation of multispecies biofilms in the mammalian gut. We use a hybridization-based approach to visualize biofilms in clarified whole colon tissue with unprecedented 3D spatial resolution. These biofilms increase bacterial survival to common stressors encountered in the gut, increasing strain resiliency, and providing a rationale for the plasmid's recent spread and high worldwide prevalence.

Characterization of tongue coating microbiome from patients with colorectal cancer

Background

Tongue coating microbiota has aroused particular interest in profiling oral and digestive system cancers. However, little is known on the relationship between tongue coating microbiome and colorectal cancer (CRC).

Methods

Metagenomic shotgun sequencing was performed on tongue coating samples collected from 30 patients with CRC, 30 patients with colorectal polyps (CP), and 30 healthy controls (HC). We further validated the potential of the tongue coating microbiota to predict the CRC by a random forest model.

Results

We found a greater species diversity in CRC samples, and the nucleoside and nucleotide biosynthesis pathway was more apparent in the CRC group. Importantly, various species across participants jointly shaped three distinguishable fur types.The tongue coating microbiome profiling data gave an area under the receiver operating characteristic curve (AUC) of 0.915 in discriminating CRC patients from control participants; species such as Atopobium rimae, Streptococcus sanguinis, and Prevotella oris aided differentiation of CRC patients from healthy participants.

Conclusion

These results elucidate the use of tongue coating microbiome in CRC patients firstly, and the fur-types observed contribute to a better understanding of the microbial community in human. Furthermore, the tongue coating microbiota-based biomarkers provide a valuable reference for CRC prediction and diagnosis.