High abundance of Lachnospiraceae in the human gut microbiome is related to high immunoscores in advanced colorectal cancer

The Role of Beneficial Microbiota in COVID-19: Insights from Key Bacterial Genera

The COVID-19 pandemic has highlighted the need for a comprehensive understanding of the factors influencing disease severity and progression. Emerging research indicates that the human microbiota, particularly beneficial bacteria, significantly impacts immune responses and health outcomes in COVID-19 patients. While existing studies provide general insights into the relationship between the microbiota and probiotics with COVID-19, they often lack a detailed exploration of how specific bacterial taxa might be used as adjunctive treatments. This review aims to address this gap by focusing on ten key genera of beneficial bacteria, discussing their roles in COVID-19 and evaluating their potential as probiotics for prevention and treatment. The review covers the impact of these microbes on human health, their population alterations in COVID-19 patients, and their interactions with other viral infections. Among these microbes, several exhibit distinct patterns of abundance in COVID-19 patients, influencing disease outcomes and highlighting their potential roles in infection dynamics. In COVID-19 patients, populations of Akkermansia, Ruminococcus, and Roseburia are consistently reduced, while those of Faecalibacterium show a significant decline in more severe cases. Bacteroides presents varying effects depending on the species involved. Alterations in the abundance of Blautia and Lachnospiraceae are associated with increased inflammation and disease severity. Likewise, the depletion of Lachnospira and Coprococcus populations, both linked to anti-inflammatory effects, may exacerbate symptom severity. Oscillospira, though less studied, is connected to overall health and could have implications for viral infections. This review synthesizes the current understanding of these beneficial microbes to highlight the importance of maintaining a healthy microbiota to alleviate the impact of COVID-19 and contribute to the development of novel therapeutic strategies involving microbiota modulation.

Gut microbiome signature in response to neoadjuvant chemoradiotherapy in patients with rectal cancer

Background

Rectal cancer remains a leading cause of cancer-associated mortality, especially in advanced cases with limited treatment options. Emerging evidence suggests that the gut microbiome may influence the therapeutic efficacy of neoadjuvant chemoradiotherapy (CRT).

Objective

This study aimed to explore the dynamic changes in gut microbiome composition and metabolic pathways in rectal cancer patients undergoing CRT.

Methods

Paired fecal samples were collected from rectal cancer patients pre- and post-CRT. 16S rRNA amplicon sequencing and proteomics analysis were conducted to investigate microbial and metabolic alterations.

Results

Significant shifts in the microbiome were observed, with Fusobacterium, Subdoligranulum, Prevotella, Alloprevotella, and Bacteroides being enriched pre-CRT, while Streptococcus, Megamonas, Megasphaera, Escherichia-Shigella, and Olsenella became dominant post-CRT. Metabolic analysis revealed upregulated carbohydrate metabolism and downregulated lipid and energy metabolism.

Conclusion

These findings identify potential microbial biomarkers and metabolic pathways associated with CRT response, offering insights into personalized treatment strategies.

Multi-cohort analysis reveals colorectal cancer tumor location-associated fecal microbiota and their clinical impact

Microbial alterations in different tumor locations of colorectal cancer (CRC) remain unclear. Here, 1,375 fecal metagenomes from six in-house and published datasets were analyzed, including 128 right-sided CRC (rCRC), 168 left-sided CRC (lCRC), 250 rectal cancer (RC), and 829 controls. Firmicutes progressively increase from rCRC, lCRC, to RC, in contrast to the gradual decrease of Bacteroidetes. Tumor location-associated fecal microbes are identified, including Veillonella parvula for rCRC, Streptococcus angionosus for lCRC, and Peptostreptococcus anaerobius for RC, while Fusobacterium nucleatum is enriched in all tumor locations. Tumor location-associated bacteria correlate with patient survival. Clinically, we establish a microbial biomarker panel for each tumor location that accurately diagnoses rCRC (area under the receiver operating characteristic curve [AUC] = 91.59%), lCRC (AUC = 91.69%), or RC (AUC = 90.53%) from controls. Tumor location-specific biomarkers also have higher diagnostic accuracy (AUC = 91.38%) than location-non-specific biomarkers (AUC = 82.92%). Overall, we characterize fecal microbes associated with different CRC tumor locations, highlighting that tumor location should be considered in non-invasive diagnosis.

Decoding the link between microbial secondary metabolites and colorectal cancer

Colorectal cancer (CRC) is a prevalent form of cancer in humans, with the gut microbiota playing a significant role in its pathogenesis. Although previous research has primarily focused on the role of primary metabolites produced by gut microbes in CRC development, the role of secondary metabolites remains largely unexplored. Secondary metabolites are known to mediate crucial interactions between the microbiota and the host, potentially influencing CRC progression. However, their specific relationship to CRC pathogenesis is poorly understood. To address this gap, we performed a meta-analysis using fecal metagenomic data from a cohort of CRC patients and healthy controls, aiming to identify CRC-associated microbial secondary metabolite biosynthetic gene clusters (BGCs). Our findings not only provide valuable insights into the pathogenicity and carcinogenicity of CRC but also shed light on the potential mechanisms underlying its development.

Gene prediction of immune cells association between gut microbiota and colorectal cancer: a Mendelian randomization study

Background

An increasing number of studies have revealed that gut microbiota influences the development and progression of Colorectal cancer (CRC). However, whether a causal relationship exists between the two remains unclear, and the role of immune cells in this context is not well understood.

Objective

To elucidate the causal relationship between gut microbiota and CRC and to explore the potential mediating role of circulating immune cells.

Materials and methods

To analyze the causal relationship between gut microbiota and CRC, we employed a univariable Mendelian randomization (UVMR) approach. Subsequently, a two-step multivariable Mendelian randomization (MVMR) to assess the potential mediating role of circulating immune cells. Primarily, applied the Inverse-Variance Weighted method to evaluate the causal relationship between exposure and outcome. To ensure the robustness of the results linking gut microbiota and CRC, we validated the findings using Robust Inverse-Variance Weighted, Penalized Inverse-Variance Weighted, and Penalized Robust Inverse-Variance Weighted methods. Additionally, we employed MR-Egger Intercept to mitigate the influence of horizontal pleiotropy. MR-PRESSO was used to detect and correct outliers by excluding anomalous instrumental variables. Finally, we supplemented our analysis with methods such as Bayesian Weighted Mendelian Randomization (BWMR), Maximum-Likelihood, Lasso, Debiased Inverse Variance Weighted, and Contamination Mixture to establish a robust and compelling causal relationship.

Results

After accounting for reverse causality, horizontal pleiotropy, and various methodological corrections, Bifidobacterium kashiwanohense, GCA-900066755 sp900066755, Geminocystis, and Saccharofermentanaceae exhibited strong and robust causal effects on CRC. Specifically, CD40 on monocytes (2.82%) and CD45 on CD33+HLA-DR+CD14- cells (12.87%) mediated the causal relationship between Bifidobacterium kashiwanohense and CRC risk. Furthermore, CD45 on CD33-HLA-DR+ (3.94%) mediated the causal relationship between GCA-900066755 sp900066755 and CRC risk. Additionally, terminally differentiated CD4+T cells (11.55%) mediated the causal relationship between Geminocystis and CRC risk. Lastly, CD40 on monocytes (2.35%), central memory CD4+T cells (5.76%), and CD28 on CD28+CD45RA+CD8+T cells (5.00%) mediated the causal relationship between Saccharofermentanaceae and CRC risk.

Conclusion

Our mediation MR analysis provides genetic evidence suggesting that circulating immune cells may mediate the causal relationship between gut microbiota and CRC. The identified associations and mediation effects offer new insights into potential therapeutic avenues for CRC.

Gut metatranscriptomics based de novo assembly reveals microbial signatures predicting immunotherapy outcomes in non-small cell lung cancer

BACKGROUND

Advanced-stage non-small cell lung cancer (NSCLC) poses treatment challenges, with immune checkpoint inhibitors (ICIs) as the main therapy. Emerging evidence suggests the gut microbiome significantly influences ICI efficacy. This study explores the link between the gut microbiome and ICI outcomes in NSCLC patients, using metatranscriptomic (MTR) signatures.

METHODS

We utilized a de novo assembly-based MTR analysis on fecal samples from 29 NSCLC patients undergoing ICI therapy, segmented according to progression-free survival (PFS) into long (> 6 months) and short (≤ 6 months) PFS groups. Through RNA sequencing, we employed the Trinity pipeline for assembly, MMSeqs2 for taxonomic classification, DESeq2 for differential expression (DE) analysis. We constructed Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost) machine learning (ML) algorithms and comprehensive microbial profiles.

RESULTS

We detected no significant differences concerning alpha-diversity, but we revealed a biologically relevant separation between the two patient groups in beta-diversity. Actinomycetota was significantly overrepresented in patients with short PFS (vs long PFS, 36.7% vs. 5.4%, p < 0.001), as was Euryarchaeota (1.3% vs. 0.002%, p = 0.009), while Bacillota showed higher prevalence in the long PFS group (66.2% vs. 42.3%, p = 0.007), when comparing the abundance of corresponding RNA reads. Among the 120 significant DEGs identified, cluster analysis clearly separated a large set of genes more active in patients with short PFS and a smaller set of genes more active in long PFS patients. Protein Domain Families (PFAMs) were analyzed to identify pathways enriched in patient groups. Pathways related to DNA synthesis and Translesion were more enriched in short PFS patients, while metabolism-related pathways were more enriched in long PFS patients. E. coli-derived PFAMs dominated in patients with long PFS. RF, SVM and XGBoost ML models all confirmed the predictive power of our selected RNA-based microbial signature, with ROC AUCs all greater than 0.84. Multivariate Cox regression tested with clinical confounders PD-L1 expression and chemotherapy history underscored the influence of n = 6 key RNA biomarkers on PFS.

CONCLUSION

According to ML models specific gut microbiome MTR signatures' associate with ICI treated NSCLC outcomes. Specific gene clusters and taxa MTR gene expression might differentiate long vs short PFS.

Exploring the Role of the Gut Microbiota in Modulating Colorectal Cancer Immunity

The gut microbiota plays an essential role in maintaining immune homeostasis and influencing the immune landscape within the tumor microenvironment. This review aims to elucidate the interactions between gut microbiota and tumor immune dynamics, with a focus on colorectal cancer (CRC). The review spans foundational concepts of immuno-microbial interplay, factors influencing microbiome composition, and evidence linking gut microbiota to cancer immunotherapy outcomes. Gut microbiota modulates anti-cancer immunity through several mechanisms, including enhancement of immune surveillance and modulation of inflammatory responses. Specific microbial species and their metabolic byproducts can significantly influence the efficacy of cancer immunotherapies. Furthermore, microbial diversity within the gut microbiota correlates with clinical outcomes in CRC, suggesting potential as a valuable biomarker for predicting response to immunotherapy. Conclusions: Understanding the relationship between gut microbiota and tumor immune responses offers potential for novel therapeutic strategies and biomarker development. The gut microbiota not only influences the natural history and treatment response of CRC but also serves as a critical modulator of immune homeostasis and anti-cancer activity. Further exploration into the microbiome's role could enhance the effectiveness of existing treatments and guide the development of new therapeutic modalities.

Effect of chronic alcohol consumption on oral microbiota in rats with periodontitis

Background

The imbalance of oral microbiota can contribute to various oral disorders and potentially impact general health. Chronic alcohol consumption beyond a certain threshold has been implicated in influencing both the onset and progression of periodontitis. However, the mechanism by which chronic alcohol consumption affects periodontitis and its association with changes in the oral microbial community remains unclear.

Objective

This study used 16S rRNA gene amplicon sequencing to examine the dynamic changes in the oral microbial community of rats with periodontitis influenced by chronic alcohol consumption.

Methods

Twenty-four male Wistar rats were randomly allocated to either a periodontitis (P) or periodontitis + alcohol (PA) group. The PA group had unrestricted access to alcohol for 10 weeks, while the P group had access to water only. Four weeks later, both groups developed periodontitis. After 10 weeks, serum levels of alanine aminotransferase and aspartate aminotransferase in the rats' serum were measured. The oral swabs were obtained from rats, and 16S rRNA gene sequencing was conducted. Alveolar bone status was assessed using hematoxylin and eosin staining and micro-computed tomography.

Results

Rats in the PA group exhibited more severe periodontal tissue damage compared to those in the periodontitis group. Although oral microbial diversity remained stable, the relative abundance of certain microbial communities differed significantly between the two groups. Actinobacteriota and Desulfobacterota were more prevalent at the phylum level in the PA group. At the genus level, Cutibacterium, Tissierella, Romboutsia, Actinomyces, Lawsonella, Anaerococcus, and Clostridium_sensu_stricto_1 were significantly more abundant in the PA group, while Haemophilus was significantly less abundant. Additionally, functional prediction using Tax4Fun revealed a significant enrichment of carbohydrate metabolism in the PA group.

Conclusion

Chronic alcohol consumption exacerbated periodontitis in rats and influenced the composition and functional characteristics of their oral microbiota, as indicated by 16S rRNA gene sequencing results. These microbial alterations may contribute to the exacerbation of periodontitis in rats due to chronic alcohol consumption.

Effects of immune cells in mediating the relationship between gut microbiota and myelodysplastic syndrome: a bidirectional two-sample, two-step Mendelian randomization study

BACKGROUND

The definitive establishment of a causal relationship between gut microbiota and myelodysplastic syndrome (MDS) has not been achieved. Furthermore, the involvement of immune cells in mediating the connection between gut microbiota and MDS is presently unclear.

METHODS

To elucidate the bidirectional correlation between gut microbiota and MDS, as well as to investigate the mediating role of immune cells, a bidirectional two-sample, two-step Mendelian randomization (MR) study was conducted. Summary statistics were obtained from genome-wide association studies (GWAS), including MDS (456,348 individuals), gut microbiota (18,340 individuals), and 731 immune cells signatures (3757 individuals).

RESULTS

Genetically predicted eight gut microbiota traits were significantly associated with MDS risk, but not vice versa. Through biological annotation of host-microbiome shared genes, we found that immune regulation may mediate the impact of gut microbiota on MDS. Subsequently, twenty-three immunophenotypes that exhibited significant associations with MDS risk and five of these immunophenotypes were under the causal influence of gut microbiota. Importantly, the causal effects of gut microbiota on MDS were significantly mediated by five immunophenotypes, including CD4 +T cell %leukocyte, CD127 on CD45RA - CD4 not regulatory T cell, CD45 on CD33 + HLA DR + WHR, CD33 on basophil, and Monocyte AC.

CONCLUSIONS

Gut microbiota was causally associated with MDS risk, and five specific immunophenotypes served as potential causal mediators of the effect of gut microbiota on MDS. Understanding the causality among gut microbiota, immune cells and MDS is critical in identifying potential targets for diagnosis and treatment.

Microbiome Taxonomic and Functional Differences in C3H/HeJ Mice Fed a Long-Term High-Fat Diet with Beef Protein ± Ammonium Hydroxide Supplementation

Studies have suggested that alkalinized foods may reduce the effects of the acidogenic Western diet in promoting obesity, metabolic syndrome, type 2 diabetes, cancer, and coronary heart disease. Indeed, a recent study in mice fed a high-fat diet containing dietary beef supplemented with ammonium hydroxide showed improvement in a suite of metabolic outcomes. However, the effects of dietary protein ammonium supplementation on the microbiome remain unknown. In this study, the effects of ammonium supplementation on beef protein towards microbiome taxa and function in a high-fat diet were analyzed. Fecal microbiomes were characterized using a shotgun metagenomic approach for 16-month-old male and female mice after long-term diet treatments. The results for ammoniated diets showed that several bacteria known to be associated with health benefits increased significantly, including Romboutsia, Oscillospiraceae, and Lactococcus cremoris. The beneficial mucin-degrader Akkermansia was especially abundant, with a high prevalence (~86%) in females. Concurrently, the phyla Actinomycetota (Actinobacteria) and Bacteroidota (Bacteroidetes) were significantly reduced. While sex was a confounding factor affecting microbiome responses to ammonium supplementation in dietary protein, it is worth noting that several putatively beneficial microbiome functions increased with ammonium supplementation, such as glycine betaine transport, xenobiotic detoxification, enhanced defense, and others. Conversely, many disease-associated microbiome functions reduced. Importantly, modifying protein pH alone via ammonium supplementation induced beneficial microbiota changes. Taken together, these results suggest that ammonium-supplemented proteins may mediate some negative microbiome-associated effects of high-fat/Western diets.

Dysbiosis Signature of Fecal Microbiota in Patients with Pancreatic Adenocarcinoma and Pancreatic Intraductal Papillary Mucinous Neoplasms

Pancreatic cancer (PC) ranks as the seventh leading cause of cancer-related deaths, with approximately 500,000 new cases reported in 2020. Existing strategies for early PC detection primarily target individuals at high risk of developing the disease. Nevertheless, there is a pressing need to identify innovative clinical approaches and personalized treatments for effective PC management. This study aimed to explore the dysbiosis signature of the fecal microbiota in PC and potential distinctions between its Intraductal papillary mucinous neoplasm (IPMN) and pancreatic ductal adenocarcinoma (PDAC) phenotypes, which could carry diagnostic significance. The study enrolled 33 participants, including 22 diagnosed with PDAC, 11 with IPMN, and 24 healthy controls. Fecal samples were collected and subjected to microbial diversity analysis across various taxonomic levels. The findings revealed elevated abundances of Firmicutes and Proteobacteria in PC patients, whereas healthy controls exhibited higher proportions of Bacteroidota. Both LEfSe and Random Forest analyses indicated the microbiome's potential to effectively distinguish between PC and healthy control samples but fell short of differentiating between IPMN and PDAC samples. These results contribute to the current understanding of this challenging cancer type and highlight the applications of microbiome research. In essence, the study provides clear evidence of the gut microbiome's capability to serve as a biomarker for PC detection, emphasizing the steps required for further differentiation among its diverse phenotypes.

Explainable artificial intelligence for microbiome data analysis in colorectal cancer biomarker identification

Background

Colorectal cancer (CRC) is a type of tumor caused by the uncontrolled growth of cells in the mucosa lining the last part of the intestine. Emerging evidence underscores an association between CRC and gut microbiome dysbiosis. The high mortality rate of this cancer has made it necessary to develop new early diagnostic methods. Machine learning (ML) techniques can represent a solution to evaluate the interaction between intestinal microbiota and host physiology. Through explained artificial intelligence (XAI) it is possible to evaluate the individual contributions of microbial taxonomic markers for each subject. Our work also implements the Shapley Method Additive Explanations (SHAP) algorithm to identify for each subject which parameters are important in the context of CRC.

Results

The proposed study aimed to implement an explainable artificial intelligence framework using both gut microbiota data and demographic information from subjects to classify a cohort of control subjects from those with CRC. Our analysis revealed an association between gut microbiota and this disease. We compared three machine learning algorithms, and the Random Forest (RF) algorithm emerged as the best classifier, with a precision of 0.729 ± 0.038 and an area under the Precision-Recall curve of 0.668 ± 0.016. Additionally, SHAP analysis highlighted the most crucial variables in the model's decision-making, facilitating the identification of specific bacteria linked to CRC. Our results confirmed the role of certain bacteria, such as Fusobacterium, Peptostreptococcus, and Parvimonas, whose abundance appears notably associated with the disease, as well as bacteria whose presence is linked to a non-diseased state.

Discussion

These findings emphasizes the potential of leveraging gut microbiota data within an explainable AI framework for CRC classification. The significant association observed aligns with existing knowledge. The precision exhibited by the RF algorithm reinforces its suitability for such classification tasks. The SHAP analysis not only enhanced interpretability but identified specific bacteria crucial in CRC determination. This approach opens avenues for targeted interventions based on microbial signatures. Further exploration is warranted to deepen our understanding of the intricate interplay between microbiota and health, providing insights for refined diagnostic and therapeutic strategies.

Digestive characteristics of extracellular polysaccharide from Lactiplantibacillus plantarum T1 and its regulation of intestinal microbiota

This study assessed the potential prebiotic characteristics of the previously reported Lactiplantibacillus plantarum extracellular polysaccharide (EPS-T1) with immunological activity. EPS-T1 was a novel heteropolysaccharide composed of glucose and galactose (1.00:1.21), with a molecular weight of 1.41 × 106 Da. The monosaccharide composition, molecular weight, fourier transform infrared, and 1H NMR analysis showed that EPS-T1 was well tolerated in the simulated oral cavity, gastric fluid, and small intestinal fluid environments, and was not easily degraded. Meanwhile, EPS-T1 could effectively be used as a carbon source to promote the growth of beneficial Lactobacillus species (Lactobacillus delbrueckii ssp. Bulgaricus, Streptococcus thermophilus, Lacticaseibacillus rhamnose GG, Lactiplantibacillus plantarum, Lacticaseibacillus paracasei and Lactobacillus reuteri). After 24 h of fecal fermentation, EPS-T1(5 mg/mL) effectively reduced the relative abundance of harmful bacteria such as the Escherichia-Shigella, Citrobacter, Fusobacterium, Parasutterella, and Lachnoclostridium. While, the level content of beneficial flora (Bacteroides, Blautia, Phascolarctobacterium, Bifidobacterium, Parabacteroides, and Subdoligranulum) were significantly increased. In addition, EPS-T1 was able to significantly promote the enrichment of short-chain fatty acids such as acetic acid, propionic acid and butyric acid. These results provide some basis for the functional application of EPS-T1 as a potential prebiotic.

Dissecting the Impact of the Gut Microbiome on Cancer Immunotherapy

The gut microbiome has emerged as a key regulator of response to cancer immunotherapy. However, there is a gap in our understanding of the underlying mechanisms by which the microbiome influences immunotherapy. To this end, we developed a mathematical model based on i) gut microbiome data derived from preclinical studies on melanomas after fecal microbiota transplant, ii) mechanistic modeling of antitumor immune response, and iii) robust association analysis of murine and human microbiome profiles with model-predicted immune profiles. Using our model, we could distill the complexity of these murine and human studies on microbiome modulation in terms of just two model parameters: the activation and killing rate constants of immune cells. We further investigated associations between specific bacterial taxonomies and antitumor immunity and immunotherapy efficacy. This model can guide the design of studies to refine and validate mechanistic links between the microbiome and immune system.

Could immunoscore improve the prognostic and therapeutic management in patients with solid tumors?

The Immunoscore (ISc) is an emerging immune-based scoring system that has shown potential in improving the prognostic and therapeutic management of patients with solid tumors. The ISc evaluates the immune infiltrate within the tumor microenvironment (TME) and has demonstrated superior predictive ability compared to traditional histopathological parameters. It has been particularly promising in colorectal, lung, breast, and melanoma cancers. This review summarizes the clinical evidence supporting the prognostic value of the ISc and explores its potential in guiding therapeutic decisions, such as the selection of adjuvant therapies and recognizing patients likely to profit from immune checkpoint inhibitors (ICIs). The challenges and future directions of ISc implementation are also discussed, including standardization and integration into routine clinical practice.

From-Toilet-to-Freezer: A Review on Requirements for an Automatic Protocol to Collect and Store Human Fecal Samples for Research Purposes

The composition, viability and metabolic functionality of intestinal microbiota play an important role in human health and disease. Studies on intestinal microbiota are often based on fecal samples, because these can be sampled in a non-invasive way, although procedures for sampling, processing and storage vary. This review presents factors to consider when developing an automated protocol for sampling, processing and storing fecal samples: donor inclusion criteria, urine-feces separation in smart toilets, homogenization, aliquoting, usage or type of buffer to dissolve and store fecal material, temperature and time for processing and storage and quality control. The lack of standardization and low-throughput of state-of-the-art fecal collection procedures promote a more automated protocol. Based on this review, an automated protocol is proposed. Fecal samples should be collected and immediately processed under anaerobic conditions at either room temperature (RT) for a maximum of 4 h or at 4 °C for no more than 24 h. Upon homogenization, preferably in the absence of added solvent to allow addition of a buffer of choice at a later stage, aliquots obtained should be stored at either -20 °C for up to a few months or -80 °C for a longer period-up to 2 years. Protocols for quality control should characterize microbial composition and viability as well as metabolic functionality.

Associations of Adherence to the 2018 World Cancer Research Fund and the American Institute for Cancer Research Dietary Recommendations with Gut Microbiota and Inflammation Levels

BACKGROUND

Whether the World Cancer Research Fund and the American Institute for Cancer Research (WCRF/AICR) dietary recommendations affect the gut microbiota and inflammatory status remains unclear. We examined the association of dietary adherence scores to the WCRF/AICR with gut microbiota and inflammation in a cross-sectional setting.

METHODS

The WCRF/AICR diet adherence scores were calculated for 151 participants (adenoma 97, non-adenoma 54) from 7-day dietary records. The gut microbiota was analyzed by 16S rRNA gene sequencing of fecal samples. The levels of inflammatory biomarkers in both blood (i.e., IL-6, IL-8, IgA, IgM, and IgG) and fecal samples (i.e., FCP) were evaluated in 97 colorectal adenoma patients who had blood samples available. Multivariable linear regression analyses were conducted to examine the association of individual and total dietary adherence scores with gut microbiota and inflammatory biomarker levels.

RESULTS

Participants with higher adherence had lower relative abundance of Proteobacteria (β = -0.041, 95%CI: -0.073, -0.009), Enterobacteriaceae (β = -0.035, 95%CI: -0.067, -0.003), and unidentified Enterobacteriaceae at the genus level (β = -0.029, 95%CI: -0.055, -0.003) compared to those with lower adherence. Plant-based food intake was positively correlated with increased abundance of Phascolarctobacterium (β = 0.013, 95%CI: 0.001, 0.026). Restricting fast food was linked to high abundance of Bacteroidaceae (β = 0.149, 95%CI: 0.040, 0.257) and Bacteroides (β = 0.149, 95%CI: 0.040, 0.257). Limiting sugary drinks was associated with reduced abundance of Lachnospiraceae (β = -0.155, 95%CI: -0.292, -0.018). Plant-based food intake (β = -0.251, 95%CI: -0.450, -0.052) and restriction of fast food (β = -0.226, 95%CI: -0.443, -0.008) were associated with reduced IGG levels in men. Alcohol restriction was linked to lower IL-6 (β = -7.095, 95%CI: -11.286, -2.903) and IL-8 (β = -7.965, 95%CI: -14.700, -1.230) levels in women, but with higher IL-6 (β = 0.918, 95%CI: 0.161, 1.675) levels in men.

CONCLUSIONS

Our findings support the association of adherence to the WCRF/AICR diet with gut microbiota and inflammation. These results need to be validated in additional prospective or interventional studies.

Fecal Microbiota and Associated Volatile Organic Compounds Distinguishing No-Adenoma from High-Risk Colon Adenoma Adults

Microbiota and the metabolites they produce within the large intestine interact with the host epithelia under the influence of a range of host-derived metabolic, immune, and homeostatic factors. This complex host-microbe interaction affects intestinal tumorigenesis, but established microbial or metabolite profiles predicting colorectal cancer (CRC) risk are missing. Here, we aimed to identify fecal bacteria, volatile organic compounds (VOC), and their associations that distinguish healthy (non-adenoma, NA) from CRC prone (high-risk adenoma, HRA) individuals. Analyzing fecal samples obtained from 117 participants ≥15 days past routine colonoscopy, we highlight the higher abundance of Proteobacteria and Parabacteroides distasonis, and the lower abundance of Lachnospiraceae species, Roseburia faecis, Blautia luti, Fusicatenibacter saccharivorans, Eubacterium rectale, and Phascolarctobacterium faecium in the samples of HRA individuals. Volatolomic analysis of samples from 28 participants revealed a higher concentration of five compounds in the feces of HRA individuals, isobutyric acid, methyl butyrate, methyl propionate, 2-hexanone, and 2-pentanone. We used binomial logistic regression modeling, revealing 68 and 96 fecal bacteria-VOC associations at the family and genus level, respectively, that distinguish NA from HRA endpoints. For example, isobutyric acid associations with Lachnospiraceae incertae sedis and Bacteroides genera exhibit positive and negative regression lines for NA and HRA endpoints, respectively. However, the same chemical associates with Coprococcus and Colinsella genera exhibit the reverse regression line trends. Thus, fecal microbiota and VOC profiles and their associations in NA versus HRA individuals indicate the significance of multiple levels of analysis towards the identification of testable CRC risk biomarkers.

Alterations in metabolome and microbiome signatures provide clues to the role of antimicrobial peptide KT2 in ulcerative colitis

Introduction

Ulcerative colitis (UC) is an inflammatory disease of the intestinal tract with unknown etiology. Both genetic and environmental factors are involved in the occurrence and development of UC. Understanding changes in the microbiome and metabolome of the intestinal tract is crucial for the clinical management and treatment of UC.

Methods

Here, we performed metabolomic and metagenomic profiling of fecal samples from healthy control mice (HC group), DSS (Dextran Sulfate Sodium Salt) -induced UC mice (DSS group), and KT2-treated UC mice (KT2 group).

Results and Discussion

In total, 51 metabolites were identified after UC induction, enriched in phenylalanine metabolism, while 27 metabolites were identified after KT2 treatment, enriched in histidine metabolism and bile acid biosynthesis. Fecal microbiome analysis revealed significant differences in nine bacterial species associated with the course of UC, including Bacteroides, Odoribacter, and Burkholderiales, which were correlated with aggravated UC, and Anaerotruncus, Lachnospiraceae, which were correlated with alleviated UC. We also identified a disease-associated network connecting the above bacterial species with UC-associated metabolites, including palmitoyl sphingomyelin, deoxycholic acid, biliverdin, and palmitoleic acid. In conclusion, our results indicated that Anaerotruncus, Lachnospiraceae, and Mucispirillum were protective species against DSS-induced UC in mice. The fecal microbiomes and metabolomes differed significantly among the UC mice and KT2-treated and healthy-control mice, providing potential evidence for the discovery of biomarkers of UC.

Exploring the alterations and function of skin microbiome mediated by ionizing radiation injury

Background

Radiation-induced skin injury (RISI) is still the most common and severe side effect of radiotherapy. The role of the skin’s microbial barrier in the pathogenesis and progression of RISI needs to be fully investigated.

Methods

This study aimed to explore the alterations in and functions of the skin microbiota in RISI. We applied the unculturable approach to characterize the cutaneous microbiomes of a radiation-induced animal model by sequencing the V1–V3 regions of the 16S ribosomal RNA (rRNA) gene. Combined with the downloaded clinical data of patients, a comprehensive analysis was performed to identify potential radioprotective species and metabolic pathways.

Results

There were no significant differences in the alpha diversity indices (Sobs, Shannon, Simpson, Ace, and Chao) between the acute radiation injury and control groups. Phylum-level analysis of the RISI microbiomes exhibited significant predominance of Firmicutes (mean abundance = 67%, corrected p = 0.0035). The high abundance of Firmicutes was significantly associated with rapid healing of RISI (average relative abundance = 52%; Kruskal–Wallis: p = 5.7E−4). Among its members, Streptococcus, Staphylococcus, Acetivibrio ethanolgignens group, Peptostreptococcus, Anaerofilum, and UCG-002 [linear discriminant analysis (LDA) &gt; 3, p &lt; 0.05] were identified as the core genera of Firmicutes. In addition, Lachnosiraceae and Lactobacillus occupied an important position in the interaction network (r &gt; 0.6, p &lt; 0.05). The differential metabolic pathways of RISI were mainly associated with carbohydrate metabolism (butanoate and propanoate metabolism), amino acid metabolism (tryptophan and histidine metabolism), energy metabolism, and lipid metabolism (fatty acid degradation and biosynthesis).

Conclusion

This study provides new insights into the potential mechanism and skin microbial changes in the progression of RISI. The overwhelming predominance of members of Firmicutes, including Streptococcaceae, Staphylococcaceae, Lachnospiraceae, and Lactobacillus, is potentially related to rapid healing of RISI. The microbiota–metabolite axis plays a critical role in RISI and provides promising therapeutic targets for the treatment of adverse side effects.